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This study builds a prognostic model based on SiaTs-related genes (SRGs) to estimate patient outcomes and therapeutic responsiveness in bladder cancer using TCGA-BLCA and GSE13507. It identifies key SRG signatures and evaluates their predictive performance via survival and ROC analyses, then validates with nomograms and decision curves.",{"@graph":69,"@context":123},[70,84,106],{"@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":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/a-sialyltransferases-related-gene-signature-serves-as-a-potential-predictor-of-prognosis-and-therapeutic-response-for-bladder-cancer/385342/",{"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/a-sialyltransferases-related-gene-signature-serves-as-a-potential-predictor-of-prognosis-and-therapeutic-response-for-bladder-cancer/385342.png","ImageObject",300,407,{"name":92,"@type":93},"Mary Man","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-01","2026-09-24",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",11,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What is the goal of the sialyltransferases-related gene signature in bladder cancer?","Question",{"text":113,"@type":114},"The study aims to develop an SRGs-based prognostic model that can predict survival outcomes and therapeutic responsiveness for bladder cancer patients.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How were the SiaTs-related genes and clusters identified?",{"text":118,"@type":114},"RNA-seq, clinical, and mutation data from TCGA-BLCA and GSE13507 were analyzed to screen differentially expressed SiaTs-related genes, then clustering was performed using ConsensusClusterPlus, followed by survival analyses.",{"name":120,"@type":111,"acceptedAnswer":121},"What clinical relevance did the final SRGs signature show?",{"text":122,"@type":114},"The signature separated patients into high- and low-risk groups, where high-risk patients had worse outcomes, more immune infiltration, higher immune checkpoint gene expression, and distinct predicted therapy responsiveness.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},385342,1790668190,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":140,"language":141,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":67,"update_tm":145,"read_time":146},7421720224475,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","Cao et al. European Journal  \nEuropean Journal of Medical Research (2023) 28:515  \n[https://doi.org/10.1186/s40001-023-01496-7](https://doi.org/10.1186/s40001-023-01496-7 of Medical Research)[ of Medical Research](https://doi.org/10.1186/s40001-023-01496-7 of Medical Research)  \n RESEARCH Open Access  \nA sialyltransferases-related gene signature   serves as a potential predictor of prognosis and therapeutic response for bladder cancer  \nPenglong Cao1†, Mingying Chen1†, Tianya Zhang1†, Qin Zheng2* and Mulin Liu 1*  \nAbstract  \nBackground Aberrant glycosylation, catalyzed by the specific glycosyltransferase, is one of the dominant features of cancers. Among the glycosyltransferase subfamilies, sialyltransferases (SiaTs) are an essential part which has close linkages with tumor-associated events, such as tumor growth, metastasis and angiogenesis. Considering the relationship between SiaTs and cancer, the current study attempted to establish an effective prognostic model with SiaTsrelated genes (SRGs) to predict patients’ outcome and therapeutic responsiveness of bladder cancer.  \nMethods RNA-seq data, clinical information and genomic mutation data were downloaded (TCGA-BLCA and GSE13507 datasets) . The comprehensive landscape of the 20 SiaTs was analyzed, and the differentially expressed SiaTs-related genes were screened with“DESeq2” R package. ConsensusClusterPlus was applied for clustering, following with survival analysis with Kaplan–Meier curve. The overall survival related SRGs were determined with univariate Cox proportional hazards regression analysis, and the least absolute shrinkage and selection operator (LASSO) regression analysis was performed to generate a SRGs-related prognostic model. The predictive value was estimated with Kaplan–Meier plot and the receiver operating characteristic (ROC) curve, which was further validated with the constructed nomogram and decision curve.  \nResults In bladder cancer tissues, 17 out of the 20 SiaTs were differentially expressed with CNV changes and somatic mutations. Two SiaTs_Clusters were determined based on the expression of the 20 SiaTs, and two gene_Clusters were identified based on the expression of differentially expressed genes between SiaTs_Clusters. The SRGs-related prognostic model was generated with 7 key genes (CD109, TEAD4, FN1, TM4SF1, CDCA7L, ATOH8 and GZMA), and the accuracy for outcome prediction was validated with ROC curve and a constructed nomogram. The SRGsrelated prognostic signature could separate patients into high-and low-risk group, where the high-risk group showed poorer outcome, more abundant immune infiltration, and higher expression of immune checkpoint genes. In addition, the risk score derived from the SRGs-related prognostic model could be utilized as a predictor to evaluate the responsiveness of patients to the medical therapies.  \n†Penglong Cao, Mingying Chen and Tianya Zhang contributed equally to this study.  \n*Correspondence: Qin Zheng [zhengqin90@126.com](zhengqin90@126.com)[ ](zhengqin90@126.com)Mulin Liu [liumulin87@126.com](liumulin87@126.com)  \nFull list of author information is available at the end of the article  \n© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://cre","cbCaiarBqRFVT7zM","https://ap.wps.com/l/cbCaiarBqRFVT7zM","pdf",12912742,17,"English","# Abstract\n## Background\n## Methods\n## Results\n## Conclusions\n# Introduction","[{\"question\":\"What is the goal of the sialyltransferases-related gene signature in bladder cancer?\",\"answer\":\"The study aims to develop an SRGs-based prognostic model that can predict survival outcomes and therapeutic responsiveness for bladder cancer patients.\"},{\"question\":\"How were the SiaTs-related genes and clusters identified?\",\"answer\":\"RNA-seq, clinical, and mutation data from TCGA-BLCA and GSE13507 were analyzed to screen differentially expressed SiaTs-related genes, then clustering was performed using ConsensusClusterPlus, followed by survival analyses.\"},{\"question\":\"What clinical relevance did the final SRGs signature show?\",\"answer\":\"The signature separated patients into high- and low-risk groups, where high-risk patients had worse outcomes, more immune infiltration, higher immune checkpoint gene expression, and distinct predicted therapy responsiveness.\"}]","A sialyltransferases-related gene signature - serves as a potential predictor of prognosis and therapeutic response for bladder cancer | PDF",1790268072,43]