Evidence map›Paper›PMID 32093698›Full record

ArticleBMC medical genomics2020

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

Chai-Jin Lee, Hongryul Ahn, Dabin Jeong, Minwoo Pak, Ji Hwan Moon, Sun Kim

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.6field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 31 citations in OpenAlex.

  1. Article
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  5. A Pre-Leukemic DNA Methylation Signature in Healthy Individuals at Higher Risk for Developing Myeloid Malignancy.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024
    Article
  6. Article
  7. Article
  8. Review
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  10. Hypermethylation ofFrontiers in immunology · 2023
    Article
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  12. Article
  13. Review
  14. Urinary Markers for Bladder Cancer Diagnosis and Monitoring.Frontiers in cell and developmental biology · 2022
    Review
  15. Article
  16. Article
  17. Analyses of DNA Methylation Profiling in the Diagnosis of Intramedullary Astrocytomas.Journal of neuropathology and experimental neurology · 2021
    Article
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Chai-Jin LeeInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Korea.
Hongryul AhnDepartment of Computer Science and Engineering, Seoul National University, Seoul, 08826, Korea.
Dabin JeongInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Korea.
Minwoo PakDepartment of Computer Science and Engineering, Seoul National University, Seoul, 08826, Korea.
Ji Hwan MoonInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Korea.
Sun KimInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Korea. sunkim.bioinfo@snu.ac.kr.
Seoul National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn 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.

methodsFirst, 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.

resultsWe 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.

conclusionsOur study on DNA methylation modification genes in mutated vs. non-mutated groups could provide useful insight into the epigenetic regulation of DEGs in cancer.

Indexed as

Gene Expression Regulation, NeoplasticDNA MethylationDNA, NeoplasmEpigenesis, GeneticEpigenomeGenome, HumanHumansMutationNeoplasmsPromoter Regions, GeneticDNA, NeoplasmDMR-DEG integrationDNA methylation modifierGenome-wide landscapePan-cancer analysisSub-network clustering

Identifiers

PMID32093698
PMCPMC7038532
OpenAlexW3008227704

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.