Abstract PR06: Clonal evolution over narrow time frames via circulating tumor DNA in metastatic breast cancer
Authors: Zachary Weber, David Tallman, Sinclair Stockaard, Katharine Collier, Sarah Asad, Justin Rhoades, Samuel Freeman, Heather A. Parsons, Sara M. Tolaney, Gavin Ha, Viktor A. Adalsteinsson, Daniel G. Stover
Journal: Clinical Cancer Research (2020)

Abstract Introduction: Circulating tumor DNA (ctDNA) offers the ability to serially interrogate tumor genomic information, providing an opportunity for real-time monitoring of tumor genomic shifts. In this study, we deeply analyzed multiple ctDNA samples collected over narrow time frames (days-to-weeks) from seven patients with metastatic triple-negative breast cancer (mTNBC), a cancer type known to have high ctDNA content. Methods: Patients were enrolled in a clinical trial of the multikinase inhibitor cabozantinib, providing uniform and targeted treatment, and samples were collected at study entry, then every 21 to 42 days on study. ctDNA was extracted from each plasma sample and underwent ultra-low pass whole-genome sequencing (ULP-WGS; average depth 0.1x; n=42 samples), deep targeted panel sequencing of 402 cancer-related genes with unique molecular identifier indexing (depth 10,000x; n=42 samples), and samples with tumor fraction &amp;gt;10% underwent whole-exome sequencing (WES; depth 200x; n=31 samples), with germline sequencing of both targeted panel and WES for downstream analyses. SCNAs were identified from ULP-WGS and WES. PyClone with targeted panel sequencing data was employed for clonal evolution analyses. Predicted neoantigens were determined from WES. Results: 42 total plasma samples were analyzed (range 4-8 samples per patient) collected at narrow time intervals, ranging from 6 to 42 days (median 21 days) between samples. The median tumor fraction across all samples was 18.1% (range 2.5% to 44.3%). Tumor fraction/purity estimates were largely concordant when comparing orthogonal sequencing approaches (ULP-WGS, WES) and tumor fraction estimation algorithms (ichorCNA and FACETS, respectively). Of all samples, 31/42 (73.8%) had tumor fraction &amp;gt;10% and underwent WES; each patient had at least 3 samples that underwent WES. SCNAs were largely concordant between ULP-WGS and WES (all Cohen’s kappa &amp;gt;0.8). When comparing first and last available sample, there were not recurrent shifts in SCNAs. At lower tumor fractions, fewer mutations were detected, yet clonal alterations were consistently identified across multiple samples within patients. Through statistical modeling, we tracked distinct clonal populations for each patient and found diverse clonal architectures and dynamics through treatment. Additionally, several emergent somatic alterations were discovered at late time points, including alterations found in coding regions, proximal regulatory sites, and introns of key drug targets, underscoring the speed at which tumors can adapt to therapeutic agents. Conclusions: Analysis of serial ctDNA samples collected at narrow time intervals (days-to-weeks) provides unique insight into the dynamics of ctDNA as well as clonal evolution. We show that despite low tumor content, evolving genomic features of tumor populations can be identified while on treatment, potentially providing real-time insight for clinical decision-making. This abstract is also being presented as Poster A27. Citation Format: Zachary Weber, David Tallman, Sinclair Stockaard, Katharine Collier, Sarah Asad, Justin Rhoades, Samuel Freeman, Heather A. Parsons, Sara M. Tolaney, Gavin Ha, Viktor A. Adalsteinsson, Daniel G. Stover. Clonal evolution over narrow time frames via circulating tumor DNA in metastatic breast cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr PR06.