Scan_tcga tools for integrated epigenomic and transcriptomic analysis of tumor subgroups. (October 2016)

• Record Type: Journal Article
• Authors: Chatterjee, Aniruddha; Stockwell, Peter A; Rodger, Euan J; Parry, Matthew F; Eccles, Michael R
• Is Part Of: Epigenomics. Volume 8:Number 10(2016)
• Page Start: 1315
• Page End: 1330
• Publication Date: 2016-10
• Subjects: cancer genome atlas -- DNA methylation -- gene expression -- melanoma -- miRNA; Epigenesis -- Periodicals; Genomics -- Periodicals; Chromatin -- Periodicals; DNA -- Periodicals; 572.87
• DOI: 10.2217/epi-2016-0063
• Languages: English
• ISSNs: 1750-1911

Abstract

Aim: The Cancer Genome Atlas contains multiple levels of genomic data (mutation, gene expression, DNA methylation, copy number variation) for 33 cancer types for almost 11, 000 patients. However, a dearth of appropriate software tools makes it difficult for bench scientists to use these data effectively.Materials & methods: Here, we present a suite of flexible, fast and command line-based scripts that will allow retrieval and analysis of DNA methylation (tool: scan_tcga_methylation.awk), mRNA (tool: scan_tcga_mRNA.awk) and miRNA expression (tool: scan_tcga_miRNAs.awk) from cancer genome atlas network level 3 data.Results: We demonstrate the utility of these tools by analyzing DNA methylation and mRNA expression signatures of 60 frequently deregulated cancer genes and also of 30 miRNAs in primary (n = 102) and metastatic melanoma patients (n = 367).Conclusion: Our analysis illustrates the validity of the scan_tcga tools and reveals the epigenomic signatures and importance of identifying smaller patient subgroups with distinct molecular profiles.