Evidence map›Paper›PMID 28827728›Full record

SynthesisScientific reports2017

Reference miRNAs for colorectal cancer: analysis and verification of current data.

E Danese, A M Minicozzi, M Benati, E Paviati, G Lima-Oliveira, M Gusella, F Pasini, G L Salvagno, M Montagnana, G Lippi

Abstract readSystematic Review
In one paragraph

Synthesis in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
–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

34 citing papers in PubMed.

  1. Trial
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  13. Reference Genes for qPCR-Based miRNA Expression Profiling in 14 Human Tissues.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2022
    Review
  14. Review
  15. Article
  16. Molecular therapy. Nucleic acids · 2021
    Article
  17. Article
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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

10 authors.

E DaneseClinical Biochemistry section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy. elisa.danese@univr.it.ORCID 0000-0002-2454-0410
A M MinicozziColorectal & Peritoneal Oncology Centre, The Christie NHS Foundation Trust, Manchester, Manchester, M20 4BX, United Kingdom.
M BenatiClinical Biochemistry section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
E PaviatiClinical Biochemistry section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
G Lima-OliveiraClinical Biochemistry section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
M GusellaLaboratory of Pharmacology and Molecular Biology, Oncology Department, Rovigo General Hospital, 45027, Trecenta, Italy.
F PasiniDepartment of Medical Oncology, Rovigo Hospital, 45100, Rovigo, Italy.
G L SalvagnoClinical Biochemistry section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.ORCID 0000-0003-0487-9051
M MontagnanaClinical Biochemistry section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
G LippiClinical Biochemistry section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.ORCID 0000-0001-9523-9054

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) hold great promise in cancer research. The use of appropriate reference miRNAs for normalization of qPCR data is crucial for accurate expression analysis. We present here analysis and verification of current data, proposing a workflow strategy for identification of reference miRNAs in colorectal cancer (CRC). We performed a systematic review of studies aimed to identify stable reference miRNAs in CRC through high-throughput screening. Among the candidate miRNAs selected from the literature we excluded those predicted to target oncogenes or tumor suppressor gene. We then assessed the expression levels of the remaining candidates in exosomes, plasma and tissue samples from CRC patients and healthy controls. The expression stability was evaluated by box-plot, ∆Cq analysis, NormFinder and BestKeeper statistical algorithms. The effects of normalisers on the relative quantification of the oncogenic miR-1290 was also assessed. Our results consistently showed that different combinations of miR-520d, miR-1228 and miR-345 provided the most stably expressed reference miRNAs in the three biological matrices. We identified suitable reference miRNAs for future miRNA expression studies in exosomes plasma and tissues CRC samples. We also provided a novel conceptual framework that overcome the need of performing ex novo identification of suitable reference genes in single experimental systems.

Indexed as

Reference StandardsColorectal NeoplasmsGene Expression ProfilingHumansMicroRNAsReal-Time Polymerase Chain ReactionMicroRNAs

Identifiers

PMID28827728
PMCPMC5567181

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.