Evidence map›Paper›PMID 27259231›Full record

SynthesisOncotarget2016

Diagnostic value of microRNAs in asbestos exposure and malignant mesothelioma: systematic review and qualitative meta-analysis.

Luigina Micolucci, Most Mauluda Akhtar, Fabiola Olivieri, Maria Rita Rippo, Antonio Domenico Procopio

Open access · diamondAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
9.5field-weighted citation impact, top 2% 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

42 citing papers in PubMed, 80 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. Article
  9. Review
  10. miRNAs in Cancer (Review of Literature).International journal of molecular sciences · 2022
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Research progress in lncRNA and its action as ceRNA in ovarian function as well as the relevant diseases.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2021
    Article
  16. Article
  17. Article
  18. Review
  19. Review
  20. Article
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

5 authors at 2 institutions in 1 country.

Luigina MicolucciComputational Pathology Unit, Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy.
Most Mauluda AkhtarComputational Pathology Unit, Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy.
Fabiola OlivieriLaboratory of Experimental Pathology, Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy.
Maria Rita RippoLaboratory of Experimental Pathology, Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy.
Antonio Domenico ProcopioLaboratory of Experimental Pathology, Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy.
Marche Polytechnic University · ITInnova (Italy) · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAsbestos is a harmful and exceptionally persistent natural material. Malignant mesothelioma (MM), an asbestos-related disease, is an insidious, lethal cancer that is poorly responsive to current treatments. Minimally invasive, specific, and sensitive biomarkers providing early and effective diagnosis in high-risk patients are urgently needed. MicroRNAs (miRNAs, miRs) are endogenous, non-coding, small RNAs with established diagnostic value in cancer and pollution exposure. A systematic review and a qualitative meta-analysis were conducted to identify high-confidence miRNAs that can serve as biomarkers of asbestos exposure and MM.

methodsThe major biomedical databases were systematically searched for miRNA expression signatures related to asbestos exposure and MM. The qualitative meta-analysis applied a novel vote-counting method that takes into account multiple parameters. The most significant miRNAs thus identified were then subjected to functional and bioinformatic analysis to assess their biomarker potential.

resultsA pool of deregulated circulating and tissue miRNAs with biomarker potential for MM was identified and designated as "mesomiRs" (MM-associated miRNAs). Comparison of data from asbestos-exposed and MM subjects found that the most promising candidates for a multimarker signature were circulating miR-126-3p, miR-103a-3p, and miR-625-3p in combination with mesothelin. The most consistently described tissue miRNAs, miR-16-5p, miR-126-3p, miR-143-3p, miR-145-5p, miR-192-5p, miR-193a-3p, miR-200b-3p, miR-203a-3p, and miR-652-3p, were also found to provide a diagnostic signature and should be further investigated as possible therapeutic targets.

conclusionThe qualitative meta-analysis and functional investigation confirmed the early diagnostic value of two miRNA signatures for MM. Large-scale, standardized validation studies are needed to assess their clinical relevance, so as to move from the workbench to the clinic.

Indexed as

AsbestosBiomarkers, TumorComputational BiologyEpigenesis, GeneticGene Expression ProfilingGene Expression Regulation, NeoplasticGPI-Linked ProteinsHumansLung NeoplasmsMesothelinMesotheliomaMesothelioma, MalignantMicroRNAsOligonucleotide Array Sequence AnalysisPhenotypeTissue Array AnalysisAsbestosBiomarkers, TumorGPI-Linked ProteinsMesothelinMicroRNAsMIRN103 microRNA, humanMIRN1266 microRNA, humanMIRN625 microRNA, humanasbestosbiomarkermesotheliomamicroRNAsystematic review

Identifiers

PMID27259231
PMCPMC5295457
OpenAlexW2413328166

What Socratic 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 Socratic graph.