Evidence map›Paper›PMID 23984644›Full record

ArticleGenetic testing and molecular biomarkers2013

Screening biomarkers of prostate cancer by integrating microRNA and mRNA microarrays.

Jiayu Feng, Chibing Huang, Xinwei Diao, Minqi Fan, Pingxian Wang, Ya Xiao, Xiao Zhong, Ronghua Wu

Open access · greenAbstract read
In one paragraph

Article in Genetic testing and molecular biomarkers, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

14 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. MicroRNA-31 Regulates Expression ofInternational journal of molecular sciences · 2020
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Identifying relevant group of miRNAs in cancer using fuzzy mutual information.Medical & biological engineering & computing · 2016
    Article
  9. Article
  10. Identification and Functional Validation of Reciprocal microRNA-mRNA Pairings in African American Prostate Cancer Disparities.Clinical cancer research : an official journal of the American Association for Cancer Research · 2015
    Article
  11. Review
  12. Article
  13. Article
  14. Review
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

8 authors at 2 institutions in 1 country.

Jiayu Feng1 Department of Urology, Second Affiliated Hospital, Third Military Medical University , Chongqing, China .
Chibing Huang
Xinwei Diao
Minqi Fan
Pingxian Wang
Ya Xiao
Xiao Zhong
Ronghua Wu
Xinqiao Hospital · CNArmy Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveIn this study, we screened microRNA (miRNA) target genes of prostate cancer by integrating miRNA and mRNA expression profiles after target prediction and performed function enrichment analysis for selected candidate genes.

methodsThe miRNA expression profile (GSE36802) and mRNA expression profile (GSE36801) were downloaded from the Gene Expression Omnibus database. We processed data and identified the differentially expressed miRNAs and mRNAs with R packages. Verified targets of miRNAs were identified through miRecods and miRTarBase. Then, software of Search Tool for the Retrieval of Interacting Genes was used to construct the interaction network of target genes. Finally, we performed function enrichment analysis for genes in the interaction network with the Functional Classification Tool.

resultsA total of 22 upregulated and 8 downregulated miRNAs were detected in this study, of which, hsa-mir-31 was the most overexpressed miRNA in prostate cancer. Both ITGA5 and RDX, two target genes of hsa-mir-31, were found to be differentially expressed from mRNA profiles by overexpressing hsa-mir-31. The cell adhesion molecule was found to be the most significant pathway enriched by ITGA5 and RDX.

conclusionOverexpression of hsa-mir-31 can be a significant marker to distinguish cancer tissues from benign tissues. The targets such as ITGA5 and RDX regulated by hsa-mir-31 are candidate genes of prostate cancer, which provide new treatment strategies for its gene therapy.

Indexed as

Biomarkers, TumorGene Expression ProfilingGene Regulatory NetworksHumansMaleMass ScreeningMicroarray AnalysisMicroRNAsProstatic NeoplasmsRNA, MessengerSystems IntegrationBiomarkers, TumorMicroRNAsMIRN31 microRNA, humanRNA, Messenger

Identifiers

PMID23984644
PMCPMC3816787
OpenAlexW1981988131

What OpenQuestion holds

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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.