Scan-tcga tools for integrated epigenomic and transcriptomic analysis of tumor subgroups

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.