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The study evaluates EC cancer genomes deposited in COSMIC to label mutations as driver or passenger using artificial intelligence methods that incorporate parameters such as gene function and mutation frequency. Results indicate ~2.5% driver mutations associated with cellular transformation and immortalization, alongside distinct nucleotide substitution, chromosomal re-arrangement, and gene expression patterns, including high CLDN18 expression.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/detection-of-driver-mutations-and-genomic-signatures-in-endometrial-cancers-using-artificial-intelligence-algorithms/331877/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/detection-of-driver-mutations-and-genomic-signatures-in-endometrial-cancers-using-artificial-intelligence-algorithms/331877.png","ImageObject",300,407,{"name":92,"@type":93},"Patrick","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-15","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the study’s main goal for endometrial cancer genomes?","Question",{"text":112,"@type":113},"To classify mutations from endometrial cancer genomes as driver or passenger using artificial intelligence algorithms, leveraging data deposited in COSMIC.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What proportion of mutations were identified as driver mutations?",{"text":117,"@type":113},"Approximately 2.5% of all analyzed mutations were reported as driver mutations associated with cellular transformation and immortalization.",{"name":119,"@type":110,"acceptedAnswer":120},"Which findings distinguish endometrial cancers from other cancers in the analysis?",{"text":121,"@type":113},"The work reports distinct nucleotide substitution and chromosomal re-arrangement signatures, along with characterized nucleotide-level mutation signatures and gene expression profiles, including high CLDN18 expression.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},331877,1790568095,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":44,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":56,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144,"preview_page_count":4},549758146520,"https://ap-avatar.wpscdn.com/avatar/80002397d8c0411e94?_k=1775819394049821470","PLOS ONE  \nOPEN ACCESS  \nCitation: Stan A, Bosart K, Kaur M, Vo M, Escorcia W, Yoder RJ, et al. (2024) Detection of driver mutations and genomic signatures in endometrial cancers using artificial intelligence algorithms. PLoS ONE 19(2): e0299114 . [https://doi.org/](https://doi.org/)[ ](https://doi.org/)[10.1371/journal.pone](10.1371/journal.pone).0299114  \nEditor: Nandini Dey, Avera Research Institute, UNITED STATES  \nReceived: October 16, 2023  \nAccepted: February 5, 2024  \nPublished: February 26, 2024  \nCopyright: © 2024 Stan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.  \nData Availability Statement: All data can be found at COSMIC: [https://cancer.sanger.ac.uk/cosmic](https://cancer.sanger.ac.uk/cosmic)  \ncBioPortal: [https://www.cbioportal.org/](https://www.cbioportal.org/).  \nFunding: Ohio State University Comprehensive Cancer Center–Arthur G. James Cancer Hospital and Richard J. Solove Research Institute. There is no grant number.  \nCompeting interests: The authors have declared that no competing interests exist.  \nRESEARCH ARTICLE  \nDetection of driver mutations and genomic signatures in endometrial cancers using artificial intelligence algorithms  \nAnda Stan1☯, Korey Bosart1☯, Mehak Kaur1☯, Martin Vo2, Wilber Escorcia2, Ryan J. Yoder3, Renee A. Bouley3 *, Ruben C. Petreaca4,5 *  \n1 Biology Program, The Ohio State University, Marion, Ohio, United States of America, 2 Biology Department, Xavier University, Cincinnati, Ohio, United States of America, 3 Department of Chemistry and Biochemistry, The Ohio State University, Marion, Ohio, United States of America, 4 Department of Molecular Genetics, The Ohio State University, Marion, Ohio, United States of America, 5 James Comprehensive Cancer Center, The Ohio State University Columbus, Columbus, Ohio, United States of America  \n☯ These authors contributed equally to this work.  \n* [bouley.8@osu.edu](bouley.8@osu.edu) (RAB); [petreaca.1@osu.edu](petreaca.1@osu.edu) (RCB)  \nAbstract  \nAnalyzed endometrial cancer (EC) genomes have allowed for the identification of molecular signatures, which enable the classification, and sometimes prognostication, of these cancers. Artificial intelligence algorithms have facilitated the partitioning of mutations into driver and passenger based on a variety of parameters, including gene function and frequency of mutation. Here, we undertook an evaluation of EC cancer genomes deposited on the Catalogue of Somatic Mutations in Cancers (COSMIC), with the goal to classify all mutations as either driver or passenger. Our analysis showed that approximately 2 .5% of all mutations are driver and cause cellular transformation and immortalization. We also characterized nucleotide level mutation signatures, gross chromosomal re-arrangements, and gene expression profiles. We observed that endometrial cancers show distinct nucleotide substitution and chromosomal re-arrangement signatures compared to other cancers. We also identified high expression levels of the CLDN18 claudin gene, which is involved in growth, survival, metastasis and proliferation. We then used in silico protein structure analysis to examine the effect of certain previously uncharacterized driver mutations on protein structure. We found that certain mutations in CTNNB1 and TP53 increase protein stability, which may contribute to cellular transformation. While our analysis retrieved previously classified mutations and genomic alterations, which is to be expected, this study also identified new signatures. Additionally, we show that artificial intelligence algorithms can be effectively leveraged to accurately predict key drivers of cancer. This analysis will expand our understanding of ECs and improve the molecular toolbox for classification, diagnosis, or potential treatment of these cancers.  \n","cbCaidar0szH23SN","https://ap.wps.com/l/cbCaidar0szH23SN","pdf",2913735,"English","# Abstract\n# Introduction","[{\"question\":\"What is the study’s main goal for endometrial cancer genomes?\",\"answer\":\"To classify mutations from endometrial cancer genomes as driver or passenger using artificial intelligence algorithms, leveraging data deposited in COSMIC.\"},{\"question\":\"What proportion of mutations were identified as driver mutations?\",\"answer\":\"Approximately 2.5% of all analyzed mutations were reported as driver mutations associated with cellular transformation and immortalization.\"},{\"question\":\"Which findings distinguish endometrial cancers from other cancers in the analysis?\",\"answer\":\"The work reports distinct nucleotide substitution and chromosomal re-arrangement signatures, along with characterized nucleotide-level mutation signatures and gene expression profiles, including high CLDN18 expression.\"}]","Detection of driver mutations and genomic signatures in endometrial cancers using artificial intelligence algorithms | PDF",1789995592,48]