AH Shih

DA Russler-Germain

HC Tsai

JM Klco

JP Patel

K Lund

ME Figueroa

Olga A Guryanova

R Claus

Ross L Levine

Genome Biology

Crossref

Guryanova and Levine Genome Biology 2014, 15:441http://genomebiology.com/2014/15/8/441RESEARCH HIGHLIGHTA WIMSical approach to decoding DNAmethylation in myeloid leukemiaOlga A Guryanova1 and Ross L Levine1,2*See related Research, http://genomebiology.com/2014/15/7/406AbstractIntegrated transcriptomic and high-resolution wholegenome methylation analysis in a myeloid leukemiacell line defines genes that respond to clinically relevantDNA methyltransferase inhibitors.an attempt to identify the gene targets of hypomethylatingNucleotide sequence serves as the essential text of thegenetic ‘book’ known as the human genome, but this bookalso comes with ‘reading instructions’, ‘bookmarks’ and‘highlighted passages’ in the form of epigenetic patterns.Not surprisingly, the initiation and progression of cancerare governed not only by the accumulation of geneticlesions in the text itself but also by perturbationsin the epigenome. Indeed, epigenetic alterations thatdysregulate the ability of cancer cells to utilize genomicinformation are increasingly being appreciated as an im-portant contributing factor in the development of differ-ent malignancies [1].Epigenetic therapies for malignanciesUnlike genetic lesions, epigenetic patterns are relativelyfluid and might be correctable by therapeutic perturba-tions. Such malleability has made epigenetic therapiesan attractive alternative to cytotoxic chemotherapies.Rather than trying to destroy rapidly dividing cells in-stantly, epigenetic therapies aim to reprogram cancer cellsby attenuating cancer-promoting transcriptional networks[1]. These therapies, specifically the DNA hypomethylat-ing agents 5-azacitidine (Aza) and 5-aza-2′-deoxycytidine(decitabine, Dac), have been used increasingly for thetreatment of patients with myelodysplastic syndrome(MDS) and acute myeloid leukemia (AML) [2]. Despite* Correspondence: leviner@mskcc.org1Human Oncology and Pathogenesis Program, Memorial Sloan KetteringCancer Center, New York, NY 10065, USA2Leukemia Service, Department of Medicine, Memorial Sloan KetteringCancer Center, New York, NY 10065, USA© 2014 Guryanova and Levine; licensee BioMe12 months following its publication. After this tim(http://creativecommons.org/licenses/by/4.0), whioriginal work is properly credited. The Creative Co1.0/) applies to the data made available in this artthe successful use of both Aza and Dac in the clinic,the molecular mechanisms behind their efficacy re-quires additional investigation. In this issue of GenomeBiology, Lund et al. [3] employ a sophisticated method-ology, which they term WIMSi, to sift through high-resolution DNA methylomic and transcriptomic data intherapies [3].Myelodysplastic syndrome (MDS) and acute myeloidleukemia (AML) are malignant disorders of hematopoieticprogenitor cells that lead to defective hematopoiesis. MDSis characterized by cytopenia (a reduction in the numberof blood cells); AML, on the other hand, is typified byleukocytosis, which primarily results from the expansionof immature myeloid blasts. Both types of malignanciesare most commonly diagnosed later in life (median ageat AML diagnosis is 68 years). An intense interest indemethylating therapies for AML and MDS has beenfueled by the presence of hallmark focal DNA hyperme-thylation that distinguishes leukemic blasts from normalhematopoietic progenitors, and by the high frequency ofsomatic mutations in genes that regulate the methyla-tion of genomic DNA, including IDH1/2, TET2, andDNMT3A [1,2,4,5], in myeloid malignancies.Under investigation: mechanism of action ofhypomethylating drugsThe classical view of the establishment and maintenanceof site-specific DNA methylation posits that methyl groupsare introduced at CpG palindromic sites by de novo DNAmethyltransferases (DNMTs; DNMT3A and DNMT3B)over the course of cellular differentiation, starting in em-bryogenesis. After each round of replication, the methyla-tion pattern can be copied from the (methylated) parentstrand to the (unmethylated) daughter strand by the main-tenance methyltransferase DNMT1 because of its pref-erence for hemimethylated DNA. The TET family ofenzymes can mediate active DNA demethylation, al-though the steps subsequent to TET enzymatic activityd Central Ltd. The licensee has exclusive rights to distribute this article, in any medium, fore, the article is available under the terms of the Creative Commons Attribution Licensech permits unrestricted use, distribution, and reproduction in any medium, provided themmons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/icle, unless otherwise stated.Guryanova and Levine Genome Biology 2014, 15:441 Page 2 of 3http://genomebiology.com/2014/15/8/441have not been fully elucidated. In replicating cells, DNAmethylation also decreases passively in the absence ofre-methylation [1]. Passive demethylation is thought tounderlie the mechanism of action of DNMT inhibitors.The nucleoside analogs Aza and Dac, and their metabo-lites, act as DNMT suicide substrates upon incorporationinto replicating DNA. Additionally, exposure to higherdoses of these agents results in bulky adduct formationand DNA damage [2,6].Cancer-associated focal DNA hypermethylation, espe-cially in the promoter regions of key effector genes, isbelieved to be responsible for silencing critical tumorsuppressors, such as pro-apoptotic genes and regulatorsof the cell cycle and differentiation commitment [1,6,7].Treatment with DNMT inhibitors induces early loss ofDNA methylation, even at low drug doses [6,8], but pub-lished studies report discordant effects of hypomethylatingagents on gene expression [6-8]. Some investigators ob-served widespread reactivation of silenced tumor suppres-sor genes in response to DNMT inhibitors. Others failedto detect any relationship between DNA hypomethylationand gene expression, despite consistent robust correlationbetween DNA methylation and gene repression in un-treated primary cultured cells and cell lines [6,7,9]. Thevery short extent of treatment (most studies chose 48 to72 hour timepoints) [6,8] may not be sufficient to inducerobust changes in gene expression despite early widespreadhypomethylation. In addition, the accumulation of DNAmethylation during gene silencing precedes the depositionof repressive histone marks and chromatin compaction. Itis conceivable that the same would hold true during genereactivation and would require days rather than hours.As an alternative hypothesis to explain why there was nocorrelation between gene expression and DNA methyla-tion changes, Lund et al. [3] reasoned that the limitedresolution and skewed representation of genomic featuresinherent in a previous generation of experimental methodswere to blame. To zero in on a list of candidate genesregulated exclusively by DNA methylation, Lund et al.[3] investigated a combined dataset of high-resolutionwhole-genome bisulfite sequencing (WGBS) data andgene expression profiles by RNA-seq in an AML cell linetreated with Aza. Although higher than that used in previ-ously published studies, a low dose of Aza (0.5 μM) waschosen to minimize changes in cell proliferation and DNAdamage. DNA damage and changes in proliferation ratesinduced by high-dose Aza may obscure the impact ofDNA demethylation on gene expression. To avoid this theauthors chose a significantly lower dose that did not affectproliferation and did not induce DNA damage.The study focused on the OCI/AML-3 leukemic cellline, which is known to carry mutations in the NPM1 andDNMT3A genes. The nucleophosmin gene NPM1 is oneof the most frequently mutated genes in AML. Mutationsin NPM1 most often disrupt its nuclear localization signaland are associated with favorable prognosis [4,5]. Eventhough NPM1 is not directly involved in the regulation ofDNA methylation, mutated NPM1 defines a distinct epi-genetic cluster identified by the DNA methylation profil-ing of 344 AML patients [9]. DNMT3A is another genethat is frequently mutated in AML. In contrast to NPM1mutations, DNMT3A mutations predict poor survivalrates [1,5]. The presence of two mutations with oppositeprognostic effects challenges unequivocal risk stratifica-tion. Despite the frequent occurrence of mutations in bothNPM1 and DNMT3A in AML, the co-occurrence ofmutations in both of these genes in the absence of FLT3internal tandem duplications (FLT3-ITD) is relativelyuncommon [4]. Consequently, the OCI/AML-3 cell linedoes not reflect the genotypic context most commonlyobserved in AML patients whose leukemia cells carrythese mutant disease alleles.DNMT3A is directly involved in the establishment andmaintenance of DNA methylation patterns, and DNMT3Amutant AML patient-derived samples show a small butsignificant decrease in mean methylation relative to non-mutated samples [10]. Despite having solid adverse prog-nostic implications, the predictive value of DNMT3Amutations with respect to the response to hypomethy-lating agents has not been conclusively established.Overall, four small-scale clinical trials that investigatedthe relationship between DNMT3A mutations and responseto hypomethylating agents showed a trend towards pro-longed progression-free survival (PFS) and higher completeremission (CR) rate in those carrying the mutation [2].The authors’ general characterization of the DNA-methylation landscape by WGBS confirmed previousfindings [6,7,9]: methylation is enhanced in the bodies(transcribed portions) of highly expressed genes, butthere are low methylation levels in promoters and analmost complete loss of methylation just downstreamof transcriptional start sites. Treatment of OCI/AML-3cells with Aza resulted in general, genome-wide hypo-methylation; genomic features with the highest levels ofmethylation pre-treatment were affected to the greatestextent. Consistent with most previously published stud-ies, there was no obvious correlation between DNA hy-pomethylation at gene promoters or CpG islands andexpression of the corresponding gene. The authors thenused WIMSi (Washington University Interpolated Methy-lation Signatures), a more sophisticated computational ap-proach, to tease out subtle co-regulation between DNAmethylation and gene expression [3].WIMSi analysis identifies genes directly regulatedby DNA methylationWIMSi analysis relies on the identification of gene clustersthat share similar DNA methylation profiles by shape-Guryanova and Levine Genome Biology 2014, 15:441 Page 3 of 3http://genomebiology.com/2014/15/8/441curve and concordant changes in gene expression beforeand after treatment with Aza to identify specific genes orloci of interest. This approach yielded a list of 246 dere-pressed genes that have functions in cell death and sur-vival or in cell movement and proliferation, all presumablyregulated directly by DNA methylation. Cross-validationwith other published datasets showed that WIMSi geneswere enriched among genes whose expression was down-regulated in AML compared to normal hematopoieticstem and progenitor cells (HSPCs). Many WIMSi geneswere also found as upregulated in a previous study investi-gating the impact of DNMT inhibitors on methylationand gene expression in primary AML samples that failedto detect a relationship between DNA hypomethylationand gene expression by more general methods [6]. Over-all, the study by Lund et al. [3] demonstrates the feasibilityof using high-resolution WGBS and RNA-seq, when com-bined with sophisticated computational methods, to un-cover relationships between DNA methylation and geneexpression.As with any novel methodology, this study raises manyquestions for subsequent investigation. First, the questionof whether other epigenetic marks are involved in earlyregulation of gene expression is the most important andthe most informative. Are DNA methylation and histonemodifications co-regulated, or does one direct the other?What is the timing of the chromatin reorganization that isnecessary to allow gene de-repression, and what is the op-timal time point at which to measure it? Would histonemodifications be more directly related to changes in geneexpression than changes in DNA methylation? Compre-hensive epigenetic profiling that integrates analysis of theDNA methylome, the epigenome and the transcriptomewill further our understanding of the mechanisms behindthe efficacy of hypomethylating therapies. Such studieswill be welcomed with great enthusiasm in the field ofclinical cancer epigenetics. Second, what are the implica-tions of the apparent reprogramming of OCI/AML-3 cellsinto a state more similar to HSPCs after Aza exposure?Are the effects on self-renewal genes distinct from thoseon differentiation and lineage-commitment genes? Howsimilar are the reprogrammed profiles to those of moremature populations? Detailed studies involving additionalleukemic and normal samples will be needed to shed lighton the complex processes that guide epigenetic repro-gramming. Finally, how generalizable are these findings,given the specific genetic make-up of the OCI/AML-3cells and the uncertain impact of DNMT3A mutationalstatus on predicting response to hypomethylating agents?Extension of these studies to cellular models (cell lines orprimary AML samples) with more relevant and compre-hensive mutational landscapes will be eagerly awaited.In the book of life that is the genome, aberrant DNAhypermethylation that silences tumor suppressor genescan be likened to pages that are stuck together, concealingimportant plot twists. Hypomethylating therapies can peelthese pages apart and open the book at the right chapter.Whether it will be fully readable and able to guide the re-programming of malignant cells, and what other signalsor epigenetic marks are needed to promote proper gen-ome reading, are questions that we are just beginning toanswer.AbbreviationsAML: Acute myeloid leukemia; Aza: 5-azacitidine; CR: Complete remission;Dac: 5-aza-2′-deoxycytidine; DNMT: DNA methyltransferase; FLT3-ITD: FLT3internal tandem duplication; HSPC: Hematopoietic stem and progenitor cells;MDS: Myelodysplastic syndrome; PFS: Progression-free survival; WGBS: Wholegenome bisulfite sequencing.References1. Shih AH, Abdel-Wahab O, Patel JP, Levine RL: The role of mutations inepigenetic regulators in myeloid malignancies. Nat Rev Cancer 2012,12:599–612.2. Im AP, Sehgal AR, Carroll MP, Smith BD, Tefferi A, Johnson DE, Boyiadzis M:DNMT3A and IDH mutations in acute myeloid leukemia and othermyeloid malignancies: associations with prognosis and potentialtreatment strategies. Leukemia 2014, doi:10.1038/leu.2014.124.3. Lund K, Cole J, VanderKraats ND, McBryan T, Pchelintsev NA, Clark W,Copland M, Edwards JR, Adams PD: DNMT inhibitors reverse a specificsignature of aberrant promoter DNA methylation and associated genesilencing in AML. Genome Biol 2014, 8:406.4. Cancer Genome Atlas Research Network: Genomic and epigenomiclandscapes of adult de novo acute myeloid leukemia. N Engl J Med 2013,368:2059–2074.5. Patel JP, Gönen M, Figueroa ME, Fernandez H, Sun Z, Racevskis J, VanVlierberghe P, Dolgalev I, Thomas S, Aminova O, Huberman K, Cheng J,Viale A, Socci ND, Heguy A, Cherry A, Vance G, Higgins RR, Ketterling RP,Gallagher RE, Litzow M, van den Brink MR, Lazarus HM, Rowe JM, Luger S,Ferrando A, Paietta E, Tallman MS, Melnick A, Abdel-Wahab O, et al: Prognosticrelevance of integrated genetic profiling in acute myeloid leukemia. N EnglJ Med 2012, 366:1079–1089.6. Klco JM, Spencer DH, Lamprecht TL, Sarkaria SM, Wylie T, Magrini V, Hundal J,Walker J, Varghese N, Erdmann-Gilmore P, Lichti CF, Meyer MR, Townsend RR,Wilson RK, Mardis ER, Ley TJ: Genomic impact of transient low-dosedecitabine treatment on primary AML cells. Blood 2013, 121:1633–1643.7. Tsai HC, Li H, Van Neste L, Cai Y, Robert C, Rassool FV, Shin JJ, Harbom KM,Beaty R, Pappou E, Harris J, Yen RW, Ahuja N, Brock MV, Stearns V,Feller-Kopman D, Yarmus LB, Lin YC, Welm AL, Issa JP, Minn I, Matsui W,Jang YY, Sharkis SJ, Baylin SB, Zahnow CA: Transient low doses ofDNA-demethylating agents exert durable antitumor effects onhematological and epithelial tumor cells. Cancer Cell 2012, 21:430–446.8. Claus R, Pfeifer D, Almstedt M, Zucknick M, Hackanson B, Plass C, Lubbert M:Decitabine induces very early in vivo DNA methylation changes in blastsfrom patients with acute myeloid leukemia. Leuk Res 2013, 37:190–196.9. Figueroa ME, Lugthart S, Li Y, Erpelinck-Verschueren C, Deng X, Christos PJ,Schifano E, Booth J, van Putten W, Skrabanek L, Campagne F, Mazumdar M,Greally JM, Valk PJ, Löwenberg B, Delwel R, Melnick A: DNA methylationsignatures identify biologically distinct subtypes in acute myeloidleukemia. Cancer Cell 2010, 17:13–27.10. Russler-Germain DA, Spencer DH, Young MA, Lamprecht TL, Miller CA,Fulton R, Meyer MR, Erdmann-Gilmore P, Townsend RR, Wilson RK, Ley TJ:The R882H DNMT3A mutation associated with AML dominantly inhibitswild-type DNMT3A by blocking its ability to form active tetramers.Cancer Cell 2014, 25:442–454.doi:10.1186/s13059-014-0441-zCite this article as: Guryanova and Levine: A WIMSical approach todecoding DNA methylation in myeloid leukemia. Genome Biology2014 15:441.

A WIMSical approach to decoding DNA methylation in myeloid leukemia

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A WIMSical approach to decoding DNA methylation in myeloid leukemia

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