Impact of mutations in DNA methylation modification genes on genome-wide methylation landscapes and downstream gene activations in pan-cancer

Abstract Background In cancer, mutations of DNA methylation modification genes have crucial roles for epigenetic modifications genome-wide, which lead to the activation or suppression of important genes including tumor suppressor genes. Mutations on the epigenetic modifiers could affect the enzyme a...

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Main Authors: Chai-Jin Lee, Hongryul Ahn, Dabin Jeong, Minwoo Pak, Ji Hwan Moon, Sun Kim
Format: Article
Language:English
Published: BMC 2020-02-01
Series:BMC Medical Genomics
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12920-020-0659-4
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spelling doaj-1e3eac32bf0d4f1ca139f360f91a562b2021-04-02T08:49:53ZengBMCBMC Medical Genomics1755-87942020-02-0113S311410.1186/s12920-020-0659-4Impact of mutations in DNA methylation modification genes on genome-wide methylation landscapes and downstream gene activations in pan-cancerChai-Jin Lee0Hongryul Ahn1Dabin Jeong2Minwoo Pak3Ji Hwan Moon4Sun Kim5Interdisciplinary Program in Bioinformatics, Seoul National UniversityDepartment of Computer Science and Engineering, Seoul National UniversityInterdisciplinary Program in Bioinformatics, Seoul National UniversityDepartment of Computer Science and Engineering, Seoul National UniversityInterdisciplinary Program in Bioinformatics, Seoul National UniversityInterdisciplinary Program in Bioinformatics, Seoul National UniversityAbstract Background In cancer, mutations of DNA methylation modification genes have crucial roles for epigenetic modifications genome-wide, which lead to the activation or suppression of important genes including tumor suppressor genes. Mutations on the epigenetic modifiers could affect the enzyme activity, which would result in the difference in genome-wide methylation profiles and, activation of downstream genes. Therefore, we investigated the effect of mutations on DNA methylation modification genes such as DNMT1, DNMT3A, MBD1, MBD4, TET1, TET2 and TET3 through a pan-cancer analysis. Methods First, we investigated the effect of mutations in DNA methylation modification genes on genome-wide methylation profiles. We collected 3,644 samples that have both of mRNA and methylation data from 12 major cancer types in The Cancer Genome Atlas (TCGA). The samples were divided into two groups according to the mutational signature. Differentially methylated regions (DMR) that overlapped with the promoter region were selected using minfi and differentially expressed genes (DEG) were identified using EBSeq. By integrating the DMR and DEG results, we constructed a comprehensive DNA methylome profiles on a pan-cancer scale. Second, we investigated the effect of DNA methylations in the promoter regions on downstream genes by comparing the two groups of samples in 11 cancer types. To investigate the effects of promoter methylation on downstream gene activations, we performed clustering analysis of DEGs. Among the DEGs, we selected highly correlated gene set that had differentially methylated promoter regions using graph based sub-network clustering methods. Results We chose an up-regulated DEGs cluster where had hypomethylated promoter in acute myeloid leukemia (LAML) and another down-regulated DEGs cluster where had hypermethylated promoter in colon adenocarcinoma (COAD). To rule out effects of gene regulation by transcription factor (TF), if differentially expressed TFs bound to the promoter of DEGs, that DEGs did not included to the gene set that effected by DNA methylation modifiers. Consequently, we identified 54 hypomethylated promoter DMR up-regulated DEGs in LAML and 45 hypermethylated promoter DMR down-regulated DEGs in COAD. Conclusions Our study on DNA methylation modification genes in mutated vs. non-mutated groups could provide useful insight into the epigenetic regulation of DEGs in cancer.http://link.springer.com/article/10.1186/s12920-020-0659-4DNA methylation modifierSub-network clusteringDMR-DEG integrationPan-cancer analysisGenome-wide landscape
collection DOAJ
language English
format Article
sources DOAJ
author Chai-Jin Lee
Hongryul Ahn
Dabin Jeong
Minwoo Pak
Ji Hwan Moon
Sun Kim
spellingShingle Chai-Jin Lee
Hongryul Ahn
Dabin Jeong
Minwoo Pak
Ji Hwan Moon
Sun Kim
Impact of mutations in DNA methylation modification genes on genome-wide methylation landscapes and downstream gene activations in pan-cancer
BMC Medical Genomics
DNA methylation modifier
Sub-network clustering
DMR-DEG integration
Pan-cancer analysis
Genome-wide landscape
author_facet Chai-Jin Lee
Hongryul Ahn
Dabin Jeong
Minwoo Pak
Ji Hwan Moon
Sun Kim
author_sort Chai-Jin Lee
title Impact of mutations in DNA methylation modification genes on genome-wide methylation landscapes and downstream gene activations in pan-cancer
title_short Impact of mutations in DNA methylation modification genes on genome-wide methylation landscapes and downstream gene activations in pan-cancer
title_full Impact of mutations in DNA methylation modification genes on genome-wide methylation landscapes and downstream gene activations in pan-cancer
title_fullStr Impact of mutations in DNA methylation modification genes on genome-wide methylation landscapes and downstream gene activations in pan-cancer
title_full_unstemmed Impact of mutations in DNA methylation modification genes on genome-wide methylation landscapes and downstream gene activations in pan-cancer
title_sort impact of mutations in dna methylation modification genes on genome-wide methylation landscapes and downstream gene activations in pan-cancer
publisher BMC
series BMC Medical Genomics
issn 1755-8794
publishDate 2020-02-01
description Abstract Background In cancer, mutations of DNA methylation modification genes have crucial roles for epigenetic modifications genome-wide, which lead to the activation or suppression of important genes including tumor suppressor genes. Mutations on the epigenetic modifiers could affect the enzyme activity, which would result in the difference in genome-wide methylation profiles and, activation of downstream genes. Therefore, we investigated the effect of mutations on DNA methylation modification genes such as DNMT1, DNMT3A, MBD1, MBD4, TET1, TET2 and TET3 through a pan-cancer analysis. Methods First, we investigated the effect of mutations in DNA methylation modification genes on genome-wide methylation profiles. We collected 3,644 samples that have both of mRNA and methylation data from 12 major cancer types in The Cancer Genome Atlas (TCGA). The samples were divided into two groups according to the mutational signature. Differentially methylated regions (DMR) that overlapped with the promoter region were selected using minfi and differentially expressed genes (DEG) were identified using EBSeq. By integrating the DMR and DEG results, we constructed a comprehensive DNA methylome profiles on a pan-cancer scale. Second, we investigated the effect of DNA methylations in the promoter regions on downstream genes by comparing the two groups of samples in 11 cancer types. To investigate the effects of promoter methylation on downstream gene activations, we performed clustering analysis of DEGs. Among the DEGs, we selected highly correlated gene set that had differentially methylated promoter regions using graph based sub-network clustering methods. Results We chose an up-regulated DEGs cluster where had hypomethylated promoter in acute myeloid leukemia (LAML) and another down-regulated DEGs cluster where had hypermethylated promoter in colon adenocarcinoma (COAD). To rule out effects of gene regulation by transcription factor (TF), if differentially expressed TFs bound to the promoter of DEGs, that DEGs did not included to the gene set that effected by DNA methylation modifiers. Consequently, we identified 54 hypomethylated promoter DMR up-regulated DEGs in LAML and 45 hypermethylated promoter DMR down-regulated DEGs in COAD. Conclusions Our study on DNA methylation modification genes in mutated vs. non-mutated groups could provide useful insight into the epigenetic regulation of DEGs in cancer.
topic DNA methylation modifier
Sub-network clustering
DMR-DEG integration
Pan-cancer analysis
Genome-wide landscape
url http://link.springer.com/article/10.1186/s12920-020-0659-4
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