A DNA Damage Repair Gene Signature Associated With Immunotherapy Response and Clinical Prognosis in Clear Cell Renal Cell Carcinoma.

Abstract

Background: Clear cell renal cell carcinoma (ccRCC) is the most common subtype in renal cell carcinoma with relatively poor clinical outcomes DNA damage repair genes (DDRGs) as potential biomarkers are rarely reported in predicting immunotherapy response and clinical prognosis for ccRCC. Methods: RNA-seq and clinical data of ccRCC cohort were collected form TCGA database. Univariate Cox regression and LASSO analysis were performed to construct a DDRG risk signature. Functional enrichment analysis was performed to explore latently enriched pathways associated with DDRG signature. Immune cell infiltration level was estimated using gene set enrichment analysis, and immune response of ccRCC was predicted by tumor immune dysfunction and exclusion (TIDE) algorithm. To predict 1-, 3-, and 5-years overall survival (OS), a nomogram was constructed based on independent prognostic factors, whose performance would be evaluated by calibration curve. Results: A total of 47 DNA damage repair related genes (DDRGs) with significant prognostic value were identified in the ccRCC cohort (n = 519). A DDRG risk signature comprising six DRRGs (MSH3, RAD54L, RAD50, EME1, UNG, and NEIL3) were constructed by the LASSO analysis. ccRCC patients were then divided into low- and high-risk groups based on the risk score. Survival analysis revealed that patients in high-risk groups exhibited significantly poorer OS and progression-free survival (PFS), as was confirmed by the testing dataset. Functional enrichment analysis indicated that differentially expressed genes (DEGs) between high- and low-risk groups were mainly associated with immune-related biological processes in ccRCC, among which the immunodeficiency pathway was significantly enriched in the high-risk group. Though the risk signature was significantly correlated with the immune cell infiltration, PD-1 and PD-L1 were less expressed in the DDRG signature, which might indicate the poor response to immunotherapy in the high-risk group. Furthermore, the Cox regression analysis indicated that the DDRG signature can be served as an independent prognostic predictor when compared to clinical characteristics. Based on the independent prognostic predictors, we constructed a nomogram with excellent predictive ability in OS prediction for ccRCC patients. Conclusion: We developed a reliable DDRG risk signature that can independently predict the OS and PFS of ccRCC, which is also promising for predicting immunotherapeutic responses in ccRCC patients.