Evidence map›Paper›PMID 30956173›Full record

ArticleEBioMedicine2019

Pan-cancer analysis on microRNA-associated gene activation.

Hua Tan, Shan Huang, Zhigang Zhang, Xiaohua Qian, Peiqing Sun, Xiaobo Zhou

Open access · goldAbstract read
In one paragraph

Article in EBioMedicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
3.4field-weighted citation impact, top 6% 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

43 citing papers in PubMed, 77 citations in OpenAlex.

  1. Article
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  7. Evaluating Genetic Regulators of MicroRNAs Using Machine Learning Models.International journal of molecular sciences · 2025
    Article
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  13. Review
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  15. Article
  16. miR-617 interacts with the promoter ofFrontiers in oncology · 2024
    Article
  17. Review
  18. RNA activation in ticks.Scientific reports · 2023
    Article
  19. Article
  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 4 institutions in 2 countries.

Hua TanSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA. Electronic address: Hua.Tan@uth.tmc.edu.
Shan HuangDepartment of Cancer Biology, Wake Forest Comprehensive Cancer Center, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA.
Zhigang ZhangSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Xiaohua QianInstitute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.
Peiqing SunDepartment of Cancer Biology, Wake Forest Comprehensive Cancer Center, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA. Electronic address: psun@wakehealth.edu.
Xiaobo ZhouSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA. Electronic address: Xiaobo.Zhou@uth.tmc.edu.
The University of Texas Health Science Center · USWake Forest University · USShanghai Jiao Tong University · CNThe University of Texas Health Science Center at Houston · US

Funding

Systems Modeling Guided Bone regenerationU01AR069395 · NIAMS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI YANG, YUNZHI, ZHOU, XIAOBO · 2016 to 2021
$3.4M
The role of microRNA in oncogene-induced senescence and cancer developmentR01CA172115 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI SUN, PEIQING · 2014 to 2018
$1.8M
Integrative approach to studying LncRNA functionsR01GM123037 · NIGMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHOU, XIAOBO · 2017 to 2020
$1.5M
NCI NIH HHS R01 CA172115NIAMS NIH HHS U01 AR069395NIGMS NIH HHS R01 GM123037
6 · The paper itself

Abstract

backgroundWhile microRNAs (miRNAs) were widely considered to repress target genes at mRNA and/or protein levels, emerging evidence from in vitro experiments has shown that miRNAs can also activate gene expression in particular contexts. However, this counterintuitive observation has rarely been reported or interpreted in in vivo conditions.

methodsWe systematically explored the positive correlation between miRNA and gene expressions and its potential implications in tumorigenesis, based on 8375 patient samples across 31 major human cancers from The Cancer Genome Atlas (TCGA).

findingsWe found that positive miRNA-gene correlations are surprisingly prevalent and consistent across cancer types, and show distinct patterns than negative correlations. The top-ranked positive correlations are significantly involved in the immune cell differentiation and cell membrane signaling related processes, and display strong power in stratifying patients in terms of survival rate. Although intragenic miRNAs generally tend to co-express with their host genes, a substantial portion of miRNAs shows no obvious correlation with their host gene plausibly due to non-conservation. A miRNA can upregulate a gene by inhibiting its upstream suppressor, or shares transcription factors with that gene, both leading to positive correlation. The miRNA/gene sites associated with the top-ranked positive correlations are more likely to form super-enhancers compared to randomly chosen pairs. Wet-lab experiments revealed that positive correlations partially remain in in vitro condition.

interpretationOur study brings new insights into the critical role of miRNA in gene regulation and the complex mechanisms underlying miRNA functions, and reveals both biological and clinical significance of miRNA-associated gene activation.

Indexed as

Gene Expression ProfilingGene Expression Regulation, NeoplasticRNA InterferenceComputational BiologyEnhancer Elements, GeneticGenes, ReporterHumansMicroRNAsModels, BiologicalNeoplasmsRNA, MessengerTranscriptional ActivationMicroRNAsRNA, MessengerIntragenic miRNAmiRNA activationPan-cancer miRNASuper-enhancer

Identifiers

PMID30956173
PMCPMC6557760
OpenAlexW2951391897

What OpenQuestion holds

Textmetadata
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.