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Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.. http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See http://creativecommons.org/licenses/by-nc/4.0/." /> <meta name="DC.AccessRights" content="open-access" /> <meta name="DC.Description" content="Background Novel treatment selection biomarkers are critical to improve outcomes in head and neck squamous cell carcinoma (HNSCC). In this retrospective pilot study, we evaluated, for the first time, a customized, highly multiplexed antibody panel (multi-IF) to identify molecular, cellular, meta-cellular, and network-level biomarkers. We analyzed HPV negative, tobacco associated oral cavity SCC from a multi-institutional, Phase 2 trial ([NCT03529422][1]) evaluating post-operative, concurrent radiation therapy (XRT) with durvalumab (anti-PD-(L)1 therapy) in intermediate-risk HNSCC. We hypothesized that distinct differences exist before treatment initiation at the level of intra- and peritumoral cell populations, associated cell state, and the spatial organization of the tumor-immune microenvironment (‘ecotypes’) between patients who remain disease free (‘responders’) versus those with recurrent disease (‘non-responders’). Methods Using a 41-antibody panel for multiplexed imaging, spatial analyses were conducted on pre-treatment tongue and floor of the mouth HNSCC specimens. Human-in-the-loop cell segmentation was first performed using Cellpose-3, resulting in a CELLxFEATURE multi-IF matrix. Next, cells identities were assigned via TACIT (Threshold-based Assignment of Cell Types from Multiplexed Imaging Data) using deep learning of cell type signature markers. The relative proportions of cell types between responders versus non-responders were compared using the Wilcoxon rank-sum test to identify the enrichment of specific cell types in either group. Exhaustion cell state markers were used to evaluate changes in exhaustion pathways. Recurring intratumoral ecotypes representing cell meta-architectures were recovered by Spatial-LDA. The correlation of their occurrences with clinical outcomes was further examined using Kaplan-Meier analysis to identify spatial biomarkers differentiating responders from non-responders. Results 9/18 patients enrolled on-trial were included in this analysis including 5 responders versus 4 non-responders. All completed post-operative XRT+durvalumab, per protocol. Clinical and outcome data were collected and have been presented previously. In responders, exhausted T cells were associated with PD-L1+ dendritic cells (DC) and ICOS+ CD20 B Cells. The neighborhood analysis, using a co-occurrence of cells in a single-cell level, showed a higher prevalence of a peritumoral exhaustion in responders, compared to non-responders who presented an innate/exhaustion prevalence. Low tumor cell, high CD4 T-cell, and high DC proportions were associated with improved overall survival (p<0.05, figures 1,2). Conclusions We show for the first time that spatial ecotypes within individual tumor microenvironments have distinct spatial organization and are associated with survival (figure 1). Given proof-of-principle, we plan to scale-up to verify our findings. Tumor meta-cellular arrangements serve as a promising biomarker for optimal treatment selection for post-operative therapy in HNSCC. Trial Registration NCT03529422. Ethics Approval LCCC1725 ([NCT03529422][1]) was a single-arm, multicenter, phase 2 clinical trial conducted at the Lineberger Comprehensive Cancer Center at the University of North Carolina at Chapel Hill, Medical University of South Carolina, University of Alabama at Birmingham. The protocol was approved by the relevant scientific and ethical review boards at each institution. It was conducted under an Investigational New Drug and in accordance with the Declaration of Helsinki. ![Abstract 210 Figure 1][2]</img> Abstract 210 Figure 1 a. Multiplex immunofluorescence of 41 antibodies from a responder. Images from lower to higher magnification show the tumor origin, tumor parenchyma, and invasion front represented by an intense immune infiltrate around the area, respectively. The lower inset highlights tumor features, including glandular invasion, lymphovascular invasion, and necrosis. b. Voronoi reconstruction of the slide using the TACIT algorithm to assign cell identities. c. Multiplex immunofluorescence of 41 antibodies in a non-responder. Images from lower to higher magnification show the tumor origin, tumor parenchyma, and invasion front, respectively. The lower inset highlights tumor features, including glandular invasion, lymphovascular invasion, and necrosis. d. Voronoi reconstruction of the slide using the TACIT algorithm to assign cell identities. e. Relative distribution of cell proportions comparison between responders and non- responders. Colored cell types are matched with the Voronoi reconstruction. f. Statistical difference between the immune population prevalence and tumor cells between responders and non-responders. g. Heatmaps of cell expression of cell state markers correlated with cell exhaustion and immunosuppression, showing that non-responders presented a higher prevalence of PD-L1. h. Delaunay triangulation showing the co-occurrence of cells within their coordinates. Responders presented a correlation between tumor cells, dendritic cells, and exhausted immune cells and a correlation between adaptive immune cells and innate immune cells; a distinct co-occurrence pattern was observed in non-responders. i. KM showing the DFS relation with PD-L1/PD-1 interaction and IDO1 correlation. j. Increased PD-L1 expression in T exhausted cells observed in responders compared to non-responders ![Abstract 210 Figure 2][2]</img> Abstract 210 Figure 2 KM showing overall survival (OS) based on tumor cell proportion (left), CD4+ T cells proportion (middle), and dendritic cells proportion (right). Low tumor cell proportion, high CD4+ T cells proportion, and high dendritic cells proportion associated with improved OS [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT03529422&atom=%2Fjitc%2F12%2FSuppl_2%2FA240.atom [2]: pending:yes" /> <meta name="DC.Contributor" content="Siddharth Sheth" /> <meta name="DC.Contributor" content="Nikhil Kumar" /> <meta name="DC.Contributor" content="Bruno Matuck" /> <meta name="DC.Contributor" content="Khoa Huynh" /> <meta name="DC.Contributor" content="Allison Deal" /> <meta name="DC.Contributor" content="John Kaczmar" /> <meta name="DC.Contributor" content="Bhisham Chera" /> <meta name="DC.Contributor" content="James Bonner" /> <meta name="DC.Contributor" content="Jared Weiss" /> <meta name="DC.Contributor" content="Jinze Liu" /> <meta name="DC.Contributor" content="Kevin Byrd" /> <meta name="article:published_time" content="2024-11-01" /> <meta name="article:section" content="Regular and Young Investigator Award Abstracts" /> <meta name="citation_title" content="210 Metacellular networks and proteomic ecotypes predict survival outcomes in HNSCC treated with post-operative radiation therapy and durvalumab" /> <meta name="citation_abstract" lang="en" content="<h3>Background</h3> <p>Novel treatment selection biomarkers are critical to improve outcomes in head and neck squamous cell carcinoma (HNSCC). In this retrospective pilot study, we evaluated, for the first time, a customized, highly multiplexed antibody panel (multi-IF) to identify molecular, cellular, meta-cellular, and network-level biomarkers. We analyzed HPV negative, tobacco associated oral cavity SCC from a multi-institutional, Phase 2 trial (NCT03529422) evaluating post-operative, concurrent radiation therapy (XRT) with durvalumab (anti-PD-(L)1 therapy) in intermediate-risk HNSCC. We hypothesized that distinct differences exist before treatment initiation at the level of intra- and peritumoral cell populations, associated cell state, and the spatial organization of the tumor-immune microenvironment (‘ecotypes’) between patients who remain disease free (‘responders’) versus those with recurrent disease (‘non-responders’).</p><h3>Methods</h3> <p>Using a 41-antibody panel for multiplexed imaging, spatial analyses were conducted on pre-treatment tongue and floor of the mouth HNSCC specimens. Human-in-the-loop cell segmentation was first performed using Cellpose-3, resulting in a CELLxFEATURE multi-IF matrix. Next, cells identities were assigned via TACIT (Threshold-based Assignment of Cell Types from Multiplexed Imaging Data) using deep learning of cell type signature markers. The relative proportions of cell types between responders versus non-responders were compared using the Wilcoxon rank-sum test to identify the enrichment of specific cell types in either group. Exhaustion cell state markers were used to evaluate changes in exhaustion pathways. Recurring intratumoral ecotypes representing cell meta-architectures were recovered by Spatial-LDA. The correlation of their occurrences with clinical outcomes was further examined using Kaplan-Meier analysis to identify spatial biomarkers differentiating responders from non-responders.</p><h3>Results</h3> <p>9/18 patients enrolled on-trial were included in this analysis including 5 responders versus 4 non-responders. All completed post-operative XRT+durvalumab, per protocol. Clinical and outcome data were collected and have been presented previously. In responders, exhausted T cells were associated with PD-L1+ dendritic cells (DC) and ICOS+ CD20 B Cells. The neighborhood analysis, using a co-occurrence of cells in a single-cell level, showed a higher prevalence of a peritumoral exhaustion in responders, compared to non-responders who presented an innate/exhaustion prevalence. Low tumor cell, high CD4 T-cell, and high DC proportions were associated with improved overall survival (p&lt;0.05, figures 1,2).</p><h3>Conclusions</h3> <p>We show for the first time that spatial ecotypes within individual tumor microenvironments have distinct spatial organization and are associated with survival (figure 1). Given proof-of-principle, we plan to scale-up to verify our findings. Tumor meta-cellular arrangements serve as a promising biomarker for optimal treatment selection for post-operative therapy in HNSCC.</p><h3>Trial Registration</h3> <p>NCT03529422.</p><h3>Ethics Approval</h3> <p>LCCC1725 (NCT03529422) was a single-arm, multicenter, phase 2 clinical trial conducted at the Lineberger Comprehensive Cancer Center at the University of North Carolina at Chapel Hill, Medical University of South Carolina, University of Alabama at Birmingham. The protocol was approved by the relevant scientific and ethical review boards at each institution. It was conducted under an Investigational New Drug and in accordance with the Declaration of Helsinki.</p>" /> <meta name="citation_journal_title" content="Journal for ImmunoTherapy of Cancer" /> <meta name="citation_publisher" content="BMJ Specialist Journals" /> <meta name="citation_publication_date" content="2024/11/01" /> <meta name="citation_mjid" content="jitc;12/Suppl_2/A240" /> <meta name="citation_id" content="12/Suppl_2/A240" /> <meta name="citation_public_url" content="https://jitc.bmj.com/content/12/Suppl_2/A240" /> <meta name="citation_abstract_html_url" content="https://jitc.bmj.com/content/12/Suppl_2/A240.abstract" /> <meta name="citation_full_html_url" content="https://jitc.bmj.com/content/12/Suppl_2/A240.full" /> <meta name="citation_pdf_url" content="https://jitc.bmj.com/content/jitc/12/Suppl_2/A240.full.pdf" /> <meta name="citation_issn" content="2051-1426" /> <meta name="citation_journal_abbrev" content="J Immunother Cancer" /> <meta name="citation_doi" content="10.1136/jitc-2024-SITC2024.0210" /> <meta name="citation_volume" content="12" /> <meta name="citation_issue" content="Suppl 2" /> <meta name="citation_article_type" content="Meeting Report" /> <meta name="citation_section" content="Regular and Young Investigator Award Abstracts" /> <meta name="citation_access" content="all" /> <meta name="citation_author" content="Siddharth Sheth" /> <meta name="citation_author_institution" content="University of North Carolina at Chapel Hill, Chapel Hill, NC, USA" /> <meta name="citation_author" content="Nikhil Kumar" /> <meta name="citation_author_institution" content="ADA Science and Research Institute, Gaithersburg, MD, USA" /> <meta name="citation_author" content="Bruno Matuck" /> <meta name="citation_author_institution" content="ADA Science and Research Institute, Gaithersburg, MD, USA" /> <meta name="citation_author" content="Khoa Huynh" /> <meta name="citation_author_institution" content="Virginia Commonwealth University, Richmond, VA, USA" /> <meta name="citation_author" content="Allison Deal" /> <meta name="citation_author_institution" content="Lineberger Comprehensive Cancer Center, Chapel Hill, NC, USA" /> <meta name="citation_author" content="John Kaczmar" /> <meta name="citation_author_institution" content="Hollings Cancer Center, Charleston, SC, USA" /> <meta name="citation_author" content="Bhisham Chera" /> <meta name="citation_author_institution" content="Hollings Cancer Center, Charleston, SC, USA" /> <meta name="citation_author" content="James Bonner" /> <meta name="citation_author_institution" content="University of Alabama at Birmingham, Birmingham, AL, USA" /> <meta name="citation_author" content="Jared Weiss" /> <meta name="citation_author_institution" content="Lineberger Comprehensive Cancer Center, Chapel Hill, NC, USA" /> <meta name="citation_author_institution" content="University of North Carolina School of Medicine, Chapel Hill, NC, USA" /> <meta name="citation_author" content="Jinze Liu" /> <meta name="citation_author_institution" content="Virginia Commonwealth University, Richmond, VA, USA" /> <meta name="citation_author" content="Kevin Byrd" /> <meta name="citation_author_institution" content="University of North Carolina at Chapel Hill, Chapel Hill, NC, USA" /> <meta name="citation_author_institution" content="ADA Science and Research Institute, Gaithersburg, MD, USA" /> <meta name="citation_author_institution" content="Lineberger Comprehensive Cancer Center, Chapel Hill, NC, USA" /> <meta name="citation_fulltext_world_readable" content="" /> <meta name="twitter:title" content="210 Metacellular networks and proteomic ecotypes predict survival outcomes in HNSCC treated with post-operative radiation therapy and durvalumab" /> <meta name="twitter:card" content="summary" /> <meta name="twitter:description" content="Background Novel treatment selection biomarkers are critical to improve outcomes in head and neck squamous cell carcinoma (HNSCC). In this retrospective pilot study, we evaluated, for the first time, a customized, highly multiplexed antibody panel (multi-IF) to identify molecular, cellular, meta-cellular, and network-level biomarkers. We analyzed HPV negative, tobacco associated oral cavity SCC from a multi-institutional, Phase 2 trial ([NCT03529422][1]) evaluating post-operative, concurrent radiation therapy (XRT) with durvalumab (anti-PD-(L)1 therapy) in intermediate-risk HNSCC. We hypothesized that distinct differences exist before treatment initiation at the level of intra- and peritumoral cell populations, associated cell state, and the spatial organization of the tumor-immune microenvironment (‘ecotypes’) between patients who remain disease free (‘responders’) versus those with recurrent disease (‘non-responders’). Methods Using a 41-antibody panel for multiplexed imaging, spatial analyses were conducted on pre-treatment tongue and floor of the mouth HNSCC specimens. Human-in-the-loop cell segmentation was first performed using Cellpose-3, resulting in a CELLxFEATURE multi-IF matrix. Next, cells identities were assigned via TACIT (Threshold-based Assignment of Cell Types from Multiplexed Imaging Data) using deep learning of cell type signature markers. The relative proportions of cell types between responders versus non-responders were compared using the Wilcoxon rank-sum test to identify the enrichment of specific cell types in either group. Exhaustion cell state markers were used to evaluate changes in exhaustion pathways. Recurring intratumoral ecotypes representing cell meta-architectures were recovered by Spatial-LDA. The correlation of their occurrences with clinical outcomes was further examined using Kaplan-Meier analysis to identify spatial biomarkers differentiating responders from non-responders. Results 9/18 patients enrolled on-trial were included in this analysis including 5 responders versus 4 non-responders. All completed post-operative XRT+durvalumab, per protocol. Clinical and outcome data were collected and have been presented previously. In responders, exhausted T cells were associated with PD-L1+ dendritic cells (DC) and ICOS+ CD20 B Cells. The neighborhood analysis, using a co-occurrence of cells in a single-cell level, showed a higher prevalence of a peritumoral exhaustion in responders, compared to non-responders who presented an innate/exhaustion prevalence. Low tumor cell, high CD4 T-cell, and high DC proportions were associated with improved overall survival (p<0.05, figures 1,2). Conclusions We show for the first time that spatial ecotypes within individual tumor microenvironments have distinct spatial organization and are associated with survival (figure 1). Given proof-of-principle, we plan to scale-up to verify our findings. Tumor meta-cellular arrangements serve as a promising biomarker for optimal treatment selection for post-operative therapy in HNSCC. Trial Registration NCT03529422. Ethics Approval LCCC1725 ([NCT03529422][1]) was a single-arm, multicenter, phase 2 clinical trial conducted at the Lineberger Comprehensive Cancer Center at the University of North Carolina at Chapel Hill, Medical University of South Carolina, University of Alabama at Birmingham. The protocol was approved by the relevant scientific and ethical review boards at each institution. It was conducted under an Investigational New Drug and in accordance with the Declaration of Helsinki. ![Abstract 210 Figure 1][2]</img> Abstract 210 Figure 1 a. Multiplex immunofluorescence of 41 antibodies from a responder. Images from lower to higher magnification show the tumor origin, tumor parenchyma, and invasion front represented by an intense immune infiltrate around the area, respectively. The lower inset highlights tumor features, including glandular invasion, lymphovascular invasion, and necrosis. b. Voronoi reconstruction of the slide using the TACIT algorithm to assign cell identities. c. Multiplex immunofluorescence of 41 antibodies in a non-responder. Images from lower to higher magnification show the tumor origin, tumor parenchyma, and invasion front, respectively. The lower inset highlights tumor features, including glandular invasion, lymphovascular invasion, and necrosis. d. Voronoi reconstruction of the slide using the TACIT algorithm to assign cell identities. e. Relative distribution of cell proportions comparison between responders and non- responders. Colored cell types are matched with the Voronoi reconstruction. f. Statistical difference between the immune population prevalence and tumor cells between responders and non-responders. g. Heatmaps of cell expression of cell state markers correlated with cell exhaustion and immunosuppression, showing that non-responders presented a higher prevalence of PD-L1. h. Delaunay triangulation showing the co-occurrence of cells within their coordinates. Responders presented a correlation between tumor cells, dendritic cells, and exhausted immune cells and a correlation between adaptive immune cells and innate immune cells; a distinct co-occurrence pattern was observed in non-responders. i. KM showing the DFS relation with PD-L1/PD-1 interaction and IDO1 correlation. j. Increased PD-L1 expression in T exhausted cells observed in responders compared to non-responders ![Abstract 210 Figure 2][2]</img> Abstract 210 Figure 2 KM showing overall survival (OS) based on tumor cell proportion (left), CD4+ T cells proportion (middle), and dendritic cells proportion (right). Low tumor cell proportion, high CD4+ T cells proportion, and high dendritic cells proportion associated with improved OS [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT03529422&atom=%2Fjitc%2F12%2FSuppl_2%2FA240.atom [2]: pending:yes" /> <meta name="og-title" property="og:title" content="210 Metacellular networks and proteomic ecotypes predict survival outcomes in HNSCC treated with post-operative radiation therapy and durvalumab" /> <meta name="og-url" property="og:url" content="https://jitc.bmj.com/content/12/Suppl_2/A240" /> <meta name="og-site-name" property="og:site_name" content="Journal for ImmunoTherapy of Cancer" /> <meta name="og-description" property="og:description" content="Background Novel treatment selection biomarkers are critical to improve outcomes in head and neck squamous cell carcinoma (HNSCC). In this retrospective pilot study, we evaluated, for the first time, a customized, highly multiplexed antibody panel (multi-IF) to identify molecular, cellular, meta-cellular, and network-level biomarkers. We analyzed HPV negative, tobacco associated oral cavity SCC from a multi-institutional, Phase 2 trial ([NCT03529422][1]) evaluating post-operative, concurrent radiation therapy (XRT) with durvalumab (anti-PD-(L)1 therapy) in intermediate-risk HNSCC. We hypothesized that distinct differences exist before treatment initiation at the level of intra- and peritumoral cell populations, associated cell state, and the spatial organization of the tumor-immune microenvironment (‘ecotypes’) between patients who remain disease free (‘responders’) versus those with recurrent disease (‘non-responders’). Methods Using a 41-antibody panel for multiplexed imaging, spatial analyses were conducted on pre-treatment tongue and floor of the mouth HNSCC specimens. Human-in-the-loop cell segmentation was first performed using Cellpose-3, resulting in a CELLxFEATURE multi-IF matrix. Next, cells identities were assigned via TACIT (Threshold-based Assignment of Cell Types from Multiplexed Imaging Data) using deep learning of cell type signature markers. The relative proportions of cell types between responders versus non-responders were compared using the Wilcoxon rank-sum test to identify the enrichment of specific cell types in either group. Exhaustion cell state markers were used to evaluate changes in exhaustion pathways. Recurring intratumoral ecotypes representing cell meta-architectures were recovered by Spatial-LDA. The correlation of their occurrences with clinical outcomes was further examined using Kaplan-Meier analysis to identify spatial biomarkers differentiating responders from non-responders. Results 9/18 patients enrolled on-trial were included in this analysis including 5 responders versus 4 non-responders. All completed post-operative XRT+durvalumab, per protocol. Clinical and outcome data were collected and have been presented previously. In responders, exhausted T cells were associated with PD-L1+ dendritic cells (DC) and ICOS+ CD20 B Cells. The neighborhood analysis, using a co-occurrence of cells in a single-cell level, showed a higher prevalence of a peritumoral exhaustion in responders, compared to non-responders who presented an innate/exhaustion prevalence. Low tumor cell, high CD4 T-cell, and high DC proportions were associated with improved overall survival (p<0.05, figures 1,2). Conclusions We show for the first time that spatial ecotypes within individual tumor microenvironments have distinct spatial organization and are associated with survival (figure 1). Given proof-of-principle, we plan to scale-up to verify our findings. Tumor meta-cellular arrangements serve as a promising biomarker for optimal treatment selection for post-operative therapy in HNSCC. Trial Registration NCT03529422. Ethics Approval LCCC1725 ([NCT03529422][1]) was a single-arm, multicenter, phase 2 clinical trial conducted at the Lineberger Comprehensive Cancer Center at the University of North Carolina at Chapel Hill, Medical University of South Carolina, University of Alabama at Birmingham. The protocol was approved by the relevant scientific and ethical review boards at each institution. It was conducted under an Investigational New Drug and in accordance with the Declaration of Helsinki. ![Abstract 210 Figure 1][2]</img> Abstract 210 Figure 1 a. Multiplex immunofluorescence of 41 antibodies from a responder. Images from lower to higher magnification show the tumor origin, tumor parenchyma, and invasion front represented by an intense immune infiltrate around the area, respectively. The lower inset highlights tumor features, including glandular invasion, lymphovascular invasion, and necrosis. b. Voronoi reconstruction of the slide using the TACIT algorithm to assign cell identities. c. Multiplex immunofluorescence of 41 antibodies in a non-responder. Images from lower to higher magnification show the tumor origin, tumor parenchyma, and invasion front, respectively. The lower inset highlights tumor features, including glandular invasion, lymphovascular invasion, and necrosis. d. Voronoi reconstruction of the slide using the TACIT algorithm to assign cell identities. e. Relative distribution of cell proportions comparison between responders and non- responders. Colored cell types are matched with the Voronoi reconstruction. f. Statistical difference between the immune population prevalence and tumor cells between responders and non-responders. g. Heatmaps of cell expression of cell state markers correlated with cell exhaustion and immunosuppression, showing that non-responders presented a higher prevalence of PD-L1. h. Delaunay triangulation showing the co-occurrence of cells within their coordinates. Responders presented a correlation between tumor cells, dendritic cells, and exhausted immune cells and a correlation between adaptive immune cells and innate immune cells; a distinct co-occurrence pattern was observed in non-responders. i. KM showing the DFS relation with PD-L1/PD-1 interaction and IDO1 correlation. j. Increased PD-L1 expression in T exhausted cells observed in responders compared to non-responders ![Abstract 210 Figure 2][2]</img> Abstract 210 Figure 2 KM showing overall survival (OS) based on tumor cell proportion (left), CD4+ T cells proportion (middle), and dendritic cells proportion (right). 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node56859" data-node-nid="56859" id="node-56859--2992963874" data-pisa="jitc;12/Suppl_2/A240" data-pisa-master="jitc;jitc-2024-SITC2024.0210" data-apath="/jitc/12/Suppl_2/A240.atom"><cite class="highwire-cite highwire-cite-highwire-article highwire-citation-bmjj-title clearfix"> <div class="highwire-cite-title">210 Metacellular networks and proteomic ecotypes predict survival outcomes in HNSCC treated with post-operative radiation therapy and durvalumab</div> <span class="highwire-cite-access"><span class="highwire-citation-access"><svg class="icon icon-open-access bmjj-open-access bmjj-access-tag"><use xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="#icon-openaccess"></use><svg></svg></svg></span></span> </cite> </div> </div> </div> <div class="panel-separator"></div><div class="panel-pane pane-highwire-panel-tabs-container col-narrow-12 clear" > <div class="pane-content"> <div data-panels-ajax-tab-preloaded="jnl_template_bmjj_tab_art" id="panels-ajax-tab-container-highwire_article_tabs" class="panels-ajax-tab-container"><div class="panels-ajax-tab-loading" style ="display:none"><img class="loading" src="https://jitc.bmj.com/sites/all/modules/contrib/panels_ajax_tab/images/loading.gif" alt="Loading" title="Loading" /></div><div class="panels-ajax-tab-wrap-jnl_template_bmjj_tab_art"><div class="panel-display panel-1col clearfix" > <div class="panel-panel panel-col"> <div><div class="panel-pane pane-highwire-markup author-affiliates col-narrow-12 author-affiliates-corresp article" > <div class="pane-content"> <div class="highwire-markup"><div xmlns="http://www.w3.org/1999/xhtml" class="content-block-markup" xmlns:xhtml="http://www.w3.org/1999/xhtml"><div xmlns:xhtml="http://www.w3.org/1999/xhtml" class="contributors"><ol class="contributor-list" id="contrib-group-1"><li class="contributor" id="contrib-1"><span class="name">Siddharth Sheth</span><a id="xref-aff-1-1" class="xref-aff" href="#aff-1">1</a>, </li><li class="contributor" id="contrib-2"><span class="name">Nikhil Kumar</span><a id="xref-aff-2-1" class="xref-aff" href="#aff-2">2</a>, </li><li class="contributor" id="contrib-3"><span class="name">Bruno Matuck</span><a id="xref-aff-2-2" class="xref-aff" href="#aff-2">2</a>, </li><li class="contributor" id="contrib-4"><span class="name">Khoa Huynh</span><a id="xref-aff-3-1" class="xref-aff" href="#aff-3">3</a>, </li><li class="contributor" id="contrib-5"><span class="name">Allison Deal</span><a id="xref-aff-4-1" class="xref-aff" href="#aff-4">4</a>, </li><li class="contributor" id="contrib-6"><span class="name">John Kaczmar</span><a id="xref-aff-5-1" class="xref-aff" href="#aff-5">5</a>, </li><li class="contributor" id="contrib-7"><span class="name">Bhisham Chera</span><a id="xref-aff-5-2" class="xref-aff" href="#aff-5">5</a>, </li><li class="contributor" id="contrib-8"><span class="name">James Bonner</span><a id="xref-aff-6-1" class="xref-aff" href="#aff-6">6</a>, </li><li class="contributor" id="contrib-9"><span class="name">Jared Weiss</span><a id="xref-aff-4-2" class="xref-aff" href="#aff-4">4</a><span class="xref-sep">,</span><a id="xref-aff-7-1" class="xref-aff" href="#aff-7">7</a>, </li><li class="contributor" id="contrib-10"><span class="name">Jinze Liu</span><a id="xref-aff-3-2" class="xref-aff" href="#aff-3">3</a> and </li><li class="last" id="contrib-11"><span class="name">Kevin Byrd</span><a id="xref-aff-1-2" class="xref-aff" href="#aff-1">1</a><span class="xref-sep">,</span><a id="xref-aff-2-3" class="xref-aff" href="#aff-2">2</a><span class="xref-sep">,</span><a id="xref-aff-4-3" class="xref-aff" href="#aff-4">4</a></li></ol><ol class="affiliation-list"><li class="aff"><a id="aff-1" name="aff-1"></a><address> <sup>1</sup>University of North Carolina at Chapel Hill, Chapel Hill, NC, USA</address></li><li class="aff"><a id="aff-2" name="aff-2"></a><address> <sup>2</sup>ADA Science and Research Institute, Gaithersburg, MD, USA</address></li><li class="aff"><a id="aff-3" name="aff-3"></a><address> <sup>3</sup>Virginia Commonwealth University, Richmond, VA, USA</address></li><li class="aff"><a id="aff-4" name="aff-4"></a><address> <sup>4</sup>Lineberger Comprehensive Cancer Center, Chapel Hill, NC, USA</address></li><li class="aff"><a id="aff-5" name="aff-5"></a><address> <sup>5</sup>Hollings Cancer Center, Charleston, SC, USA</address></li><li class="aff"><a id="aff-6" name="aff-6"></a><address> <sup>6</sup>University of Alabama at Birmingham, Birmingham, AL, USA</address></li><li class="aff"><a id="aff-7" name="aff-7"></a><address> <sup>7</sup>University of North Carolina School of Medicine, Chapel Hill, NC, USA</address></li></ol><ul class="author-notes"><li class="fn" id="fn-1"><p id="p-1">Journal for ImmunoTherapy of Cancer (JITC) preprint. The copyright holder for this preprint are the authors/funders, who have granted JITC permission to display the preprint. All rights reserved. No reuse allowed without permission.</p></li></ul></div></div></div> </div> </div> <div class="panel-separator"></div><div class="panel-pane pane-highwire-markup abstract-with-bc" > <div class="pane-content"> <div class="highwire-markup"><div xmlns="http://www.w3.org/1999/xhtml" id="content-block" xmlns:xhtml="http://www.w3.org/1999/xhtml"><div class="article abstract-view "><span class="highwire-journal-article-marker-start"></span><div class="section abstract" id="abstract-1"><h2>Abstract</h2><div id="sec-1" class="subsection"><p id="p-3"><strong>Background</strong> Novel treatment selection biomarkers are critical to improve outcomes in head and neck squamous cell carcinoma (HNSCC). In this retrospective pilot study, we evaluated, for the first time, a customized, highly multiplexed antibody panel (multi-IF) to identify molecular, cellular, meta-cellular, and network-level biomarkers. We analyzed HPV negative, tobacco associated oral cavity SCC from a multi-institutional, Phase 2 trial (<a class="external-ref external-ref-type-clintrialgov" href="/lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT03529422&atom=%2Fjitc%2F12%2FSuppl_2%2FA240.atom">NCT03529422</a>) evaluating post-operative, concurrent radiation therapy (XRT) with durvalumab (anti-PD-(L)1 therapy) in intermediate-risk HNSCC. We hypothesized that distinct differences exist before treatment initiation at the level of intra- and peritumoral cell populations, associated cell state, and the spatial organization of the tumor-immune microenvironment (‘ecotypes’) between patients who remain disease free (‘responders’) versus those with recurrent disease (‘non-responders’).</p></div><div id="sec-2" class="subsection"><p id="p-4"><strong>Methods</strong> Using a 41-antibody panel for multiplexed imaging, spatial analyses were conducted on pre-treatment tongue and floor of the mouth HNSCC specimens. Human-in-the-loop cell segmentation was first performed using Cellpose-3, resulting in a CELLxFEATURE multi-IF matrix. Next, cells identities were assigned via TACIT (Threshold-based Assignment of Cell Types from Multiplexed Imaging Data) using deep learning of cell type signature markers. The relative proportions of cell types between responders versus non-responders were compared using the Wilcoxon rank-sum test to identify the enrichment of specific cell types in either group. Exhaustion cell state markers were used to evaluate changes in exhaustion pathways. Recurring intratumoral ecotypes representing cell meta-architectures were recovered by Spatial-LDA. The correlation of their occurrences with clinical outcomes was further examined using Kaplan-Meier analysis to identify spatial biomarkers differentiating responders from non-responders.</p></div><div id="sec-3" class="subsection"><p id="p-5"><strong>Results</strong> 9/18 patients enrolled on-trial were included in this analysis including 5 responders versus 4 non-responders. All completed post-operative XRT+durvalumab, per protocol. Clinical and outcome data were collected and have been presented previously. In responders, exhausted T cells were associated with PD-L1+ dendritic cells (DC) and ICOS+ CD20 B Cells. The neighborhood analysis, using a co-occurrence of cells in a single-cell level, showed a higher prevalence of a peritumoral exhaustion in responders, compared to non-responders who presented an innate/exhaustion prevalence. Low tumor cell, high CD4 T-cell, and high DC proportions were associated with improved overall survival (p<0.05, figures 1,2).</p></div><div id="sec-4" class="subsection"><p id="p-6"><strong>Conclusions</strong> We show for the first time that spatial ecotypes within individual tumor microenvironments have distinct spatial organization and are associated with survival (figure 1). Given proof-of-principle, we plan to scale-up to verify our findings. Tumor meta-cellular arrangements serve as a promising biomarker for optimal treatment selection for post-operative therapy in HNSCC.</p></div><div id="sec-5" class="subsection"><p id="p-7"><strong>Trial Registration</strong> NCT03529422.</p></div><div id="sec-6" class="subsection"><p id="p-8"><strong>Ethics Approval</strong> LCCC1725 (<a class="external-ref external-ref-type-clintrialgov" href="/lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT03529422&atom=%2Fjitc%2F12%2FSuppl_2%2FA240.atom">NCT03529422</a>) was a single-arm, multicenter, phase 2 clinical trial conducted at the Lineberger Comprehensive Cancer Center at the University of North Carolina at Chapel Hill, Medical University of South Carolina, University of Alabama at Birmingham. The protocol was approved by the relevant scientific and ethical review boards at each institution. It was conducted under an Investigational New Drug and in accordance with the Declaration of Helsinki.</p><div id="F1" class="fig pos-float odd"><div class="highwire-figure"><div class="fig-inline-img-wrapper"><div class="fig-inline-img"><a href="https://jitc.bmj.com/content/jitc/12/Suppl_2/A240/F1.large.jpg?width=800&height=600&carousel=1" title="a. Multiplex immunofluorescence of 41 antibodies from a responder. Images from lower to higher magnification show the tumor origin, tumor parenchyma, and invasion front represented by an intense immune infiltrate around the area, respectively. The lower inset highlights tumor features, including glandular invasion, lymphovascular invasion, and necrosis. b. Voronoi reconstruction of the slide using the TACIT algorithm to assign cell identities. c. Multiplex immunofluorescence of 41 antibodies in a non-responder. Images from lower to higher magnification show the tumor origin, tumor parenchyma, and invasion front, respectively. The lower inset highlights tumor features, including glandular invasion, lymphovascular invasion, and necrosis. d. Voronoi reconstruction of the slide using the TACIT algorithm to assign cell identities. e. Relative distribution of cell proportions comparison between responders and non- responders. Colored cell types are matched with the Voronoi reconstruction. f. Statistical difference between the immune population prevalence and tumor cells between responders and non-responders. g. Heatmaps of cell expression of cell state markers correlated with cell exhaustion and immunosuppression, showing that non-responders presented a higher prevalence of PD-L1. h. Delaunay triangulation showing the co-occurrence of cells within their coordinates. Responders presented a correlation between tumor cells, dendritic cells, and exhausted immune cells and a correlation between adaptive immune cells and innate immune cells; a distinct co-occurrence pattern was observed in non-responders. i. KM showing the DFS relation with PD-L1/PD-1 interaction and IDO1 correlation. j. Increased PD-L1 expression in T exhausted cells observed in responders compared to non-responders" class="highwire-fragment fragment-images colorbox-load" rel="gallery-fragment-images-848138373" data-figure-caption="<div class="highwire-markup">a. Multiplex immunofluorescence of 41 antibodies from a responder. Images from lower to higher magnification show the tumor origin, tumor parenchyma, and invasion front represented by an intense immune infiltrate around the area, respectively. The lower inset highlights tumor features, including glandular invasion, lymphovascular invasion, and necrosis. b. Voronoi reconstruction of the slide using the TACIT algorithm to assign cell identities. c. Multiplex immunofluorescence of 41 antibodies in a non-responder. Images from lower to higher magnification show the tumor origin, tumor parenchyma, and invasion front, respectively. The lower inset highlights tumor features, including glandular invasion, lymphovascular invasion, and necrosis. d. Voronoi reconstruction of the slide using the TACIT algorithm to assign cell identities. e. Relative distribution of cell proportions comparison between responders and non- responders. Colored cell types are matched with the Voronoi reconstruction. f. Statistical difference between the immune population prevalence and tumor cells between responders and non-responders. g. Heatmaps of cell expression of cell state markers correlated with cell exhaustion and immunosuppression, showing that non-responders presented a higher prevalence of PD-L1. h. Delaunay triangulation showing the co-occurrence of cells within their coordinates. Responders presented a correlation between tumor cells, dendritic cells, and exhausted immune cells and a correlation between adaptive immune cells and innate immune cells; a distinct co-occurrence pattern was observed in non-responders. i. KM showing the DFS relation with PD-L1/PD-1 interaction and IDO1 correlation. j. Increased PD-L1 expression in T exhausted cells observed in responders compared to non-responders</div>" data-icon-position="" data-hide-link-title="0"><span class="hw-responsive-img"><img class="highwire-fragment fragment-image lazyload" alt="Abstract 210 Figure 1" src="data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" data-src="https://jitc.bmj.com/content/jitc/12/Suppl_2/A240/F1.medium.gif" width="310" height="440"/><noscript><img class="highwire-fragment fragment-image" alt="Abstract 210 Figure 1" src="https://jitc.bmj.com/content/jitc/12/Suppl_2/A240/F1.medium.gif" width="310" height="440"/></noscript></span></a></div></div><ul class="highwire-figure-links inline"><li class="download-fig first"><a href="https://jitc.bmj.com/content/jitc/12/Suppl_2/A240/F1.large.jpg?download=true" class="highwire-figure-link highwire-figure-link-download" title="Download Abstract 210 Figure 1" data-icon-position="" data-hide-link-title="0">Download figure</a></li> <li class="new-tab"><a href="https://jitc.bmj.com/content/jitc/12/Suppl_2/A240/F1.large.jpg" class="highwire-figure-link highwire-figure-link-newtab" target="_blank" data-icon-position="" data-hide-link-title="0">Open in new tab</a></li> <li class="download-ppt last"><a href="/highwire/powerpoint/57005" class="highwire-figure-link highwire-figure-link-ppt" data-icon-position="" data-hide-link-title="0">Download powerpoint</a></li> </ul></div><div class="fig-caption" xmlns:xhtml="http://www.w3.org/1999/xhtml"><span class="fig-label">Abstract 210 Figure 1</span> <p id="p-9" class="first-child">a. Multiplex immunofluorescence of 41 antibodies from a responder. Images from lower to higher magnification show the tumor origin, tumor parenchyma, and invasion front represented by an intense immune infiltrate around the area, respectively. The lower inset highlights tumor features, including glandular invasion, lymphovascular invasion, and necrosis. b. Voronoi reconstruction of the slide using the TACIT algorithm to assign cell identities. c. Multiplex immunofluorescence of 41 antibodies in a non-responder. Images from lower to higher magnification show the tumor origin, tumor parenchyma, and invasion front, respectively. The lower inset highlights tumor features, including glandular invasion, lymphovascular invasion, and necrosis. d. Voronoi reconstruction of the slide using the TACIT algorithm to assign cell identities. e. Relative distribution of cell proportions comparison between responders and non- responders. Colored cell types are matched with the Voronoi reconstruction. f. Statistical difference between the immune population prevalence and tumor cells between responders and non-responders. g. Heatmaps of cell expression of cell state markers correlated with cell exhaustion and immunosuppression, showing that non-responders presented a higher prevalence of PD-L1. h. Delaunay triangulation showing the co-occurrence of cells within their coordinates. Responders presented a correlation between tumor cells, dendritic cells, and exhausted immune cells and a correlation between adaptive immune cells and innate immune cells; a distinct co-occurrence pattern was observed in non-responders. i. KM showing the DFS relation with PD-L1/PD-1 interaction and IDO1 correlation. j. Increased PD-L1 expression in T exhausted cells observed in responders compared to non-responders</p><div class="sb-div caption-clear"></div></div></div><div id="F2" class="fig pos-float odd"><div class="highwire-figure"><div class="fig-inline-img-wrapper"><div class="fig-inline-img"><a href="https://jitc.bmj.com/content/jitc/12/Suppl_2/A240/F2.large.jpg?width=800&height=600&carousel=1" title="KM showing overall survival (OS) based on tumor cell proportion (left), CD4+ T cells proportion (middle), and dendritic cells proportion (right). Low tumor cell proportion, high CD4+ T cells proportion, and high dendritic cells proportion associated with improved OS" class="highwire-fragment fragment-images colorbox-load" rel="gallery-fragment-images-848138373" data-figure-caption="<div class="highwire-markup">KM showing overall survival (OS) based on tumor cell proportion (left), CD4+ T cells proportion (middle), and dendritic cells proportion (right). Low tumor cell proportion, high CD4+ T cells proportion, and high dendritic cells proportion associated with improved OS</div>" data-icon-position="" data-hide-link-title="0"><span class="hw-responsive-img"><img class="highwire-fragment fragment-image lazyload" alt="Abstract 210 Figure 2" src="data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" data-src="https://jitc.bmj.com/content/jitc/12/Suppl_2/A240/F2.medium.gif" width="440" height="118"/><noscript><img class="highwire-fragment fragment-image" alt="Abstract 210 Figure 2" src="https://jitc.bmj.com/content/jitc/12/Suppl_2/A240/F2.medium.gif" width="440" height="118"/></noscript></span></a></div></div><ul class="highwire-figure-links inline"><li class="download-fig first"><a href="https://jitc.bmj.com/content/jitc/12/Suppl_2/A240/F2.large.jpg?download=true" class="highwire-figure-link highwire-figure-link-download" title="Download Abstract 210 Figure 2" data-icon-position="" data-hide-link-title="0">Download figure</a></li> <li class="new-tab"><a href="https://jitc.bmj.com/content/jitc/12/Suppl_2/A240/F2.large.jpg" class="highwire-figure-link highwire-figure-link-newtab" target="_blank" data-icon-position="" data-hide-link-title="0">Open in new tab</a></li> <li class="download-ppt last"><a href="/highwire/powerpoint/57162" class="highwire-figure-link highwire-figure-link-ppt" data-icon-position="" data-hide-link-title="0">Download powerpoint</a></li> </ul></div><div class="fig-caption"><span class="fig-label">Abstract 210 Figure 2</span> <p id="p-10" class="first-child">KM showing overall survival (OS) based on tumor cell proportion (left), CD4+ T cells proportion (middle), and dendritic cells proportion (right). 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