Abstract P4-06-02: Multi-parameter FACS sorting identifies higher mutational burden in aromatase inhibitor resistant subclones in estrogen positive breast cancer at diagnosis

Abstract

Abstract Background: In many cancers, intratumor heterogeneity is associated with poor outcomes and resistance to treatment but datasets and techniques to identify genomic differences between the resistant and sensitive subclones in primary tumors have been limited. Short-term presurgical treatment of estrogen positive (ER+) breast cancer with aromatase inhibitors (AIs) leads to marked reduction in proliferation in most tumours. However, some proliferating cells remain in most ER+ cancers after treatment and these cells may be responsible for the outgrowth of resistant clones. We provide data from a novel approach that may allow a better understanding of the molecular drivers of the de novo endocrine resistant cells that may underpin the eventual emergence of clinical resistance and allow early intervention to avoid this. Methods: Twenty-six FFPE ER+ breast cancer excision biopsies that showed partial Ki67 suppression after 2-weeks neoadjuvant AI treatment were studied. Single cell suspensions were obtained by enzymatic dispersion of 50-µm thick sections using a collagenase/dispase digestion method and were simultaneously stained for cytokeratin (Alexa Fluor 488), vimentin (Alexa Fluor 647), and DNA (DAPI). The stained suspensions were analysed using BD FACSAria II flow cytometer, and cytokeratin positive (epithelial) cells were separated from vimentin positive (stromal) cells by gating on a dot plot showing green (Alexa Fluor 488) versus far red (Alexa Fluor 647) fluorescence. Epithelial cells were further subdivided according to cell cycle into G0/G1 (mainly non-proliferating) and S/G2M (proliferating) populations using DNA histogram gating based on DAPI staining. Cells were sorted until ~90,000 cells or all cells if <90,000 were collected for each sub-population and DNA was extracted for whole exome sequencing. Consensus calls from multiple software packages were used to detect somatic mutations in epithelial cells using the vimentin positive cells as normal controls. Results: Twenty-six samples were FACS sorted into the 3 populations (non-proliferating and proliferating epithelial cells and stromal cells). Vimentin/stromal populations were almost all diploid and most epithelial populations were aneuploid. Two samples had more than 2 epithelial peaks suggesting multiple tumor subclones. The mean coverage for all samples was 52x and mean number of mutations per sorted sample was 418 (missense, nonsense, splicing, frame shift and non-stop mutations). Two samples had low coverage and were removed for further analysis, and in the remaining 24 FACS sorted samples, mean somatic mutational burden was significantly greater in proliferating cells compared to non-proliferation cells (mean 474 vs. 372, p=0.008 Wilcoxon signed rank test) with 5 tumors showing gross increases. There was no significant difference between the percent of the genome with copy number gains or losses between proliferating and non-proliferating cells. There were no individual genes that had significantly higher mutation rates in proliferating cells after correction for multiple testing. Conclusions: FACS sorting of neoadjuvant AI treated samples allows the separation of de novo AI-resistant from sensitive cell populations and revealed higher mutational burden in the AI resistant populations at the time of disease presentation. Interrogation of the mutational differences between the proliferative and non-proliferative cells may allow identification of putative drivers of resistance in individual tumours. Additional samples are under analysis to determine whether common drivers can be identified. Citation Format: Eugene F Schuster, Lila Zabalgo, Charles M Perou, Mitch Dowsett. Multi-parameter FACS sorting identifies higher mutational burden in aromatase inhibitor resistant subclones in estrogen positive breast cancer at diagnosis [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-06-02.