Background: Clear cell renal cell carcinoma (ccRCC) is the most common solid lesion in the kidney. This study aims to establish an aging and senescence-related mRNA model for risk assessment and prognosis prediction in ccRCC patients. Methods: ccRCC data were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. By applying univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression, a new prognostic model based on aging and senescence-related genes (ASRGs) was established. Depending on the prognostic model, high- and low-risk groups were identified for further study. The reliability of the prediction was evaluated in the validation cohort. Pan-cancer analysis was conducted to explore the role of GNRH1 in tumors. Results: A novel prognostic model was established based on eight ASRGs. This model was an independent risk factor and significantly correlated with the prognosis and clinicopathological features of ccRCC patients. The high- and low-risk groups exhibited distinct modes in the principal component analysis and different patterns in immune infiltration. Moreover, the nomogram combining risk score and other clinical factors showed excellent predictive ability, with AUC values for predicting 1-, 3-, and 5-year overall survival in the TCGA cohort equal to 0.88, 0.82, and 0.81, respectively. Conclusion: The model and nomogram based on the eight ASRGs had a significant value for survival prediction and risk assessment for ccRCC patients, providing new insights into the roles of aging and senescence in ccRCC.
Keywords: The Cancer Genome Atlas; aging; clear cell renal cell carcinoma; mRNAs; prognostic model; senescence.
Copyright © 2022 Li, Gui, Yao, Luo, Song, Lin, Xu, Chen, Huang, Luo and Chen.