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      Mutation, methylation, and gene expression profiles in dup(1q)-positive pediatric B-cell precursor acute lymphoblastic leukemia

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          Abstract

          High-throughput sequencing was applied to investigate the mutation/methylation patterns on 1q and gene expression profiles in pediatric B-cell precursor acute lymphoblastic leukemia (BCP ALL) with/without (w/wo) dup(1q). Sequencing of the breakpoint regions and all exons on 1q in seven dup(1q)-positive cases revealed non-synonymous somatic single nucleotide variants (SNVs) in BLZF1, FMN2, KCNT2, LCE1C, NES, and PARP1. Deep sequencing of these in a validation cohort w ( n = 17)/wo ( n = 94) dup(1q) revealed similar SNV frequencies in the two groups (47% vs. 35%; P = 0.42). Only 0.6% of the 36,259 CpGs on 1q were differentially methylated between cases w ( n = 14)/wo ( n = 13) dup(1q). RNA sequencing of high hyperdiploid (HeH) and t(1;19)(q23;p13)-positive cases w ( n = 14)/wo ( n = 52) dup(1q) identified 252 and 424 differentially expressed genes, respectively; only seven overlapped. Of the overexpressed genes in the HeH and t(1;19) groups, 23 and 31%, respectively, mapped to 1q; 60-80% of these encode nucleic acid/protein binding factors or proteins with catalytic activity. We conclude that the pathogenetically important consequence of dup(1q) in BCP ALL is a gene-dosage effect, with the deregulated genes differing between genetic subtypes, but involving similar molecular functions, biological processes, and protein classes.

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          Chromosome-wide and promoter-specific analyses identify sites of differential DNA methylation in normal and transformed human cells.

          Cytosine methylation is required for mammalian development and is often perturbed in human cancer. To determine how this epigenetic modification is distributed in the genomes of primary and transformed cells, we used an immunocapturing approach followed by DNA microarray analysis to generate methylation profiles of all human chromosomes at 80-kb resolution and for a large set of CpG islands. In primary cells we identified broad genomic regions of differential methylation with higher levels in gene-rich neighborhoods. Female and male cells had indistinguishable profiles for autosomes but differences on the X chromosome. The inactive X chromosome (Xi) was hypermethylated at only a subset of gene-rich regions and, unexpectedly, overall hypomethylated relative to its active counterpart. The chromosomal methylation profile of transformed cells was similar to that of primary cells. Nevertheless, we detected large genomic segments with hypomethylation in the transformed cell residing in gene-poor areas. Furthermore, analysis of 6,000 CpG islands showed that only a small set of promoters was methylated differentially, suggesting that aberrant methylation of CpG island promoters in malignancy might be less frequent than previously hypothesized.
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            Identification of ETV6-RUNX1-like and DUX4-rearranged subtypes in paediatric B-cell precursor acute lymphoblastic leukaemia

            Fusion genes are potent driver mutations in cancer. In this study, we delineate the fusion gene landscape in a consecutive series of 195 paediatric B-cell precursor acute lymphoblastic leukaemia (BCP ALL). Using RNA sequencing, we find in-frame fusion genes in 127 (65%) cases, including 27 novel fusions. We describe a subtype characterized by recurrent IGH-DUX4 or ERG-DUX4 fusions, representing 4% of cases, leading to overexpression of DUX4 and frequently co-occurring with intragenic ERG deletions. Furthermore, we identify a subtype characterized by an ETV6-RUNX1-like gene-expression profile and coexisting ETV6 and IKZF1 alterations. Thus, this study provides a detailed overview of fusion genes in paediatric BCP ALL and adds new pathogenetic insights, which may improve risk stratification and provide therapeutic options for this disease.
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              DNA hypomethylation and ovarian cancer biology.

              Hypomethylation of some portions of the genome and hypermethylation of others are very frequent in human cancer. The hypomethylation often involves satellite 2 (Sat2) DNA in the juxtacentromeric (centromere-adjacent) region of chromosome 1. In this study, we analyzed methylation in centromeric and juxtacentromeric satellite DNA in 115 ovarian cancers, 26 non-neoplastic ovarian specimens, and various normal somatic tissue standards. We found that hypomethylation of both types of satellite DNA in ovarian samples increased significantly from non-neoplastic toward cancer tissue. Furthermore, strong hypomethylation was significantly more prevalent in tumors of advanced stage or high grade. Importantly, extensive hypomethylation of Sat2 DNA in chromosome 1 was a highly significant marker of poor prognosis (relative risk for relapse, 4.1, and death, 9.4) and more informative than tumor grade or stage. Also, comparing methylation of satellite DNA and 15 5' gene regions, which are often hypermethylated in cancer or implicated in ovarian carcinogenesis, we generally found no positive or negative association between methylation changes in satellite DNA and in the gene regions. However, hypermethylation at two loci, CDH13 (at 16q24) and RNR1 (at 13p12), was correlated strongly with lower levels of Sat2 hypomethylation. The CDH13/Sat2 epigenetic correlation was seen also in breast cancers. We conclude that satellite DNA hypomethylation is an important issue in ovarian carcinogenesis as demonstrated by: (a) an increase from non-neoplastic tissue toward ovarian cancer; (b) an increase within the ovarian cancer group toward advanced grade and stage; and (c) the finding that strong hypomethylation was an independent marker of poor prognosis.
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                Author and article information

                Contributors
                +46 46 2229400 , rebeqa.gunnarsson@med.lu.se
                Journal
                Leukemia
                Leukemia
                Leukemia
                Nature Publishing Group UK (London )
                0887-6924
                1476-5551
                12 March 2018
                12 March 2018
                2018
                : 32
                : 10
                : 2117-2125
                Affiliations
                [1 ]ISNI 0000 0001 0930 2361, GRID grid.4514.4, Division of Clinical Genetics, Department of Laboratory Medicine, , Lund University, ; Lund, Sweden
                [2 ]ISNI 0000 0004 1936 9457, GRID grid.8993.b, Array and Analysis Facility, Department of Medical Sciences, , Uppsala University, ; Uppsala, Sweden
                [3 ]ISNI 0000 0004 1936 9457, GRID grid.8993.b, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, , Uppsala University, ; Uppsala, Sweden
                [4 ]ISNI 0000 0001 0930 2361, GRID grid.4514.4, Department of Clinical Genetics and Pathology, , Division of Laboratory Medicine, ; Lund, Sweden
                [5 ]ISNI 0000 0004 1936 9457, GRID grid.8993.b, Department of Medical Sciences, Molecular Medicine and Science for Life Laboratory, , Uppsala University, ; Uppsala, Sweden
                [6 ]ISNI 0000 0004 0623 9987, GRID grid.411843.b, Department of Pediatrics, , Skåne University Hospital, ; Lund, Sweden
                [7 ]ISNI 0000 0000 9309 6304, GRID grid.411384.b, Department of Pediatrics, , Linköping University Hospital, ; Linköping, Sweden
                Author information
                http://orcid.org/0000-0001-8703-1173
                http://orcid.org/0000-0001-7950-222X
                http://orcid.org/0000-0001-6576-7825
                Article
                92
                10.1038/s41375-018-0092-2
                6170391
                29626196
                77e6dbc6-bfa4-49c5-bc44-291fda11f647
                © 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
                : 1 December 2017
                : 19 January 2018
                : 1 February 2018
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                © Springer Nature Limited 2018

                Oncology & Radiotherapy
                Oncology & Radiotherapy

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