Open AccessIdentification and validation of a glycolysis-associated multiomics prognostic model for hepatocellular carcinoma
Author(s) -
Tuo Deng,
Qian Ye,
Chen Jin,
Manman Wu,
Kaiyu Chen,
Jinhuan Yang,
Zi-Yan Chen,
Xianjun Yu,
Gang Chen,
Yi Wang
Publication year - 2021
Publication title -
aging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 90
ISSN - 1945-4589
DOI - 10.18632/aging.202613
Subject(s) - glycolysis , hepatocellular carcinoma , cancer research , biology , medicine , oncology , metabolism
Increased glycolysis has been reported as a major metabolic hallmark in many cancers, and is closely related to malignant behavior of tumors. However, the potential mechanism of glycolysis in hepatocellular carcinoma (HCC) and its prognostic value are not well understood. To address this, we investigated glycolysis-related gene expression data of patients with HCC from TCGA and ICGC. Patients were categorized into three different glycolysis-associated subgroups: Glycolysis-M, Glycolysis-H, and Glycolysis-L. We found that Glycolysis-H combined with Glycolysis-M (Glycolysis-H+M) subgroup was associated with poor overall survival and distinct cancer stem cell characteristics and immune infiltrate patterns. Additionally, multiomics-based analyses were conducted to evaluate genomic patterns of glycolysis subgroups, including their gene mutations, copy number variations, and RNA-sequencing data. Finally, a glycolysis-associated multiomics prognostic model (GMPM) consisting of 19 glycolysis-associated genes was developed. The capability of GMPM in categorizing patients with HCC into high- and low-risk groups was validated with independent HCC datasets. Finally, GMPM was confirmed as an independent risk factor for the prognosis of patients with HCC. We believe that our findings provide new insights into the mechanism of glycolysis and highlight the potential clinical value of GMPM in predicting the prognosis of patients with HCC.