Weighted Gene Co-Expression Network Analysis Can Sort Cancer-Associated Fibroblast-Specific Markers Promoting Bladder Cancer Progression

Abstract

Background: Cancer-associated fibroblasts (CAFs) play an important role in cancer progression, but their roles in bladder urothelial carcinoma (BLCA) have not been thoroughly investigated. Methods: Estimate the Proportion of Immune and Cancer cells (EPIC) application was designed to calculate cell fractions in tissues. Weighted gene co-expression network analysis (WGCNA), by combining calculation principles, was used to identify genes expressed in specific cells in a tumour microenvironment (TME). Functional enrichment analysis and external data validation were conducted to assess the relationship between key genes and CAFs. Findings: Cell fraction of CAFs gradually increases with the progression of BLCA. Network construction revealed a specific gene module of CAFs that is the most relevant to cancer progression and survival status. Fifteen key genes of the CAF module were functionally related to the extracellular matrix and were significant in the analysis of survival and differentiation of tumour staging. A comparison of luminal-infiltrated subtypes with luminal-papillary subtypes and fibroblast cell lines with urothelial carcinoma cell lines, and the analysis of immunohistochemical data demonstrated that the key genes were specifically expressed in CAFs. Importantly, the key genes were highly correlated with some previously reported CAF markers. Interpretation: CAFs play a major role in the progression of BLCA. BLCA-specific CAF markers, the 15 key genes, can predict the changes in CAFs. The WGCNA can sort cell-specific gene sets in cancer tissues. Funding Statement: 345 Talent project - Shengjing Hospital of China Medical University. Declaration of Interests: The authors declare no conflict of interest. Ethics Approval Statement: Not required.