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Weighted gene co‐expression network analysis can sort cancer‐associated fibroblast‐specific markers promoting bladder cancer progression
Authors:Bitian Liu  Yunhong Zhan  Xiaonan Chen  Xiaoru Hu  Bin Wu  Shen Pan
Abstract:The role of cancer‐associated fibroblasts (CAFs) has been thoroughly investigated in tumour microenvironments but not in bladder urothelial carcinoma (BLCA). The cell fraction of CAFs gradually increased with BLCA progression. Weighted gene co‐expression network analysis (WGCNA) revealed a specific gene expression module of CAFs that are relevant to cancer progression and survival status. Fifteen key genes of the module were consistent with a fibroblast signature in single‐cell RNA sequencing, functionally related to the extracellular matrix, and significant in survival analysis and tumour staging. A comparison of the luminal‐infiltrated versus luminal‐papillary subtypes and fibroblast versus urothelial carcinoma cell lines and immunohistochemical data analysis demonstrated that the key genes were specifically expressed in CAFs. Moreover, these genes are highly correlated with previously reported CAF markers. In summary, CAFs play a major role in the progression of BLCA, and the 15 key genes act as BLCA‐specific CAF markers and can predict CAF changes. WGCNA can, therefore, be used to sort CAF‐specific gene set in cancer tissues.
Keywords:bladder cancer  cancer‐associated fibroblast  marker  tumour microenvironment  weighted gene co‐expression network analysis
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