Abstract
BackgroundHepatocellular carcinoma (HCC) is the most common primary liver cancer in the world. Although great advances in HCC diagnosis and treatment have been achieved, due to the complicated mechanisms in tumor development and progression, the prognosis of HCC is still dismal. Recent studies have revealed that the Warburg effect is related to the development, progression and treatment of various cancers; however, there have been a few explorations of the relationship between glycolysis and HCC prognosis.MethodsmRNA expression profiling was downloaded from public databases. Gene set enrichment analysis (GSEA) was used to explore glycolysis-related genes (GRGs), and the LASSO method and Cox regression analysis were used to identify GRGs related to HCC prognosis and to construct predictive models associated with overall survival (OS) and disease-free survival (DFS). The relationship between the predictive model and the tumor mutation burden (TMB) and tumor immune microenvironment (TIME) was explored. Finally, real-time PCR was used to validate the expression levels of the GRGs in clinical samples and different cell lines.ResultsFive GRGs (ABCB6, ANKZF1, B3GAT3, KIF20A and STC2) were identified and used to construct gene signatures to predict HCC OS and DFS. Using the median value, HCC patients were divided into low- and high-risk groups. Patients in the high-risk group had worse OS/DFS than those in the low-risk group, were related to higher TMB and were associated with a higher rate of CD4+ memory T cells resting and CD4+ memory T cells activated. Finally, real-time PCR suggested that the five GRGs were all dysregulated in HCC samples compared to adjacent normal samples.ConclusionsWe identified five GRGs associated with HCC prognosis and constructed two GRGs-related gene signatures to predict HCC OS and DFS. The findings in this study may contribute to the prediction of prognosis and promote HCC treatment.
Highlights
Hepatocellular carcinoma (HCC) is the most common primary liver cancer in the world
In this study, using data obtained from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and International Cancer Genome Consortium Japan (ICGC) databases, we identified five glycolysis-related genes (GRGs) related to HCC prognosis
Identification of GRGs related to overall survival (OS) and construction of a gene signature for prediction of OS After removing patients with unknown survival information, those with less than 3 months of survival and those without clinicopathological information, a total of 273 HCC patients in the TCGA dataset were included in the survival analysis
Summary
Great advances in HCC diagnosis and treatment have been achieved, due to the complicated mechanisms in tumor development and progression, the prognosis of HCC is still dismal. Recent studies have revealed that the Warburg effect is related to the development, progression and treatment of various cancers; there have been a few explorations of the relationship between glycolysis and HCC prognosis. New biomarkers related to tumor development, progression and prognosis could be identified using bioinformatic methods, which might contribute to revealing the complex biological processes related to cancers and could be potential therapeutic targets. Using The Cancer Genome Atlas (TCGA) database, methylation profiling suggested that several biomarkers including DET (amplification), WNT signalling (CTNNB1 mutation) and IDH1 (mutation) were potential therapeutic targets for HCC [8]
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