Identifying hub genes of clear cell renal cell carcinoma associated with the proportion of regulatory T cells by weighted gene co-expression network analysis

Abstract

Background: Numerous patients with clear cell renal cell carcinoma (ccRCC) experience drug resistance after immunotherapy. Regulatory T (Treg) cells may work as a suppressor for anti-tumor immune response. Purpose: We performed bioinformatics analysis to better understand the role of Treg cells in ccRCC. Results: Module 10 revealed the most relevance with Treg cells. Functional annotation showed that biological processes and pathways were mainly related to activation of the immune system and the processes of immunoreaction. Four hub genes were selected: LCK, MAP4K1, SLAMF6, and RHOH. Further validation showed that the four hub genes well-distinguished tumor and normal tissues and were good prognostic biomarkers for ccRCC. Conclusion: The identified hub genes facilitate our knowledge of the underlying molecular mechanism of how Treg cells affect ccRCC in anti-tumor immune therapy. Methods: The CIBERSORT algorithm was performed to evaluate tumor-infiltrating immune cells based on the Cancer Genome Atlas cohort. Weighted gene co-expression network analysis was conducted to explore the modules related to Treg cells. Gene Ontology analysis and pathway enrichment analysis were performed for functional annotation and a protein–protein interaction network was built. Samples from the International Cancer Genomics Consortium database was used as a validation set.