부산대학교 도서관

Abstract Background Colorectal cancer (CRC) is a malignancy of remarkable heterogeneity and heightened morbidity. Cancer associated fibroblasts (CAFs) are abundant in CRC tissues and are essential for CRC growth. Here, we aimed to develop a CAF-related classifier for predicting the prognosis of CRC and identify critical pro-tumorigenic genes in CAFs. Method The mRNA expression and clinical information of CRC samples were sourced from two comprehensive databases, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Using a weighted gene co-expression network analysis (WGCNA) approach, CAF-related genes were identified and a CAF risk signature was developed through the application of univariate analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression model. EdU cell proliferation assay, and transwell assay were performed to detect the oncogenic role of KCNE4 in CAFs. Results We constructed a prognostic CAF model consisting of two genes (SFRP2 and KCNE4). CRC patients were classified into low- and high-CAF-risk groups using the median CAF risk score, and patients in the high-CAF-risk group had worse prognosis. Meanwhile, a higher risk score for CAFs was associated with greater stromal and CAF infiltrations, as well as higher expression of CAF markers. Furthermore, TIDE analysis indicated that patients with a high CAF risk score are less responsive to immunotherapy. Our further experiments had confirmed the strong correlation between KCNE4 and the malignant phenotypes of CAFs. Moreover, we had shown that KCNE4 could actively promote tumor-promoting phenotypes in CAFs, indicating its critical role in cancer progression. Conclusion The two-gene prognostic CAF signature was constructed and could be reliable for predicting prognosis for CRC patients. Moreover, KCNE4 may be a promising strategy for the development of novel anti-cancer therapeutics specifically directed against CAFs.