Evidence map›Paper›PMID 34793290›Full record

ArticleRNA biology2021

A novel panel of blood-based microRNAs capable of discrimination between benign breast disease and breast cancer at early stages.

Hanieh Sadeghi, Aryan Kamal, Marzieh Ahmadi, Hadi Najafi, Ali Sharifi Zarchi, Peyman Haddad, Bahareh Shayestehpour, Leila Kamkar, Masoumeh Salamati, Loabat Geranpayeh and 2 more

Open access · bronzeAbstract read
In one paragraph

Article in RNA biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 33% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
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  4. 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

12 authors at 5 institutions in 2 countries.

Hanieh SadeghiDepartment of Genetics, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, Acecr, Tehran, Iran.
Aryan KamalDepartment of Clinical Bioinformatics, Saarland University, Saarbrücken, Germany.
Marzieh AhmadiDepartment of Genetics, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, Acecr, Tehran, Iran.
Hadi NajafiDepartment of Genetics, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, Acecr, Tehran, Iran.
Ali Sharifi ZarchiDepartment of Computer Engineering, Sharif University of Technology, Tehran, Iran.
Peyman HaddadRadiation Oncology Research Center, Iran Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran.
Bahareh ShayestehpourDepartment of Genetics, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, Acecr, Tehran, Iran.
Leila KamkarDepartment of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
Masoumeh SalamatiDepartment of Reproductive Imaging, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, Acecr, Tehran, Iran.
Loabat GeranpayehDepartment of Surgery, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran.
Marzieh LashkariRadiation Oncology Research Center, Iran Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran.
Mehdi TotonchiDepartment of Genetics, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, Acecr, Tehran, Iran.
Royan Institute · IRTehran University of Medical Sciences · IRSaarland University · DESharif University of Technology · IRUniversity of Tehran · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer (BC) as a leading cause of cancer death among women, exhibits a wide range of genetic heterogeneity in affected individuals. Satisfactory management of BC depends on early diagnosis and proper monitoring of patients' response to therapy. In this study, we aimed to assess the relation between the expression patterns of blood-based microRNAs (miRNAs) with demographic characteristics of the patients with BC in an attempt to find novel diagnostic markers for BC with acceptable precision in clinical applications. To this end, we performed comprehensive statistical analysis of the data of the Cancer Genome Atlas (TCGA) database and the blood miRNome dataset (GSE31309). As a result, 21 miRNAs were selected for experimental verification by quantitative RT-PCR on blood samples of 70 BC patients and 60 normal individuals (without any lesions or benign breast diseases). Statistical one-way ANOVA revealed no significant difference in the blood levels of the selected miRNAs in BC patients compared to any lesions or benign breast diseases. However, the multi-marker panel consisting of hsa-miR-106b-5p, -126-3p, -140-3p, -193a-5p, and -10b-5p could detect early-stages of BC with 0.79 sensitivity, 0.86 specificity and 0.82 accuracy. Furthermore, this multi-marker panel showed the potential of detecting benign breast diseases from BC patients with 0.67 sensitivity, 0.80 specificity, and 0.74 accuracy. In conclusion, these data indicate that the present panel might be considered an asset in detecting benign breast disease and BC.

Indexed as

BiomarkersCirculating MicroRNABiomarkers, TumorBreast DiseasesBreast NeoplasmsDiagnosis, DifferentialEarly Detection of CancerFemaleHigh-Throughput Nucleotide SequencingHumansLiquid BiopsyMicroRNAsNeoplasm StagingPhosphatidylinositol 3-KinasesPrognosisProto-Oncogene Proteins c-aktBiomarkersBiomarkers, TumorCirculating MicroRNAMicroRNAsPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktblood-based microRNAcancer detectionclinical bioinformaticsMicroRNA biomarkerTCGA

Identifiers

PMID34793290
PMCPMC8782186
OpenAlexW3211935214

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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.