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Research Article

Global Measures of Peripheral Blood-Derived DNA Methylation as a Risk Factor in the Development of Mature B-Cell Neoplasms

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Pages 55-66 | Received 17 May 2015, Accepted 25 Sep 2015, Published online: 18 Dec 2015

References

  • Swerdlow S , SwerdlowE , HarrisNet al. WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues . IARC , Lyon, France ( 2008 ).
  • SEER Cancer Statistics Review, 1975–2012, National Cancer Institute . http://seer.Cancer.Gov/csr/1975_2012/ .
  • Yuille MR , MatutesE , MarossyA , HilditchB , CatovskyD , HoulstonRS . Familial chronic lymphocytic leukaemia: a survey and review of published studies . Br. J. Haematol.109 ( 4 ), 794 – 799 ( 2000 ).
  • Goldin LR , PfeifferRM , LiX , HemminkiK . Familial risk of lymphoproliferative tumors in families of patients with chronic lymphocytic leukemia: results from the Swedish family-cancer database . Blood104 ( 6 ), 1850 – 1854 ( 2004 ).
  • Landgren O , KristinssonSY , GoldinLRet al. Risk of plasma cell and lymphoproliferative disorders among 14621 first-degree relatives of 4458 patients with monoclonal gammopathy of undetermined significance in sweden . Blood114 ( 4 ), 791 – 795 ( 2009 ).
  • Herman JG , BaylinSB . Gene silencing in cancer in association with promoter hypermethylation . N. Engl. J. Med.349 ( 21 ), 2042 – 2054 ( 2003 ).
  • Martín-Subero JI , KreuzM , BibikovaMet al. New insights into the biology and origin of mature aggressive B-cell lymphomas by combined epigenomic, genomic, and transcriptional profiling . Blood113 ( 11 ), 2488 – 2497 ( 2009 ).
  • Walker BA , WardellCP , ChiecchioLet al. Aberrant global methylation patterns affect the molecular pathogenesis and prognosis of multiple myeloma . Blood117 ( 2 ), 553 – 562 ( 2011 ).
  • Kanduri M , CahillN , GoranssonHet al. Differential genome-wide array-based methylation profiles in prognostic subsets of chronic lymphocytic leukemia . Blood115 ( 2 ), 296 – 305 ( 2010 ).
  • Salhia B , BakerA , AhmannG , AuclairD , FonsecaR , CarptenJ . DNA methylation analysis determines the high frequency of genic hypomethylation and low frequency of hypermethylation events in plasma cell tumors . Cancer Res.70 ( 17 ), 6934 – 6944 ( 2010 ).
  • Martin-Subero JI , AmmerpohlO , BibikovaMet al. A comprehensive microarray-based DNA methylation study of 367 hematological neoplasms . PLoS ONE4 ( 9 ), e6986 ( 2009 ).
  • Chen RZ , PetterssonU , BeardC , Jackson-GrusbyL , JaenischR . DNA hypomethylation leads to elevated mutation rates . Nature395 ( 6697 ), 89 – 93 ( 1998 ).
  • Berdasco M , EstellerM . Aberrant epigenetic landscape in cancer: how cellular identity goes awry . Dev. Cell19 ( 5 ), 698 – 711 ( 2010 ).
  • Park G , KangSH , LeeJHet al. Concurrent p16 methylation pattern as an adverse prognostic factor in multiple myeloma: a methylation-specific polymerase chain reaction study using two different primer sets . Ann. Hematol.90 ( 1 ), 73 – 79 ( 2011 ).
  • Braggio E , MaiolinoA , GouveiaMEet al. Methylation status of nine tumor suppressor genes in multiple myeloma . Int. J. Hematol.91 ( 1 ), 87 – 96 ( 2010 ).
  • Kocemba KA , GroenRW , Van AndelHet al. Transcriptional silencing of the Wnt-antagonist DKK1 by promoter methylation is associated with enhanced Wnt signaling in advanced multiple myeloma . PLoS ONE7 ( 2 ), e30359 ( 2012 ).
  • Dawson S-J , TsuiDWY , MurtazaMet al. Analysis of circulating tumor DNA to monitor metastatic breast cancer . N. Engl. J. Med.368 ( 13 ), 1199 – 1209 ( 2013 ).
  • Woo HD , KimJ . Global DNA hypomethylation in peripheral blood leukocytes as a biomarker for cancer risk: a meta-analysis . PLoS ONE7 ( 4 ), e34615 ( 2012 ).
  • Giachelia M , BozzoliV , D’AloFet al. Quantification of DAPK1 promoter methylation in bone marrow and peripheral blood as a follicular lymphoma biomarker . J. Mol. Diagn.16 ( 4 ), 467 – 476 ( 2014 ).
  • Joo JE , WongEM , BagliettoLet al. The use of DNA from archival dried blood spots with the Infinium Humanmethylation450 array . BMC Biotechnol.13 , 23 ( 2013 ).
  • Giles GG , EnglishDR . The Melbourne Collaborative Cohort Study . IARC Sci. Publ.156 , 69 – 70 ( 2002 ).
  • R Core Team, R Foundation for Statistical Computing, 2015 . www.r-project.org/ .
  • Aryee MJ , JaffeAE , Corrada-BravoHet al. Minfi: a flexible and comprehensive bioconductor package for the analysis of infinium DNA methylation microarrays . Bioinformatics30 ( 10 ), 1363 – 1369 ( 2014 ).
  • Maksimovic J , GordonL , OshlackA . Swan: subset-quantile within array normalization for illumina infinium humanmethylation450 beadchips . Genome Biol.13 ( 6 ), R44 ( 2012 ).
  • Johnson WE , LiC , RabinovicA . Adjusting batch effects in microarray expression data using empirical bayes methods . Biostatistics8 ( 1 ), 118 – 127 ( 2007 ).
  • Marabita F , AlmgrenM , LindholmMEet al. An evaluation of analysis pipelines for DNA methylation profiling using the Illumina Humanmethylation450 beadchip platform . Epigenetics8 ( 3 ), 333 – 346 ( 2013 ).
  • Naeem H , WongNC , ChattertonZet al. Reducing the risk of false discovery enabling identification of biologically significant genome-wide methylation status using the humanmethylation450 array . BMC Genomics15 , 51 ( 2014 ).
  • Du P , ZhangX , HuangCCet al. Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis . BMC Bioinformatics11 , 587 ( 2010 ).
  • Weber M , HellmannI , StadlerMBet al. Distribution, silencing potential and evolutionary impact of promoter DNA methylation in the human genome . Nat. Genet.39 ( 4 ), 457 – 466 ( 2007 ).
  • Martin-Subero JI , KreuzM , BibikovaMet al. New insights into the biology and origin of mature aggressive b-cell lymphomas by combined epigenomic, genomic, and transcriptional profiling . Blood113 ( 11 ), 2488 – 2497 ( 2009 ).
  • Price ME , CottonAM , LamLLet al. Additional annotation enhances potential for biologically-relevant analysis of the Illumina Infinium Humanmethylation450 beadchip array . Epigenetics Chromatin6 ( 1 ), 4 ( 2013 ).
  • Houseman EA , AccomandoWP , KoestlerDCet al. DNA methylation arrays as surro-gate measures of cell mixture distribution . BMC Bioinformatics13 ( 1 ), 86 ( 2012 ).
  • Choi JH , LiY , GuoJet al. Genome-wide DNA methylation maps in follicular lymphoma cells determined by methylation-enriched bisulfite sequencing . PLoS ONE5 ( 9 ), e13020 ( 2010 ).
  • Narayan G , XieD , FreddyAJet al. PCDH10 promoter hypermethylation is frequent in most histologic subtypes of mature lymphoid malignancies and occurs early in lymphomagenesis . Genes Chromosomes Cancer52 ( 11 ), 1030 – 1041 ( 2013 ).
  • Halldorsdottir AM , KanduriM , MarincevicMet al. Mantle cell lymphoma displays a homogenous methylation profile: a comparative analysis with chronic lymphocytic leukemia . Am. J. Hematol.87 ( 4 ), 361 – 367 ( 2012 ).
  • Handa H , TaharaK , ShimizuHet al. Chromosome 16q located genes CDH1, CDH13 and ADAMTS18 are correlated and frequently methylated but not associated with dnmts levels in human lymphoma . Blood122 , 4289 – 4289 ( 2013 ).
  • Dudbridge F , GusnantoA . Estimation of significance thresholds for genomewide association scans . Genet. Epidemiol.32 ( 3 ), 227 – 234 ( 2008 ).
  • O’Riain C , O’SheaDM , YangYet al. Array-based DNA methylation profiling in follicular lymphoma . Leukemia23 ( 10 ), 1858 – 1866 ( 2009 ).
  • Cahill N , BerghAC , KanduriMet al. 450k-array analysis of chronic lymphocytic leukemia cells reveals global DNA methylation to be relatively stable over time and similar in resting and proliferative compartments . Leukemia27 ( 1 ), 150 – 158 ( 2013 ).
  • Irizarry RA , Ladd-AcostaC , WenBet al. The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores . Nat. Genet.41 ( 2 ), 178 – 186 ( 2009 ).
  • Reinius LE , AcevedoN , JoerinkMet al. Differential DNA methylation in purified human blood cells: implications for cell lineage and studies on disease susceptibility . PLoS ONE7 ( 7 ), e41361 ( 2012 ).
  • Koestler DC , ChristensenB , KaragasMRet al. Blood-based profiles of DNA methylation predict the underlying distribution of cell types: a validation analysis . Epigenetics8 ( 8 ), 816 – 826 ( 2013 ).
  • Jaffe AE , IrizarryRA . Accounting for cellular heterogeneity is critical in epigenome-wide association studies . Genome Biol.15 ( 2 ), R31 ( 2014 ).
  • Hughes T , Ture-OzdemirF , Alibaz-OnerF , CoitP , DireskeneliH , SawalhaAH . Epigenome-wide scan identifies a treatment-responsive pattern of altered DNA methylation among cytoskeletal remodeling genes in monocytes and CD4+ T cells in behcet’s disease . Arthritis Rheumatol.66 ( 6 ), 1648 – 1658 ( 2014 ).
  • Altorok N , CoitP , HughesTet al. Genome-wide DNA methylation patterns in naive CD4+ T cells from patients with primary sjögren’s syndrome . Arthritis Rheumatol.66 ( 3 ), 731 – 739 ( 2014 ).

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