An integrated prognostic model of nuclear-encoded mitochondrial gene signature and clinical information for hepatocellular carcinoma

Abstract

Objective·To establish a prognostic model for the overall survival (OS) of hepatocellular carcinoma (HCC) based on mitochondrial genes and clinical information.Methods·The gene expression and the clinical data of 369 HCC patients and 50 controls with normal liver were downloaded from The Cancer Genome Atlas (TCGA) database. The nuclear-encoded mitochondrial genes (NEMGs) were obtained from the MitoCarta3.0 database. The "DESeq2" R package and univariate Cox analysis were used to select NEMGs [ubiquinol cytochrome C reductase hinge protein (UQCRH), ATP citrate lyase (ACLY), phosphoenolpyruvate carboxykinase 2 (PCK2), Bcl-2 homologous antagonist/killer1 (BAK1), Bcl-2-associated X protein (BAX) and Bcl-2/adenovirus E1B interacting protein 3-like (BNIP3L)] in HCC that were associated with OS of HCC and participated in dysregulation of oxidative phosphorylation, tricarboxylic acid cycle and cell apoptosis. Multivariate Cox analysis was applied to select independent risk factors for OS of HCC. A comprehensive prognostic model and a prognostic nomogram with 6-NEMG risk characteristics and TNM staging were established. By using the median of prognostic scores as a cut-off, HCC patients were classified into low-risk and high-risk group. Kaplan-Meier survival curve analysis was conducted and log-rank test was performed to evaluate the survival rates between the low-risk and high-risk group. The area under the curve (AUC) values of receiver operating characteristic (ROC) curve were calculated via using the "timeROC" package. The prognostic model for HCC was validated by using the GEO HCC cohort (GSE14520) for 1, 3 and 5 years. Finally, the relative expression level of 6-NEMG was validated in 34 clinical samples of HCC from Xinhua Hospital, Shanghai Jiao Tong University School of Medicine by using real-time quantitative polymerase chain reaction (qPCR) method.Results·Compared to 6-NEMG risk signature only (AUCs for 1, 3 and 5 years were 0.77, 0.66 and 0.65, respectively) or TNM stage only (AUCs for 1, 3 and 5 years were 0.66, 0.67 and 0.63, respectively), ROC curve analysis showed that this integrated prognostic model displayed better predictive performance for 1-year (AUC, 0.78), 3-year (AUC, 0.73) and 5-year (AUC, 0.69) OS of HCC. The Kaplan-Meier survival curve analysis showed that the OS of HCC patients in the high-risk group was significantly worse than that in the low-risk group (P=0.001). In addition, predictive performance of the prognostic model (AUC for 1, 3 and 5 years is 0.67, 0.66 and 0.74, respectively) and prognostic differences between the high-risk and low-risk group (P=0.001) were further validated in GEO (GSE14520) external cohort, and these results were consistent with the TCGA data. In addition to BNIP3L, dysregulation of five other NEMGs in the clinical HCC cohort was validated. The correlation analysis in GSE14520 and HCC clinical cohort showed a positive correlation between prognosis score and the size and number of tumors.Conclusion·A new prognostic model that combines 6-NEMG risk characteristics with TNM staging for predicting OS in HCC patients was constructed and validated. This model may help improve the prognosis prediction of HCC patients.

Keywords

• nuclear encoded mitochondrial gene
• hepatocellular carcinoma
• tcga
• geo
• overall survival