Evidence map›Paper›PMID 32436932›Full record

ArticleBriefings in bioinformatics2021

miRactDB characterizes miRNA-gene relation switch between normal and cancer tissues across pan-cancer.

Hua Tan, Pora Kim, Peiqing Sun, Xiaobo Zhou

Open access · greenAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 32% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. ESOMIR: a curated database of biomarker genes and miRNAs associated with esophageal cancer.Database : the journal of biological databases and curation · 2023
    Article
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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

4 authors.

Pora Kim
Peiqing Sun
Xiaobo Zhou

Funding

Systems Modeling Guided Bone regenerationU01AR069395 · NIAMS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI YANG, YUNZHI, ZHOU, XIAOBO · 2016 to 2021
$3.4M
Tissue Engineering Approaches for Improved Treatment of Early Stage Osteonecrosis of the HipR01AR072613 · NIAMS · STANFORD UNIVERSITY · PI GOODMAN, STUART B, YANG, YUNZHI · 2018 to 2022
$2.2M
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
Functional annotation of new genes aided by deep learningR35GM138184 · NIGMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI KIM, PORA · 2020 to 2024
$1.7M
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 R01 AR072613NIAMS NIH HHS U01 AR069395NIGMS NIH HHS R01 GM123037NIGMS NIH HHS R35 GM138184
6 · The paper itself

Abstract

It has been increasingly accepted that microRNA (miRNA) can both activate and suppress gene expression, directly or indirectly, under particular circumstances. Yet, a systematic study on the switch in their interaction pattern between activation and suppression and between normal and cancer conditions based on multi-omics evidences is not available. We built miRactDB, a database for miRNA-gene interaction, at https://ccsm.uth.edu/miRactDB, to provide a versatile resource and platform for annotation and interpretation of miRNA-gene relations. We conducted a comprehensive investigation on miRNA-gene interactions and their biological implications across tissue types in both tumour and normal conditions, based on TCGA, CCLE and GTEx databases. We particularly explored the genetic and epigenetic mechanisms potentially contributing to the positive correlation, including identification of miRNA binding sites in the gene coding sequence (CDS) and promoter regions of partner genes. Integrative analysis based on this resource revealed that top-ranked genes derived from TCGA tumour and adjacent normal samples share an overwhelming part of biological processes, which are quite different than those from CCLE and GTEx. The most active miRNAs predicted to target CDS and promoter regions are largely overlapped. These findings corroborate that adjacent normal tissues might have undergone significant molecular transformations towards oncogenesis before phenotypic and histological change; and there probably exists a small yet critical set of miRNAs that profoundly influence various cancer hallmark processes. miRactDB provides a unique resource for the cancer and genomics communities to screen, prioritize and rationalize their candidates of miRNA-gene interactions, in both normal and cancer scenarios.

Indexed as

Gene Expression Regulation, NeoplasticBinding SitesCarcinogenesisEpigenesis, GeneticHumansMicroRNAsNeoplasmsPromoter Regions, GeneticMicroRNAscorrelationepigenetic regulationgenetic mechanismmicroRNA activationpan-cancer

Identifiers

PMID32436932
PMCPMC8138827
OpenAlexW3028132168

What OpenQuestion holds

Textmetadata
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.