Research Papers:

Gene network analysis reveals a novel 22-gene signature of carbon metabolism in hepatocellular carcinoma

Jinqiang Zhang, Melody Baddoo, Chang Han, Michael J. Strong, Jennifer Cvitanovic, Krzysztof Moroz, Srikanta Dash, Erik K. Flemington and Tong Wu _

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Oncotarget. 2016; 7:49232-49245. https://doi.org/10.18632/oncotarget.10249

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Jinqiang Zhang1, Melody Baddoo2, Chang Han1, Michael J. Strong2, Jennifer Cvitanovic3, Krzysztof Moroz1,3, Srikanta Dash1, Erik K. Flemington1,2, Tong Wu1

1Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, New Orleans, Louisiana, USA

2Bioinformatics Core, Tulane Health Sciences Center and Tulane Cancer Center, New Orleans, Louisiana, USA

3Biospecimen Core, Louisiana Cancer Research Consortium, New Orleans, Louisiana, USA

Correspondence to:

Tong Wu, email: twu@tulane.edu

Jinqiang Zhang, email: jzhang@tulane.edu

Keywords: transcriptome, carbon metabolism, weighted gene coexpression network analysis (WGCNA), citrate synthase (CS), Acetyl-CoA synthetases short-chain family member 1 (ACSS1)

Received: February 22, 2016     Accepted: May 28, 2016     Published: June 23, 2016


Although much progress has been made in understanding cancer cellular metabolism adaptation, the co-regulations between genes of metabolism and cancer pathways and their interactions remain poorly characterized. Here, we applied gene co-expression network analysis to 1509 metabolic gene expression data generated from 120 HCC and 180 non-tumor human liver tissues by microarray. Our analyses reveal that metabolism genes can be classified into different co-expression modules based on their associations with HCC related traits. The co-regulation mechanism of the carbon metabolism genes in normal liver tissues was interrupted during the processes of carcinogenesis. In parallel, we performed RNAseq analysis of HCC and non-tumor human liver tissues, and identified a unique 22-carbon-metabolism-gene-signature of increased expression. This gene signature was further verified in multiple microarray data sets, and its prognostic value was also proven by HCC patients’ survival data from TCGA. Additionally, the tumorigenic function of two representative genes, CS and ACSS1, were validated experimentally by cell growth and spheroid formation assays. The current study provides evidence for the reprogramming of the co-regulation network between carbon metabolism and cancer pathway genes in HCC. In addition, this study also reveals a unique 22-carbon-metabolism-gene-expression-signature in HCC. Strategies targeting these genes may represent new therapeutic approaches for HCC treatment.

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