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Deciphering the molecular heterogeneity of HER2-positive breast cancer: the critical interplay of hormone receptor status and transcriptomic landscapes

delete2026-06-16
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I
Ilker Sengul *
D
Demet Şengül
Ç
Çağrı Akalın
DOI:10.1007/s00726-026-03534-0delete
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Abstract

Abstract

En 中文
The clinical management of HER2-positive breast cancer is undergoing a paradigm shift, recognizing that hormone receptor (HR) co-expression defines a fundamental biological dichotomy rather than a minor clinical variation. This perspective evaluates the profound heterogeneity within the HER2-positive subclass, where HR status acts as a master regulator of genomic landscapes and patient outcomes. Evidence from large-scale database analyses reveals that HR+/HER2 + malignancies are associated with a significant survival advantage, contrasting with the heightened phenotypic aggression and advanced staging characteristic of HR-negative disease. At the molecular level, this divergence is underpinned by distinct transcriptomic profiles; specifically, the enrichment of drug-metabolizing pathways—including cytochrome P450 and retinol metabolism involving CYP2A6 and UGT2B7—suggests a mechanism for superior endocrine sensitivity and modulated apoptotic signaling in the double-positive cohort. Furthermore, the tumor microenvironment reflects this biological disparity, with HR status potentially governing local immune responses, as evidenced by the differential infiltration of resting mast cells versus plasma cells. Of note, while somatic mutations in TP53 and PIK3CA persist across both cohorts, the unique metabolic and immunological milieus confirm that these subtypes represent biologically discrete entities. Moving forward, the “HER2-positive” designation must be refined through integrated, biomarker-driven frameworks. Incorporating these molecular nuances into prospective clinical trials is essential for optimizing therapeutic de-escalation and overcoming the persistent challenges of resistance in HER2-targeted care.
Keywords:
HR status
HER2 positive
Breast cancer
Prognostic factors
Pathology
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Amino Acids
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