Tailoring neoadjuvant treatment of HR-positive/HER2-negative breast cancers: Which role for gene expression assays?

Neoadjuvant chemotherapy (NACT) for breast cancer (BC) increases surgical and conservative surgery chances. However, a significant proportion of patients will not be eligible for conservative surgery following NACT because of large tumor size and/or low chemosensitivity, especially for hormone receptor (HR)-positive/ human epidermal growth factor receptor 2 (HER2)-negative tumors, for which pathological complete response rates are lower than for other BC subtypes. On the other hand, for luminal BC neoadjuvant endocrine therapy could represent a valid alternative. Several gene expression assays have been introduced into clinical practice in last decades, in order to define prognosis more accurately than clinico-pathological features alone and to predict the benefit of adjuvant treatments. A series of studies have demonstrated the feasibility of using core needle biopsy for gene expression risk testing, finding a high concordance rate in the risk result between biopsy sample and surgical samples. Based on these premises, recent efforts have focused on the utility of gene expression signatures to guide therapeutic decisions even in the neoadjuvant setting. Several prospective and retrospective studies have investigated the correlation between gene expression risk score from core needle biopsy before neoadjuvant therapy and the likelihood of 1) clinical and pathological response to neoadjuvant chemotherapy and endocrine therapy, 2) conservative surgery after neoadjuvant chemotherapy and endocrine therapy, and 3) survival following neoadjuvant chemotherapy and endocrine therapy. The purpose of this review is to provide an overview of the potential clinical utility of the main commercially available gene expression panels (Oncotype DX, MammaPrint, EndoPredict, Prosigna/PAM50 and Breast Cancer Index) in the neoadjuvant setting, in order to better inform decision making for luminal BC beyond the exclusive contribution of clinico-pathological features.