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A prognostic prediction model was developed using Weighted Gene Co-Expression Network Analysis (WGCNA) on TCGA-UCEC gene expression data to define hub modules tied to T-lymphocyte infiltration, then built with LASSO regression and validated across multiple immune and clinical features. Hub module analysis identified ARPC1B, BATF, CCL2, and COTL1 as key genes, with BATF linked to CD8+ T cell infiltration and antitumor immunity. The resulting model stratified high- vs low-risk patients, associated with immune pathways and immunotherapy response potential. ",{"@graph":69,"@context":126},[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/development-and-validation-of-a-prognostic-prediction-model-for-endometrial-cancer-based-on-cd8-t-cell-infiltration-related-genes/332848/",{"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/development-and-validation-of-a-prognostic-prediction-model-for-endometrial-cancer-based-on-cd8-t-cell-infiltration-related-genes/332848.png","ImageObject",300,407,{"name":92,"@type":93},"Evangeline","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-05","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118,122],{"name":109,"@type":110,"acceptedAnswer":111},"What was the goal of the prognostic prediction model in this study?","Question",{"text":112,"@type":113},"To develop and validate a prognostic prediction model for endometrial cancer using genes related to CD8+ T cell infiltration, with the aim of improving risk stratification and identifying potential therapeutic targets.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were the key genes selected for the prognostic model?",{"text":117,"@type":113},"WGCNA was used to identify hub modules associated with T-lymphocyte infiltration, and LASSO regression was then applied to genes within these hub modules. The green-yellow module yielded four genes: ARPC1B, BATF, CCL2, and COTL1.",{"name":119,"@type":110,"acceptedAnswer":120},"Which analyses were used to connect the model to immune and therapy-related features?",{"text":121,"@type":113},"The study used gene set variation analysis for enrichment between high- and low-risk groups, and examined associations with microsatellite instability, tumor mutational burden, immune infiltration, and predicted chemotherapy and immunotherapy resistance using TCGA and other pharmacogenomic/immune databases.",{"name":123,"@type":110,"acceptedAnswer":124},"What experimental evidence supports the role of BATF in relation to CD8+ T cell infiltration?",{"text":125,"@type":113},"Immunohistochemical staining of EC tissue microarrays was performed to relate expression of the key genes to immune infiltration. BATF expression in EC tissues positively correlated with CD8+ T cell infiltration, suggesting a crucial role in EC development and antitumor immunity.","https://schema.org",{"og:url":83,"og:type":128,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":130,"canonical":83},"index,follow",{"doc_id":132,"site_id":62},332848,1790012821,{"code":4,"msg":5,"data":135},{"doc_id":132,"user_id":136,"nickname":92,"user_avatar":137,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":138,"file_id":139,"file_url":140,"file_type":141,"file_size":142,"view_count":44,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":143,"language":144,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":145,"faqs":146,"seo_title":147,"seo_description":67,"update_tm":148,"read_time":149,"preview_page_count":4},13056703019662,"https://ap-avatar.wpscdn.com/avatar/be000253a8e92610077?_k=1778726343310543188","®  \n Observational Study   \nDevelopment and validation of a prognostic prediction model for endometrial cancer based on CD8+ T cell infiltration-related genes  \nChao Chen, MMa , Lipeng Pei, MMa , Wei Ren, MMa ,* , Jingli Sun, MMa  \n\n| Abstract\u003Cbr>Endometrial cancer (EC) is the most common gynecologic malignancy with increasing incidence and mortality. The tumor immune microenvironment significantly impacts cancer prognosis. Weighted Gene Co-Expression Network Analysis (WGCNA) is a systems biology approach that analyzes gene expression data to uncover gene co-expression networks and functional modules. This study aimed to use WGCNA to develop a prognostic prediction model for EC based on immune cell infiltration, and to identify new potential therapeutic targets. WGCNA was performed using the Cancer Genome Atlas Uterine Corpus Endometrial Carcinoma dataset to identify hub modules associated with T-lymphocyte cell infiltration. Prognostic models were developed using LASSO regression based on genes in these hub modules. The Search Tool for the Retrieval of Interacting Genes/ Proteins was used for protein–protein interaction network analysis of the hub module. Gene Set Variation Analysis identified differential gene enrichment analysis between high-and low-risk groups. The relationship between the model and microsatellite instability, tumor mutational burden, and immune cell infiltration was analyzed using The Cancer Genome Atlas data. The model’s correlation with chemotherapy and immunotherapy resistance was examined using the Genomics of Drug Sensitivity in Cancer and Cancer Immunome Atlas databases. Immunohistochemical staining of EC tissue microarrays was performed to analyze the relationship between the expression of key genes and immune infiltration. The green-yellow module was identified as a hub module, with 4 genes (ARPC1B, BATF, CCL2, and COTL1) linked to CD8+ T cell infiltration. The prognostic model constructed from these genes showed satisfactory predictive efficacy. Differentially expressed genes in high- and low-risk groups were enriched in tumor immunity-related pathways. The model correlated with EC-related phenotypes, indicating its potential to predict immunotherapeutic response. Basic leucine zipper activating transcription factor-like transcription factor(BATF) expression in EC tissues positively correlated with CD8+ T cell infiltration, suggesting BATF’s crucial role in EC development and antitumor immunity. The prognostic model comprising ARPC1B, BATF, CCL2, and COTL1 can effectively identify high-risk EC patients and predict their response to immunotherapy, demonstrating significant clinical potential. These genes are implicated in EC development and immune infiltration, with BATF emerging as a potential therapeutic target for EC. |\n| --- |\n| Abbreviations: BATF = basic leucine zipper activating transcription factor-like transcription factor, CCL2 = C-C motif chemokine ligand 2, CIBERSORT = Cell-type Identification by Estimating Relative Subsets Of RNA Transcripts, COTL1 = coactosin-like 1, EC = endometrial cancer, GDSC = Genomics of Drug Sensitivity in Cancer, GO = gene ontology, GSVA = Gene Set Variation Analysis, HH = Hedgehog-GLI, IHC = immunohistochemical, KEGG = Kyoto Encyclopedia of Genes and Genomes, MSI = microsatellite instability, MSI-H = high levels of microsatellite instability, OS = overall survival, PPI = protein–protein interaction, ROC = receiver operating characteristic, TCGA = The Cancer Genome Atlas, TCGA-UCEC = The Cancer Genome Atlas Uterine Corpus Endometrial Carcinoma, TCIA = The Cancer Immunome Atlas, TIME = tumor immune microenvironment, TMA = tissue microarrays, TMB = tumor mutational burden, UCEC = Uterine Corpus Endometrial Carcinoma, WGCNA = Weighted Gene Co-Expression Network Analysis. |\n| Keywords: basic leucine zipper activating transcription factor-like transcription factor, CD8+ T cell infiltration, endometrial cancer, prognostic prediction model |\n\nCC, LP, WR, and JS cont","cbCaiprIdFIKX704","https://ap.wps.com/l/cbCaiprIdFIKX704","pdf",4304759,18,"English","# Introduction\n## Study rationale and background\n# Methods\n## WGCNA-based hub module identification\n## LASSO prognostic model construction\n## Network and pathway analyses (PPI, GSVA)\n## Assessment with clinical and immune datasets\n## Tissue validation via immunohistochemistry\n# Results\n## Hub genes linked to CD8+ T cell infiltration\n## Risk stratification and predictive performance\n## Enrichment of immune-related pathways\n## Associations with phenotypes and therapy resistance\n# Discussion\n## BATF as a potential therapeutic target\n# Conclusion\n## Clinical potential of the gene-based model","[{\"question\":\"What was the goal of the prognostic prediction model in this study?\",\"answer\":\"To develop and validate a prognostic prediction model for endometrial cancer using genes related to CD8+ T cell infiltration, with the aim of improving risk stratification and identifying potential therapeutic targets.\"},{\"question\":\"How were the key genes selected for the prognostic model?\",\"answer\":\"WGCNA was used to identify hub modules associated with T-lymphocyte infiltration, and LASSO regression was then applied to genes within these hub modules. The green-yellow module yielded four genes: ARPC1B, BATF, CCL2, and COTL1.\"},{\"question\":\"Which analyses were used to connect the model to immune and therapy-related features?\",\"answer\":\"The study used gene set variation analysis for enrichment between high- and low-risk groups, and examined associations with microsatellite instability, tumor mutational burden, immune infiltration, and predicted chemotherapy and immunotherapy resistance using TCGA and other pharmacogenomic/immune databases.\"},{\"question\":\"What experimental evidence supports the role of BATF in relation to CD8+ T cell infiltration?\",\"answer\":\"Immunohistochemical staining of EC tissue microarrays was performed to relate expression of the key genes to immune infiltration. BATF expression in EC tissues positively correlated with CD8+ T cell infiltration, suggesting a crucial role in EC development and antitumor immunity.\"}]","Development and validation of a prognostic prediction model for endometrial cancer based on CD8+ T cell infiltration-related genes | PDF",1789999752,45]