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

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      Nature Communications
      Nature Publishing Group UK

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          Abstract

          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.

          Abstract

          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.

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          Most cited references14

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          A faster circular binary segmentation algorithm for the analysis of array CGH data.

          Array CGH technologies enable the simultaneous measurement of DNA copy number for thousands of sites on a genome. We developed the circular binary segmentation (CBS) algorithm to divide the genome into regions of equal copy number. The algorithm tests for change-points using a maximal t-statistic with a permutation reference distribution to obtain the corresponding P-value. The number of computations required for the maximal test statistic is O(N2), where N is the number of markers. This makes the full permutation approach computationally prohibitive for the newer arrays that contain tens of thousands markers and highlights the need for a faster algorithm. We present a hybrid approach to obtain the P-value of the test statistic in linear time. We also introduce a rule for stopping early when there is strong evidence for the presence of a change. We show through simulations that the hybrid approach provides a substantial gain in speed with only a negligible loss in accuracy and that the stopping rule further increases speed. We also present the analyses of array CGH data from breast cancer cell lines to show the impact of the new approaches on the analysis of real data. An R version of the CBS algorithm has been implemented in the "DNAcopy" package of the Bioconductor project. The proposed hybrid method for the P-value is available in version 1.2.1 or higher and the stopping rule for declaring a change early is available in version 1.5.1 or higher.
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            Oncotator: cancer variant annotation tool.

            Oncotator is a tool for annotating genomic point mutations and short nucleotide insertions/deletions (indels) with variant- and gene-centric information relevant to cancer researchers. This information is drawn from 14 different publicly available resources that have been pooled and indexed, and we provide an extensible framework to add additional data sources. Annotations linked to variants range from basic information, such as gene names and functional classification (e.g. missense), to cancer-specific data from resources such as the Catalogue of Somatic Mutations in Cancer (COSMIC), the Cancer Gene Census, and The Cancer Genome Atlas (TCGA). For local use, Oncotator is freely available as a python module hosted on Github (https://github.com/broadinstitute/oncotator). Furthermore, Oncotator is also available as a web service and web application at http://www.broadinstitute.org/oncotator/.
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              Whole exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer

              Comprehensive analyses of cancer genomes promise to inform prognoses and precise cancer treatments. A major barrier, however, is inaccessibility of metastatic tissue. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming the challenges of isolating rare cells and sequencing low-input material. Here we report an integrated process to isolate, qualify and sequence whole exomes of CTCs with high fidelity, using a census-based sequencing strategy. Power calculations suggest that mapping of >99.995% of the standard exome is possible in CTCs. We validated our process in two prostate cancer patients including one for whom we sequenced CTCs, a lymph node metastasis and nine cores of the primary tumor. Fifty-one of 73 CTC mutations (70%) were observed in matched tissue. Moreover, we identified 10 early-trunk and 56 metastatic-trunk mutations in the non-CTC tumor samples and found 90% and 73% of these, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic.
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                Author and article information

                Contributors
                viktor@broadinstitute.org
                gadgetz@broadinstitute.org
                clove@mit.edu
                matthew_meyerson@dfci.harvard.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                6 November 2017
                6 November 2017
                2017
                : 8
                : 1324
                Affiliations
                [1 ]GRID grid.66859.34, Eli and Edythe L. Broad Institute of MIT and Harvard, ; 415 Main Street, Cambridge, 02142 MA USA
                [2 ]ISNI 0000 0001 2341 2786, GRID grid.116068.8, Koch Institute for Integrative Cancer Research, , Massachusetts Institute of Technology, ; 500 Main Street, Cambridge, 02142 MA USA
                [3 ]ISNI 0000 0001 2106 9910, GRID grid.65499.37, Dana-Farber Cancer Institute, ; 450 Brookline Avenue, Boston, 02215 MA USA
                [4 ]ISNI 000000041936754X, GRID grid.38142.3c, Harvard Medical School, ; 250 Longwood Avenue, Boston, 02115 MA USA
                [5 ]ISNI 0000 0004 0386 9924, GRID grid.32224.35, Massachusetts General Hospital, ; 55 Fruit Street, Boston, 02129 MA USA
                [6 ]ISNI 0000 0004 0378 8294, GRID grid.62560.37, Brigham and Women’s Hospital, ; 75 Francis Street, Boston, 02115 MA USA
                [7 ]ISNI 0000 0001 2167 1581, GRID grid.413575.1, Howard Hughes Medical Institute, ; 4000 Jones Bridge Road, Chevy Chase, 20815 MD USA
                Author information
                http://orcid.org/0000-0001-9003-8165
                http://orcid.org/0000-0003-2528-1446
                http://orcid.org/0000-0001-8942-9265
                http://orcid.org/0000-0002-5732-3471
                http://orcid.org/0000-0002-2153-4488
                http://orcid.org/0000-0003-0113-2403
                http://orcid.org/0000-0002-6795-6336
                http://orcid.org/0000-0002-0936-0753
                http://orcid.org/0000-0002-9133-8108
                Article
                965
                10.1038/s41467-017-00965-y
                5673918
                29109393
                1ba757a7-9a4a-40d8-a87f-ce58084516dc
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 14 March 2017
                : 9 August 2017
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