Development and Validation of a Novel Mitophagy-Related Gene Prognostic Signature for Hepatocellular Carcinoma Based on Immunoscore Classification of Tumor.
Hao ChenJinghua WangRuijie ZengYujun LuoKehang GuoHuihuan WuQi YangRui JiangWeihong ShaZewei ZhuoPublished in: Journal of oncology (2021)
Emerging evidence suggested that mitophagy may play an important role in the progression of hepatocellular carcinoma (HCC), whereas the association between mitophagy-related genes and HCC patients' prognosis remains unknown. In this study, we aimed to investigate the potential prognostic values of mitophagy-related genes (MRGs) on HCC patients at the genetic level. According to median immunoscore, we categorized HCC patients from TCGA cohort into two immune score groups, while 39 differential expression MRGs were identified. By using univariate analysis, we screened out 18 survival-associated MRGs, and then, the least absolute shrinkage and selection operator (LASSO) analysis was applied to construct a prognosis model that consisted of 9 MRGs (ATG7, ATG9A, BNIP3L, GABARAPL1, HTRA2, MAP1LC3B2, TFE3, TIGAR, and TOMM70). In our prognostic model, overall survival in the high and low-risk groups was significantly different (P < 0.001), and the respective areas under the curve (AUC) of our prognostic model were 0.686 for 3-year survival in the TCGA cohort and 0.776 for 3-year survival in the ICGC cohort. Moreover, we identified the risk score as the independent factor for predicting the HCC patients' prognosis by using single and multifactor analyses, and a nomogram was also constructed for future clinical application. Further functional analyses showed that the immune status between two risk groups was significantly different. Our findings may provide a novel mitophagy-related gene signature, and these will be better used for prognostic prediction in HCC, thus improving patient outcome.
Keyphrases
- end stage renal disease
- newly diagnosed
- ejection fraction
- chronic kidney disease
- prognostic factors
- machine learning
- case report
- peritoneal dialysis
- deep learning
- gene expression
- patient reported outcomes
- free survival
- dna methylation
- transcription factor
- lymph node metastasis
- current status
- tandem mass spectrometry
- gas chromatography