Histopathological correlation with molecular classification of breast carcinoma in a rural population of Pune Maharashtra, India

Breast cancer is the most prevalent cancer among women globally, with an increasing incidence in countries like India. Despite the established histopathological classification of breast cancer, its heterogeneity poses challenges in predicting patient outcomes and selecting appropriate treatments. Recent advancements in molecular biology have led to the development of molecular subtypes of breast cancer, which provide a more precise prognostic assessment. This study aims to correlate histopathological features with molecular subtypes using immunohistochemical (IHC) markers to improve the accuracy of breast cancer diagnosis and treatment. A cross-sectional, observational study was conducted on 500 primary breast carcinoma patients diagnosed between January 2020 and January 2024. Patients were categorized based on clinical features, histopathological findings, and molecular subtypes determined by IHC markers for estrogen receptor (ER), progesterone receptor (PR), HER2, Ki67, epidermal growth factor receptor (EGFR), and CK 5/6. The molecular subtypes identified included Luminal A, Luminal B, HER2-enriched, and Basal-like (triple-negative), with histopathological features such as tumor grade, size, lymphovascular invasion (LVI), and lymph node involvement also recorded. Showed that Luminal A tumors were associated with lower tumor grades, smaller sizes, and less aggressive features. In contrast, HER2-enriched and Basal-like subtypes demonstrated more aggressive behavior, with higher tumor grades, larger sizes, and increased rates of metastasis. Statistically significant correlations were found between molecular subtypes and histopathological features (p < 0.05). Immunohistochemical markers like HER2, Ki67, and EGFR were key in determining tumor aggressiveness and treatment planning. This study emphasizes integrating molecular subtyping with histopathological evaluation to personalize breast cancer treatment. By identifying the molecular characteristics of tumors, clinicians can optimize therapeutic strategies, reduce unnecessary chemotherapy, and improve patient outcomes. These findings advocate for using molecular profiling in clinical practice to enhance breast cancer diagnosis and treatment strategies.