Immunohistochemical Breast Cancer Profiling Among Iraqi Women: Molecular Subtype Classification, Clinicopathology Associations, and Treatment-Decision Making Tools: A Cross-Sectional Study.

Breast cancer is the most common cause of female cancer-related death in Iraq. This study aimed to classify breast cancer molecular subtypes in the Iraqi population, and investigate the association with clinicopathology parameters, and predict survival outcomes. This cross-sectional study collected breast cancer samples that included: tumor size, grade, lymph node involvement, and LVI. Cases were stained for estrogen (ER) and progesterone (PR) receptors, HER2, and Ki-67 for IHC subtyping. HER2 score 3 cases were further evaluated by SISH. Molecular profile classification used the St Gallen consensus. The tumor profiles were modelled with treatment combinations using the PREDICT decision making tool of up to 10-year OS outcomes; > 5% differences were deemed clinically relevant. The mean age of patients was 50.16 ± 12.28 years. ER and PR positivity was high (81.8% and 73.7%) relative to HER2 (20.8%). Significant clinicopathology associations occurred between ER expression and tumor type and grade (p = 0.001, 0.027); HER2 with histology (p = 0.044). Ki-67 high expression (26.8%) was associated with LVI (p = 0.006). Molecular classification (IHC subtypes) identified Luminal A (Luminal-A-like) tumors in most cases (61.7%), followed by Luminal B (Luminal-B-like) (20.0%), HER2 (9.5%) and basal-like (triple negative breast cancer (TNBC)) at 8.7%. By selecting the right treatment adjuvant to tumor profile, PREDICT modelling estimated that most post-surgery patients (85.7%, ER+; 100%, ER-) would have clinically relevant overall survival (OS) benefit. St Gallen molecular characterisation of breast tumors is critical for refining triage of healthcare patients in Iraq. Molecular classification using IHC subtypes identified a high prevalence of favorable Luminal-A-like type, and the lowest worldwide rates of poor prognostic TNBC cancer. The use of immunohistochemistry-based cancer subtyping is further strengthened in clinical practice with online prognostication tools that assist the treatment selection process.