Novel genes exhibiting DNA methylation alterations in Korean patients with chronic lymphocytic leukaemia: a methyl-CpG-binding domain sequencing study.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
23 01 2020
23 01 2020
Historique:
received:
26
08
2019
accepted:
06
01
2020
entrez:
25
1
2020
pubmed:
25
1
2020
medline:
20
11
2020
Statut:
epublish
Résumé
Chronic lymphocytic leukaemia (CLL) exhibits differences between Asians and Caucasians in terms of incidence rate, age at onset, immunophenotype, and genetic profile. We performed genome-wide methylation profiling of CLL in an Asian cohort for the first time. Eight Korean patients without somatic immunoglobulin heavy chain gene hypermutations underwent methyl-CpG-binding domain sequencing (MBD-seq), as did five control subjects. Gene Ontology, pathway analysis, and network-based prioritization of differentially methylated genes were also performed. More regions were hypomethylated (2,062 windows) than were hypermethylated (777 windows). Promoters contained the highest proportion of differentially methylated regions (0.08%), while distal intergenic and intron regions contained the largest number of differentially methylated regions. Protein-coding genes were the most abundant, followed by long noncoding and short noncoding genes. The most significantly over-represented signalling pathways in the differentially methylated gene list included immune/cancer-related pathways and B-cell receptor signalling. Among the top 10 hub genes identified via network-based prioritization, four (UBC, GRB2, CREBBP, and GAB2) had no known relevance to CLL, while the other six (STAT3, PTPN6, SYK, STAT5B, XPO1, and ABL1) have previously been linked to CLL in Caucasians. As such, our analysis identified four novel candidate genes of potential significance to Asian patients with CLL.
Identifiants
pubmed: 31974418
doi: 10.1038/s41598-020-57919-6
pii: 10.1038/s41598-020-57919-6
pmc: PMC6978354
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1085Références
Swerdlow, S. H. et al. Chronic lymphocytic leukaemia/small lymphocytic lymphoma. In WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues (eds. Campo, E. et al.) 216–219 (IARC, 2017).
Kim, J. A. et al. Genomic Profile of Chronic Lymphocytic Leukemia in Korea Identified by Targeted Sequencing. PLoS One. 11, e0167641 (2016).
pubmed: 27959900
pmcid: 5154520
doi: 10.1371/journal.pone.0167641
Jang, M. A. et al. Chronic lymphocytic leukemia in Korean patients: frequent atypical immunophenotype and relatively aggressive clinical behavior. Int. J. Hematol. 97, 403–8 (2016).
doi: 10.1007/s12185-013-1286-z
Xia, Y. et al. Frequencies of SF3B1, NOTCH1, MYD88, BIRC3 and IGHV mutations and TP53 disruptions in Chinese with chronic lymphocytic leukemia: disparities with Europeans. Oncotarget. 6, 5426–34 (2015).
pubmed: 25605254
pmcid: 25605254
Chen, S. S. et al. Silencing of the inhibitor of DNA binding protein 4 (ID4) contributes to the pathogenesis of mouse and human CLL. Blood. 117, 862–71 (2011).
pubmed: 21098398
pmcid: 3035078
doi: 10.1182/blood-2010-05-284638
Corcoran, M. et al. ZAP-70 methylation status is associated with ZAP-70 expression status in chronic lymphocytic leukemia. Haematologica. 90, 1078–88 (2005).
pubmed: 16079107
pmcid: 16079107
Raval, A. et al. Downregulation of death-associated protein kinase 1 (DAPK1) in chronic lymphocytic leukemia. Cell. 129, 879–90 (2007).
pubmed: 17540169
pmcid: 4647864
doi: 10.1016/j.cell.2007.03.043
Seeliger, B., Wilop, S., Osieka, R., Galm, O. & Jost, E. CpG island methylation patterns in chronic lymphocytic leukemia. Leuk. Lymphoma. 50, 419–26 (2009).
pubmed: 19347729
doi: 10.1080/10428190902756594
pmcid: 19347729
Kanduri, M. et al. Differential genome-wide array-based methylation profiles in prognostic subsets of chronic lymphocytic leukemia. Blood. 115, 296–305 (2010).
pubmed: 19897574
doi: 10.1182/blood-2009-07-232868
pmcid: 19897574
Cahill, N. et 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. Leukemia. 27, 150–8 (2013).
pubmed: 22922567
doi: 10.1038/leu.2012.245
Kulis, M. et al. Epigenomic analysis detects widespread gene-body DNA hypomethylation in chronic lymphocytic leukemia. Nat. Genet. 44, 1236–42 (2012).
pubmed: 23064414
doi: 10.1038/ng.2443
Landau, D. A. et al. Locally disordered methylation forms the basis of intratumor methylome variation in chronic lymphocytic leukemia. Cancer Cell. 26, 813–825 (2014).
pubmed: 25490447
pmcid: 4302418
doi: 10.1016/j.ccell.2014.10.012
Serre, D., Lee, B. H. & Ting, A. H. MBD-isolated Genome Sequencing provides a high-throughput and comprehensive survey of DNA methylation in the human genome. Nucleic Acids Res. 38, 391–9 (2010).
pubmed: 19906696
doi: 10.1093/nar/gkp992
pmcid: 19906696
Aberg, K. A. et al. MBD-seq as a cost-effective approach for methylome-wide association studies: demonstration in 1500 case–control samples. Epigenomics. 4, 605–21 (2012).
pubmed: 23244307
pmcid: 3923085
doi: 10.2217/epi.12.59
Harris, R. A. et al. Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications. Nat. Biotechnol. 28, 1097–105 (2010).
pubmed: 20852635
pmcid: 2955169
doi: 10.1038/nbt.1682
Subhash, S., Andersson, P. O., Kosalai, S. T., Kanduri, C. & Kanduri, M. Global DNA methylation profiling reveals new insights into epigenetically deregulated protein coding and long noncoding RNAs in CLL. Clin. Epigenetics. 8, 106 (2016).
pubmed: 27777635
pmcid: 5062931
doi: 10.1186/s13148-016-0274-6
Cahill, N. & Rosenquist, R. Uncovering the DNA methylome in chronic lymphocytic leukemia. Epigenetics. 8, 138–48 (2013).
pubmed: 23321535
pmcid: 3592899
doi: 10.4161/epi.23439
Pei, L. et al. Genome-wide DNA methylation analysis reveals novel epigenetic changes in chronic lymphocytic leukemia. Epigenetics. 7, 567–78 (2012).
pubmed: 22534504
pmcid: 3398986
doi: 10.4161/epi.20237
Kulis, M. et al. Whole-genome fingerprint of the DNA methylome during human B cell differentiation. Nat. Genet. 47, 746–56 (2015).
pubmed: 26053498
pmcid: 5444519
doi: 10.1038/ng.3291
Ehrlich, M. DNA methylation in cancer: too much, but also too little. Oncogene. 21, 5400–5413 (2002).
pubmed: 12154403
doi: 10.1038/sj.onc.1205651
Ogishima, T. et al. Increased heparanase expression is caused by promoter hypomethylation and upregulation of transcriptional factor early growth response-1 in human prostate cancer. Clin. Cancer Res. 11, 1028–1036 (2005).
pubmed: 15709168
Gaudet, F. et al. Induction of tumors in mice by genomic hypomethylation. Science. 300, 489–492 (2003).
pubmed: 12702876
doi: 10.1126/science.1083558
Qu, G., Grundy, P. E., Narayan, A. & Ehrlich, M. Frequent hypomethylation in Wilms tumors of pericentromeric DNA in chromosomes 1 and 16. Cancer Genet. Cytogenet. 109, 34–39 (1999).
pubmed: 9973957
doi: 10.1016/S0165-4608(98)00143-5
Medvedeva, Y. A. et al. Intergenic, gene terminal, and intragenic CpG islands in the human genome. BMC Genomics. 11, 48 (2010).
pubmed: 20085634
pmcid: 2817693
doi: 10.1186/1471-2164-11-48
Baylin, S. B. & Herman, J. G. DNA hypermethylation in tumorigenesis: epigenetics joins genetics. Trends. Genet. 16, 168–74 (2000).
pubmed: 10729832
doi: 10.1016/S0168-9525(99)01971-X
pmcid: 10729832
Esteller, M. Epigenetic gene silencing in cancer: the DNA hypermethylome. Hum. Mol. Genet. 16, R50–9 (2007).
pubmed: 17613547
doi: 10.1093/hmg/ddm018
pmcid: 17613547
Weber, B., Stresemann, C., Brueckner, B. & Lyko, F. Methylation of human microRNA genes in normal and neoplastic cells. Cell Cycle. 6, 1001–5 (2007).
pubmed: 17457051
doi: 10.4161/cc.6.9.4209
pmcid: 17457051
Ling, H. et al. Junk DNA and the long non-coding RNA twist in cancer genetics. Oncogene. 34, 5003–5011 (2015).
pubmed: 25619839
pmcid: 4552604
doi: 10.1038/onc.2014.456
Yang, G., Lu, X. & Yuan, L. LncRNA: a link between RNA and cancer. Biochim. Biophys. Acta. 1839, 1097–1109 (2014).
pubmed: 25159663
doi: 10.1016/j.bbagrm.2014.08.012
pmcid: 25159663
Nobili, L., Ronchetti, D., Taiana, E. & Neri, A. Long non-coding RNAs in B-cell malignancies: a comprehensive overview. Oncotarget. 8, 60605–60623 (2017).
pubmed: 28947998
pmcid: 5601166
doi: 10.18632/oncotarget.17303
Sattari, A. et al. Upregulation of long noncoding RNA MIAT in aggressive form of chronic lymphocytic leukemias. Oncotarget. 7, 54174–54182 (2016).
pubmed: 27527866
pmcid: 5338916
doi: 10.18632/oncotarget.11099
Balatti, V., Acunzo, M., Pekarky, Y. & Croce, C. M. Novel mechanisms of regulation of miRNAs in CLL. Trends. Cancer. 2, 134–143 (2016).
Fabbri, G. et al. Common nonmutational NOTCH1 activation in chronic lymphocytic leukemia. Proc. Natl. Acad. Sci. USA 114, E2911–E2919 (2017).
pubmed: 28314854
doi: 10.1073/pnas.1702564114
pmcid: 28314854
Giménez, N. et al. Mutations in the RAS-BRAF-MAPK-ERK pathway define a specific subgroup of patients with adverse clinical features and provide new therapeutic options in chronic lymphocytic leukemia. Haematologica. 104, 576–586 (2019).
pubmed: 30262568
pmcid: 6395334
doi: 10.3324/haematol.2018.196931
Sharman, J. et al. An open-label phase 2 trial of entospletinib (GS-9973), a selective spleen tyrosine kinase inhibitor, in chronic lymphocytic leukemia. Blood. 125, 2336–43 (2015).
pubmed: 25696919
pmcid: 4401348
doi: 10.1182/blood-2014-08-595934
Wolf, C. et al. NFATC1 activation by DNA hypomethylation in chronic lymphocytic leukemia correlates with clinical staging and can be inhibited by ibrutinib. Int. J. Cancer. 142, 322–333 (2018).
pubmed: 28921505
doi: 10.1002/ijc.31057
pmcid: 28921505
Yepes, S., Torres, M. M. & Andrade, R. E. Clustering of Expression Data in Chronic Lymphocytic Leukemia Reveals New Molecular Subdivisions. PLoS One. 10, e0137132 (2015).
pubmed: 26355846
pmcid: 4565688
doi: 10.1371/journal.pone.0137132
Bhalla, S. et al. Gene expression-based biomarkers for discriminating early and late stage of clear cell renal cancer. Sci. Rep. 7, 44997 (2017).
pubmed: 28349958
pmcid: 5368637
doi: 10.1038/srep44997
Tang, Y. et al. Downregulation of ubiquitin inhibits the proliferation and radioresistance of non-small cell lung cancer cells in vitro and in vivo. Sci. Rep. 5, 9476 (2015).
pubmed: 25820571
pmcid: 4377628
doi: 10.1038/srep09476
Ijaz, M. et al. The Role of Grb2 in Cancer and Peptides as Grb2 Antagonists. Protein. Pept. Lett. 24, 1084–1095 (2018).
pubmed: 29173143
doi: 10.2174/0929866525666171123213148
Dixon, Z. A. et al. CREBBP knockdown enhances RAS/RAF/MEK/ERK signaling in Ras pathway mutated acute lymphoblastic leukemia but does not modulate chemotherapeutic response. Haematologica. 102, 736–745 (2017).
pubmed: 27979926
pmcid: 5395114
doi: 10.3324/haematol.2016.145177
Gao, C. et al. Low CREBBP expression is associated with adverse long-term outcomes in paediatric acute lymphoblastic leukaemia. Eur. J. Haematol. 99, 150–159 (2017).
pubmed: 28452416
doi: 10.1111/ejh.12897
pmcid: 28452416
Hashwah, H. et al. Inactivation of CREBBP expands the germinal center B cell compartment, down-regulates MHCII expression and promotes DLBCL growth. Proc. Natl. Acad. Sci. USA 114, 9701–9706 (2017).
pubmed: 28831000
doi: 10.1073/pnas.1619555114
pmcid: 28831000
Jia, D. et al. Crebbp Loss Drives Small Cell Lung Cancer and Increases Sensitivity to HDAC Inhibition. Cancer Discov. 8, 1422–1437 (2018).
pubmed: 30181244
pmcid: 6294438
doi: 10.1158/2159-8290.CD-18-0385
Mullighan, C. G. et al. CREBBP mutations in relapsed acute lymphoblastic leukaemia. Nature. 471, 235–9 (2011).
pubmed: 21390130
pmcid: 3076610
doi: 10.1038/nature09727
Gu, H. & Neel, B. G. The “Gab” in signal transduction. Trends Cell Biol. 13, 122–30 (2003).
pubmed: 12628344
doi: 10.1016/S0962-8924(03)00002-3
pmcid: 12628344
Huang, E. et al. Gene expression predictors of breast cancer outcomes. Lancet. 361, 1590–1596 (2003).
pubmed: 12747878
doi: 10.1016/S0140-6736(03)13308-9
pmcid: 12747878
Chen, Y. et al. GAB2 promotes cell proliferation by activating the ERK signaling pathway in hepatocellular carcinoma. Tumour Biol. 37, 11763–11773 (2016).
pubmed: 27026230
doi: 10.1007/s13277-016-5019-9
pmcid: 27026230
Coutts, A. S. & La Thangue, N. B. The p53 response: emerging levels of co-factor complexity. Biochem. Biophys. Res. Commun. 331, 778–85 (2005).
pubmed: 15865933
doi: 10.1016/j.bbrc.2005.03.150
pmcid: 15865933
Lev Maor, G., Yearim, A. & Ast, G. The alternative role of DNA methylation in splicing regulation. Trends Genet. 31, 274–80 (2015).
pubmed: 25837375
doi: 10.1016/j.tig.2015.03.002
pmcid: 25837375
Oakes, C. C. et al. DNA methylation dynamics during B cell maturation underlie a continuum of disease phenotypes in chronic lymphocytic leukemia. Nat. Genet. 48, 253–64 (2016).
pubmed: 26780610
pmcid: 4963005
doi: 10.1038/ng.3488
Beekman, R. et al. The reference epigenome and regulatory chromatin landscape of chronic lymphocytic leukemia. Nat. Med. 24, 868–880 (2018).
pubmed: 29785028
pmcid: 6363101
doi: 10.1038/s41591-018-0028-4
Kanduri, M. et al. Distinct transcriptional control in major immunogenetic subsets of chronic lymphocytic leukemia exhibiting subset-biased global DNA methylation profiles. Epigenetics. 7, 1435–42 (2012).
pubmed: 23154584
pmcid: 3528698
doi: 10.4161/epi.22901
Ronchetti, D. et al. Distinct patterns of global promoter methylation in early stage chronic lymphocytic leukemia. Genes Chromosomes Cancer. 53, 264–73 (2014).
pubmed: 24347044
doi: 10.1002/gcc.22139
Hovestadt, V. et al. Decoding the regulatory landscape of medulloblastoma using DNA methylation sequencing. Nature. 510, 537–41 (2014).
pubmed: 24847876
doi: 10.1038/nature13268
Aran, D., Sabato, S. & Hellman, A. DNA methylation of distal regulatory sites characterizes dysregulation of cancer genes. Genome Biol. 14, R21 (2013).
pubmed: 23497655
pmcid: 4053839
doi: 10.1186/gb-2013-14-3-r21
Yamasaki, S. et al. Docking protein Gab2 is phosphorylated by ZAP-70 and negatively regulates T cell receptor signaling by recruitment of inhibitory molecules. J. Biol. Chem. 276, 45175–83 (2001).
pubmed: 11572860
doi: 10.1074/jbc.M105384200
pmcid: 11572860
Wilson, A. S., Power, B. E. & Molloy, P. L. DNA hypomethylation and human diseases. Biochim. Biophys. Acta. 1775, 138–62 (2007).
pubmed: 17045745
pmcid: 17045745
Jaffe, E. S., Harris, N. L., Stein, H. & Vardiman, J. W. Chronic lymphocytic leukaemia/small lymphocytic lymphoma. In WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues (eds. Muller-Hermelink, H. K., Montserrat, E., Catovsky, D. & Harris, N. L.) 127–130 (IARC, 2001).
Swerdlow, S. H. et al. Chronic lymphocytic leukaemia/small lymphocytic lymphoma. In WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues (eds. Muller-Hermelink, H.K. et al.) 180–182 (IARC, 2008).
Hallek, M. et al. Guidelines for the diagnosis and treatment of chronic lymphocytic leukemia: a report from the International Workshop on Chronic Lymphocytic Leukemia updating the National Cancer Institute-Working Group 1996 guidelines. Blood. 111, 5446–56 (2008).
pubmed: 18216293
pmcid: 2972576
doi: 10.1182/blood-2007-06-093906
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 30, 2114–20 (2014).
pubmed: 24695404
pmcid: 24695404
doi: 10.1093/bioinformatics/btu170
Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009).
pubmed: 19261174
pmcid: 2690996
doi: 10.1186/gb-2009-10-3-r25
Lienhard, M., Grimm, C., Morkel, M., Herwig, R. & Chavez, L. MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments. Bioinformatics. 30, 284–6 (2014).
pubmed: 24227674
doi: 10.1093/bioinformatics/btt650
Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 26, 139–40 (2010).
pubmed: 19910308
doi: 10.1093/bioinformatics/btp616
Servant, N. et al. EMA - A R package for Easy Microarray data analysis. BMC Res. Notes. 3, 277 (2010).
pubmed: 21047405
pmcid: 2987873
doi: 10.1186/1756-0500-3-277
Yu, G., Wang, L. G. & He, Q. Y. ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics. 31, 2382–3 (2015).
pubmed: 25765347
doi: 10.1093/bioinformatics/btv145
Yu, G., Wang, L. G., Han, Y. & He, Q. Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 16, 284–7 (2012).
pubmed: 22455463
pmcid: 3339379
doi: 10.1089/omi.2011.0118
Kanehisa, M., Sato, Y., Furumichi, M., Morishima, K. & Tanabe, M. New approach for understanding genome variations in KEGG. Nucleic Acids Res. 47, D590–D595 (2019).
pubmed: 30321428
doi: 10.1093/nar/gky962
pmcid: 30321428
Luo, W., Pant, G., Bhavnasi, Y. K., Blanchard, S. G. Jr. & Brouwer, C. Pathview Web: user friendly pathway visualization and data integration. Nucleic Acids Res. 45, W501–W508 (2017).
pubmed: 28482075
pmcid: 5570256
doi: 10.1093/nar/gkx372
Piñero, J. et al. DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic Acids Res. 45, D833–D839 (2017).
pubmed: 27924018
doi: 10.1093/nar/gkw943
pmcid: 27924018
Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–504 (2003).
pubmed: 14597658
pmcid: 403769
doi: 10.1101/gr.1239303
Martin, A. et al. BisoGenet: a new tool for gene network building, visualization and analysis. BMC Bioinformatics. 11, 91 (2010).
pubmed: 20163717
pmcid: 3098113
doi: 10.1186/1471-2105-11-91
Wu, G., Dawson, E., Duong, A., Haw, R. & Stein, L. ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis. Version 2, F1000Res (2014).
Doncheva, N. T., Assenov, Y., Domingues, F. S. & Albrecht, M. Topological analysis and interactive visualization of biological networks and protein structures. Nat. Protoc. 7, 670–85 (2012).
pubmed: 22422314
doi: 10.1038/nprot.2012.004
pmcid: 22422314