Abstract
BackgroundRecent large-scale cancer sequencing studies have discovered many novel cancer driver genes (CDGs) in human cancers. Some studies also suggest that CDG mutations contribute to cancer-associated epigenomic and transcriptomic alterations across many cancer types. Here we aim to improve our understanding of the connections between CDG mutations and altered cancer cell epigenomes and transcriptomes on pan-cancer level and how these connections contribute to the known association between epigenome and transcriptome.MethodUsing multi-omics data including somatic mutation, DNA methylation, and gene expression data of 20 cancer types from The Cancer Genome Atlas (TCGA) project, we conducted a pan-cancer analysis to identify CDGs, when mutated, have strong associations with genome-wide methylation or expression changes across cancer types, which we refer as methylation driver genes (MDGs) or expression driver genes (EDGs), respectively.ResultsWe identified 32 MDGs, among which, eight are known chromatin modification or remodeling genes. Many of the remaining 24 MDGs are connected to chromatin regulators through either regulating their transcription or physically interacting with them as potential co-factors. We identified 29 EDGs, 26 of which are also MDGs. Further investigation on target genes’ promoters methylation and expression alteration patterns of these 26 overlapping driver genes shows that hyper-methylation of target genes’ promoters are significantly associated with down-regulation of the same target genes and hypo-methylation of target genes’ promoters are significantly associated with up-regulation of the same target genes.ConclusionThis finding suggests a pivotal role for genetically driven changes in chromatin remodeling in shaping DNA methylation and gene expression patterns during tumor development.
Highlights
Recent large-scale cancer sequencing studies have discovered many novel cancer driver genes (CDGs) in human cancers
We used the number of genome-wide differentially methylated sites as the test statistic to measure degree of genome-wide methylation changes associated with the mutation status of a CDG for one cancer type
We use Benjamini-Hochberg procedure to adjust for multiple comparisons for pi, where the adjustment is done within the group of CDGs that were mutated in the same number of cancer types
Summary
Recent large-scale cancer sequencing studies have discovered many novel cancer driver genes (CDGs) in human cancers. A recent study investigated associations between driver gene mutations and DNA methylation alterations across many cancer types [5], and identified associations between mutated driver genes and site-specific methylation changes as well as some genome-wide trends in specific cancer types. They further used these mutation-methylation associations to better define cancer subtypes. It remains largely unknown how the CDG mutations contribute to changes in cancer cell epigenomes on a pan-cancer level [6]. A better understanding of the connections between CDGs and altered cancer cell epigenomes is an important goal, since mutations in epigenetic regulators could be novel targets for anti-cancer therapies [6]
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