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      Single-cell sequencing reveals the origin and the order of mutation acquisition in T-cell acute lymphoblastic leukemia

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          Abstract

          Next-generation sequencing has provided a detailed overview of the various genomic lesions implicated in the pathogenesis of T-cell acute lymphoblastic leukemia (T-ALL). Typically, 10–20 protein-altering lesions are found in T-ALL cells at diagnosis. However, it is currently unclear in which order these mutations are acquired and in which progenitor cells this is initiated. To address these questions, we used targeted single-cell sequencing of total bone marrow cells and CD34 +CD38 multipotent progenitor cells for four T-ALL cases. Hierarchical clustering detected a dominant leukemia cluster at diagnosis, accompanied by a few smaller clusters harboring only a fraction of the mutations. We developed a graph-based algorithm to determine the order of mutation acquisition. Two of the four patients had an early event in a known oncogene ( MED12, STAT5B) among various pre-leukemic events. Intermediate events included loss of 9p21 ( CDKN2A/B) and acquisition of fusion genes, while NOTCH1 mutations were typically late events. Analysis of CD34 +CD38 cells and myeloid progenitors revealed that in half of the cases somatic mutations were detectable in multipotent progenitor cells. We demonstrate that targeted single-cell sequencing can elucidate the order of mutation acquisition in T-ALL and that T-ALL development can start in a multipotent progenitor cell.

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          Quantitative single-cell RNA-seq with unique molecular identifiers.

          Single-cell RNA sequencing (RNA-seq) is a powerful tool to reveal cellular heterogeneity, discover new cell types and characterize tumor microevolution. However, losses in cDNA synthesis and bias in cDNA amplification lead to severe quantitative errors. We show that molecular labels--random sequences that label individual molecules--can nearly eliminate amplification noise, and that microfluidic sample preparation and optimized reagents produce a fivefold improvement in mRNA capture efficiency.
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            THE GENOMIC LANDSCAPE OF PEDIATRIC AND YOUNG ADULT T-LINEAGE ACUTE LYMPHOBLASTIC LEUKEMIA

            Genetic alterations activating NOTCH1 signaling and T cell transcription factors, coupled with inactivation of the INK4/ARF tumor suppressors are hallmarks of T-ALL, but detailed genome-wide sequencing of large T-ALL cohorts has not been performed. Using integrated genomic analysis of 264 T-ALL cases, we identify 106 putative driver genes, half of which were not previously described in childhood T-ALL (e.g. CCND3, CTCF, MYB, SMARCA4, ZFP36L2 and MYCN). We described new mechanisms of coding and non-coding alteration, and identify 10 recurrently altered pathways, with associations between mutated genes and pathways, and stage or subtype of T-ALL. For example, NRAS/FLT3 mutations were associated with immature T-ALL, JAK3/STAT5B mutations in HOX1 deregulated ALL, PTPN2 mutations in TLX1 T-ALL, and PIK3R1/PTEN mutations in TAL1 ALL, suggesting that different signaling pathways have distinct roles according to maturational stage. This genomic landscape provides a logical framework for the development of faithful genetic models and new therapeutic approaches.
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              Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor.

              Clear cell renal cell carcinoma (ccRCC) is the most common kidney cancer and has very few mutations that are shared between different patients. To better understand the intratumoral genetics underlying mutations of ccRCC, we carried out single-cell exome sequencing on a ccRCC tumor and its adjacent kidney tissue. Our data indicate that this tumor was unlikely to have resulted from mutations in VHL and PBRM1. Quantitative population genetic analysis indicates that the tumor did not contain any significant clonal subpopulations and also showed that mutations that had different allele frequencies within the population also had different mutation spectrums. Analyses of these data allowed us to delineate a detailed intratumoral genetic landscape at a single-cell level. Our pilot study demonstrates that ccRCC may be more genetically complex than previously thought and provides information that can lead to new ways to investigate individual tumors, with the aim of developing more effective cellular targeted therapies. Copyright © 2012 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                +32 16330082 , jan.cools@kuleuven.vib.be
                Journal
                Leukemia
                Leukemia
                Leukemia
                Nature Publishing Group UK (London )
                0887-6924
                1476-5551
                18 April 2018
                18 April 2018
                2018
                : 32
                : 6
                : 1358-1369
                Affiliations
                [1 ]ISNI 0000 0001 0668 7884, GRID grid.5596.f, Center for Human Genetics, , KU Leuven, ; Leuven, Belgium
                [2 ]ISNI 0000 0001 0668 7884, GRID grid.5596.f, Center for Cancer Biology, , VIB, ; Leuven, Belgium
                [3 ]ISNI 0000 0001 0668 7884, GRID grid.5596.f, Leuvens Kanker Instituut (LKI), , KU Leuven – UZ Leuven, ; Leuven, Belgium
                [4 ]ISNI 0000 0004 0626 3338, GRID grid.410569.f, Department of Pediatric Hemato-Oncology, , UZ Leuven, ; Leuven, Belgium
                [5 ]ISNI 0000 0004 0626 3338, GRID grid.410569.f, Department of Hematology, , UZ Leuven, ; Leuven, Belgium
                [6 ]ISNI 0000 0004 0606 5382, GRID grid.10306.34, Wellcome Trust Sanger Institute, ; Hinxton Cambridge, UK
                [7 ]ISNI 0000 0001 0668 7884, GRID grid.5596.f, Department of Oncology, , KU Leuven, ; Leuven, Belgium
                [8 ]ISNI 0000 0004 0626 3338, GRID grid.410569.f, Department of Laboratory Medicine, , UZ Leuven, ; Leuven, Belgium
                Author information
                http://orcid.org/0000-0002-4168-060X
                http://orcid.org/0000-0003-4719-1935
                http://orcid.org/0000-0001-6626-5843
                Article
                127
                10.1038/s41375-018-0127-8
                5990522
                29740158
                14fa1e81-8986-4ab8-acf9-fe550e77e0af
                © The Author(s) 2018

                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
                : 9 November 2017
                : 28 February 2018
                : 21 March 2018
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                © Macmillan Publishers Limited, part of Springer Nature 2018

                Oncology & Radiotherapy
                Oncology & Radiotherapy

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