SummaryThe inter- and intra-tumor heterogeneity of breast cancer needs to be adequately captured in pre-clinical models. We have created a large collection of breast cancer patient-derived tumor xenografts (PDTXs), in which the morphological and molecular characteristics of the originating tumor are preserved through passaging in the mouse. An integrated platform combining in vivo maintenance of these PDTXs along with short-term cultures of PDTX-derived tumor cells (PDTCs) was optimized. Remarkably, the intra-tumor genomic clonal architecture present in the originating breast cancers was mostly preserved upon serial passaging in xenografts and in short-term cultured PDTCs. We assessed drug responses in PDTCs on a high-throughput platform and validated several ex vivo responses in vivo. The biobank represents a powerful resource for pre-clinical breast cancer pharmacogenomic studies (http://caldaslab.cruk.cam.ac.uk/bcape), including identification of biomarkers of response or resistance.

Circulating tumour DNA analysis can be used to track tumour burden and analyse cancer genomes non-invasively but the extent to which it represents metastatic heterogeneity is unknown. Here we follow a patient with metastatic ER-positive and HER2-positive breast cancer receiving two lines of targeted therapy over 3 years. We characterize genomic architecture and infer clonal evolution in eight tumour biopsies and nine plasma samples collected over 1,193 days of clinical follow-up using exome and targeted amplicon sequencing. Mutation levels in the plasma samples reflect the clonal hierarchy inferred from sequencing of tumour biopsies. Serial changes in circulating levels of sub-clonal private mutations correlate with different treatment responses between metastatic sites. This comparison of biopsy and plasma samples in a single patient with metastatic breast cancer shows that circulating tumour DNA can allow real-time sampling of multifocal clonal evolution.

High-throughput sequencing can be used to measure changes in tumor composition across space and time. Specifically, comparisons of pre- and post-treatment samples can reveal the underlying clonal dynamics and resistance mechanisms. Here, we discuss evidence for distinct modes of tumor evolution and their implications for therapeutic strategies. In addition, we consider the utility of spatial tissue sampling schemes, single-cell analysis, and circulating tumor DNA to track tumor evolution and the emergence of resistance, as well as approaches that seek to forestall resistance by targeting tumor evolution. Ultimately, characterization of the (epi)genomic, transcriptomic, and phenotypic changes that occur during tumor progression coupled with computational and mathematical modeling of tumor evolutionary dynamics may inform personalized treatment strategies.