Molecular Characterization, Tumor Microenvironment Association, and Drug Susceptibility of DNA Methylation-Driven Genes in Renal Cell Carcinoma

Abstract

Accumulating evidence suggests that DNA methylation has essential roles in the development of renal cell carcinoma (RCC). Aberrant DNA methylation acts as a vital role in RCC progression through regulating the gene expression, yet little is known about the role of methylation and its association with prognosis in RCC. The purpose of this study is to explore the DNA methylation-driven genes for establishing prognostic-related molecular clusters and providing a basis for survival prediction. In this study, 5,198 differentially expressed genes (DEGs) and 270 DNA methylation-driven genes were selected to obtain 146 differentially expressed DNA methylation-driven genes (DEMDGs). Two clusters were distinguished by consensus clustering using 146 DEMDGs. We further evaluated the immune status of two clusters and selected 106 DEGs in cluster 1. Cluster-based immune status analysis and functional enrichment analysis of 106 DEGs provide new insights for the development of RCC. To predict the prognosis of patients with RCC, a prognostic model based on eight DEMDGs was constructed. The patients were divided into high-risk groups and low-risk groups based on their risk scores. The predictive nomogram and the web-based survival rate calculator (http://127.0.0.1:3496) were built to validate the predictive accuracy of the prognostic model. Gene set enrichment analysis was performed to annotate the signaling pathways in which the genes are enriched. The correlation of the risk score with clinical features, immune status, and drug susceptibility was also evaluated. These results suggested that the prognostic model might be a promising prognostic tool for RCC and might facilitate the management of patients with RCC.

Identification of Differentially Methylated Genes Associated with Clear Cell Renal Cell Carcinoma and Their Prognostic Values

“…Abnormal DNA methylation usually occurs during early carcinogenesis, being one of the hallmarks of some human cancers, including ccRCC [ 13 ]. DNA methylation profiling may reveal important new therapeutic targets for cancer diagnosis and prognosis prediction.…”

An In Vitro Analysis of TKI-Based Sequence Therapy in Renal Cell Carcinoma Cell Lines

“…At present, therapeutic approaches used to treat patients with metastatic RCC (mRCC) are based on specific molecular characteristics that play an essential role in disease development [ 6 ]. In clear cell RCC (ccRCC, 80% of cases), the mutation of the tumor-suppressor von Hippel–Lindau ( VHL ) gene; chromosome remodeling by PBRM1 , BAP1 and SETD2 genes; hyperactivated PI3K/AKT pathways; and mTOR alterations are the main molecular features [ 7 , 8 , 9 , 10 ].…”

The categorizations of vasculogenic mimicry in clear cell renal cell carcinoma unveil inherent connections with clinical and immune features

“…In pursuit of this goal, numerous studies have devised intricate multigene expression profiles ( Frew and Moch, 2015 ). These profiles, whether utilized independently or in conjunction with the conventional stratification system, have demonstrated their capacity to improve the precision of ccRCC prognosis ( Rydzanicz et al, 2013 ; Frew and Moch, 2015 ; Wang et al, 2022 ; Zhang et al, 2022 ). Nevertheless, the collective insights derived from molecular and clinicopathological parameters still do not provide precise prognostications for patient outcomes.…”