Evidence map›Paper›PMID 20429937›Full record

ArticleBMC cancer2010

MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer.

Kah Hoong Chang, Pieter Mestdagh, Jo Vandesompele, Michael J Kerin, Nicola Miller

Open access · goldAbstract readValidation Study
In one paragraph

Article in BMC cancer, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
114citing papers in PubMed, 1 pooled it
10.5field-weighted citation impact, top 1% 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

114 citing papers in PubMed, 1 synthesis or guideline pooled it, 223 citations in OpenAlex.

  1. Pooled it
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  11. 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
  12. Article
  13. TERRA Gene Expression in Gastric Cancer: Role of hTERT.Journal of gastrointestinal cancer · 2021
    Review
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  18. Article
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54 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

5 authors at 2 institutions in 2 countries.

Kah Hoong ChangDepartment of Surgery, National University of Ireland, Galway, Republic of Ireland.
Pieter Mestdagh
Jo Vandesompele
Michael J Kerin
Nicola Miller
Ollscoil na Gaillimhe – University of Galway · IEGhent University Hospital · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdvances in high-throughput technologies and bioinformatics have transformed gene expression profiling methodologies. The results of microarray experiments are often validated using reverse transcription quantitative PCR (RT-qPCR), which is the most sensitive and reproducible method to quantify gene expression. Appropriate normalisation of RT-qPCR data using stably expressed reference genes is critical to ensure accurate and reliable results. Mi(cro)RNA expression profiles have been shown to be more accurate in disease classification than mRNA expression profiles. However, few reports detailed a robust identification and validation strategy for suitable reference genes for normalisation in miRNA RT-qPCR studies.

methodsWe adopt and report a systematic approach to identify the most stable reference genes for miRNA expression studies by RT-qPCR in colorectal cancer (CRC). High-throughput miRNA profiling was performed on ten pairs of CRC and normal tissues. By using the mean expression value of all expressed miRNAs, we identified the most stable candidate reference genes for subsequent validation. As such the stability of a panel of miRNAs was examined on 35 tumour and 39 normal tissues. The effects of normalisers on the relative quantity of established oncogenic (miR-21 and miR-31) and tumour suppressor (miR-143 and miR-145) target miRNAs were assessed.

resultsIn the array experiment, miR-26a, miR-345, miR-425 and miR-454 were identified as having expression profiles closest to the global mean. From a panel of six miRNAs (let-7a, miR-16, miR-26a, miR-345, miR-425 and miR-454) and two small nucleolar RNA genes (RNU48 and Z30), miR-16 and miR-345 were identified as the most stably expressed reference genes. The combined use of miR-16 and miR-345 to normalise expression data enabled detection of a significant dysregulation of all four target miRNAs between tumour and normal colorectal tissue.

conclusionsOur study demonstrates that the top six most stably expressed miRNAs (let-7a, miR-16, miR-26a, miR-345, miR-425 and miR-454) described herein should be validated as suitable reference genes in both high-throughput and lower throughput RT-qPCR colorectal miRNA studies.

Indexed as

Gene Expression Regulation, NeoplasticOligonucleotide Array Sequence AnalysisReverse Transcriptase Polymerase Chain ReactionAgedAged, 80 and overColorectal NeoplasmsFemaleGene Expression ProfilingHumansMaleMicroRNAsMiddle AgedProspective StudiesReference StandardsReproducibility of ResultsRNA StabilityMicroRNAsMIRN454 microRNA, human

Identifiers

PMID20429937
PMCPMC2873395
OpenAlexW2139016888

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.