Evidence map›Paper›PMID 41879447›Full record

ArticleCurrent drug targets2026

Robust Association of Breast Cancer Co-morbidity Using Subtype-specific Expressed Genes.

Megha Gupta, Surekha Verma, Satyanarayan Rao, Rajesh Kumar

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Article in Current drug targets, 2026. 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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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Megha GuptaDepartment of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India.
Surekha VermaDepartment of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India.
Satyanarayan RaoDepartment of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India.
Rajesh KumarDepartment of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionBreast cancer is a heterogeneous disease characterized by complex genetic and molecular alterations that drive its progression and metastasis to distant organs. It frequently cooccurs with comorbid conditions, which complicates diagnosis, treatment planning, and overall prognosis. Understanding the genetic overlap between breast cancer and comorbid diseases is therefore critical for improving precision medicine approaches and clinical outcomes.

methodsWe performed a comprehensive comorbidity assessment for breast cancer using gene-level associations and identified 194 diseases strongly associated with the disease. Gene Ontology and pathway-based analyses were conducted to explore functional overlaps. In addition, differential gene expression profiles were analyzed across major breast cancer subtypes, Luminal, HER2-enriched, and Basal-like, to investigate subtype-specific molecular contributions to comorbidity and metastasis.

resultsWe identified strong associations between breast cancer and several disease classes, including neoplastic, respiratory, digestive, cardiovascular, and musculoskeletal disorders. Distinct organspecific metastatic patterns were observed across subtypes: Basal-like tumors showed lung metastasis, HER2-enriched subtypes favored liver metastasis, and Luminal subtypes preferentially metastasized to bone. These metastatic patterns were supported by subtype-specific gene expression profiles, suggesting that key genes may drive both comorbidity and metastasis. DISCUSSION: The integration of gene expression and comorbidity profiling highlights the molecular mechanisms that link breast cancer progression with associated diseases. These findings provide valuable insights into how comorbid conditions may influence therapeutic responses and treatment planning. Subtype-specific metastasis further emphasizes the role of molecular drivers in determining clinical outcomes and offers an avenue for more tailored interventions.

conclusionThis study underscores the importance of comorbidity profiling in breast cancer. Our findings provide perspectives for developing personalized therapeutic strategies and may aid in improving clinical management and long-term outcomes for breast cancer patients.

Indexed as

Breast NeoplasmsComorbidityErb-b2 Receptor Tyrosine KinasesFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansNeoplasm MetastasisErb-b2 Receptor Tyrosine KinasesBreast cancercancer patientscomorbidity assessmentdisease-disease networkgene disease associationnetwork-based method

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PMID41879447

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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.