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A prognostic model was developed to predict overall survival using OS-related genes and to evaluate the importance of genetic markers for bladder cancer outcomes. Transcriptomic datasets from TCGA-BLCA and GSE31684 were used to define molecular subtypes via non-negative matrix factorization, with risk signatures assessed by lasso and Cox regression. Tumor immune microenvironment differences were analyzed with CIBERSORT, and immunotherapy potential was explored using IPS and chemotherapy sensitivity forecasted by pRRophetic.",{"@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/prognostic-model-development-and-molecular-subtypes-identification-in-bladder-urothelial-cancer-by-oxidative-stress-signatures-research-paper/331899/",{"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/prognostic-model-development-and-molecular-subtypes-identification-in-bladder-urothelial-cancer-by-oxidative-stress-signatures-research-paper/331899.png","ImageObject",300,407,{"name":92,"@type":93},"Anda","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-26","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":24},"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 in bladder urothelial cancer?","Question",{"text":112,"@type":113},"To verify prognostic predictive accuracy by constructing an OS-related gene model and evaluating the prognostic importance of associated genetic markers in BLCA.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were molecular subtypes and the prognostic model built?",{"text":117,"@type":113},"Transcriptomic data from TCGA-BLCA and GSE31684 were clustered into subtypes using non-negative matrix factorization, while OS-associated genes were selected and evaluated using lasso regression and Cox regression analyses.",{"name":119,"@type":110,"acceptedAnswer":120},"What were the key prognostic findings and external validation results?",{"text":121,"@type":113},"Patients in the high-risk group had significantly worse overall survival than those in the low-risk group, with model discrimination supported by ROC AUC > 0.6 and Cox analyses showing risk score significance; the sample distribution was consistent across GEO and TCGA.","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},331899,1790136851,{"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":24,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},962075006959,"https://ap-avatar.wpscdn.com/avatar/e0002397efbe92a78e?_k=1776741047341049297","[www.aging-us.com](www.aging-us.com) AGING 2024, Vol. 16, No. 3  \nResearch Paper  \nPrognostic model development and molecular subtypes identification in bladder urothelial cancer by oxidative stress signatures  \nYing Dong1,*, Xiaoqing Wu2,*, Chaojie Xu3,*, Yasir Hameed4, Mostafa A. Abdel-Maksoud5, Taghreed N. Almanaa5, Mohamed H. Kotob6, Wahidah H. Al-Qahtani7, Ayman M. Mahmoud8, William C. Cho9, Chen Li10  \n1 Department of Urology, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, China  \n2 Department of Oncology, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China 3 Department of Urology, Peking University First Hospital, Peking University, Beijing, China  \n4 Department of Biochemistry, Biotechnology, The Islamia University of Bahawalpur, Pakistan  \n5 Botany and Microbiology Department, College of Science, King Saud University, Riyadh, Saudi Arabia 6 Department of Pharmaceutical Sciences, Division of Pharmacology and Toxicology, University of Vienna, Vienna, Austria  \n7 Department of Food Sciences and Nutrition, College of Food and Agricultural Sciences, King Saud University, Riyadh, Saudi Arabia  \n8 Department of Life Sciences, Faculty of Science and Engineering, Manchester Metropolitan University, Manchester, United Kingdom  \n9 Department of Clinical Oncology, Queen Elizabeth Hospital, Kowloon, Hong Kong, China 10 Department of Biology, Chemistry, Pharmacy, Free University of Berlin, Berlin, Germany  \n*Equal contribution  \nCorrespondence to: Yasir Hameed, William C. Cho, Chen Li; [email:](email: Yasirhameed2011@gmail.com)[ ](email: Yasirhameed2011@gmail.com)[Yasirhameed2011@gmail.com](email: Yasirhameed2011@gmail.com), [https://orcid.org/0000-](https://orcid.org/0000-)[ ](https://orcid.org/0000-)0002-6378-1962; [chocs@ha.org.hk](chocs@ha.org.hk); [chen.li@fu-berlin.de](chen.li@fu-berlin.de)  \nKeywords: oxidative stress, bladder urothelial cancer, tumor microenvironment, immunotherapy  \nReceived: August 22, 2023 Accepted: December 18, 2023 Published: February 1, 2024  \nCopyright: © 2024 Dong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.  \nABSTRACT  \nBackground: Mounting studies indicate that oxidative stress (OS) significantly contributes to tumor progression. Our study focused on bladder urothelial cancer (BLCA), an escalating malignancy worldwide that is growing rapidly. Our objective was to verify the predictive precision of genes associated with overall survival (OS) by constructing a model that forecasts outcomes for bladder cancer and evaluates the prognostic importance of these genetic markers.  \nMethods: Transcriptomic data were obtained from TCGA-BLCA and GSE31684, which are components of the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), respectively. To delineate distinct molecular subtypes, we employed the non-negative matrix factorization (NMF)method. The significance of OS-associated genes in predicting outcomes was assessed using lasso regression, multivariate Cox analysis, and univariate Cox regression analysis. For external validation, we employed the GSE31684 dataset. CIBERSORT was utilized to examine the tumor immune microenvironment (TIME) . A nomogram was created and verified using calibration and receiver operating characteristic (ROC) curves, which are based on risk signatures. We examined variations in clinical characteristics and tumor mutational burden (TMB) among groups classified as high-risk and low-risk.  \nTo evaluate the potential of immunotherapy, the immune phenomenon score (IPS) was computed based on the risk score. In the end, the pRRophetic algorithm was employed to forecast the IC50 values of chemotherapy medications.  \nResults: In our research, we examined the expression of 275 genes associa","cbCaip9DbLzJEulT","https://ap.wps.com/l/cbCaip9DbLzJEulT","pdf",4570681,26,"English","# Abstract\n## Background\n## Methods\n## Results\n## Conclusions\n# Introduction\n## Bladder urothelial carcinoma overview","[{\"question\":\"What is the study’s main goal in bladder urothelial cancer?\",\"answer\":\"To verify prognostic predictive accuracy by constructing an OS-related gene model and evaluating the prognostic importance of associated genetic markers in BLCA.\"},{\"question\":\"How were molecular subtypes and the prognostic model built?\",\"answer\":\"Transcriptomic data from TCGA-BLCA and GSE31684 were clustered into subtypes using non-negative matrix factorization, while OS-associated genes were selected and evaluated using lasso regression and Cox regression analyses.\"},{\"question\":\"What were the key prognostic findings and external validation results?\",\"answer\":\"Patients in the high-risk group had significantly worse overall survival than those in the low-risk group, with model discrimination supported by ROC AUC \\u003e 0.6 and Cox analyses showing risk score significance; the sample distribution was consistent across GEO and TCGA.\"}]","Prognostic model development and molecular subtypes identification in bladder urothelial cancer by oxidative stress signatures - Research paper | PDF",1789995659,66]