Evidence map›Paper›PMID 31414268›Full record

ArticleInvestigational new drugs2020

Identification of HGF as a novel target of miR-15a/16/195 in gastric cancer.

Dongying Liu, Haiyang Zhang, Shaohua Ge, Dan Lin, Jiayi Han, Guoguang Ying, Yi Ba

Abstract read
PubMed Publisher
In one paragraph

Article in Investigational new drugs, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 36% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Signaling pathways and therapeutic interventions in gastric cancer.Signal transduction and targeted therapy · 2022
    Review
  2. Review
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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

7 authors at 1 institution in 1 country.

Dongying LiuTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University, Tianjin, China.
Haiyang ZhangTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University, Tianjin, China.
Shaohua GeTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University, Tianjin, China.
Dan LinTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University, Tianjin, China.
Jiayi HanTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University, Tianjin, China.
Guoguang YingTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University, Tianjin, China. yingguoguang163@163.com.
Yi BaTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University, Tianjin, China. bayi@tjmuch.com.
Tianjin Medical University Cancer Institute and Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Gastric malignancy is the third most frequently encountered cancer globally and have been documented to confer extremely poor prognosis, given their limited treatment options. The up-regulation of hepatocyte growth factor (HGF) has been found in various tumor tissues, including GC tissue, and has been linked with tumor development. Nevertheless, the pathways leading to HGF upregulation have yet to be fully explored. Methods Immunohistochemistry (IHC) assay was used to detect HGF expression in human gastric tumor tissues, while western blotting allowed quantification of protein levels. Bioinformatics tools were used to predict potential miRNA that may target HGF mRNA. Relative levels of miR-15a/16/195 as well as the target mRNA levels were analyzed with qRT-PCR. Direct targeting between miRNA and mRNA was then validated by luciferase assay. Finally, a mouse xenograft tumor model was selected to demonstrate the in vivo effects of miR-15a/16/195. Results HGF protein expressions were markedly raised, while miR-15a/16/195 levels were dramatically down-regulated in tumor tissues of GC. miR-15a/16/195 were shown to directly bind with the 3'-UTR of HGF mRNA. This study demonstrated that HGF can be repressed by overexpressed miR-15a/16/195, which resulted in the suppression of GC cell proliferation and migration. Furthermore, in the xenograft mouse model, miR-15a/16/195 were also found to have a tumor growth suppression effect. Conclusions miR-15a/16/195 suppresses tumorigenesis by targeting HGF and may have a potential therapeutic application in the clinical treatment of GC.

Indexed as

MicroRNAsAnimalsCell Line, TumorCell MovementCell ProliferationDown-RegulationHepatocyte Growth FactorHumansMaleMice, Inbred BALB CMice, NudeStomach NeoplasmsWound HealingHepatocyte Growth FactorHGF protein, humanMicroRNAsMIRN15 microRNA, humanMIRN16 microRNA, humanMIRN195 microRNA, humanGastric cancerHGFMigrationmiR-15a/16/195Proliferation

Identifiers

PMID31414268
OpenAlexW2968097176

What OpenQuestion holds

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Registered trials

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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.