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Cited by 48Epigenetics and DNA MethylationCancer Genomics and DiagnosticsGene expression and cancer classification

Integrative analysis with expanded DNA methylation data reveals common key regulators and pathways in cancers

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Fan, Shicai, Tang, Jianxiong, Li, Nan, Zhao, Ying, Ai, Rizi, Zhang, Kai, Wang, Mengchi, Du, Wei +1 more·2019·npj Genomic Medicine
DOI 10.1038/s41525-019-0077-8PMC PMC6358616

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Abstract

The integration of genomic and DNA methylation data has been demonstrated as a powerful strategy in understanding cancer mechanisms and identifying therapeutic targets. The TCGA consortium has mapped DNA methylation in thousands of cancer samples using Illumina Infinium Human Methylation 450 K BeadChip (Illumina 450 K array) that only covers about 1.5% of CpGs in the human genome. Therefore, increasing the coverage of the DNA methylome would significantly leverage the usage of the TCGA data. Here, we present a new model called EAGLING that can expand the Illumina 450 K array data 18 times to cover about 30% of the CpGs in the human genome. We applied it to analyze 13 cancers in TCGA. By integrating the expanded methylation, gene expression, and somatic mutation data, we identified the genes showing differential patterns in each of the 13 cancers. Many of the triple-evidenced genes identified in majority of the cancers are biomarkers or potential biomarkers. Pan-cancer analysis also revealed the pathways in which the triple-evidenced genes are enriched, which include well known ones as well as new ones, such as axonal guidance signaling pathway and pathways related to inflammatory processing or inflammation response. Triple-evidenced genes, particularly TNXB, RRM2, CELSR3, SLC16A3, FANCI, MMP9, MMP11, SIK1, and TRIM59 showed superior predictive power in both tumor diagnosis and prognosis. These results have demonstrated that the integrative analysis using the expanded methylation data is powerful in identifying critical genes/pathways that may serve as new therapeutic targets.

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  • Hypermethylation across multiple tumor types occurs predominantly in genes that are specifically repressed in the tissue of origin.

    “our results support that hypermethylation across multiple tumor types occurs predominantly in genes that are specifically repressed in the tissue of origin”

    From Comprehensive in silico CpG methylation analysis in hepatocellular carcinoma identifies tissue- and tumor-type specific marks disconnected from gene expression (2024) · cites this paper as [14]

    The Results section ('Identification of triple-evidenced genes'; page unavailable) examines methylation and expression across 13 cancers but says methylation shows no clear trend for the five genes discussed. The Methods compare tumors with corresponding normal samples. Neither passage addresses whether hypermethylation occurs predominantly in genes specifically repressed in the tissue of origin; searches for that relationship found no supporting passage. (LLM, conf=0.74)

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Authors
Fan, S., Tang, J., Li, N., Zhao, Y., Ai, R., Zhang, K., Wang, M., Du, W., & Wang, W.
Affiliations
  • University of Electronic Science and Technology of China (CN)
  • University of California San Diego (US)
  • Jilin University (CN)
Corresponding author
  • Fan, Shicai
  • Wang, Wei
ORCID
Venue
npj Genomic Medicine
Publisher
Springer Science and Business Media LLC
Published
2019-02-01
Volume
4
Issue
1
Pages
2-2
ISSN
2056-7944 (ISSN-L)
DOI
10.1038/s41525-019-0077-8
PMC
PMC6358616
OpenAlex
W2905459733
Cited by
48
References
64
Citations by year
2026: 2 · 2025: 6 · 2024: 6 · 2023: 6 · 2022: 8 · 2021: 12 · 2020: 4 · 2019: 4
FWCI
2.32
Type
journal article
Language
en
Open access
Licence
Locations
  • npj Genomic Medicine (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • National Natural Science Foundation of China (61503061)
  • Foundation for the National Institutes of Health (HG009626)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Keywords
DNA methylation, pan-cancer analysis, gene expression, somatic mutations, biomarkers, tumor diagnosis, prognosis, inflammation, therapeutic target, TCGA

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