Androgen Receptor as a Predictive Marker for Pathologic Complete Response in Hormone Receptor‒Positive and HER-2‒Negative Breast Cancer with Neoadjuvant Chemotherapy

다국어 초록 (Multilingual Abstract)

Purpose This study investigated pathological complete response (pCR) according to androgen receptor (AR) in breast cancer patients undergoing neoadjuvant chemotherapy and estimated the relationship between AR expression and clinicopathological factors.
Materials and Methods We identified 624 breast cancer patients who underwent surgery after neoadjuvant chemotherapy at the National Cancer Center in Goyang, Korea from April 2016 to October 2019. We retrospectively collected the clinicopathologic information and AR expression results and analyzed the data according to cancer stage, hormonal receptor (HR) status, human epidermal growth factor receptor 2 (HER2) status, tumor subtype, and pCR.
Results Among the 624 breast cancer patients, 529 (84.8%) were AR-positive (AR+) patients and 95 (15.2%) were AR-negative (AR–) patients. AR+ patients showed more estrogen receptor (ER) positivity, progesterone receptor (PR) positivity, HER2-positivity, and HR-positive and HER2-negative (HR+/HER2–) subtype. The rate of pCR was 31.4% (196/624). AR– patients had a significantly higher rate of pCR than AR+ patients (AR– 43.2% vs. AR+ 29.3%, p=0.007). The tumor factors associated with pCR were early stage, histologic grade 3, ER-negative, PR-negative, AR-negative, HER2-positive, and high Ki-67 values. In univariable analysis, AR+ significantly decreased the state of pCR (odds ratio, 0.546; 95% confidence interval, 0.349 to 0.853; p=0.008). According to tumor subtype, AR– tumor showed higher pCR rate in HR+/HER2– subtype (AR– 28.6% vs. AR+ 7.3%, p=0.022).
Conclusion AR expression is predominant in the HR+/HER2– subtype. AR– is significantly associated with the pCR rate in breast cancer patients, especially within HR+/HER2– subtype. When determining neoadjuvant chemotherapy for the HR+/HER2– subtype, AR expression can be considered as a pCR predictive marker.