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data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173640/I_SPY_COVID_adaptive_platform_trial_for_COVID_19_acute_respiratory_failure_rationale_design_and_operations"><img alt="Research paper thumbnail of I-SPY COVID adaptive platform trial for COVID-19 acute respiratory failure: rationale, design and operations" class="work-thumbnail" src="https://attachments.academia-assets.com/111659564/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173640/I_SPY_COVID_adaptive_platform_trial_for_COVID_19_acute_respiratory_failure_rationale_design_and_operations">I-SPY COVID adaptive platform trial for COVID-19 acute respiratory failure: rationale, design and operations</a></div><div class="wp-workCard_item"><span>BMJ Open</span><span>, Jun 1, 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{"id":115173640,"title":"I-SPY COVID adaptive platform trial for COVID-19 acute respiratory failure: rationale, design and operations","translated_title":"","metadata":{"publisher":"BMJ","grobid_abstract":"Introduction The COVID-19 pandemic brought an urgent need to discover novel effective therapeutics for patients hospitalised with severe COVID-19. The Investigation of Serial studies to Predict Your Therapeutic Response with Imaging And moLecular Analysis (ISPY COVID-19 trial) was designed and implemented in early 2020 to evaluate investigational agents rapidly and simultaneously on a phase 2 adaptive platform. This manuscript outlines the design, rationale, implementation and challenges of the ISPY COVID-19 trial during the first phase of trial activity from April 2020 until December 2021. Methods and analysis The ISPY COVID-19 Trial is a multicentre open-label phase 2 platform trial in the USA designed to evaluate therapeutics that may have a large effect on improving outcomes from severe COVID-19. The ISPY COVID-19 Trial network includes academic and community hospitals with significant geographical diversity across the country. Enrolled patients are randomised to receive one of up to four investigational agents or a control and are evaluated for a family of two primary outcomestime to recovery and mortality. The statistical design uses a Bayesian model with 'stopping' and 'graduation' criteria designed to efficiently discard ineffective therapies and graduate promising agents for definitive efficacy trials. Each investigational agent arm enrols to a maximum of 125 patients per arm and is compared with concurrent controls. As of December 2021, 11 investigational agent arms had been activated, and 8 arms were complete. Enrolment and adaptation of the trial design are ongoing. Ethics and dissemination ISPY COVID-19 operates under a central institutional review board via Wake Forest School of Medicine IRB00066805. Data generated from this trial will be reported in peer-reviewed medical journals. Trial registration number NCT04488081.","publication_date":{"day":1,"month":6,"year":2022,"errors":{}},"publication_name":"BMJ Open","grobid_abstract_attachment_id":111659564},"translated_abstract":null,"internal_url":"https://www.academia.edu/115173640/I_SPY_COVID_adaptive_platform_trial_for_COVID_19_acute_respiratory_failure_rationale_design_and_operations","translated_internal_url":"","created_at":"2024-02-20T08:16:15.190-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":111659564,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/111659564/thumbnails/1.jpg","file_name":"e060664.full.pdf","download_url":"https://www.academia.edu/attachments/111659564/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"I_SPY_COVID_adaptive_platform_trial_for.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/111659564/e060664.full-libre.pdf?1708457094=\u0026response-content-disposition=attachment%3B+filename%3DI_SPY_COVID_adaptive_platform_trial_for.pdf\u0026Expires=1732512681\u0026Signature=K7CcP1mpvOM2-DWPK10PvoKwVvwK66U4UU8wkzMUGOZT8egG237vCuJLc4Ci-V8ZvhSBvAxl2Rqh6N5bm~o8X-J81wWrsL0JWTtFF4Z8Ea5Toj9cEbRgPvOkj5RzgC8VuBWywfANCpS~159Jfl4~82InL5p-qNvdL6K1F~V4nxIjccoL1XcrsqhZ4vUp9rWYs9OMqppw~WsgPtvDABvLX6zT6byaeqKZQAaz7W3546HXi6J1gkUTy2LWLPoNm9YARz~MxkVsS~VXLMWUuFmriydaYImAVmtIDpawSlAmb~YW~Sg6Hp-vA3OlJGo5gS9GX-LvvE8C6OJrpKSAxeBMbw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"I_SPY_COVID_adaptive_platform_trial_for_COVID_19_acute_respiratory_failure_rationale_design_and_operations","translated_slug":"","page_count":12,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[{"id":111659564,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/111659564/thumbnails/1.jpg","file_name":"e060664.full.pdf","download_url":"https://www.academia.edu/attachments/111659564/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"I_SPY_COVID_adaptive_platform_trial_for.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/111659564/e060664.full-libre.pdf?1708457094=\u0026response-content-disposition=attachment%3B+filename%3DI_SPY_COVID_adaptive_platform_trial_for.pdf\u0026Expires=1732512681\u0026Signature=K7CcP1mpvOM2-DWPK10PvoKwVvwK66U4UU8wkzMUGOZT8egG237vCuJLc4Ci-V8ZvhSBvAxl2Rqh6N5bm~o8X-J81wWrsL0JWTtFF4Z8Ea5Toj9cEbRgPvOkj5RzgC8VuBWywfANCpS~159Jfl4~82InL5p-qNvdL6K1F~V4nxIjccoL1XcrsqhZ4vUp9rWYs9OMqppw~WsgPtvDABvLX6zT6byaeqKZQAaz7W3546HXi6J1gkUTy2LWLPoNm9YARz~MxkVsS~VXLMWUuFmriydaYImAVmtIDpawSlAmb~YW~Sg6Hp-vA3OlJGo5gS9GX-LvvE8C6OJrpKSAxeBMbw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":4531,"name":"Clinical Trial","url":"https://www.academia.edu/Documents/in/Clinical_Trial"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":1028827,"name":"Pandemic","url":"https://www.academia.edu/Documents/in/Pandemic"},{"id":3686510,"name":"Coronavirus Disease 2019 (COVID-19)","url":"https://www.academia.edu/Documents/in/Coronavirus_Disease_2019_COVID-19_"}],"urls":[{"id":39639213,"url":"https://bmjopen.bmj.com/content/bmjopen/12/6/e060664.full.pdf"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173639"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115173639/Abstract_GS5_03_Evaluation_of_anti_PD_1_Cemiplimab_plus_anti_LAG_3_REGN3767_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL"><img alt="Research paper thumbnail of Abstract GS5-03: Evaluation of anti-PD-1 Cemiplimab plus anti-LAG-3 REGN3767 in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/115173639/Abstract_GS5_03_Evaluation_of_anti_PD_1_Cemiplimab_plus_anti_LAG_3_REGN3767_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL">Abstract GS5-03: Evaluation of anti-PD-1 Cemiplimab plus anti-LAG-3 REGN3767 in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, Mar 1, 2023</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within b...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR). Cemiplimab is an anti-PD-1 inhibitor approved for the treatment of NSCLC and cutaneous basal and squamous cell CA. Lymphocyte activation gene 3 (LAG-3) binds MHC class II leading to inhibition of T-cell proliferation and activation and is often co-expressed with PD-1. REGN3767 is a fully humanized mAb that binds to LAG-3 and blocks inhibitory T-cell signaling. Concurrent blockade of LAG-3 with an anti-PD-1 may enhance efficacy of an anti-PD-1. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment; HR positive (HR+) patients had to be MP high risk. Treatment included Paclitaxel 80 mg/m2 IV weekly x 12 and Cemiplimab 350 mg and REGN3767 1600 mg both given q3weeks x 4, followed by doxorubicin/cyclophosphamide (AC) every 2 weeks x 4. The control arm was weekly paclitaxel x 12 followed by AC every 2-3 weeks x 4. Cemiplimab/REGN3767 was eligible to graduate in 3 of 10 pre-defined signatures: HER2-, HR-HER2-, and HR+HER2-. The statistical methods for evaluating I-SPY 2 agents has been previously described. To adapt to changing standard of care, we constructed “dynamic controls” comprising ‘best’ alternative therapies using I-SPY 2 and external data and estimated the probability of Cemiplimab/REGN3767 being superior to the dynamic control. Response predictive subtypes (Immune+ vs Immune-) were assessed using pre-treatment gene expression data and the ImPrint signature. Results: 73 HER2- patients (40 HR+ and 33 HR-) received Cemiplimab/REGN3767 treatment. The control group included [357 patients with HER2- tumors (201 HR+ and 156 HR-) enrolled since March 2010. Cemiplimab/REGN3767 graduated in both HR-/HER2- and HR+/HER2- groups; estimated pCR rates (as of June 2022) are summarized in the table. Safety events of note for Cemiplimab/REGN3767 include hypothyroidism 30.8%, adrenal insufficiency (AI) 19.2%, hyperthyroidism 14.1%, pneumonitis 1.3%, and hepatitis 3.8%. All were G1/2 except for 6 (7.7%) G3 AI and 3 (3.8%) G3 colitis. Rash occurred in 62.8%, 9% G3 and 2 pts (2.6%) had pulmonary embolism. X% of adrenal insufficiency cases required replacement therapy. 40 patients (11 HR+ and 29 HR-) in Cemiplimab/REGN3767 were predicted Immune+; 32 (29 HR+ and 3 HR-) were predicted Immune-. In the HR+ group pCR was achieved in 10/11 (91%) patients with Immune+ subtype compared with 8/29 (28%) with Immune- subtype. Additional biomarker analyses are ongoing and will be presented at the meeting. Conclusion: The I-SPY 2 study aims to assess the probability that investigational regimens will be successful in a phase 3 neoadjuvant trial. Dual immune blockade with a LAG-3 inhibitor and anti-PD1 therapy resulted in a high predicted pCR rate both in HR-/HER2- (60%) and HR+/HER2- (37%) disease. The novel Imprint signature identified a group of HR+ patients most likely to benefit from this active regimen. Table 1: Estimated pCR rates Citation Format: Claudine Isaacs, Rita Nanda, Jo Chien, Meghna S. Trivedi, Erica Stringer-Reasor, Christos Vaklavas, Judy C. Boughey, Amy Sanford, Anne Wallace, Amy S. Clark, Alexandra Thomas, Kathy S. Albain, Laura C. Kennedy, Tara B. Sanft, Kevin Kalinsky, Hyo S. Han, Nicole Williams, Mili Arora, Anthony Elias, Carla Falkson, Smita Asare, Ruixiao Lu, Maria Pitsouni, Amy Wilson, Jane Perlmutter, Hope Rugo, Richard Schwab, W. Fraser Symmans, Nola M. Hylton, Laura Van’t Veer, Douglas Yee, Angela DeMichele, Donald Berry, Laura J. Esserman, I-SPY Investigators. Evaluation of anti-PD-1 Cemiplimab plus anti-LAG-3 REGN3767 in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr GS5-03.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173639"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173639"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173639; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173639]").text(description); $(".js-view-count[data-work-id=115173639]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173639; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173639']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173639, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115173639]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173639,"title":"Abstract GS5-03: Evaluation of anti-PD-1 Cemiplimab plus anti-LAG-3 REGN3767 in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL","translated_title":"","metadata":{"abstract":"Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR). Cemiplimab is an anti-PD-1 inhibitor approved for the treatment of NSCLC and cutaneous basal and squamous cell CA. Lymphocyte activation gene 3 (LAG-3) binds MHC class II leading to inhibition of T-cell proliferation and activation and is often co-expressed with PD-1. REGN3767 is a fully humanized mAb that binds to LAG-3 and blocks inhibitory T-cell signaling. Concurrent blockade of LAG-3 with an anti-PD-1 may enhance efficacy of an anti-PD-1. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment; HR positive (HR+) patients had to be MP high risk. Treatment included Paclitaxel 80 mg/m2 IV weekly x 12 and Cemiplimab 350 mg and REGN3767 1600 mg both given q3weeks x 4, followed by doxorubicin/cyclophosphamide (AC) every 2 weeks x 4. The control arm was weekly paclitaxel x 12 followed by AC every 2-3 weeks x 4. Cemiplimab/REGN3767 was eligible to graduate in 3 of 10 pre-defined signatures: HER2-, HR-HER2-, and HR+HER2-. The statistical methods for evaluating I-SPY 2 agents has been previously described. To adapt to changing standard of care, we constructed “dynamic controls” comprising ‘best’ alternative therapies using I-SPY 2 and external data and estimated the probability of Cemiplimab/REGN3767 being superior to the dynamic control. Response predictive subtypes (Immune+ vs Immune-) were assessed using pre-treatment gene expression data and the ImPrint signature. Results: 73 HER2- patients (40 HR+ and 33 HR-) received Cemiplimab/REGN3767 treatment. The control group included [357 patients with HER2- tumors (201 HR+ and 156 HR-) enrolled since March 2010. Cemiplimab/REGN3767 graduated in both HR-/HER2- and HR+/HER2- groups; estimated pCR rates (as of June 2022) are summarized in the table. Safety events of note for Cemiplimab/REGN3767 include hypothyroidism 30.8%, adrenal insufficiency (AI) 19.2%, hyperthyroidism 14.1%, pneumonitis 1.3%, and hepatitis 3.8%. All were G1/2 except for 6 (7.7%) G3 AI and 3 (3.8%) G3 colitis. Rash occurred in 62.8%, 9% G3 and 2 pts (2.6%) had pulmonary embolism. X% of adrenal insufficiency cases required replacement therapy. 40 patients (11 HR+ and 29 HR-) in Cemiplimab/REGN3767 were predicted Immune+; 32 (29 HR+ and 3 HR-) were predicted Immune-. In the HR+ group pCR was achieved in 10/11 (91%) patients with Immune+ subtype compared with 8/29 (28%) with Immune- subtype. Additional biomarker analyses are ongoing and will be presented at the meeting. Conclusion: The I-SPY 2 study aims to assess the probability that investigational regimens will be successful in a phase 3 neoadjuvant trial. Dual immune blockade with a LAG-3 inhibitor and anti-PD1 therapy resulted in a high predicted pCR rate both in HR-/HER2- (60%) and HR+/HER2- (37%) disease. The novel Imprint signature identified a group of HR+ patients most likely to benefit from this active regimen. Table 1: Estimated pCR rates Citation Format: Claudine Isaacs, Rita Nanda, Jo Chien, Meghna S. Trivedi, Erica Stringer-Reasor, Christos Vaklavas, Judy C. Boughey, Amy Sanford, Anne Wallace, Amy S. Clark, Alexandra Thomas, Kathy S. Albain, Laura C. Kennedy, Tara B. Sanft, Kevin Kalinsky, Hyo S. Han, Nicole Williams, Mili Arora, Anthony Elias, Carla Falkson, Smita Asare, Ruixiao Lu, Maria Pitsouni, Amy Wilson, Jane Perlmutter, Hope Rugo, Richard Schwab, W. Fraser Symmans, Nola M. Hylton, Laura Van’t Veer, Douglas Yee, Angela DeMichele, Donald Berry, Laura J. Esserman, I-SPY Investigators. Evaluation of anti-PD-1 Cemiplimab plus anti-LAG-3 REGN3767 in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr GS5-03.","publisher":"American Association for Cancer Research","publication_date":{"day":1,"month":3,"year":2023,"errors":{}},"publication_name":"Cancer Research"},"translated_abstract":"Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR). Cemiplimab is an anti-PD-1 inhibitor approved for the treatment of NSCLC and cutaneous basal and squamous cell CA. Lymphocyte activation gene 3 (LAG-3) binds MHC class II leading to inhibition of T-cell proliferation and activation and is often co-expressed with PD-1. REGN3767 is a fully humanized mAb that binds to LAG-3 and blocks inhibitory T-cell signaling. Concurrent blockade of LAG-3 with an anti-PD-1 may enhance efficacy of an anti-PD-1. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment; HR positive (HR+) patients had to be MP high risk. Treatment included Paclitaxel 80 mg/m2 IV weekly x 12 and Cemiplimab 350 mg and REGN3767 1600 mg both given q3weeks x 4, followed by doxorubicin/cyclophosphamide (AC) every 2 weeks x 4. The control arm was weekly paclitaxel x 12 followed by AC every 2-3 weeks x 4. Cemiplimab/REGN3767 was eligible to graduate in 3 of 10 pre-defined signatures: HER2-, HR-HER2-, and HR+HER2-. The statistical methods for evaluating I-SPY 2 agents has been previously described. To adapt to changing standard of care, we constructed “dynamic controls” comprising ‘best’ alternative therapies using I-SPY 2 and external data and estimated the probability of Cemiplimab/REGN3767 being superior to the dynamic control. Response predictive subtypes (Immune+ vs Immune-) were assessed using pre-treatment gene expression data and the ImPrint signature. Results: 73 HER2- patients (40 HR+ and 33 HR-) received Cemiplimab/REGN3767 treatment. The control group included [357 patients with HER2- tumors (201 HR+ and 156 HR-) enrolled since March 2010. Cemiplimab/REGN3767 graduated in both HR-/HER2- and HR+/HER2- groups; estimated pCR rates (as of June 2022) are summarized in the table. Safety events of note for Cemiplimab/REGN3767 include hypothyroidism 30.8%, adrenal insufficiency (AI) 19.2%, hyperthyroidism 14.1%, pneumonitis 1.3%, and hepatitis 3.8%. All were G1/2 except for 6 (7.7%) G3 AI and 3 (3.8%) G3 colitis. Rash occurred in 62.8%, 9% G3 and 2 pts (2.6%) had pulmonary embolism. X% of adrenal insufficiency cases required replacement therapy. 40 patients (11 HR+ and 29 HR-) in Cemiplimab/REGN3767 were predicted Immune+; 32 (29 HR+ and 3 HR-) were predicted Immune-. In the HR+ group pCR was achieved in 10/11 (91%) patients with Immune+ subtype compared with 8/29 (28%) with Immune- subtype. Additional biomarker analyses are ongoing and will be presented at the meeting. Conclusion: The I-SPY 2 study aims to assess the probability that investigational regimens will be successful in a phase 3 neoadjuvant trial. Dual immune blockade with a LAG-3 inhibitor and anti-PD1 therapy resulted in a high predicted pCR rate both in HR-/HER2- (60%) and HR+/HER2- (37%) disease. The novel Imprint signature identified a group of HR+ patients most likely to benefit from this active regimen. Table 1: Estimated pCR rates Citation Format: Claudine Isaacs, Rita Nanda, Jo Chien, Meghna S. Trivedi, Erica Stringer-Reasor, Christos Vaklavas, Judy C. Boughey, Amy Sanford, Anne Wallace, Amy S. Clark, Alexandra Thomas, Kathy S. Albain, Laura C. Kennedy, Tara B. Sanft, Kevin Kalinsky, Hyo S. Han, Nicole Williams, Mili Arora, Anthony Elias, Carla Falkson, Smita Asare, Ruixiao Lu, Maria Pitsouni, Amy Wilson, Jane Perlmutter, Hope Rugo, Richard Schwab, W. Fraser Symmans, Nola M. Hylton, Laura Van’t Veer, Douglas Yee, Angela DeMichele, Donald Berry, Laura J. Esserman, I-SPY Investigators. Evaluation of anti-PD-1 Cemiplimab plus anti-LAG-3 REGN3767 in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr GS5-03.","internal_url":"https://www.academia.edu/115173639/Abstract_GS5_03_Evaluation_of_anti_PD_1_Cemiplimab_plus_anti_LAG_3_REGN3767_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL","translated_internal_url":"","created_at":"2024-02-20T08:16:14.980-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_GS5_03_Evaluation_of_anti_PD_1_Cemiplimab_plus_anti_LAG_3_REGN3767_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"},{"id":168351,"name":"Paclitaxel","url":"https://www.academia.edu/Documents/in/Paclitaxel"}],"urls":[{"id":39639212,"url":"https://doi.org/10.1158/1538-7445.sabcs22-gs5-03"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173638"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173638/Abstract_P5_17_03_The_12_gene_DCIS_score_assay_Impact_on_radiation_treatment_XRT_recommendations_and_clinical_utility"><img alt="Research paper thumbnail of Abstract P5-17-03: The 12-gene DCIS score assay: Impact on radiation treatment (XRT) recommendations and clinical utility" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173638/Abstract_P5_17_03_The_12_gene_DCIS_score_assay_Impact_on_radiation_treatment_XRT_recommendations_and_clinical_utility">Abstract P5-17-03: The 12-gene DCIS score assay: Impact on radiation treatment (XRT) recommendations and clinical utility</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: In the management of DCIS clinicians and patients (pts) must choose between the vario...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: In the management of DCIS clinicians and patients (pts) must choose between the various options for breast conservation treatment based on an assessment of local recurrence (LR) risk. Traditional clinicopathologic (CP) factors such as age, size, grade, margin width or comedo necrosis, provide an average LR risk derived from clinical trials and population studies. The Oncotype DX® 12-gene assay for DCIS gives individual 10-yr LR risk estimates and has now been validated in two studies in a total of 893 pts. We report the 2nd study assessing the impact of the DCIS Score result on XRT recommendations. In addition, surveys assessing pt and physician confidence will provide insight into the overall clinical utility of the DCIS Score result. Baseline characteristics including the pre-assay LR risk and XRT recommendation are described here; final results on change in XRT recommendation from pre- to post-assay and distribution of the score across the CP factors will be presented. Methods: 13 U.S. sites enrolled pts with DCIS from 3/2014-5/2015. Pts with LCIS but no DCIS, invasive BC, or planned mastectomy were excluded. Data were prospectively collected on CP factors, physician estimates of LR risk, DCIS score, and pre/post XRT recommendation. Each pt had a surgeon and radiation oncologist complete study surveys. Pt surveys were also administered pre/post assay for decision conflict and the STAIT anxiety survey. The LR risk estimates and XRT recommendations were analyzed for all physicians as well as by specialty. Descriptive statistics summarized study variables. 95% Clopper-Pearson Exact CIs were calculated for percent change in XRT recommendation. McNemar&#39;s test was used to determine if the proportion of pts had a significant change in XRT recommendation post assay. Paired t-tests were used to compare physician estimates of recurrence risk pre/post assay. Results: Of the 121 pts enrolled, median age was 61y (34-83) and 80.2% were postmenopausal. Median size was 8mm and 40% were &amp;lt; 5mm; 22.3% were grade 1, 51.2% grade 2, and 26.4% grade 3. Comedo necrosis was noted in 55.4% and 19% had multiple foci. Median margin width was 3mm and 47.1% had margins 1-3mm. ER and PR by IHC were positive in 88.4% and 75.2% of pts. Among the 242 MD risk assessments, mean 10-yr LR risk was 14.8% (range 4-50%) for any LR; 14.2% for surgeons and 15.3% for radiation oncologists. The pre-assay XRT recommendation was 70.2%; 68.6% for surgeons and 71.9% for radiation oncologists. Conclusions: The role of new molecular tools such as the DCIS Score assay that provide individual risk estimates for LR on treatment decisions is evolving. The DCIS pts enrolled in the study reveal inclusion of baseline features like higher nuclear grade (26%), comedo necrosis (55%) and margin width of 1-3mm (47%) that have historically been associated with XRT use. This represents a continued broadening of the assay use from the predominantly lower risk DCIS cohort in the 1st validation study (E5194). The impact on XRT decisions is critical to establishing the clinical utility of the assay. The decision impact analysis, differences in use of the assay among surgeons and radiation oncologists and the impact on overall confidence with the treatment decision will be presented. Citation Format: Manders JB, Kuerer HM, Smith BD, McCluskey C, Farrar WB, Frazier TG, Li L, Leonard CE, Carter DL, Chawla S, Medeiros LE, Guenther JM, Castellini LE, Buchholz DJ, Mamounas EP, Wapnir IL, Horst KC, Chagpar A, Evans SB, Riker AI, Vali FS, Solin LJ, Jablon L, Recht A, Sharma R, Lu R, Sing AP, Hwang ES, White J. The 12-gene DCIS score assay: Impact on radiation treatment (XRT) recommendations and clinical utility. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P5-17-03.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173638"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173638"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173638; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173638]").text(description); $(".js-view-count[data-work-id=115173638]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173638; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173638']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173638, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115173638]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173638,"title":"Abstract P5-17-03: The 12-gene DCIS score assay: Impact on radiation treatment (XRT) recommendations and clinical utility","translated_title":"","metadata":{"abstract":"Background: In the management of DCIS clinicians and patients (pts) must choose between the various options for breast conservation treatment based on an assessment of local recurrence (LR) risk. Traditional clinicopathologic (CP) factors such as age, size, grade, margin width or comedo necrosis, provide an average LR risk derived from clinical trials and population studies. The Oncotype DX® 12-gene assay for DCIS gives individual 10-yr LR risk estimates and has now been validated in two studies in a total of 893 pts. We report the 2nd study assessing the impact of the DCIS Score result on XRT recommendations. In addition, surveys assessing pt and physician confidence will provide insight into the overall clinical utility of the DCIS Score result. Baseline characteristics including the pre-assay LR risk and XRT recommendation are described here; final results on change in XRT recommendation from pre- to post-assay and distribution of the score across the CP factors will be presented. Methods: 13 U.S. sites enrolled pts with DCIS from 3/2014-5/2015. Pts with LCIS but no DCIS, invasive BC, or planned mastectomy were excluded. Data were prospectively collected on CP factors, physician estimates of LR risk, DCIS score, and pre/post XRT recommendation. Each pt had a surgeon and radiation oncologist complete study surveys. Pt surveys were also administered pre/post assay for decision conflict and the STAIT anxiety survey. The LR risk estimates and XRT recommendations were analyzed for all physicians as well as by specialty. Descriptive statistics summarized study variables. 95% Clopper-Pearson Exact CIs were calculated for percent change in XRT recommendation. McNemar\u0026#39;s test was used to determine if the proportion of pts had a significant change in XRT recommendation post assay. Paired t-tests were used to compare physician estimates of recurrence risk pre/post assay. Results: Of the 121 pts enrolled, median age was 61y (34-83) and 80.2% were postmenopausal. Median size was 8mm and 40% were \u0026amp;lt; 5mm; 22.3% were grade 1, 51.2% grade 2, and 26.4% grade 3. Comedo necrosis was noted in 55.4% and 19% had multiple foci. Median margin width was 3mm and 47.1% had margins 1-3mm. ER and PR by IHC were positive in 88.4% and 75.2% of pts. Among the 242 MD risk assessments, mean 10-yr LR risk was 14.8% (range 4-50%) for any LR; 14.2% for surgeons and 15.3% for radiation oncologists. The pre-assay XRT recommendation was 70.2%; 68.6% for surgeons and 71.9% for radiation oncologists. Conclusions: The role of new molecular tools such as the DCIS Score assay that provide individual risk estimates for LR on treatment decisions is evolving. The DCIS pts enrolled in the study reveal inclusion of baseline features like higher nuclear grade (26%), comedo necrosis (55%) and margin width of 1-3mm (47%) that have historically been associated with XRT use. This represents a continued broadening of the assay use from the predominantly lower risk DCIS cohort in the 1st validation study (E5194). The impact on XRT decisions is critical to establishing the clinical utility of the assay. The decision impact analysis, differences in use of the assay among surgeons and radiation oncologists and the impact on overall confidence with the treatment decision will be presented. Citation Format: Manders JB, Kuerer HM, Smith BD, McCluskey C, Farrar WB, Frazier TG, Li L, Leonard CE, Carter DL, Chawla S, Medeiros LE, Guenther JM, Castellini LE, Buchholz DJ, Mamounas EP, Wapnir IL, Horst KC, Chagpar A, Evans SB, Riker AI, Vali FS, Solin LJ, Jablon L, Recht A, Sharma R, Lu R, Sing AP, Hwang ES, White J. The 12-gene DCIS score assay: Impact on radiation treatment (XRT) recommendations and clinical utility. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P5-17-03.","publication_date":{"day":15,"month":2,"year":2016,"errors":{}}},"translated_abstract":"Background: In the management of DCIS clinicians and patients (pts) must choose between the various options for breast conservation treatment based on an assessment of local recurrence (LR) risk. Traditional clinicopathologic (CP) factors such as age, size, grade, margin width or comedo necrosis, provide an average LR risk derived from clinical trials and population studies. The Oncotype DX® 12-gene assay for DCIS gives individual 10-yr LR risk estimates and has now been validated in two studies in a total of 893 pts. We report the 2nd study assessing the impact of the DCIS Score result on XRT recommendations. In addition, surveys assessing pt and physician confidence will provide insight into the overall clinical utility of the DCIS Score result. Baseline characteristics including the pre-assay LR risk and XRT recommendation are described here; final results on change in XRT recommendation from pre- to post-assay and distribution of the score across the CP factors will be presented. Methods: 13 U.S. sites enrolled pts with DCIS from 3/2014-5/2015. Pts with LCIS but no DCIS, invasive BC, or planned mastectomy were excluded. Data were prospectively collected on CP factors, physician estimates of LR risk, DCIS score, and pre/post XRT recommendation. Each pt had a surgeon and radiation oncologist complete study surveys. Pt surveys were also administered pre/post assay for decision conflict and the STAIT anxiety survey. The LR risk estimates and XRT recommendations were analyzed for all physicians as well as by specialty. Descriptive statistics summarized study variables. 95% Clopper-Pearson Exact CIs were calculated for percent change in XRT recommendation. McNemar\u0026#39;s test was used to determine if the proportion of pts had a significant change in XRT recommendation post assay. Paired t-tests were used to compare physician estimates of recurrence risk pre/post assay. Results: Of the 121 pts enrolled, median age was 61y (34-83) and 80.2% were postmenopausal. Median size was 8mm and 40% were \u0026amp;lt; 5mm; 22.3% were grade 1, 51.2% grade 2, and 26.4% grade 3. Comedo necrosis was noted in 55.4% and 19% had multiple foci. Median margin width was 3mm and 47.1% had margins 1-3mm. ER and PR by IHC were positive in 88.4% and 75.2% of pts. Among the 242 MD risk assessments, mean 10-yr LR risk was 14.8% (range 4-50%) for any LR; 14.2% for surgeons and 15.3% for radiation oncologists. The pre-assay XRT recommendation was 70.2%; 68.6% for surgeons and 71.9% for radiation oncologists. Conclusions: The role of new molecular tools such as the DCIS Score assay that provide individual risk estimates for LR on treatment decisions is evolving. The DCIS pts enrolled in the study reveal inclusion of baseline features like higher nuclear grade (26%), comedo necrosis (55%) and margin width of 1-3mm (47%) that have historically been associated with XRT use. This represents a continued broadening of the assay use from the predominantly lower risk DCIS cohort in the 1st validation study (E5194). The impact on XRT decisions is critical to establishing the clinical utility of the assay. The decision impact analysis, differences in use of the assay among surgeons and radiation oncologists and the impact on overall confidence with the treatment decision will be presented. Citation Format: Manders JB, Kuerer HM, Smith BD, McCluskey C, Farrar WB, Frazier TG, Li L, Leonard CE, Carter DL, Chawla S, Medeiros LE, Guenther JM, Castellini LE, Buchholz DJ, Mamounas EP, Wapnir IL, Horst KC, Chagpar A, Evans SB, Riker AI, Vali FS, Solin LJ, Jablon L, Recht A, Sharma R, Lu R, Sing AP, Hwang ES, White J. The 12-gene DCIS score assay: Impact on radiation treatment (XRT) recommendations and clinical utility. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P5-17-03.","internal_url":"https://www.academia.edu/115173638/Abstract_P5_17_03_The_12_gene_DCIS_score_assay_Impact_on_radiation_treatment_XRT_recommendations_and_clinical_utility","translated_internal_url":"","created_at":"2024-02-20T08:16:14.713-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_P5_17_03_The_12_gene_DCIS_score_assay_Impact_on_radiation_treatment_XRT_recommendations_and_clinical_utility","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"}],"urls":[{"id":39639211,"url":"https://doi.org/10.1158/1538-7445.sabcs15-p5-17-03"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173637"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115173637/Abstract_GS5_04_Identification_of_symptoms_that_are_associated_with_irAEs_in_the_I_SPY_clinical_trial"><img alt="Research paper thumbnail of Abstract GS5-04: Identification of symptoms that are associated with irAEs in the I-SPY clinical trial" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/115173637/Abstract_GS5_04_Identification_of_symptoms_that_are_associated_with_irAEs_in_the_I_SPY_clinical_trial">Abstract GS5-04: Identification of symptoms that are associated with irAEs in the I-SPY clinical trial</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, Mar 1, 2023</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173637"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173637"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173637; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115173637]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173637,"title":"Abstract GS5-04: Identification of symptoms that are associated with irAEs in the I-SPY clinical trial","translated_title":"","metadata":{"publisher":"American Association for Cancer Research","publication_date":{"day":1,"month":3,"year":2023,"errors":{}},"publication_name":"Cancer Research"},"translated_abstract":null,"internal_url":"https://www.academia.edu/115173637/Abstract_GS5_04_Identification_of_symptoms_that_are_associated_with_irAEs_in_the_I_SPY_clinical_trial","translated_internal_url":"","created_at":"2024-02-20T08:16:14.565-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_GS5_04_Identification_of_symptoms_that_are_associated_with_irAEs_in_the_I_SPY_clinical_trial","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"},{"id":2601211,"name":"Adverse effect","url":"https://www.academia.edu/Documents/in/Adverse_effect"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173636"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173636/Abstract_P5_05_05_Monitoring_for_response_and_recurrence_in_neoadjuvant_treated_hormone_receptor_positive_HER2_negative_breast_cancer_by_personalized_circulating_tumor_DNA_testing"><img alt="Research paper thumbnail of Abstract P5-05-05: Monitoring for response and recurrence in neoadjuvant-treated hormone receptor-positive HER2-negative breast cancer by personalized circulating tumor DNA testing" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173636/Abstract_P5_05_05_Monitoring_for_response_and_recurrence_in_neoadjuvant_treated_hormone_receptor_positive_HER2_negative_breast_cancer_by_personalized_circulating_tumor_DNA_testing">Abstract P5-05-05: Monitoring for response and recurrence in neoadjuvant-treated hormone receptor-positive HER2-negative breast cancer by personalized circulating tumor DNA testing</a></div><div class="wp-workCard_item"><span>Cancer Research</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: The detection of circulating tumor DNA (ctDNA) may serve as an early predictor of res...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: The detection of circulating tumor DNA (ctDNA) may serve as an early predictor of response and recurrence. In this study, we used a tumor-informed ctDNA test to monitor clinical outcomes in patients with high-risk hormone receptor-positive HER2-negative (HR+HER2-) tumors who received neoadjuvant chemotherapy (NAC) on the I-SPY 2 trial (NCT01042379). Methods: We collected blood samples at pretreatment, during (at 3 and 12 weeks after initiation of paclitaxel-based treatment with or without an investigational drug), after NAC prior to surgery, 4 weeks after surgery, and annually until clinical diagnosis of recurrence. Cell-free DNA was isolated from plasma (N=329 samples) and ctDNA was detected using a personalized, tumor-informed multiplex polymerase chain reaction next generation sequencing-based test (SignateraTM). All patients were at high risk for recurrence by MammaPrint. The response endpoints were pathologic complete response (pCR) and residual cancer burden (RCB),...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173636"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173636"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173636; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173636]").text(description); $(".js-view-count[data-work-id=115173636]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173636; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173636']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173636, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115173636]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173636,"title":"Abstract P5-05-05: Monitoring for response and recurrence in neoadjuvant-treated hormone receptor-positive HER2-negative breast cancer by personalized circulating tumor DNA testing","translated_title":"","metadata":{"abstract":"Background: The detection of circulating tumor DNA (ctDNA) may serve as an early predictor of response and recurrence. In this study, we used a tumor-informed ctDNA test to monitor clinical outcomes in patients with high-risk hormone receptor-positive HER2-negative (HR+HER2-) tumors who received neoadjuvant chemotherapy (NAC) on the I-SPY 2 trial (NCT01042379). Methods: We collected blood samples at pretreatment, during (at 3 and 12 weeks after initiation of paclitaxel-based treatment with or without an investigational drug), after NAC prior to surgery, 4 weeks after surgery, and annually until clinical diagnosis of recurrence. Cell-free DNA was isolated from plasma (N=329 samples) and ctDNA was detected using a personalized, tumor-informed multiplex polymerase chain reaction next generation sequencing-based test (SignateraTM). All patients were at high risk for recurrence by MammaPrint. The response endpoints were pathologic complete response (pCR) and residual cancer burden (RCB),...","publisher":"American Association for Cancer Research (AACR)","publication_name":"Cancer Research"},"translated_abstract":"Background: The detection of circulating tumor DNA (ctDNA) may serve as an early predictor of response and recurrence. In this study, we used a tumor-informed ctDNA test to monitor clinical outcomes in patients with high-risk hormone receptor-positive HER2-negative (HR+HER2-) tumors who received neoadjuvant chemotherapy (NAC) on the I-SPY 2 trial (NCT01042379). Methods: We collected blood samples at pretreatment, during (at 3 and 12 weeks after initiation of paclitaxel-based treatment with or without an investigational drug), after NAC prior to surgery, 4 weeks after surgery, and annually until clinical diagnosis of recurrence. Cell-free DNA was isolated from plasma (N=329 samples) and ctDNA was detected using a personalized, tumor-informed multiplex polymerase chain reaction next generation sequencing-based test (SignateraTM). All patients were at high risk for recurrence by MammaPrint. The response endpoints were pathologic complete response (pCR) and residual cancer burden (RCB),...","internal_url":"https://www.academia.edu/115173636/Abstract_P5_05_05_Monitoring_for_response_and_recurrence_in_neoadjuvant_treated_hormone_receptor_positive_HER2_negative_breast_cancer_by_personalized_circulating_tumor_DNA_testing","translated_internal_url":"","created_at":"2024-02-20T08:16:14.365-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_P5_05_05_Monitoring_for_response_and_recurrence_in_neoadjuvant_treated_hormone_receptor_positive_HER2_negative_breast_cancer_by_personalized_circulating_tumor_DNA_testing","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"}],"urls":[{"id":39639210,"url":"https://aacrjournals.org/cancerres/article/83/5_Supplement/P5-05-05/717430/Abstract-P5-05-05-Monitoring-for-response-and"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173635"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173635/Validating_the_association_of_adverse_pathology_with_distant_metastasis_and_prostate_cancer_mortality_20_years_after_radical_prostatectomy"><img alt="Research paper thumbnail of Validating the association of adverse pathology with distant metastasis and prostate cancer mortality 20-years after radical prostatectomy" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173635/Validating_the_association_of_adverse_pathology_with_distant_metastasis_and_prostate_cancer_mortality_20_years_after_radical_prostatectomy">Validating the association of adverse pathology with distant metastasis and prostate cancer mortality 20-years after radical prostatectomy</a></div><div class="wp-workCard_item"><span>Urologic Oncology: Seminars and Original Investigations</span><span>, 2022</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">PURPOSE To assess the association of adverse pathology (AP), defined as high-grade (≥ Gleason Gra...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">PURPOSE To assess the association of adverse pathology (AP), defined as high-grade (≥ Gleason Grade Group 3) and/or non-organ confined disease, with long-term oncologic outcomes after radical prostatectomy (RP). MATERIALS AND METHODS Using a stratified cohort sampling design, we evaluated the association of AP with the risk of distant metastasis (DM) and prostate cancer-specific mortality (PCSM) up to 20 years after RP in 428 patients treated between 1987 to 2004. Cox regression of cause-specific hazards was used to estimate the absolute risk of both endpoints, with death from other causes treated as a competing risk. Additionally, subgroup analysis in patients with low and/or intermediate-risk disease, who are potentially eligible for active surveillance (AS), was performed. RESULTS Within the cohort sample, 53% of men exhibited AP at time of RP, with median follow up of 15.5 years (IQR 14.6-16.6 years) thereafter. Adverse pathology was highly associated with DM and PCSM in the overall cohort (HR 12.30, 95% confidence interval [CI] 5.30-28.55, and HR 10.03, 95% CI 3.42-29.47, respectively, both P &lt; 0.001). Adverse pathology was also highly associated with DM and PCSM in the low/intermediate-risk subgroup (HR 10.48, 95% CI 4.18-26.28, and 8.60, 95% CI 2.40-30.48, respectively, both P &lt; 0.001). CONCLUSIONS Adverse pathology at the time of RP is highly associated with future development of DM and PCSM. Accurate prediction of AP may thus be useful for individualizing risk-based surveillance and treatment strategies.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173635"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173635"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173635; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173635]").text(description); $(".js-view-count[data-work-id=115173635]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173635; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173635']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173635, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115173635]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173635,"title":"Validating the association of adverse pathology with distant metastasis and prostate cancer mortality 20-years after radical prostatectomy","translated_title":"","metadata":{"abstract":"PURPOSE To assess the association of adverse pathology (AP), defined as high-grade (≥ Gleason Grade Group 3) and/or non-organ confined disease, with long-term oncologic outcomes after radical prostatectomy (RP). MATERIALS AND METHODS Using a stratified cohort sampling design, we evaluated the association of AP with the risk of distant metastasis (DM) and prostate cancer-specific mortality (PCSM) up to 20 years after RP in 428 patients treated between 1987 to 2004. Cox regression of cause-specific hazards was used to estimate the absolute risk of both endpoints, with death from other causes treated as a competing risk. Additionally, subgroup analysis in patients with low and/or intermediate-risk disease, who are potentially eligible for active surveillance (AS), was performed. RESULTS Within the cohort sample, 53% of men exhibited AP at time of RP, with median follow up of 15.5 years (IQR 14.6-16.6 years) thereafter. Adverse pathology was highly associated with DM and PCSM in the overall cohort (HR 12.30, 95% confidence interval [CI] 5.30-28.55, and HR 10.03, 95% CI 3.42-29.47, respectively, both P \u0026lt; 0.001). Adverse pathology was also highly associated with DM and PCSM in the low/intermediate-risk subgroup (HR 10.48, 95% CI 4.18-26.28, and 8.60, 95% CI 2.40-30.48, respectively, both P \u0026lt; 0.001). CONCLUSIONS Adverse pathology at the time of RP is highly associated with future development of DM and PCSM. Accurate prediction of AP may thus be useful for individualizing risk-based surveillance and treatment strategies.","publisher":"Elsevier BV","publication_date":{"day":null,"month":null,"year":2022,"errors":{}},"publication_name":"Urologic Oncology: Seminars and Original Investigations"},"translated_abstract":"PURPOSE To assess the association of adverse pathology (AP), defined as high-grade (≥ Gleason Grade Group 3) and/or non-organ confined disease, with long-term oncologic outcomes after radical prostatectomy (RP). MATERIALS AND METHODS Using a stratified cohort sampling design, we evaluated the association of AP with the risk of distant metastasis (DM) and prostate cancer-specific mortality (PCSM) up to 20 years after RP in 428 patients treated between 1987 to 2004. Cox regression of cause-specific hazards was used to estimate the absolute risk of both endpoints, with death from other causes treated as a competing risk. Additionally, subgroup analysis in patients with low and/or intermediate-risk disease, who are potentially eligible for active surveillance (AS), was performed. RESULTS Within the cohort sample, 53% of men exhibited AP at time of RP, with median follow up of 15.5 years (IQR 14.6-16.6 years) thereafter. Adverse pathology was highly associated with DM and PCSM in the overall cohort (HR 12.30, 95% confidence interval [CI] 5.30-28.55, and HR 10.03, 95% CI 3.42-29.47, respectively, both P \u0026lt; 0.001). Adverse pathology was also highly associated with DM and PCSM in the low/intermediate-risk subgroup (HR 10.48, 95% CI 4.18-26.28, and 8.60, 95% CI 2.40-30.48, respectively, both P \u0026lt; 0.001). CONCLUSIONS Adverse pathology at the time of RP is highly associated with future development of DM and PCSM. Accurate prediction of AP may thus be useful for individualizing risk-based surveillance and treatment strategies.","internal_url":"https://www.academia.edu/115173635/Validating_the_association_of_adverse_pathology_with_distant_metastasis_and_prostate_cancer_mortality_20_years_after_radical_prostatectomy","translated_internal_url":"","created_at":"2024-02-20T08:16:13.999-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Validating_the_association_of_adverse_pathology_with_distant_metastasis_and_prostate_cancer_mortality_20_years_after_radical_prostatectomy","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":12980,"name":"Prostate Cancer","url":"https://www.academia.edu/Documents/in/Prostate_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"},{"id":190203,"name":"Cohort","url":"https://www.academia.edu/Documents/in/Cohort"},{"id":418283,"name":"Proportional hazards model","url":"https://www.academia.edu/Documents/in/Proportional_hazards_model"},{"id":2601211,"name":"Adverse effect","url":"https://www.academia.edu/Documents/in/Adverse_effect"},{"id":2943946,"name":"Urologic Oncology","url":"https://www.academia.edu/Documents/in/Urologic_Oncology"},{"id":3382526,"name":"Prostatectomy","url":"https://www.academia.edu/Documents/in/Prostatectomy"}],"urls":[{"id":39639209,"url":"https://api.elsevier.com/content/article/PII:S1078143921004737?httpAccept=text/xml"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173634"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173634/Adverse_pathology_at_radical_prostatectomy_GPS_test_and_clinical_pathology_features_as_predictors_of_long_term_prostate_cancer_outcomes"><img alt="Research paper thumbnail of Adverse pathology at radical prostatectomy, GPS™ test, and clinical/pathology features as predictors of long-term prostate cancer outcomes" class="work-thumbnail" src="https://attachments.academia-assets.com/111659597/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173634/Adverse_pathology_at_radical_prostatectomy_GPS_test_and_clinical_pathology_features_as_predictors_of_long_term_prostate_cancer_outcomes">Adverse pathology at radical prostatectomy, GPS™ test, and clinical/pathology features as predictors of long-term prostate cancer outcomes</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="7b16e2bc7447241eb6e1c75eedb28190" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":111659597,"asset_id":115173634,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/111659597/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173634"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173634"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173634; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173634]").text(description); $(".js-view-count[data-work-id=115173634]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173634; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173634']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173634, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "7b16e2bc7447241eb6e1c75eedb28190" } } $('.js-work-strip[data-work-id=115173634]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173634,"title":"Adverse pathology at radical prostatectomy, GPS™ test, and clinical/pathology features as predictors of long-term prostate cancer outcomes","translated_title":"","metadata":{"grobid_abstract":"Introduction \u0026 Objectives: Evaluate the association of adverse pathology (AP) in radical prostatectomy (RP) tissue with 20-year risk of clinical recurrence (CR), distant metastasis (DM) and prostate cancer mortality (PCM). Explore associations of the Oncotype DX Genomic Prostate Score® (GPS™) test, grade, stage and PSA level with long-term outcomes of CR, DM, and PCM. Materials \u0026 Methods: Long term follow-up of 2641 clinical stage T1/T2 prostate cancer (PCa) patients treated with RP at the Cleveland Clinic from 1987-2004 was obtained from an IRB-approved prospectively maintained database. Using cohort sampling, 428 patients were selected with CR and no CR in 1:3 ratio. AP (pT3 or higher or primary Gleason pattern ≥4 or any pattern 5), was assessed using the 2005 International Society of Urological Pathology guidelines. Times from surgery to CR (DM or local recurrence), DM and PCM were analyzed using a weighted Cox model. The absolute risk of these outcomes over 20 years after surgery was evaluated using Cox regression of cause-specific hazards treating death due to non-PCa causes as a competing risk. Since the GPS test was developed using this cohort, GPS hazard ratios were corrected for regression to the mean (RM) and false discovery rates (FDR) were reported. Results: Median follow up was 15.5 years. Most patients had AUA low (55%) or intermediate risk (35%) disease. At RP, 52.8% of patients had AP. AP was strongly associated with DM (hazard ratio (HR) and 95% Confidence Interval 12.30 (5.30, 28.55), p\u003c.001) and PCM (HR 10.03 (3.42, 29.47), p\u003c.001). AP was also strongly associated with CR, but the strength of association appeared to change over time (0-10 years, HR 9.01 (4.01, 20.25), p\u003c.001; after 10 years, HR 1.85 (0.39, 8.71), p=.44). Results with AUA low and intermediate risk PCa were similar. GPS result appeared associated with long-term outcomes (RM-corrected HR (95% Confidence Interval) per 20 units for DM 3.67 (2.34, 6.27), FDR \u003c.01), as did log2","publication_date":{"day":null,"month":null,"year":2020,"errors":{}},"grobid_abstract_attachment_id":111659597},"translated_abstract":null,"internal_url":"https://www.academia.edu/115173634/Adverse_pathology_at_radical_prostatectomy_GPS_test_and_clinical_pathology_features_as_predictors_of_long_term_prostate_cancer_outcomes","translated_internal_url":"","created_at":"2024-02-20T08:16:13.846-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":111659597,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/111659597/thumbnails/1.jpg","file_name":"main.pdf","download_url":"https://www.academia.edu/attachments/111659597/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Adverse_pathology_at_radical_prostatecto.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/111659597/main-libre.pdf?1708457080=\u0026response-content-disposition=attachment%3B+filename%3DAdverse_pathology_at_radical_prostatecto.pdf\u0026Expires=1732512681\u0026Signature=dIFbOQ5wuLCLwRL47Gr6bUKRGXOHPxLJq~~ZrGGW0CqiRKPbl-a3Omlbyth5182XAeUjn8DhIJdAeu5JaVi2mebst3x2NcEk3vQ9nMf9Iyn0ShTNihfFtp-HeEnicFMR9nG-Fw4mpr6bNypZRV1X3qNXzsyxYBEzRMcBxGs-YeC2TuxrSUmqJbt0VLEGJrq8TCenbDC2XvDn3BoyHWH-6GXxF85Kl6q4ovvFEucudKhQh~8lfw-OFza~gN9hi~3pdKRi0sjC~Wux4k7TKL0r5L3Uuq1MJogKzscaKRtxgaw8gR1rRcXUCg~fJo2rf4VpmFEjqERkIiODbyxsoLqIwQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Adverse_pathology_at_radical_prostatectomy_GPS_test_and_clinical_pathology_features_as_predictors_of_long_term_prostate_cancer_outcomes","translated_slug":"","page_count":1,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[{"id":111659597,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/111659597/thumbnails/1.jpg","file_name":"main.pdf","download_url":"https://www.academia.edu/attachments/111659597/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Adverse_pathology_at_radical_prostatecto.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/111659597/main-libre.pdf?1708457080=\u0026response-content-disposition=attachment%3B+filename%3DAdverse_pathology_at_radical_prostatecto.pdf\u0026Expires=1732512681\u0026Signature=dIFbOQ5wuLCLwRL47Gr6bUKRGXOHPxLJq~~ZrGGW0CqiRKPbl-a3Omlbyth5182XAeUjn8DhIJdAeu5JaVi2mebst3x2NcEk3vQ9nMf9Iyn0ShTNihfFtp-HeEnicFMR9nG-Fw4mpr6bNypZRV1X3qNXzsyxYBEzRMcBxGs-YeC2TuxrSUmqJbt0VLEGJrq8TCenbDC2XvDn3BoyHWH-6GXxF85Kl6q4ovvFEucudKhQh~8lfw-OFza~gN9hi~3pdKRi0sjC~Wux4k7TKL0r5L3Uuq1MJogKzscaKRtxgaw8gR1rRcXUCg~fJo2rf4VpmFEjqERkIiODbyxsoLqIwQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":12980,"name":"Prostate Cancer","url":"https://www.academia.edu/Documents/in/Prostate_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":3382526,"name":"Prostatectomy","url":"https://www.academia.edu/Documents/in/Prostatectomy"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173633"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173633/Abstract_P4_15_09_Refined_estimates_of_local_recurrence_risk_in_a_clinical_utility_study_Integrating_the_DCIS_score_patient_age_and_DCIS_tumor_size"><img alt="Research paper thumbnail of Abstract P4-15-09: Refined estimates of local recurrence risk in a clinical utility study: Integrating the DCIS score, patient age and DCIS tumor size" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173633/Abstract_P4_15_09_Refined_estimates_of_local_recurrence_risk_in_a_clinical_utility_study_Integrating_the_DCIS_score_patient_age_and_DCIS_tumor_size">Abstract P4-15-09: Refined estimates of local recurrence risk in a clinical utility study: Integrating the DCIS score, patient age and DCIS tumor size</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background:Better tools are needed to estimate the risk of local recurrence (LR; DCIS or invasive...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background:Better tools are needed to estimate the risk of local recurrence (LR; DCIS or invasive) after breast-conserving surgery (BCS) for pts with DCIS in order to inform treatment decisions. Traditional clinico-pathologic (CP) factors, e.g., age and tumor size, provide an average LR risk derived from clinical trials and population studies. The Oncotype DX 12-gene DCIS Score assay has been validated to provide individual 10 yr LR risk estimates (Solin JNCI 2013; Rakovitch BCRT 2015). Previously we reported the impact of the DCIS Score result on radiotherapy (RT) recommendations including the pre-assay LR risk and RT recommendation and the change in RT recommendation from pre- to post-assay (Manders Ann Surg Oncol 2016).Recently a patient specific meta-analysis (MA) combined data from E5194 and Ontario DCIS Cohort (ODC) adjusting for pertinent clinico-pathologic factors to provide refined prediction estimates of LR risk after BCS alone (Rakovitch ASCO 2017). Herein we applied thes...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173633"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173633"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173633; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173633]").text(description); $(".js-view-count[data-work-id=115173633]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173633; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173633']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173633, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115173633]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173633,"title":"Abstract P4-15-09: Refined estimates of local recurrence risk in a clinical utility study: Integrating the DCIS score, patient age and DCIS tumor size","translated_title":"","metadata":{"abstract":"Background:Better tools are needed to estimate the risk of local recurrence (LR; DCIS or invasive) after breast-conserving surgery (BCS) for pts with DCIS in order to inform treatment decisions. Traditional clinico-pathologic (CP) factors, e.g., age and tumor size, provide an average LR risk derived from clinical trials and population studies. The Oncotype DX 12-gene DCIS Score assay has been validated to provide individual 10 yr LR risk estimates (Solin JNCI 2013; Rakovitch BCRT 2015). Previously we reported the impact of the DCIS Score result on radiotherapy (RT) recommendations including the pre-assay LR risk and RT recommendation and the change in RT recommendation from pre- to post-assay (Manders Ann Surg Oncol 2016).Recently a patient specific meta-analysis (MA) combined data from E5194 and Ontario DCIS Cohort (ODC) adjusting for pertinent clinico-pathologic factors to provide refined prediction estimates of LR risk after BCS alone (Rakovitch ASCO 2017). Herein we applied thes...","publisher":"American Association for Cancer Research (AACR)","publication_date":{"day":null,"month":null,"year":2018,"errors":{}},"publication_name":"Cancer Research"},"translated_abstract":"Background:Better tools are needed to estimate the risk of local recurrence (LR; DCIS or invasive) after breast-conserving surgery (BCS) for pts with DCIS in order to inform treatment decisions. Traditional clinico-pathologic (CP) factors, e.g., age and tumor size, provide an average LR risk derived from clinical trials and population studies. The Oncotype DX 12-gene DCIS Score assay has been validated to provide individual 10 yr LR risk estimates (Solin JNCI 2013; Rakovitch BCRT 2015). Previously we reported the impact of the DCIS Score result on radiotherapy (RT) recommendations including the pre-assay LR risk and RT recommendation and the change in RT recommendation from pre- to post-assay (Manders Ann Surg Oncol 2016).Recently a patient specific meta-analysis (MA) combined data from E5194 and Ontario DCIS Cohort (ODC) adjusting for pertinent clinico-pathologic factors to provide refined prediction estimates of LR risk after BCS alone (Rakovitch ASCO 2017). Herein we applied thes...","internal_url":"https://www.academia.edu/115173633/Abstract_P4_15_09_Refined_estimates_of_local_recurrence_risk_in_a_clinical_utility_study_Integrating_the_DCIS_score_patient_age_and_DCIS_tumor_size","translated_internal_url":"","created_at":"2024-02-20T08:16:13.591-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_P4_15_09_Refined_estimates_of_local_recurrence_risk_in_a_clinical_utility_study_Integrating_the_DCIS_score_patient_age_and_DCIS_tumor_size","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":64336,"name":"Population","url":"https://www.academia.edu/Documents/in/Population"},{"id":231720,"name":"Mastectomy","url":"https://www.academia.edu/Documents/in/Mastectomy"}],"urls":[{"id":39639208,"url":"https://aacrjournals.org/cancerres/article/78/4_Supplement/P4-15-09/542070/Abstract-P4-15-09-Refined-estimates-of-local"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173632"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173632/Recurrence_score_distributions_in_stage_II_colon_cancers_of_African_American_AA_and_Caucasian_CA_patients"><img alt="Research paper thumbnail of Recurrence score distributions in stage II colon cancers of African American (AA) and Caucasian (CA) patients" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173632/Recurrence_score_distributions_in_stage_II_colon_cancers_of_African_American_AA_and_Caucasian_CA_patients">Recurrence score distributions in stage II colon cancers of African American (AA) and Caucasian (CA) patients</a></div><div class="wp-workCard_item"><span>Journal of Clinical Oncology</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">613 Background: The 12-gene colon cancer assay (Oncotype DX) can identify groups of stage II colo...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">613 Background: The 12-gene colon cancer assay (Oncotype DX) can identify groups of stage II colon cancer patients with lower or higher recurrence risk, but distribution of scores based on race/ethnicity has not been assessed. This study compared the distribution of Recurrence Score results and gene expression profiles between African American (AA) and Caucasian (CA) stage II colon cancer patients. Methods: Stage II colon cancer patients were identified from tumor registry data from four institutions: University of Arkansas for Medical Sciences, Little Rock; Veterans Administration Medical Center, Little Rock; Baptist Medical Center, Memphis, and University of Alabama at Birmingham. The 12-gene assay and mismatch repair (MMR) status were performed on formalin-fixed paraffin-embedded tissues by Genomic Health (Redwood City, CA). T-test and Wilcoxon test were used to compare data from the two groups (SAS Enterprise Guide 5.1). Results: Of the 244 subjects, there were 118 women (63 AA,...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173632"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173632"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173632; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173632]").text(description); $(".js-view-count[data-work-id=115173632]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173632; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173632']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173632, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115173632]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173632,"title":"Recurrence score distributions in stage II colon cancers of African American (AA) and Caucasian (CA) patients","translated_title":"","metadata":{"abstract":"613 Background: The 12-gene colon cancer assay (Oncotype DX) can identify groups of stage II colon cancer patients with lower or higher recurrence risk, but distribution of scores based on race/ethnicity has not been assessed. This study compared the distribution of Recurrence Score results and gene expression profiles between African American (AA) and Caucasian (CA) stage II colon cancer patients. Methods: Stage II colon cancer patients were identified from tumor registry data from four institutions: University of Arkansas for Medical Sciences, Little Rock; Veterans Administration Medical Center, Little Rock; Baptist Medical Center, Memphis, and University of Alabama at Birmingham. The 12-gene assay and mismatch repair (MMR) status were performed on formalin-fixed paraffin-embedded tissues by Genomic Health (Redwood City, CA). T-test and Wilcoxon test were used to compare data from the two groups (SAS Enterprise Guide 5.1). Results: Of the 244 subjects, there were 118 women (63 AA,...","publisher":"American Society of Clinical Oncology (ASCO)","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"Journal of Clinical Oncology"},"translated_abstract":"613 Background: The 12-gene colon cancer assay (Oncotype DX) can identify groups of stage II colon cancer patients with lower or higher recurrence risk, but distribution of scores based on race/ethnicity has not been assessed. This study compared the distribution of Recurrence Score results and gene expression profiles between African American (AA) and Caucasian (CA) stage II colon cancer patients. Methods: Stage II colon cancer patients were identified from tumor registry data from four institutions: University of Arkansas for Medical Sciences, Little Rock; Veterans Administration Medical Center, Little Rock; Baptist Medical Center, Memphis, and University of Alabama at Birmingham. The 12-gene assay and mismatch repair (MMR) status were performed on formalin-fixed paraffin-embedded tissues by Genomic Health (Redwood City, CA). T-test and Wilcoxon test were used to compare data from the two groups (SAS Enterprise Guide 5.1). Results: Of the 244 subjects, there were 118 women (63 AA,...","internal_url":"https://www.academia.edu/115173632/Recurrence_score_distributions_in_stage_II_colon_cancers_of_African_American_AA_and_Caucasian_CA_patients","translated_internal_url":"","created_at":"2024-02-20T08:16:13.399-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Recurrence_score_distributions_in_stage_II_colon_cancers_of_African_American_AA_and_Caucasian_CA_patients","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":37292,"name":"Colorectal cancer","url":"https://www.academia.edu/Documents/in/Colorectal_cancer"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"},{"id":115895,"name":"Clinical oncology","url":"https://www.academia.edu/Documents/in/Clinical_oncology"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173631"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173631/Assessing_probe_specific_dye_and_slide_biases_in_two_color_microarray_data"><img alt="Research paper thumbnail of Assessing probe-specific dye and slide biases in two-color microarray data" class="work-thumbnail" src="https://attachments.academia-assets.com/111659561/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173631/Assessing_probe_specific_dye_and_slide_biases_in_two_color_microarray_data">Assessing probe-specific dye and slide biases in two-color microarray data</a></div><div class="wp-workCard_item"><span>BMC Bioinformatics</span><span>, 2008</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background A primary reason for using two-color microarrays is that the use of two samples labele...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background A primary reason for using two-color microarrays is that the use of two samples labeled with different dyes on the same slide, that bind to probes on the same spot, is supposed to adjust for many factors that introduce noise and errors into the analysis. Most users assume that any differences between the dyes can be adjusted out by standard methods of normalization, so that measures such as log ratios on the same slide are reliable measures of comparative expression. However, even after the normalization, there are still probe specific dye and slide variation among the data. We define a method to quantify the amount of the dye-by-probe and slide-by-probe interaction. This serves as a diagnostic, both visual and numeric, of the existence of probe-specific dye bias. We show how this improved the performance of two-color array analysis for arrays for genomic analysis of biological samples ranging from rice to human tissue. Results We develop a procedure for quantifying the e...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="07cc69f797dc82c5bd29810287a07fca" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":111659561,"asset_id":115173631,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/111659561/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173631"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173631"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173631; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173631]").text(description); $(".js-view-count[data-work-id=115173631]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173631; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173631']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173631, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "07cc69f797dc82c5bd29810287a07fca" } } $('.js-work-strip[data-work-id=115173631]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173631,"title":"Assessing probe-specific dye and slide biases in two-color microarray data","translated_title":"","metadata":{"abstract":"Background A primary reason for using two-color microarrays is that the use of two samples labeled with different dyes on the same slide, that bind to probes on the same spot, is supposed to adjust for many factors that introduce noise and errors into the analysis. Most users assume that any differences between the dyes can be adjusted out by standard methods of normalization, so that measures such as log ratios on the same slide are reliable measures of comparative expression. However, even after the normalization, there are still probe specific dye and slide variation among the data. We define a method to quantify the amount of the dye-by-probe and slide-by-probe interaction. This serves as a diagnostic, both visual and numeric, of the existence of probe-specific dye bias. We show how this improved the performance of two-color array analysis for arrays for genomic analysis of biological samples ranging from rice to human tissue. Results We develop a procedure for quantifying the e...","publisher":"Springer Science and Business Media LLC","publication_date":{"day":null,"month":null,"year":2008,"errors":{}},"publication_name":"BMC Bioinformatics"},"translated_abstract":"Background A primary reason for using two-color microarrays is that the use of two samples labeled with different dyes on the same slide, that bind to probes on the same spot, is supposed to adjust for many factors that introduce noise and errors into the analysis. Most users assume that any differences between the dyes can be adjusted out by standard methods of normalization, so that measures such as log ratios on the same slide are reliable measures of comparative expression. However, even after the normalization, there are still probe specific dye and slide variation among the data. We define a method to quantify the amount of the dye-by-probe and slide-by-probe interaction. This serves as a diagnostic, both visual and numeric, of the existence of probe-specific dye bias. We show how this improved the performance of two-color array analysis for arrays for genomic analysis of biological samples ranging from rice to human tissue. Results We develop a procedure for quantifying the 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Tucatinib is a potent HER2 (ErbB2) tyrosine kinase inhibitor, selective for HER2 vs. epidermal growth factor receptor (EGFR) and is active vs. brain metastases. Safety and efficacy of tucatinib combined with paclitaxel, pertuzumab, and trastuzumab are unknown and were tested in a planned 10 patient (pt) safety run-in of the I-SPY 2 trial. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only pts with tumors that were HER2+ by FISH were eligible for this treatment. Treatment included tucatinib (max dose 300 mg) BID for 12 weeks with weekly paclitaxel 80 mg/m2 and trastuzumab (2 mg/kg weekly following loading), and pertuzumab (420 mg every 3 weeks following loading), followed by doxorubicin/cyclophosphamide (AC) every ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="105817430"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="105817430"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 105817430; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=105817430]").text(description); $(".js-view-count[data-work-id=105817430]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 105817430; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='105817430']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 105817430, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=105817430]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":105817430,"title":"Abstract PD8-07: Evaluation of Tucatinib + (Paclitaxel + Pertuzumab + Trastuzumab) followed by AC in high-risk HER2 positive (HER2+) stage II/III breast cancer: Results from the I-SPY 2 TRIAL","translated_title":"","metadata":{"abstract":"Background: I-SPY 2 is a multicenter, phase 2 trial using response-adaptive randomization within molecular subtypes defined by receptor status and MammaPrint (MP) risk to evaluate novel agents as neoadjuvant therapy for women with high-risk breast cancer. Tucatinib is a potent HER2 (ErbB2) tyrosine kinase inhibitor, selective for HER2 vs. epidermal growth factor receptor (EGFR) and is active vs. brain metastases. Safety and efficacy of tucatinib combined with paclitaxel, pertuzumab, and trastuzumab are unknown and were tested in a planned 10 patient (pt) safety run-in of the I-SPY 2 trial. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only pts with tumors that were HER2+ by FISH were eligible for this treatment. Treatment included tucatinib (max dose 300 mg) BID for 12 weeks with weekly paclitaxel 80 mg/m2 and trastuzumab (2 mg/kg weekly following loading), and pertuzumab (420 mg every 3 weeks following loading), followed by doxorubicin/cyclophosphamide (AC) every ...","publisher":"American Association for Cancer Research (AACR)","publication_date":{"day":null,"month":null,"year":2022,"errors":{}},"publication_name":"Cancer Research"},"translated_abstract":"Background: I-SPY 2 is a multicenter, phase 2 trial using response-adaptive randomization within molecular subtypes defined by receptor status and MammaPrint (MP) risk to evaluate novel agents as neoadjuvant therapy for women with high-risk breast cancer. Tucatinib is a potent HER2 (ErbB2) tyrosine kinase inhibitor, selective for HER2 vs. epidermal growth factor receptor (EGFR) and is active vs. brain metastases. Safety and efficacy of tucatinib combined with paclitaxel, pertuzumab, and trastuzumab are unknown and were tested in a planned 10 patient (pt) safety run-in of the I-SPY 2 trial. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only pts with tumors that were HER2+ by FISH were eligible for this treatment. Treatment included tucatinib (max dose 300 mg) BID for 12 weeks with weekly paclitaxel 80 mg/m2 and trastuzumab (2 mg/kg weekly following loading), and pertuzumab (420 mg every 3 weeks following loading), followed by doxorubicin/cyclophosphamide (AC) every ...","internal_url":"https://www.academia.edu/105817430/Abstract_PD8_07_Evaluation_of_Tucatinib_Paclitaxel_Pertuzumab_Trastuzumab_followed_by_AC_in_high_risk_HER2_positive_HER2_stage_II_III_breast_cancer_Results_from_the_I_SPY_2_TRIAL","translated_internal_url":"","created_at":"2023-08-21T09:09:55.626-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_PD8_07_Evaluation_of_Tucatinib_Paclitaxel_Pertuzumab_Trastuzumab_followed_by_AC_in_high_risk_HER2_positive_HER2_stage_II_III_breast_cancer_Results_from_the_I_SPY_2_TRIAL","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"},{"id":168351,"name":"Paclitaxel","url":"https://www.academia.edu/Documents/in/Paclitaxel"},{"id":983616,"name":"Trastuzumab","url":"https://www.academia.edu/Documents/in/Trastuzumab"}],"urls":[{"id":33542138,"url":"https://aacrjournals.org/cancerres/article/82/4_Supplement/PD8-07/681476/Abstract-PD8-07-Evaluation-of-Tucatinib-Paclitaxel"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="105817429"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/105817429/Abstract_P5_13_12_Immune_signatures_and_MammaPrint_ultra_high_risk_class_MP2_as_predictors_of_response_to_pembrolizumab_combined_with_the_TLR9_agonist_SD101_in_the_neoadjuvant_I_SPY_2_TRIAL"><img alt="Research paper thumbnail of Abstract P5-13-12: Immune signatures and MammaPrint (ultra) high risk class (MP2) as predictors of response to pembrolizumab combined with the TLR9 agonist SD101 in the neoadjuvant I-SPY 2 TRIAL" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/105817429/Abstract_P5_13_12_Immune_signatures_and_MammaPrint_ultra_high_risk_class_MP2_as_predictors_of_response_to_pembrolizumab_combined_with_the_TLR9_agonist_SD101_in_the_neoadjuvant_I_SPY_2_TRIAL">Abstract P5-13-12: Immune signatures and MammaPrint (ultra) high risk class (MP2) as predictors of response to pembrolizumab combined with the TLR9 agonist SD101 in the neoadjuvant I-SPY 2 TRIAL</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2022</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: Pembrolizumab, an anti-PD-1 immune checkpoint inhibitor, is approved for treatment in...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: Pembrolizumab, an anti-PD-1 immune checkpoint inhibitor, is approved for treatment in multiple cancers and has been shown to increase pathologic complete response (pCR) and survival in the neoadjuvant setting in breast cancer. Pembrolizumab combined with paclitaxel followed by doxorubicin/cyclophosphamide (P+T-&gt;AC) was evaluated in HER2- patients in the neoadjuvant I-SPY 2 TRIAL and graduated in the HER2-, HR+HER2- and triple negative (TN) signatures. Our biomarker analysis revealed that immune cell abundance and MP2 class predicts response in HR+HER2- patients whereas tumor-immune proximity scores (multiplex-IF) and signaling signatures (mRNA) predict response in TN patients. In an effort to further improve response, the TLR9 agonist SD101 was added to Pembro (P+S+T -&gt; AC) for testing in I-SPY 2. While P+S increased estimated pCR rates relative to control (T-&gt;AC), it did not graduate for efficacy. To better understand the biology underlying response to P+S, we ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="105817429"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="105817429"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 105817429; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=105817429]").text(description); $(".js-view-count[data-work-id=105817429]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 105817429; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='105817429']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 105817429, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=105817429]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":105817429,"title":"Abstract P5-13-12: Immune signatures and MammaPrint (ultra) high risk class (MP2) as predictors of response to pembrolizumab combined with the TLR9 agonist SD101 in the neoadjuvant I-SPY 2 TRIAL","translated_title":"","metadata":{"abstract":"Background: Pembrolizumab, an anti-PD-1 immune checkpoint inhibitor, is approved for treatment in multiple cancers and has been shown to increase pathologic complete response (pCR) and survival in the neoadjuvant setting in breast cancer. Pembrolizumab combined with paclitaxel followed by doxorubicin/cyclophosphamide (P+T-\u0026gt;AC) was evaluated in HER2- patients in the neoadjuvant I-SPY 2 TRIAL and graduated in the HER2-, HR+HER2- and triple negative (TN) signatures. Our biomarker analysis revealed that immune cell abundance and MP2 class predicts response in HR+HER2- patients whereas tumor-immune proximity scores (multiplex-IF) and signaling signatures (mRNA) predict response in TN patients. In an effort to further improve response, the TLR9 agonist SD101 was added to Pembro (P+S+T -\u0026gt; AC) for testing in I-SPY 2. While P+S increased estimated pCR rates relative to control (T-\u0026gt;AC), it did not graduate for efficacy. To better understand the biology underlying response to P+S, we ...","publisher":"American Association for Cancer Research (AACR)","publication_date":{"day":null,"month":null,"year":2022,"errors":{}},"publication_name":"Cancer Research"},"translated_abstract":"Background: Pembrolizumab, an anti-PD-1 immune checkpoint inhibitor, is approved for treatment in multiple cancers and has been shown to increase pathologic complete response (pCR) and survival in the neoadjuvant setting in breast cancer. Pembrolizumab combined with paclitaxel followed by doxorubicin/cyclophosphamide (P+T-\u0026gt;AC) was evaluated in HER2- patients in the neoadjuvant I-SPY 2 TRIAL and graduated in the HER2-, HR+HER2- and triple negative (TN) signatures. Our biomarker analysis revealed that immune cell abundance and MP2 class predicts response in HR+HER2- patients whereas tumor-immune proximity scores (multiplex-IF) and signaling signatures (mRNA) predict response in TN patients. In an effort to further improve response, the TLR9 agonist SD101 was added to Pembro (P+S+T -\u0026gt; AC) for testing in I-SPY 2. While P+S increased estimated pCR rates relative to control (T-\u0026gt;AC), it did not graduate for efficacy. To better understand the biology underlying response to P+S, we ...","internal_url":"https://www.academia.edu/105817429/Abstract_P5_13_12_Immune_signatures_and_MammaPrint_ultra_high_risk_class_MP2_as_predictors_of_response_to_pembrolizumab_combined_with_the_TLR9_agonist_SD101_in_the_neoadjuvant_I_SPY_2_TRIAL","translated_internal_url":"","created_at":"2023-08-21T09:09:52.907-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_P5_13_12_Immune_signatures_and_MammaPrint_ultra_high_risk_class_MP2_as_predictors_of_response_to_pembrolizumab_combined_with_the_TLR9_agonist_SD101_in_the_neoadjuvant_I_SPY_2_TRIAL","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":216943,"name":"CD","url":"https://www.academia.edu/Documents/in/CD"},{"id":324154,"name":"Immune system","url":"https://www.academia.edu/Documents/in/Immune_system"},{"id":2754235,"name":"Pembrolizumab","url":"https://www.academia.edu/Documents/in/Pembrolizumab"}],"urls":[{"id":33542137,"url":"https://aacrjournals.org/cancerres/article/82/4_Supplement/P5-13-12/681330/Abstract-P5-13-12-Immune-signatures-and-MammaPrint"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="105817423"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/105817423/Abstract_PD11_01_PD11_01_Evaluation_of_the_PD_1_Inhibitor_Cemiplimab_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL"><img alt="Research paper thumbnail of Abstract PD11-01: PD11-01 Evaluation of the PD-1 Inhibitor Cemiplimab in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/105817423/Abstract_PD11_01_PD11_01_Evaluation_of_the_PD_1_Inhibitor_Cemiplimab_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL">Abstract PD11-01: PD11-01 Evaluation of the PD-1 Inhibitor Cemiplimab in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL</a></div><div class="wp-workCard_item"><span>Cancer Research</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within b...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR). Cemiplimab (Cemi) is a PD-1 inhibitor approved for the treatment of NSCLC, cutaneous basal, and squamous cell cancer. Here, we report current efficacy rates of Cemi in combination with paclitaxel followed by AC. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment; HR positive (HR+) patients had to be MP high risk. Treatment included paclitaxel 80 mg/m2 IV weekly x 12 and Cemi 350 mg IV given q3weeks x 4, followed by doxorubicin/cyclophosphamide (AC) every 2 weeks x 4. The control arm was weekly paclitaxel x 12 followed by AC every 2-3 weeks x 4. All patients undergo serial MRI imaging; and ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="105817423"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="105817423"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 105817423; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=105817423]").text(description); $(".js-view-count[data-work-id=105817423]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 105817423; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='105817423']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 105817423, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=105817423]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":105817423,"title":"Abstract PD11-01: PD11-01 Evaluation of the PD-1 Inhibitor Cemiplimab in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL","translated_title":"","metadata":{"abstract":"Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR). Cemiplimab (Cemi) is a PD-1 inhibitor approved for the treatment of NSCLC, cutaneous basal, and squamous cell cancer. Here, we report current efficacy rates of Cemi in combination with paclitaxel followed by AC. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment; HR positive (HR+) patients had to be MP high risk. Treatment included paclitaxel 80 mg/m2 IV weekly x 12 and Cemi 350 mg IV given q3weeks x 4, followed by doxorubicin/cyclophosphamide (AC) every 2 weeks x 4. The control arm was weekly paclitaxel x 12 followed by AC every 2-3 weeks x 4. All patients undergo serial MRI imaging; and ...","publisher":"American Association for Cancer Research (AACR)","publication_name":"Cancer Research"},"translated_abstract":"Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR). Cemiplimab (Cemi) is a PD-1 inhibitor approved for the treatment of NSCLC, cutaneous basal, and squamous cell cancer. Here, we report current efficacy rates of Cemi in combination with paclitaxel followed by AC. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment; HR positive (HR+) patients had to be MP high risk. Treatment included paclitaxel 80 mg/m2 IV weekly x 12 and Cemi 350 mg IV given q3weeks x 4, followed by doxorubicin/cyclophosphamide (AC) every 2 weeks x 4. The control arm was weekly paclitaxel x 12 followed by AC every 2-3 weeks x 4. All patients undergo serial MRI imaging; and ...","internal_url":"https://www.academia.edu/105817423/Abstract_PD11_01_PD11_01_Evaluation_of_the_PD_1_Inhibitor_Cemiplimab_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL","translated_internal_url":"","created_at":"2023-08-21T09:09:40.601-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_PD11_01_PD11_01_Evaluation_of_the_PD_1_Inhibitor_Cemiplimab_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"},{"id":168351,"name":"Paclitaxel","url":"https://www.academia.edu/Documents/in/Paclitaxel"},{"id":2530768,"name":"neoadjuvant therapy","url":"https://www.academia.edu/Documents/in/neoadjuvant_therapy"}],"urls":[{"id":33542132,"url":"https://aacrjournals.org/cancerres/article/83/5_Supplement/PD11-01/717156/Abstract-PD11-01-PD11-01-Evaluation-of-the-PD-1"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="90622408"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/90622408/The_I_SPY_COVID_Adaptive_Platform_Trial_for_COVID_19_Acute_Respiratory_Failure_Rationale_Design_and_Operations"><img alt="Research paper thumbnail of The I-SPY COVID Adaptive Platform Trial for COVID-19 Acute Respiratory Failure: Rationale, Design and Operations" class="work-thumbnail" src="https://attachments.academia-assets.com/94135132/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/90622408/The_I_SPY_COVID_Adaptive_Platform_Trial_for_COVID_19_Acute_Respiratory_Failure_Rationale_Design_and_Operations">The I-SPY COVID Adaptive Platform Trial for COVID-19 Acute Respiratory Failure: Rationale, Design and Operations</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">IntroductionThe COVID-19 pandemic brought an urgent need to discover novel effective therapeutics...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">IntroductionThe COVID-19 pandemic brought an urgent need to discover novel effective therapeutics for patients hospitalized with severe COVID-19. The ISPY COVID trial was designed and implemented in early 2020 to evaluate investigational agents rapidly and simultaneously on a phase 2 adaptive platform. This manuscript outlines the design, rationale, implementation, and challenges of the ISPY COVID trial during the first phase of trial activity from April 2020 until December 2021.Methods and analysisThe ISPY COVID Trial is a multi-center open label phase 2 platform trial in the United States designed to evaluate therapeutics that may have a large effect on improving outcomes from severe COVID-19. The ISPY COVID Trial network includes academic and community hospitals with significant geographic diversity across the country. Enrolled patients are randomized to receive one of up to four investigational agents or a control and are evaluated for a family of two primary outcomes—time to re...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ca4aa49e188e50c1a6a79a7ca9d5f5fe" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":94135132,"asset_id":90622408,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/94135132/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="90622408"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="90622408"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 90622408; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=90622408]").text(description); $(".js-view-count[data-work-id=90622408]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 90622408; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='90622408']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 90622408, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "ca4aa49e188e50c1a6a79a7ca9d5f5fe" } } $('.js-work-strip[data-work-id=90622408]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":90622408,"title":"The I-SPY COVID Adaptive Platform Trial for COVID-19 Acute Respiratory Failure: Rationale, Design and Operations","translated_title":"","metadata":{"abstract":"IntroductionThe COVID-19 pandemic brought an urgent need to discover novel effective therapeutics for patients hospitalized with severe COVID-19. 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Enrolled patients are randomized to receive one of up to four investigational agents or a control and are evaluated for a family of two primary outcomes—time to re...","publisher":"Cold Spring Harbor Laboratory"},"translated_abstract":"IntroductionThe COVID-19 pandemic brought an urgent need to discover novel effective therapeutics for patients hospitalized with severe COVID-19. The ISPY COVID trial was designed and implemented in early 2020 to evaluate investigational agents rapidly and simultaneously on a phase 2 adaptive platform. This manuscript outlines the design, rationale, implementation, and challenges of the ISPY COVID trial during the first phase of trial activity from April 2020 until December 2021.Methods and analysisThe ISPY COVID Trial is a multi-center open label phase 2 platform trial in the United States designed to evaluate therapeutics that may have a large effect on improving outcomes from severe COVID-19. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="90622407"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/90622407/Abstract_PD10_07_Chemokine12_CK12_tertiary_lymphoid_gene_expression_signature_as_a_predictor_of_response_in_3_immunotherapy_arms_of_the_neoadjuvant_ISPY_2_TRIAL_pembrolizumab_with_and_without_SD101_and_durvalumab_combined_with_olaparib_and_in_9_other_arms_of_the_trial_including_platinum_b_"><img alt="Research paper thumbnail of Abstract PD10-07: Chemokine12 (CK12) tertiary lymphoid gene expression signature as a predictor of response in 3 immunotherapy arms of the neoadjuvant ISPY 2 TRIAL - pembrolizumab with and without SD101, and durvalumab combined with olaparib - and in 9 other arms of the trial including platinum-b..." class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/90622407/Abstract_PD10_07_Chemokine12_CK12_tertiary_lymphoid_gene_expression_signature_as_a_predictor_of_response_in_3_immunotherapy_arms_of_the_neoadjuvant_ISPY_2_TRIAL_pembrolizumab_with_and_without_SD101_and_durvalumab_combined_with_olaparib_and_in_9_other_arms_of_the_trial_including_platinum_b_">Abstract PD10-07: Chemokine12 (CK12) tertiary lymphoid gene expression signature as a predictor of response in 3 immunotherapy arms of the neoadjuvant ISPY 2 TRIAL - pembrolizumab with and without SD101, and durvalumab combined with olaparib - and in 9 other arms of the trial including platinum-b...</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2022</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: The CK12 expression signature consists of genes CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: The CK12 expression signature consists of genes CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11, CXCL13 and was previously shown to associate with the presence of T and B cell rich tertiary lymphoid structures in melanoma and other cancers, and with better patient survival independent of tumor staging and treatment. I-SPY 2 is a biomarker-rich, phase II neoadjuvant platform trial for high risk early stage breast cancer. Here we leverage the I-SPY 2 biomarker program to test the hypothesis that this signature associates with sensitivity to neoadjuvant immunotherapies and potentially other classes cancer therapeutics in breast cancer. Methods: Data from 1130 patients across 12 arms of I-SPY2 (control (ctr): 210; veliparib/carboplatin (VC): 71; neratinib (N): 114; MK2206: 93; ganitumab: 106; ganetespib: 93; AMG386: 134; TDM1/pertuzumab(P): 52; H/P: 44; pembrolizumab (pembro): 69; durvalumab/olaparib (durva/olap): 71; pembro/SD101: 72) were available...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="90622407"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="90622407"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 90622407; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=90622407]").text(description); $(".js-view-count[data-work-id=90622407]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 90622407; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='90622407']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 90622407, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=90622407]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":90622407,"title":"Abstract PD10-07: Chemokine12 (CK12) tertiary lymphoid gene expression signature as a predictor of response in 3 immunotherapy arms of the neoadjuvant ISPY 2 TRIAL - pembrolizumab with and without SD101, and durvalumab combined with olaparib - and in 9 other arms of the trial including platinum-b...","translated_title":"","metadata":{"abstract":"Background: The CK12 expression signature consists of genes CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11, CXCL13 and was previously shown to associate with the presence of T and B cell rich tertiary lymphoid structures in melanoma and other cancers, and with better patient survival independent of tumor staging and treatment. I-SPY 2 is a biomarker-rich, phase II neoadjuvant platform trial for high risk early stage breast cancer. Here we leverage the I-SPY 2 biomarker program to test the hypothesis that this signature associates with sensitivity to neoadjuvant immunotherapies and potentially other classes cancer therapeutics in breast cancer. Methods: Data from 1130 patients across 12 arms of I-SPY2 (control (ctr): 210; veliparib/carboplatin (VC): 71; neratinib (N): 114; MK2206: 93; ganitumab: 106; ganetespib: 93; AMG386: 134; TDM1/pertuzumab(P): 52; H/P: 44; pembrolizumab (pembro): 69; durvalumab/olaparib (durva/olap): 71; pembro/SD101: 72) were available...","publisher":"American Association for Cancer Research (AACR)","publication_date":{"day":null,"month":null,"year":2022,"errors":{}},"publication_name":"Cancer Research"},"translated_abstract":"Background: The CK12 expression signature consists of genes CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11, CXCL13 and was previously shown to associate with the presence of T and B cell rich tertiary lymphoid structures in melanoma and other cancers, and with better patient survival independent of tumor staging and treatment. I-SPY 2 is a biomarker-rich, phase II neoadjuvant platform trial for high risk early stage breast cancer. Here we leverage the I-SPY 2 biomarker program to test the hypothesis that this signature associates with sensitivity to neoadjuvant immunotherapies and potentially other classes cancer therapeutics in breast cancer. Methods: Data from 1130 patients across 12 arms of I-SPY2 (control (ctr): 210; veliparib/carboplatin (VC): 71; neratinib (N): 114; MK2206: 93; ganitumab: 106; ganetespib: 93; AMG386: 134; TDM1/pertuzumab(P): 52; H/P: 44; pembrolizumab (pembro): 69; durvalumab/olaparib (durva/olap): 71; pembro/SD101: 72) were available...","internal_url":"https://www.academia.edu/90622407/Abstract_PD10_07_Chemokine12_CK12_tertiary_lymphoid_gene_expression_signature_as_a_predictor_of_response_in_3_immunotherapy_arms_of_the_neoadjuvant_ISPY_2_TRIAL_pembrolizumab_with_and_without_SD101_and_durvalumab_combined_with_olaparib_and_in_9_other_arms_of_the_trial_including_platinum_b_","translated_internal_url":"","created_at":"2022-11-12T17:21:38.448-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_PD10_07_Chemokine12_CK12_tertiary_lymphoid_gene_expression_signature_as_a_predictor_of_response_in_3_immunotherapy_arms_of_the_neoadjuvant_ISPY_2_TRIAL_pembrolizumab_with_and_without_SD101_and_durvalumab_combined_with_olaparib_and_in_9_other_arms_of_the_trial_including_platinum_b_","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"}],"urls":[{"id":25884803,"url":"https://aacrjournals.org/cancerres/article/82/4_Supplement/PD10-07/681423/Abstract-PD10-07-Chemokine12-CK12-tertiary"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="90622406"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/90622406/Abstract_OT1_10_02_I_SPY2_endocrine_optimization_protocol_EOP_A_pilot_neoadjuvant_endocrine_therapy_study_with_amcenestrant_as_monotherapy_or_in_combination_with_abemacicilib_or_letrozole_in_molecularly_selected_HR_HER2_clinical_stage_2_3_breast_cancer"><img alt="Research paper thumbnail of Abstract OT1-10-02: I-SPY2 endocrine optimization protocol (EOP): A pilot neoadjuvant endocrine therapy study with amcenestrant as monotherapy or in combination with abemacicilib or letrozole in molecularly selected HR+/HER2- clinical stage 2/3 breast cancer" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/90622406/Abstract_OT1_10_02_I_SPY2_endocrine_optimization_protocol_EOP_A_pilot_neoadjuvant_endocrine_therapy_study_with_amcenestrant_as_monotherapy_or_in_combination_with_abemacicilib_or_letrozole_in_molecularly_selected_HR_HER2_clinical_stage_2_3_breast_cancer">Abstract OT1-10-02: I-SPY2 endocrine optimization protocol (EOP): A pilot neoadjuvant endocrine therapy study with amcenestrant as monotherapy or in combination with abemacicilib or letrozole in molecularly selected HR+/HER2- clinical stage 2/3 breast cancer</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2022</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: There is no clinical equipoise on the best upfront management of patients with early-...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: There is no clinical equipoise on the best upfront management of patients with early-stage hormone receptor-positive (HR+)/HER2-negative (HER2-) breast cancer (BC) that is high-risk by clinicopathologic criteria, and low-risk based on molecular profiling. These patients are unlikely to respond to chemotherapy. However, these patients still have risk, often risk of late recurrence, despite standard adjuvant endocrine therapy. Novel endocrine-based strategies that are more effective and tolerable than current standard therapies are needed for this population. Next-generation orally-bioavailable selective estrogen receptor degraders (oSERDs) with improved pharmacokinetic (PK) properties are promising potential therapies for HR+ BC. The oSERD amcenestrant has demonstrated a favorable safety profile and encouraging efficacy in a phase I/II dose escalation and expansion trial for heavily pre-treated patients with HR+ metastatic BC and is an attractive agent for assessment in t...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="90622406"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="90622406"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 90622406; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=90622406]").text(description); $(".js-view-count[data-work-id=90622406]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 90622406; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='90622406']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 90622406, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=90622406]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":90622406,"title":"Abstract OT1-10-02: I-SPY2 endocrine optimization protocol (EOP): A pilot neoadjuvant endocrine therapy study with amcenestrant as monotherapy or in combination with abemacicilib or letrozole in molecularly selected HR+/HER2- clinical stage 2/3 breast cancer","translated_title":"","metadata":{"abstract":"Background: There is no clinical equipoise on the best upfront management of patients with early-stage hormone receptor-positive (HR+)/HER2-negative (HER2-) breast cancer (BC) that is high-risk by clinicopathologic criteria, and low-risk based on molecular profiling. These patients are unlikely to respond to chemotherapy. However, these patients still have risk, often risk of late recurrence, despite standard adjuvant endocrine therapy. Novel endocrine-based strategies that are more effective and tolerable than current standard therapies are needed for this population. Next-generation orally-bioavailable selective estrogen receptor degraders (oSERDs) with improved pharmacokinetic (PK) properties are promising potential therapies for HR+ BC. The oSERD amcenestrant has demonstrated a favorable safety profile and encouraging efficacy in a phase I/II dose escalation and expansion trial for heavily pre-treated patients with HR+ metastatic BC and is an attractive agent for assessment in t...","publisher":"American Association for Cancer Research (AACR)","publication_date":{"day":null,"month":null,"year":2022,"errors":{}},"publication_name":"Cancer Research"},"translated_abstract":"Background: There is no clinical equipoise on the best upfront management of patients with early-stage hormone receptor-positive (HR+)/HER2-negative (HER2-) breast cancer (BC) that is high-risk by clinicopathologic criteria, and low-risk based on molecular profiling. These patients are unlikely to respond to chemotherapy. However, these patients still have risk, often risk of late recurrence, despite standard adjuvant endocrine therapy. Novel endocrine-based strategies that are more effective and tolerable than current standard therapies are needed for this population. Next-generation orally-bioavailable selective estrogen receptor degraders (oSERDs) with improved pharmacokinetic (PK) properties are promising potential therapies for HR+ BC. The oSERD amcenestrant has demonstrated a favorable safety profile and encouraging efficacy in a phase I/II dose escalation and expansion trial for heavily pre-treated patients with HR+ metastatic BC and is an attractive agent for assessment in t...","internal_url":"https://www.academia.edu/90622406/Abstract_OT1_10_02_I_SPY2_endocrine_optimization_protocol_EOP_A_pilot_neoadjuvant_endocrine_therapy_study_with_amcenestrant_as_monotherapy_or_in_combination_with_abemacicilib_or_letrozole_in_molecularly_selected_HR_HER2_clinical_stage_2_3_breast_cancer","translated_internal_url":"","created_at":"2022-11-12T17:21:38.250-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_OT1_10_02_I_SPY2_endocrine_optimization_protocol_EOP_A_pilot_neoadjuvant_endocrine_therapy_study_with_amcenestrant_as_monotherapy_or_in_combination_with_abemacicilib_or_letrozole_in_molecularly_selected_HR_HER2_clinical_stage_2_3_breast_cancer","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":64336,"name":"Population","url":"https://www.academia.edu/Documents/in/Population"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"},{"id":2011298,"name":"Letrozole","url":"https://www.academia.edu/Documents/in/Letrozole"},{"id":2530768,"name":"neoadjuvant therapy","url":"https://www.academia.edu/Documents/in/neoadjuvant_therapy"}],"urls":[{"id":25884802,"url":"https://aacrjournals.org/cancerres/article/82/4_Supplement/OT1-10-02/680171/Abstract-OT1-10-02-I-SPY2-endocrine-optimization"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="90622405"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/90622405/Clinical_trial_design_during_and_beyond_the_pandemic_the_I_SPY_COVID_trial"><img alt="Research paper thumbnail of Clinical trial design during and beyond the pandemic: the I-SPY COVID trial" class="work-thumbnail" src="https://attachments.academia-assets.com/94135121/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/90622405/Clinical_trial_design_during_and_beyond_the_pandemic_the_I_SPY_COVID_trial">Clinical trial design during and beyond the pandemic: the I-SPY COVID trial</a></div><div class="wp-workCard_item"><span>Nature Medicine</span><span>, 2022</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c1ec3843aa682d4708d7d22aa7cecb76" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":94135121,"asset_id":90622405,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/94135121/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper 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profile--work_container" data-work-id="90622404"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/90622404/Prospective_study_of_a_17_GENE_RT_PCR_based_assay_for_prediction_of_high_risk_pathology_at_radical_prostatectomy"><img alt="Research paper thumbnail of Prospective study of a 17-GENE RT-PCR-based assay for prediction of high risk pathology at radical prostatectomy" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/90622404/Prospective_study_of_a_17_GENE_RT_PCR_based_assay_for_prediction_of_high_risk_pathology_at_radical_prostatectomy">Prospective study of a 17-GENE RT-PCR-based assay for prediction of high risk pathology at radical prostatectomy</a></div><div class="wp-workCard_item"><span>Journal of Clinical Oncology</span><span>, 2017</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">36 Background: A biopsy-based 17 gene tissue-based RTPCR assay (Oncotype Dx Genomic Prostate Scor...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">36 Background: A biopsy-based 17 gene tissue-based RTPCR assay (Oncotype Dx Genomic Prostate Score, GPS) has been validated in retrospective cohorts as a predictor of adverse pathology and biochemical recurrence in prostate cancer (PCa) patients who underwent radical prostatectomy (RP). The National Comprehensive Cancer Network (NCCN) recommends that men with pathologic Gleason Score (pGS) &gt; 8, pT3+, and/or Lymph Node positive disease (i.e. high risk surgical pathology, HRSP) consider adjuvant therapy after RP. We report herein on GPS at biopsy as a predictor of HRSP in men presenting with clinically low-risk PCa. Methods: As part of an ongoing observational study of GPS (N = 1200), we performed an exploratory analysis in men who elected RP as initial disease management. Descriptive statistics were reported. Binary logistic regression was performed to determine the association between GPS and HRSP. The odds ratio (OR) per 20 GPS units and 95% confidence interval (CI) were reporte...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="90622404"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="90622404"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 90622404; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=90622404]").text(description); $(".js-view-count[data-work-id=90622404]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 90622404; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='90622404']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 90622404, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=90622404]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":90622404,"title":"Prospective study of a 17-GENE RT-PCR-based assay for prediction of high risk pathology at radical prostatectomy","translated_title":"","metadata":{"abstract":"36 Background: A biopsy-based 17 gene tissue-based RTPCR assay (Oncotype Dx Genomic Prostate Score, GPS) has been validated in retrospective cohorts as a predictor of adverse pathology and biochemical recurrence in prostate cancer (PCa) patients who underwent radical prostatectomy (RP). The National Comprehensive Cancer Network (NCCN) recommends that men with pathologic Gleason Score (pGS) \u0026gt; 8, pT3+, and/or Lymph Node positive disease (i.e. high risk surgical pathology, HRSP) consider adjuvant therapy after RP. We report herein on GPS at biopsy as a predictor of HRSP in men presenting with clinically low-risk PCa. Methods: As part of an ongoing observational study of GPS (N = 1200), we performed an exploratory analysis in men who elected RP as initial disease management. Descriptive statistics were reported. Binary logistic regression was performed to determine the association between GPS and HRSP. The odds ratio (OR) per 20 GPS units and 95% confidence interval (CI) were reporte...","publisher":"American Society of Clinical Oncology (ASCO)","publication_date":{"day":null,"month":null,"year":2017,"errors":{}},"publication_name":"Journal of Clinical Oncology"},"translated_abstract":"36 Background: A biopsy-based 17 gene tissue-based RTPCR assay (Oncotype Dx Genomic Prostate Score, GPS) has been validated in retrospective cohorts as a predictor of adverse pathology and biochemical recurrence in prostate cancer (PCa) patients who underwent radical prostatectomy (RP). The National Comprehensive Cancer Network (NCCN) recommends that men with pathologic Gleason Score (pGS) \u0026gt; 8, pT3+, and/or Lymph Node positive disease (i.e. high risk surgical pathology, HRSP) consider adjuvant therapy after RP. We report herein on GPS at biopsy as a predictor of HRSP in men presenting with clinically low-risk PCa. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="6397133" id="papers"><div class="js-work-strip profile--work_container" data-work-id="115173640"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173640/I_SPY_COVID_adaptive_platform_trial_for_COVID_19_acute_respiratory_failure_rationale_design_and_operations"><img alt="Research paper thumbnail of I-SPY COVID adaptive platform trial for COVID-19 acute respiratory failure: rationale, design and operations" class="work-thumbnail" src="https://attachments.academia-assets.com/111659564/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173640/I_SPY_COVID_adaptive_platform_trial_for_COVID_19_acute_respiratory_failure_rationale_design_and_operations">I-SPY COVID adaptive platform trial for COVID-19 acute respiratory failure: rationale, design and operations</a></div><div class="wp-workCard_item"><span>BMJ Open</span><span>, Jun 1, 2022</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5f7d4805f4c8fdda9eab320d2718c5e7" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":111659564,"asset_id":115173640,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/111659564/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173640"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173640"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173640; 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The Investigation of Serial studies to Predict Your Therapeutic Response with Imaging And moLecular Analysis (ISPY COVID-19 trial) was designed and implemented in early 2020 to evaluate investigational agents rapidly and simultaneously on a phase 2 adaptive platform. This manuscript outlines the design, rationale, implementation and challenges of the ISPY COVID-19 trial during the first phase of trial activity from April 2020 until December 2021. Methods and analysis The ISPY COVID-19 Trial is a multicentre open-label phase 2 platform trial in the USA designed to evaluate therapeutics that may have a large effect on improving outcomes from severe COVID-19. The ISPY COVID-19 Trial network includes academic and community hospitals with significant geographical diversity across the country. Enrolled patients are randomised to receive one of up to four investigational agents or a control and are evaluated for a family of two primary outcomestime to recovery and mortality. The statistical design uses a Bayesian model with 'stopping' and 'graduation' criteria designed to efficiently discard ineffective therapies and graduate promising agents for definitive efficacy trials. Each investigational agent arm enrols to a maximum of 125 patients per arm and is compared with concurrent controls. As of December 2021, 11 investigational agent arms had been activated, and 8 arms were complete. Enrolment and adaptation of the trial design are ongoing. Ethics and dissemination ISPY COVID-19 operates under a central institutional review board via Wake Forest School of Medicine IRB00066805. Data generated from this trial will be reported in peer-reviewed medical journals. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173639"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115173639/Abstract_GS5_03_Evaluation_of_anti_PD_1_Cemiplimab_plus_anti_LAG_3_REGN3767_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL"><img alt="Research paper thumbnail of Abstract GS5-03: Evaluation of anti-PD-1 Cemiplimab plus anti-LAG-3 REGN3767 in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/115173639/Abstract_GS5_03_Evaluation_of_anti_PD_1_Cemiplimab_plus_anti_LAG_3_REGN3767_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL">Abstract GS5-03: Evaluation of anti-PD-1 Cemiplimab plus anti-LAG-3 REGN3767 in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, Mar 1, 2023</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within b...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR). Cemiplimab is an anti-PD-1 inhibitor approved for the treatment of NSCLC and cutaneous basal and squamous cell CA. Lymphocyte activation gene 3 (LAG-3) binds MHC class II leading to inhibition of T-cell proliferation and activation and is often co-expressed with PD-1. REGN3767 is a fully humanized mAb that binds to LAG-3 and blocks inhibitory T-cell signaling. Concurrent blockade of LAG-3 with an anti-PD-1 may enhance efficacy of an anti-PD-1. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment; HR positive (HR+) patients had to be MP high risk. Treatment included Paclitaxel 80 mg/m2 IV weekly x 12 and Cemiplimab 350 mg and REGN3767 1600 mg both given q3weeks x 4, followed by doxorubicin/cyclophosphamide (AC) every 2 weeks x 4. The control arm was weekly paclitaxel x 12 followed by AC every 2-3 weeks x 4. Cemiplimab/REGN3767 was eligible to graduate in 3 of 10 pre-defined signatures: HER2-, HR-HER2-, and HR+HER2-. The statistical methods for evaluating I-SPY 2 agents has been previously described. To adapt to changing standard of care, we constructed “dynamic controls” comprising ‘best’ alternative therapies using I-SPY 2 and external data and estimated the probability of Cemiplimab/REGN3767 being superior to the dynamic control. Response predictive subtypes (Immune+ vs Immune-) were assessed using pre-treatment gene expression data and the ImPrint signature. Results: 73 HER2- patients (40 HR+ and 33 HR-) received Cemiplimab/REGN3767 treatment. The control group included [357 patients with HER2- tumors (201 HR+ and 156 HR-) enrolled since March 2010. Cemiplimab/REGN3767 graduated in both HR-/HER2- and HR+/HER2- groups; estimated pCR rates (as of June 2022) are summarized in the table. Safety events of note for Cemiplimab/REGN3767 include hypothyroidism 30.8%, adrenal insufficiency (AI) 19.2%, hyperthyroidism 14.1%, pneumonitis 1.3%, and hepatitis 3.8%. All were G1/2 except for 6 (7.7%) G3 AI and 3 (3.8%) G3 colitis. Rash occurred in 62.8%, 9% G3 and 2 pts (2.6%) had pulmonary embolism. X% of adrenal insufficiency cases required replacement therapy. 40 patients (11 HR+ and 29 HR-) in Cemiplimab/REGN3767 were predicted Immune+; 32 (29 HR+ and 3 HR-) were predicted Immune-. In the HR+ group pCR was achieved in 10/11 (91%) patients with Immune+ subtype compared with 8/29 (28%) with Immune- subtype. Additional biomarker analyses are ongoing and will be presented at the meeting. Conclusion: The I-SPY 2 study aims to assess the probability that investigational regimens will be successful in a phase 3 neoadjuvant trial. Dual immune blockade with a LAG-3 inhibitor and anti-PD1 therapy resulted in a high predicted pCR rate both in HR-/HER2- (60%) and HR+/HER2- (37%) disease. The novel Imprint signature identified a group of HR+ patients most likely to benefit from this active regimen. Table 1: Estimated pCR rates Citation Format: Claudine Isaacs, Rita Nanda, Jo Chien, Meghna S. Trivedi, Erica Stringer-Reasor, Christos Vaklavas, Judy C. Boughey, Amy Sanford, Anne Wallace, Amy S. Clark, Alexandra Thomas, Kathy S. Albain, Laura C. Kennedy, Tara B. Sanft, Kevin Kalinsky, Hyo S. Han, Nicole Williams, Mili Arora, Anthony Elias, Carla Falkson, Smita Asare, Ruixiao Lu, Maria Pitsouni, Amy Wilson, Jane Perlmutter, Hope Rugo, Richard Schwab, W. Fraser Symmans, Nola M. Hylton, Laura Van’t Veer, Douglas Yee, Angela DeMichele, Donald Berry, Laura J. Esserman, I-SPY Investigators. Evaluation of anti-PD-1 Cemiplimab plus anti-LAG-3 REGN3767 in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr GS5-03.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173639"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173639"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173639; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173639]").text(description); $(".js-view-count[data-work-id=115173639]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173639; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173639']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173639, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115173639]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173639,"title":"Abstract GS5-03: Evaluation of anti-PD-1 Cemiplimab plus anti-LAG-3 REGN3767 in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL","translated_title":"","metadata":{"abstract":"Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR). Cemiplimab is an anti-PD-1 inhibitor approved for the treatment of NSCLC and cutaneous basal and squamous cell CA. Lymphocyte activation gene 3 (LAG-3) binds MHC class II leading to inhibition of T-cell proliferation and activation and is often co-expressed with PD-1. REGN3767 is a fully humanized mAb that binds to LAG-3 and blocks inhibitory T-cell signaling. Concurrent blockade of LAG-3 with an anti-PD-1 may enhance efficacy of an anti-PD-1. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment; HR positive (HR+) patients had to be MP high risk. Treatment included Paclitaxel 80 mg/m2 IV weekly x 12 and Cemiplimab 350 mg and REGN3767 1600 mg both given q3weeks x 4, followed by doxorubicin/cyclophosphamide (AC) every 2 weeks x 4. The control arm was weekly paclitaxel x 12 followed by AC every 2-3 weeks x 4. Cemiplimab/REGN3767 was eligible to graduate in 3 of 10 pre-defined signatures: HER2-, HR-HER2-, and HR+HER2-. The statistical methods for evaluating I-SPY 2 agents has been previously described. To adapt to changing standard of care, we constructed “dynamic controls” comprising ‘best’ alternative therapies using I-SPY 2 and external data and estimated the probability of Cemiplimab/REGN3767 being superior to the dynamic control. Response predictive subtypes (Immune+ vs Immune-) were assessed using pre-treatment gene expression data and the ImPrint signature. Results: 73 HER2- patients (40 HR+ and 33 HR-) received Cemiplimab/REGN3767 treatment. The control group included [357 patients with HER2- tumors (201 HR+ and 156 HR-) enrolled since March 2010. Cemiplimab/REGN3767 graduated in both HR-/HER2- and HR+/HER2- groups; estimated pCR rates (as of June 2022) are summarized in the table. Safety events of note for Cemiplimab/REGN3767 include hypothyroidism 30.8%, adrenal insufficiency (AI) 19.2%, hyperthyroidism 14.1%, pneumonitis 1.3%, and hepatitis 3.8%. All were G1/2 except for 6 (7.7%) G3 AI and 3 (3.8%) G3 colitis. Rash occurred in 62.8%, 9% G3 and 2 pts (2.6%) had pulmonary embolism. X% of adrenal insufficiency cases required replacement therapy. 40 patients (11 HR+ and 29 HR-) in Cemiplimab/REGN3767 were predicted Immune+; 32 (29 HR+ and 3 HR-) were predicted Immune-. In the HR+ group pCR was achieved in 10/11 (91%) patients with Immune+ subtype compared with 8/29 (28%) with Immune- subtype. Additional biomarker analyses are ongoing and will be presented at the meeting. Conclusion: The I-SPY 2 study aims to assess the probability that investigational regimens will be successful in a phase 3 neoadjuvant trial. Dual immune blockade with a LAG-3 inhibitor and anti-PD1 therapy resulted in a high predicted pCR rate both in HR-/HER2- (60%) and HR+/HER2- (37%) disease. The novel Imprint signature identified a group of HR+ patients most likely to benefit from this active regimen. Table 1: Estimated pCR rates Citation Format: Claudine Isaacs, Rita Nanda, Jo Chien, Meghna S. Trivedi, Erica Stringer-Reasor, Christos Vaklavas, Judy C. Boughey, Amy Sanford, Anne Wallace, Amy S. Clark, Alexandra Thomas, Kathy S. Albain, Laura C. Kennedy, Tara B. Sanft, Kevin Kalinsky, Hyo S. Han, Nicole Williams, Mili Arora, Anthony Elias, Carla Falkson, Smita Asare, Ruixiao Lu, Maria Pitsouni, Amy Wilson, Jane Perlmutter, Hope Rugo, Richard Schwab, W. Fraser Symmans, Nola M. Hylton, Laura Van’t Veer, Douglas Yee, Angela DeMichele, Donald Berry, Laura J. Esserman, I-SPY Investigators. Evaluation of anti-PD-1 Cemiplimab plus anti-LAG-3 REGN3767 in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr GS5-03.","publisher":"American Association for Cancer Research","publication_date":{"day":1,"month":3,"year":2023,"errors":{}},"publication_name":"Cancer Research"},"translated_abstract":"Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR). Cemiplimab is an anti-PD-1 inhibitor approved for the treatment of NSCLC and cutaneous basal and squamous cell CA. Lymphocyte activation gene 3 (LAG-3) binds MHC class II leading to inhibition of T-cell proliferation and activation and is often co-expressed with PD-1. REGN3767 is a fully humanized mAb that binds to LAG-3 and blocks inhibitory T-cell signaling. Concurrent blockade of LAG-3 with an anti-PD-1 may enhance efficacy of an anti-PD-1. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment; HR positive (HR+) patients had to be MP high risk. Treatment included Paclitaxel 80 mg/m2 IV weekly x 12 and Cemiplimab 350 mg and REGN3767 1600 mg both given q3weeks x 4, followed by doxorubicin/cyclophosphamide (AC) every 2 weeks x 4. The control arm was weekly paclitaxel x 12 followed by AC every 2-3 weeks x 4. Cemiplimab/REGN3767 was eligible to graduate in 3 of 10 pre-defined signatures: HER2-, HR-HER2-, and HR+HER2-. The statistical methods for evaluating I-SPY 2 agents has been previously described. To adapt to changing standard of care, we constructed “dynamic controls” comprising ‘best’ alternative therapies using I-SPY 2 and external data and estimated the probability of Cemiplimab/REGN3767 being superior to the dynamic control. Response predictive subtypes (Immune+ vs Immune-) were assessed using pre-treatment gene expression data and the ImPrint signature. Results: 73 HER2- patients (40 HR+ and 33 HR-) received Cemiplimab/REGN3767 treatment. The control group included [357 patients with HER2- tumors (201 HR+ and 156 HR-) enrolled since March 2010. Cemiplimab/REGN3767 graduated in both HR-/HER2- and HR+/HER2- groups; estimated pCR rates (as of June 2022) are summarized in the table. Safety events of note for Cemiplimab/REGN3767 include hypothyroidism 30.8%, adrenal insufficiency (AI) 19.2%, hyperthyroidism 14.1%, pneumonitis 1.3%, and hepatitis 3.8%. All were G1/2 except for 6 (7.7%) G3 AI and 3 (3.8%) G3 colitis. Rash occurred in 62.8%, 9% G3 and 2 pts (2.6%) had pulmonary embolism. X% of adrenal insufficiency cases required replacement therapy. 40 patients (11 HR+ and 29 HR-) in Cemiplimab/REGN3767 were predicted Immune+; 32 (29 HR+ and 3 HR-) were predicted Immune-. In the HR+ group pCR was achieved in 10/11 (91%) patients with Immune+ subtype compared with 8/29 (28%) with Immune- subtype. Additional biomarker analyses are ongoing and will be presented at the meeting. Conclusion: The I-SPY 2 study aims to assess the probability that investigational regimens will be successful in a phase 3 neoadjuvant trial. Dual immune blockade with a LAG-3 inhibitor and anti-PD1 therapy resulted in a high predicted pCR rate both in HR-/HER2- (60%) and HR+/HER2- (37%) disease. The novel Imprint signature identified a group of HR+ patients most likely to benefit from this active regimen. Table 1: Estimated pCR rates Citation Format: Claudine Isaacs, Rita Nanda, Jo Chien, Meghna S. Trivedi, Erica Stringer-Reasor, Christos Vaklavas, Judy C. Boughey, Amy Sanford, Anne Wallace, Amy S. Clark, Alexandra Thomas, Kathy S. Albain, Laura C. Kennedy, Tara B. Sanft, Kevin Kalinsky, Hyo S. Han, Nicole Williams, Mili Arora, Anthony Elias, Carla Falkson, Smita Asare, Ruixiao Lu, Maria Pitsouni, Amy Wilson, Jane Perlmutter, Hope Rugo, Richard Schwab, W. Fraser Symmans, Nola M. Hylton, Laura Van’t Veer, Douglas Yee, Angela DeMichele, Donald Berry, Laura J. Esserman, I-SPY Investigators. Evaluation of anti-PD-1 Cemiplimab plus anti-LAG-3 REGN3767 in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr GS5-03.","internal_url":"https://www.academia.edu/115173639/Abstract_GS5_03_Evaluation_of_anti_PD_1_Cemiplimab_plus_anti_LAG_3_REGN3767_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL","translated_internal_url":"","created_at":"2024-02-20T08:16:14.980-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_GS5_03_Evaluation_of_anti_PD_1_Cemiplimab_plus_anti_LAG_3_REGN3767_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"},{"id":168351,"name":"Paclitaxel","url":"https://www.academia.edu/Documents/in/Paclitaxel"}],"urls":[{"id":39639212,"url":"https://doi.org/10.1158/1538-7445.sabcs22-gs5-03"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173638"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173638/Abstract_P5_17_03_The_12_gene_DCIS_score_assay_Impact_on_radiation_treatment_XRT_recommendations_and_clinical_utility"><img alt="Research paper thumbnail of Abstract P5-17-03: The 12-gene DCIS score assay: Impact on radiation treatment (XRT) recommendations and clinical utility" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173638/Abstract_P5_17_03_The_12_gene_DCIS_score_assay_Impact_on_radiation_treatment_XRT_recommendations_and_clinical_utility">Abstract P5-17-03: The 12-gene DCIS score assay: Impact on radiation treatment (XRT) recommendations and clinical utility</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: In the management of DCIS clinicians and patients (pts) must choose between the vario...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: In the management of DCIS clinicians and patients (pts) must choose between the various options for breast conservation treatment based on an assessment of local recurrence (LR) risk. Traditional clinicopathologic (CP) factors such as age, size, grade, margin width or comedo necrosis, provide an average LR risk derived from clinical trials and population studies. The Oncotype DX® 12-gene assay for DCIS gives individual 10-yr LR risk estimates and has now been validated in two studies in a total of 893 pts. We report the 2nd study assessing the impact of the DCIS Score result on XRT recommendations. In addition, surveys assessing pt and physician confidence will provide insight into the overall clinical utility of the DCIS Score result. Baseline characteristics including the pre-assay LR risk and XRT recommendation are described here; final results on change in XRT recommendation from pre- to post-assay and distribution of the score across the CP factors will be presented. Methods: 13 U.S. sites enrolled pts with DCIS from 3/2014-5/2015. Pts with LCIS but no DCIS, invasive BC, or planned mastectomy were excluded. Data were prospectively collected on CP factors, physician estimates of LR risk, DCIS score, and pre/post XRT recommendation. Each pt had a surgeon and radiation oncologist complete study surveys. Pt surveys were also administered pre/post assay for decision conflict and the STAIT anxiety survey. The LR risk estimates and XRT recommendations were analyzed for all physicians as well as by specialty. Descriptive statistics summarized study variables. 95% Clopper-Pearson Exact CIs were calculated for percent change in XRT recommendation. McNemar&#39;s test was used to determine if the proportion of pts had a significant change in XRT recommendation post assay. Paired t-tests were used to compare physician estimates of recurrence risk pre/post assay. Results: Of the 121 pts enrolled, median age was 61y (34-83) and 80.2% were postmenopausal. Median size was 8mm and 40% were &amp;lt; 5mm; 22.3% were grade 1, 51.2% grade 2, and 26.4% grade 3. Comedo necrosis was noted in 55.4% and 19% had multiple foci. Median margin width was 3mm and 47.1% had margins 1-3mm. ER and PR by IHC were positive in 88.4% and 75.2% of pts. Among the 242 MD risk assessments, mean 10-yr LR risk was 14.8% (range 4-50%) for any LR; 14.2% for surgeons and 15.3% for radiation oncologists. The pre-assay XRT recommendation was 70.2%; 68.6% for surgeons and 71.9% for radiation oncologists. Conclusions: The role of new molecular tools such as the DCIS Score assay that provide individual risk estimates for LR on treatment decisions is evolving. The DCIS pts enrolled in the study reveal inclusion of baseline features like higher nuclear grade (26%), comedo necrosis (55%) and margin width of 1-3mm (47%) that have historically been associated with XRT use. This represents a continued broadening of the assay use from the predominantly lower risk DCIS cohort in the 1st validation study (E5194). The impact on XRT decisions is critical to establishing the clinical utility of the assay. The decision impact analysis, differences in use of the assay among surgeons and radiation oncologists and the impact on overall confidence with the treatment decision will be presented. Citation Format: Manders JB, Kuerer HM, Smith BD, McCluskey C, Farrar WB, Frazier TG, Li L, Leonard CE, Carter DL, Chawla S, Medeiros LE, Guenther JM, Castellini LE, Buchholz DJ, Mamounas EP, Wapnir IL, Horst KC, Chagpar A, Evans SB, Riker AI, Vali FS, Solin LJ, Jablon L, Recht A, Sharma R, Lu R, Sing AP, Hwang ES, White J. The 12-gene DCIS score assay: Impact on radiation treatment (XRT) recommendations and clinical utility. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P5-17-03.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173638"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173638"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173638; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173638]").text(description); $(".js-view-count[data-work-id=115173638]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173638; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173638']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173638, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115173638]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173638,"title":"Abstract P5-17-03: The 12-gene DCIS score assay: Impact on radiation treatment (XRT) recommendations and clinical utility","translated_title":"","metadata":{"abstract":"Background: In the management of DCIS clinicians and patients (pts) must choose between the various options for breast conservation treatment based on an assessment of local recurrence (LR) risk. Traditional clinicopathologic (CP) factors such as age, size, grade, margin width or comedo necrosis, provide an average LR risk derived from clinical trials and population studies. The Oncotype DX® 12-gene assay for DCIS gives individual 10-yr LR risk estimates and has now been validated in two studies in a total of 893 pts. We report the 2nd study assessing the impact of the DCIS Score result on XRT recommendations. In addition, surveys assessing pt and physician confidence will provide insight into the overall clinical utility of the DCIS Score result. Baseline characteristics including the pre-assay LR risk and XRT recommendation are described here; final results on change in XRT recommendation from pre- to post-assay and distribution of the score across the CP factors will be presented. Methods: 13 U.S. sites enrolled pts with DCIS from 3/2014-5/2015. Pts with LCIS but no DCIS, invasive BC, or planned mastectomy were excluded. Data were prospectively collected on CP factors, physician estimates of LR risk, DCIS score, and pre/post XRT recommendation. Each pt had a surgeon and radiation oncologist complete study surveys. Pt surveys were also administered pre/post assay for decision conflict and the STAIT anxiety survey. The LR risk estimates and XRT recommendations were analyzed for all physicians as well as by specialty. Descriptive statistics summarized study variables. 95% Clopper-Pearson Exact CIs were calculated for percent change in XRT recommendation. McNemar\u0026#39;s test was used to determine if the proportion of pts had a significant change in XRT recommendation post assay. Paired t-tests were used to compare physician estimates of recurrence risk pre/post assay. Results: Of the 121 pts enrolled, median age was 61y (34-83) and 80.2% were postmenopausal. Median size was 8mm and 40% were \u0026amp;lt; 5mm; 22.3% were grade 1, 51.2% grade 2, and 26.4% grade 3. Comedo necrosis was noted in 55.4% and 19% had multiple foci. Median margin width was 3mm and 47.1% had margins 1-3mm. ER and PR by IHC were positive in 88.4% and 75.2% of pts. Among the 242 MD risk assessments, mean 10-yr LR risk was 14.8% (range 4-50%) for any LR; 14.2% for surgeons and 15.3% for radiation oncologists. The pre-assay XRT recommendation was 70.2%; 68.6% for surgeons and 71.9% for radiation oncologists. Conclusions: The role of new molecular tools such as the DCIS Score assay that provide individual risk estimates for LR on treatment decisions is evolving. The DCIS pts enrolled in the study reveal inclusion of baseline features like higher nuclear grade (26%), comedo necrosis (55%) and margin width of 1-3mm (47%) that have historically been associated with XRT use. This represents a continued broadening of the assay use from the predominantly lower risk DCIS cohort in the 1st validation study (E5194). The impact on XRT decisions is critical to establishing the clinical utility of the assay. The decision impact analysis, differences in use of the assay among surgeons and radiation oncologists and the impact on overall confidence with the treatment decision will be presented. Citation Format: Manders JB, Kuerer HM, Smith BD, McCluskey C, Farrar WB, Frazier TG, Li L, Leonard CE, Carter DL, Chawla S, Medeiros LE, Guenther JM, Castellini LE, Buchholz DJ, Mamounas EP, Wapnir IL, Horst KC, Chagpar A, Evans SB, Riker AI, Vali FS, Solin LJ, Jablon L, Recht A, Sharma R, Lu R, Sing AP, Hwang ES, White J. The 12-gene DCIS score assay: Impact on radiation treatment (XRT) recommendations and clinical utility. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P5-17-03.","publication_date":{"day":15,"month":2,"year":2016,"errors":{}}},"translated_abstract":"Background: In the management of DCIS clinicians and patients (pts) must choose between the various options for breast conservation treatment based on an assessment of local recurrence (LR) risk. Traditional clinicopathologic (CP) factors such as age, size, grade, margin width or comedo necrosis, provide an average LR risk derived from clinical trials and population studies. The Oncotype DX® 12-gene assay for DCIS gives individual 10-yr LR risk estimates and has now been validated in two studies in a total of 893 pts. We report the 2nd study assessing the impact of the DCIS Score result on XRT recommendations. In addition, surveys assessing pt and physician confidence will provide insight into the overall clinical utility of the DCIS Score result. Baseline characteristics including the pre-assay LR risk and XRT recommendation are described here; final results on change in XRT recommendation from pre- to post-assay and distribution of the score across the CP factors will be presented. Methods: 13 U.S. sites enrolled pts with DCIS from 3/2014-5/2015. Pts with LCIS but no DCIS, invasive BC, or planned mastectomy were excluded. Data were prospectively collected on CP factors, physician estimates of LR risk, DCIS score, and pre/post XRT recommendation. Each pt had a surgeon and radiation oncologist complete study surveys. Pt surveys were also administered pre/post assay for decision conflict and the STAIT anxiety survey. The LR risk estimates and XRT recommendations were analyzed for all physicians as well as by specialty. Descriptive statistics summarized study variables. 95% Clopper-Pearson Exact CIs were calculated for percent change in XRT recommendation. McNemar\u0026#39;s test was used to determine if the proportion of pts had a significant change in XRT recommendation post assay. Paired t-tests were used to compare physician estimates of recurrence risk pre/post assay. Results: Of the 121 pts enrolled, median age was 61y (34-83) and 80.2% were postmenopausal. Median size was 8mm and 40% were \u0026amp;lt; 5mm; 22.3% were grade 1, 51.2% grade 2, and 26.4% grade 3. Comedo necrosis was noted in 55.4% and 19% had multiple foci. Median margin width was 3mm and 47.1% had margins 1-3mm. ER and PR by IHC were positive in 88.4% and 75.2% of pts. Among the 242 MD risk assessments, mean 10-yr LR risk was 14.8% (range 4-50%) for any LR; 14.2% for surgeons and 15.3% for radiation oncologists. The pre-assay XRT recommendation was 70.2%; 68.6% for surgeons and 71.9% for radiation oncologists. Conclusions: The role of new molecular tools such as the DCIS Score assay that provide individual risk estimates for LR on treatment decisions is evolving. The DCIS pts enrolled in the study reveal inclusion of baseline features like higher nuclear grade (26%), comedo necrosis (55%) and margin width of 1-3mm (47%) that have historically been associated with XRT use. This represents a continued broadening of the assay use from the predominantly lower risk DCIS cohort in the 1st validation study (E5194). The impact on XRT decisions is critical to establishing the clinical utility of the assay. The decision impact analysis, differences in use of the assay among surgeons and radiation oncologists and the impact on overall confidence with the treatment decision will be presented. Citation Format: Manders JB, Kuerer HM, Smith BD, McCluskey C, Farrar WB, Frazier TG, Li L, Leonard CE, Carter DL, Chawla S, Medeiros LE, Guenther JM, Castellini LE, Buchholz DJ, Mamounas EP, Wapnir IL, Horst KC, Chagpar A, Evans SB, Riker AI, Vali FS, Solin LJ, Jablon L, Recht A, Sharma R, Lu R, Sing AP, Hwang ES, White J. The 12-gene DCIS score assay: Impact on radiation treatment (XRT) recommendations and clinical utility. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P5-17-03.","internal_url":"https://www.academia.edu/115173638/Abstract_P5_17_03_The_12_gene_DCIS_score_assay_Impact_on_radiation_treatment_XRT_recommendations_and_clinical_utility","translated_internal_url":"","created_at":"2024-02-20T08:16:14.713-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_P5_17_03_The_12_gene_DCIS_score_assay_Impact_on_radiation_treatment_XRT_recommendations_and_clinical_utility","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"}],"urls":[{"id":39639211,"url":"https://doi.org/10.1158/1538-7445.sabcs15-p5-17-03"}]}, dispatcherData: dispatcherData }); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173636"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173636/Abstract_P5_05_05_Monitoring_for_response_and_recurrence_in_neoadjuvant_treated_hormone_receptor_positive_HER2_negative_breast_cancer_by_personalized_circulating_tumor_DNA_testing"><img alt="Research paper thumbnail of Abstract P5-05-05: Monitoring for response and recurrence in neoadjuvant-treated hormone receptor-positive HER2-negative breast cancer by personalized circulating tumor DNA testing" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173636/Abstract_P5_05_05_Monitoring_for_response_and_recurrence_in_neoadjuvant_treated_hormone_receptor_positive_HER2_negative_breast_cancer_by_personalized_circulating_tumor_DNA_testing">Abstract P5-05-05: Monitoring for response and recurrence in neoadjuvant-treated hormone receptor-positive HER2-negative breast cancer by personalized circulating tumor DNA testing</a></div><div class="wp-workCard_item"><span>Cancer Research</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: The detection of circulating tumor DNA (ctDNA) may serve as an early predictor of res...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: The detection of circulating tumor DNA (ctDNA) may serve as an early predictor of response and recurrence. In this study, we used a tumor-informed ctDNA test to monitor clinical outcomes in patients with high-risk hormone receptor-positive HER2-negative (HR+HER2-) tumors who received neoadjuvant chemotherapy (NAC) on the I-SPY 2 trial (NCT01042379). Methods: We collected blood samples at pretreatment, during (at 3 and 12 weeks after initiation of paclitaxel-based treatment with or without an investigational drug), after NAC prior to surgery, 4 weeks after surgery, and annually until clinical diagnosis of recurrence. Cell-free DNA was isolated from plasma (N=329 samples) and ctDNA was detected using a personalized, tumor-informed multiplex polymerase chain reaction next generation sequencing-based test (SignateraTM). All patients were at high risk for recurrence by MammaPrint. The response endpoints were pathologic complete response (pCR) and residual cancer burden (RCB),...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173636"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173636"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173636; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173636]").text(description); $(".js-view-count[data-work-id=115173636]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173636; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173636']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173636, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115173636]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173636,"title":"Abstract P5-05-05: Monitoring for response and recurrence in neoadjuvant-treated hormone receptor-positive HER2-negative breast cancer by personalized circulating tumor DNA testing","translated_title":"","metadata":{"abstract":"Background: The detection of circulating tumor DNA (ctDNA) may serve as an early predictor of response and recurrence. In this study, we used a tumor-informed ctDNA test to monitor clinical outcomes in patients with high-risk hormone receptor-positive HER2-negative (HR+HER2-) tumors who received neoadjuvant chemotherapy (NAC) on the I-SPY 2 trial (NCT01042379). Methods: We collected blood samples at pretreatment, during (at 3 and 12 weeks after initiation of paclitaxel-based treatment with or without an investigational drug), after NAC prior to surgery, 4 weeks after surgery, and annually until clinical diagnosis of recurrence. Cell-free DNA was isolated from plasma (N=329 samples) and ctDNA was detected using a personalized, tumor-informed multiplex polymerase chain reaction next generation sequencing-based test (SignateraTM). All patients were at high risk for recurrence by MammaPrint. The response endpoints were pathologic complete response (pCR) and residual cancer burden (RCB),...","publisher":"American Association for Cancer Research (AACR)","publication_name":"Cancer Research"},"translated_abstract":"Background: The detection of circulating tumor DNA (ctDNA) may serve as an early predictor of response and recurrence. In this study, we used a tumor-informed ctDNA test to monitor clinical outcomes in patients with high-risk hormone receptor-positive HER2-negative (HR+HER2-) tumors who received neoadjuvant chemotherapy (NAC) on the I-SPY 2 trial (NCT01042379). Methods: We collected blood samples at pretreatment, during (at 3 and 12 weeks after initiation of paclitaxel-based treatment with or without an investigational drug), after NAC prior to surgery, 4 weeks after surgery, and annually until clinical diagnosis of recurrence. Cell-free DNA was isolated from plasma (N=329 samples) and ctDNA was detected using a personalized, tumor-informed multiplex polymerase chain reaction next generation sequencing-based test (SignateraTM). All patients were at high risk for recurrence by MammaPrint. The response endpoints were pathologic complete response (pCR) and residual cancer burden (RCB),...","internal_url":"https://www.academia.edu/115173636/Abstract_P5_05_05_Monitoring_for_response_and_recurrence_in_neoadjuvant_treated_hormone_receptor_positive_HER2_negative_breast_cancer_by_personalized_circulating_tumor_DNA_testing","translated_internal_url":"","created_at":"2024-02-20T08:16:14.365-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_P5_05_05_Monitoring_for_response_and_recurrence_in_neoadjuvant_treated_hormone_receptor_positive_HER2_negative_breast_cancer_by_personalized_circulating_tumor_DNA_testing","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"}],"urls":[{"id":39639210,"url":"https://aacrjournals.org/cancerres/article/83/5_Supplement/P5-05-05/717430/Abstract-P5-05-05-Monitoring-for-response-and"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173635"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173635/Validating_the_association_of_adverse_pathology_with_distant_metastasis_and_prostate_cancer_mortality_20_years_after_radical_prostatectomy"><img alt="Research paper thumbnail of Validating the association of adverse pathology with distant metastasis and prostate cancer mortality 20-years after radical prostatectomy" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173635/Validating_the_association_of_adverse_pathology_with_distant_metastasis_and_prostate_cancer_mortality_20_years_after_radical_prostatectomy">Validating the association of adverse pathology with distant metastasis and prostate cancer mortality 20-years after radical prostatectomy</a></div><div class="wp-workCard_item"><span>Urologic Oncology: Seminars and Original Investigations</span><span>, 2022</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">PURPOSE To assess the association of adverse pathology (AP), defined as high-grade (≥ Gleason Gra...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">PURPOSE To assess the association of adverse pathology (AP), defined as high-grade (≥ Gleason Grade Group 3) and/or non-organ confined disease, with long-term oncologic outcomes after radical prostatectomy (RP). MATERIALS AND METHODS Using a stratified cohort sampling design, we evaluated the association of AP with the risk of distant metastasis (DM) and prostate cancer-specific mortality (PCSM) up to 20 years after RP in 428 patients treated between 1987 to 2004. Cox regression of cause-specific hazards was used to estimate the absolute risk of both endpoints, with death from other causes treated as a competing risk. Additionally, subgroup analysis in patients with low and/or intermediate-risk disease, who are potentially eligible for active surveillance (AS), was performed. RESULTS Within the cohort sample, 53% of men exhibited AP at time of RP, with median follow up of 15.5 years (IQR 14.6-16.6 years) thereafter. Adverse pathology was highly associated with DM and PCSM in the overall cohort (HR 12.30, 95% confidence interval [CI] 5.30-28.55, and HR 10.03, 95% CI 3.42-29.47, respectively, both P &lt; 0.001). Adverse pathology was also highly associated with DM and PCSM in the low/intermediate-risk subgroup (HR 10.48, 95% CI 4.18-26.28, and 8.60, 95% CI 2.40-30.48, respectively, both P &lt; 0.001). CONCLUSIONS Adverse pathology at the time of RP is highly associated with future development of DM and PCSM. Accurate prediction of AP may thus be useful for individualizing risk-based surveillance and treatment strategies.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173635"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173635"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173635; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173635]").text(description); $(".js-view-count[data-work-id=115173635]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173635; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173635']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173635, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115173635]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173635,"title":"Validating the association of adverse pathology with distant metastasis and prostate cancer mortality 20-years after radical prostatectomy","translated_title":"","metadata":{"abstract":"PURPOSE To assess the association of adverse pathology (AP), defined as high-grade (≥ Gleason Grade Group 3) and/or non-organ confined disease, with long-term oncologic outcomes after radical prostatectomy (RP). MATERIALS AND METHODS Using a stratified cohort sampling design, we evaluated the association of AP with the risk of distant metastasis (DM) and prostate cancer-specific mortality (PCSM) up to 20 years after RP in 428 patients treated between 1987 to 2004. Cox regression of cause-specific hazards was used to estimate the absolute risk of both endpoints, with death from other causes treated as a competing risk. Additionally, subgroup analysis in patients with low and/or intermediate-risk disease, who are potentially eligible for active surveillance (AS), was performed. RESULTS Within the cohort sample, 53% of men exhibited AP at time of RP, with median follow up of 15.5 years (IQR 14.6-16.6 years) thereafter. Adverse pathology was highly associated with DM and PCSM in the overall cohort (HR 12.30, 95% confidence interval [CI] 5.30-28.55, and HR 10.03, 95% CI 3.42-29.47, respectively, both P \u0026lt; 0.001). Adverse pathology was also highly associated with DM and PCSM in the low/intermediate-risk subgroup (HR 10.48, 95% CI 4.18-26.28, and 8.60, 95% CI 2.40-30.48, respectively, both P \u0026lt; 0.001). CONCLUSIONS Adverse pathology at the time of RP is highly associated with future development of DM and PCSM. Accurate prediction of AP may thus be useful for individualizing risk-based surveillance and treatment strategies.","publisher":"Elsevier BV","publication_date":{"day":null,"month":null,"year":2022,"errors":{}},"publication_name":"Urologic Oncology: Seminars and Original Investigations"},"translated_abstract":"PURPOSE To assess the association of adverse pathology (AP), defined as high-grade (≥ Gleason Grade Group 3) and/or non-organ confined disease, with long-term oncologic outcomes after radical prostatectomy (RP). MATERIALS AND METHODS Using a stratified cohort sampling design, we evaluated the association of AP with the risk of distant metastasis (DM) and prostate cancer-specific mortality (PCSM) up to 20 years after RP in 428 patients treated between 1987 to 2004. Cox regression of cause-specific hazards was used to estimate the absolute risk of both endpoints, with death from other causes treated as a competing risk. Additionally, subgroup analysis in patients with low and/or intermediate-risk disease, who are potentially eligible for active surveillance (AS), was performed. RESULTS Within the cohort sample, 53% of men exhibited AP at time of RP, with median follow up of 15.5 years (IQR 14.6-16.6 years) thereafter. Adverse pathology was highly associated with DM and PCSM in the overall cohort (HR 12.30, 95% confidence interval [CI] 5.30-28.55, and HR 10.03, 95% CI 3.42-29.47, respectively, both P \u0026lt; 0.001). Adverse pathology was also highly associated with DM and PCSM in the low/intermediate-risk subgroup (HR 10.48, 95% CI 4.18-26.28, and 8.60, 95% CI 2.40-30.48, respectively, both P \u0026lt; 0.001). CONCLUSIONS Adverse pathology at the time of RP is highly associated with future development of DM and PCSM. Accurate prediction of AP may thus be useful for individualizing risk-based surveillance and treatment strategies.","internal_url":"https://www.academia.edu/115173635/Validating_the_association_of_adverse_pathology_with_distant_metastasis_and_prostate_cancer_mortality_20_years_after_radical_prostatectomy","translated_internal_url":"","created_at":"2024-02-20T08:16:13.999-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Validating_the_association_of_adverse_pathology_with_distant_metastasis_and_prostate_cancer_mortality_20_years_after_radical_prostatectomy","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":12980,"name":"Prostate Cancer","url":"https://www.academia.edu/Documents/in/Prostate_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"},{"id":190203,"name":"Cohort","url":"https://www.academia.edu/Documents/in/Cohort"},{"id":418283,"name":"Proportional hazards model","url":"https://www.academia.edu/Documents/in/Proportional_hazards_model"},{"id":2601211,"name":"Adverse effect","url":"https://www.academia.edu/Documents/in/Adverse_effect"},{"id":2943946,"name":"Urologic Oncology","url":"https://www.academia.edu/Documents/in/Urologic_Oncology"},{"id":3382526,"name":"Prostatectomy","url":"https://www.academia.edu/Documents/in/Prostatectomy"}],"urls":[{"id":39639209,"url":"https://api.elsevier.com/content/article/PII:S1078143921004737?httpAccept=text/xml"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173634"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173634/Adverse_pathology_at_radical_prostatectomy_GPS_test_and_clinical_pathology_features_as_predictors_of_long_term_prostate_cancer_outcomes"><img alt="Research paper thumbnail of Adverse pathology at radical prostatectomy, GPS™ test, and clinical/pathology features as predictors of long-term prostate cancer outcomes" class="work-thumbnail" src="https://attachments.academia-assets.com/111659597/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173634/Adverse_pathology_at_radical_prostatectomy_GPS_test_and_clinical_pathology_features_as_predictors_of_long_term_prostate_cancer_outcomes">Adverse pathology at radical prostatectomy, GPS™ test, and clinical/pathology features as predictors of long-term prostate cancer outcomes</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="7b16e2bc7447241eb6e1c75eedb28190" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":111659597,"asset_id":115173634,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/111659597/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173634"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173634"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173634; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "7b16e2bc7447241eb6e1c75eedb28190" } } $('.js-work-strip[data-work-id=115173634]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173634,"title":"Adverse pathology at radical prostatectomy, GPS™ test, and clinical/pathology features as predictors of long-term prostate cancer outcomes","translated_title":"","metadata":{"grobid_abstract":"Introduction \u0026 Objectives: Evaluate the association of adverse pathology (AP) in radical prostatectomy (RP) tissue with 20-year risk of clinical recurrence (CR), distant metastasis (DM) and prostate cancer mortality (PCM). Explore associations of the Oncotype DX Genomic Prostate Score® (GPS™) test, grade, stage and PSA level with long-term outcomes of CR, DM, and PCM. Materials \u0026 Methods: Long term follow-up of 2641 clinical stage T1/T2 prostate cancer (PCa) patients treated with RP at the Cleveland Clinic from 1987-2004 was obtained from an IRB-approved prospectively maintained database. Using cohort sampling, 428 patients were selected with CR and no CR in 1:3 ratio. AP (pT3 or higher or primary Gleason pattern ≥4 or any pattern 5), was assessed using the 2005 International Society of Urological Pathology guidelines. Times from surgery to CR (DM or local recurrence), DM and PCM were analyzed using a weighted Cox model. The absolute risk of these outcomes over 20 years after surgery was evaluated using Cox regression of cause-specific hazards treating death due to non-PCa causes as a competing risk. Since the GPS test was developed using this cohort, GPS hazard ratios were corrected for regression to the mean (RM) and false discovery rates (FDR) were reported. Results: Median follow up was 15.5 years. Most patients had AUA low (55%) or intermediate risk (35%) disease. At RP, 52.8% of patients had AP. AP was strongly associated with DM (hazard ratio (HR) and 95% Confidence Interval 12.30 (5.30, 28.55), p\u003c.001) and PCM (HR 10.03 (3.42, 29.47), p\u003c.001). AP was also strongly associated with CR, but the strength of association appeared to change over time (0-10 years, HR 9.01 (4.01, 20.25), p\u003c.001; after 10 years, HR 1.85 (0.39, 8.71), p=.44). Results with AUA low and intermediate risk PCa were similar. GPS result appeared associated with long-term outcomes (RM-corrected HR (95% Confidence Interval) per 20 units for DM 3.67 (2.34, 6.27), FDR \u003c.01), as did log2","publication_date":{"day":null,"month":null,"year":2020,"errors":{}},"grobid_abstract_attachment_id":111659597},"translated_abstract":null,"internal_url":"https://www.academia.edu/115173634/Adverse_pathology_at_radical_prostatectomy_GPS_test_and_clinical_pathology_features_as_predictors_of_long_term_prostate_cancer_outcomes","translated_internal_url":"","created_at":"2024-02-20T08:16:13.846-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":111659597,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/111659597/thumbnails/1.jpg","file_name":"main.pdf","download_url":"https://www.academia.edu/attachments/111659597/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Adverse_pathology_at_radical_prostatecto.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/111659597/main-libre.pdf?1708457080=\u0026response-content-disposition=attachment%3B+filename%3DAdverse_pathology_at_radical_prostatecto.pdf\u0026Expires=1732512681\u0026Signature=dIFbOQ5wuLCLwRL47Gr6bUKRGXOHPxLJq~~ZrGGW0CqiRKPbl-a3Omlbyth5182XAeUjn8DhIJdAeu5JaVi2mebst3x2NcEk3vQ9nMf9Iyn0ShTNihfFtp-HeEnicFMR9nG-Fw4mpr6bNypZRV1X3qNXzsyxYBEzRMcBxGs-YeC2TuxrSUmqJbt0VLEGJrq8TCenbDC2XvDn3BoyHWH-6GXxF85Kl6q4ovvFEucudKhQh~8lfw-OFza~gN9hi~3pdKRi0sjC~Wux4k7TKL0r5L3Uuq1MJogKzscaKRtxgaw8gR1rRcXUCg~fJo2rf4VpmFEjqERkIiODbyxsoLqIwQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Adverse_pathology_at_radical_prostatectomy_GPS_test_and_clinical_pathology_features_as_predictors_of_long_term_prostate_cancer_outcomes","translated_slug":"","page_count":1,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[{"id":111659597,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/111659597/thumbnails/1.jpg","file_name":"main.pdf","download_url":"https://www.academia.edu/attachments/111659597/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Adverse_pathology_at_radical_prostatecto.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/111659597/main-libre.pdf?1708457080=\u0026response-content-disposition=attachment%3B+filename%3DAdverse_pathology_at_radical_prostatecto.pdf\u0026Expires=1732512681\u0026Signature=dIFbOQ5wuLCLwRL47Gr6bUKRGXOHPxLJq~~ZrGGW0CqiRKPbl-a3Omlbyth5182XAeUjn8DhIJdAeu5JaVi2mebst3x2NcEk3vQ9nMf9Iyn0ShTNihfFtp-HeEnicFMR9nG-Fw4mpr6bNypZRV1X3qNXzsyxYBEzRMcBxGs-YeC2TuxrSUmqJbt0VLEGJrq8TCenbDC2XvDn3BoyHWH-6GXxF85Kl6q4ovvFEucudKhQh~8lfw-OFza~gN9hi~3pdKRi0sjC~Wux4k7TKL0r5L3Uuq1MJogKzscaKRtxgaw8gR1rRcXUCg~fJo2rf4VpmFEjqERkIiODbyxsoLqIwQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":12980,"name":"Prostate Cancer","url":"https://www.academia.edu/Documents/in/Prostate_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":3382526,"name":"Prostatectomy","url":"https://www.academia.edu/Documents/in/Prostatectomy"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173633"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173633/Abstract_P4_15_09_Refined_estimates_of_local_recurrence_risk_in_a_clinical_utility_study_Integrating_the_DCIS_score_patient_age_and_DCIS_tumor_size"><img alt="Research paper thumbnail of Abstract P4-15-09: Refined estimates of local recurrence risk in a clinical utility study: Integrating the DCIS score, patient age and DCIS tumor size" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173633/Abstract_P4_15_09_Refined_estimates_of_local_recurrence_risk_in_a_clinical_utility_study_Integrating_the_DCIS_score_patient_age_and_DCIS_tumor_size">Abstract P4-15-09: Refined estimates of local recurrence risk in a clinical utility study: Integrating the DCIS score, patient age and DCIS tumor size</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background:Better tools are needed to estimate the risk of local recurrence (LR; DCIS or invasive...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background:Better tools are needed to estimate the risk of local recurrence (LR; DCIS or invasive) after breast-conserving surgery (BCS) for pts with DCIS in order to inform treatment decisions. Traditional clinico-pathologic (CP) factors, e.g., age and tumor size, provide an average LR risk derived from clinical trials and population studies. The Oncotype DX 12-gene DCIS Score assay has been validated to provide individual 10 yr LR risk estimates (Solin JNCI 2013; Rakovitch BCRT 2015). Previously we reported the impact of the DCIS Score result on radiotherapy (RT) recommendations including the pre-assay LR risk and RT recommendation and the change in RT recommendation from pre- to post-assay (Manders Ann Surg Oncol 2016).Recently a patient specific meta-analysis (MA) combined data from E5194 and Ontario DCIS Cohort (ODC) adjusting for pertinent clinico-pathologic factors to provide refined prediction estimates of LR risk after BCS alone (Rakovitch ASCO 2017). Herein we applied thes...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173633"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173633"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173633; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173633]").text(description); $(".js-view-count[data-work-id=115173633]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173633; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173633']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173633, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115173633]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173633,"title":"Abstract P4-15-09: Refined estimates of local recurrence risk in a clinical utility study: Integrating the DCIS score, patient age and DCIS tumor size","translated_title":"","metadata":{"abstract":"Background:Better tools are needed to estimate the risk of local recurrence (LR; DCIS or invasive) after breast-conserving surgery (BCS) for pts with DCIS in order to inform treatment decisions. Traditional clinico-pathologic (CP) factors, e.g., age and tumor size, provide an average LR risk derived from clinical trials and population studies. The Oncotype DX 12-gene DCIS Score assay has been validated to provide individual 10 yr LR risk estimates (Solin JNCI 2013; Rakovitch BCRT 2015). Previously we reported the impact of the DCIS Score result on radiotherapy (RT) recommendations including the pre-assay LR risk and RT recommendation and the change in RT recommendation from pre- to post-assay (Manders Ann Surg Oncol 2016).Recently a patient specific meta-analysis (MA) combined data from E5194 and Ontario DCIS Cohort (ODC) adjusting for pertinent clinico-pathologic factors to provide refined prediction estimates of LR risk after BCS alone (Rakovitch ASCO 2017). Herein we applied thes...","publisher":"American Association for Cancer Research (AACR)","publication_date":{"day":null,"month":null,"year":2018,"errors":{}},"publication_name":"Cancer Research"},"translated_abstract":"Background:Better tools are needed to estimate the risk of local recurrence (LR; DCIS or invasive) after breast-conserving surgery (BCS) for pts with DCIS in order to inform treatment decisions. Traditional clinico-pathologic (CP) factors, e.g., age and tumor size, provide an average LR risk derived from clinical trials and population studies. The Oncotype DX 12-gene DCIS Score assay has been validated to provide individual 10 yr LR risk estimates (Solin JNCI 2013; Rakovitch BCRT 2015). Previously we reported the impact of the DCIS Score result on radiotherapy (RT) recommendations including the pre-assay LR risk and RT recommendation and the change in RT recommendation from pre- to post-assay (Manders Ann Surg Oncol 2016).Recently a patient specific meta-analysis (MA) combined data from E5194 and Ontario DCIS Cohort (ODC) adjusting for pertinent clinico-pathologic factors to provide refined prediction estimates of LR risk after BCS alone (Rakovitch ASCO 2017). Herein we applied thes...","internal_url":"https://www.academia.edu/115173633/Abstract_P4_15_09_Refined_estimates_of_local_recurrence_risk_in_a_clinical_utility_study_Integrating_the_DCIS_score_patient_age_and_DCIS_tumor_size","translated_internal_url":"","created_at":"2024-02-20T08:16:13.591-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_P4_15_09_Refined_estimates_of_local_recurrence_risk_in_a_clinical_utility_study_Integrating_the_DCIS_score_patient_age_and_DCIS_tumor_size","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":64336,"name":"Population","url":"https://www.academia.edu/Documents/in/Population"},{"id":231720,"name":"Mastectomy","url":"https://www.academia.edu/Documents/in/Mastectomy"}],"urls":[{"id":39639208,"url":"https://aacrjournals.org/cancerres/article/78/4_Supplement/P4-15-09/542070/Abstract-P4-15-09-Refined-estimates-of-local"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173632"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173632/Recurrence_score_distributions_in_stage_II_colon_cancers_of_African_American_AA_and_Caucasian_CA_patients"><img alt="Research paper thumbnail of Recurrence score distributions in stage II colon cancers of African American (AA) and Caucasian (CA) patients" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173632/Recurrence_score_distributions_in_stage_II_colon_cancers_of_African_American_AA_and_Caucasian_CA_patients">Recurrence score distributions in stage II colon cancers of African American (AA) and Caucasian (CA) patients</a></div><div class="wp-workCard_item"><span>Journal of Clinical Oncology</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">613 Background: The 12-gene colon cancer assay (Oncotype DX) can identify groups of stage II colo...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">613 Background: The 12-gene colon cancer assay (Oncotype DX) can identify groups of stage II colon cancer patients with lower or higher recurrence risk, but distribution of scores based on race/ethnicity has not been assessed. This study compared the distribution of Recurrence Score results and gene expression profiles between African American (AA) and Caucasian (CA) stage II colon cancer patients. Methods: Stage II colon cancer patients were identified from tumor registry data from four institutions: University of Arkansas for Medical Sciences, Little Rock; Veterans Administration Medical Center, Little Rock; Baptist Medical Center, Memphis, and University of Alabama at Birmingham. The 12-gene assay and mismatch repair (MMR) status were performed on formalin-fixed paraffin-embedded tissues by Genomic Health (Redwood City, CA). T-test and Wilcoxon test were used to compare data from the two groups (SAS Enterprise Guide 5.1). Results: Of the 244 subjects, there were 118 women (63 AA,...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173632"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173632"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173632; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173632]").text(description); $(".js-view-count[data-work-id=115173632]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173632; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173632']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173632, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115173632]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173632,"title":"Recurrence score distributions in stage II colon cancers of African American (AA) and Caucasian (CA) patients","translated_title":"","metadata":{"abstract":"613 Background: The 12-gene colon cancer assay (Oncotype DX) can identify groups of stage II colon cancer patients with lower or higher recurrence risk, but distribution of scores based on race/ethnicity has not been assessed. This study compared the distribution of Recurrence Score results and gene expression profiles between African American (AA) and Caucasian (CA) stage II colon cancer patients. Methods: Stage II colon cancer patients were identified from tumor registry data from four institutions: University of Arkansas for Medical Sciences, Little Rock; Veterans Administration Medical Center, Little Rock; Baptist Medical Center, Memphis, and University of Alabama at Birmingham. The 12-gene assay and mismatch repair (MMR) status were performed on formalin-fixed paraffin-embedded tissues by Genomic Health (Redwood City, CA). T-test and Wilcoxon test were used to compare data from the two groups (SAS Enterprise Guide 5.1). Results: Of the 244 subjects, there were 118 women (63 AA,...","publisher":"American Society of Clinical Oncology (ASCO)","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"Journal of Clinical Oncology"},"translated_abstract":"613 Background: The 12-gene colon cancer assay (Oncotype DX) can identify groups of stage II colon cancer patients with lower or higher recurrence risk, but distribution of scores based on race/ethnicity has not been assessed. This study compared the distribution of Recurrence Score results and gene expression profiles between African American (AA) and Caucasian (CA) stage II colon cancer patients. Methods: Stage II colon cancer patients were identified from tumor registry data from four institutions: University of Arkansas for Medical Sciences, Little Rock; Veterans Administration Medical Center, Little Rock; Baptist Medical Center, Memphis, and University of Alabama at Birmingham. The 12-gene assay and mismatch repair (MMR) status were performed on formalin-fixed paraffin-embedded tissues by Genomic Health (Redwood City, CA). T-test and Wilcoxon test were used to compare data from the two groups (SAS Enterprise Guide 5.1). Results: Of the 244 subjects, there were 118 women (63 AA,...","internal_url":"https://www.academia.edu/115173632/Recurrence_score_distributions_in_stage_II_colon_cancers_of_African_American_AA_and_Caucasian_CA_patients","translated_internal_url":"","created_at":"2024-02-20T08:16:13.399-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Recurrence_score_distributions_in_stage_II_colon_cancers_of_African_American_AA_and_Caucasian_CA_patients","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":37292,"name":"Colorectal cancer","url":"https://www.academia.edu/Documents/in/Colorectal_cancer"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"},{"id":115895,"name":"Clinical oncology","url":"https://www.academia.edu/Documents/in/Clinical_oncology"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173631"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/115173631/Assessing_probe_specific_dye_and_slide_biases_in_two_color_microarray_data"><img alt="Research paper thumbnail of Assessing probe-specific dye and slide biases in two-color microarray data" class="work-thumbnail" src="https://attachments.academia-assets.com/111659561/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/115173631/Assessing_probe_specific_dye_and_slide_biases_in_two_color_microarray_data">Assessing probe-specific dye and slide biases in two-color microarray data</a></div><div class="wp-workCard_item"><span>BMC Bioinformatics</span><span>, 2008</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background A primary reason for using two-color microarrays is that the use of two samples labele...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background A primary reason for using two-color microarrays is that the use of two samples labeled with different dyes on the same slide, that bind to probes on the same spot, is supposed to adjust for many factors that introduce noise and errors into the analysis. Most users assume that any differences between the dyes can be adjusted out by standard methods of normalization, so that measures such as log ratios on the same slide are reliable measures of comparative expression. However, even after the normalization, there are still probe specific dye and slide variation among the data. We define a method to quantify the amount of the dye-by-probe and slide-by-probe interaction. This serves as a diagnostic, both visual and numeric, of the existence of probe-specific dye bias. We show how this improved the performance of two-color array analysis for arrays for genomic analysis of biological samples ranging from rice to human tissue. Results We develop a procedure for quantifying the e...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="07cc69f797dc82c5bd29810287a07fca" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":111659561,"asset_id":115173631,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/111659561/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173631"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173631"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173631; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173631]").text(description); $(".js-view-count[data-work-id=115173631]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173631; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173631']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173631, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "07cc69f797dc82c5bd29810287a07fca" } } $('.js-work-strip[data-work-id=115173631]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173631,"title":"Assessing probe-specific dye and slide biases in two-color microarray data","translated_title":"","metadata":{"abstract":"Background A primary reason for using two-color microarrays is that the use of two samples labeled with different dyes on the same slide, that bind to probes on the same spot, is supposed to adjust for many factors that introduce noise and errors into the analysis. Most users assume that any differences between the dyes can be adjusted out by standard methods of normalization, so that measures such as log ratios on the same slide are reliable measures of comparative expression. However, even after the normalization, there are still probe specific dye and slide variation among the data. We define a method to quantify the amount of the dye-by-probe and slide-by-probe interaction. This serves as a diagnostic, both visual and numeric, of the existence of probe-specific dye bias. We show how this improved the performance of two-color array analysis for arrays for genomic analysis of biological samples ranging from rice to human tissue. Results We develop a procedure for quantifying the e...","publisher":"Springer Science and Business Media LLC","publication_date":{"day":null,"month":null,"year":2008,"errors":{}},"publication_name":"BMC Bioinformatics"},"translated_abstract":"Background A primary reason for using two-color microarrays is that the use of two samples labeled with different dyes on the same slide, that bind to probes on the same spot, is supposed to adjust for many factors that introduce noise and errors into the analysis. Most users assume that any differences between the dyes can be adjusted out by standard methods of normalization, so that measures such as log ratios on the same slide are reliable measures of comparative expression. However, even after the normalization, there are still probe specific dye and slide variation among the data. We define a method to quantify the amount of the dye-by-probe and slide-by-probe interaction. This serves as a diagnostic, both visual and numeric, of the existence of probe-specific dye bias. We show how this improved the performance of two-color array analysis for arrays for genomic analysis of biological samples ranging from rice to human tissue. Results We develop a procedure for quantifying the e...","internal_url":"https://www.academia.edu/115173631/Assessing_probe_specific_dye_and_slide_biases_in_two_color_microarray_data","translated_internal_url":"","created_at":"2024-02-20T08:16:13.174-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":111659561,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/111659561/thumbnails/1.jpg","file_name":"1471-2105-9-314.pdf","download_url":"https://www.academia.edu/attachments/111659561/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Assessing_probe_specific_dye_and_slide_b.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/111659561/1471-2105-9-314-libre.pdf?1708457094=\u0026response-content-disposition=attachment%3B+filename%3DAssessing_probe_specific_dye_and_slide_b.pdf\u0026Expires=1732512681\u0026Signature=GUmX6fsfoHfMczQiGOjEg~ZKtT98Q1oB9AJBVKJ~dgKZtZLdlVGwaDMuSBTWlEwGn1nNxr79~eJJnF1Xrcp3khWzYPBSUdEd-~tRYDJS4cXGXfDqF4V4VI~I5FvpmuPtOWbhNiRVMpcKiWZDeUKXXu6ukT3qHqHi50io9kTZQ7XC7wMhsaIcGVUzOS9jX38QS-v9MKXC7om3uHqGqO2zMPpuGFL1JcHsy8xtxBDK1pHrXuO59p6XuSjaHA9APvQz1S21SH6763nyEIf45fywCE8aKQtX1qJdroXzqMK~IpyVqajdOi-dkmYZkDYjZzcJv4d1e41s9sr2Y8vNSxcSHQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Assessing_probe_specific_dye_and_slide_biases_in_two_color_microarray_data","translated_slug":"","page_count":8,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao 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$a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115173618"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115173618/The_I_SPY_COVID_Trial_First_Results_from_an_Adaptive_Platform_Phase_2_Trial_for_Severe_COVID_19"><img alt="Research paper thumbnail of The I-SPY COVID Trial: First Results from an Adaptive Platform Phase 2 Trial for Severe COVID-19" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/115173618/The_I_SPY_COVID_Trial_First_Results_from_an_Adaptive_Platform_Phase_2_Trial_for_Severe_COVID_19">The I-SPY COVID Trial: First Results from an Adaptive Platform Phase 2 Trial for Severe COVID-19</a></div><div class="wp-workCard_item"><span>D94. PANDEMIC OUTPUT: ALL THAT IS COVID-19</span><span>, May 1, 2022</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115173618"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115173618"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115173618; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115173618]").text(description); $(".js-view-count[data-work-id=115173618]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115173618; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115173618']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 115173618, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115173618]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115173618,"title":"The I-SPY COVID Trial: First Results from an Adaptive Platform Phase 2 Trial for Severe COVID-19","translated_title":"","metadata":{"publication_date":{"day":1,"month":5,"year":2022,"errors":{}},"publication_name":"D94. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="105817430"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/105817430/Abstract_PD8_07_Evaluation_of_Tucatinib_Paclitaxel_Pertuzumab_Trastuzumab_followed_by_AC_in_high_risk_HER2_positive_HER2_stage_II_III_breast_cancer_Results_from_the_I_SPY_2_TRIAL"><img alt="Research paper thumbnail of Abstract PD8-07: Evaluation of Tucatinib + (Paclitaxel + Pertuzumab + Trastuzumab) followed by AC in high-risk HER2 positive (HER2+) stage II/III breast cancer: Results from the I-SPY 2 TRIAL" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/105817430/Abstract_PD8_07_Evaluation_of_Tucatinib_Paclitaxel_Pertuzumab_Trastuzumab_followed_by_AC_in_high_risk_HER2_positive_HER2_stage_II_III_breast_cancer_Results_from_the_I_SPY_2_TRIAL">Abstract PD8-07: Evaluation of Tucatinib + (Paclitaxel + Pertuzumab + Trastuzumab) followed by AC in high-risk HER2 positive (HER2+) stage II/III breast cancer: Results from the I-SPY 2 TRIAL</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2022</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: I-SPY 2 is a multicenter, phase 2 trial using response-adaptive randomization within ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: I-SPY 2 is a multicenter, phase 2 trial using response-adaptive randomization within molecular subtypes defined by receptor status and MammaPrint (MP) risk to evaluate novel agents as neoadjuvant therapy for women with high-risk breast cancer. Tucatinib is a potent HER2 (ErbB2) tyrosine kinase inhibitor, selective for HER2 vs. epidermal growth factor receptor (EGFR) and is active vs. brain metastases. Safety and efficacy of tucatinib combined with paclitaxel, pertuzumab, and trastuzumab are unknown and were tested in a planned 10 patient (pt) safety run-in of the I-SPY 2 trial. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only pts with tumors that were HER2+ by FISH were eligible for this treatment. Treatment included tucatinib (max dose 300 mg) BID for 12 weeks with weekly paclitaxel 80 mg/m2 and trastuzumab (2 mg/kg weekly following loading), and pertuzumab (420 mg every 3 weeks following loading), followed by doxorubicin/cyclophosphamide (AC) every ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="105817430"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="105817430"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 105817430; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=105817430]").text(description); $(".js-view-count[data-work-id=105817430]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 105817430; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='105817430']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 105817430, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=105817430]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":105817430,"title":"Abstract PD8-07: Evaluation of Tucatinib + (Paclitaxel + Pertuzumab + Trastuzumab) followed by AC in high-risk HER2 positive (HER2+) stage II/III breast cancer: Results from the I-SPY 2 TRIAL","translated_title":"","metadata":{"abstract":"Background: I-SPY 2 is a multicenter, phase 2 trial using response-adaptive randomization within molecular subtypes defined by receptor status and MammaPrint (MP) risk to evaluate novel agents as neoadjuvant therapy for women with high-risk breast cancer. Tucatinib is a potent HER2 (ErbB2) tyrosine kinase inhibitor, selective for HER2 vs. epidermal growth factor receptor (EGFR) and is active vs. brain metastases. Safety and efficacy of tucatinib combined with paclitaxel, pertuzumab, and trastuzumab are unknown and were tested in a planned 10 patient (pt) safety run-in of the I-SPY 2 trial. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only pts with tumors that were HER2+ by FISH were eligible for this treatment. Treatment included tucatinib (max dose 300 mg) BID for 12 weeks with weekly paclitaxel 80 mg/m2 and trastuzumab (2 mg/kg weekly following loading), and pertuzumab (420 mg every 3 weeks following loading), followed by doxorubicin/cyclophosphamide (AC) every ...","publisher":"American Association for Cancer Research (AACR)","publication_date":{"day":null,"month":null,"year":2022,"errors":{}},"publication_name":"Cancer Research"},"translated_abstract":"Background: I-SPY 2 is a multicenter, phase 2 trial using response-adaptive randomization within molecular subtypes defined by receptor status and MammaPrint (MP) risk to evaluate novel agents as neoadjuvant therapy for women with high-risk breast cancer. Tucatinib is a potent HER2 (ErbB2) tyrosine kinase inhibitor, selective for HER2 vs. epidermal growth factor receptor (EGFR) and is active vs. brain metastases. Safety and efficacy of tucatinib combined with paclitaxel, pertuzumab, and trastuzumab are unknown and were tested in a planned 10 patient (pt) safety run-in of the I-SPY 2 trial. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only pts with tumors that were HER2+ by FISH were eligible for this treatment. Treatment included tucatinib (max dose 300 mg) BID for 12 weeks with weekly paclitaxel 80 mg/m2 and trastuzumab (2 mg/kg weekly following loading), and pertuzumab (420 mg every 3 weeks following loading), followed by doxorubicin/cyclophosphamide (AC) every ...","internal_url":"https://www.academia.edu/105817430/Abstract_PD8_07_Evaluation_of_Tucatinib_Paclitaxel_Pertuzumab_Trastuzumab_followed_by_AC_in_high_risk_HER2_positive_HER2_stage_II_III_breast_cancer_Results_from_the_I_SPY_2_TRIAL","translated_internal_url":"","created_at":"2023-08-21T09:09:55.626-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_PD8_07_Evaluation_of_Tucatinib_Paclitaxel_Pertuzumab_Trastuzumab_followed_by_AC_in_high_risk_HER2_positive_HER2_stage_II_III_breast_cancer_Results_from_the_I_SPY_2_TRIAL","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"},{"id":168351,"name":"Paclitaxel","url":"https://www.academia.edu/Documents/in/Paclitaxel"},{"id":983616,"name":"Trastuzumab","url":"https://www.academia.edu/Documents/in/Trastuzumab"}],"urls":[{"id":33542138,"url":"https://aacrjournals.org/cancerres/article/82/4_Supplement/PD8-07/681476/Abstract-PD8-07-Evaluation-of-Tucatinib-Paclitaxel"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="105817429"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/105817429/Abstract_P5_13_12_Immune_signatures_and_MammaPrint_ultra_high_risk_class_MP2_as_predictors_of_response_to_pembrolizumab_combined_with_the_TLR9_agonist_SD101_in_the_neoadjuvant_I_SPY_2_TRIAL"><img alt="Research paper thumbnail of Abstract P5-13-12: Immune signatures and MammaPrint (ultra) high risk class (MP2) as predictors of response to pembrolizumab combined with the TLR9 agonist SD101 in the neoadjuvant I-SPY 2 TRIAL" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/105817429/Abstract_P5_13_12_Immune_signatures_and_MammaPrint_ultra_high_risk_class_MP2_as_predictors_of_response_to_pembrolizumab_combined_with_the_TLR9_agonist_SD101_in_the_neoadjuvant_I_SPY_2_TRIAL">Abstract P5-13-12: Immune signatures and MammaPrint (ultra) high risk class (MP2) as predictors of response to pembrolizumab combined with the TLR9 agonist SD101 in the neoadjuvant I-SPY 2 TRIAL</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2022</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: Pembrolizumab, an anti-PD-1 immune checkpoint inhibitor, is approved for treatment in...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: Pembrolizumab, an anti-PD-1 immune checkpoint inhibitor, is approved for treatment in multiple cancers and has been shown to increase pathologic complete response (pCR) and survival in the neoadjuvant setting in breast cancer. Pembrolizumab combined with paclitaxel followed by doxorubicin/cyclophosphamide (P+T-&gt;AC) was evaluated in HER2- patients in the neoadjuvant I-SPY 2 TRIAL and graduated in the HER2-, HR+HER2- and triple negative (TN) signatures. Our biomarker analysis revealed that immune cell abundance and MP2 class predicts response in HR+HER2- patients whereas tumor-immune proximity scores (multiplex-IF) and signaling signatures (mRNA) predict response in TN patients. In an effort to further improve response, the TLR9 agonist SD101 was added to Pembro (P+S+T -&gt; AC) for testing in I-SPY 2. While P+S increased estimated pCR rates relative to control (T-&gt;AC), it did not graduate for efficacy. To better understand the biology underlying response to P+S, we ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="105817429"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="105817429"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 105817429; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=105817429]").text(description); $(".js-view-count[data-work-id=105817429]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 105817429; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='105817429']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 105817429, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=105817429]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":105817429,"title":"Abstract P5-13-12: Immune signatures and MammaPrint (ultra) high risk class (MP2) as predictors of response to pembrolizumab combined with the TLR9 agonist SD101 in the neoadjuvant I-SPY 2 TRIAL","translated_title":"","metadata":{"abstract":"Background: Pembrolizumab, an anti-PD-1 immune checkpoint inhibitor, is approved for treatment in multiple cancers and has been shown to increase pathologic complete response (pCR) and survival in the neoadjuvant setting in breast cancer. Pembrolizumab combined with paclitaxel followed by doxorubicin/cyclophosphamide (P+T-\u0026gt;AC) was evaluated in HER2- patients in the neoadjuvant I-SPY 2 TRIAL and graduated in the HER2-, HR+HER2- and triple negative (TN) signatures. Our biomarker analysis revealed that immune cell abundance and MP2 class predicts response in HR+HER2- patients whereas tumor-immune proximity scores (multiplex-IF) and signaling signatures (mRNA) predict response in TN patients. In an effort to further improve response, the TLR9 agonist SD101 was added to Pembro (P+S+T -\u0026gt; AC) for testing in I-SPY 2. While P+S increased estimated pCR rates relative to control (T-\u0026gt;AC), it did not graduate for efficacy. To better understand the biology underlying response to P+S, we ...","publisher":"American Association for Cancer Research (AACR)","publication_date":{"day":null,"month":null,"year":2022,"errors":{}},"publication_name":"Cancer Research"},"translated_abstract":"Background: Pembrolizumab, an anti-PD-1 immune checkpoint inhibitor, is approved for treatment in multiple cancers and has been shown to increase pathologic complete response (pCR) and survival in the neoadjuvant setting in breast cancer. Pembrolizumab combined with paclitaxel followed by doxorubicin/cyclophosphamide (P+T-\u0026gt;AC) was evaluated in HER2- patients in the neoadjuvant I-SPY 2 TRIAL and graduated in the HER2-, HR+HER2- and triple negative (TN) signatures. Our biomarker analysis revealed that immune cell abundance and MP2 class predicts response in HR+HER2- patients whereas tumor-immune proximity scores (multiplex-IF) and signaling signatures (mRNA) predict response in TN patients. In an effort to further improve response, the TLR9 agonist SD101 was added to Pembro (P+S+T -\u0026gt; AC) for testing in I-SPY 2. While P+S increased estimated pCR rates relative to control (T-\u0026gt;AC), it did not graduate for efficacy. To better understand the biology underlying response to P+S, we ...","internal_url":"https://www.academia.edu/105817429/Abstract_P5_13_12_Immune_signatures_and_MammaPrint_ultra_high_risk_class_MP2_as_predictors_of_response_to_pembrolizumab_combined_with_the_TLR9_agonist_SD101_in_the_neoadjuvant_I_SPY_2_TRIAL","translated_internal_url":"","created_at":"2023-08-21T09:09:52.907-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_P5_13_12_Immune_signatures_and_MammaPrint_ultra_high_risk_class_MP2_as_predictors_of_response_to_pembrolizumab_combined_with_the_TLR9_agonist_SD101_in_the_neoadjuvant_I_SPY_2_TRIAL","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":216943,"name":"CD","url":"https://www.academia.edu/Documents/in/CD"},{"id":324154,"name":"Immune system","url":"https://www.academia.edu/Documents/in/Immune_system"},{"id":2754235,"name":"Pembrolizumab","url":"https://www.academia.edu/Documents/in/Pembrolizumab"}],"urls":[{"id":33542137,"url":"https://aacrjournals.org/cancerres/article/82/4_Supplement/P5-13-12/681330/Abstract-P5-13-12-Immune-signatures-and-MammaPrint"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="105817423"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/105817423/Abstract_PD11_01_PD11_01_Evaluation_of_the_PD_1_Inhibitor_Cemiplimab_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL"><img alt="Research paper thumbnail of Abstract PD11-01: PD11-01 Evaluation of the PD-1 Inhibitor Cemiplimab in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/105817423/Abstract_PD11_01_PD11_01_Evaluation_of_the_PD_1_Inhibitor_Cemiplimab_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL">Abstract PD11-01: PD11-01 Evaluation of the PD-1 Inhibitor Cemiplimab in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL</a></div><div class="wp-workCard_item"><span>Cancer Research</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within b...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR). Cemiplimab (Cemi) is a PD-1 inhibitor approved for the treatment of NSCLC, cutaneous basal, and squamous cell cancer. Here, we report current efficacy rates of Cemi in combination with paclitaxel followed by AC. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment; HR positive (HR+) patients had to be MP high risk. Treatment included paclitaxel 80 mg/m2 IV weekly x 12 and Cemi 350 mg IV given q3weeks x 4, followed by doxorubicin/cyclophosphamide (AC) every 2 weeks x 4. The control arm was weekly paclitaxel x 12 followed by AC every 2-3 weeks x 4. All patients undergo serial MRI imaging; and ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="105817423"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="105817423"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 105817423; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=105817423]").text(description); $(".js-view-count[data-work-id=105817423]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 105817423; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='105817423']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 105817423, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=105817423]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":105817423,"title":"Abstract PD11-01: PD11-01 Evaluation of the PD-1 Inhibitor Cemiplimab in early-stage, high-risk HER2-negative breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL","translated_title":"","metadata":{"abstract":"Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR). Cemiplimab (Cemi) is a PD-1 inhibitor approved for the treatment of NSCLC, cutaneous basal, and squamous cell cancer. Here, we report current efficacy rates of Cemi in combination with paclitaxel followed by AC. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment; HR positive (HR+) patients had to be MP high risk. Treatment included paclitaxel 80 mg/m2 IV weekly x 12 and Cemi 350 mg IV given q3weeks x 4, followed by doxorubicin/cyclophosphamide (AC) every 2 weeks x 4. The control arm was weekly paclitaxel x 12 followed by AC every 2-3 weeks x 4. All patients undergo serial MRI imaging; and ...","publisher":"American Association for Cancer Research (AACR)","publication_name":"Cancer Research"},"translated_abstract":"Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR). Cemiplimab (Cemi) is a PD-1 inhibitor approved for the treatment of NSCLC, cutaneous basal, and squamous cell cancer. Here, we report current efficacy rates of Cemi in combination with paclitaxel followed by AC. Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment; HR positive (HR+) patients had to be MP high risk. Treatment included paclitaxel 80 mg/m2 IV weekly x 12 and Cemi 350 mg IV given q3weeks x 4, followed by doxorubicin/cyclophosphamide (AC) every 2 weeks x 4. The control arm was weekly paclitaxel x 12 followed by AC every 2-3 weeks x 4. All patients undergo serial MRI imaging; and ...","internal_url":"https://www.academia.edu/105817423/Abstract_PD11_01_PD11_01_Evaluation_of_the_PD_1_Inhibitor_Cemiplimab_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL","translated_internal_url":"","created_at":"2023-08-21T09:09:40.601-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_PD11_01_PD11_01_Evaluation_of_the_PD_1_Inhibitor_Cemiplimab_in_early_stage_high_risk_HER2_negative_breast_cancer_Results_from_the_neoadjuvant_I_SPY_2_TRIAL","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"},{"id":168351,"name":"Paclitaxel","url":"https://www.academia.edu/Documents/in/Paclitaxel"},{"id":2530768,"name":"neoadjuvant therapy","url":"https://www.academia.edu/Documents/in/neoadjuvant_therapy"}],"urls":[{"id":33542132,"url":"https://aacrjournals.org/cancerres/article/83/5_Supplement/PD11-01/717156/Abstract-PD11-01-PD11-01-Evaluation-of-the-PD-1"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="90622408"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/90622408/The_I_SPY_COVID_Adaptive_Platform_Trial_for_COVID_19_Acute_Respiratory_Failure_Rationale_Design_and_Operations"><img alt="Research paper thumbnail of The I-SPY COVID Adaptive Platform Trial for COVID-19 Acute Respiratory Failure: Rationale, Design and Operations" class="work-thumbnail" src="https://attachments.academia-assets.com/94135132/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/90622408/The_I_SPY_COVID_Adaptive_Platform_Trial_for_COVID_19_Acute_Respiratory_Failure_Rationale_Design_and_Operations">The I-SPY COVID Adaptive Platform Trial for COVID-19 Acute Respiratory Failure: Rationale, Design and Operations</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">IntroductionThe COVID-19 pandemic brought an urgent need to discover novel effective therapeutics...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">IntroductionThe COVID-19 pandemic brought an urgent need to discover novel effective therapeutics for patients hospitalized with severe COVID-19. The ISPY COVID trial was designed and implemented in early 2020 to evaluate investigational agents rapidly and simultaneously on a phase 2 adaptive platform. This manuscript outlines the design, rationale, implementation, and challenges of the ISPY COVID trial during the first phase of trial activity from April 2020 until December 2021.Methods and analysisThe ISPY COVID Trial is a multi-center open label phase 2 platform trial in the United States designed to evaluate therapeutics that may have a large effect on improving outcomes from severe COVID-19. The ISPY COVID Trial network includes academic and community hospitals with significant geographic diversity across the country. Enrolled patients are randomized to receive one of up to four investigational agents or a control and are evaluated for a family of two primary outcomes—time to re...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ca4aa49e188e50c1a6a79a7ca9d5f5fe" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":94135132,"asset_id":90622408,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/94135132/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="90622408"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="90622408"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 90622408; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=90622408]").text(description); $(".js-view-count[data-work-id=90622408]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 90622408; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='90622408']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 90622408, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "ca4aa49e188e50c1a6a79a7ca9d5f5fe" } } $('.js-work-strip[data-work-id=90622408]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":90622408,"title":"The I-SPY COVID Adaptive Platform Trial for COVID-19 Acute Respiratory Failure: Rationale, Design and Operations","translated_title":"","metadata":{"abstract":"IntroductionThe COVID-19 pandemic brought an urgent need to discover novel effective therapeutics for patients hospitalized with severe COVID-19. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="90622407"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/90622407/Abstract_PD10_07_Chemokine12_CK12_tertiary_lymphoid_gene_expression_signature_as_a_predictor_of_response_in_3_immunotherapy_arms_of_the_neoadjuvant_ISPY_2_TRIAL_pembrolizumab_with_and_without_SD101_and_durvalumab_combined_with_olaparib_and_in_9_other_arms_of_the_trial_including_platinum_b_"><img alt="Research paper thumbnail of Abstract PD10-07: Chemokine12 (CK12) tertiary lymphoid gene expression signature as a predictor of response in 3 immunotherapy arms of the neoadjuvant ISPY 2 TRIAL - pembrolizumab with and without SD101, and durvalumab combined with olaparib - and in 9 other arms of the trial including platinum-b..." class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/90622407/Abstract_PD10_07_Chemokine12_CK12_tertiary_lymphoid_gene_expression_signature_as_a_predictor_of_response_in_3_immunotherapy_arms_of_the_neoadjuvant_ISPY_2_TRIAL_pembrolizumab_with_and_without_SD101_and_durvalumab_combined_with_olaparib_and_in_9_other_arms_of_the_trial_including_platinum_b_">Abstract PD10-07: Chemokine12 (CK12) tertiary lymphoid gene expression signature as a predictor of response in 3 immunotherapy arms of the neoadjuvant ISPY 2 TRIAL - pembrolizumab with and without SD101, and durvalumab combined with olaparib - and in 9 other arms of the trial including platinum-b...</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2022</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: The CK12 expression signature consists of genes CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: The CK12 expression signature consists of genes CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11, CXCL13 and was previously shown to associate with the presence of T and B cell rich tertiary lymphoid structures in melanoma and other cancers, and with better patient survival independent of tumor staging and treatment. I-SPY 2 is a biomarker-rich, phase II neoadjuvant platform trial for high risk early stage breast cancer. Here we leverage the I-SPY 2 biomarker program to test the hypothesis that this signature associates with sensitivity to neoadjuvant immunotherapies and potentially other classes cancer therapeutics in breast cancer. Methods: Data from 1130 patients across 12 arms of I-SPY2 (control (ctr): 210; veliparib/carboplatin (VC): 71; neratinib (N): 114; MK2206: 93; ganitumab: 106; ganetespib: 93; AMG386: 134; TDM1/pertuzumab(P): 52; H/P: 44; pembrolizumab (pembro): 69; durvalumab/olaparib (durva/olap): 71; pembro/SD101: 72) were available...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="90622407"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="90622407"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 90622407; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=90622407]").text(description); $(".js-view-count[data-work-id=90622407]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 90622407; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='90622407']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 90622407, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=90622407]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":90622407,"title":"Abstract PD10-07: Chemokine12 (CK12) tertiary lymphoid gene expression signature as a predictor of response in 3 immunotherapy arms of the neoadjuvant ISPY 2 TRIAL - pembrolizumab with and without SD101, and durvalumab combined with olaparib - and in 9 other arms of the trial including platinum-b...","translated_title":"","metadata":{"abstract":"Background: The CK12 expression signature consists of genes CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11, CXCL13 and was previously shown to associate with the presence of T and B cell rich tertiary lymphoid structures in melanoma and other cancers, and with better patient survival independent of tumor staging and treatment. I-SPY 2 is a biomarker-rich, phase II neoadjuvant platform trial for high risk early stage breast cancer. Here we leverage the I-SPY 2 biomarker program to test the hypothesis that this signature associates with sensitivity to neoadjuvant immunotherapies and potentially other classes cancer therapeutics in breast cancer. Methods: Data from 1130 patients across 12 arms of I-SPY2 (control (ctr): 210; veliparib/carboplatin (VC): 71; neratinib (N): 114; MK2206: 93; ganitumab: 106; ganetespib: 93; AMG386: 134; TDM1/pertuzumab(P): 52; H/P: 44; pembrolizumab (pembro): 69; durvalumab/olaparib (durva/olap): 71; pembro/SD101: 72) were available...","publisher":"American Association for Cancer Research (AACR)","publication_date":{"day":null,"month":null,"year":2022,"errors":{}},"publication_name":"Cancer Research"},"translated_abstract":"Background: The CK12 expression signature consists of genes CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11, CXCL13 and was previously shown to associate with the presence of T and B cell rich tertiary lymphoid structures in melanoma and other cancers, and with better patient survival independent of tumor staging and treatment. I-SPY 2 is a biomarker-rich, phase II neoadjuvant platform trial for high risk early stage breast cancer. Here we leverage the I-SPY 2 biomarker program to test the hypothesis that this signature associates with sensitivity to neoadjuvant immunotherapies and potentially other classes cancer therapeutics in breast cancer. Methods: Data from 1130 patients across 12 arms of I-SPY2 (control (ctr): 210; veliparib/carboplatin (VC): 71; neratinib (N): 114; MK2206: 93; ganitumab: 106; ganetespib: 93; AMG386: 134; TDM1/pertuzumab(P): 52; H/P: 44; pembrolizumab (pembro): 69; durvalumab/olaparib (durva/olap): 71; pembro/SD101: 72) were available...","internal_url":"https://www.academia.edu/90622407/Abstract_PD10_07_Chemokine12_CK12_tertiary_lymphoid_gene_expression_signature_as_a_predictor_of_response_in_3_immunotherapy_arms_of_the_neoadjuvant_ISPY_2_TRIAL_pembrolizumab_with_and_without_SD101_and_durvalumab_combined_with_olaparib_and_in_9_other_arms_of_the_trial_including_platinum_b_","translated_internal_url":"","created_at":"2022-11-12T17:21:38.448-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_PD10_07_Chemokine12_CK12_tertiary_lymphoid_gene_expression_signature_as_a_predictor_of_response_in_3_immunotherapy_arms_of_the_neoadjuvant_ISPY_2_TRIAL_pembrolizumab_with_and_without_SD101_and_durvalumab_combined_with_olaparib_and_in_9_other_arms_of_the_trial_including_platinum_b_","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"}],"urls":[{"id":25884803,"url":"https://aacrjournals.org/cancerres/article/82/4_Supplement/PD10-07/681423/Abstract-PD10-07-Chemokine12-CK12-tertiary"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="90622406"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/90622406/Abstract_OT1_10_02_I_SPY2_endocrine_optimization_protocol_EOP_A_pilot_neoadjuvant_endocrine_therapy_study_with_amcenestrant_as_monotherapy_or_in_combination_with_abemacicilib_or_letrozole_in_molecularly_selected_HR_HER2_clinical_stage_2_3_breast_cancer"><img alt="Research paper thumbnail of Abstract OT1-10-02: I-SPY2 endocrine optimization protocol (EOP): A pilot neoadjuvant endocrine therapy study with amcenestrant as monotherapy or in combination with abemacicilib or letrozole in molecularly selected HR+/HER2- clinical stage 2/3 breast cancer" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/90622406/Abstract_OT1_10_02_I_SPY2_endocrine_optimization_protocol_EOP_A_pilot_neoadjuvant_endocrine_therapy_study_with_amcenestrant_as_monotherapy_or_in_combination_with_abemacicilib_or_letrozole_in_molecularly_selected_HR_HER2_clinical_stage_2_3_breast_cancer">Abstract OT1-10-02: I-SPY2 endocrine optimization protocol (EOP): A pilot neoadjuvant endocrine therapy study with amcenestrant as monotherapy or in combination with abemacicilib or letrozole in molecularly selected HR+/HER2- clinical stage 2/3 breast cancer</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2022</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: There is no clinical equipoise on the best upfront management of patients with early-...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: There is no clinical equipoise on the best upfront management of patients with early-stage hormone receptor-positive (HR+)/HER2-negative (HER2-) breast cancer (BC) that is high-risk by clinicopathologic criteria, and low-risk based on molecular profiling. These patients are unlikely to respond to chemotherapy. However, these patients still have risk, often risk of late recurrence, despite standard adjuvant endocrine therapy. Novel endocrine-based strategies that are more effective and tolerable than current standard therapies are needed for this population. Next-generation orally-bioavailable selective estrogen receptor degraders (oSERDs) with improved pharmacokinetic (PK) properties are promising potential therapies for HR+ BC. The oSERD amcenestrant has demonstrated a favorable safety profile and encouraging efficacy in a phase I/II dose escalation and expansion trial for heavily pre-treated patients with HR+ metastatic BC and is an attractive agent for assessment in t...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="90622406"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="90622406"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 90622406; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=90622406]").text(description); $(".js-view-count[data-work-id=90622406]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 90622406; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='90622406']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 90622406, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=90622406]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":90622406,"title":"Abstract OT1-10-02: I-SPY2 endocrine optimization protocol (EOP): A pilot neoadjuvant endocrine therapy study with amcenestrant as monotherapy or in combination with abemacicilib or letrozole in molecularly selected HR+/HER2- clinical stage 2/3 breast cancer","translated_title":"","metadata":{"abstract":"Background: There is no clinical equipoise on the best upfront management of patients with early-stage hormone receptor-positive (HR+)/HER2-negative (HER2-) breast cancer (BC) that is high-risk by clinicopathologic criteria, and low-risk based on molecular profiling. These patients are unlikely to respond to chemotherapy. However, these patients still have risk, often risk of late recurrence, despite standard adjuvant endocrine therapy. Novel endocrine-based strategies that are more effective and tolerable than current standard therapies are needed for this population. Next-generation orally-bioavailable selective estrogen receptor degraders (oSERDs) with improved pharmacokinetic (PK) properties are promising potential therapies for HR+ BC. The oSERD amcenestrant has demonstrated a favorable safety profile and encouraging efficacy in a phase I/II dose escalation and expansion trial for heavily pre-treated patients with HR+ metastatic BC and is an attractive agent for assessment in t...","publisher":"American Association for Cancer Research (AACR)","publication_date":{"day":null,"month":null,"year":2022,"errors":{}},"publication_name":"Cancer Research"},"translated_abstract":"Background: There is no clinical equipoise on the best upfront management of patients with early-stage hormone receptor-positive (HR+)/HER2-negative (HER2-) breast cancer (BC) that is high-risk by clinicopathologic criteria, and low-risk based on molecular profiling. These patients are unlikely to respond to chemotherapy. However, these patients still have risk, often risk of late recurrence, despite standard adjuvant endocrine therapy. Novel endocrine-based strategies that are more effective and tolerable than current standard therapies are needed for this population. Next-generation orally-bioavailable selective estrogen receptor degraders (oSERDs) with improved pharmacokinetic (PK) properties are promising potential therapies for HR+ BC. The oSERD amcenestrant has demonstrated a favorable safety profile and encouraging efficacy in a phase I/II dose escalation and expansion trial for heavily pre-treated patients with HR+ metastatic BC and is an attractive agent for assessment in t...","internal_url":"https://www.academia.edu/90622406/Abstract_OT1_10_02_I_SPY2_endocrine_optimization_protocol_EOP_A_pilot_neoadjuvant_endocrine_therapy_study_with_amcenestrant_as_monotherapy_or_in_combination_with_abemacicilib_or_letrozole_in_molecularly_selected_HR_HER2_clinical_stage_2_3_breast_cancer","translated_internal_url":"","created_at":"2022-11-12T17:21:38.250-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":58854969,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Abstract_OT1_10_02_I_SPY2_endocrine_optimization_protocol_EOP_A_pilot_neoadjuvant_endocrine_therapy_study_with_amcenestrant_as_monotherapy_or_in_combination_with_abemacicilib_or_letrozole_in_molecularly_selected_HR_HER2_clinical_stage_2_3_breast_cancer","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":58854969,"first_name":"Ruixiao","middle_initials":null,"last_name":"Lu","page_name":"RuixiaoLu","domain_name":"novartis","created_at":"2017-01-13T16:26:37.257-08:00","display_name":"Ruixiao Lu","url":"https://novartis.academia.edu/RuixiaoLu"},"attachments":[],"research_interests":[{"id":626,"name":"Oncology","url":"https://www.academia.edu/Documents/in/Oncology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":64336,"name":"Population","url":"https://www.academia.edu/Documents/in/Population"},{"id":65390,"name":"Internal Medicine","url":"https://www.academia.edu/Documents/in/Internal_Medicine"},{"id":2011298,"name":"Letrozole","url":"https://www.academia.edu/Documents/in/Letrozole"},{"id":2530768,"name":"neoadjuvant therapy","url":"https://www.academia.edu/Documents/in/neoadjuvant_therapy"}],"urls":[{"id":25884802,"url":"https://aacrjournals.org/cancerres/article/82/4_Supplement/OT1-10-02/680171/Abstract-OT1-10-02-I-SPY2-endocrine-optimization"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="90622405"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/90622405/Clinical_trial_design_during_and_beyond_the_pandemic_the_I_SPY_COVID_trial"><img alt="Research paper thumbnail of Clinical trial design during and beyond the pandemic: the I-SPY COVID trial" class="work-thumbnail" src="https://attachments.academia-assets.com/94135121/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/90622405/Clinical_trial_design_during_and_beyond_the_pandemic_the_I_SPY_COVID_trial">Clinical trial design during and beyond the pandemic: the I-SPY COVID trial</a></div><div class="wp-workCard_item"><span>Nature Medicine</span><span>, 2022</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c1ec3843aa682d4708d7d22aa7cecb76" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":94135121,"asset_id":90622405,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/94135121/download_file?st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&st=MTczMjUwOTA4MSw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span 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profile--work_container" data-work-id="90622404"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/90622404/Prospective_study_of_a_17_GENE_RT_PCR_based_assay_for_prediction_of_high_risk_pathology_at_radical_prostatectomy"><img alt="Research paper thumbnail of Prospective study of a 17-GENE RT-PCR-based assay for prediction of high risk pathology at radical prostatectomy" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/90622404/Prospective_study_of_a_17_GENE_RT_PCR_based_assay_for_prediction_of_high_risk_pathology_at_radical_prostatectomy">Prospective study of a 17-GENE RT-PCR-based assay for prediction of high risk pathology at radical prostatectomy</a></div><div class="wp-workCard_item"><span>Journal of Clinical Oncology</span><span>, 2017</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">36 Background: A biopsy-based 17 gene tissue-based RTPCR assay (Oncotype Dx Genomic Prostate Scor...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">36 Background: A biopsy-based 17 gene tissue-based RTPCR assay (Oncotype Dx Genomic Prostate Score, GPS) has been validated in retrospective cohorts as a predictor of adverse pathology and biochemical recurrence in prostate cancer (PCa) patients who underwent radical prostatectomy (RP). The National Comprehensive Cancer Network (NCCN) recommends that men with pathologic Gleason Score (pGS) &gt; 8, pT3+, and/or Lymph Node positive disease (i.e. high risk surgical pathology, HRSP) consider adjuvant therapy after RP. We report herein on GPS at biopsy as a predictor of HRSP in men presenting with clinically low-risk PCa. Methods: As part of an ongoing observational study of GPS (N = 1200), we performed an exploratory analysis in men who elected RP as initial disease management. Descriptive statistics were reported. Binary logistic regression was performed to determine the association between GPS and HRSP. 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