Abstract
Abstract Triple-negative breast cancer (TNBC) is an aggressive subtype that displays extensive intratumor heterogeneity and frequently (46%) develops resistance to neoadjuvant chemotherapy (NAC). Currently, the genomic basis of chemoresistance remains poorly understood. An important question is whether resistance to chemotherapy is driven by the selection of rare pre-existing subclones with genomic mutations and transcriptional programs that confer resistance to chemotherapy (adaptive resistance) or by the spontaneous induction of new mutations and expression changes that confer a resistant phenotype (acquired resistance). To investigate this question we applied single cell DNA and RNA sequencing methods and deep-exome sequencing to longitudinal time-point samples collected from a cohort of 20 TNBC patients. Deep-exome sequencing of the cohort at three time points revealed a random death model, wherein multiple clones were targeted, as opposed to the selection of specific somatic mutations. In contrast, single cell copy number profiling of ~800 cells from 8 patients identified an adaptive resistance model, wherein minor subclones from the pre-treatment tumors were selected and expanded in response to NAC. Similarly, single cell RNA sequencing of ~8000 cells from 8 patients identified subclones with chemoresistant phenotypes that were selected in response to NAC, resulting in the expansion of the resistant tumor mass. These data suggest that chemoresistance evolves through the selection of copy number changes and expression changes in signaling pathways associated with chemoresistance, rather than point mutations. This adaptive resistance model has important translational implications in clinical diagnostics, by suggesting that resistant clones can be detected in TNBC patients prior to the administration of chemotherapy. Citation Format: Charissa Kim, Ruli Gao, Emi Sei, Rachel Brandt, Nicola Crosetto, Theodoros Foukakis, Nicholas Navin. Adaptive resistance to chemotherapy in triple-negative breast cancer revealed by single cell DNA and RNA sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 418. doi:10.1158/1538-7445.AM2017-418
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