Cancers | An Open Access Journal from MDPI

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<option value="hydrogen" > Hydrogen </option> <option value="hydrology" > Hydrology </option> <option value="hygiene" > Hygiene </option> <option value="immuno" > Immuno </option> <option value="idr" > Infectious Disease Reports </option> <option value="informatics" > Informatics </option> <option value="information" > Information </option> <option value="infrastructures" > Infrastructures </option> <option value="inorganics" > Inorganics </option> <option value="insects" > Insects </option> <option value="instruments" > Instruments </option> <option value="iic" > Intelligent Infrastructure and Construction </option> <option value="ijerph" > International Journal of Environmental Research and Public Health (IJERPH) </option> <option value="ijfs" > International Journal of Financial Studies (IJFS) </option> <option value="ijms" > International Journal of Molecular Sciences (IJMS) </option> <option value="IJNS" > International Journal of Neonatal Screening (IJNS) </option> <option value="ijpb" > International Journal of Plant Biology (IJPB) </option> <option value="ijt" > International Journal of Topology </option> <option value="ijtm" > International Journal of Translational Medicine (IJTM) </option> <option value="ijtpp" > International Journal of Turbomachinery, Propulsion and Power (IJTPP) </option> <option value="ime" > International Medical Education (IME) </option> <option value="inventions" > Inventions </option> <option value="IoT" > IoT </option> <option value="ijgi" > ISPRS International Journal of Geo-Information (IJGI) </option> <option value="J" > J </option> <option value="jal" > Journal of Ageing and Longevity (JAL) </option> <option value="jcdd" > Journal of Cardiovascular Development and Disease (JCDD) </option> <option value="jcto" > Journal of Clinical & Translational Ophthalmology (JCTO) </option> <option value="jcm" > Journal of Clinical Medicine (JCM) </option> <option value="jcs" > Journal of Composites Science (J. 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Management (JRFM) </option> <option value="jsan" > Journal of Sensor and Actuator Networks (JSAN) </option> <option value="joma" > Journal of the Oman Medical Association (JOMA) </option> <option value="jtaer" > Journal of Theoretical and Applied Electronic Commerce Research (JTAER) </option> <option value="jvd" > Journal of Vascular Diseases (JVD) </option> <option value="jox" > Journal of Xenobiotics (JoX) </option> <option value="jzbg" > Journal of Zoological and Botanical Gardens (JZBG) </option> <option value="journalmedia" > Journalism and Media </option> <option value="kidneydial" > Kidney and Dialysis </option> <option value="kinasesphosphatases" > Kinases and Phosphatases </option> <option value="knowledge" > Knowledge </option> <option value="labmed" > LabMed </option> <option value="laboratories" > Laboratories </option> <option value="land" > Land </option> <option value="languages" > Languages </option> <option value="laws" > Laws </option> <option value="life" > Life 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Mathematics </option> <option value="medsci" > Medical Sciences </option> <option value="msf" > Medical Sciences Forum </option> <option value="medicina" > Medicina </option> <option value="medicines" > Medicines </option> <option value="membranes" > Membranes </option> <option value="merits" > Merits </option> <option value="metabolites" > Metabolites </option> <option value="metals" > Metals </option> <option value="meteorology" > Meteorology </option> <option value="methane" > Methane </option> <option value="mps" > Methods and Protocols (MPs) </option> <option value="metrics" > Metrics </option> <option value="metrology" > Metrology </option> <option value="micro" > Micro </option> <option value="microbiolres" > Microbiology Research </option> <option value="micromachines" > Micromachines </option> <option value="microorganisms" > Microorganisms </option> <option value="microplastics" > Microplastics </option> <option value="minerals" > Minerals </option> <option value="mining" > Mining </option> <option value="modelling" > Modelling </option> <option value="mmphys" > Modern Mathematical Physics </option> <option value="molbank" > Molbank </option> <option value="molecules" > Molecules </option> <option value="mti" > Multimodal Technologies and Interaction (MTI) </option> <option value="muscles" > Muscles </option> <option value="nanoenergyadv" > Nanoenergy Advances </option> <option value="nanomanufacturing" > Nanomanufacturing </option> <option value="nanomaterials" > Nanomaterials </option> <option value="ndt" > NDT </option> <option value="network" > Network </option> <option value="neuroglia" > Neuroglia </option> <option value="neurolint" > Neurology International </option> <option value="neurosci" > NeuroSci </option> <option value="nitrogen" > Nitrogen </option> <option value="ncrna" > Non-Coding RNA (ncRNA) </option> <option value="nursrep" > Nursing Reports </option> <option value="nutraceuticals" > Nutraceuticals </option> <option value="nutrients" > Nutrients </option> <option value="obesities" > Obesities </option> <option value="oceans" > Oceans </option> <option value="onco" > Onco </option> <option value="optics" > Optics </option> <option value="oral" > Oral </option> <option value="organics" > Organics </option> <option value="organoids" > Organoids </option> <option value="osteology" > Osteology </option> <option value="oxygen" > Oxygen </option> <option value="parasitologia" > Parasitologia </option> <option value="particles" > Particles </option> <option value="pathogens" > Pathogens </option> <option value="pathophysiology" > Pathophysiology </option> <option value="pediatrrep" > Pediatric Reports </option> <option value="pets" > Pets </option> <option value="pharmaceuticals" > Pharmaceuticals </option> <option value="pharmaceutics" > Pharmaceutics </option> <option value="pharmacoepidemiology" > Pharmacoepidemiology </option> <option value="pharmacy" > Pharmacy </option> <option value="philosophies" > Philosophies </option> <option value="photochem" > Photochem </option> <option value="photonics" > Photonics </option> <option value="phycology" > Phycology </option> <option value="physchem" > Physchem </option> <option value="psf" > Physical Sciences Forum </option> <option value="physics" > Physics </option> <option value="physiologia" > Physiologia </option> <option value="plants" > Plants </option> <option value="plasma" > Plasma </option> <option value="platforms" > Platforms </option> <option value="pollutants" > Pollutants </option> <option value="polymers" > Polymers </option> <option value="polysaccharides" > Polysaccharides </option> <option value="populations" > Populations </option> <option value="poultry" > Poultry </option> <option value="powders" > Powders </option> <option value="proceedings" > Proceedings </option> <option value="processes" > Processes </option> <option value="prosthesis" > Prosthesis </option> <option value="proteomes" > Proteomes </option> <option 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<option value="toxins" > Toxins </option> <option value="transplantology" > Transplantology </option> <option value="traumacare" > Trauma Care </option> <option value="higheredu" > Trends in Higher Education </option> <option value="tropicalmed" > Tropical Medicine and Infectious Disease (TropicalMed) </option> <option value="universe" > Universe </option> <option value="urbansci" > Urban Science </option> <option value="uro" > Uro </option> <option value="vaccines" > Vaccines </option> <option value="vehicles" > Vehicles </option> <option value="venereology" > Venereology </option> <option value="vetsci" > Veterinary Sciences </option> <option value="vibration" > Vibration </option> <option value="virtualworlds" > Virtual Worlds </option> <option value="viruses" > Viruses </option> <option value="vision" > Vision </option> <option value="waste" > Waste </option> <option value="water" > Water </option> <option value="wild" > Wild </option> <option value="wind" > Wind </option> <option 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journal of oncology, published semimonthly online by MDPI. The <a href="http://www.iacr.ie/">Irish Association for Cancer Research (IACR)</a>, <a href="https://www.aseica.es/quienes-somos?lang=en">Spanish Association for Cancer Research (ASEICA)</a>, <a href="https://cibm.ugr.es/">Biomedical Research Centre (CIBM)</a>, <a href="https://www.bnos.org.uk/who-are-we/">British Neuro-Oncology Society (BNOS)</a> and <a href="https://getica.org">Spanish Group for Cancer Immuno-Biotherapy (GÉTICA)</a> are affiliated with <em>Cancers</em> and their members receive a discount on the article processing charges.<br /> <ul> <li><strong><span class="label openaccess"><a title="Open Access" href="https://www.mdpi.com/openaccess">Open Access</a></span></strong>— free for readers, with <a href="https://www.mdpi.com/journal/cancers/apc">article processing charges (APC)</a> paid by authors or their institutions.</li> <li><strong>High Visibility:</strong> indexed within <a href="https://www.scopus.com/sourceid/19700188419">Scopus</a>, <a href="https://mjl.clarivate.com/search-results?issn=2072-6694&hide_exact_match_fl=true&utm_source=mjl&utm_medium=share-by-link&utm_campaign=search-results-share-this-journal">SCIE (Web of Science)</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/?term=%22cancers+%28basel%29%22%5Bjour%5D&sort=pubdate">PubMed</a>, <a href="https://www.ncbi.nlm.nih.gov/pmc/journals/2105/">PMC</a>, <a href="https://www.embase.com/login">Embase</a>, <a href="https://sso.cas.org/as/authorization.oauth2?response_type=code&client_id=scifinder-n&redirect_uri=https%3A%2F%2Fscifinder-n.cas.org%2Fpa%2Foidc%2Fcb&state=eyJ6aXAiOiJERUYiLCJhbGciOiJkaXIiLCJlbmMiOiJBMTI4Q0JDLUhTMjU2Iiwia2lkIjoianMiLCJzdWZmaXgiOiJUYWozcGUu">CAPlus / SciFinder</a>, and <a href="https://www.mdpi.com/journal/cancers/indexing">other databases</a>.</li> <li><strong><strong>Journal Rank: </strong></strong>JCR - Q1 (</em>Oncology</em>) / CiteScore - Q1 (</em>Oncology</em>)</li> <li><strong>Rapid Publication:</strong> manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.3 days after submission; acceptance to publication is undertaken in 2.5 days (median values for papers published in this journal in the first half of 2024).</li> <li><strong>Recognition of Reviewers:</strong> reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.</li> <li><strong>Sections:</strong> published in 18 <a href='https://www.mdpi.com/journal/cancers/sections'>topical sections</a>.</li> <li><strong>Companion journals for <em>Cancers</em> include:</strong> <em><a href="https://www.mdpi.com/journal/Radiation">Radiation</a></em> and <em><a href="https://www.mdpi.com/journal/onco">Onco</a></em>.</li> </ul> </div> <div style="margin-bottom: 15px;"> <strong>Impact Factor:</strong> 4.5 (2023); 5-Year Impact Factor: 4.9 (2023) </div> <div> <a href="/journal/cancers/imprint" class="UI_JournalImprintsInfoButton"> <i class="material-icons spaced-link">subject</i> Imprint Information </a>    <a href="/journal/cancers/cancers_flyer.pdf" class="UD_JournalFlyer"> <i class="material-icons spaced-link">get_app</i> Journal Flyer </a>     <a class="oa-link" href="https://www.mdpi.com/about/openaccess"> <i class="material icons spaced-link"></i> Open Access </a>     <strong> ISSN: 2072-6694 </strong> </div> <div style="clear: both;"></div> </div> </div> </div> <div class="content__container content__container--overflow-initial"> <div class="custom-accordion-for-small-screen-link active"> <h2 class="no-padding-left">Latest Articles</h2> </div> <div class="custom-accordion-for-small-screen-content"> <div class="expanding-div collapsed"> <div class="generic-item article-item no-border"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-1530290" aria-controls="drop-supplementary-1530290" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-1530290" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2072-6694/16/23/3970/s1?version=1732639596"> Supplementary File 1 (ZIP, 75 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 765 KiB   </span> <a href="/2072-6694/16/23/3970/pdf?version=1732639596" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Detection of Mismatch Repair Deficiency in Endome-Trial Cancer: Assessment of IHC, Fragment Length Analysis, and Amplicon Sequencing Based MSI Testing" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-6694/16/23/3970">Detection of Mismatch Repair Deficiency in Endome-Trial Cancer: Assessment of IHC, Fragment Length Analysis, and Amplicon Sequencing Based MSI Testing</a> <div class="authors"> by <span class="inlineblock "><strong>Peter Sowter</strong>, </span><span class="inlineblock "><strong>Richard Gallon</strong>, </span><span class="inlineblock "><strong>Christine Hayes</strong>, </span><span class="inlineblock "><strong>Rachel Phelps</strong>, </span><span class="inlineblock "><strong>Gillian Borthwick</strong>, </span><span class="inlineblock "><strong>Shaun Prior</strong>, </span><span class="inlineblock "><strong>Jenny Combe</strong>, </span><span class="inlineblock "><strong>Holly Buist</strong>, </span><span class="inlineblock "><strong>Rachel Pearlman</strong>, </span><span class="inlineblock "><strong>Heather Hampel</strong>, </span><span class="inlineblock "><strong>Paul Goodfellow</strong>, </span><span class="inlineblock "><strong>D. Gareth Evans</strong>, </span><span class="inlineblock "><strong>Emma J. Crosbie</strong>, </span><span class="inlineblock "><strong>Neil Ryan</strong>, </span><span class="inlineblock "><strong>John Burn</strong>, </span><span class="inlineblock "><strong>Mauro Santibanez-Koref</strong> and </span><span class="inlineblock "><strong>Michael S. Jackson</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3970; https://doi.org/10.3390/cancers16233970 (registering DOI) - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> <b>Background/Objectives: </b>Mismatch repair (MMR) deficiency can be indicative of Lynch syndrome (LS) and guide treatment with immune checkpoint inhibitors. Colorectal cancers (CRCs) and endometrial cancers (ECs) are routinely screened to identify LS, primarily using immunohistochemistry (IHC) or microsatellite instability (MSI) testing, but concordance <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3970/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> <b>Background/Objectives: </b>Mismatch repair (MMR) deficiency can be indicative of Lynch syndrome (LS) and guide treatment with immune checkpoint inhibitors. Colorectal cancers (CRCs) and endometrial cancers (ECs) are routinely screened to identify LS, primarily using immunohistochemistry (IHC) or microsatellite instability (MSI) testing, but concordance between these methods is variable in ECs. Here, we investigate this variability in 361 ECs from the Ohio OCCPI/OPTEC (<i>n</i> = 196) and Manchester PETALS (<i>n</i> = 165) trials, where concordance between assays differed significantly. <b>Methods:</b> Samples were re-tested using the amplicon-sequencing-based Newcastle MSI assay (NCL_MSI), and analysed with respect to existing IHC, MSI and MLH1 promoter hypermethylation data. <b>Results:</b> NCL_MSI showed consistency with the Ohio results (94% and 97% concordance with IHC and original MSI assays, respectively) and increased concordance within the Manchester cohort from 78% to 86% (MSI) and 84% (IHC). Among discordant Manchester samples, NCL_MSI was significantly associated with <i>MLH1 </i>promoter methylation status (<i>p</i> = 0.0028) and had the highest concordance with methylation, (62/69 samples, 90%), indicating utility as a screening tool in this tumour type. However, tumours with germline <i>MSH6</i> defects were only detected efficiently with IHC; seven out of eight LS tumours classified as MSS by either MSI assay had isolated MSH6 loss, compared to four out of twelve classified as MSI-H by both (<i>p</i> = 0.028). Furthermore, reduced MSI signal was observed in tumours with isolated MSH6 loss (<i>p</i> = 0.009 Ohio, <i>p</i> = 6.2 × 10<sup>−5</sup> Manchester) and in both ECs and CRCs with germline defects, although this only reached significance in CRCs (<i>p</i> = 0.002). <b>Conclusions:</b> These results provide further evidence that ECs with MSH6 loss in particular and LS tumours in general have an attenuated MSI signal, providing support for current guidelines specifically recommending IHC for LS detection and immune checkpoint therapy assessment in EC. <a href="/2072-6694/16/23/3970">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/cancers/special_issues/PUUDR1882R ">Prevention and Screening in Gynaecological Cancers</a>)<br/> </div> </div> </div> </div> <div class="extending-content content-ready"> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-1530278" aria-controls="drop-supplementary-1530278" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-1530278" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2072-6694/16/23/3969/s1?version=1732638591"> Supplementary File 1 (ZIP, 72 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 17 pages, 530 KiB   </span> <a href="/2072-6694/16/23/3969/pdf?version=1732638590" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Diagnostic Utility of Metalloproteinases from Collagenase Group (MMP-1, MMP-8 and MMP-13) in Biochemical Diagnosis of Ovarian Carcinoma" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-6694/16/23/3969">Diagnostic Utility of Metalloproteinases from Collagenase Group (MMP-1, MMP-8 and MMP-13) in Biochemical Diagnosis of Ovarian Carcinoma</a> <div class="authors"> by <span class="inlineblock "><strong>Aleksandra Kicman</strong>, </span><span class="inlineblock "><strong>Ewa Gacuta</strong>, </span><span class="inlineblock "><strong>Rafał Marecki</strong>, </span><span class="inlineblock "><strong>Michał Stanisław Kicman</strong>, </span><span class="inlineblock "><strong>Monika Kulesza</strong>, </span><span class="inlineblock "><strong>Ewa Klank-Sokołowska</strong>, </span><span class="inlineblock "><strong>Paweł Knapp</strong>, </span><span class="inlineblock "><strong>Marek Niczyporuk</strong>, </span><span class="inlineblock "><strong>Maciej Szmitkowski</strong> and </span><span class="inlineblock "><strong>Sławomir Ławicki</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3969; https://doi.org/10.3390/cancers16233969 (registering DOI) - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Background: Ovarian carcinoma (OC) has an unfavorable prognosis due to lack of screening and an asymptomatic course. New diagnostic methods are being sought to enable earlier diagnosis of this condition. The purpose of this study was to determine the diagnostic utility of collagenases <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3969/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Background: Ovarian carcinoma (OC) has an unfavorable prognosis due to lack of screening and an asymptomatic course. New diagnostic methods are being sought to enable earlier diagnosis of this condition. The purpose of this study was to determine the diagnostic utility of collagenases (MMP-1, MMP-8 and MMP-13) in the diagnosis of OC compared to HE4 and CA125 and the ROMA. Methods: The study group consisted of 120 patients with OC, the control group: 70 patients with benign ovarian lesions (BLs) and 50 healthy women (HS). MMP-1, MMP-8 and MMP-13 were determined by ELISA and HE4 and CA125 by CMIA. Results: OC patients had higher levels of MMP-1 and MMP-13 compared to the BL and HS groups. MMP-1 (SE: 81.66%; SP: 94%; PPV: 97.02%; NPV: 68.11%; AUC: 0.9625) and MMP-13 (SE: 77.50%; SP: 94%; PPV: 96.875%; NPV: 63.51%; AUC: 0.917) showed similar or higher diagnostic values to routine markers (HE4: SE:85%; SP: 92%; PPV: 96.22%; NPV: 71.875%; AUC: 0.943; CA125: SE: 80%; SP: 98%; PPV: 98.96%; NPV: 67.12%; AUC: 0.909) and the ROMA (SE: 90.83%; SP: 94%; PPV: 97.32%; NPV: 81.03%; AUC: 0.955). Performing combined analyses of individual MMPs and MMPs with ROMA was associated with further increases in diagnostic parameters. Conclusions: MMP-1 and MMP-13 have shown preliminary potential as diagnostic markers and auxiliary markers to ROMA in biochemical diagnosis of OC. <a href="/2072-6694/16/23/3969">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/cancers/special_issues/94YKU5XLT6 ">Ovarian Cancer Biomarkers, Diagnostic, and Therapeutic Technologies 2nd Edition</a>)<br/> </div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 13 pages, 761 KiB   </span> <a href="/2072-6694/16/23/3968/pdf?version=1732635803" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Heterogeneous Surface CD79b Expression in Aggressive B-Cell Lymphomas Assessed by Flow Cytometry on Lymph Node Biopsies" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-6694/16/23/3968">Heterogeneous Surface CD79b Expression in Aggressive B-Cell Lymphomas Assessed by Flow Cytometry on Lymph Node Biopsies</a> <div class="authors"> by <span class="inlineblock "><strong>Elena Maiolo</strong>, </span><span class="inlineblock "><strong>Silvia Bellesi</strong>, </span><span class="inlineblock "><strong>Fabrizia Campana</strong>, </span><span class="inlineblock "><strong>Camilla Iacovelli</strong>, </span><span class="inlineblock "><strong>Rosalia Malafronte</strong>, </span><span class="inlineblock "><strong>Gabriele Schiaffini</strong>, </span><span class="inlineblock "><strong>Eleonora Alma</strong>, </span><span class="inlineblock "><strong>Flaminia Bellisario</strong>, </span><span class="inlineblock "><strong>Marcello Viscovo</strong>, </span><span class="inlineblock "><strong>Simone D’Innocenzo</strong>, </span><span class="inlineblock "><strong>Alessia Toscano</strong>, </span><span class="inlineblock "><strong>Francesco D’Alò</strong>, </span><span class="inlineblock "><strong>Valerio De Stefano</strong>, </span><span class="inlineblock "><strong>Luigi Maria Larocca</strong> and </span><span class="inlineblock "><strong>Stefan Hohaus</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3968; https://doi.org/10.3390/cancers16233968 (registering DOI) - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> <b>Background: </b>CD79b is a B-cell-specific antigen that is crucial to the B-cell receptor and is considered a key target for treatment in aggressive B-cell lymphomas. <b>Methods: </b>While immunohistochemical studies have shown widespread expression of CD79b in mature B-cell-derived lymphomas, flow cytometry allows for <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3968/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> <b>Background: </b>CD79b is a B-cell-specific antigen that is crucial to the B-cell receptor and is considered a key target for treatment in aggressive B-cell lymphomas. <b>Methods: </b>While immunohistochemical studies have shown widespread expression of CD79b in mature B-cell-derived lymphomas, flow cytometry allows for precise measurement and differentiation between surface and intracellular localization. <b>Results: </b>In our comparative analysis, we discovered that CD79b expression percentages and mean fluorescence intensity (MFI) were lower in a group of 127 cases of aggressive B-cell lymphomas compared to a control group of benign reactive hyperplasia. We also observed significant variability in the surface expression of CD79b among lymphoma cases, with 18% showing predominantly intracellular positivity. There was a strong correlation between the surface expression of CD79b and clonal light chains.<b> </b>Notably, primary mediastinal B-cell lymphomas exhibited significantly lower surface CD79b expression compared to other lymphoma subtypes (median 0.8% IQR 0–48.5 vs. 80% IQR 24–97, <i>p </i>=<i> </i>0.0005). Furthermore, patients over 60 years old and those with a higher Revised International Prognostic Index (R-IPI) had significantly higher CD79b expression, both of which are associated with a significant benefit from adding an anti-CD79b drug conjugate to first-line chemotherapy in diffuse large B-cell lymphomas. <b>Conclusion: </b>In conclusion, the quantitative flow cytometric analysis of CD79b surface expression in aggressive B-cell lymphomas provides clinically relevant information, highlighting its potential usefulness in guiding therapeutic decisions. <a href="/2072-6694/16/23/3968">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/cancers/sections/Molecular_Cancer_Biology">Molecular Cancer Biology</a>)<br/> </div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 13 pages, 813 KiB   </span> <a href="/2072-6694/16/23/3967/pdf?version=1732631406" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Molecular and Clinical Features of Adrenocortical Tumors in Beckwith–Wiedemann Spectrum" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-6694/16/23/3967">Molecular and Clinical Features of Adrenocortical Tumors in Beckwith–Wiedemann Spectrum</a> <div class="authors"> by <span class="inlineblock "><strong>Diana Carli</strong>, </span><span class="inlineblock "><strong>Federico Rondot</strong>, </span><span class="inlineblock "><strong>Maria Luca</strong>, </span><span class="inlineblock "><strong>Anna Campello</strong>, </span><span class="inlineblock "><strong>Stefano Gabriele Vallero</strong>, </span><span class="inlineblock "><strong>Elisa Tirtei</strong>, </span><span class="inlineblock "><strong>Andrea Gazzin</strong>, </span><span class="inlineblock "><strong>Simona Cardaropoli</strong>, </span><span class="inlineblock "><strong>Francesca Montanari</strong>, </span><span class="inlineblock "><strong>Claudio Graziano</strong>, </span><span class="inlineblock "><strong>Paola Quarello</strong>, </span><span class="inlineblock "><strong>Abu Saadat</strong>, </span><span class="inlineblock "><strong>Angela Sparago</strong>, </span><span class="inlineblock "><strong>Giovanni Battista Ferrero</strong>, </span><span class="inlineblock "><strong>Franca Fagioli</strong> and </span><span class="inlineblock "><strong>Alessandro Mussa</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3967; <a href="https://doi.org/10.3390/cancers16233967">https://doi.org/10.3390/cancers16233967</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Background/Objectives: Adrenocortical tumors (ACTs), including adrenocortical adenoma (ACA) and carcinoma (ACC), represent 0.3–0.4% of pediatric tumors. Beckwith–Wiedemann spectrum (BWSp) confer an increased risk of ACTs, but prognosis, management, and associated molecular characteristics are unclear. Methods: This paper combines a literature review of 54 <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3967/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Background/Objectives: Adrenocortical tumors (ACTs), including adrenocortical adenoma (ACA) and carcinoma (ACC), represent 0.3–0.4% of pediatric tumors. Beckwith–Wiedemann spectrum (BWSp) confer an increased risk of ACTs, but prognosis, management, and associated molecular characteristics are unclear. Methods: This paper combines a literature review of 54 published cases of BWSp-ACT with a report of one newly identified patient, totaling 55 cases with a confirmed BWSp clinical and/or molecular diagnosis. Results: Nineteen patients with ACA, 33 with ACC, and 3 with ACT of uncertain malignant potential (umACT) were included. Twenty patients had uniparental disomy of chromosome 11p15.5 (patUPD11), 11imprinting Center 2 Loss-of-methylation (IC2-LoM), and had 2 11p15 locus duplication. Eleven patients were diagnosed during cancer screening procedures, including two metastatic at diagnosis ACC. Conclusions: Almost half of ACC patients reached the minimum score for clinical BWSp diagnosis only after ACC onset, suggesting that the BWSp score has limited value for the early diagnosis in such a setting. Two patients with metastatic ACC had a histopathological Wieneke score ≤2, not correlating with clinical malignancy and confirming limitations of the current histopathological classification, as previously documented. Ultrasound screening failed identifying the ACC before metastasis in two cases, indicating an urgent need to develop new strategies for screening of ACTs in BWSp. Furthermore, some cases of metastatic ACC exhibited unexpectedly indolent behavior despite being malignant. <a href="/2072-6694/16/23/3967">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/cancers/sections/Pediatric_Oncology">Pediatric Oncology</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3967/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1530052"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1530052"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1530052" data-cycle-prev="#prev1530052" data-cycle-progressive="#images1530052" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1530052-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/cancers/cancers-16-03967/article_deploy/html/images/cancers-16-03967-g001-550.jpg?1732631528" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1530052" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1530052-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03967/article_deploy/html/images/cancers-16-03967-g002-550.jpg?1732631530'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1530052-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03967/article_deploy/html/images/cancers-16-03967-g003-550.jpg?1732631531'><p>Figure 3</p></div></script></div></div><div id="article-1530052-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/cancers/cancers-16-03967/article_deploy/html/images/cancers-16-03967-g001-550.jpg?1732631528" title=" <strong>Figure 1</strong><br/> <p>DNA methylation analysis of IC1 and IC2 regions in blood and tumoral DNA samples as measured by bisulfite pyrosequencing. Control is a blood DNA sample from a normal individual.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3967'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03967/article_deploy/html/images/cancers-16-03967-g002-550.jpg?1732631530" title=" <strong>Figure 2</strong><br/> <p>Distribution of age of diagnosis for ACC in BWSp patients.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3967'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03967/article_deploy/html/images/cancers-16-03967-g003-550.jpg?1732631531" title=" <strong>Figure 3</strong><br/> <p>Distribution of age of diagnosis for ACA in BWSp patients.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3967'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 12 pages, 1038 KiB   </span> <a href="/2072-6694/16/23/3966/pdf?version=1732629571" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Expression of CK17 and SOX2 in Vulvar Intraepithelial Neoplasia: A Comprehensive Analysis of 150 Vulvar Lesions" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-6694/16/23/3966">Expression of CK17 and SOX2 in Vulvar Intraepithelial Neoplasia: A Comprehensive Analysis of 150 Vulvar Lesions</a> <div class="authors"> by <span class="inlineblock "><strong>Nikki B. Thuijs</strong>, </span><span class="inlineblock "><strong>Féline O. Voss</strong>, </span><span class="inlineblock "><strong>Patricia C. Ewing-Graham</strong>, </span><span class="inlineblock "><strong>Shatavisha Dasgupta</strong>, </span><span class="inlineblock "><strong>Johannes Berkhof</strong>, </span><span class="inlineblock "><strong>Johan Bulten</strong>, </span><span class="inlineblock "><strong>Koen van de Vijver</strong> and </span><span class="inlineblock "><strong>Maaike C. G. Bleeker</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3966; <a href="https://doi.org/10.3390/cancers16233966">https://doi.org/10.3390/cancers16233966</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Background: Recently, the immunohistochemical markers cytokeratin 17 (CK17) and SRY-box2 (SOX2) have been evaluated as adjuncts for the diagnosis of high-grade vulvar intraepithelial neoplasia (VIN). In the present study, the aim was to assess CK17 and SOX2 expression in VIN by studying 150 <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3966/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Background: Recently, the immunohistochemical markers cytokeratin 17 (CK17) and SRY-box2 (SOX2) have been evaluated as adjuncts for the diagnosis of high-grade vulvar intraepithelial neoplasia (VIN). In the present study, the aim was to assess CK17 and SOX2 expression in VIN by studying 150 vulvar lesions, originally reported as high-grade VIN and to assess the diagnostic accuracy. Methods: All slides (H&E, p16<sup>INK4a</sup>, p53, Ki-67, CK17, and SOX2 stains) were independently assessed by six pathologists and the final diagnosis was reached in consensus meetings, as follows: 46 human papillomavirus (HPV)-independent VIN (including 30 p53 mutant and 16 p53 wild-type lesions), 58 high-grade squamous intraepithelial lesions (HSILs), 4 low-grade SILs (LSILs), 37 non-dysplastic lesions, and 5 lesions where the histology was inconclusive. Results: CK17 positivity was observed in 100% p53 wild-type HPV-independent VIN, compared to 73% p53 mutant HPV-independent VIN, 14% HSILs, 0% LSILs, and 24% non-dysplastic lesions. SOX2 positivity was observed in 13% p53 wild-type HPV-independent VIN, 43% p53 mutant HPV-independent VIN, 2% HSILs, 0% LSILs, and 3% non-dysplastic lesions. The highest diagnostic accuracy (89%) for HPV-independent VIN was obtained when combining p53 and CK17 immunohistochemistry. The addition of SOX2 did not further increase diagnostic accuracy. Conclusion: To conclude, aside from p53, both CK17 and SOX2 can be of value for reaching an accurate diagnosis of HPV-independent VIN. <a href="/2072-6694/16/23/3966">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/cancers/special_issues/7F4053E86O ">Biomarkers for Treatment Prediction, Prognosis and Early Detection of Gynecologic Cancer</a>)<br/> </div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 28 pages, 1972 KiB   </span> <a href="/2072-6694/16/23/3965/pdf?version=1732628823" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Unraveling the Genetic Heterogeneity of Acute Lymphoblastic Leukemia Based on NGS Applications" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2072-6694/16/23/3965">Unraveling the Genetic Heterogeneity of Acute Lymphoblastic Leukemia Based on NGS Applications</a> <div class="authors"> by <span class="inlineblock "><strong>Valentina Ramírez Maldonado</strong>, </span><span class="inlineblock "><strong>Josgrey Navas Acosta</strong>, </span><span class="inlineblock "><strong>Iván Maldonado Marcos</strong>, </span><span class="inlineblock "><strong>Ángela Villaverde Ramiro</strong>, </span><span class="inlineblock "><strong>Alberto Hernández-Sánchez</strong>, </span><span class="inlineblock "><strong>Jesús M. Hernández Rivas</strong> and </span><span class="inlineblock "><strong>Rocío Benito Sánchez</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3965; <a href="https://doi.org/10.3390/cancers16233965">https://doi.org/10.3390/cancers16233965</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Acute lymphoblastic leukemia (ALL) is a hematological neoplasm characterized by the clonal expansion of abnormal lymphoid precursors in bone marrow, which leads to alterations in the processes of cell differentiation and maturation as a consequence of genetic alterations. The integration of conventional methods, <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3965/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Acute lymphoblastic leukemia (ALL) is a hematological neoplasm characterized by the clonal expansion of abnormal lymphoid precursors in bone marrow, which leads to alterations in the processes of cell differentiation and maturation as a consequence of genetic alterations. The integration of conventional methods, such as cytogenetics and immunophenotyping, and next-generation sequencing (NGS) has led to significant improvements at diagnosis and patient stratification; this has also allowed the discovery of several novel molecular entities with specific genetic variants that may drive the processes of leukemogenesis. Nevertheless, the understanding of the process of leukemogenesis remains a challenge since this disease persists as the most frequent cancer in children; it accounts for approximately one-quarter of adult acute leukemias, and the patient management may take into consideration the high intra- and inter-tumor heterogeneity and the relapse risk due to the various molecular events that can occur during clonal evolution. Some germline variants have been identified as risk factors or have been found to be related to the response to treatment. Therefore, better knowledge of the genetic alterations in B-ALL will have a prognostic impact from the perspective of personalized medicine. This review aims to compare, synthesize, and highlight recent findings concerning ALL obtained through NGS that have led to a better understanding of new molecular subtypes based on immunophenotypic characteristics, mutational profiles, and expression profiles. <a href="/2072-6694/16/23/3965">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/cancers/special_issues/G6QO6QUS2H ">Algorithms and Data Analysis of High Throughput Sequencing in Cancers</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3965/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529982"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529982"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529982" data-cycle-prev="#prev1529982" data-cycle-progressive="#images1529982" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529982-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/cancers/cancers-16-03965/article_deploy/html/images/cancers-16-03965-g001-550.jpg?1732628898" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1529982" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03965/article_deploy/html/images/cancers-16-03965-g002-550.jpg?1732628900'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1529982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03965/article_deploy/html/images/cancers-16-03965-g003-550.jpg?1732628902'><p>Figure 3</p></div></script></div></div><div id="article-1529982-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/cancers/cancers-16-03965/article_deploy/html/images/cancers-16-03965-g001-550.jpg?1732628898" title=" <strong>Figure 1</strong><br/> <p>Milestones in ALL based on the use and implementation of molecular cytogenetic and NGS technologies. GEP: gene expression profile, LOH: loss of heterozygosity, CNAs: copy number alterations, iAMP: intrachromosomal amplification, SNP: single nucleotide polymorphism, GWAS: genome-wide association studies, WGS: whole-genome sequencing, WHO: World Health Organization, MTX: methotrexate, MRD: minimal residual disease, tNGS: targeted NGS.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3965'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03965/article_deploy/html/images/cancers-16-03965-g002-550.jpg?1732628900" title=" <strong>Figure 2</strong><br/> <p>Recent ALL classification and risk subtypes based on genomic/transcriptomic profiles in child patients. As can be seen, genomic classification not only contributes to a better diagnosis but also has prognostic implications. Considerations: The width of the band corresponds to the percentage of cases with each of the alterations. An * indicates the provisional entity status according to the International Consensus Classification (2022).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3965'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03965/article_deploy/html/images/cancers-16-03965-g003-550.jpg?1732628902" title=" <strong>Figure 3</strong><br/> <p>Frequency of recurrent alterations in T-ALL. Based on average values found in the reports analyzed in this review.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3965'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 2 pages, 429 KiB   </span> <a href="/2072-6694/16/23/3964/pdf?version=1732621557" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Correction: Ádány et al. Discrepancies Between the Spatial Distribution of Cancer Incidence and Mortality as an Indicator of Unmet Needs in Cancer Prevention and/or Treatment in Hungary. Cancers 2024, 16, 2917" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Correction</span></div> <a class="title-link" href="/2072-6694/16/23/3964">Correction: Ádány et al. Discrepancies Between the Spatial Distribution of Cancer Incidence and Mortality as an Indicator of Unmet Needs in Cancer Prevention and/or Treatment in Hungary. <i>Cancers</i> 2024, <i>16</i>, 2917</a> <div class="authors"> by <span class="inlineblock "><strong>Róza Ádány</strong>, </span><span class="inlineblock "><strong>Attila Juhász</strong>, </span><span class="inlineblock "><strong>Csilla Nagy</strong>, </span><span class="inlineblock "><strong>Bernadett Burkali</strong>, </span><span class="inlineblock "><strong>Péter Pikó</strong>, </span><span class="inlineblock "><strong>Martin McKee</strong> and </span><span class="inlineblock "><strong>Beatrix Oroszi</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3964; <a href="https://doi.org/10.3390/cancers16233964">https://doi.org/10.3390/cancers16233964</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-full inline"> In the original publication [...] <a href="/2072-6694/16/23/3964">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/cancers/special_issues/J5574VDUTR ">Disparities in Cancer Prevention, Screening, Diagnosis and Management</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3964/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="absgraph cycle-slideshow"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529873-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/cancers/cancers-16-03964/article_deploy/html/images/cancers-16-03964-g001-550.jpg?1732621631" alt="" style="border: 0;"><p>Figure 1</p></div></div></div><div id="article-1529873-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/cancers/cancers-16-03964/article_deploy/html/images/cancers-16-03964-g001-550.jpg?1732621631" title=" <strong>Figure 1</strong><br/> <p>Proportion of incidence and premature mortality due to selected major malignant neoplasms in the Hungarian population, at ages 25–64, 2007–2018.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3964'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-1529894" aria-controls="drop-supplementary-1529894" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-1529894" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2072-6694/16/23/3963/s1?version=1732623483"> Supplementary File 1 (ZIP, 3541 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 27 pages, 5437 KiB   </span> <a href="/2072-6694/16/23/3963/pdf?version=1732670880" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Multiple Myeloma Cells with Increased Proteasomal and ER Stress Are Hypersensitive to ATX-101, an Experimental Peptide Drug Targeting PCNA" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-6694/16/23/3963">Multiple Myeloma Cells with Increased Proteasomal and ER Stress Are Hypersensitive to ATX-101, an Experimental Peptide Drug Targeting PCNA</a> <div class="authors"> by <span class="inlineblock "><strong>Camilla Olaisen</strong>, </span><span class="inlineblock "><strong>Lisa Marie Røst</strong>, </span><span class="inlineblock "><strong>Animesh Sharma</strong>, </span><span class="inlineblock "><strong>Caroline Krogh Søgaard</strong>, </span><span class="inlineblock "><strong>Tiffany Khong</strong>, </span><span class="inlineblock "><strong>Sigrid Berg</strong>, </span><span class="inlineblock "><strong>Mi Jang</strong>, </span><span class="inlineblock "><strong>Aina Nedal</strong>, </span><span class="inlineblock "><strong>Andrew Spencer</strong>, </span><span class="inlineblock "><strong>Per Bruheim</strong> and </span><span class="inlineblock "><strong>Marit Otterlei</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3963; <a href="https://doi.org/10.3390/cancers16233963">https://doi.org/10.3390/cancers16233963</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> <b>Objectives</b>: To examine the regulatory role of PCNA in MM, we have targeted PCNA with the experimental drug ATX-101 in three commercial cell lines (JJN3, RPMI 1660, AMO) and seven in-house patient-derived cell lines with a more primary cell-like phenotype (TK9, 10, <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3963/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> <b>Objectives</b>: To examine the regulatory role of PCNA in MM, we have targeted PCNA with the experimental drug ATX-101 in three commercial cell lines (JJN3, RPMI 1660, AMO) and seven in-house patient-derived cell lines with a more primary cell-like phenotype (TK9, 10, 12, 13, 14, 16 and 18) and measured the systemic molecular effects. <b>Methods</b>: We have used a multi-omics untargeted approach, measuring the gene expression (transcriptomics), a subproteomics approach measuring mainly signalling proteins and proteins in complex with these (signallomics) and quantitative metabolomics. These results are supplemented with traditional analysis, e.g., viability, Western and ELISA analysis. <b>Results</b>: The sensitivity of the cell lines to ATX-101 varied, including between three cell lines derived from the same patient at different times of disease. A trend towards increased sensitivity to ATX-101 during disease progression was detected. Although with different sensitivities, ATX-101 treatment resulted in numerous changes in signalling and metabolite pools in all cell lines. Transcriptomics and signallomics analysis of the TK cell lines revealed that elevated endogenous expression of ribosomal genes, elevated proteasomal and endoplasmic reticulum (ER) stress and low endogenous levels of NAD+ and NADH were associated with ATX-101 hypersensitivity. ATX-101 treatment further enhanced the ER stress, reduced primary metabolism and reduced the levels of the redox pair GSH/GSSG in sensitive cells. Signallome analysis suggested that eleven proteins (TPD52, TNFRS17/BCMA, LILRB4/ILT3, TSG101, ZNRF2, UPF3B, FADS2, C11orf38/SMAP, CGREF1, GAA, COG4) were activated only in the sensitive MM cell lines (TK13, 14 and 16 and JJN3), and not in nine other cancer cell lines or in primary monocytes. These proteins may therefore be biomarkers of cells with activated proteasomal and ER stress even though the gene expression levels of these proteins were not elevated. Interestingly, carfilzomib-resistant cells were at least as sensitive to ATX-101 as the wild-type cells, suggesting both low cross-resistance between ATX-101 and proteasome inhibitors and elevated proteasomal stress in carfilzomib-resistant cells. <b>Conclusions</b>: Our multi-omics approach revealed a vital role of PCNA in regulation of proteasomal and ER stress in MM. <a href="/2072-6694/16/23/3963">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/cancers/sections/Tumor_Microenvironment">Tumor Microenvironment</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3963/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529894"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529894"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529894" data-cycle-prev="#prev1529894" data-cycle-progressive="#images1529894" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529894-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g001-550.jpg?1732671039" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1529894" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529894-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g002-550.jpg?1732671041'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1529894-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g003-550.jpg?1732671045'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1529894-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g004-550.jpg?1732671047'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1529894-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g005-550.jpg?1732671047'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1529894-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g006-550.jpg?1732671049'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1529894-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g007-550.jpg?1732671051'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1529894-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g008-550.jpg?1732671052'><p>Figure 8</p></div></script></div></div><div id="article-1529894-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g001-550.jpg?1732671039" title=" <strong>Figure 1</strong><br/> <p>Systemic changes after ATX-101 treatment of MM cells lead to reduced primary metabolism, increased ER stress and reduced redox capacity. (<b>A</b>) Log2 fold change in proteins detected by MIB assay performed on extract from JJN3 cells treated with ATX-101 (6 µM) for 4 h. Proteins in bold are mentioned specifically in the text. Data shown are mean of three repeated experiments relative to untreated control. Dark-coloured bars indicate significant change from untreated control (Wilcoxon sign rank test). (<b>B</b>) Top up- and downregulated STRING GO (KEGG) pathways based on significantly changed proteins in the MIB assays according to the Wilcoxon sign rank test. (<b>C</b>) Number of DE genes (upper panel) and up/downregulated DE genes in specific pathways (lower panel) in JJN3 cells after 24 h of APIM- or ATX-A (6 µM) treatment. M denotes that the gene product also was detected by the MIB assay. Average of three repeated experiments for 24 h and two repeated experiments for 4 and 8 h (included only if same trend in both) is shown. Dark-coloured circles are DE genes in three out of three replicates, while light-coloured circles are DE genes in two out of three replicates. (<b>D</b>) Average GSH levels after ATX-101 (6 µM: JJN3, RPMI 8226, HL60 and DU145 or 8 µM: HEK293) treatment for 4 and 24 h. Data based on triplicates from two (JJN3, HEK293 and RPMI 8226) or three (DU145 and HL60) repeated experiments. (<b>E</b>) Average HIF1A protein levels (fg/cell) in JJN3 cells 4, 8, 12 and 24 h after treatment with ATX-101 (8 µM) ± SD, <span class="html-italic">n</span> = 3. (<b>F</b>) Average viability relative to untreated control cells measured by the MTT assay in JJN3 cells treated with ATX-101 (6 µM) under atmospheric O<sub>2</sub> tension (normoxia) or 1% O<sub>2</sub> (hypoxia) at 24 h ± SD, <span class="html-italic">n</span> = 10. Data from one representative out of two repeated experiments are shown. * <span class="html-italic">p</span> ≤ 0.5, ** <span class="html-italic">p</span> ≤ 0.01, <span class="html-italic">t</span>-test. These results were previously published in [<a href="#B48-cancers-16-03963" class="html-bibr">48</a>].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3963'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g002-550.jpg?1732671041" title=" <strong>Figure 2</strong><br/> <p>Sensitive TK cells have elevated expression of genes involved in translation (<b>A</b>) Viability measured by the MTT assay relative to untreated control presented for TK9, 10, 12, 13, 14, 16 and 18 cell lines on day 4 after treatment with ATX-101 (4 or 8 µM), melphalan (1 µM) and the combination of ATX-101 (8 µM) and melphalan. The average of 6 replicate wells from one representative out of two repeated experiments is shown. (<b>B</b>) Expression of genes in GO:0022626, cytosolic ribosome and cluster analysis for TK9, 10, 12, 13, 14, 16 and 18. Bolded italic genes have increased expression in TK13 and TK14 compared to TK12. (<b>C</b>) Selected biological processes (GO) of genes downregulated in sensitive (TK13, 14 and 16) relative to not sensitive (TK9, 10, 12 and 18) cells. GO network analysis revealed networks with 153 nodes/126 edges and a PPI enrichment <span class="html-italic">p</span>-value of 1.08 × 10<sup>–9</sup>. A subnetwork where proteins in VEGF (purple)/MAPK (green) and PI3K (yellow) signalling pathways is shown.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3963'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g003-550.jpg?1732671045" title=" <strong>Figure 3</strong><br/> <p>Sensitivity to ATX-101 increases with increasing ER stress. (<b>A</b>) Hierarchical clustering of all quantified protein groups in controls (untreated) TK12, 13, 14 and 16 cells. Cell line over grey box is less sensitive to ATX-101. (<b>B</b>) Top KEGG pathways enriched in clusters 1, 2 and 3 shown in (<b>A</b>), identified by STRING GO analysis. (<b>C</b>) Top KEGG pathways found in the only cluster (same analysis as in (<b>A</b>)) with increasing pull-down of proteins from TK12-16- in ATX-101-treated cells. (<b>D</b>) Cluster analysis of all proteins in untreated and ATX-101-treated cells belonging to GO:003476, response to ER stress. Same heat maps with protein identifications are shown in <a href="#app1-cancers-16-03963" class="html-app">Supplementary Figure S3</a>. Data from 3–5 independent biological replica are shown.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3963'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g004-550.jpg?1732671047" title=" <strong>Figure 4</strong><br/> <p>ATX-101 affects multiple signalling pathways differently in TK13, 14 and 16 versus TK12. (<b>A</b>) Venn diagram of proteins pulled down from ATX-101 (10 µM)-treated TK12, TK13, TK14 and TK16 cell extracts using MIB assay. Only proteins that are significantly changed from untreated control (changed in same direction in extracts from all three repeated experiments, Wilcoxon sign rank test) are shown. Full data set is deposit in PXD033510. (<b>B</b>) Enriched KEGG pathways (STRING) of proteins changed after ATX-101 treatment (10 µM) in in TK13, TK14 and TK16 (120 proteins) relative to untreated control. (<b>C</b>) Heat map of changes in proteins involved in metabolism (only including proteins significantly changed in more than 2 of the sensitive cell lines). Cell line over grey box is less sensitive to ATX-101. (<b>D</b>) Heat map of selected proteins involved in glycolysis, energy metabolism, proteasome, PI3K/AKT/mTOR, MAPK, STAT and apoptosis that changed in opposite directions in TK12 versus the sensitive cell lines (TK13, TK14 and TK16) (proteins significantly changed in more than 1 of the sensitive cell lines are included, for full pathway analysis see <a href="#app1-cancers-16-03963" class="html-app">Supplementary Figure S4</a>). Full data set is deposit in PXD033510.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3963'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g005-550.jpg?1732671047" title=" <strong>Figure 5</strong><br/> <p>Reduced primary metabolism detected after ATX-101 treatment in ATX-101-sensitive cell lines. Log2 fold change (FC) of central carbon metabolites relative to untreated control measured in TK9, TK10, TK12, TK13, TK14 and TK16 cell lines treated with ATX-101 (10 µM) for 4 h. Average given relative to untreated control. Cell lines over grey boxes are less sensitive to ATX-101. Values are from <span class="html-italic">n</span> = 2–3 independent experiments. All sample concentrations are normalised to total protein in the extracts.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3963'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g006-550.jpg?1732671049" title=" <strong>Figure 6</strong><br/> <p>The GSH/GSSG ratio is reduced after ATX-101 treatment in the TK cell lines that also respond to treatment with a metabolic shift. (<b>A</b>) Intracellular GSH levels (nmol/g protein) in untreated and ATX-101-treated (10 µM, 4 h) TK cell lines. Mean ± SD from three replicate cultures. (<b>B</b>) Change relative to untreated control (%) in GSH/GSSH ratio in ATX-101 treated (10 µM, 4 h) TK cell lines. Mean from three replicate cultures. (<b>C</b>) Endogenous intracellular NAD+ and NADH levels (nmol/g protein) in TK cell lines. Mean ± SD from three replicate cultures. TK16 levels &lt; limit of quantification (LOQ). (<b>D</b>) 6PGD activity in TK16 cells treated with ATX-101 (orange, 10 µM), ATX-A (brown, 10 µM) or the 6PGD-inhibitor ebselen (blue, 30 µM) for 4 h relative to activity in untreated control cells. Data displayed are mean ± SD (<span class="html-italic">n</span> = 3). (<b>E</b>) Protein levels of ENO1, 6PGD, GAPDH and PCNA in TK16 cells treated with ATX-101 (orange, 10 µM) or ATX-A (brown, 10 µM) for 24 h. Protein levels are normalised against H3 levels and relative to protein levels in untreated control cells. Data are displayed as mean ± SD (<span class="html-italic">n</span> = 3, ENO1 and 6PGD) or just mean (<span class="html-italic">n</span> = 2, GAPDH and PCNA). Representative Western blots are shown below the bars. (<b>F</b>) Protein levels of AKT and AKT-p in the panel of untreated TK cell lines arranged by increase in sensitivity towards ATX-101. Proteins are normalised to EIF2S1 levels and presented as relative to TK18 levels as mean ± SD (<span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, unpaired two-tailed Student <span class="html-italic">t</span>-test. Representative Western blots are shown below the bars. Raw data and intensity measurements of Western blots in (<b>E</b>) and (<b>F</b>) are shown in <a href="#app1-cancers-16-03963" class="html-app">Supplementary Figures S8 and S9</a>, respectively.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3963'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g007-550.jpg?1732671051" title=" <strong>Figure 7</strong><br/> <p>Potential biomarkers for ATX-101-sensitive MM cells. (<b>A</b>) Venn diagram of proteins pulled down from untreated TK12, TK13, TK14 and TK16 cell extracts using the MIB assay. Only proteins that are significantly changed from untreated control (similar change in extracts from all three repeated experiments, Wilcoxon sign rank test) are shown. Full data set is deposit in PXD033510. (<b>B</b>) Proteins out of the 39 proteins marked with red ring in A which are also detected in JJN3 but not in MCCAR, NB4, HL60, primary human monocytes from three donors [<a href="#B6-cancers-16-03963" class="html-bibr">6</a>], PXD028314, PXD017474), UmUc-3, T24 ([<a href="#B5-cancers-16-03963" class="html-bibr">5</a>] PXD011044), U2OS, H460, A549 [<a href="#B30-cancers-16-03963" class="html-bibr">30</a>] (PXD005286) or TK9 (PXD033531). Only proteins that are significantly changed from untreated control (similar change in extracts from all three repeated experiments, Wilcoxon sign rank test) are included.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3963'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03963/article_deploy/html/images/cancers-16-03963-g008-550.jpg?1732671052" title=" <strong>Figure 8</strong><br/> <p>Proteasome inhibitor-resistant MM cells remain sensitive to ATX-101. Dose response of carfilzomib (0.032 to 2500 nM, blue) (<b>A</b>) and ATX-101 (2–12 μM, orange), (<b>B</b>) in sensitive (AMO-1, blank) and carfilzomib (CFZ)-resistant (AMO-CFZ, diagonal stripes) AMO-1 cells. (<b>C</b>) Single agent and combination treatments of CFZ and ATX-101; 0.8 nM CFZ and 6 μM ATX-101 on AMO-1 ((<b>left</b>) panel) and 250 nM CFZ and 2 μM ATX-101 on AMO-CFZ cells ((<b>right</b>) panel). All data presented are from the PrestoBlue assay on day 4 after treatment. The average of 4–6 replicate wells from one representative out of two repeated experiments is shown. Data are normalised to untreated control.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3963'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-1529864" aria-controls="drop-supplementary-1529864" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-1529864" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2072-6694/16/23/3962/s1?version=1732620767"> Supplementary File 1 (ZIP, 526 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 15 pages, 4785 KiB   </span> <a href="/2072-6694/16/23/3962/pdf?version=1732620766" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Mechanism of miRNAs and miRNA-mRNA Regulatory Networks in Modulating Drug Resistance in HER2-Positive Breast Cancer: An Integrative Bioinformatics Approach" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-6694/16/23/3962">Mechanism of miRNAs and miRNA-mRNA Regulatory Networks in Modulating Drug Resistance in HER2-Positive Breast Cancer: An Integrative Bioinformatics Approach</a> <div class="authors"> by <span class="inlineblock "><strong>Thanh Hoa Vo</strong>, </span><span class="inlineblock "><strong>Edel A. McNeela</strong>, </span><span class="inlineblock "><strong>Orla O’Donovan</strong>, </span><span class="inlineblock "><strong>Sweta Rani</strong> and </span><span class="inlineblock "><strong>Jai Prakash Mehta</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3962; <a href="https://doi.org/10.3390/cancers16233962">https://doi.org/10.3390/cancers16233962</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Background: HER2-positive breast cancer is an aggressive subtype where innate/acquired resistance to targeted drugs remains a challenge. This study aims to uncover the underlying mechanisms of HER2 drug resistance through miRNA analysis and target identification. Methods: MiRNA datasets were systematically retrieved from the <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3962/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Background: HER2-positive breast cancer is an aggressive subtype where innate/acquired resistance to targeted drugs remains a challenge. This study aims to uncover the underlying mechanisms of HER2 drug resistance through miRNA analysis and target identification. Methods: MiRNA datasets were systematically retrieved from the GEO database, and differential expression analysis was conducted for both miRNA and mRNA datasets. Functional analyses were also conducted to validate the identified miRNAs and assess their clinical relevance. Results: We identified 113 differentially expressed miRNAs (DEMs) and 923 target genes. Validation was performed using external mRNA datasets, and intersection with significant genes identified 110 overlapping genes associated with HER2 drug resistance. Further analyses included functional enrichment, construction of a protein–protein interaction (PPI) network, identification of key hub genes such as BCL2, FOS, and CXCR4, and assessment of clinical relevance through survival analysis and immunohistochemistry (IHC) assessments. Conclusions: This integrative approach unveils a complex landscape of HER2 drug resistance in breast cancer, identifying crucial miRNAs, target genes, and significant pathways. The findings offer novel insights into the mechanisms governing drug resistance and highlight the potential for enhancing therapeutic strategies. Future studies are necessary for experimental validation to further explore the complex mechanisms involved. <a href="/2072-6694/16/23/3962">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/cancers/special_issues/G846SWI499 ">New Insights into Targeted Drugs for Breast Cancer (Volume II)</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3962/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529864"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529864"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529864" data-cycle-prev="#prev1529864" data-cycle-progressive="#images1529864" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529864-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/cancers/cancers-16-03962/article_deploy/html/images/cancers-16-03962-g001-550.jpg?1732620886" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1529864" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03962/article_deploy/html/images/cancers-16-03962-g002-550.jpg?1732620888'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1529864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03962/article_deploy/html/images/cancers-16-03962-g003-550.jpg?1732620890'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1529864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03962/article_deploy/html/images/cancers-16-03962-g004-550.jpg?1732620892'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1529864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03962/article_deploy/html/images/cancers-16-03962-g005-550.jpg?1732620893'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1529864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03962/article_deploy/html/images/cancers-16-03962-g006-550.jpg?1732620894'><p>Figure 6</p></div></script></div></div><div id="article-1529864-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/cancers/cancers-16-03962/article_deploy/html/images/cancers-16-03962-g001-550.jpg?1732620886" title=" <strong>Figure 1</strong><br/> <p>Schematic of our study.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3962'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03962/article_deploy/html/images/cancers-16-03962-g002-550.jpg?1732620888" title=" <strong>Figure 2</strong><br/> <p>Summary of DEMs and DEGs across multiple datasets. (<b>A</b>) Volcano plot for miRNA meta-datasets, the result of the meta-analysis. Yellow points indicate downregulated miRNAs, and green points indicate upregulated miRNAs, with an adjusted <span class="html-italic">p</span>-value &lt; 0.05 as the significance threshold. (<b>B</b>–<b>D</b>) Volcano plots for mRNA datasets GSE89216 (<b>B</b>), GSE132055 (<b>C</b>), and GSE121105 (<b>D</b>), showing differential expression analysis. Blue points represent downregulated genes, and red points represent upregulated genes. In all volcano plots, the Log<sub>2</sub>-fold differences are plotted on the horizontal axis, and the −Log10pvalue differences are plotted on the vertical axis. The significance criteria for identifying DEGs are an adjusted <span class="html-italic">p</span>-value &lt; 0.05 and an absolute Log<sub>2</sub>-fold change|Log<sub>2</sub>FC| &gt; 1. (<b>E</b>) Venn diagram depicting the intersection between DEM target genes and DEGs, highlighting genes associated with HER2-targeted drug resistance.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3962'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03962/article_deploy/html/images/cancers-16-03962-g003-550.jpg?1732620890" title=" <strong>Figure 3</strong><br/> <p>Gene Ontology (GO) and KEGG pathway enrichment analysis for significant overlapped genes associated with HER2-targeted drug resistance. (<b>A</b>) KEGG pathway enrichment analysis by EnrichR, where the size of each point represents the number of genes in the term, and color indicates the <span class="html-italic">p</span>-value. The analysis highlights key pathways, structures, and mechanisms potentially underlying resistance. (<b>B</b>–<b>D</b>) GO analyses for molecular functions (<b>B</b>), cellular components (<b>C</b>), and biological processes (<b>D</b>), visualized with ClueGO in Cytoscape. In these plots, color represents different groups, and size corresponds to the number of genes in each term. All terms shown meet a significance threshold of <span class="html-italic">p</span> &lt; 0.05.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3962'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03962/article_deploy/html/images/cancers-16-03962-g004-550.jpg?1732620892" title=" <strong>Figure 4</strong><br/> <p>Protein–protein interaction (PPI) network for HER2-targeted drug resistance. This figure represents the PPI network constructed using STRING, showcasing the interconnectivity among significant genes associated with HER2 drug resistance in breast cancer. Key hub genes like BCL2 are depicted, along with their connections to other relevant proteins such as FOS, CXCR4, CXCL10, IL6R, IL6ST, IRS2, DAPK1, and CDH2. Separate clusters involving PLCB1, ADCY1, and GNAO1 are also visualized.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3962'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03962/article_deploy/html/images/cancers-16-03962-g005-550.jpg?1732620893" title=" <strong>Figure 5</strong><br/> <p>Kaplan–Meier survival plots for hub genes in HER2+ breast cancer. The plots illustrate the overall survival associated with the expression levels of hub genes BCL2, FOS, CXCR4, CXCL10, PLCB1, ADCY1, and GNAO1. Statistically significant associations were found for CXCR4 and FOS, indicating longer overall survival in patients with high expression of these genes. The hazard ratios (HRs) and 95% confidence intervals (CIs) are provided in the plot for each gene.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3962'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03962/article_deploy/html/images/cancers-16-03962-g006-550.jpg?1732620894" title=" <strong>Figure 6</strong><br/> <p>Immunohistochemical (IHC) staining comparison of hub genes in normal and tumor breast tissue. The figure illustrates the differences in staining intensity and patterns for genes including FOS, BCL2, PLCB1, ADCY1, and GNAO1. A noticeable increase in staining in tumor cells for the FOS gene emphasizes its enhanced expression in cancerous tissues, while other genes demonstrate marked or subtle changes. The data for CXCR4 and CXCL10 were not available from the Human Protein Atlas.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3962'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 11 pages, 3456 KiB   </span> <a href="/2072-6694/16/23/3961/pdf?version=1732669255" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Patterns of Childhood Cancer Mortality in Hungary Since the Turn of the Millennium, Including the Two Years of the COVID-19 Pandemic" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-6694/16/23/3961">Patterns of Childhood Cancer Mortality in Hungary Since the Turn of the Millennium, Including the Two Years of the COVID-19 Pandemic</a> <div class="authors"> by <span class="inlineblock "><strong>Kristóf Németh</strong>, </span><span class="inlineblock "><strong>Tibor András Nyári</strong> and </span><span class="inlineblock "><strong>Tamás Lantos</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3961; <a href="https://doi.org/10.3390/cancers16233961">https://doi.org/10.3390/cancers16233961</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> <b>Objectives</b>: We aimed to analyse the pattern of childhood cancer mortality among children under 15 years in Hungary between 2001 and 2021. In addition, annual and cyclical trends were examined. <b>Methods</b>: The number of deaths was obtained from the nationwide population <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3961/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> <b>Objectives</b>: We aimed to analyse the pattern of childhood cancer mortality among children under 15 years in Hungary between 2001 and 2021. In addition, annual and cyclical trends were examined. <b>Methods</b>: The number of deaths was obtained from the nationwide population register over the study period by gender, age group, and region for each year. Data were analysed using the Poisson regression method and cyclic trends were investigated using the Walter–Elwood method. <b>Results</b>: Overall, 14,931 childhood deaths (1092 from cancers) were registered between 2001 and 2021. The cancer mortality risk was significantly higher among boys than girls. A significantly decreasing trend was detected for yearly childhood cancer mortality rates, with an annual IRR of 0.976 (95% CI: 0.966–0.986; <i>p</i> < 0.001). This tendency was not influenced by the pandemic. However, different patterns of seasonal variation were revealed in childhood cancer mortality rates during 2020–2021 and 2001–2019. <b>Conclusions</b>: The annual trend in childhood cancer mortality was not affected by the coronavirus pandemic. However, there was a different pattern of childhood cancer mortality during the pandemic and non-pandemic period in Hungary. Considering the seasonal variation in monthly childhood cancer mortality rates, we hypothesized that environmental factors might play an important role in the aetiology of childhood cancer deaths. <a href="/2072-6694/16/23/3961">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/cancers/sections/Cancer_Epidemiology_Prevention">Cancer Epidemiology and Prevention</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3961/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529823"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529823"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529823" data-cycle-prev="#prev1529823" data-cycle-progressive="#images1529823" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529823-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/cancers/cancers-16-03961/article_deploy/html/images/cancers-16-03961-g001-550.jpg?1732669327" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1529823" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529823-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03961/article_deploy/html/images/cancers-16-03961-g002-550.jpg?1732669329'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1529823-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03961/article_deploy/html/images/cancers-16-03961-g003-550.jpg?1732669331'><p>Figure 3</p></div></script></div></div><div id="article-1529823-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/cancers/cancers-16-03961/article_deploy/html/images/cancers-16-03961-g001-550.jpg?1732669327" title=" <strong>Figure 1</strong><br/> <p>NUTS2 regions of Hungary coloured by age-standardised childhood cancer mortality rates per 100,000 children in the periods (<b>A</b>) 2001–2019 and (<b>B</b>) 2020–2021. Codes: <span class="html-italic">HU11</span>—Budapest; <span class="html-italic">HU12</span>—Pest County, Central Hungary; <span class="html-italic">HU21</span>—Central Transdanubia; <span class="html-italic">HU22</span>—Western Transdanubia; <span class="html-italic">HU23</span>—Southern Transdanubia; <span class="html-italic">HU31</span>—Northern Hungary; <span class="html-italic">HU32</span>—Northern Great Plain; <span class="html-italic">HU33</span>—Southern Great Plain. The maps depicted in the figure are the authors’ own work and were created using R, packages <span class="html-italic">sf</span> (version 1.0-12; <a href="https://cran.r-project.org/web/packages/sf/index.html" target="_blank">https://cran.r-project.org/web/packages/sf/index.html</a>, accessed on 25 September 2024 ) and <span class="html-italic">ggplot2</span> (version 3.3.5; <a href="https://cran.r-project.org/web/packages/ggplot2/index.html" target="_blank">https://cran.r-project.org/web/packages/ggplot2/index.html</a>, accessed on 25 September 2024).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3961'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03961/article_deploy/html/images/cancers-16-03961-g002-550.jpg?1732669329" title=" <strong>Figure 2</strong><br/> <p>Annual trends in childhood cancer mortality rates. (<b>A</b>) All deaths from childhood cancer. (<b>B</b>) Male deaths from childhood cancer. (<b>C</b>) Female deaths from childhood cancer.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3961'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03961/article_deploy/html/images/cancers-16-03961-g003-550.jpg?1732669331" title=" <strong>Figure 3</strong><br/> <p>Cyclic trends in childhood cancer mortality rates in the periods (<b>A</b>) 2001–2010; (<b>B</b>) 2011–2019; and (<b>C</b>) 2020–2021.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3961'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 14 pages, 1945 KiB   </span> <a href="/2072-6694/16/23/3960/pdf?version=1732614448" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Circulating Tumor DNA (ctDNA) Dynamics Predict Early Response to Treatment in Metastasized Gastroesophageal Cancer (mGEC) After 2 Weeks of Systemic Treatment" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Hypothesis</span></div> <a class="title-link" href="/2072-6694/16/23/3960">Circulating Tumor DNA (ctDNA) Dynamics Predict Early Response to Treatment in Metastasized Gastroesophageal Cancer (mGEC) After 2 Weeks of Systemic Treatment</a> <div class="authors"> by <span class="inlineblock "><strong>Stefan Tatalovic</strong>, </span><span class="inlineblock "><strong>Bernhard Doleschal</strong>, </span><span class="inlineblock "><strong>Alexander Kupferthaler</strong>, </span><span class="inlineblock "><strong>Stephan Grundner</strong>, </span><span class="inlineblock "><strong>Jonathan Burghofer</strong>, </span><span class="inlineblock "><strong>Gerald Webersinke</strong>, </span><span class="inlineblock "><strong>Simon Schwendinger</strong>, </span><span class="inlineblock "><strong>Emina Jukic</strong>, </span><span class="inlineblock "><strong>Johannes Zschocke</strong>, </span><span class="inlineblock "><strong>Lorenz Danhel</strong>, </span><span class="inlineblock "><strong>Antonia Kirchweger</strong>, </span><span class="inlineblock "><strong>Lukas Havranek</strong>, </span><span class="inlineblock "><strong>Demetre Shalamberidze</strong>, </span><span class="inlineblock "><strong>Daniel Rezaie</strong>, </span><span class="inlineblock "><strong>Matthias Biebl</strong>, </span><span class="inlineblock "><strong>Holger Rumpold</strong> and </span><span class="inlineblock "><strong>Patrick Kirchweger</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3960; <a href="https://doi.org/10.3390/cancers16233960">https://doi.org/10.3390/cancers16233960</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> mGEC is associated with poor overall survival (OS) of approximately 4–10 months. CtDNA is emerging as a promising prognostic biomarker with high potential for early relapse detection. However, until now, there was little knowledge on serial ctDNA detection and its impact on early <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3960/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> mGEC is associated with poor overall survival (OS) of approximately 4–10 months. CtDNA is emerging as a promising prognostic biomarker with high potential for early relapse detection. However, until now, there was little knowledge on serial ctDNA detection and its impact on early treatment evaluation and prognosis in mGEC. Methods: ctDNA detection (ddPCR) was carried out serially in 37 matched tissue (NGS) patients with mGEC prior to systemic treatment initiation and every two weeks thereafter until restaging (n = 173 samples). The results have been correlated with response to treatment (restaging CT), overall survival (OS), and progression-free survival (PFS). Results: The pretherapeutic detection rate was 77.8%. Response to treatment assessment was correct in 54.2% (pretherapeutically pos./neg.) and 85.7% (dynamics at week 4). Moreover, a decline in ctDNA (MAF in %) below 57.1% of the pretherapeutic value after 2 weeks of systemic treatment was accompanied by a sensitivity of 57.1% and a specificity of 90% (AUC = 0.73) for correct restaging assessment (response evaluation by CT after 3 months) evaluating 76.5% of patients correctly after only 2 weeks. In contrast to mere pretherapeutic ctDNA positivity (<i>p</i> = 0.445), a decline in ctDNA dynamics to under 57.1% of its initial value was significantly associated with OS (4.1 (95% Cl 2.1–6.1) vs. 13.6 (95% CI 10.4–16.6) months, <i>p</i> < 0.001) and PFS (3.2 (1.9–4.5) vs. 9.5 (95% CI 5.5–13.5) months, <i>p</i> = 0.001) after two weeks of treatment. Additionally, the change in detectability from positive pretherapeutic levels to negative during treatment was associated with similar survival as for patients who were always regarded as ctDNA-negative (9.5 (95%Cl 0.4–18.5) vs. 9.6 (95%Cl 1.3–17.9)). The absence of becoming undetectable was associated with worse survival (4.7 months). Conclusions: ctDNA is a promising additional biomarker allowing for early evaluation of response to treatment and saving unevaluated treatment time for patients with mGEC, and could allow for an early change in treatment with anticipated prognostic benefit in the future. <a href="/2072-6694/16/23/3960">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/cancers/special_issues/NJ4ZQ55501 ">Liquid Biopsy in Cancer 2.0</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3960/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529678"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529678"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529678" data-cycle-prev="#prev1529678" data-cycle-progressive="#images1529678" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529678-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/cancers/cancers-16-03960/article_deploy/html/images/cancers-16-03960-g001-550.jpg?1732614576" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1529678" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529678-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03960/article_deploy/html/images/cancers-16-03960-g002-550.jpg?1732614577'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1529678-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03960/article_deploy/html/images/cancers-16-03960-g003-550.jpg?1732614578'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1529678-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03960/article_deploy/html/images/cancers-16-03960-g004-550.jpg?1732614579'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1529678-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03960/article_deploy/html/images/cancers-16-03960-g005-550.jpg?1732614580'><p>Figure 5</p></div></script></div></div><div id="article-1529678-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/cancers/cancers-16-03960/article_deploy/html/images/cancers-16-03960-g001-550.jpg?1732614576" title=" <strong>Figure 1</strong><br/> <p>Consort flow diagram of study population.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3960'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03960/article_deploy/html/images/cancers-16-03960-g002-550.jpg?1732614577" title=" <strong>Figure 2</strong><br/> <p>Mutational pattern of ctDNA targets (ddPCR) used after individual assay design from tumor tissue NGS given as genomic target families (<b>A</b>) and exact targets (<b>B</b>). Abbreviations: ND, not detectable.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3960'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03960/article_deploy/html/images/cancers-16-03960-g003-550.jpg?1732614578" title=" <strong>Figure 3</strong><br/> <p>ctDNA kinetics stratified by response categories (each patients course is indicated as different color): Progressive disease (PD, (<b>A</b>)) and non-progressive disease (non-PD, (<b>B</b>)) with a cut-off line of 57.1%. Each patient’s ctDNA kinetics are represented using distinct colors. CtDNA refers to circulating tumor DNA; non-PD signifies non-progressive disease (including complete response, partial response, and stable disease). In addition to <a href="#cancers-16-03960-f003" class="html-fig">Figure 3</a>, <a href="#cancers-16-03960-t002" class="html-table">Table 2</a> has been included to provide a more comprehensive understanding of the data and graphical content. The table offers a detailed overview of the Mutant Allele Frequency (MAF) kinetics, categorized into two response groups: progressive disease and non-progressive disease. This addition allows for a more precise interpretation of the ctDNA dynamics presented in the figure and facilitates a deeper understanding of the results.; MAF denotes mutant allele frequency; PD indicates progressive disease.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3960'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03960/article_deploy/html/images/cancers-16-03960-g004-550.jpg?1732614579" title=" <strong>Figure 4</strong><br/> <p>The impact of changes in ctDNA detectability (ctDNA pos/neg.) during treatment. Overall survival (OS) of 4 patients with mGEC stratified by their change in circulating tumor DNA (ctDNA) detectability. Patients starting as positive and becoming negative (blue) showed significantly better OS compared to patients starting as positive and staying positive during the whole course of palliative chemotherapy (red).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3960'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03960/article_deploy/html/images/cancers-16-03960-g005-550.jpg?1732614580" title=" <strong>Figure 5</strong><br/> <p>ctDNA dynamics after 2 weeks predict PFS (<b>A</b>) and OS (<b>B</b>). Applying a threshold for circulating tumor DNA (ctDNA) decline under the threshold of 57.1% of its pretherapeutic baseline after 2 weeks of systemic chemotherapy was associated with a significant prognostic impact on progression-free survival (<b>A</b>) and overall survival (<b>B</b>).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3960'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 1427 KiB   </span> <a href="/2072-6694/16/23/3959/pdf?version=1732614414" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Machine Perfusion as a Strategy to Decrease Ischemia-Reperfusion Injury and Lower Cancer Recurrence Following Liver Transplantation" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2072-6694/16/23/3959">Machine Perfusion as a Strategy to Decrease Ischemia-Reperfusion Injury and Lower Cancer Recurrence Following Liver Transplantation</a> <div class="authors"> by <span class="inlineblock "><strong>Karla Bracho Garcia</strong>, </span><span class="inlineblock "><strong>Ahmed Hussein</strong>, </span><span class="inlineblock "><strong>Sangeeta Satish</strong>, </span><span class="inlineblock "><strong>Chase J. Wehrle</strong>, </span><span class="inlineblock "><strong>Omer Karakaya</strong>, </span><span class="inlineblock "><strong>Rebecca Panconesi</strong>, </span><span class="inlineblock "><strong>Keyue Sun</strong>, </span><span class="inlineblock "><strong>Chunbao Jiao</strong>, </span><span class="inlineblock "><strong>Eduardo Fernandes</strong>, </span><span class="inlineblock "><strong>Antonio Pinna</strong>, </span><span class="inlineblock "><strong>Koji Hashimoto</strong>, </span><span class="inlineblock "><strong>Charles Miller</strong>, </span><span class="inlineblock "><strong>Federico Aucejo</strong> and </span><span class="inlineblock "><strong>Andrea Schlegel</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3959; <a href="https://doi.org/10.3390/cancers16233959">https://doi.org/10.3390/cancers16233959</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Liver transplantation (LT) is a key treatment for primary and secondary liver cancers, reducing tumor burden with concurrent improvement of liver function. While significant improvement in survival is noted with LT, cancer recurrence rates remain high. Mitochondrial dysfunction caused by ischemia-reperfusion injury (IRI) <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3959/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Liver transplantation (LT) is a key treatment for primary and secondary liver cancers, reducing tumor burden with concurrent improvement of liver function. While significant improvement in survival is noted with LT, cancer recurrence rates remain high. Mitochondrial dysfunction caused by ischemia-reperfusion injury (IRI) is known to drive tumor recurrence by creating a favorable microenvironment rich in pro-inflammatory and angiogenic factors. Therefore, strategies that decrease reperfusion injury and mitochondrial dysfunction may also decrease cancer recurrence following LT. Machine perfusion techniques are increasingly used in routine clinical practice of LT with improved post-transplant outcomes and increased use of marginal grafts. Normothermic (NMP) and hypothermic oxygenated machine perfusion (HOPE) provide oxygen to ischemic tissues, and impact IRI and potential cancer recurrence through different mechanisms. This article discussed the link between IRI-associated inflammation and tumor recurrence after LT. The current literature was screened for the role of machine perfusion as a strategy to mitigate the risk of cancer recurrence. Upfront NMP (“ischemia free organ transplantation”) and end-ischemic HOPE were shown to reduce hepatocellular carcinoma recurrence in retrospective studies. Three prospective randomized controlled trials are ongoing in Europe to provide robust evidence on the impact of HOPE on cancer recurrence in LT. <a href="/2072-6694/16/23/3959">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/cancers/special_issues/61BLTUB2PA ">The Evolving Treatment and Clinical Trials of Hepatocellular Carcinoma</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3959/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529674"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529674"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529674" data-cycle-prev="#prev1529674" data-cycle-progressive="#images1529674" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529674-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/cancers/cancers-16-03959/article_deploy/html/images/cancers-16-03959-g001-550.jpg?1732614486" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1529674" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529674-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03959/article_deploy/html/images/cancers-16-03959-g002-550.jpg?1732614489'><p>Figure 2</p></div></script></div></div><div id="article-1529674-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/cancers/cancers-16-03959/article_deploy/html/images/cancers-16-03959-g001-550.jpg?1732614486" title=" <strong>Figure 1</strong><br/> <p>Risk factors and mechanism of ischemia-reperfusion injury (IRI) and cancer recurrence. Tumor biology, recipient factors, surgical factors, and donor features all contribute to recurrence of cancer. Tumor biology such as size, number, vascular invasion, and low-grade differentiation all highlight features of an aggressive tumor with increased risk of recurrence. Recipient factors such as older age, higher body mass index (BMI), underlying co-morbidities, and post-transplant immunosuppression play a role in recurrence risk. Surgical factors such as duration of surgery, intraoperative hypotension, and medical treatment may impact the level of IRI. Finally, donor features, such as macro-steatosis, donation after circulatory death (DCD), prolonged warm and cold ischemia, and small graft size may increase risk of IRI and tumor recurrence. IRI is characterized by two phases: ischemia and reperfusion. During ischemia, cell injury and anaerobic respiration occur resulting in acidosis and buildup of sodium, calcium, and respiration substrates, such as succinate. Upon reperfusion, these factors stimulate release of reactive oxygen species (ROS) at mitochondrial complex I and damage-associated molecular patterns (DAMPs) from hepatocytes, hepatic sinusoidal epithelial cells (HSEC), and Kupffer cells (KC), attracting recipient neutrophils to the site. Inflammatory cytokines such as TNF-α, IL-6, and IL-12 are released stimulating a pro-inflammatory milieu consisting of lymphoid cells and macrophages. Increased vascular endothelial growth factor (VEGF), hypoxia inducible factor (HIF-1a), and matrix metalloproteinases (MMP) allow for remodeling and stimulate angiogenesis. This allows for circulating tumor cells (CTC) to migrate and settle, resulting in recurrence. Significant IRI after liver implantation is also seen in lungs with initial inflammation and edema potentially contributing to the elevated HCC recurrence in lungs after liver transplantation. In addition, this pro-inflammatory environment stimulates early liver fibrosis and ischemic biliary strictures. Created with BioRender.com.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3959'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03959/article_deploy/html/images/cancers-16-03959-g002-550.jpg?1732614489" title=" <strong>Figure 2</strong><br/> <p>Decreased tumor recurrence with machine perfusion techniques. (1) Upfront normothermic machine perfusion (NMP) is utilized in “ischemia free liver transplantation” (IFLT). Immediate and continuous NMP without initial cold flush and cold storage maintain mitochondrial and other cell function to prevent further mitochondrial injury as seen with reperfusion under normothermic conditions after standard cold storage (SCS). As some injury already occurs in the donor, some reactive oxygen species (ROS) and flavin mononucleotide (FMN) are released from complex 1. The reduction in additional injury can reduce the downstream inflammation and cancer recurrence. (2) Hypothermic oxygenated perfusion (HOPE) reprograms the mitochondria and improves complex protein activity by restoring the electron transport chain (ETC) function. This allows for clearance of NADH and respiratory substrates such as succinate with concomitant ATP recharging. The direct consequence is a significant decrease in ROS and FMN release from complex 1 at implantation or subsequent NMP. (3) Downstream inflammation is also reduced with less DAMPs and cytokine release and less recruitment of pro-inflammatory cells. The releases of mediators like vascular endothelial growth factor (VEGF), hypoxia inducible factor (HIF-1a), and membrane metalloprotease (MMP) are reduced and there is decreased mobilization and engraftment of circulating tumor cells (CTC). This results in decreased tumor recurrence. Created with BioRender.com.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3959'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 11 pages, 1592 KiB   </span> <a href="/2072-6694/16/23/3958/pdf?version=1732613625" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="The Vascular Endothelial Growth Factor-A121/Vascular Endothelial Growth Factor-A165 Ratio as a Predictor of the Therapeutic Response to Immune Checkpoint Inhibitors in Gastric Cancer" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-6694/16/23/3958">The Vascular Endothelial Growth Factor-A121/Vascular Endothelial Growth Factor-A165 Ratio as a Predictor of the Therapeutic Response to Immune Checkpoint Inhibitors in Gastric Cancer</a> <div class="authors"> by <span class="inlineblock "><strong>Yuki Hamada</strong>, </span><span class="inlineblock "><strong>Kiyonori Tanoue</strong>, </span><span class="inlineblock "><strong>Takaaki Arigami</strong>, </span><span class="inlineblock "><strong>Munekazu Yamakuchi</strong>, </span><span class="inlineblock "><strong>Masashi Okawa</strong>, </span><span class="inlineblock "><strong>Daisuke Matsushita</strong>, </span><span class="inlineblock "><strong>Kazunori Takenouchi</strong>, </span><span class="inlineblock "><strong>Shingo Yamada</strong>, </span><span class="inlineblock "><strong>Drew N. Maywar</strong>, </span><span class="inlineblock "><strong>Chieri Nakayama</strong>, </span><span class="inlineblock "><strong>Yoko Oyama</strong>, </span><span class="inlineblock "><strong>Sadayuki Higashi</strong>, </span><span class="inlineblock "><strong>Chieko Fujisaki</strong>, </span><span class="inlineblock "><strong>Yuto Hozaka</strong>, </span><span class="inlineblock "><strong>Yoshiaki Kita</strong>, </span><span class="inlineblock "><strong>Teruto Hashiguchi</strong> and </span><span class="inlineblock "><strong>Takao Ohtsuka</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3958; <a href="https://doi.org/10.3390/cancers16233958">https://doi.org/10.3390/cancers16233958</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Background/Objectives: The response rate to immune checkpoint inhibitor (ICI) therapy is limited. Further, there is a need to discover biomarkers to predict therapeutic efficacy. The vascular endothelial growth factor (VEGF) is strongly associated with intra-tumoral immunity; however, its utility as a marker remains <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3958/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Background/Objectives: The response rate to immune checkpoint inhibitor (ICI) therapy is limited. Further, there is a need to discover biomarkers to predict therapeutic efficacy. The vascular endothelial growth factor (VEGF) is strongly associated with intra-tumoral immunity; however, its utility as a marker remains unknown. Therefore, our objectives were to examine the isoforms of VEGF and determine whether VEGF levels predict ICI efficacy. Methods: Levels of VEGF isoforms VEGF-A121 and VEGF-A165 were measured in stored serum samples obtained from 30 patients with advanced or recurrent gastric cancer who received nivolumab monotherapy at Kagoshima University Hospital, and the association with prognosis and treatment efficacy was retrospectively analyzed. Results: The serum levels of the total VEGF, VEGF-A121, and VEGF-A165 were not significantly associated with prognosis. However, the ratio of VEGF-A121/VEGF-A165 (VEGF-A121/165) exhibited a statistically significant (<i>p</i> = 0.0088) difference in progression-free survival (PFS) with the low-ratio group having a 67-day prolonged median PFS time. Under univariable analysis, only VEGF-A121/165 values exhibited reduced progression-free survival with statistical significance. When comparing treatment responses in the low (<i>n</i> = 15) and high <i>(n</i> = 15) serum VEGF-A-121/165 groups, RECIST evaluation was 3 to 0 for complete response (CR), 2 to 0 for partial response (PR), 3 to 2 for stable disease (SD), and 3 to 10 for progressive disease (PD). Patients with clinically unsettled PR or SD were classified as non-CR/non-PD (4 vs. 3), with a disease control rate of 80% vs. 33%. Conclusions: The serum VEGF-A121/165 ratio may represent a new, easily measured biomarker for predicting the therapeutic response to ICIs. <a href="/2072-6694/16/23/3958">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/cancers/sections/Cancer_Immunology_Immunotherapy">Cancer Immunology and Immunotherapy</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3958/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529632"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529632"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529632" data-cycle-prev="#prev1529632" data-cycle-progressive="#images1529632" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529632-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/cancers/cancers-16-03958/article_deploy/html/images/cancers-16-03958-g001-550.jpg?1732613732" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1529632" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529632-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03958/article_deploy/html/images/cancers-16-03958-g002-550.jpg?1732613735'><p>Figure 2</p></div></script></div></div><div id="article-1529632-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/cancers/cancers-16-03958/article_deploy/html/images/cancers-16-03958-g001-550.jpg?1732613732" title=" <strong>Figure 1</strong><br/> <p>Kaplan–Meier curves of OS for each protein in patients with gastric cancer treated with nivolumab. The median OS time in the lower-level group was prolonged by (<b>A</b>) +26 days for total-VEGF-A, (<b>B</b>) +68 days for VEGF-A121, (<b>C</b>) +181 days for VEGF-A165, (<b>D</b>) +68 days for VEGF-A121/165 ratio, (<b>F</b>) +105 days for PD-1, and (<b>G</b>) +3.5 days for PD-L1 and shortened by (<b>E</b>) −76.5 days for VEGF-C, but without any case exhibiting statistical significance. Median OS times and <span class="html-italic">p</span>-values of the log-rank tests are given in the figure. OS—overall survival; VEGF—vascular endothelial growth factor; VEGF-A121/165, VEGF-A121-to-VEGF-A165 ratio; PD-1—programmed cell death protein 1; PD-L1—programmed death-ligand 1.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3958'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03958/article_deploy/html/images/cancers-16-03958-g002-550.jpg?1732613735" title=" <strong>Figure 2</strong><br/> <p>Kaplan–Meier curves of PFS for each protein in patients with gastric cancer treated with nivolumab. The median PFS time in the lower-level group was prolonged by (<b>A</b>) +53 days for total-VEGF-A, (<b>B</b>) +53 days for VEGF-A121, (<b>C</b>) +37 days for VEGF-A165, and (<b>D</b>) +67 days for VEGF-A121/165 ratio, and shortened by (<b>E</b>) −40 days for VEGF-C, (<b>F</b>) −15 days for PD-1, and (<b>G</b>) −15 days for PD-L1. Statistical significance was found only for the VEGF-A121/165 ratio, whose log-rank test <span class="html-italic">p</span>-value = 0.0088. All other <span class="html-italic">p</span>-values and all median PFS times are given in the figure. PFS—progression-free survival; VEGF—vascular endothelial growth factor; VEGF-A121/165, VEGF-A121-to-VEGF-A165 ratio; PD-1—programmed cell death protein 1; PD-L1—programmed death-ligand 1.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3958'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 23 pages, 1814 KiB   </span> <a href="/2072-6694/16/23/3957/pdf?version=1732613653" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="The Emerging Roles of the Stress Epigenetic Reader LEDGF/p75 in Cancer Biology and Therapy Resistance: Mechanisms and Targeting Opportunities" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2072-6694/16/23/3957">The Emerging Roles of the Stress Epigenetic Reader LEDGF/p75 in Cancer Biology and Therapy Resistance: Mechanisms and Targeting Opportunities</a> <div class="authors"> by <span class="inlineblock "><strong>Greisha L. Ortiz-Hernandez</strong>, </span><span class="inlineblock "><strong>Evelyn S. Sanchez-Hernandez</strong>, </span><span class="inlineblock "><strong>Pedro T. Ochoa</strong> and </span><span class="inlineblock "><strong>Carlos A. Casiano</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3957; <a href="https://doi.org/10.3390/cancers16233957">https://doi.org/10.3390/cancers16233957</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The lens epithelium derived growth factor of 75 kD (LEDGF/p75) is a transcription co-activator and epigenetic reader that has emerged as a stress oncoprotein in multiple human cancers. Growing evidence indicates that it promotes tumor cell survival against certain therapeutic drugs. The amino <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3957/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The lens epithelium derived growth factor of 75 kD (LEDGF/p75) is a transcription co-activator and epigenetic reader that has emerged as a stress oncoprotein in multiple human cancers. Growing evidence indicates that it promotes tumor cell survival against certain therapeutic drugs. The amino (N)-terminal region of LEDGF/p75 contains a PWWP domain that reads methylated histone marks, critical for recognizing transcriptionally active chromatin sites. Its carboxyl (C)-terminus has an integrase binding domain (IBD) that serves as the binding site for the HIV-1 integrase and multiple oncogenic transcription factors. Acting as hubs for protein-protein interactions, both domains facilitate the tethering of oncogenic transcription factors and regulators to active chromatin to regulate mRNA splicing, promote DNA repair, and enhance the expression of stress and cancer-related genes that contribute to tumor cell aggressiveness and chemoresistance. This review summarizes our current knowledge of the emerging roles of LEDGF/p75 in cancer biology and therapy resistance and discusses its potential as a novel oncotherapeutic target in combinatorial treatments. <a href="/2072-6694/16/23/3957">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/cancers/sections/Cancer_Therapy">Cancer Therapy</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3957/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529634"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529634"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529634" data-cycle-prev="#prev1529634" data-cycle-progressive="#images1529634" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529634-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/cancers/cancers-16-03957/article_deploy/html/images/cancers-16-03957-g001-550.jpg?1732613808" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1529634" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529634-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03957/article_deploy/html/images/cancers-16-03957-g002-550.jpg?1732613808'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1529634-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03957/article_deploy/html/images/cancers-16-03957-g003-550.jpg?1732613810'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1529634-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03957/article_deploy/html/images/cancers-16-03957-g004-550.jpg?1732613811'><p>Figure 4</p></div></script></div></div><div id="article-1529634-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/cancers/cancers-16-03957/article_deploy/html/images/cancers-16-03957-g001-550.jpg?1732613808" title=" <strong>Figure 1</strong><br/> <p>LEDGF domains and functions. The N-terminal region of LEDGF/p75 (aa 1–530) and its short variant p52 (aa 1–325) contains a PWWP domain, three charged regions (CR), nuclear localization signal (NLS), and AT-hooks (ATH). The C-terminal region of LEDGF/p75 (aa 325–530) contains the HIV integrase binding domain (IBD, aa 347–429), which is targeted by autoantibodies in certain individuals. The IBD is absent in LEDGF/p52, which instead has a unique 8-amino acid stretch called the carboxy-terminal tail (CTT, aa 326–333). The functions of both domains are listed.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3957'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03957/article_deploy/html/images/cancers-16-03957-g002-550.jpg?1732613808" title=" <strong>Figure 2</strong><br/> <p>Domain structure of LEDGF/p75 and HRP-2. Both proteins have PWWP and IBD domains as well as AT-hook (ATH) motifs. HRP-2 has a conserved homology region III (HR3) not present in LEDGF/p75. The PWWP and IBD domains have equivalent functions in both proteins.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3957'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03957/article_deploy/html/images/cancers-16-03957-g003-550.jpg?1732613810" title=" <strong>Figure 3</strong><br/> <p>LEDGF/p75 (PSIP1) interaction module for the PWWP and IBD domains generated by STRING analysis (<a href="https://string-db.org" target="_blank">https://string-db.org</a>, accessed on 9 October 2024).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3957'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03957/article_deploy/html/images/cancers-16-03957-g004-550.jpg?1732613811" title=" <strong>Figure 4</strong><br/> <p>Multiple functions of LEDGF/p75 in cancer and potential as oncotherapeutic target to attenuate tumor aggressiveness. Interactions of LEDGF/p75 with multiple proteins at its PWWP domain are critical for DNA damage repair through homologous recombination, regulating mRNA splicing, chromatin remodeling, and reading of active chromatin. Interactions at its IBD domain with oncogenic transcription factors are critical for the upregulation of gene pathways associated with cancer progression and aggressiveness. Targeting LEDGF/p75 with specific inhibitors, alone or in combination with inhibitors of its transcriptional network and standard chemotherapeutic drugs could be a promising strategy to attenuate tumor aggressive properties, particularly resistance to chemotherapy.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3957'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-1529506" aria-controls="drop-supplementary-1529506" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-1529506" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2072-6694/16/23/3956/s1?version=1732610422"> Supplementary File 1 (ZIP, 136 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 14 pages, 563 KiB   </span> <a href="/2072-6694/16/23/3956/pdf?version=1732610421" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Mesothelioma of the Tunica Vaginalis Testis: Diagnostic and Therapeutic Management: A Comprehensive Review, 1982–2024" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2072-6694/16/23/3956">Mesothelioma of the Tunica Vaginalis Testis: Diagnostic and Therapeutic Management: A Comprehensive Review, 1982–2024</a> <div class="authors"> by <span class="inlineblock "><strong>Simona Stella</strong>, </span><span class="inlineblock "><strong>Giovanni Luca Ceresoli</strong>, </span><span class="inlineblock "><strong>Barbara Dallari</strong>, </span><span class="inlineblock "><strong>Rosalba Barile</strong>, </span><span class="inlineblock "><strong>Fabio Maisenti</strong>, </span><span class="inlineblock "><strong>Sabrina Rugarli</strong>, </span><span class="inlineblock "><strong>Alessandro Marinaccio</strong>, </span><span class="inlineblock "><strong>Dario Consonni</strong> and </span><span class="inlineblock "><strong>Carolina Mensi</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3956; <a href="https://doi.org/10.3390/cancers16233956">https://doi.org/10.3390/cancers16233956</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Background: Mesothelioma of the tunica vaginalis testis (MTVT) is an extremely rare and aggressive cancer. The diagnosis and management of MTVT is complex, and no standard treatment protocol is available. Methods: We conducted a systematic literature review from 1 January 1982 to 14 <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3956/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Background: Mesothelioma of the tunica vaginalis testis (MTVT) is an extremely rare and aggressive cancer. The diagnosis and management of MTVT is complex, and no standard treatment protocol is available. Methods: We conducted a systematic literature review from 1 January 1982 to 14 March 2024 using PubMed to collect all the available case reports and case series. A descriptive analysis of patient characteristics with clinical presentation, diagnostic work-up, therapeutic management, and past asbestos exposure was performed. Survival times of patients treated with different therapeutic approaches were evaluated. Results: Overall, 289 patients with MTVT were included in our analysis. The most common clinical presentations were scrotal/testicular swelling or mass (187 patients, 65%) and the presence of hydrocele (159, 55%). Imaging evaluation, mostly with ultrasonography or CT scan, was reported in two-thirds of cases. Radical surgery (216 patients, 75%) with orchiectomy and, in select cases, hemiscrotectomy and inguinal lymphadenectomy was the most frequent therapeutic approach. A minority of patients (49, 17%) received adjuvant therapy after surgery (radiotherapy, chemotherapy, or a combination of the two), with no evidence of survival improvement. Conclusions: No standard guidelines for MTVT are available so far. Radical surgery following accurate radiological staging should be the mainstay of treatment. The role of adjuvant treatments remains undefined. Due to its rarity, MTVT should be treated in referral centers, and patients’ data should be collected in a dedicated register in order to improve the knowledge of this exceedingly rare disease and establish optimal diagnostic and therapeutic management. <a href="/2072-6694/16/23/3956">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/cancers/sections/Clinical_Research_Cancer">Clinical Research of Cancer</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3956/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="absgraph cycle-slideshow"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529506-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/cancers/cancers-16-03956/article_deploy/html/images/cancers-16-03956-g001-550.jpg?1732610565" alt="" style="border: 0;"><p>Figure 1</p></div></div></div><div id="article-1529506-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/cancers/cancers-16-03956/article_deploy/html/images/cancers-16-03956-g001-550.jpg?1732610565" title=" <strong>Figure 1</strong><br/> <p>Flow chart of selection of studies on cases of mesothelioma of the tunica vaginalis testis.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3956'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-1529526" aria-controls="drop-supplementary-1529526" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-1529526" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2072-6694/16/23/3955/s1?version=1732610773"> Supplementary File 1 (ZIP, 2822 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 15 pages, 2498 KiB   </span> <a href="/2072-6694/16/23/3955/pdf?version=1732610771" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Exploring Genomic Biomarkers for Pembrolizumab Response: A Real-World Approach and Patient Similarity Network Analysis Reveal DNA Response and Repair Gene Mutations as a Signature" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-6694/16/23/3955">Exploring Genomic Biomarkers for Pembrolizumab Response: A Real-World Approach and Patient Similarity Network Analysis Reveal DNA Response and Repair Gene Mutations as a Signature</a> <div class="authors"> by <span class="inlineblock "><strong>Marco Filetti</strong>, </span><span class="inlineblock "><strong>Mario Occhipinti</strong>, </span><span class="inlineblock "><strong>Alessio Cirillo</strong>, </span><span class="inlineblock "><strong>Fabio Scirocchi</strong>, </span><span class="inlineblock "><strong>Alessio Ugolini</strong>, </span><span class="inlineblock "><strong>Raffaele Giusti</strong>, </span><span class="inlineblock "><strong>Pasquale Lombardi</strong>, </span><span class="inlineblock "><strong>Gennaro Daniele</strong>, </span><span class="inlineblock "><strong>Andrea Botticelli</strong>, </span><span class="inlineblock "><strong>Giuseppe Lo Russo</strong>, </span><span class="inlineblock "><strong>Filippo De Braud</strong>, </span><span class="inlineblock "><strong>Paolo Marchetti</strong>, </span><span class="inlineblock "><strong>Marianna Nuti</strong>, </span><span class="inlineblock "><strong>Elisabetta Ferretti</strong>, </span><span class="inlineblock "><strong>Lorenzo Farina</strong>, </span><span class="inlineblock "><strong>Aurelia Rughetti</strong> and </span><span class="inlineblock "><strong>Manuela Petti</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3955; <a href="https://doi.org/10.3390/cancers16233955">https://doi.org/10.3390/cancers16233955</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> <b>Purpose</b>: Single-agent immune checkpoint inhibitor (IO) therapy is the standard for non-oncogene-addicted advanced non-small cell lung cancer (aNSCLC) with PD-L1 tumor proportion score ≥ 50%. Smoking-induced harm generates high tumor mutation burden (H-TMB) in smoking patients (S-pts), while never-smoking patients (NS-pts) typically <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3955/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> <b>Purpose</b>: Single-agent immune checkpoint inhibitor (IO) therapy is the standard for non-oncogene-addicted advanced non-small cell lung cancer (aNSCLC) with PD-L1 tumor proportion score ≥ 50%. Smoking-induced harm generates high tumor mutation burden (H-TMB) in smoking patients (S-pts), while never-smoking patients (NS-pts) typically have low TMB (L-TMB) and are unresponsive to IO. However, the molecular characterization of NS-pts with H-TMB remains unclear. <b>Experimental design</b>: Clinical data of 142 aNSCLC patients with PD-L1 ≥ 50% treated with first line pembrolizumab were retrospectively collected. Next-generation sequencing was performed using the FoundationOne<sup>®</sup>CDx assay to correlate genomic alterations with clinical characteristics and response outcomes. Detected mutations were classified into eleven main pathways and enrichment analysis identified patient subgroups based on mutated pathways. Additionally, a patient similarity network was constructed to analyze molecular characterization. Results were validated using data from 853 aNSCLC patients in POPLAR and OAK trials. <b>Results</b>: Among the patients, S-pts had higher TMB than NS-pts. Interestingly, 11 (8%) NS-pts exhibited H-TMB and were enriched in β-catenin/Wnt and DDR pathway mutations. DDR pathway mutations were confirmed to be enriched in NS-pts with H-TMB using data from POPLAR and OAK trials. In the real-world cohort, the NS/H-TMB subgroup with DDR pathway mutations demonstrated improved IO outcome. Patient similarity network analysis confirmed the clustering of NS/H-TMB patients with DDR mutations and their association with improved overall survival in both the real-world cohort and the trials. <b>Conclusions</b>: The DDR signature has a potential role as an additional generator of H-TMB in NS-pts. This subgroup of IO-responsive NS-pts may have better prognosis. Our findings suggest that DDR-based mutational profiling may help identify NS-pts who could benefit from IO therapy. <a href="/2072-6694/16/23/3955">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/cancers/sections/Cancer_Immunology_Immunotherapy">Cancer Immunology and Immunotherapy</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3955/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529526"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529526"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529526" data-cycle-prev="#prev1529526" data-cycle-progressive="#images1529526" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529526-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/cancers/cancers-16-03955/article_deploy/html/images/cancers-16-03955-g001-550.jpg?1732610888" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1529526" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529526-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03955/article_deploy/html/images/cancers-16-03955-g002-550.jpg?1732610888'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1529526-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03955/article_deploy/html/images/cancers-16-03955-g003-550.jpg?1732610891'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1529526-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03955/article_deploy/html/images/cancers-16-03955-g004-550.jpg?1732610894'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1529526-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03955/article_deploy/html/images/cancers-16-03955-g005-550.jpg?1732610895'><p>Figure 5</p></div></script></div></div><div id="article-1529526-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/cancers/cancers-16-03955/article_deploy/html/images/cancers-16-03955-g001-550.jpg?1732610888" title=" <strong>Figure 1</strong><br/> <p>TMB values according to the smoking status population of the real-world aNSCLC patient cohort (142 pts). The violin plots depict the TMB values (Mut/Mb) in S-pts (111) and NS-pts (31). Median values are indicated as red dashes.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3955'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03955/article_deploy/html/images/cancers-16-03955-g002-550.jpg?1732610888" title=" <strong>Figure 2</strong><br/> <p>Clinical responses to pembrolizumab in H-TMB patients identified according to smoking status (S- vs. NS-patients): Kaplan-Meier curves for overall survival (OS) (panel <b>A</b>) and bar diagram showing ORR values (panel <b>B</b>).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3955'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03955/article_deploy/html/images/cancers-16-03955-g003-550.jpg?1732610891" title=" <strong>Figure 3</strong><br/> <p>(<b>A</b>) Patient similarity network of the never-smoking cohort. Nodes color codes for the TMB level: orange for TMB &gt; 10 Mut/Mb, yellow for TMB ≤ 10 Mut/Mb. (<b>B</b>) Kruskal–Wallis test results on the effect of TMB. (<b>C</b>) The four identified communities are shown with the associated mutated pathways profile: bar diagrams of the percentage of patients characterized by at least one mutation in each of the analyzed pathways (1-Cell cycle-pathway, 2-Hippo pathway, 3-Myc pathway, 4-Notch pathway, 5-Oxidative stress/Nrf2 pathway, 6-PI3K pathway, 7-RTK/RAS/MAP pathway, 8-TGF beta pathway, 9-p53 pathway, 10-beta-catenin/Wnt pathway, and 11-DDR pathway).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3955'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03955/article_deploy/html/images/cancers-16-03955-g004-550.jpg?1732610894" title=" <strong>Figure 4</strong><br/> <p>(<b>A</b>) Patient similarity network of the smoking cohort. Nodes color codes for the TMB level: orange for TMB &gt; 10 Mut/Mb, yellow for TMB ≤ 10 Mut/Mb. (<b>B</b>) Kruskal–Wallis test results on the effect of TMB. (<b>C</b>) The four identified communities are shown with the associated mutated pathways profile: bar diagrams of the percentage of patients characterized by at least one mutation in each of the analyzed pathways (1-Cell cycle-pathway, 2-Hippo pathway, 3-Myc pathway, 4-Notch pathway, 5-Oxidative stress/Nrf2 pathway, 6-PI3K pathway, 7-RTK/RAS/MAP pathway, 8-TGF beta pathway, 9-p53 pathway, 10-beta-catenin/Wnt pathway, and 11-DDR pathway).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3955'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03955/article_deploy/html/images/cancers-16-03955-g005-550.jpg?1732610895" title=" <strong>Figure 5</strong><br/> <p>Mutated pathways profile of the OAK/POPLAR NS community (panel <b>A</b>) correlated with the mutational profile of the real-world NS C1 (panel <b>B</b>): Spearman correlation, ρ = 0.727. The bar diagrams show the percentage of patients characterized by at least one mutation in each of the analyzed pathways (1—Cell cycle-pathway, 2—Hippo pathway, 3—Myc pathway, 4—Notch pathway, 5—Oxidative stress/Nrf2 pathway, 6—PI3K pathway, 7—RTK/RAS/MAP pathway, 8—TGF-β pathway, 9—p53 pathway, 10—β-catenin/Wnt pathway, and 11—DDR pathway). In the network community representation, nodes represent the patients and their color codes for the TMB level: orange for TMB &gt; 10 Mut/Mb, yellow for TMB ≤ 10 Mut/Mb.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3955'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-1529409" aria-controls="drop-supplementary-1529409" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-1529409" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2072-6694/16/23/3954/s1?version=1732604946"> Supplementary File 1 (ZIP, 128 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 17 pages, 4481 KiB   </span> <a href="/2072-6694/16/23/3954/pdf?version=1732604946" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Simulated Galactic Cosmic Radiation Exposure-Induced Mammary Tumorigenesis in ApcMin/+ Mice Coincides with Activation of ERα-ERRα-SPP1 Signaling Axis" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-6694/16/23/3954">Simulated Galactic Cosmic Radiation Exposure-Induced Mammary Tumorigenesis in <i>Apc</i><sup>Min/+</sup> Mice Coincides with Activation of ERα-ERRα-SPP1 Signaling Axis</a> <div class="authors"> by <span class="inlineblock "><strong>Kamendra Kumar</strong>, </span><span class="inlineblock "><strong>Jerry Angdisen</strong>, </span><span class="inlineblock "><strong>Jinwenrui Ma</strong>, </span><span class="inlineblock "><strong>Kamal Datta</strong>, </span><span class="inlineblock "><strong>Albert J. Fornace, Jr.</strong> and </span><span class="inlineblock "><strong>Shubhankar Suman</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3954; <a href="https://doi.org/10.3390/cancers16233954">https://doi.org/10.3390/cancers16233954</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Background: Exposure to galactic cosmic radiation (GCR) is a breast cancer risk factor for female astronauts on deep-space missions. However, the specific signaling mechanisms driving GCR-induced breast cancer have not yet been determined. Methods: This study aimed to investigate the role of the <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3954/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Background: Exposure to galactic cosmic radiation (GCR) is a breast cancer risk factor for female astronauts on deep-space missions. However, the specific signaling mechanisms driving GCR-induced breast cancer have not yet been determined. Methods: This study aimed to investigate the role of the estrogen-induced ERα-ERRα-SPP1 signaling axis in relation to mammary tumorigenesis in female <i>Apc</i><sup>Min/+</sup> mice exposed to simulated GCR (GCRsim) at 100–110 days post-exposure. Results: In GCRsim-exposed mice, we observed marked elevations in serum estradiol, increased ductal overgrowth, ERα activation, and upregulation of ERα target genes with pro-tumorigenic functions in mammary tissues that was coupled with a higher mammary tumorigenesis, relative to control. Additionally, the ERα target gene <i>Esrra</i>, which encodes ERRα, was also upregulated along with its oncogenic target gene <i>Spp1</i>, indicating the activation of the ERα-ERRα-SPP1 axis in mouse mammary tissues after GCRsim exposure. Using a human tissue microarray and human breast cancer gene expression analysis, we also highlighted the conserved nature of the ERα-ERRα-SPP1 signaling in human breast cancer development. Conclusions: We identified the ERα-ERRα-SPP1 signaling axis as a potential key mediator in GCR-induced breast cancer with conserved activation in human breast cancer. These findings suggest that targeting this pathway could serve as a potential target for therapeutic intervention to safeguard female astronauts during and after a prolonged outer space mission. <a href="/2072-6694/16/23/3954">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/cancers/special_issues/33Q81IUBU9 ">Radiation Exposure, Inflammation and Cancers</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3954/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529409"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529409"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529409" data-cycle-prev="#prev1529409" data-cycle-progressive="#images1529409" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529409-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g001-550.jpg?1732605018" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1529409" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529409-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g002-550.jpg?1732605021'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1529409-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g003-550.jpg?1732605023'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1529409-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g004-550.jpg?1732605025'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1529409-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g005-550.jpg?1732605027'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1529409-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g006-550.jpg?1732605031'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1529409-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g007-550.jpg?1732605031'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1529409-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g008-550.jpg?1732605032'><p>Figure 8</p></div></script></div></div><div id="article-1529409-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g001-550.jpg?1732605018" title=" <strong>Figure 1</strong><br/> <p>GCRsim exposure promotes mammary tissue overgrowth and increased duct density. (<b>A</b>) Schematic representation of the experimental setup depicting chronic exposure to GCRsim, using a 33-ion mixed beam to simulate the deep-space environment. Experimental animals were exposed to 2.08 cGy per day, 6 days per week, for 4 weeks, resulting in a cumulative dose of 50 cGy. (<b>B</b>) Representative images of mammary tissues: whole-mount micrographs (scale bar = 500 µm) show the extent of ductal branching, while H&amp;E-stained sections (scale bar = 100 µm) highlight histological features. (<b>C</b>) Quantification of ductal density, expressed as the number of ducts per high-power microscopic field (HPF). (<b>D</b>) Representative H&amp;E-stained normal mammary gland and tumor samples. (<b>E</b>) Comparison of mammary tumor incidence between control and GCRsim-exposed animals, showing increased tumor formation in the 50 cGy irradiated GCRsim group. Statistically significant difference (<span class="html-italic">p</span> &lt; 0.05) relative to the control group is denoted by an asterisk (*).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3954'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g002-550.jpg?1732605021" title=" <strong>Figure 2</strong><br/> <p>Chronic GCRsim exposure increases serum estradiol levels and enhances estrogen receptor signaling and proliferation markers in mammary tissue. (<b>A</b>) Serum estradiol levels expressed as fold change (FC) relative to control animals, demonstrating increased estradiol in GCRsim-exposed mice. (<b>B</b>) Representative photomicrographs illustrating increased immunohistochemical staining for estrogen receptor alpha (ERα) and Cyclin D1 in mammary tissues of GCRsim-exposed animals (scale bar = 50 µm). (<b>C</b>) Quantification of ERα-positive nuclei in mammary tissue, showing increased receptor expression in the GCRsim group. (<b>D</b>) Quantification of Cyclin D1-positive nuclei, indicating increased cellular proliferation in response to GCRsim exposure. (<b>E</b>) Fold change in mRNA expression of ERα downstream target gene Cyclin D1 (or <span class="html-italic">Ccnd1</span>), demonstrating activation of estrogen signaling. (<b>F</b>) Fold change in mRNA expression of ERα downstream target gene <span class="html-italic">cMyc</span>, indicating enhanced proliferative signaling. Statistically significant difference (<span class="html-italic">p</span> &lt; 0.05) relative to the control group is indicated by an asterisk (*).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3954'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g003-550.jpg?1732605023" title=" <strong>Figure 3</strong><br/> <p>Chronic GCRsim exposure elevates mRNA and protein levels of estrogen-related receptor alpha (ERRα). (<b>A</b>) Fold change in mRNA expression of ERRα (or <span class="html-italic">Esrra</span>) in mammary tissue of control and GCRsim-exposed mice, showing elevated expression in response to GCRsim exposure. (<b>B</b>) Representative photomicrographs of ERRα protein expression in the mammary gland, demonstrating increased levels in GCRsim-exposed mice (scale bar = 50 µm). (<b>C</b>) Quantification of ERRα-positive cells per high-power microscopic field (HPF), indicating increased receptor expression in GCRsim-exposed animals. (<b>D</b>) Gene expression analysis showing activation of ERRα downstream target <span class="html-italic">Spp1</span>, expressed as fold change relative to control. (<b>E</b>) Gene expression analysis showing activation of ERRα downstream target Nrip1, expressed as fold change relative to control. Statistically significant change (<span class="html-italic">p</span> &lt; 0.05) relative to the control group is denoted by an asterisk (*).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3954'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g004-550.jpg?1732605025" title=" <strong>Figure 4</strong><br/> <p>GCRsim exposure elevates SPP1 expression at both systemic and tissue levels. (<b>A</b>) Serum levels of SPP1 expressed as fold change relative to the control group, indicating increased levels in GCRsim-exposed mice. (<b>B</b>) Representative photomicrographs of mammary gland tissue showing increased SPP1 expression in GCRsim-exposed animals compared to controls (scale bar = 50 µm). (<b>C</b>) Quantification of SPP1 signal intensity in mammary tissue, demonstrating enhanced expression in response to GCRsim exposure. Statistically significant change (<span class="html-italic">p</span> &lt; 0.05) relative to the control group is denoted by an asterisk (*).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3954'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g005-550.jpg?1732605027" title=" <strong>Figure 5</strong><br/> <p>Increased ERα, ERRα, and SPP1 protein expression in GCRsim-induced tumors from <span class="html-italic">Apc</span><sup>Min/+</sup> mice compared to controls. (<b>A</b>) Representative immunohistochemically (IHC) stained images of mammary tissue showing the expression of ERα, ERRα, and SPP1 in both control and GCRsim-induced tumor samples (scale bar = 50 µm). (<b>B</b>) Increased tissue expression of ERα in GCRsim-exposed <span class="html-italic">Apc</span><sup>Min/+</sup> tumors compared to controls. (<b>C</b>) Elevated ERRα protein expression in GCRsim-induced tumors compared to controls. (<b>D</b>) Enhanced SPP1 expression in GCRsim-exposed tumors relative to control tumors. Statistically significant changes (<span class="html-italic">p</span> &lt; 0.05) are denoted by an asterisk (*). AU: Arbitrary unit; ROI: Region of interest.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3954'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g006-550.jpg?1732605031" title=" <strong>Figure 6</strong><br/> <p>Tissue Microarray (TMA) analysis of ERRα and SPP1 protein expression in normal and malignant human breast tissues. Expression of ERRα and SPP1 in different types of breast tissue, including normal tissue, invasive lobular carcinoma (ILC), fibroadenoma (FA), and invasive ductal carcinoma (IDC). <b>Upper panels</b> show representative images of tissue microarray (TMA) cores captured using an Aperio whole-slide digital scanner while <b>lower panels</b> show magnified views (marked by blue color box in the respective upper panel) of selected regions with increased expression (scale bar = 100 µm). Comparisons are provided for normal breast tissue and various tumor types to demonstrate a correlation in ERRα and SPP1 expressions.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3954'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g007-550.jpg?1732605031" title=" <strong>Figure 7</strong><br/> <p>Co-expression analysis of <span class="html-italic">Esr1</span>, <span class="html-italic">Esrra</span>, and <span class="html-italic">Spp1</span> genes in human breast cancer using RNA-Seq data from The Cancer Genome Atlas (TCGA). Presented bar graph illustrates the co-expression patterns of the genes <span class="html-italic">Esr1</span>, <span class="html-italic">Esrra</span>, and <span class="html-italic">Spp1</span> in human breast cancer samples, analyzed using RNA sequencing (RNA-Seq) data from TCGA. Samples were categorized based on Fragments Per Kilobase of transcript per Million mapped reads (FPKM) values as negative (i.e., samples with FPKM values in the lowest quartile, specifically <span class="html-italic">Esr1</span> FPKM ≤ 10.1, <span class="html-italic">Esrra</span> FPKM ≤ 2.45, and <span class="html-italic">Spp1</span> FPKM ≤ 30.22) and positive (i.e., samples with FPKM values above the 25th percentile cutoff). This analysis provides insight into how these genes are co-expressed and their relationship in the context of human breast cancer progression.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3954'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03954/article_deploy/html/images/cancers-16-03954-g008-550.jpg?1732605032" title=" <strong>Figure 8</strong><br/> <p>Schematic representation of putative molecular pathways linking GCRsim-induced estrogen response to increased breast cancer risk. GCRsim exposure results in: elevated estrogen levels, enhancing estrogen signaling in breast tissues involving activation of ERα, ERRα, and proliferation markers such as Cyclin D1 and cMyc. Both ERα and ERRα could induce overexpression of SPP1 at both systemic and tissue levels, ultimately contributing to enhanced breast cancer risk. Arrows in the schematic indicate the putative molecular connections between GCRsim-induced changes, receptor upregulation, proliferative signaling, and tumor development.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3954'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-1529406" aria-controls="drop-supplementary-1529406" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-1529406" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2072-6694/16/23/3953/s1?version=1732604535"> Supplementary File 1 (ZIP, 276 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 11 pages, 929 KiB   </span> <a href="/2072-6694/16/23/3953/pdf?version=1732604534" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Ultra-Processed Food and Prostate Cancer Risk: A Systemic Review and Meta-Analysis" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2072-6694/16/23/3953">Ultra-Processed Food and Prostate Cancer Risk: A Systemic Review and Meta-Analysis</a> <div class="authors"> by <span class="inlineblock "><strong>Cayla Fichtel-Epstein</strong>, </span><span class="inlineblock "><strong>Janice Huang</strong>, </span><span class="inlineblock "><strong>Benjamin James Rich</strong>, </span><span class="inlineblock "><strong>Crystal Seldon Taswell</strong>, </span><span class="inlineblock "><strong>Derek Isrow</strong> and </span><span class="inlineblock "><strong>William Jin</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3953; <a href="https://doi.org/10.3390/cancers16233953">https://doi.org/10.3390/cancers16233953</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> <b>Background/Objectives:</b> Prostate cancer is the second leading cause of cancer death among American men, following lung cancer. While diet and exercise have been extensively studied in relation to prostate cancer prevention, the evidence remains inconclusive. <b>Methods</b>: A comprehensive literature search was performed <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3953/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> <b>Background/Objectives:</b> Prostate cancer is the second leading cause of cancer death among American men, following lung cancer. While diet and exercise have been extensively studied in relation to prostate cancer prevention, the evidence remains inconclusive. <b>Methods</b>: A comprehensive literature search was performed to identify observational studies investigating the association between ultra-processed food (UPF) consumption and prostate cancer risk and mortality, determined by the NOVA classification system. In addition, we conducted subgroup analyses to assess the association based on study design, age, and data collection methods. <b>Results</b>: Six studies were identified, including four cohort studies and two case–control studies. No significant association was found between high UPF consumption and increased risk of prostate cancer [RR = 1.02, 95% confidence interval (CI) = 0.96–1.08, n = 5]. However, there was a slight increase in mortality (RR = 1.15, 95% CI = 0.99–1.35, n = 2). A subgroup analysis by the dietary assessment method revealed an RR of 1.01 (95% CI = 0.93–1.09) for studies using the food frequency questionnaire (FFQ) and 1.04 (95% CI = 0.93–1.16) for studies using 24-h recalls. There was no significant heterogeneity among the studies (I<sup>2</sup> = 0, <i>p</i> = 0.82). <b>Conclusions</b>: This meta-analysis suggests no significant association between high UPF consumption and prostate cancer risk. Given the known associations with other chronic diseases, the potential public health implications of reducing UPF consumption remain important. Further research with the use of more robust food assignment systems and more precise dietary assessments is needed to clarify the role of UPF in prostate cancer development. <a href="/2072-6694/16/23/3953">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/cancers/sections/Systematic_Review_Meta-Analysis">Systematic Review or Meta-Analysis in Cancer Research</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3953/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529406"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529406"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529406" data-cycle-prev="#prev1529406" data-cycle-progressive="#images1529406" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529406-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/cancers/cancers-16-03953/article_deploy/html/images/cancers-16-03953-g001-550.jpg?1732604662" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1529406" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529406-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03953/article_deploy/html/images/cancers-16-03953-g002-550.jpg?1732604663'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1529406-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/cancers/cancers-16-03953/article_deploy/html/images/cancers-16-03953-g003-550.jpg?1732604663'><p>Figure 3</p></div></script></div></div><div id="article-1529406-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/cancers/cancers-16-03953/article_deploy/html/images/cancers-16-03953-g001-550.jpg?1732604662" title=" <strong>Figure 1</strong><br/> <p>PRISMA flowchart showing the studies’ selection.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3953'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03953/article_deploy/html/images/cancers-16-03953-g002-550.jpg?1732604663" title=" <strong>Figure 2</strong><br/> <p>Forest plot represents the relationship between ultra-processed consumption and the risk of developing prostate cancer [<a href="#B14-cancers-16-03953" class="html-bibr">14</a>,<a href="#B16-cancers-16-03953" class="html-bibr">16</a>,<a href="#B23-cancers-16-03953" class="html-bibr">23</a>,<a href="#B25-cancers-16-03953" class="html-bibr">25</a>,<a href="#B26-cancers-16-03953" class="html-bibr">26</a>]. (<b>a</b>) Across cohort studies and case–control studies. (<b>b</b>) Stratified by age. (<b>c</b>) Stratified by dietary assessment method.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3953'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/cancers/cancers-16-03953/article_deploy/html/images/cancers-16-03953-g003-550.jpg?1732604663" title=" <strong>Figure 3</strong><br/> <p>Forest plot corresponding to consumption of ultra-processed food and prostate cancer mortality [<a href="#B23-cancers-16-03953" class="html-bibr">23</a>,<a href="#B24-cancers-16-03953" class="html-bibr">24</a>].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-6694/16/23/3953'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 1 pages, 147 KiB   </span> <a href="/2072-6694/16/23/3952/pdf?version=1732606343" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Reply to Itagaki et al. Comment on “Dorobisz et al. Assessment of Prognostic Factors, Clinical Features Including the Microbiome, and Treatment Outcomes in Patients with Cancer of Unknown Primary Site. Cancers 2024, 16, 3416”" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Reply</span></div> <a class="title-link" href="/2072-6694/16/23/3952">Reply to Itagaki et al. Comment on “Dorobisz et al. Assessment of Prognostic Factors, Clinical Features Including the Microbiome, and Treatment Outcomes in Patients with Cancer of Unknown Primary Site. <i>Cancers</i> 2024, <i>16</i>, 3416”</a> <div class="authors"> by <span class="inlineblock "><strong>Karolina Dorobisz</strong>, </span><span class="inlineblock "><strong>Tadeusz Dorobisz</strong> and </span><span class="inlineblock "><strong>Katarzyna Pazdro-Zastawny</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3952; <a href="https://doi.org/10.3390/cancers16233952">https://doi.org/10.3390/cancers16233952</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-full inline"> In his commentary [...] <a href="/2072-6694/16/23/3952">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/cancers/sections/Clinical_Research_Cancer">Clinical Research of Cancer</a>)<br/> </div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-1529040" aria-controls="drop-supplementary-1529040" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-1529040" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2072-6694/16/23/3951/s1?version=1732543666"> Supplementary File 1 (ZIP, 68455 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 13 pages, 6387 KiB   </span> <a href="/2072-6694/16/23/3951/pdf?version=1732543665" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="OVsignGenes: A Gene Expression-Based Neural Network Model Estimated Molecular Subtype of High-Grade Serous Ovarian Carcinoma" data-journal="cancers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-6694/16/23/3951">OVsignGenes: A Gene Expression-Based Neural Network Model Estimated Molecular Subtype of High-Grade Serous Ovarian Carcinoma</a> <div class="authors"> by <span class="inlineblock "><strong>Anastasiya Kobelyatskaya</strong>, </span><span class="inlineblock "><strong>Anna Tregubova</strong>, </span><span class="inlineblock "><strong>Andrea Palicelli</strong>, </span><span class="inlineblock "><strong>Alina Badlaeva</strong> and </span><span class="inlineblock "><strong>Aleksandra Asaturova</strong></span> </div> <div class="color-grey-dark"> <em>Cancers</em> <b>2024</b>, <em>16</em>(23), 3951; <a href="https://doi.org/10.3390/cancers16233951">https://doi.org/10.3390/cancers16233951</a> - 25 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Background/Objectives: High-grade serous carcinomas (HGSCs) are highly heterogeneous tumors, both among patients and within a single tumor. Differences in molecular mechanisms significantly describe this heterogeneity. Four molecular subtypes have been previously described by the Cancer Genome Atlas Consortium: differentiated, immunoreactive, mesenchymal, and proliferative. <a href="#" data-counterslink = "https://www.mdpi.com/2072-6694/16/23/3951/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Background/Objectives: High-grade serous carcinomas (HGSCs) are highly heterogeneous tumors, both among patients and within a single tumor. Differences in molecular mechanisms significantly describe this heterogeneity. Four molecular subtypes have been previously described by the Cancer Genome Atlas Consortium: differentiated, immunoreactive, mesenchymal, and proliferative. These subtypes may have varying degrees of progression, relapse-free survival, and overall survival, as well as response to therapy. The precise determination of these subtypes is certainly necessary both for diagnosis and future development of targeted therapies within personalized medicine. Methods: In this study, we analyzed gene expression data based on bulk RNA-seq, scRNA-seq, and spatial transcriptomic data from six cohorts (totaling 535 samples, including 60 single-cell samples). Differential expression analysis was performed using the edgeR package. The KEGG database and GSVA package were used for pathways enrichment analysis. As a predictive model, a deep neural network was created using the keras and tensorflow libraries. Results: We identified 357 differentially expressed genes among the four subtypes: 96 differentiated, 33 immunoreactive, 91 mesenchymal, and 137 proliferative. Based on these, we created OVsignGenes, a neural network model resistant to the effects of platform (test dataset AUC = 0.969). We then ran data from five more cohorts through our model, including scRNA-seq and spatial transcriptomics. Conclusions: Because the differentiated subtype is located at the intersection of the other three subtypes based on PCA and does not have a unique profile of differentially expressed genes or enriched pathways, it can be considered an initiating subtype of tumor that will develop into one of the three other subtypes. <a href="/2072-6694/16/23/3951">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/cancers/special_issues/AD856R62K2 ">Advances in the Diagnosis and Treatment of Solid and Hematologic Neoplasms</a>)<br/> </div> </div> </div> </div> </div> <div class="generic-item last-item"> <a class="bold" href="/search?q=&journal=cancers&sort=pubdate&page_count=50">More Articles...</a> </div> </div> </div> </div> <div id="left-column" class="content__column large-3 large-pull-6 medium-3 medium-pull-6 small-12 columns"> <div id="js-large-main-top-container"> <div id="js-main-top-container" 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show-for-medium-up"> <div class="generic-item news-item no-border"> <span class="text-information">21 November 2024</span> <br/> <a class="title-link" href="/journal/cancers/announcements/9815"><em>Cancers</em> | Notable Papers in the Field of Nanomaterials and Cancer Therapy</a> <a href="/journal/cancers/announcements/9815"><img style="margin: 5px 0; display: block; max-width: 100%; height: auto;" src="https://pub.mdpi-res.com/announcement/9815.jpg?1732615622" /></a> </div> <div class="generic-item news-item "> <span class="text-information">21 November 2024</span> <br/> <a class="title-link" href="/journal/cancers/announcements/9812"><strong>Recruiting Editorial Board Members for <em>Cancers</em></strong></a> </div> <div class="generic-item news-item "> <span class="text-information">20 November 2024</span> <br/> <a class="title-link" href="/journal/cancers/announcements/9803"><em>Cancers</em> | Notable Papers in the Section "Cancer Drug Development"</a> <a 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<span class="text-information italics times">IJMS</span>, <span class="text-information italics times">JCM</span>, <span class="text-information italics times">JMP</span>, <span class="text-information italics times">Organoids</span></span></div><a class="title-link bold" href="/topics/655S9K936W"> Novel Discoveries in Oncology </a><span class="text-information color-grey-dark">Topic Editors: Alessia Filippone, Giovanna Casili, Marika Lanza, Michela Campolo<br/></span><span class="text-information highlight">Deadline: 30 November 2024</span></div> <div class="generic-item"><div><span class="text-information times"> Topic in <span class="text-information italics times">Biology</span>, <span class="text-information italics times">Cancers</span>, <span class="text-information italics times">Molecules</span>, <span class="text-information italics times">IJMS</span>, <span class="text-information italics times">BioMedInformatics</span>, <span class="text-information italics times">Current 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