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Early During Myelomagenesis Alterations in DNA Methylation That Occur Myeloma Is Characterized by Stage-Specific

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Early During Myelomagenesis Alterations in DNA Methylation That Occur Myeloma Is Characterized by Stage-Specific The Journal of Immunology Myeloma Is Characterized by Stage-Specific Alterations in DNA Methylation That Occur Early during Myelomagenesis Christoph J. Heuck,* Jayesh Mehta,† Tushar Bhagat,* Krishna Gundabolu,* Yiting Yu,* Shahper Khan,‡ Grigoris Chrysofakis,* Carolina Schinke,* Joseph Tariman,† Eric Vickrey,† Natalie Pulliam,† Sangeeta Nischal,* Li Zhou,* Sanchari Bhattacharyya,* Richard Meagher,† Caroline Hu,* Shahina Maqbool,* Masako Suzuki,* Samir Parekh,* Frederic Reu,‡ Ulrich Steidl,* John Greally,* Amit Verma,* and Seema B. Singhal† Epigenetic changes play important roles in carcinogenesis and influence initial steps in neoplastic transformation by altering ge- nome stability and regulating gene expression. To characterize epigenomic changes during the transformation of normal plasma cells to myeloma, we modified the HpaII tiny fragment enrichment by ligation–mediated PCR assay to work with small numbers of purified primary marrow plasma cells. The nano-HpaII tiny fragment enrichment by ligation–mediated PCR assay was used to analyze the methylome of CD138+ cells from 56 subjects representing premalignant (monoclonal gammopathy of uncertain significance), early, and advanced stages of myeloma, as well as healthy controls. Plasma cells from premalignant and early stages of myeloma were characterized by striking, widespread hypomethylation. Gene-specific hypermethylation was seen to occur in the advanced stages, and cell lines representative of relapsed cases were found to be sensitive to decitabine. Aberrant demethylation in monoclonal gammopathy of uncertain significance occurred primarily in CpG islands, whereas differentially methylated loci in cases of myeloma occurred predominantly outside of CpG islands and affected distinct sets of gene pathways, demonstrating qualitative epigenetic differences between premalignant and malignant stages. Examination of the methylation machinery revealed that the methyltransferase, DNMT3A, was aberrantly hypermethylated and underexpressed, but not mutated in mye- loma. DNMT3A underexpression was also associated with adverse overall survival in a large cohort of patients, providing insights into genesis of hypomethylation in myeloma. These results demonstrate widespread, stage-specific epigenetic changes during myelomagenesis and suggest that early demethylation can be a potential contributor to genome instability seen in myeloma. We also identify DNMT3A expression as a novel prognostic biomarker and suggest that relapsed cases can be therapeutically targeted by hypomethylating agents. The Journal of Immunology, 2013, 190: 2966–2975. espite therapeutic advances, multiple myeloma (MM) re- the development of a risk model that remains robust even in the age mains incurable and needs newer insights into the path- of newer therapies (1). The use of gene expression profiling by D ogenic mechanisms that cause this disease. Gene expres- different groups has also led to the identification of distinct mo- sion profiling has been used extensively in myeloma and has led to lecular subgroups that show defined clinical features (2, 3). How- ever, pathogenic mechanisms driving these differences in gene expression have not been well described, especially for early stages *Albert Einstein College of Medicine, Bronx, NY 10461; †Northwestern University, in myelomagenesis (4). Feinberg School of Medicine, Chicago, IL 60611; and ‡Cleveland Clinic, Cleveland, Recent studies of the epigenome and in particular the methylome OH 44195 have shown that cancer is characterized by widespread epigenetic Received for publication September 7, 2012. Accepted for publication January 9, changes. These changes lead to altered gene expression that can 2013. result in activation of oncogenic pathways. Furthermore, methyl- This work was supported by National Institutes of Health Immunooncology Training ome profiling has shown greater prognostic ability than gene ex- Program Grant T32 CA009173, Gabrielle’s Angel Foundation, the Leukemia and Lymphoma Society, the American Cancer Society, the Department of Defense, and pression profiling in acute myeloid leukemia (AML) and has led to a Partnership for Cures grant. identification of newer molecular subgroups with differences in The methylation data presented in this article have been deposited in the National overall survival (5). We have shown that methylome profiling is Institutes of Health Gene Expression Omnibus (National Center for Biotechnology able to identify changes that occur early during carcinogenesis in Information, http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE 43860. solid tumors such as esophageal cancer (6). These studies have Address correspondence and reprint requests to Dr. Amit Verma, Dr. Christoph J. Heuck, and Dr. Seema B. Singhal, Albert Einstein College of Medicine, Bronx, NY been conducted with the use of the HpaII tiny fragment enrich- 10461 (A.V. and C.J.H.) and Feinberg School of Medicine, Northwestern University, ment by ligation–mediated PCR (HELP) assay, which is a ge- Chicago, IL 60611 (S.B.S.). E-mail addresses: [email protected] (A.V.), nome-wide assay that provides a reproducible analysis of the [email protected] (C.J.H.), and [email protected] (S.B.S.) methylome that is not biased toward CpG islands (7). Analyzing The online version of this article contains supplemental material. the methylome of myeloma can help identify changes that can Abbreviations used in this article: AML, acute myeloid leukemia; HAF, HpaII-amplifi- able fragment; HELP, HpaII tiny fragment enrichment by ligation–mediated PCR; MM, define disease subsets and lead to identification of newer thera- multiple myeloma; MGUS, monoclonal gammopathy of uncertain significance; peutic targets. Recent sequencing studies in myeloma have also NEWMM, newly diagnosed myeloma; NL, normal; REL, relapsed myeloma; REM, revealed mutations in enzymes that are involved in epigenetic complete remission; SMM, smoldering myeloma; TF, transcription factor. machinery, again reinforcing the need to study the epigenetic Copyright Ó 2013 by The American Association of Immunologists, Inc. 0022-1767/13/$16.00 alterations in this disease (8). We have conducted a genome-wide www.jimmunol.org/cgi/doi/10.4049/jimmunol.1202493 The Journal of Immunology 2967 analysis of changes in DNA methylation in monoclonal gamm- tative for methylation and analyzed as a continuous variable. For most loci, opathy of uncertain significance (MGUS), newly diagnosed MM, each fragment was categorized as either methylated, if the centered log , as well as relapsed MM, and compared them with normal plasma HpaII/MspI ratio was generally 0, or hypomethylated, if, in contrast, the log ratio was .0. cell controls. We used a modification of the HELP assay (nano- HELP) that was developed to work with low amounts of DNA to Quantitative DNA methylation analysis by MassArray interrogate the methylome of sorted CD138+ cells from patient Epityping samples. We report that widespread alterations in DNA methyla- Validation of the findings of the HELP assay was carried out by MALDI- tion are seen in myeloma and have the power to discriminate TOF mass spectrometry using EpiTyper by MassArray (Sequenom, CA) on between MGUS and new/relapsed cases. We report that hypo- bisulfite-converted DNA, as previously described (6). Validation was done methylation is the predominant early change during myeloma- on all samples with sufficient available DNA. MassARRAY primers were designed to cover the flanking HpaII sites for a given HAF, as well as for genesis that is gradually transformed to hypermethylation in any other HpaII sites found up to 2000 bp upstream of the downstream site relapsed cases, thus providing the epigenetic basis for the differ- and up to 2000 bp downstream of the upstream site, to cover all possible entiation between these different stages of myeloma. alternative sites of digestion within our range of PCR amplification. Microarray data analysis Materials and Methods Patient samples Unsupervised clustering of HELP data by hierarchical clustering was performed using the statistical software R version 2.6.2. A two-sample t test Bone marrow aspirates were obtained with signed informed consent from was used for each gene to summarize methylation differences between 11 patients with MGUS, 4 patients with smoldering myeloma (SMM), groups. Genes were ranked on the basis of this test statistic, and a set of top 13 patients with newly diagnosed myeloma (NEWMM), 16 patients with differentially methylated genes with an observed log fold change of .1 relapsed myeloma (REL), including 2 patients with serial samples, and 2 between group means was identified. Genes were further grouped patients in clinical complete remission (REM) who are followed at the according to the direction of the methylation change (hypomethylated myeloma clinic at the Robert H. Lurie Cancer Center at Northwestern versus hypermethylated), and the relative frequencies of these changes University. All specimens underwent CD138+ microbead selection (Mil- were computed among the top candidates to explore global methylation tenyi Biotec). Purity was confirmed by flow cytometry staining for CD38 patterns. Validation with MassArray showed good correlation with the data and CD45. Samples with a purity ,90% by flow cytometry were not used generated by the HELP assay. MassArray analysis validated significant for this study. Eight samples from normal donors without known malig- quantitative differences in methylation for differentially methylated genes nancies were obtained commercially
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