Evidence map›Paper›PMID 40724805›Full record

ArticleInternational journal of molecular sciences2025

Unveiling Epigenetic Regulatory Elements Associated with Breast Cancer Development.

Marta Jardanowska-Kotuniak, Michał Dramiński, Michal Wlasnowolski, Marcin Łapiński, Kaustav Sengupta, Abhishek Agarwal, Adam Filip, Nimisha Ghosh, Vera Pancaldi, Marcin Grynberg and 3 more

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Marta Jardanowska-KotuniakComputational Biology Group, Institute of Computer Science of the Polish Academy of Sciences, 01-248 Warsaw, Poland.ORCID 0000-0003-0181-6266
Michał DramińskiComputational Biology Group, Institute of Computer Science of the Polish Academy of Sciences, 01-248 Warsaw, Poland.
Michal WlasnowolskiLaboratory of Bioinformatics and Computational Genomics, Faculty of Mathematics and Information Science, Warsaw University of Technology, 00-662 Warsaw, Poland.ORCID 0000-0003-0857-0713
Marcin ŁapińskiComputational Biology Group, Institute of Computer Science of the Polish Academy of Sciences, 01-248 Warsaw, Poland.
Kaustav SenguptaLaboratory of Bioinformatics and Computational Genomics, Faculty of Mathematics and Information Science, Warsaw University of Technology, 00-662 Warsaw, Poland.ORCID 0000-0003-0603-0916
Abhishek AgarwalLaboratory of Functional and Structural Genomics, Centre of New Technologies, University of Warsaw, 02-097 Warsaw, Poland.ORCID 0000-0003-4981-8746
Adam FilipComputational Biology Group, Institute of Computer Science of the Polish Academy of Sciences, 01-248 Warsaw, Poland.
Nimisha GhoshDepartment of Computer Science and Engineering, Shiv Nadar University, Chennai 201314, India.
Vera PancaldiCancer Research Center Toulouse, National Centre for Scientific Research (CNRS), Inserm, Université de Toulouse, 31037 Toulouse, France.ORCID 0000-0002-7433-624X
Marcin GrynbergInstitute of Biochemistry and Biophysics of the Polish Academy of Sciences, 02-106 Warsaw, Poland.
Indrajit SahaDepartment of Computer Science and Engineering, National Institute of Technical Teachers' Training and Research, Kolkata 700106, India.ORCID 0000-0001-9513-9707
Dariusz PlewczynskiLaboratory of Bioinformatics and Computational Genomics, Faculty of Mathematics and Information Science, Warsaw University of Technology, 00-662 Warsaw, Poland.ORCID 0000-0002-3840-7610
Michał J DąbrowskiComputational Biology Group, Institute of Computer Science of the Polish Academy of Sciences, 01-248 Warsaw, Poland.ORCID 0000-0003-1269-6722

Funding

Nucleome Positioning System for Spatiotemporal Genome Organization and RegulationU54DK107967 · NIDDK · JACKSON LABORATORY · PI WEI, CHIA-LIN · 2015 to 2019
$3.6M
National Institute of Health USA 4DNucleome grant 1U54DK107967-01NIDDK NIH HHS U54 DK107967Polish Ministry of Science and Higher Education 7054/IA/SP/2020 of 2020-08-28Warsaw University of Technology within the Excellence Initiative: Research University (IDUB) programme co-supported by Polish National Science Centre 2020/37/B/NZ2/03757
6 · The paper itself

Abstract

Breast cancer affects over 2 million women annually and results in 650,000 deaths. This study aimed to identify epigenetic mechanisms impacting breast cancer-related gene expression, discover potential biomarkers, and present a novel approach integrating feature selection, Natural Language Processing, and 3D chromatin structure analysis. We used The Cancer Genome Atlas database with over 800 samples and multi-omics datasets (mRNA, miRNA, DNA methylation) to select 2701 features statistically significant in cancer versus control samples, from an initial 417,486, using the Monte Carlo Feature Selection and Interdependency Discovery algorithm. Classification of cancer vs. control samples on the selected features returned very high accuracy, depending on feature-type and classifier. The cancer samples generally showed lower expression of differentially expressed genes (DEGs) and increased

Indexed as

Breast NeoplasmsEpigenesis, GeneticChromatinComputational BiologyDNA MethylationFemaleGene Expression Regulation, NeoplasticHumansMicroRNAsRNA, MessengerChromatinMicroRNAsRNA, Messengerbreast cancerchromatin structureepigenetic regulationMCFS-IDMonte Carlo Feature SelectionNatural Language ProcessingNKAPLNRF1transcription factor

Identifiers

PMID40724805
PMCPMC12295874

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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.