Abstract 1689: Comparative whole genome analyses of breast cancer aromatase inhibitor resistance models
Authors: Hoppe Reiner , Kandabarau Siarhei , Fan Ping , Jordan V. Craig , Cunliffe Heather , Brauch Hiltrud B. 
Published: August 2019

One third of breast cancer patients treated with Aromatase Inhibitors (AI) or Tamoxifen acquire resistance leading to disease recurrence and death. The clinically observed AI resistance is mimicked by in vitro models MCF-7:5C and MCF-7:2A that are susceptible to apoptosis upon E2-treatment. These models have been instrumental to the current understanding of underlying mechanisms such as the reconfiguration of survival signaling, alterations of stress-related pathways (Ariazi et al. 2011; Fan et al. 2013, 2015), and changes in miRNA expression profiles (Hoppe et al. 2016). How the model phenotypes relate to a specific genomic background is poorly understood. In order to identify somatic variants indicative of AI resistance and potentially useful as novel therapeutic targets we performed NGS analyses of the 5C and 2A clones compared to the non-resistant WS8 and MCF-7 (ATCC). Whole genome/exome libraries were sequenced on Illumina HiSeq/NovaSeq platforms, respectively. Previously we reported first results from a preliminary analysis of gains and losses of variants in both resistant derivatives (Hoppe at al. AACR 2018). Here we report an updated analysis of raw reads trimmed and aligned to GRCh38 reference using BWAkit v 0.7.15. Duplicates were removed by Picard MarkDuplicates. Base quality scores were recalibrated using GATK4 BQSR. WGS and WES alignments were merged and tested for somatic variants using GATK4 Mutect2 (Tumor-only mode) with population variation data from gnomAD as a germline source. Called and filtered variants were uploaded to IVA for functional and clinical annotation. Copy number segments were modeled using both read- and allele-counts from WGS alignments by Gaussian-kernel binary-segmentation algorithm applied in GATK4 ModelSegments tool. To interpret copy number events causative for LOH we recovered germline variants and annotated CNVs that led to loss of the corresponding wild-type allele. In line with the COSMIC database we confirmed 461 mutated loci of which 228 were lost in both resistant derivatives. Examples of 5C-specific coding mutations classified as pathogenic include splice site alterations (i.e. SEMA3A), frameshifts (i.e. ARID1A), and stop gains (i.e. CACNA1S, CDH2, NOTCH4). 2A-specific mutations include for example a stop gain affecting ADGRV1. Copy number variation analyses revealed that both resistance models share prominent genetic defects such as amplified regions at Chr6q25.1 and Chr21q22.2. A 5C-specific aberration is a large Chr18 deletion affecting most of the q-arm, and a 2A-specific aberration is the amplification of most parts of Chr6q23.3-q24.3. We will present the status of this currently ongoing comparative genome analysis of AI resistance models and discuss the putative effects of homozygous mutations at loci with copy number aberrations within the context of AI resistance.

Citation Format: Reiner Hoppe, Siarhei Kandabarau, Ping Fan, V. Craig Jordan, Heather Cunliffe, Hiltrud B. Brauch. Comparative whole genome analyses of breast cancer aromatase inhibitor resistance models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1689.