BackgroundTo improve cancer therapy, it is critical to target metastasizing cells. Circulating tumor cells (CTCs) are rare cells found in the blood of patients with solid tumors and may play a key role in cancer dissemination. Uncovering CTC phenotypes offers a potential avenue to inform treatment. However, CTC transcriptional profiling is limited by leukocyte contamination; an approach to surmount this problem is single cell analysis. Here we demonstrate feasibility of performing high dimensional single CTC profiling, providing early insight into CTC heterogeneity and allowing comparisons to breast cancer cell lines widely used for drug discovery.Methodology/Principal FindingsWe purified CTCs using the MagSweeper, an immunomagnetic enrichment device that isolates live tumor cells from unfractionated blood. CTCs that met stringent criteria for further analysis were obtained from 70% (14/20) of primary and 70% (21/30) of metastatic breast cancer patients; none were captured from patients with non-epithelial cancer (n = 20) or healthy subjects (n = 25). Microfluidic-based single cell transcriptional profiling of 87 cancer-associated and reference genes showed heterogeneity among individual CTCs, separating them into two major subgroups, based on 31 highly expressed genes. In contrast, single cells from seven breast cancer cell lines were tightly clustered together by sample ID and ER status. CTC profiles were distinct from those of cancer cell lines, questioning the suitability of such lines for drug discovery efforts for late stage cancer therapy.Conclusions/SignificanceFor the first time, we directly measured high dimensional gene expression in individual CTCs without the common practice of pooling such cells. Elevated transcript levels of genes associated with metastasis NPTN, S100A4, S100A9, and with epithelial mesenchymal transition: VIM, TGFß1, ZEB2, FOXC1, CXCR4, were striking compared to cell lines. Our findings demonstrate that profiling CTCs on a cell-by-cell basis is possible and may facilitate the application of ‘liquid biopsies’ to better model drug discovery.

To analytically and clinically validate a circulating cell-free tumor DNA sequencing test for comprehensive tumor genotyping and demonstrate its clinical feasibility. Analytic validation was conducted according to established principles and guidelines. Blood-to-blood clinical validation comprised blinded external comparison with clinical droplet digital PCR across 222 consecutive biomarker-positive clinical samples. Blood-to-tissue clinical validation comprised comparison of digital sequencing calls to those documented in the medical record of 543 consecutive lung cancer patients. Clinical experience was reported from 10,593 consecutive clinical samples. Digital sequencing technology enabled variant detection down to 0.02% to 0.04% allelic fraction/2.12 copies with ≤0.3%/2.24-2.76 copies 95% limits of detection while maintaining high specificity [prevalence-adjusted positive predictive values (PPV) >98%]. Clinical validation using orthogonal plasma- and tissue-based clinical genotyping across >750 patients demonstrated high accuracy and specificity [positive percent agreement (PPAs) and negative percent agreement (NPAs) >99% and PPVs 92%-100%]. Clinical use in 10,593 advanced adult solid tumor patients demonstrated high feasibility (>99.6% technical success rate) and clinical sensitivity (85.9%), with high potential actionability (16.7% with FDA-approved on-label treatment options; 72.0% with treatment or trial recommendations), particularly in non-small cell lung cancer, where 34.5% of patient samples comprised a directly targetable standard-of-care biomarker. High concordance with orthogonal clinical plasma- and tissue-based genotyping methods supports the clinical accuracy of digital sequencing across all four types of targetable genomic alterations. Digital sequencing's clinical applicability is further supported by high rates of technical success and biomarker target discovery. .

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Running title: Somatic genomic landscape of circulating tumor DNA Keywords: circulating tumor DNA, tumor heterogeneity, resistance, genomic landscape, cfDNA clonality Financial support: The study was funded by and conducted at Guardant Health, Inc. No additional grant support or administrative support was provided for the study. *Corresponding author:Stephen R. Fairclough Translational relevanceThis study describes genomic alterations from the largest cell-free circulating tumor DNA cohort to date, as derived from regular clinical practice. The high prevalence of resistance alterations found in advanced, treated cancer patients necessitated accurate methods for determining mutation clonality and driver/resistance status from plasma. We provide such methods, thereby extending the utility of cell-free DNA sequencing analysis. Our finding of an association between estimated circulating tumor DNA (ctDNA) levels and tumor mutational burden ascertained from plasma suggests that ctDNA level is likely an important variable to consider for immunotherapy applications of ctDNA analysis. Although cell-free DNA can provide a summary of tumor heterogeneity across multiple metastatic sites in a patient, our findings of high variability in ctDNA levels across patients, and its impact on variant detection, highlight the need for an improved understanding of factors influencing ctDNA levels and safe methods for maximizing them at the time of ctDNA testing. AbstractPurpose: Cell-free DNA (cfDNA) sequencing provides a non-invasive method for obtaining actionable genomic information to guide personalized cancer treatment, but the presence of multiple alterations in circulation related to treatment and tumor heterogeneity complicate the interpretation of the observed variants.Experimental Design: We describe the somatic mutation landscape of 70 cancer genes from cfDNA deep-sequencing analysis of 21,807 patients with treated, late-stage cancers across >50 cancer types. To facilitate interpretation of the genomic complexity of circulating tumor DNA in advanced, treated cancer patients, we developed methods to identify cfDNA copy-number driver alterations and cfDNA clonality.Results: Patterns and prevalence of cfDNA alterations in major driver genes for non-small cell lung, breast, and colorectal cancer largely recapitulated those from tumor tissue sequencing compendia (TCGA and COSMIC;, with the principle differences in alteration prevalence being due to patient treatment. This highly sensitive cfDNA sequencing assay revealed numerous subclonal tumor-derived alterations, expected as a result of clonal evolution, but leading to an apparent departure from mutual exclusivity in treatment-naïve tumors. Upon applying novel cfDNA clonality and copy-number driver identification methods, robust mutual exclusivity was observed among predicted truncal driver cfDNA alterations (FDR=5x10 -7 for EGFR and ERBB2), in effect distinguishing tumor-initiating alterations from secondary alterations. Treatment-associated resistance, including both novel ...