Evidence map›Paper›PMID 41444310›Full record

ArticleScientific reports2025

Decoding molecular signatures and identifying therapeutic targets in triple-negative breast cancer subtypes using omics and network analysis.

Debapriya Sanyal, Abdullah M AlShahrani, Soumya Kar, S Rehan Ahmad, Chittabrata Mal, Sunil Kanti Mondal

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Debapriya SanyalDepartment of Biotechnology, University of Burdwan, Golapbag, Bardhaman, West Bengal, 713104, India.
Abdullah M AlShahraniDepartment of Basic Medical Science, College of Applied Medical Sciences, Khamis Mushait Campus, King Khalid University (KKU), 62561, Abha, Saudi Arabia.
Soumya KarDepartment of Biotechnology, University of Burdwan, Golapbag, Bardhaman, West Bengal, 713104, India.
S Rehan AhmadHiralal Mazumdar Memorial College for Women, West Bengal State University, Government of West Bengal, Kolkata, West Bengal, India. professor.rehaan@gmail.com.
Chittabrata MalDepartment of Bioinformatics, Maulana Abul Kalam Azad University of Technology, West Bengal, Nadia, Haringhata, West Bengal, 741249, India. chittabrata.mal@makautwb.ac.in.
Sunil Kanti MondalDepartment of Biotechnology, University of Burdwan, Golapbag, Bardhaman, West Bengal, 713104, India. skmondal@biotech.buruniv.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC) is the most aggressive form of breast cancer. It is resistant to therapeutic applications, making it very difficult to manage. Most patients continue to receive chemotherapy. The main challenges in treating TNBC arise from its histopathological, transcriptomic, and genomic heterogeneity. While subtype classification was once essential for understanding TNBC's diverse behavior, it is now crucial to thoroughly evaluate the molecular characteristics of each subtype to improve TNBC management. Our study employed a multi-omics approach utilizing transcriptomic data to compare TNBC subtype-specific cell lines with normal breast epithelial cell lines. Our goal was to find out essential transcription factors (TFs) regulating cancer-related pathways, subtype-specific marker genes, and their key TFs. We identified a common set of genes involved in cancer related pathways and examined their alteration level with driver mutations in each subtype. Our findings indicate that, based on alteration patterns, survivability, differential gene and protein level expressions, the genes ERBB3, ERBB4, HLA-B, AKT1, GNAS, FGFR4, PIK3R3 and AXIN2 emerge as primary risk factors in TNBC. These genes, associated with specific subtypes, are potential markers and should be the focus of further studies, paving the way for personalized anticancer treatment strategies for TNBC patients.

Indexed as

Gene Regulatory NetworksTriple Negative Breast NeoplasmsBiomarkers, TumorCell Line, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMutationTranscription FactorsTranscriptomeBiomarkers, TumorTranscription FactorsBreast cancerDrugsMiRNAsMulti-omicsPathwaysRisk candidate genesTranscription factorsTranscriptomics

Identifiers

PMID41444310
PMCPMC12738556

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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.