Evidence map›Paper›PMID 30365097›Full record

ArticleInternational journal of molecular medicine2019

Downregulation of miR-145-5p in cancer cells and their derived exosomes may contribute to the development of ovarian cancer by targeting CT.

Wenzhao Hang, Yiwen Feng, Zhenyu Sang, Ye Yang, Yaping Zhu, Qian Huang, Xiaowei Xi

Open access · hybridAbstract read
In one paragraph

Article in International journal of molecular medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 17% 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

36 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

  1. Pooled it
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  8. Effects of the MCF-7 Exhausted Medium on hADSC Behaviour.International journal of molecular sciences · 2024
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  14. Plasma miR-151-3p as a Candidate Diagnostic Biomarker for Head and Neck Cancer: A Cross-sectional Study within the INHANCE Consortium.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2022
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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 2 institutions in 1 country.

Wenzhao HangDepartment of Obstetrics and Gynecology, Shanghai General Hospital of Nanjing Medical University, Shanghai 200080, P.R. China.
Yiwen FengDepartment of Obstetrics and Gynecology, Shanghai General Hospital of Nanjing Medical University, Shanghai 200080, P.R. China.
Zhenyu SangDepartment of Obstetrics and Gynecology, Shanghai General Hospital of Nanjing Medical University, Shanghai 200080, P.R. China.
Ye YangDepartment of Obstetrics and Gynecology, Shanghai General Hospital of Nanjing Medical University, Shanghai 200080, P.R. China.
Yaping ZhuDepartment of Obstetrics and Gynecology, Shanghai General Hospital of Nanjing Medical University, Shanghai 200080, P.R. China.
Qian HuangDepartment of Oncology, Shanghai General Hospital of Nanjing Medical University, Shanghai 200080, P.R. China.
Xiaowei XiDepartment of Obstetrics and Gynecology, Shanghai General Hospital of Nanjing Medical University, Shanghai 200080, P.R. China.
Nanjing Medical University · CNShanghai First People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study aimed to identify shared microRNAs (miRNAs) in ovarian cancer (OC) cells and their exosomes using microarray data (accession number GSE103708) available from the Gene Expression Omnibus database, including exosomal samples from 13 OC cell lines and 3 normal ovarian surface epithelial cell lines, and their original cell samples. Differentially expressed miRNAs (DE‑miRNAs) were identified using the Linear Models for Microarray data method, and mRNA targets of DE‑miRNAs were predicted using the miRWalk2 database. The potential functions of target genes were analyzed using Database for Annotation, Visualization and Integrated Discovery and intersected with known OC‑associated pathways downloaded from the Comparative Toxicogenomics Database. The associations between crucial miRNAs and target genes, and their clinical associations, were validated using data from The Cancer Genome Atlas. As a result, 16 upregulated and 6 downregulated DE‑miRNAs were shared in OC cell lines and their exosomes compared with normal controls. The target genes of 11 common DE‑miRNAs were predicted. Among these DE‑miRNAs, a low expression of homo sapiens (hsa)‑miR‑145‑5p was significantly correlated with a poor prognosis and higher stages. Although 91 target genes were predicted for hsa‑miR‑145‑5p, only 4 genes [connective tissue growth factor (CTGF), myotubularin‑related protein 14, protein phosphatase 3 catalytic subunit alpha and suppressor of cytokine signaling 7] were suggested as risk factors for prognosis. The subsequent Pearson's correlation analysis validated a significant negative correlation between hsa‑miR‑145‑5p and CTGF (r=‑0.1126, P=0.02188). According to the results of the functional analysis, CTGF is involved in the Hippo signaling pathway (hsa04390). In conclusion, decreased expression of hsa‑miR‑145 in OC and OC‑derived exosomes may be a crucial biomarker for the diagnosis and treatment of OC.

Indexed as

Gene Expression Regulation, NeoplasticCarcinogenesisCell Line, TumorConnective Tissue Growth FactorDown-RegulationExosomesFemaleGene Expression ProfilingGene Regulatory NetworksHumansKaplan-Meier EstimateMicroRNAsMiddle AgedOvarian NeoplasmsPrognosisCCN2 protein, humanConnective Tissue Growth FactorMicroRNAsMIRN145 microRNA, human

Identifiers

PMID30365097
PMCPMC6257844
OpenAlexW2898267366

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.