Evidence map›Paper›PMID 30987065›Full record

ReviewGenes2019

Host⁻MicroRNA⁻Microbiota Interactions in Colorectal Cancer.

Ce Yuan, Clifford J Steer, Subbaya Subramanian

Open access · goldAbstract readReview
In one paragraph

Review in Genes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

23 citing papers in PubMed, 35 citations in OpenAlex.

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  10. Interactions between the tumor microbiota and breast cancer.Frontiers in cellular and infection microbiology · 2024
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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

3 authors at 2 institutions in 1 country.

Ce YuanBioinformatics and Computational Biology Program, University of Minnesota, Minneapolis, MN 55455, USA. yuanx236@umn.edu.
Clifford J SteerDepartment of Medicine, University of Minnesota Medical School, Minneapolis, MN 55455, USA. steer001@umn.edu.
Subbaya SubramanianBioinformatics and Computational Biology Program, University of Minnesota, Minneapolis, MN 55455, USA. subree@umn.edu.
University of Minnesota · USUniversity of Minnesota Medical Center · US

Funding

Atypical Chemokine Receptor 4 (ACKR4) in Anti-tumor Immunity in colorectal cancerR03CA219129 · NCI · UNIVERSITY OF MINNESOTA · PI SUBRAMANIAN, SUBBAYA · 2017 to 2018
$147k
NCI NIH HHS R03 CA219129
6 · The paper itself

Abstract

Changes in gut microbiota composition have consistently been observed in patients with colorectal cancer (CRC). Yet, it is not entirely clear how the gut microbiota interacts with tumor cells. We know that tumor cells undergo a drastic change in energy metabolism, mediated by microRNAs (miRNAs), and that tumor-derived miRNAs affect the stromal and immune cell fractions of the tumor microenvironment. Recent studies suggest that host intestinal miRNAs can also affect the growth and composition of the gut microbiota. Our previous CRC studies showed a high-level of interconnectedness between host miRNAs and their microbiota. Considering all the evidence to date, we postulate that the altered nutrient composition and miRNA expression in the CRC microenvironment selectively exerts pressure on the surrounding microbiota, leading to alterations in its composition. In this review article, we present our current understanding of the role of miRNAs in mediating host-microbiota interactions in CRC.

Indexed as

Colorectal NeoplasmsGastrointestinal MicrobiomeHost Microbial InteractionsHumansIntestinesMicroRNAsTumor MicroenvironmentMicroRNAscolorectal cancergut microbiotametabolic interactionsmicroRNAs

Identifiers

PMID30987065
PMCPMC6523287
OpenAlexW2925364233

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.