Construction and validation of a prognostic model based on autophagy-related genes for hepatocellular carcinoma in the Asian population

Abstract

Abstract Background and objective Hepatocellular carcinoma (HCC), which has a complex pathogenesis and poor prognosis, is one of the most common malignancies worldwide. Hepatitis virus B infection is the most common cause of HCC in Asian patients. Autophagy is the process of digestion and degradation, and studies have shown that autophagy-associated effects are closely related to the development of HCC. In this study, we aimed to construct a prognostic model based on autophagy-related genes (ARGs) for the Asian HCC population to provide new ideas for the clinical management of HCC in the Asian population. Methods The clinical information and transcriptome data of Asian patients with HCC were downloaded from The Cancer Genome Atlas (TCGA) database, and 206 ARGs were downloaded from the human autophagy database (HADB). We performed differential and Cox regression analyses to construct a risk score model. The accuracy of the model was validated by using the Kaplan–Meier (K–M) survival curve, receiver operating characteristic (ROC) curve, and univariate and multivariate Cox independent prognostic analyses. The results Thirteen ARGs that were significantly associated with prognosis were finally identified by univariate and multivariate Cox regression analyses. The K–M survival curves showed that the survival rate of the low-risk group was significantly higher than that of the high-risk group (p < 0.001), and the multi-indicator ROC curves further demonstrated the predictive ability of the model (AUC = 0.877). Conclusion The risk score model based on ARGs was effective in predicting the prognosis of Asian patients with HCC.

Keywords

• Hepatocellular carcinoma
• Autophagy-related gene
• Prognostic model
• The Cancer Genome Atlas database