PO-491 Single-cell phenotypic profiling of breast cancerpatient-derived tumour xenografts using mass cytometry

Introduction Despite the advances in patient stratification and the understanding of basic molecular mechanisms underlining breast cancer (BC), 30% of patients with early stages of the disease later relapse. To offer more effective treatments to these patients, we need to adapt pre-clinical drug development to account for the main feature of human cancer: heterogeneity. Our group has established a biobank of 160 BC patient-derived tumour xenografts (PDTXs) and has robustly shown that PDTXs and their matching patient-derived tumour cells (PDTCs) preserve most of the originating sample’s molecular features, including intra-tumour clonal diversity (Bruna et al. Cell 2016). This integrated platform permits high-throughput (HT) assessment of drug responses ex vivo in PDTCs and their validation in vivo in PDTXs. Thus, this PDTX/PDTC biobank represents a powerful resource for pre-clinical drug development in BC. Material and methods Here, we aim to add a crucial layer of molecular characterisation at single-cell resolution by studying the phenotypic tumour heterogeneity in BC PDTXs and its role in drug response mechanisms. To achieve this goal, we employed the state-of-the-art HT single-cell method called mass cytometry (CYTOF), which combines the principles of flow cytometry and mass spectrometry allowing the simultaneous analysis of about 40 molecular events using metal-conjugated antibodies. Results and discussions We designed and validated a BC-specific panel of 35 antibodies to investigate: a)the epithelial tumour compartment; b)the stroma tumour compartment; c)oncogenic signalling; d)cell cycle and apoptosis. We used this panel in CyTOF experiments to perform an in-depth phenotypic characterisation of a representative collection of BC cell lines and molecularly distinct PDTXs. Using data-driven unsupervised methods to analyse the CyTOF data focusing on the epithelial compartment, we show that we capture different degrees of both inter- and intra-tumour functional heterogeneity. Importantly, we show that CyTOF can be used to characterise the heterogeneity in signalling dynamics within the different tumour compartments under the perturbation of therapy. Conclusion CyTOF is a novel approach to characterise heterogeneity and drug responses in BC PDTXs. The integration of high-level features, such as single-cell phenotypic profiles, and functional features, such as drug response data, obtained with CyTOF will facilitate the pre-clinical development of novel therapeutic strategies and will help to uncover mechanisms of drug resistance.