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Identification of a four‐gene metabolic signature predicting overall survival for hepatocellular carcinoma
- Source :
- Journal of Cellular Physiology. 235:1624-1636
- Publication Year :
- 2019
- Publisher :
- Wiley, 2019.
-
Abstract
- While hundreds of consistently altered metabolic genes had been identified in hepatocellular carcinoma (HCC), the prognostic role of them remains to be further elucidated. Messenger RNA expression profiles and clinicopathological data were downloaded from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma and GSE14520 data set from the Gene Expression Omnibus database. Univariate Cox regression analysis and lasso Cox regression model established a novel four-gene metabolic signature (including acetyl-CoA acetyltransferase 1, glutamic-oxaloacetic transaminase 2, phosphatidylserine synthase 2, and uridine-cytidine kinase 2) for HCC prognosis prediction. Patients in the high-risk group shown significantly poorer survival than patients in the low-risk group. The signature was significantly correlated with other negative prognostic factors such as higher α-fetoprotein. The signature was found to be an independent prognostic factor for HCC survival. Nomogram including the signature shown some clinical net benefit for overall survival prediction. Furthermore, gene set enrichment analyses revealed several significantly enriched pathways, which might help explain the underlying mechanisms. Our study identified a novel robust four-gene metabolic signature for HCC prognosis prediction. The signature might reflect the dysregulated metabolic microenvironment and provided potential biomarkers for metabolic therapy and treatment response prediction in HCC.
- Subjects :
- Adult
Male
0301 basic medicine
Carcinoma, Hepatocellular
Physiology
Nitrogenous Group Transferases
Clinical Biochemistry
Kaplan-Meier Estimate
Biology
03 medical and health sciences
0302 clinical medicine
Biomarkers, Tumor
medicine
Overall survival
Humans
Aspartate Aminotransferases
Acetyl-CoA C-Acetyltransferase
Gene
Aged
Messenger RNA
Kinase
Proportional hazards model
Liver Neoplasms
Cell Biology
Middle Aged
Nomogram
Prognosis
medicine.disease
Nomograms
030104 developmental biology
030220 oncology & carcinogenesis
Acetyltransferase
Hepatocellular carcinoma
Cancer research
Female
Uridine Kinase
Transcriptome
Subjects
Details
- ISSN :
- 10974652 and 00219541
- Volume :
- 235
- Database :
- OpenAIRE
- Journal :
- Journal of Cellular Physiology
- Accession number :
- edsair.doi.dedup.....5f77d7acff1ff1ebff870aa7ecba0589
- Full Text :
- https://doi.org/10.1002/jcp.29081