Mitophagy-related gene TRIP13 predicts prognosis and immune response and promotes proliferation and migration in vitro and in vivo of clear cell renal cell carcinoma - Jiang, Zhongjun; Wang, Lanlan; He, Zhongrun; Guo, Lian; Luo, Wen; Fu, Ying; Xiao, Qiyu; Chen, Guanglan; Liu, Yinzi (Frontiers in Pharmacology, 2025)
BackgroundThe incidence of clear cell renal cell carcinoma (ccRCC) is increasing every year. Mitophagy is a unique form of autophagy that plays a crucial role in cancer development and invasion. However, its role in ccRCC remains to be fully elucidated.MethodsAfter extracting mitophagy-related genes (MRGs), differential expression analysis was performed to screen differentially expressed genes (DEGs). Univariate Cox regression analysis was used to screen prognostic-related DEGs, CNV mutation frequencies were compared, and consensus cluster analysis was constructed to evaluate the survival and functional enrichment status among different subtypes. LASSO Cox regression analysis was used to identify key prognostic genes and construct risk models to evaluate the prognostic value and immune contribution. The protein and mRNA expression levels of independent prognostic genes and their effects on ccRCC function were verified by in vitro and in vivo experiments.ResultsThe study found 174 DEGs, including 9 prognosis-related DEGs. These 9 DEGs were used to cluster ccRCC patients into two subtypes. Significant differences existed between the two subtypes in the survival status and KEGG functions. Finally, three core genes (JUP, TRIP13, and ACAD11) were identified for constructing a risk model, which can accurately predict the prognosis of ccRCC patients and evaluate the immune status. TRIP13 was identified as a key independent prognostic gene for ccRCC, and its protein and mRNA expression levels were highly expressed in ccRCC. ccRCC growth and motility can be markedly inhibited by TRIP13 knockdown, which also increases their susceptibility to destruction by CD8+ T cells.ConclusionThe prognosis and immune response of patients with ccRCC could be reliably estimated by the model in our cohorts created using MRGs in this research. The development of ccRCC is significantly influenced by MRGs, particularly TRIP13. This study can assist in offering ccRCC patients individualized treatment options.