Purpose:
Neoadjuvant treatment (NAT) of early breast cancer is increasingly being used to downstage tumors, allowing improved chances of breast-conserving surgery.Here we combine data from multiple studies to identify pre-treatment and on-treatment biomarkers of response to NAT with the potential to lead to more efficient patient stratification.
Methods:
We pool and analyse 10 independent NAT studies that have publicly available gene expression data (1861 samples, 1020 patients). Differential gene expression analysis was conducted on the pooled samples to derive a NAT response signature (NRS) and two NAT response subtypes. The NRS was then used along with additional variables to train a NAT response classifier. We use an additional 4 studies (418 samples, 258 patients) to further evaluate the performance of our classifier.
Results:
We identified 166 deferentially expressed genes between responders and non-responders, which are mainly involved in cell cycle and DNA repair pathways. We derive two molecular subtypes associated with NAT response and other clinical predictors. Our NAT response classifier achieves an Area Under the Curve (AUC) of 0.79 on a held-out test set (134 samples). Remarkably, in one external validation study, AUC increased from 0.64 to 0.82 when focusing on the estrogen receptor positive (ER+) samples only.
Conclusion:
We report a set of markers that are differentially expressed in NAT responders and demonstrate how they can be used to predict response to NAT for ER+ patients with early stage breast cancer, which might allow for improved risk stratification, surveillance or different treatments.