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Research Paper|Volume 13, Issue 9|pp 13318—13332

Development of a prognostic model for hepatocellular carcinoma using genes involved in aerobic respiration

Jiawei Rao1,2,3, Xukun Wu4, Xiaozhuan Zhou5, Ronghai Deng1,2,3, Yi Ma1,2,3
  • 1Organ Transplant Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, China
  • 2Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, China
  • 3Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, China
  • 4Department of Hepatology Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
  • 5Department of Gastroenterology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
* Equal contribution
# Co-first authors
Received: August 17, 2020Accepted: October 3, 2020Published: April 26, 2021
https://doi.org/10.18632/aging.203021

Copyright: © 2021 Rao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide. Currently, recent risk stratification has only focused on liver function and tumor characteristics. Thus, the purpose of this study was to develop a prognostic model based on genes involved in aerobic respiration. Matched tumor and normal tissues from TCGA and ICGC cohorts were analyzed to identify 15 overlapping differential expressed genes. Cox univariate analysis of the 15 genes in the TCGA cohort revealed they were all associated with disease-specific survival (DSS) in HCC patients. Using LASSO estimation and the optimal value for penalization coefficient lambda 12 genes were selected for the prognostic model, and then HCC patients in the TCGA cohort were dichotomized into low-risk and high-risk groups. Univariate and multivariate Cox analysis demonstrated patients in low-risk group had better survival. Validation of the risk score model with the ICGC cohort produces results consistent with those of the TCGA cohort. In conclusion, this study developed and validated a prognostic model of HCC through a comprehensive analysis of genes involved in aerobic respiration. This model may help develop personalized treatments for patients with HCC.