Development and validation of mitochondrial metabolism-related genes in the prognostic and immunological characterization of clear cell renal cell carcinoma
Year: 2025
Type: article
Abstract: Robust ccRCC prognostic model established using six MMRGs (ACLY, ETNK2, FDX1, G0S2, HADH, and HSD11B2). The immune characteristics of patients with ccRCC in high risk and low risk groups are heterogeneous. Specifically, the infiltration levels of Tregs/T cells CD8 and the Immune/ESTIMATE score in the high risk group are significantly higher than those in the low risk group. Based on diagnostic genes, two molecular subtypes of ccRCC were successfully identified, and significant immunological heterogeneity was found between different subtypes. As the most prevalent subtype of renal cell carcinoma, clear cell renal cell carcinoma (ccRCC) exhibits a tendency for metastasis and recurrence and demonstrates resistance to both radiotherapy and chemotherapy. Mitochondrial metabolism, as an important bioenergy hub, profoundly affects the tumor microenvironment. This study aims to screen potential biomarkers of ccRCC based on mitochondrial metabolism-related genes (MMRGs). Transcriptomic data for ccRCC patients were retrieved from the TCGA and ArrayExpress databases. An integrated analytical approach incorporating differential expression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, and multivariate Cox analysis was employed to identify prognostic genes associated with ccRCC. To elucidate the biological characteristics distinguishing high risk and low risk ccRCC patients, we performed GO and KEGG enrichment analyses. The ssGSEA and CIBERSORT algorithms were utilized to characterize immune cell infiltration landscapes across ccRCC patient. Furthermore, consensus clustering analysis was was applied to stratify ccRCC patients. A robust prognostic model for ccRCC was constructed based on a signature comprising six MMRGs. Significant enrichment in the Wnt signaling pathway was identified by gene enrichment analysis for differentially expressed genes that were upregulated in the high risk versus low risk group. The high risk group exhibited significantly elevated infiltration levels of T cells CD8 and regulatory T cells compared to the low risk group. Consensus clustering analysis successfully partitioned the ccRCC cohort into two molecular subtypes exhibiting significant differences in immune and molecular characteristics. The prognostic model constructed based on MMRGs can effectively predict ccRCC patients and their immune characteristics, providing a new perspective on the relationship between MMRGs and ccRCC.
Authors: Lipeng Lu, Jianbin Jin, Dan Lu, Yangdi Peng, Yufang Fan
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,790
OpenAlex ID: W4416668934