Estrogen Signaling in Early-Stage Breast Cancer: Impact on Neoadjuvant Chemotherapy and Immunotherapy

Abstract

Neoadjuvant chemoimmunotherapy (NACIT) has been shown to improve pathologic complete response (pCR) rates and survival outcomes in stage II-III triple-negative breast cancer (TNBC). Promising pCR rate improvements have also been documented for selected patients with estrogen receptor-positive (ER+) human epidermal growth factor receptor 2-negative (HER2-) breast cancer (BC). However, one size does not fit all and predicting which patients will benefit from NACIT remains challenging. Accurate predictions would be useful to minimize immune-related toxicity, which can be severe, irreversible, and potentially impact fertility and quality of life, and to identify patients in need of alternative treatments.

This review aims to capitalize on the existing translational and clinical evidence on predictors of treatment response in patients with early-stage BC treated with neoadjuvant chemotherapy (NACT) and NACIT. It summarizes evidence suggesting that NACT/NACIT effectiveness may correlate with pre-treatment tumor characteristics, including mutational profiles, ER expression and signaling, immune cell presence and spatial organization, specific gene signatures, and the levels of proliferating versus quiescent cancer cells.

However, the predominantly qualitative and descriptive nature of many studies highlights the challenges in integrating various potential response determinants into a validated, comprehensive, and multimodal predictive model. The potential of novel multi-modal approaches, such as those based on artificial intelligence, to overcome current challenges remains unclear, as these tools are not free from bias and shortcut learning. Despite these limitations, the rapid evolution of these technologies, coupled with further efforts in basic and translational research, holds promise for improving treatment outcome predictions in early HER2- BC.