Involved in these pathways that are bound by these PRC2 proteins exhibit differential methylation (Figure 5 and Additional file 2: Figure S4 and 5A-D). The ectoderm and epidermis developmentpathways were shown to be enriched with hypomethylated genes, which was driven by the non-PRC2 targets; the PRC2 target genes in these pathways were more prone to be hypermethylated (Additional file 2: Figure S5A and 5B). In contrast, (Z)-Pitavastatin calcium the pathways involved in embryo development and neurogenesis were enriched among hypermethylated genes, and both PRC2 PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/26369523 and nonPRC2 targets showed a higher proportion of hypermethylated genes, although the trend seemed stronger among the PRC2 targets (Additional file 2: Figure S5C and 5D). Interestingly, while around 40 of non-PRC2 target genes involved in ectoderm and epidermis development were differentially methylated in multiple myeloma (comparable to the other types of cancers), none of the PRC2target genes are significantly differentially methylated in multiple myeloma. Additional concept types available in LRpath include metabolite concepts that combine metabolic enzyme coding genes, DrugBank concepts, and transcription factor targets (see Methods for details). In our directional analysis we found several metabolite concepts that were consistently enriched across cancer types. The hypomethylated concepts included several metabolite concepts in androgen and estrogen metabolism, C21-steroid hormone PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/28484091 biosynthesis and metabolism, tyrosine metabolism, and xenobiotics metabolism (Additional file 2: Figure S6A). Genes involved in these concepts encode several prominent groups of enzymes including multiple members of the Cytochrome P450 family, steroid biosynthesis enzymes and members of the UDP glucuronosyltransferase family. The hypermethylated metabolite concepts included cyclic AMP (cAMP) and cyclic GMP (cGMP) which include genes encoding several phosphodiesterases and adenylate cyclases (Additional file 2: Figure S6A). In addition, we identified twelve Drug Bank concepts, each of which consists of genes known to interact with a specific drug (Additional file 2: Figure S6B). Several transcription factors were predicted to target genes enriched with hypermethylation across cancer types, including AHR-ARNT, ATF2 (CREBP1), PAX4, E2F2 and NRSF (Additional file 2: Figure S6C). In addition to clustering pathways and other biological concepts significant across several cancer types, we also performed clustering on biological concepts significant in any one or more cancer types (Figure 2- right side). The two heatmaps in Figure 2 look surprisingly similar, suggesting that the majority of pathways affected by DNA methylation in cancer are common to multiple cancer types.Identification of biological concepts enriched or depleted in genes dysregulated via CpG methylation across cancer types (Non-directional LRpath analysis)Similar to the directional analysis results performed on ten tumor versus normal methylation studies, theKim et al. BMC Genomics 2012, 13:526 http://www.biomedcentral.com/1471-2164/13/Page 6 ofcg00995520 (KCNA3)1 0.8 0.6 0.4 0.2Breast ( FDR < 6.7?0-20 )1 0.8 0.6 0.4 0.2Lung AC (FDR < 5 ?0-4)Percentage of Methylation1 0.8 0.6 0.4 0.2Colorectal (FDR < 1.3?0-7)0.8 0.6 0.4 0.2Ovarian (FDR < 0.12)1 0.8 0.6 0.4 0.2Kidney ( FDR < 1.1?0-18)1 0.8 0.6 0.4 0.2Prostate ( FDR < 5.0?0-10 )Normal TumorFigure 3 Hypermethylation in the KCNA3 promoter region across multiple cancer types. Voltage gated channel activity is highly.
