Genomic instability is a hallmark of cancer often associated with poor patient outcome and resistance to targeted therapy. Assessment of genomic instability in bulk tumor or biopsy can be complicated due to sample availability, surrounding tissue contamination, or tumor heterogeneity. The Epic Sciences circulating tumor cell (CTC) platform utilizes a non-enrichment based approach for the detection and characterization of rare tumor cells in clinical blood samples. Genomic profiling of individual CTCs could provide a portrait of cancer heterogeneity, identify clonal and sub-clonal drivers, and monitor disease progression. To that end, we developed a single cell Copy Number Variation (CNV) Assay to evaluate genomic instability and CNVs in patient CTCs. For proof of concept, prostate cancer cell lines, LNCaP, PC3 and VCaP, were spiked into healthy donor blood to create mock patient-like samples for downstream single cell genomic analysis. In addition, samples from seven metastatic castration resistant prostate cancer (mCRPC) patients were included to evaluate clinical feasibility. CTCs were enumerated and characterized using the Epic Sciences CTC Platform. Identified single CTCs were recovered, whole genome amplified, and sequenced using an Illumina NextSeq 500. CTCs were then analyzed for genome-wide copy number variations, followed by genomic instability analyses. Large-scale state transitions (LSTs) were measured as surrogates of genomic instability. Genomic instability scores were determined reproducibly for LNCaP, PC3, and VCaP, and were higher than white blood cell (WBC) controls from healthy donors. A wide range of LST scores were observed within and among the seven mCRPC patient samples. On the gene level, loss of the PTEN tumor suppressor was observed in PC3 and 5/7 (71%) patients. Amplification of the androgen receptor (AR) gene was observed in VCaP cells and 5/7 (71%) mCRPC patients. Using an in silico down-sampling approach, we determined that DNA copy number and genomic instability can be detected with as few as 350K sequencing reads. The data shown here demonstrate the feasibility of detecting genomic instabilities at the single cell level using the Epic Sciences CTC Platform. Understanding CTC heterogeneity has great potential for patient stratification prior to treatment with targeted therapies and for monitoring disease evolution during treatment.
Background: Inter- and intra-patient tumor heterogeneity can have a drastic impact on the efficacy of targeted therapy without accurate patient stratification. Emerging literature suggests wide-spread prevalence of intra-tumor heterogeneity (ITH) across most major solid tumor types driven by separate subclonal genomic alterations, thus highlighting the need to understand the proportion of heterogeneous tumor subclonal populations with clinically relevant genomic alterations. Circulating tumor cells (CTCs) have been shown to reflect the active metastatic populations, and Epic Sciences' non-enrichment CTC analysis platform allows for single cell resolution and a more accurate estimate genomic heterogeneity within the population. Here, we demonstrate Epic Sciences CTC Platform capabilities to characterize individual CTCs from a simple blood draw for known markers of therapeutic sensitivity related to genome wide instability (PARP inhibitors, immune check-point inhibitor sensitivity), amplification or deletion of clinically relevant tumor suppressors or oncogenes (PI3K inhibitors or AR targeted therapy), and/or single nucleotide and INDEL variants (Tyrosine Kinase Inhibitor sensitivity). Methods: Healthy donor blood was spiked with well-characterized cancer cell lines to create mock test samples for downstream single-cell genomic analysis. CTCs were enumerated and characterized using the Epic Sciences Platform. Identified single CTCs were recovered, and their whole genome amplified and characterized for the presence of genome wide instability, specific tumor suppressor loss, and oncogene amplification or point mutations by whole genome sequencing and/or mutation specific PCR. Large-scale state transitions (LSTs) and percent genome alterations (PGAs) were measured as surrogates of genomic instability. Z-scores were calculated in specific genomic loci containing tumor suppressor or oncogenes to characterize their amplification or deletion. Results: In healthy donor blood spiked with prostate cancer cell lines (PC3, VCaP or LnCaP), overall genomic instability was observed across a wide dynamic range. Loss of the PTEN tumor suppressor, associated with sensitivity to PI3K inhibitors, was confirmed in PC3 cells. Amplification of the androgen receptor (AR), associated with resistance to AR targeted therapies, was confirmed in VCaP cells. In blood spiked with lung adenocarcinoma the T790M EGFR point mutation, associated with resistance to TKIs, was also detected reproducibly. Genomic profiling of CTCs from prostate cancer patients have shown significant intra-patient heterogeneity in copy number alterations, genomic instabilities and number of mutations. Conclusions: The data shown here demonstrate the feasibility of detecting actionable genomic alterations at the single cell level using the Epic CTC platform. Understanding CTC heterogeneity has great potential for more accurate patient stratification prior to treatment with targeted therapies. Citation Format: Stephanie Greene, Angel Rodriguez, Jerry Lee, Laura Leitz, Mark Landers, Adam Jendrisak, Ryon Graf, Shannon Werner, Yipeng Wang, Ryan Dittamore, Dena Marrinucci. Single cell genomic profiling of circulating tumor cells (CTCs) in metastatic disease to characterize disease heterogeneity. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr A34.
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