Identification of a novel prognostic and therapeutic prediction model in clear cell renal carcinoma based on Renin-angiotensin system related genes.

Abstract

Background: Clear cell renal cell carcinoma is the most predominant type of renal malignancies, characterized by high aggressiveness and probability of distant metastasis. Renin angiotensin system (RAS) plays a crucial role in maintaining fluid balance within the human body, and its involvement in tumorigenesis is increasingly being uncovered, while its role in ccRCC remains unclear.

Methods: WGCNA was used to identify RAS related genes. Machine learning was applied to screen hub genes for constructing risk model, E-MTAB-1980 dataset was used for external validation. Transwell and CCK8 assays were used to investigate the impact of SLC6A19 to ccRCC cells.

Results: SLC6A19, SLC16A12 and SMIM24 were eventually screened to construct risk model and the predictive efficiency for prognosis was validated by internal and external cohorts. Moreover, the differences were found in pathway enrichment, immune cell infiltration, mutational landscapes and drug prediction between high and low risk groups. Experimental results indicated that SLC6A19 could inhibit invasion and proliferation of ccRCC cells and GSEA pinpointed that SLC6A19 was intimately correlated with fatty acid metabolism and CPT1A.

Conclusion: The risk model based on the three RAS-related genes have a robust ability to predict the prognosis and drug sensitivity of ccRCC patients, further providing a valid instruction for clinical care.