Evidence map›Paper›PMID 34044218›Full record

ArticleEBioMedicine2021

Pan-cancer characterization of long non-coding RNA and DNA methylation mediated transcriptional dysregulation.

Zhen Yang, Feng Xu, Haizhou Wang, Andrew E Teschendorff, Feng Xie, Yungang He

Open access · goldAbstract read
In one paragraph

Article in EBioMedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
5.9field-weighted citation impact, top 2% 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

25 citing papers in PubMed, 61 citations in OpenAlex.

  1. International journal of molecular sciences · 2026
    Article
  2. Review
  3. Non-coding RNA-mediated gene regulation in Alzheimer's disease pathogenesis: molecular insights and emerging innovations.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2025
    Review
  4. Review
  5. Article
  6. Article
  7. Emerging Roles of Vitamin BInternational journal of molecular sciences · 2024
    Review
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  20. LncRNA-mediated DNA methylation: an emerging mechanism in cancer and beyond.Journal of experimental & clinical cancer research : CR · 2022
    Review
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 3 institutions in 2 countries.

Zhen YangCenter for Medical Research and Innovation of Pudong Hospital, Fudan University, and the Shanghai Key Laboratory of Medical Epigenetics, the International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China. Electronic address: zhenyang@fudan.edu.cn.
Feng XuShanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.
Haizhou WangShanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.
Andrew E TeschendorffCAS Key Lab of Computational Biology, Shanghai Institute for Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China.
Feng XieSoochow University, 8 Jixue Road, Suzhou 215131, Jiangsu Province, China.
Yungang HeShanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China. Electronic address: heyungang@fudan.edu.cn.
Fudan University · CNShanghai Institute of Nutrition and Health · CNSoochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDisruption of DNA methylation (DNAm) is one of the key signatures of cancer, however, detailed mechanisms that alter the DNA methylome in cancer remain to be elucidated.

methodsHere we present a novel integrative analysis framework, called MeLncTRN (Methylation mediated LncRNA Transcriptional Regulatory Network), that integrates genome-wide transcriptome, DNA methylome and copy number variation profiles, to systematically identify the epigenetically-driven lncRNA-gene regulation circuits across 18 cancer types. FINDING: We show that a significant fraction of the aberrant DNAm and gene expression landscape in cancer is associated with long noncoding RNAs (lncRNAs). We reveal distinct types of regulation between lncRNA modulators and target genes that are operative in either only specific cancers or across cancers. Functional studies identified a common theme of cancer hallmarks that lncRNA modulators may participate in. The coupled lncRNA gene interactions via DNAm also serve as markers for classifications of cancer subtypes with different prognoses.

interpretationOur study reveals a vital layer of DNAm and associated expression regulation for many cancer-related genes and we also provide a valuable database resource for interrogating epigenetically mediated lncRNA-gene interactions in cancer.

fundingNational Natural Science Foundation of China [91959106, 31871255].

Indexed as

DNA MethylationComputational BiologyDatabases, GeneticDNA Copy Number VariationsEpigenesis, GeneticGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansNeoplasmsPrognosisRNA, Long NoncodingSequence Analysis, RNARNA, Long NoncodingDNA methylationLncRNAOmics-data integrationRegulatory networkTranscriptional regulation

Identifiers

PMID34044218
PMCPMC8245911
OpenAlexW3165548770

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.