Pan-cancer multi-omics analysis reveals the prognostic value of RGS gene family

Abstract

Abstract Background: The regulator of G-protein signaling (RGS) family, regulating cellular signaling events downstream of G-protein coupled receptors (GPCRs), is of great significance for diagnostic and prognostic prediction in cancer. At present, the comprehensive studies of RGS family genes in pan-cancer and specifically in Kidney renal clear cell carcinoma (KIRC) are rare. Methods: The performance of RGS genes in pan-cancer was assessed using the multi-omics dataset including genomic, transcriptomic, epigenetic and clinical data obtained from The Cancer Genome Atlas (TCGA). Subsequently, we conducted an in-depth exploration of RGS family genes in KIRC. Univariate cox regression and lasso regression were used to construct the risk model based on the five RGS genes. Independent prognostic factors for OS of KIRC patients were validated via univariate and multivariate COX analyses, and a nomogram was then developed. Finally, tumor mutation burden, immune infiltration, drug sensitivity and functional enrichment were analyzed and compared between the low- and high-risk groups. Result: We comprehensively found out that the abnormal expression, somatic mutations and methylation of RGS genes were associated with tumorigenesis and survival rates in pan-cancer. Interestingly, much more highly expressed RGS genes induced significantly higher risk and poorer survival in KIRC than those in other tumors. A prediction model for the prognosis based on five RGS genes (RGS2, RGS17, RGS10, RGS20 and RGS7BP) was established using univariable cox regression and lasso regression. The functional enrichment, tumor microenvironment, and immune infiltration were statistically different between the low-risk and high-risk groups. Clinically, our risk score model was effective in predicting the sensitivity of KIRC patients to chemotherapy and immune checkpoint blockade therapy. Conclusions: A five-gene risk-score signature was constructed and validated, which is of great clinical value and contributes to better clinical decision making and personalized treatment strategies associated with the benefits of KIRC patients.