Luminal B-like predominance in breast cancer: A 5-year institutional experience of 2271 women from a tertiary cancer center in South India
M. S. Sulakshana, S. Sreelakshmi, Kanyadhara Lohita Krishna, Shanthi Velusamy, V. Divya, V. Chaitra, Prasanna Kumari, B. S. Srinath, Rekha V. KumarABSTRACT
Introduction:
Breast cancer is the most frequently diagnosed malignancy among women, surpassing cervical cancer. Classifying tumors based on surrogate molecular subtypes using immunohistochemistry (IHC) and in situ hybridization (ISH) for human epidermal growth factor receptor (HER2) is essential for guiding treatment decisions. This study aims to assess the prevalence of these molecular subtypes in a South Indian population.
Materials and Methods:
This retrospective study included women diagnosed with invasive breast carcinoma between January 2019 and December 2023. Cases with incomplete biomarker data were excluded. IHC for estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki-67 was performed, and HER2 IHC 2 + cases were further evaluated using fluorescence in situ hybridization. Tumors were categorized into surrogate molecular subtypes using established American Society of Clinical Oncology and College of American Pathologists and St. Gallen guidelines. Clinical and histopathological data were collected from hospital records.
Results:
A total of 2271 patients were analyzed (median age: 58 years; 73.6% postmenopausal). Luminal B-like tumors were the most common subtype (62.6%), followed by triple-negative breast cancer (TNBC) at 16.4%, HER2-enriched (non-luminal) at 10.7%, and luminal A-like at 10.2%. Notably, the number of triple-positive tumors exceeded that of TNBC (23.38% vs. 16.4%). ER and PR positivity rates were 68.8% and 65.1%, respectively, and HER2 positivity was observed in 34.1% of cases. Invasive carcinoma of no special type constituted 95.5% of cases, with Grade 2 tumors being the most common (63.8%).
Conclusion:
The distribution of menopausal status, molecular subtypes, and histologic features in our cohort closely resembled patterns reported in Western populations. These findings emphasize the heterogeneity of patients and the need for generating local data to effectively address breast cancer treatment.