Abstract
Abstract Background: Current tissue-based genomic sequencing datasets typically reflect early stage, mostly treatment-naïve cohorts, and fail to capture the genomic landscape of advanced disease, including mutations conferring acquired resistance to therapy. Plasma cell-free DNA (cfDNA) can provide information on somatic alterations non-invasively and can capture spatial tumor heterogeneity. Here, we studied cfDNA from 15,564 blood samples from 12, 827 patients (11.5% of patients had serial samples) with MBC, and analyzed the differences in mutational landscape between cohorts of heavily pre-treated and primary untreated breast cancers. Materials and methods: Deidentified aggregate genomic data from stage III/IV breast cancer clinical samples submitted for cfDNA next-generation sequencing (NGS) analysis with Guardant360 (Guardant Health, Inc; Redwood City, CA, USA) assay between 11/25/16 and 5/26/20. This clinical assay detects somatic single nucleotide variants (SNVs), indels, copy number gains, and fusions in either all or a subset of exons in up to 74 genes. We compare the observed alterations to events detected from whole-exome sequencing data representing ~1,000 untreated primary breast cancers from The Cancer Genome Atlas (TCGA) project. Results: In the overall cohort (N = 12, 827), the average patient age was 61 (range 18-100); 99% were female. Of the 11,290 pts with at least one samples with a non-synonymous alteration, the most frequently mutated genes were TP53 (53%), PIK3CA (38%), ESR1 (28%), ATM (13%), GATA3 (10%), and ARID1A (10%) at varying allelic frequencies with dynamic changes over time (in pts with serial specimens) highlighting clonal heterogeneity and temporal evolution. Copy-number gains were most frequent in FGFR1 (13%), CCND1 (11%), EGFR (9%) and PIK3CA (9%), but fusions were infrequent (below 1%), with fusions involving FGFR3 (n=22), FGFR2 (n=12), ALK (n=7), NTRK1 (n=6), RET (n=4), and ROS1 (n=1). Overall, patients had significantly higher frequency of actionable alterations based on ctDNA analysis, as compared to that observed in TCGA. Similarly, non-synonymous mutations were identified in genes associated with acquired resistance, including ESR1 (28%), ERBB2 (9%), PTEN (8.1%), RB1 (7.7%), NF1 (6.2%), and AKT1 (4%), mutated at frequencies significantly exceeding those observed in TCGA. Finally, we developed a novel classifier to identify the breast cancer receptor subtypes based on differential genomic profile, which was further validated in an independent genomic dataset. Conclusions: In the largest dataset to date, we provide the comparative genomic landscape of the various SNVs, indels, copy-number gains, and fusions identified by next generation sequencing of cfDNA in patients with MBC, compared to primary breast cancer. Interestingly, both targetable genomic alterations and resistance mutations occur at frequencies much higher than observed in primary breast cancer, highlighting the genomic complexity of MBC and potential need for combinatorial therapy. Finally, we describe a novel classifier for detection of HR+ and HER2+ tumors, which could be particularly valuable clinically given the receptor switch with tumor evolution and practical difficulty with serial tissue biopsies in MBC. Comparison of genomic signature profiles between MBC and primary breast cancer will be presented at the meeting. Citation Format: Aditya Bardia, Massimo Cristofanilli, Justin Cha, Lesli Kiedrowski, Dejan Juric, Ben H Park, Adam Brufsky, Joyce O’Shaughnessy, Becky Nagy, Leif Ellisen, Ignaty Leshchiner, Gaddy Getz. Genomic landscape of metastatic breast cancer (MBC): Comprehensive cell-free DNA analysis from over 10,000 patients and comparison with primary breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD9-07.
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