Evidence map›Paper›PMID 34791555›Full record

ArticleBulletin of experimental biology and medicine2021

Optimized Marker System for Early Diagnosis of Breast Cancer.

A M Burdennyy, E A Filippova, D S Khodyrev, I V Pronina, S S Lukina, N A Ivanova, T P Kazubskaya, V I Loginov, E A Braga

Abstract read
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In one paragraph

Article in Bulletin of experimental biology and medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 44% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

9 authors at 3 institutions in 1 country.

A M BurdennyyResearch Institute of General Pathology and Pathophysiology, Moscow, Russia. burdennyy@gmail.com.
E A FilippovaResearch Institute of General Pathology and Pathophysiology, Moscow, Russia.
D S KhodyrevFederal Research Clinical Center of Specialized Types of Medical Care and Medical Technologies, Federal Medial-Biological Agency of Russia, Moscow, Russia.
I V ProninaResearch Institute of General Pathology and Pathophysiology, Moscow, Russia.
S S LukinaResearch Institute of General Pathology and Pathophysiology, Moscow, Russia.
N A IvanovaResearch Institute of General Pathology and Pathophysiology, Moscow, Russia.
T P KazubskayaN. N. Blokhin National Medical Research Center of Oncology, Ministry of Health of the Russian Federation, Moscow, Russia.
V I LoginovResearch Institute of General Pathology and Pathophysiology, Moscow, Russia.
E A BragaResearch Institute of General Pathology and Pathophysiology, Moscow, Russia.
Research Institute of General Pathology and Pathophysiology, the Russian Academy of Medical Sciences · RUFederal Medical-Biological Agency · RUMinistry of Health of the Russian Federation · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Changes in the methylation levels of 21 microRNA genes in 91 breast cancer samples in comparison with paired samples of histologically unchanged tissue were studied by quantitative methylation-specific PCR. For 19 microRNA genes, a significant increase in the methylation level in tumors in comparison with normal tissues was shown (Mann-Whitney test). When considering the data for breast cancer samples only from patients with clinical stages I and II (59samples), 17 genes with a significantly increased level of methylation were identified. Increased methylation level for 11 genes (MIR124-1, MIR124-3, MIR125B-1, MIR127, MIR129-2, MIR132, MIR137, MIR193a, MIR34B/C, MIR375, and MIR9-1) compared to the paired norm was highly significant (p<0.001, FDR=0.01). The ROC analysis was used to optimize a set of markers for diagnosing breast cancer at the early stages consisting of 4 microRNA genes: MIR125B1, MIR127, MIR1258, and MIR132; the system is characterized by 100% specificity, 85% sensitivity, and AUC=0.924. Importantly, 100% specificity eliminates false positive results. Detection of methylation of at least one of the 4 genes of this set is sufficient to classify the patient's sample as breast cancer.

Indexed as

Biomarkers, TumorBreast NeoplasmsDNA MethylationEarly Detection of CancerFemaleGene Expression Regulation, NeoplasticHumansMicroRNAsNeoplasm StagingBiomarkers, TumorMicroRNAsbreast cancerdiagnosticsmethylationmicroRNA genes

Identifiers

PMID34791555
OpenAlexW3190614687

What OpenQuestion holds

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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.