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      Single-cell DNA sequencing reveals a late-dissemination model in metastatic colorectal cancer

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          Abstract

          Metastasis is a complex biological process that has been difficult to delineate in human colorectal cancer (CRC) patients. A major obstacle in understanding metastatic lineages is the extensive intra-tumor heterogeneity at the primary and metastatic tumor sites. To address this problem, we developed a highly multiplexed single-cell DNA sequencing approach to trace the metastatic lineages of two CRC patients with matched liver metastases. Single-cell copy number or mutational profiling was performed, in addition to bulk exome and targeted deep-sequencing. In the first patient, we observed monoclonal seeding, in which a single clone evolved a large number of mutations prior to migrating to the liver to establish the metastatic tumor. In the second patient, we observed polyclonal seeding, in which two independent clones seeded the metastatic liver tumor after having diverged at different time points from the primary tumor lineage. The single-cell data also revealed an unexpected independent tumor lineage that did not metastasize, and early progenitor clones with the “first hit” mutation in APC that subsequently gave rise to both the primary and metastatic tumors. Collectively, these data reveal a late-dissemination model of metastasis in two CRC patients and provide an unprecedented view of metastasis at single-cell genomic resolution.

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          Most cited references51

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              Cytoscape: a software environment for integrated models of biomolecular interaction networks.

              Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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                Author and article information

                Journal
                Genome Res
                Genome Res
                genome
                genome
                GENOME
                Genome Research
                Cold Spring Harbor Laboratory Press
                1088-9051
                1549-5469
                August 2017
                : 27
                : 8
                : 1287-1299
                Affiliations
                [1 ]Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA;
                [2 ]The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, Texas 77030, USA;
                [3 ]Department of Pathology,
                [4 ]Department of Gastrointestinal Medical Oncology,
                [5 ]Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA
                Author notes
                [6]

                These authors contributed equally to this work.

                Corresponding author: nnavin@ 123456mdanderson.org
                Article
                9509184
                10.1101/gr.209973.116
                5538546
                28546418
                beaf2cb6-54d9-450b-984c-e7010698fae3
                © 2017 Leung et al.; Published by Cold Spring Harbor Laboratory Press

                This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 24 June 2016
                : 23 May 2017
                Page count
                Pages: 13
                Funding
                Funded by: MD Anderson Colon Cancer Moonshot project
                Funded by: Eric & Liz Lefkofsky Family Foundation
                Funded by: National Cancer Institute (NCI) , open-funder-registry 10.13039/100000054;
                Award ID: 1R01CA169244-01
                Funded by: American Cancer Society , open-funder-registry 10.13039/100000048;
                Award ID: 129098-RSG-16-092-01-TBG
                Funded by: Andrew Sabin Family Fellow
                Funded by: MD Anderson Cancer Moonshot Knowledge Gap Award and the Center for Genetics & Genomics
                Funded by: Research Training Award from the Cancer Prevention and Research Institute of Texas
                Award ID: CPRIT RP140106
                Funded by: American Legion Auxiliary (ALA) and Hearst Foundations
                Funded by: ALA
                Funded by: National Library of Medicine Training Program in Biomedical Informatics
                Award ID: 4T15LM007093-25
                Funded by: NCI , open-funder-registry 10.13039/100000054;
                Award ID: RO1CA184843
                Funded by: MD Anderson Sequencing Core Facility Grant
                Award ID: CA016672
                Funded by: Flow Cytometry Facility grant
                Funded by: NIH , open-funder-registry 10.13039/100000002;
                Award ID: CA016672
                Funded by: NCI…,” “N.E.N.” was substituted for “N.N.” , open-funder-registry 10.13039/100000054;
                Categories
                Research

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