Abstract
Tumorigenesis and progression can be promoted by oxidative stress. However, there is a lack of evidences regarding the expression profiles of oxidative stress-associated genes (OSRGs) in the tumorigenesis and development of clear cell renal cell carcinoma (ccRCC). In the present study, we performed transcriptome analyses on 611 samples from TCGA database and 645 samples from GEO database. Using unsupervised consensus clustering method, we identified two oxidative stress patten (OS_A and OS_B) according to the 278 differentially expressed OSRGs in both TCGA and GEO databases. We further evaluated the prognostic significance, tumor immune microenvironment, and related pathways between two oxidative stress patterns. Subsequently, we identified 7 prognostic OSRGs (CCL7, CDCA3, CRABP2, IRF6, MAGEA4, PLG, SAA1) from both two patterns to incorporate into an OSRG-based prognostic model, and developed a prognostic risk scoring system (OS_score) to distinguish patients with high-risk and poor prognosis. We then develop a miRNA-OSRG regulatory network based on differentially expressed miRNAs and prognostic OSRGs genes, and identify the correlation between OS_score and tumor mutation burden (TMB). Patients from high-risk groups performed an increased expression of immune checkpoint inhibitor (ICI) genes, including PD-1, CTLA-4, B7H3, B7H4, and were more likely to respond to anti-PD-1 immunotherapy. Correlation analysis revealed that AKT inhibitor VIII, EHT-1864 and AS601245 might provide benefits for patients with high OS_score. In conclusion, we conducted a thorough analysis of the expression profiles of OSRGs in ccRCC, culminating in the development of a robust prognostic model and scoring system aimed at accurately predicting survival outcomes for ccRCC patients. This endeavor has the potential to yield novel insights into redox biology and to advance the current treatment strategies for ccRCC.