Novel Prognosis Model for Clear-cell Renal Cell Carcinoma based on Apoptosis-related Genes

Background. Few studies have investigated the clinical prognostic significance of multiple apoptosis-related genes (ARGs), particularly in the context of clear-cell renal cell carcinoma (ccRCC). Methods. We explored ARGs in ccRCC prognosis using The Cancer Genome Atlas (TCGA) repository. Transcriptomic expression profiles and corresponding medical information for patients with ccRCC were obtained. Human ARGs were identified through gene-set enrichment analysis. Differentially expressed (DE)-ARGs and prognosis-related ARGs were identified and, subsequently, used for prognosis modelling. The prognostic predictive performance of this model was confirmed using Kaplan-Meier (KM) and receiver operating characteristic (ROC) curves. Relevant clinical prognostic variables were added to construct a predictive nomogram for ccRCC prognosis at the clinical level. Immune-cell penetration evaluation was conducted for genes included within this novel prognosis-linked model. Validation of TOP2A function in ccRCC cells by cellular experiments. Results. Overall, 49 DE-ARGs were identified. Univariate Cox regression evaluation identified 17 genes associated with ccRCC prognosis, and multivariate Cox regression analyses identified eight ARGs ( BID , CD44 , ERBB2 , HMOX1 , PLCB2 , TGFBR3 , TIMP1 , and TOP2A ), which were employed to construct the variable risk scoring. The effectiveness of risk scoring as an independent prognostic variable was verified through KM curve and ROC analyses. Risk scoring and various other relevant clinical prognostic variables were employed to construct a prognostic model. The model was statistically significant regarding its association with immune-cell penetration, immune-related function, and immune checkpoints. TOP2A promotes ccRCC cells growth and metastasis . Conclusions. Based on eight ARGs and other relevant clinical prognostic variables, we established a novel model for predicting ccRCC prognosis, which can be used to inform the individualized treatment of ccRCC patients.