Looking beyond the ER, PR, and HER2: what's new in the ARsenal for combating breast cancer?

Abstract

Breast cancer (BrCa) is a complex and heterogeneous disease with diverse molecular subtypes, leading to varied clinical outcomes and posing significant treatment challenges. The increasing global burden of BrCa, particularly in low- and middle-income countries, underscores the urgent need for more effective therapeutic strategies. The androgen receptor (AR), expressed in a substantial proportion of breast cancer cases, has emerged as a potential biomarker and therapeutic target. In breast cancer, AR exhibits diverse functions across subtypes, often interacting with other hormone receptors, thereby influencing tumor progression and treatment responses. This intricate interplay is further complicated by the presence of constitutively expressed AR splice variants (AR-Vs) that drive resistance to AR-targeting therapies through structural rearrangements in the domains and activation of aberrant signaling pathways. Although AR-targeting drugs, initially developed for prostate cancer (PCa), have shown promise in AR-positive breast cancer, significant gaps remain in understanding AR's precise functions and therapeutic potential. The systemic management of breast cancer is guided primarily by theranostic biomarkers; ER, PR, HER2, and Ki67 which also dictate the breast cancer classification. The ubiquitous expression of AR in BrCa and the emergence of AR-Vs can assist the management of disease complementing the standard of care. This article provides a comprehensive overview of AR and its splice variants in the context of breast cancer, highlighting their prognostic and predictive value across different subtypes looking beyond the conventional ER, PR, and HER2 status. This review also raises the possibility of using AR splice variants in predicting tumor aggressiveness. From the settings of developing nations, this may provide useful insight by integrating recent advances in AR-targeted therapies and exploring their translational potential, emphasizing the critical need for further research to optimize AR-based therapeutic strategies for breast cancer management.