Identification of prognostic signature of cancer-associated fibroblasts associated with castration resistance prostate cancer based on Weighted Gene Co-expression Network Analysis

Abstract

Prostate cancer (PCa) is the most common cancer in men and often progresses to castration resistant prostate cancer (CRPC) after treatment, with a poor prognosis. Cancer associated fibroblasts (CAF) are a major components of tumor microenvironment (TME), which participate in angiogenesis and immunosuppression, promote metastasis and treatment drug resistance. In order to identify the CAF prognostic genes associated with CRPC, the RNA sequencing data of 745 PCa patients from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were downloaded. The CAF-related hub genes were identified by weighted gene co-expression network analysis (WCGNA). The CAF prognostic markers (FAP, SFRP2, COL1A1, VCAN) and signature were developed by machine learning methodology. Meanwhile, verified the CAF prognostic model could predict biochemical recurrence, metastasis and immunotherapy response. In addition, CAF infiltration was associated with immunosuppressive microenvironment, positively correlated with tumor mutation burden and “p53 downstream pathway”, “MET promotes cell motility pathway” and “TGF- β signal pathway”. subsequently, verified the CAF prognostic markers (FAP, SFRP2, COL1A1, VCAN) were specifically expressed in fibroblast cell lines, and the protein expression were located in stromal cells. In conclusion, these results indicated that CAF infiltration promoted the progression of PCa and associated with PCa recurrence and poor prognosis. The PCa prognostic signature has a potential clinical application value and the prognostic markers in CAF might be targets for inhibiting the progression of PCa.