Construction of a prognosis-predicting model based on autophagy-related genes for hepatocellular carcinoma (HCC) patients

Aging (Albany NY). 2020 Jul 18;12(14):14582-14592. doi: 10.18632/aging.103507. Epub 2020 Jul 18.

Abstract

Background: Autophagy, a highly conserved cellular catabolic process by which the eukaryotic cells deliver autophagosomes engulfing cellular proteins and organelles to lysosomes for degradation, is critical for maintaining cellular homeostasis in response to various signals and nutrient stresses. The dysregulation of autophagy has been noted in the pathogenesis of cancers. Our study aims to investigate the prognosis-predicting value of autophagy-related genes (ARG) in hepatocellular carcinoma (HCC).

Results: The signature was constructed based on eight ARGs, which stratified HCC patients into high- and low-risk groups in terms of overall survival (OS) (Hazard Ratio, HR=4.641, 95% Confidential Interval, CI, 3.365-5.917, P=0.000). The ARG signature is an independent prognostic indicator for HCC patients (HR = 1.286, 95% CI, 1.194-1.385; P < 0.001). The area under the receiver operating characteristic (ROC) curve (AUC) for 5-year survival is 0.765.

Conclusion: This study provides a potential prognostic signature for predicting the prognosis of HCC patients and molecular insights into the significance of autophagy in HCC.

Methods: Sixty-two differentially expressed ARGs and the clinical characteristics and basic information of the 369 enrolled HCC patients were retrieved from The Cancer Genome Atlas (TCGA) database. the Cox proportional hazard regression analysis was adopted to identify survival-related ARGs, based on which a prognosis predicting signature was constructed.

Keywords: The Cancer Genome Atlas; autophagy-related genes; hepatocellular carcinoma; prognosis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Area Under Curve
  • Autophagy / genetics*
  • Biomarkers, Tumor
  • Carcinoma, Hepatocellular / diagnosis*
  • Carcinoma, Hepatocellular / genetics*
  • Databases, Genetic
  • Gene Expression Regulation, Neoplastic / genetics
  • Genetic Markers
  • Humans
  • Kaplan-Meier Estimate
  • Models, Theoretical
  • Predictive Value of Tests
  • Prognosis
  • Survival Analysis

Substances

  • Biomarkers, Tumor
  • Genetic Markers