Evidence map›Paper›PMID 29095529›Full record

SynthesisJournal of cellular biochemistry2018

The potential of microRNAs as human prostate cancer biomarkers: A meta-analysis of related studies.

Chun-Jiao Song, Huan Chen, Li-Zhong Chen, Guo-Mei Ru, Jian-Jun Guo, Qian-Nan Ding

Abstract readMeta-AnalysisReview
In one paragraph

Synthesis in Journal of cellular biochemistry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing papers in PubMed, 7 pooled it
–field-weighted citation impact
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

63 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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3 more citing papers are in PubMed but not listed here.

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.

Chun-Jiao SongMedical Research Center, Shaoxing people's Hospital, Shaoxing Hospital of Zhejiang University, Shaoxing, China.ORCID 0000-0001-7428-5262
Huan ChenZhejiang Institute of Microbiology, Key Laboratory of Microorganism Technology and Bioinformatics Research of Zhejiang Province, Hangzhou, China.
Li-Zhong ChenMedical Research Center, Shaoxing people's Hospital, Shaoxing Hospital of Zhejiang University, Shaoxing, China.
Guo-Mei RuMedical Research Center, Shaoxing people's Hospital, Shaoxing Hospital of Zhejiang University, Shaoxing, China.
Jian-Jun GuoMedical Research Center, Shaoxing people's Hospital, Shaoxing Hospital of Zhejiang University, Shaoxing, China.
Qian-Nan DingMedical Research Center, Shaoxing people's Hospital, Shaoxing Hospital of Zhejiang University, Shaoxing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer (PC) is a very important kind of male malignancies. When PC evolves into a stage of hormone resistance or metastasis, the fatality rate is very high. Currently, discoveries and advances in miRNAs as biomarkers have opened the potential for the diagnosis of PC, especially early diagnosis. miRNAs not only can noninvasively or minimally invasively identify PC, but also can provide the data for optimization and personalization of therapy. Moreover, miRNAs have been shown to play an important role to predict prognosis of PC. The purpose of this meta-analysis is to integrate the currently published expression profile data of miRNAs in PC, and evaluate the value of miRNAs as biomarkers for PC. All of relevant records were selected via electronic databases: Pubmed, Embase, Cochrane, and CNKI based on the assessment of title, abstract, and full text. we extracted mean ± SD or fold change of miRNAs expression levels in PC versus BPH or normal controls. Pooled hazard ratios (HRs) with 95% confidence intervals (CI) for overall survival (OS) and recurrence-free survival (RFS), were also calculated to detect the relationship between high miRNAs expression and PC prognosis. Selected 104 articles were published in 2007-2017. According to the inclusion criteria, 104 records were included for this meta-analysis. The pooled or stratified analyze showed 10 up-regulated miRNAs (miR-18a, miR-34a, miR-106b, miR-141, miR-182, miR-183, miR-200a/b, miR-301a, and miR-375) and 14 down-regulated miRNAs (miR-1, miR-23b/27b, miR-30c, miR-99b, miR-139-5p, miR-152, miR-187, miR-204, miR-205, miR-224, miR-452, miR-505, and let-7c) had relatively good diagnostic and predictive potential to discriminate PC from BPH/normal controls. Furthermore, high expression of miR-32 and low expression of let-7c could be used to differentiate metastatic PC from local/primary PC. Additional interesting findings were that the expression profiles of five miRNAs (miR-21, miR-30c, miR-129, miR-145, and let-7c) could predict poor RFS of PC, while the evaluation of miR-375 was associated with worse OS. miRNAs are important regulators in PC progression. Our results indicate that miRNAs are suitable for predicting the different stages of PC. The detection of miRNAs is an effective way to control patient's prognosis and evaluate therapeutic efficacy. However, large-scale detections based on common clinical guidelines are still necessary to further validate our conclusions, due to the bias induced by molecular heterogeneity and differences in study design and detection methods.

Indexed as

Gene Expression Regulation, NeoplasticBiomarkers, TumorHumansMaleMicroRNAsNeoplasm MetastasisProstatic NeoplasmsRNA, NeoplasmBiomarkers, TumorMicroRNAsRNA, Neoplasmbiomarkermeta-analysismicroRNAprostate cancer

Identifiers

PMID29095529
PMCPMC5814937

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.