Justin Rhoades

Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors

Whole-exome sequencing of cell-free DNA (cfDNA) could enable comprehensive profiling of tumors from blood but the genome-wide concordance between cfDNA and tumor biopsies is uncertain. Here we report ichorCNA, software that quantifies tumor content in cfDNA from 0.1× coverage whole-genome sequencing data without prior knowledge of tumor mutations. We apply ichorCNA to 1439 blood samples from 520 patients with metastatic prostate or breast cancers. In the earliest tested sample for each patient, 34% of patients have ≥10% tumor-derived cfDNA, sufficient for standard coverage whole-exome sequencing. Using whole-exome sequencing, we validate the concordance of clonal somatic mutations (88%), copy number alterations (80%), mutational signatures, and neoantigens between cfDNA and matched tumor biopsies from 41 patients with ≥10% cfDNA tumor content. In summary, we provide methods to identify patients eligible for comprehensive cfDNA profiling, revealing its applicability to many patients, and demonstrate high concordance of cfDNA and metastatic tumor whole-exome sequencing.Identifying the mutational landscape of tumours from cell-free DNA in the blood could help diagnostics in cancer. Here, the authors present ichorCNA, software that quantifies tumour content in cell free DNA, and they demonstrate that cell-free DNA whole-exome sequencing is concordant with metastatic tumour whole-exome sequencing.

Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma

Gastroesophageal adenocarcinoma (GEA) is a lethal disease where targeted therapies, even when guided by genomic biomarkers, have had limited efficacy. A potential reason for the failure of such therapies is that genomic profiling results could commonly differ between the primary and metastatic tumors. To evaluate genomic heterogeneity, we sequenced paired primary GEA and synchronous metastatic lesions across multiple cohorts, finding extensive differences in genomic alterations, including discrepancies in potentially clinically relevant alterations. Multiregion sequencing showed significant discrepancy within the primary tumor (PT) and between the PT and disseminated disease, with oncogene amplification profiles commonly discordant. In addition, a pilot analysis of cell-free DNA (cfDNA) sequencing demonstrated the feasibility of detecting genomic amplifications not detected in PT sampling. Lastly, we profiled paired primary tumors, metastatic tumors, and cfDNA from patients enrolled in the personalized antibodies for GEA (PANGEA) trial of targeted therapies in GEA and found that genomic biomarkers were recurrently discrepant between the PT and untreated metastases. Divergent primary and metastatic tissue profiling led to treatment reassignment in 32% (9/28) of patients. In discordant primary and metastatic lesions, we found 87.5% concordance for targetable alterations in metastatic tissue and cfDNA, suggesting the potential for cfDNA profiling to enhance selection of therapy.Significance: We demonstrate frequent baseline heterogeneity in targetable genomic alterations in GEA, indicating that current tissue sampling practices for biomarker testing do not effectively guide precision medicine in this disease and that routine profiling of metastatic lesions and/or cfDNA should be systematically evaluated. Cancer Discov; 8(1); 37-48. ©2017 AACR.See related commentary by Sundar and Tan, p. 14See related article by Janjigian et al., p. 49This article is highlighted in the In This Issue feature, p. 1.

Structural Alterations Driving Castration-Resistant Prostate Cancer Revealed by Linked-Read Genome Sequencing

Nearly all prostate cancer deaths are from metastatic castration-resistant prostate cancer (mCRPC), but there have been few whole-genome sequencing (WGS) studies of this disease state. We performed linked-read WGS on 23 mCRPC biopsy specimens and analyzed cell-free DNA sequencing data from 86 patients with mCRPC. In addition to frequent rearrangements affecting known prostate cancer genes, we observed complex rearrangements of the AR locus in most cases. Unexpectedly, these rearrangements include highly recurrent tandem duplications involving an upstream enhancer of AR in 70%-87% of cases compared with <2% of primary prostate cancers. A subset of cases displayed AR or MYC enhancer duplication in the context of a genome-wide tandem duplicator phenotype associated with CDK12 inactivation. Our findings highlight the complex genomic structure of mCRPC, nominate alterations that may inform prostate cancer treatment, and suggest that additional recurrent events in the non-coding mCRPC genome remain to be discovered.

Whole-exome sequencing of cell-free DNA and circulating tumor cells in multiple myeloma

Liquid biopsies including circulating tumor cells (CTCs) and cell-free DNA (cfDNA) have enabled minimally invasive characterization of many cancers, but are rarely analyzed together. Understanding the detectability and genomic concordance of CTCs and cfDNA may inform their use in guiding cancer precision medicine. Here, we report the detectability of cfDNA and CTCs in blood samples from 107 and 56 patients with multiple myeloma (MM), respectively. Using ultra-low pass whole-genome sequencing, we find both tumor fractions correlate with disease progression. Applying whole-exome sequencing (WES) to cfDNA, CTCs, and matched tumor biopsies, we find concordance in clonal somatic mutations (~99%) and copy number alterations (~81%) between liquid and tumor biopsies. Importantly, analyzing CTCs and cfDNA together enables cross-validation of mutations, uncovers mutations exclusive to either CTCs or cfDNA, and allows blood-based tumor profiling in a greater fraction of patients. Our study demonstrates the utility of analyzing both CTCs and cfDNA in MM.Circulating tumor cells (CTCs) and cell-free DNA (cfDNA) enables characterization of a patient’s cancer. Here, the authors analyse CTCs, cfDNA, and tumor biopsies from multiple myeloma patients to show these approaches are complementary for mutation detection, together enabling a greater fraction of patient tumors to be profiled.

Abstract 5689: Identify tissue-of-origin in cancer cfDNA by whole genome sequencing

Cell free DNA (cfDNA) has been shown to be an emerging non-invasive biomarker to monitor tumor progression in cancer patients. Elevated cfDNA has been found not only from tumors, but also from normal tissues. Thus, the identification of cfDNA’s tissue-of-origin is critical to understand the mechanism of cfDNA release and tumor progression. Recent efforts to identify cfDNA’s tissue-of-origin begin to utilize cfDNA’s epigenomic status, such as DNA methylation and nucleosome spacing. However, both of these methods have limitations: (1) For nucleosome positioning, lack of reference nucleosome maps in different tumor and normal tissues has limited its application to tissue-of-origin deconvolution; (2) For DNA methylation, large DNA degradation during whole genome bisulfite sequencing (WGBS) library preparation, even with current low-input DNA technology, is still the major hurdle for its clinical application, although extensive DNA methylation studies by WGBS in tumor and normal tissues during the last decade have provided many reference maps. Very recently, a pioneer study showed significant differences between DNA fragment lengths of methylated and unmethylated cfDNA. Taking advantage of this experimental observation, we developed a machine learning approach to infer the base pair resolution DNA methylation level from fragment size information in whole genome sequencing (WGS). The predicted DNA methylation, from not only high coverage but also dozens of ultra-low-pass WGS (ULP-WGS), showed high concordance with the ground truth DNA methylation level from WGBS in the same cancer patients. Furthermore, by using hundreds of WGBS datasets from different tumor and normal tissues/cells as the reference map, we deconvoluted cfDNA’s tissue-of-origin status by inferred DNA methylation level at ULP-WGS from thousands of breast/prostate cancer samples and healthy individuals. The cfDNA’s tissue-of-origin status in cancer patients showed high concordance with confirmed metastasis tissues from physicians. Interestingly, some clinical information, such as cancer grades/stages, seemed to be correlated with cfDNA’s tissue-of-origin status. Overall, our methods here pave the road for cfDNA’s application in clinical diagnosis and monitoring. Citation Format: Yaping Liu, Sarah Reed, Atish D. Choudhury, Heather A. Parsons, Daniel G. Stover, Gavin Ha, Gregory Gydush, Justin Rhoades, Denisse Rotem, Samuel Freeman, Viktor Adalsteinsson, Manolis Kellis. Identify tissue-of-origin in cancer cfDNA by whole genome sequencing [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 5689. doi:10.1158/1538-7445.AM2017-5689