Abstract 2757: Using liquid biopsies and NGS as tools to analyze mutation burden and copy number variation in the blood of a patient with triple negative breast cancer to better inform therapeutic targets

The ability to characterize molecular features of cancer from liquid biopsies is resulting in the development of innovative health care for patients. Longitudinal changes in the mutational profiles of DNA isolated from liquid biopsies are being used to better understand and monitor the development, progression, and evolution of therapy resistance in cancer patients. To define changes in the mutational landscape and predict drug susceptibilities in Triple Negative Breast Cancer (TNBC) patients, we used whole exome analysis to profile circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) from eight selected time points of a patient enrolled in the Intensive Trial of OMics in Cancer clinical Trial (ITOMIC-001). The patient initially received weekly cisplatin infusions followed by additional targeted therapy. Peripheral blood samples were collected at specific time points over a period of 272 days following enrollment in the clinical trial. Our data indicates that the identified mutations in genomic DNA isolated from CTCs and ctDNA can be used to understand and mitigate the impact of tumor heterogeneity in addition to identifying clinically relevant mutations at these selected time points. To further increase the resolution of our analysis, we profiled ctDNA from these samples to a higher depth targeting only clinically relevant genes. These analyses increased the sensitivity of detection and identified additional targets that could have been used for therapeutic intervention. In addition to sequence variants, copy number variations (CNVs) have also been significantly associated with the development of metastasis and changes in CNVs have been used to monitor disease progression. We performed a bioinformatics analysis of genomic instability and CNVs across 32 different time points from ctDNA from the same patient throughout the treatment period. The genomic instability number (GIN) calculated for each of the 32 time points seems to mirror the overall CTC burden in the patient at each time point tested. CNV analysis is ongoing and these data sets are being further analyzed in combination with TCGA data to define possible cancer driver genes for the functional prediction of significant TNBC candidate alterations and the results of these analyses will be presented. Citation Format: Kellie Howard, Kimberly Kruse, Brianna Greenwood, Elliott Swanson, Mathias Ehrich, Christopher K. Ellison, Taylor Jensen, Sharon Austin, Arturo Ramirez, Debbie Boles, John Pruitt, Elisabeth Mahen, Jackie L. Stilwell, Eric P. Kaldjian, Michael Dorschner, Sibel Blau, Marcia Eisenberg, Steve Anderson, Anup Madan. Using liquid biopsies and NGS as tools to analyze mutation burden and copy number variation in the blood of a patient with triple negative breast cancer to better inform therapeutic targets [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 2757. doi:10.1158/1538-7445.AM2017-2757