{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["13"],"submitter":["Liu Y"],"funding":["National Natural Science Foundation of China"],"pubmed_abstract":["<h4>Background</h4>The ability of cancer-associated fibroblasts (CAFs) to encourage angiogenesis, tumor cell spread, and increase treatment resistance makes them pro-tumorigenic. We aimed to investigate the CAF signature in Bladder urothelial carcinoma (BLCA) and, for clinical application, to build a CAF-based risk signature to decipher the immune landscape and screen for suitable treatment BLCA samples.<h4>Methods</h4>CAF-related genes were discovered by superimposing CAF marker genes discovered from single-cell RNA-seq (scRNA-seq) data taken from the GEO database with CAF module genes discovered by weighted gene co-expression network analysis (WGCNA) using bulk RNA-seq data from TCGA. After identifying prognostic genes related with CAF using univariate Cox regression, Lasso regression wa"],"journal":["Frontiers in oncology"],"pagination":["1170893"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10140328"],"repository":["biostudies-literature"],"pubmed_title":["Construction of cancer- associated fibroblasts related risk signature based on single-cell RNA-seq and bulk RNA-seq data in bladder urothelial carcinoma."],"pmcid":["PMC10140328"],"pubmed_authors":["Liu X","Liu Y","Chen Z","Zhang Y","Jian J","Wang L"],"additional_accession":[]},"is_claimable":false,"name":"Construction of cancer- associated fibroblasts related risk signature based on single-cell RNA-seq and bulk RNA-seq data in bladder urothelial carcinoma.","description":"<h4>Background</h4>The ability of cancer-associated fibroblasts (CAFs) to encourage angiogenesis, tumor cell spread, and increase treatment resistance makes them pro-tumorigenic. We aimed to investigate the CAF signature in Bladder urothelial carcinoma (BLCA) and, for clinical application, to build a CAF-based risk signature to decipher the immune landscape and screen for suitable treatment BLCA samples.<h4>Methods</h4>CAF-related genes were discovered by superimposing CAF marker genes discovered from single-cell RNA-seq (scRNA-seq) data taken from the GEO database with CAF module genes discovered by weighted gene co-expression network analysis (WGCNA) using bulk RNA-seq data from TCGA. After identifying prognostic genes related with CAF using univariate Cox regression, Lasso regression wa","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023","modification":"2026-04-08T13:33:32.814Z","creation":"2025-02-19T04:46:04.948Z"},"accession":"S-EPMC10140328","cross_references":{"pubmed":["37124542"],"doi":["10.3389/fonc.2023.1170893"]}}