Association of Immunohistochemically Defined Molecular Subtypes With Clinicopathologic Factors in Indonesian Women With Breast Cancer

Background: Breast cancer is a heterogeneous disease. It is classified into various subtypes based on molecular difference, primarily through gene expression profiling (GEP) and immunohistochemistry (IHC) techniques. GEP is able to reveal gene signatures that predict clinical outcomes, and can discern prognostically relevant breast cancer subtypes, but it is not yet used routinely in the clinical practice, especially in the developing countries. On the other hand, IHC analysis is commonly used for breast cancer subtyping and provides critical prognostic and predictive information. Aim: The current study was aimed to established a comprehensive outline of Indonesian breast cancer subtypes distribution and their associations with the clinicopathologic factors based on a standard routinely used biomarker panel, i.e., estrogen-receptor (ER), progesterone-receptor (PR), and human epidermal growth factor receptor 2 (HER2). Methods: A retrospective cross-sectional study was conducted of 390 breast cancer cases in Dr. Sardjito General Hospital Yogyakarta, Indonesia from 2010 to 2015. Breast cancer subtypes were classified based on the expression of ER, PR, HER2 and histologic grade. The association of Indonesian breast cancer subtypes with clinicopathologic factors was evaluated using χ2 tests. Results: The majority of Indonesian breast cancer patients were older than 50 years, have larger tumor size (> 2 cm), high grade and absence of lymph node metastases. Among 390 cases, 32.1% were luminal A, 24.6% were luminal B, 17.9% were HER2+ and the remaining 25.4% were triple negative breast cancer (TNBC). High association was found in breast cancer molecular subtypes with regard to patients age, tumor size, histologic grade and lymph node metastases. Conclusion: Luminal A is the most common Indonesian breast cancer subtypes, followed by TNBC, luminal B and HER2. Immunohistochemistry-based subtyping is essential to classify breast cancer into subtypes that vary in clinicopathologic characteristics, which implies distinct prognosis and therapy response. Further studies are needed to clarify the mechanisms associated with development of each subtype.