Clear cell renal cell carcinoma (ccRCC) is associated with complex immune interactions. We conducted a comprehensive analysis of immune-related differentially expressed genes in patients with ccRCC using data from The Cancer Genome Atlas and ImmPort databases. The immune-related differentially expressed genes underwent functional and pathway enrichment analysis, followed by COX regression combined with LASSO regression to construct an immune-related risk prognostic model. The model comprised 4 IRGs: CLDN4, SEMA3G, CAT, and UCN. Patients were stratified into high-risk and low-risk groups based on the median risk score, and the overall survival rate of the high-risk group was significantly lower than that of the low-risk group, confirming the reliability of the model from various perspectives. Further comparison of immune infiltration, tumor mutation load, and immunophenoscore (IPS) comparison between the 2 groups indicates that the high-risk group could potentially demonstrate a heightened sensitivity towards immunotherapy checkpoints PD-1, CTLA-4, IL-6, and LAG3 in ccRCC patients. The proposed model not only applies to ccRCC but also shows potential in developing into a prognostic model for renal cancer, thus introducing a novel approach for personalized immunotherapy in ccRCC.
Medicine. 2023 Aug 25 [Epub]
Ronghui Chen, Jun Wu, Shan Liu, Yefeng Sun, Guozhi Liu, Lin Zhang, Qing Yu, Juan Xu, Lingxin Meng
Clinical Medical College of Weifang Medical University, Weifang, China., Department of Oncology, People's Hospital of Rizhao, Rizhao, China., Department of Emergency, People's Hospital of Rizhao, Rizhao, China., Jining Medical University, Jining, China.