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      Data mining of the expression and regulatory role of BCAT1 in hepatocellular carcinoma

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          Abstract

          Branched chain amino acid transaminase 1 (BCAT1) catalyzes the production of glutamates and branched-chain α-ketoacids from branched chain amino acids, and a normal BCAT1 expression is associated with tumorigenesis. Sequencing data from public databases, including The Cancer Genome Atlas, was used to analyze BCAT1 expression and regulation networks for hepatocellular carcinoma (HCC). Expression and methylation were assessed using UALCAN analysis, and data from multiple datasets concerning the BCAT1 expression level and associated survival rates were further analyzed using HCCDB; interaction networks of biological function were constructed using GeneMANIA. LinkedOmics was used to indicate correlations between BCAT1 and any identified differentially expressed genes. Gene enrichment analysis of BCAT-associated genes was conducted using the Web-based Gene SeT AnaLysis Toolkit. The expression levels of BCAT1 were increased in patients with HCC and in most cases, the level of BCAT1 promoter methylation was reduced. Interaction network analysis suggested that BCAT1 was involved in ‘metabolism’, ‘carcinogenesis’ and the ‘immune response’ via numerous cancer-associated pathways. The present study revealed the expression patterns and potential function networks of BCAT1 in HCC, providing insights for future research into the role of BCAT1 in hepatocarcinogenesis. In addition, the study provided researchers with a way to analyze the genes of interest so they can continue their research in the right direction.

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          Most cited references47

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          Gene expression in fixed tissues and outcome in hepatocellular carcinoma.

          It is a challenge to identify patients who, after undergoing potentially curative treatment for hepatocellular carcinoma, are at greatest risk for recurrence. Such high-risk patients could receive novel interventional measures. An obstacle to the development of genome-based predictors of outcome in patients with hepatocellular carcinoma has been the lack of a means to carry out genomewide expression profiling of fixed, as opposed to frozen, tissue. We aimed to demonstrate the feasibility of gene-expression profiling of more than 6000 human genes in formalin-fixed, paraffin-embedded tissues. We applied the method to tissues from 307 patients with hepatocellular carcinoma, from four series of patients, to discover and validate a gene-expression signature associated with survival. The expression-profiling method for formalin-fixed, paraffin-embedded tissue was highly effective: samples from 90% of the patients yielded data of high quality, including samples that had been archived for more than 24 years. Gene-expression profiles of tumor tissue failed to yield a significant association with survival. In contrast, profiles of the surrounding nontumoral liver tissue were highly correlated with survival in a training set of tissue samples from 82 Japanese patients, and the signature was validated in tissues from an independent group of 225 patients from the United States and Europe (P=0.04). We have demonstrated the feasibility of genomewide expression profiling of formalin-fixed, paraffin-embedded tissues and have shown that a reproducible gene-expression signature correlated with survival is present in liver tissue adjacent to the tumor in patients with hepatocellular carcinoma. Copyright 2008 Massachusetts Medical Society.
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            Focal gains of VEGFA and molecular classification of hepatocellular carcinoma.

            Hepatocellular carcinomas represent the third leading cause of cancer-related deaths worldwide. The vast majority of cases arise in the context of chronic liver injury due to hepatitis B virus or hepatitis C virus infection. To identify genetic mechanisms of hepatocarcinogenesis, we characterized copy number alterations and gene expression profiles from the same set of tumors associated with hepatitis C virus. Most tumors harbored 1q gain, 8q gain, or 8p loss, with occasional alterations in 13 additional chromosome arms. In addition to amplifications at 11q13 in 6 of 103 tumors, 4 tumors harbored focal gains at 6p21 incorporating vascular endothelial growth factor A (VEGFA). Fluorescence in situ hybridization on an independent validation set of 210 tumors found 6p21 high-level gains in 14 tumors, as well as 2 tumors with 6p21 amplifications. Strikingly, this locus overlapped with copy gains in 4 of 371 lung adenocarcinomas. Overexpression of VEGFA via 6p21 gain in hepatocellular carcinomas suggested a novel, non-cell-autonomous mechanism of oncogene activation. Hierarchical clustering of gene expression among 91 of these tumors identified five classes, including "CTNNB1", "proliferation", "IFN-related", a novel class defined by polysomy of chromosome 7, and an unannotated class. These class labels were further supported by molecular data; mutations in CTNNB1 were enriched in the "CTNNB1" class, whereas insulin-like growth factor I receptor and RPS6 phosphorylation were enriched in the "proliferation" class. The enrichment of signaling pathway alterations in gene expression classes provides insights on hepatocellular carcinoma pathogenesis. Furthermore, the prevalence of VEGFA high-level gains in multiple tumor types suggests indications for clinical trials of antiangiogenic therapies.
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              DNA methylation-based prognosis and epidrivers in hepatocellular carcinoma.

              Epigenetic deregulation has emerged as a driver in human malignancies. There is no clear understanding of the epigenetic alterations in hepatocellular carcinoma (HCC) and of the potential role of DNA methylation markers as prognostic biomarkers. Analysis of tumor tissue from 304 patients with HCC treated with surgical resection allowed us to generate a methylation-based prognostic signature using a training-validation scheme. Methylome profiling was done with the Illumina HumanMethylation450 array (Illumina, Inc., San Diego, CA), which covers 96% of known cytosine-phosphate-guanine (CpG) islands and 485,000 CpG, and transcriptome profiling was performed with Affymetrix Human Genome U219 Plate (Affymetrix, Inc., Santa Clara, CA) and miRNA Chip 2.0. Random survival forests enabled us to generate a methylation signature based on 36 methylation probes. We computed a risk score of mortality for each individual that accurately discriminated patient survival both in the training (221 patients; 47% hepatitis C-related HCC) and validation sets (n = 83; 47% alcohol-related HCC). This signature correlated with known predictors of poor outcome and retained independent prognostic capacity of survival along with multinodularity and platelet count. The subset of patients identified by this signature was enriched in the molecular subclass of proliferation with progenitor cell features. The study confirmed a high prevalence of genes known to be deregulated by aberrant methylation in HCC (e.g., Ras association [RalGDS/AF-6] domain family member 1, insulin-like growth factor 2, and adenomatous polyposis coli) and other solid tumors (e.g., NOTCH3) and describes potential candidate epidrivers (e.g., septin 9 and ephrin B2).
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                Author and article information

                Journal
                Oncol Lett
                Oncol Lett
                OL
                Oncology Letters
                D.A. Spandidos
                1792-1074
                1792-1082
                December 2019
                30 September 2019
                30 September 2019
                : 18
                : 6
                : 5879-5888
                Affiliations
                [1 ]Laboratory of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Guilin Medical University, Guilin, Guangxi 541001, P.R. China
                [2 ]Scientific Experiment Center, Guilin Medical University, Guilin, Guangxi 541001, P.R. China
                [3 ]Clinical School of Medicine, Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
                Author notes
                Correspondence to: Professor Weijia Liao or Dr Renzhi Yao, Laboratory of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Guilin Medical University, 15 Lequn Road, Guilin, Guangxi 541001, P.R. China, E-mail: liaoweijia288@ 123456163.com , E-mail: yaorenzhi_gzb@ 123456163.com
                [*]

                Contributed equally

                Article
                OL-0-0-10932
                10.3892/ol.2019.10932
                6865021
                88ffb4b2-f616-40f5-b51b-5ac393b3fa76
                Copyright: © Zou et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

                History
                : 10 May 2019
                : 06 September 2019
                Categories
                Articles

                Oncology & Radiotherapy
                branched chain amino acid transaminase 1,hepatocellular carcinoma,expression,network analysis,data mining

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