Evidence map›Paper›PMID 28051134›Full record

ArticleScientific reports2017

Validation of suitable normalizers for miR expression patterns analysis covering tumour heterogeneity.

C Morata-Tarifa, M Picon-Ruiz, C Griñan-Lison, H Boulaiz, M Perán, M A Garcia, J A Marchal

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

17 citing papers in PubMed, 24 citations in OpenAlex.

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  5. Targeted MicroRNA Profiling in Gastric Cancer with Clinical Assessement.Balkan journal of medical genetics : BJMG · 2021
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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

7 authors at 3 institutions in 2 countries.

C Morata-TarifaBiopathology and Medicine Regenerative Institute (IBIMER), University of Granada, Granada, Spain.
M Picon-RuizBiopathology and Medicine Regenerative Institute (IBIMER), University of Granada, Granada, Spain.
C Griñan-LisonBiopathology and Medicine Regenerative Institute (IBIMER), University of Granada, Granada, Spain.
H BoulaizBiopathology and Medicine Regenerative Institute (IBIMER), University of Granada, Granada, Spain.
M PeránBiopathology and Medicine Regenerative Institute (IBIMER), University of Granada, Granada, Spain.
M A GarciaBiopathology and Medicine Regenerative Institute (IBIMER), University of Granada, Granada, Spain.
J A MarchalBiopathology and Medicine Regenerative Institute (IBIMER), University of Granada, Granada, Spain.
Instituto de Investigación Biosanitaria de Granada · ESUniversidad de Granada · ESUniversidad de Jaén · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oncogenic microRNAs (miRs) have emerged as diagnostic biomarkers and novel molecular targets for anti-cancer drug therapies. Real-time quantitative PCR (qPCR) is one of the most powerful techniques for analyzing miRs; however, the use of unsuitable normalizers might bias the results. Tumour heterogeneity makes even more difficult the selection of an adequate endogenous normalizer control. Here, we have evaluated five potential referenced small RNAs (U6, rRNA5s, SNORD44, SNORD24 and hsa-miR-24c-3p) using RedFinder algorisms to perform a stability expression analysis in i) normal colon cells, ii) colon and breast cancer cell lines and iii) cancer stem-like cell subpopulations. We identified SNORD44 as a suitable housekeeping gene for qPCR analysis comparing normal and cancer cells. However, this small nucleolar RNA was not a useful normalizer for cancer stem-like cell subpopulations versus subpopulations without stemness properties. In addition, we show for the first time that hsa-miR-24c-3p is the most stable normalizer for comparing these two subpopulations. Also, we have identified by bioinformatic and qPCR analysis, different miR expression patterns in colon cancer versus non tumour cells using the previously selected suitable normalizers. Our results emphasize the importance of select suitable normalizers to ensure the robustness and reliability of qPCR data for analyzing miR expression.

Indexed as

Biomarkers, TumorCell Line, TumorComputational BiologyGene Expression Regulation, NeoplasticHumansMicroRNAsNeoplasmsReal-Time Polymerase Chain ReactionBiomarkers, TumorMicroRNAs

Identifiers

PMID28051134
PMCPMC5209713
OpenAlexW2569202120

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.