Discovering Cure Hub Genes of Chromophobe Cell Renal Carcinoma Using weighted gene co-expression network analysis (WGCNA) and the Cure Defective Models

Abstract

Abstract methods WGCNA for gene network analysis and the 3-parameter defective Gompertz model to pinpoint therapeutic genes. Through WGCNA, we identified six key modules linked to various aspects of cancer progression and survival. Hub genes, important players in cellular interactions, were identified using network analysis. Using survival analysis, we detected genes associated with patient survival (SRGs) and genes linked to successful treatment outcomes (CSRGs) in RCC. Among the hub genes found using both survival methods, ten were commonly identified by the defective 3-parameter Gompertz and Cox models. Notably, six genes (NCAPG, TTK, DLGAP5, TOP2A, BUB1B, and BUB1) stood out with strong predictive values. Additionally, the defective Gompertz model highlighted six genes (TTK, KIF20A, DLGAP5, BUB1, AURKB, and CDC45) that significantly impacted the cure rate when their expression was at its highest. This suggests that targeting these genes might hold promise for improving RCC treatment outcomes. The hub genes identified also hold potential for predicting patient prognosis and aiding in diagnosis. Our study provides insights into RCC's molecular underpinnings and emphasizes the potential of the defective 3-parameter Gompertz model in guiding targeted therapeutic approaches.