Dataset Information

Classification of Colon Cancer Patients Based on the Methylation Patterns of Promoters.

ABSTRACT: Diverse somatic mutations have been reported to serve as cancer drivers. Recently, it has also been reported that epigenetic regulation is closely related to cancer development. However, the effect of epigenetic changes on cancer is still elusive. In this study, we analyzed DNA methylation data on colon cancer taken from The Caner Genome Atlas. We found that several promoters were significantly hypermethylated in colon cancer patients. Through clustering analysis of differentially methylated DNA regions, we were able to define subgroups of patients and observed clinical features associated with each subgroup. In addition, we analyzed the functional ontology of aberrantly methylated genes and identified the G-protein-coupled receptor signaling pathway as one of the major pathways affected epigenetically. In conclusion, our analysis shows the possibility of characterizing the clinical features of colon cancer subgroups based on DNA methylation patterns and provides lists of important genes and pathways possibly involved in colon cancer development.

SUBMITTER: Choi W

PROVIDER: S-EPMC4951400 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Classification of Colon Cancer Patients Based on the Methylation Patterns of Promoters.

Choi Wonyoung W Lee Jungwoo J Lee Jin-Young JY Lee Sun-Min SM Kim Da-Won DW Kim Young-Joon YJ

Genomics & informatics 20160630 2

Diverse somatic mutations have been reported to serve as cancer drivers. Recently, it has also been reported that epigenetic regulation is closely related to cancer development. However, the effect of epigenetic changes on cancer is still elusive. In this study, we analyzed DNA methylation data on colon cancer taken from The Caner Genome Atlas. We found that several promoters were significantly hypermethylated in colon cancer patients. Through clustering analysis of differentially methylated DNA ...[more]

PMID: 27445647

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Project description:Four different histones (H2A, H2B, H3, and H4; two subunits each) constitute a histone octamer, around which DNA wraps to form histone-DNA complexes called nucleosomes. Amino acid residues in each histone are occasionally modified, resulting in several biological effects, including differential regulation of transcription. Core promoters that encompass the transcription start site have well-conserved DNA motifs, including the initiator (Inr), TATA box, and DPE, which are collectively called the core promoter elements (CPEs). In this study, we systematically studied the associations between the CPEs and histone modifications by integrating the Drosophila Core Promoter Database and time-series ChIP-seq data for histone modifications (H3K4me3, H3K27ac, and H3K27me3) during development in Drosophila melanogaster via the modENCODE project. We classified 96 core promoters into four groups based on the presence or absence of the TATA box or DPE, calculated the histone modification ratio at the core promoter region, and transcribed region for each core promoter. We found that the histone modifications in TATA-less groups were static during development and that the core promoters could be clearly divided into three types: i) core promoters with continuous active marks (H3K4me3 and H3K27ac), ii) core promoters with a continuous inactive mark (H3K27me3) and occasional active marks, and iii) core promoters with occasional histone modifications. Linear regression analysis and non-linear regression by random forest showed that the TATA-containing groups included core promoters without histone modifications, for which the measured RNA expression values were not predictable accurately from the histone modification status. DPE-containing groups had a higher relative frequency of H3K27me3 in both the core promoter region and transcribed region. In summary, our analysis showed that there was a systematic link between the existence of the CPEs and the dynamics, frequency and influence on transcriptional activity of histone modifications.

Project description:Recent studies have highlighted the biological significance of RNA N6-methyladenosine (m6A) modification in tumorigenicity and progression. However, it remains unclear whether m6A modifications also have potential roles in immune regulation and tumor microenvironment (TME) formation. Methods: In this study, we curated 23 m6A regulators and performed consensus molecular subtyping with NMF algorithm to determine m6A modification patterns and the m6A-related gene signature in colon cancer (CC). The ssGSEA and CIBERSORT algorithms were employed to quantify the relative infiltration levels of various immune cell subsets. An PCA algorithm based m6Sig scoring scheme was used to evaluate the m6A modification patterns of individual tumors with an immune response. Results: Three distinct m6A modification patterns were identified among 1307 CC samples, which were also associated with different clinical outcomes and biological pathways. The TME characterization revealed that the identified m6A patterns were highly consistent with three known immune profiles: immune-inflamed, immune-excluded, and immune-desert, respectively. Based on the m6Sig score, which was extracted from the m6A-related signature genes, CC patients can be divided into high and low score subgroups. Patients with lower m6Sig score was characterized by prolonged survival time and enhanced immune infiltration. Further analysis indicated that lower m6Sig score also correlated with greater tumor mutation loads, PD-L1 expression, and higher mutation rates in SMGs (e.g., PIK3CA and SMAD4). In addition, patients with lower m6Sig scores showed a better immune responses and durable clinical benefits in three independent immunotherapy cohorts. Conclusions: This study highlights that m6A modification is significantly associated with TME diversity and complexity. Quantitatively evaluating the m6A modification patterns of individual tumors will strengthen our understanding of TME characteristics and promote more effective immunotherapy strategies.

Dataset Information

Classification of Colon Cancer Patients Based on the Methylation Patterns of Promoters.

Publications

Classification of Colon Cancer Patients Based on the Methylation Patterns of Promoters.

Similar Datasets

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