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Updated: Mar 27, 2026

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
Published on: August 1, 2018
Robust Association of Breast Cancer Co-morbidity Using Subtype-specific Expressed Genes
Megha Gupta1, Surekha Verma1, Satyanarayan Rao1
1Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India.
Introduction:
Breast 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.
Methods:
We 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.
Results:
We 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.
Conclusion:
This 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.
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