Cancer-associated fibroblast-related gene signatures predict survival and drug response in patients with colorectal cancer

• DOI: 10.3389/fgene.2022.1054152
• Publication Date: 2022-11-25T05:28:40Z
• Authors: Lei Zhang; Chao Xu; Si-Han Wang; Qin-Wen Ge; Xiao-Wei Wang; Pan Xiao; Qing-Hua Yao
• Keywords: Nomogram; Cancer-Associated Fibroblasts; Gene signature

Background: Cancer-associated fibroblasts (CAFs) play an important role in the tumorigenesis, immunosuppression and metastasis of colorectal cancer (CRC), can predict poor prognosis patients with CRC. The present study aimed to construct a CAFs-related prognostic signature for Methods: clinical information corresponding RNA data CRC were downloaded from Cancer Genome Atlas (TCGA) Gene Expression Omnibus (GEO) databases. Estimation STromal Immune cells MAlignant Tumor tissues (ESTIMATES) xCell methods applied evaluate tumor microenvironment infiltration bulk gene expression data. Weighted co-expression network analysis (WGCNA) was used modules. key module identified by calculating module-trait correlations. univariate Cox regression least absolute shrinkage operator (LASSO) analyses combined develop model. Moreover, pRRophetic Dysfunction Exclusion (TIDE) algorithms utilized chemosensitivity immunotherapy response. Human Protein (HPA) databases employed protein expressions. Results: ESTIMATES showed that high CAFs associated adverse prognoses. A twenty-gene (CAFPS) established training cohort. Kaplan-Meier survival reveled higher risk scores each Univariate multivariate verified CAFPS as independent factor predicting overall survival, nomogram built utility prognosis. Patients tended not respond immunotherapy, but more sensitive five conventional chemotherapeutic drugs. Conclusion: In summary, could serve robust indicator patients, which might help optimize stratification provide new insight into individual treatments