Advancing breast cancer subtyping: optimizing immunohistochemical staining classification with insights from real-world Taiwanese data.

Gene expression signatures provide valuable information to guide postoperative treatment in breast cancer (BC) patients. However, genetic tests are prohibitively expensive for the majority of BC patients. Immunohistochemical staining (IHC) subtype classification system has been widely used for treatment guideline and is affordable to most BC patients. We aimed to revise immunohistochemical staining (IHC) subtyping to better match gene expression-based Prediction Analysis of Microarray 50 (PAM50) subtyping. Real world data of 372 BC patients were recruited in the Tri-Service General Hospital between Jan 2019 and Dec 2021. Clinical pathological information, blood, twelve pathological tissue slide samples, and fresh surgical tumor specimens were collected to examine IHC and PAM50. Current IHC subtyping (cIHC) tends to misclassify PAM50-based luminal A (lum A) to luminal B (lum B) by 35.81%, PAM50-lum B to PAM50-lum A by 9.09%, PAM50-Her2-enriched to lum B by 61.11%, PAM50-based Her2-enriched to lum B by 61.11%, and PAM50-based basal-like to lum B by 33.33%. We used random forest to identify estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (Her2), and Ki-67 status as the best indicators for revised IHC subtyping (rIHC4) and revised the classification rules by stratified analysis and prediction efficacy. rIHC4 increased the concordance rate for PAM50 subtypes from 68.3% to 74.7%. Both sensitivity and precision increased in most rIHC4 subtypes. Sensitivity increased from 33.3% to 87.4% in the Her2-enriched subtype; precision increased more evidently in the basal-like and lum B subtypes, from 71.4% to 83.3% and 57% to 65.1%, respectively. Our rIHC4 subtyping improved consistency with the PAM50 subtype, which could improve clinical management of BC patients without increasing medical expense.