Application of Random Forest and data integration identifies three dysregulated genes and enrichment of Central Carbon Metabolism pathway in Oral Cancer

Author:

Mukhopadhyay Srija,Ghosh Sahana,Das Debodipta,Arun P.,Roy Bidyut,Biswas Nidhan K.,Maitra Arindam,Majumder Partha P.ORCID

Abstract

Abstract Background Studies of epigenomic alterations associated with diseases primarily focus on methylation profiles of promoter regions of genes, but not of other genomic regions. In our past work (Das et al. 2019) on patients suffering from gingivo-buccal oral cancer – the most prevalent form of cancer among males in India – we have also focused on promoter methylation changes and resultant impact on transcription profiles. Here, we have investigated alterations in non-promoter (gene-body) methylation profiles and have carried out an integrative analysis of gene-body methylation and transcriptomic data of oral cancer patients. Methods Tumor and adjacent normal tissue samples were collected from 40 patients. Data on methylation in the non-promoter (gene-body) regions of genes and transcriptome profiles were generated and analyzed. Because of high dimensionality and highly correlated nature of these data, we have used Random Forest (RF) and other data-analytical methods. Results Integrative analysis of non-promoter methylation and transcriptome data revealed significant methylation-driven alterations in some genes that also significantly impact on their transcription levels. These changes result in enrichment of the Central Carbon Metabolism (CCM) pathway, primarily by dysregulation of (a) NTRK3, which plays a dual role as an oncogene and a tumor suppressor; (b) SLC7A5 (LAT1) which is a transporter dedicated to essential amino acids, and is overexpressed in cancer cells to meet the increased demand for nutrients that include glucose and essential amino acids; and, (c) EGFR which has been earlier implicated in progression, recurrence, and stemness of oral cancer, but we provide evidence of epigenetic impact on overexpression of this gene for the first time. Conclusions In rapidly dividing cancer cells, metabolic reprogramming from normal cells takes place to enable enhanced proliferation. Here, we have identified that among oral cancer patients, genes in the CCM pathway – that plays a fundamental role in metabolic reprogramming – are significantly dysregulated because of perturbation of methylation in non-promoter regions of the genome. This result compliments our previous result that perturbation of promoter methylation results in significant changes in key genes that regulate the feedback process of DNA methylation for the maintenance of normal cell division.

Funder

Department of Biotechnology, Government of West Bengal

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Genetics,Oncology

Reference50 articles.

1. Jiao, Y., Widschwendter, M., Teschendorff, AE. A systems-level integrative framework for genome-wide DNA methylation and gene expression data identifies differential gene expression modules under epigenetic control. Bioinformatics. 2014; 30:2360–2366. doi: https://doi.org/10.1093/bioinformatics/btu316.

2. Udali S, Guarini P, Ruzzenente A, Ferrarini A, Guglielmi A, Lotto V, Tononi P, Pattini P, Moruzzi S, Campagnaro T, Conci S, Olivieri O, Corrocher R, Delledonne M, Choi S-W, Friso S. DNA methylation and gene expression profiles show novel regulatory pathways in hepatocellular carcinoma. Clin Epigenet. 2015;7:43. https://doi.org/10.1186/s13148-015-0077-1.

3. Li M, Balch C, Montgomery JS, Jeong M, Chung JH, Yan P, Huang T, HM KS, Nephew KP. Integrated analysis of DNA methylation and gene expression reveals specific signaling pathways associated with platinum resistance in ovarian cancer. BMC Med Genomics. 2009;2:34. https://doi.org/10.1186/1755-8794-2-34.

4. Das D, Ghosh S, Maitra A, Biswas NK, Panda CK, Roy B, Sarin R, Majumder PP. Epigenomic dysregulation-mediated alterations of key biological pathways and tumor immune evasion are hallmarks of gingivo-buccal oral cancer. Clin Epigenet. 2019;11(1):178. https://doi.org/10.1186/s13148-019-0782-2.

5. Ma X, Liu Z, Zhang Z, Huang X, Tang W. Multiple network algorithm for epigenetic modules via the integration of genome-wide DNA methylation and gene expression data. BMC Bioinformatics. 2017;18:72. https://doi.org/10.1186/s12859-017-1490-6.

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