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  • 1
    In: JAMA, American Medical Association (AMA), Vol. 314, No. 8 ( 2015-08-25), p. 811-
    Type of Medium: Online Resource
    ISSN: 0098-7484
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    Language: English
    Publisher: American Medical Association (AMA)
    Publication Date: 2015
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  • 2
    In: Cancer Cell, Elsevier BV, Vol. 25, No. 4 ( 2014-04), p. 442-454
    Type of Medium: Online Resource
    ISSN: 1535-6108
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2014
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  • 3
    In: Cancer Cell, Elsevier BV, Vol. 25, No. 3 ( 2014-03), p. 379-392
    Type of Medium: Online Resource
    ISSN: 1535-6108
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2014
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  • 4
    In: Nature, Springer Science and Business Media LLC, Vol. 481, No. 7382 ( 2012-1), p. 506-510
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2012
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  • 5
    In: New England Journal of Medicine, Massachusetts Medical Society, Vol. 363, No. 25 ( 2010-12-16), p. 2424-2433
    Type of Medium: Online Resource
    ISSN: 0028-4793 , 1533-4406
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    Language: English
    Publisher: Massachusetts Medical Society
    Publication Date: 2010
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  • 6
    In: Blood, American Society of Hematology, Vol. 120, No. 21 ( 2012-11-16), p. 2527-2527
    Abstract: Abstract 2527 Acute myeloid leukemia (AML) is a hematopoietic neoplasm with high mortality that is typically treated with daunorubicin/cytarabine induction chemotherapy. Alternative therapies with cytosine analogs such as decitabine are also used in some cases with a variable clinical response that some have estimated to be as high as 25%. The mechanism of these agents is unclear, but at low doses they produce passive DNA hypomethylation by inhibiting DNMT1. Although the impact of these drugs on cell growth and DNA methylation in AML cell lines has been evaluated1, studies using primary cells are limited; importantly, most have involved extended drug treatments that may be confounded by the differentiation of the treated cells2. In addition, some evidence suggests that decitabine has a differential effect on methylation in patients who respond to treatment2, but the utility of this phenotype as an in vitro biomarker for decitabine responsiveness is unknown. In this study, we used a novel in vitro culture system for primary leukemia cells to explore the initial genomic effects of short-term low dose decitabine on primary samples from 22 AML patients. Primary bone marrow or blood samples from these patients were cultured on HS27 stromal cells in DMEM supplemented with beta-mercaptoethanol and 15% FBS along with hSCF, hIL3, hIL-6, hTPO and hFLT3L for an initial 4-day period prior to daily treatment for 3 days with either 100 nM decitabine, 100 nM cytarabine, or vehicle controls. Cells were then evaluated for growth, cell cycle effects, and differentiation (by flow cytometry and morphologic evaluation). DNA was prepared from all samples for 5-methylcytosine content measurements by mass spectrometry, and 8 samples were selected for genome-wide methylation and gene expression profiling with the Illumina Human Methylation 450 and Affymetrix Human Exon 1.0ST array platforms. Mass spectrometry revealed a mean decrease in 5-mdC of 29% (range: 13% to 62%) in the decitabine-treated samples; in comparison, cytarabine treatment resulted in a mean increase in 5-mdC of 5% (range: −10% to 37%). Methylation arrays also showed a modest shift toward lower methylation values, but unsupervised hierarchical clustering demonstrated that methylation patterns were driven by sample-specific differences and not drug treatment. Analysis of methylation changes showed the most pronounced hypomethylation at CpGs with high baseline methylation levels, irrespective of CpG island and gene-based annotation, suggesting that the initial methylation status of each CpG is responsible for preferential effects of decitabine, rather than its genomic context. Methylation at promoter-associated CpGs showed a small but statistically significant negative correlation with change in gene expression, but expression changes at individual genes were not consistent across the samples, including genes previously shown to be regulated by methylation-dependent mechanisms (eg. CDKN2B and CDx H1). In addition to these findings, we observed that a sample from a long-term decitabine responder had an exaggerated in vitro response to decitabine (58% decrease in 5-mdC after 6 days of treatment), compared to a cohort of decitabine non-responders; a sample from a second patient also showed marked hypomethylation by both mass spectrometry and methylation array, although this patient was not treated with decitabine. While more investigation is needed, this observation might suggest that extreme in vitro hypomethylation in response to decitabine could serve as a biomarker for a clinical response. In summary, our study showed that short-term low dose decitabine treatment has modest but detectable effects on DNA methylation and gene expression, but these changes did not result in activation of any canonical gene expression pathway at this early time point. We found that the baseline methylation status of a CpG appears to be the best predictor of decitabine-induced hypomethylation, with highly methylated CpGs showing the greatest change. We also observed that hypomethylation is highly variable across primary samples and at specific genes, implying that single gene approaches for measuring decitabine effect may be problematic. Finally, extreme in vitro decitabine-induced hypomethylation should be further investigated as a biomarker for decitabine responsiveness. Disclosures: No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2012
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  • 7
    In: Blood, American Society of Hematology, Vol. 124, No. 21 ( 2014-12-06), p. 608-608
    Abstract: Mutations in the de novo DNA methyltransferase DNMT3A are found in ~25% of patients with acute myeloid leukemia (AML) and most commonly affect codon 882 within the catalytic domain of the protein. We have previously shown that this mutation has dominant negative activity in vitro and is associated with hypomethylation at specific CpG dinucleotides in primary AML samples using array-based methylation data. However, the genome-wide extent and patterns of DNA methylation associated with this hypomethylation are currently unknown. In addition, it is unclear if the methylation differences caused by this mutation result in RNA expression changes at specific targets across the genome, or whether they are associated with altered chromatin structure. To explore the genome-wide consequences of the DNMT3A R882H mutation on DNA methylation and chromatin structure, we carried out whole-genome bisulfite sequencing (WGBS) and transposase-mediated chromatin accessibility profiling (ATAC-seq) on 3 primary normal karyotype AML samples with the DNMT3A R882H mutation and 4 matched AML samples without a DNMT3A mutation. All 7 had the NPMc mutation but lacked mutations in other genes involved in DNA methylation, including IDH1, IDH2, and TET2. WGBS produced methylation data on 〉 93% of the CpGs in the human reference sequence with a median coverage of 7-13x. The overall mean methylation was not statistically different in the samples with R882H mutations, although there was a small but statistically significant difference in the methylation at CpGs in CpG islands (DNMT3A R882H mean: 18.1%, DNMT3A wild-type mean: 21.4%; P=0.02). Differential methylation analysis was performed on ~5 million CpG clusters (median of 5 CpGs per cluster; median cluster size of 202 bp) and identified 95,845 differentially methylated clusters with a mean difference 〉 25% and a q-value 〈 0.01, the majority of which (88,512; 93%) were hypomethylated in the DNMT3A R882H samples. Using more strict criteria ( 〉 50% mean difference) and merging differentially methylated clusters within 50 bp, we identified 2,782 differentially methylated regions (DMRs) with a mean size of 255 bp (median of 11 CpGs), of which 97% were hypomethylated. These DMRs were distributed across the genome and were statistically associated with CpG dense regions, including annotated CpG islands and shores (islands: 1,104 of 2,782; 29.9%; shores: 1,118 of 2,782; 30.3%; P 〈 10-10), and gene promoters (816 of 2,782; 23.7%; P 〈 10-12). Analysis of chromatin accessibility data from 6 samples (3 DNMT3A R882H and 3 DNMT3A wild-type) showed that a subset of the DNMT3A R882H-associated hypomethylated DMRs (366 of 2,704; 13.5%) were located within 100 bp of an ATAC-seq peak unique to DNMT3A R882H AML samples. Further analysis of all DMRs showed ATAC-seq signal enrichment in the R882H samples specifically at hypomethylated loci (Figure 1). Similar enrichment was not observed in the DNMT3A wild-type AMLs at hypomethylated DMRs (N=78), suggesting that hypomethylation caused by the DNMT3A R882H mutation is specifically associated with changes in chromatin structure. Initial analysis of existing PolyA+ RNA-seq data for these AMLs did not reveal canonical expression changes in annotated genes located near the DMRs, implying that methylation and other epigenetic changes might affect distant genes or previously unannotated RNA species that were not present in our dataset. Efforts to sequence all RNA species present in these samples are therefore underway. In summary, we have conducted an initial analysis of genome-wide, CpG-resolution DNA methylation data from primary AML samples with the DNMT3A R882H mutation. This mutation is associated with a genome-wide, focal hypomethylation phenotype that occurs at small, CpG-dense loci across the genome. We also found that many hypomethylated loci are associated with changes in chromatin structure. These findings represent the first evidence that the methylation changes caused by this mutation can have functional consequences on the epigenetic state of specific loci in AML cells, and set the stage for defining the specific events that are responsible for AML pathogenesis in patients who have this mutation. Figure 1 WGBS (bottom tracks) and chromatin accessibility (ATAC-seq, top tracks) from 3 primary AML samples with the DNMT3A R882H mutation (in red) and 3 with no DNMT3A mutation (in blue) at a hypomethylated locus within the HS3ST3B1 gene. Figure 1. WGBS (bottom tracks) and chromatin accessibility (ATAC-seq, top tracks) from 3 primary AML samples with the DNMT3A R882H mutation (in red) and 3 with no DNMT3A mutation (in blue) at a hypomethylated locus within the HS3ST3B1 gene. Disclosures No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2014
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  • 8
    In: Blood, American Society of Hematology, Vol. 128, No. 22 ( 2016-12-02), p. 1050-1050
    Abstract: Altered DNA methylation is a well-known feature of acute myeloid leukemia (AML) genomes, but the mechanisms underlying these changes and their relevance for AML pathogenesis are unclear. We previously showed that DNMT3A is the predominant de novo methyltransferase expressed in AML cells, and that the DNMT3AR882H mutation in AML creates a dominant negative protein that reduces in vitro DNA methylation activity by ~80%. Since DNMT3A provides themajority of the methylation activity in AML cells, we hypothesized that AML samples with and without DNMT3AR882H could reveal novel insights about the role of this enzyme in AML initiation and progression. We performed whole-genome bisulfite sequencing (WGBS) of 38 primary human AML samples and 17 normal human hematopoietic cell samples, as well as a remission sample from a patient with a persistent DNMT3AR882H mutation, and blood samples from a non-leukemic patient with a constitutional DNMT3AR882H mutation. We first identified 3,848 differentially methylated regions ('DMRs') between DNMT3AR882H and DNMT3AWT AMLs, virtually all of which were hypomethylated in the DNMT3AR882H AMLs. Further, 28% (1,087/3,848) of these DMRs were also hypomethylated when compared to CD34 cells, implying that these regions are truly hypomethylated in the AML cells with the R882H mutation. In contrast, 72% (2,759/3,848) of the DMRs were unmethylated in bothDNMT3AR882H AMLs and CD34 cells, but were hypermethylated in the DNMT3AWT AML samples. These loci were associated with CpG dense regions, suggesting that they represent abnormal CpG island hypermethylation that occurs only in AML samples with wild-type DNMT3A. Analysis of 21 additional primary AML samples with wild-type DNMT3A identified 4,912 hypermethylated regions compared to CD34 cells, of which 4,544 (92%) were significantly less methylated in DNMT3AR882H AMLs, implying that functional DNMT3A mediates abnormal CpG island hypermethylation in AML. WGBS analysis of two non-leukemic hematopoietic samples with DNMT3AR882H mutations was also performed to understand the direct effects of DNMT3AR882H in non-transformed myeloid cells. These samples included peripheral blood (PB) neutrophils and monocytes from a newly identified 9-year old patient with an overgrowth syndrome and developmental delay (Tatton-Brown et. al., Nature Genetics 2014), who was found to have a heterozygous DNMT3AR882H mutation in all skin and peripheral blood cells. His CBC was normal, and he had no evidence of clonal hematopoiesis by exome sequencing. We identified 2,051 DMRs in his PB myeloid cells, all of which were hypomethylated compared to control PB myeloid cells from his healthy 13-year old brother (and also normal CD34 cells), demonstrating that DNMT3AR882H directly causes focal methylation loss. We also performed WGBS on cells expanded from single stem/progenitor cells from an AML patient with a persistent DNMT3AR882H mutation during remission. Expanded cells with DNMT3AR882H were hypomethylated relative to wild-type DNMT3A cells expanded from the same sample. The majority of the hypomethylated regions were also present in the patient's AML cells, implying that DNMT3AR882H-associated hypomethylation in pre-leukemic cells is maintained during AML progression. These findings demonstrate that DNMT3AR882H-associated hypomethylation precedes leukemia development, and may therefore represent an important initiating phenotype for AML. Our data also suggest that the abnormal hypermethylation of CpG islands in AML cells is DNMT3A-dependent, and must occur during disease progression. This hypermethylation is absent in AMLs with DNMT3AR882H, revealing that it is not required for leukemia progression. We therefore propose a model where DNMT3A-dependent DNA methylation in AML cells acts as a 'brake' that prevents abnormal self-renewal; the abnormal CpG island hypermethylation in DNMT3AWT AMLs may be an adaptive response that is ultimately overcome during leukemia progression. The absence of this 'braking' activity in AMLs with DNMT3AR882H may contribute directly to leukemia initiation. The restoration of DNMT3A activity in AML cells with the DNMT3AR882H mutation is therefore a therapeutic goal. Disclosures Spencer: Cofactor Genomics: Consultancy.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2016
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  • 9
    Online Resource
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    American Society of Hematology ; 2018
    In:  Blood Vol. 132, No. Supplement 1 ( 2018-11-29), p. 2775-2775
    In: Blood, American Society of Hematology, Vol. 132, No. Supplement 1 ( 2018-11-29), p. 2775-2775
    Abstract: We and others recently showed that the mutational spectrum of de novo pediatric myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) is different than those in adults. MDS and AML also occur in children as a consequence of cytotoxic therapies used to treat childhood malignancies and are collectively referred to as therapy-related myeloid neoplasms (tMN). The incidence of pediatric tMN is ~1% in the pediatric cancer population. These secondary malignancies are usually resistant to conventional chemotherapy and managed with hematopoietic cell transplantation (HCT). These patients have a dismal prognosis. TP53 mutations and somatic alterations in chromatin modifiers predominate in adults with tMN, yet whether children with tMN have a similar constellation of genetic alterations remains unclear since comprehensive genomic profiling has not been completed in a large pediatric tMN cohort. We hypothesize that the mutational profile of pediatric tMN will be different than adult tMN given the patients' younger age and the different spectrum of primary tumor types and chemotherapies. Here we describe the somatic mutational profile of pediatric tMN (including tMDS & tAML) using whole exome (WES) and RNA-sequencing. We evaluated 65 diagnostic bone marrow samples from 61 unique patients, obtained from the St. Jude Children's Research Hospital Tissue Bank from patients diagnosed between 1987 & 2018. The cohort contains 26 tMDS and 39 tAML cases; in 4 patients both tMDS and tAML samples were included. Primary tumors included hematological malignancies (n=45), bone and soft tissue solid tumors (n=14), and brain tumors (n=2); acute lymphoblastic leukemia (ALL) was the most common primary tumor (n = 38, 62%). WES was completed for 61 tumor/normal pairs using Nextera Rapid Capture Expanded Exome (Illumina), while WGS was completed on 4 pairs. Normal comparator genomic DNA was obtained from flow-sorted lymphocytes. Median sequencing coverage for the tumor and normal samples were 107x and 95x, respectively. An average of 49 variants/patient (range: 6-217) was observed in the tMN cohort, including coding, non-coding, silent, and splice site variants, which is significantly different than our previously reported 5 variants/patient in pediatric primary MDS (p = 1x10-6). There was not a significant difference in the number of mutations/patient when tMDS was compared to tAML. Mutational signature analysis (https://cancer.sanger.ac.uk/cosmic/signatures) identified 3 major signatures, the most predominant was characterized by a strong bias for C 〉 A mutations (Signature 24), followed by a signature with strong transcriptional strand bias for T 〉 A mutations (Signature 27) and then a smaller subset resembling MDS and AML (Signature 1). Interestingly, patients with Signature 1 had an inferior 2-year overall survival than the other mutational signatures, with a median survival of 0.3 years (p = 0.0005). WES data and conventional karyotyping showed that chromosome 7 deletions (del(7)) were frequent (n=21, 32%), followed by deletions involving chromosome 5 (del(5)) (n=10, 15%). All of the cases with del(5) had complex cytogenetics and 6 of the 10 cases also had del(7). Ras/MAPK pathway mutations were present in 37% of the cases (40 total mutations in 27 cases). Canonical KRAS (n = 14), NF1 (n = 8), and NRAS (n = 7) mutations were the most frequent coding mutations present overall. Only 5 patients had somatic TP53 mutations, all of which had complex karyotypes. RNA sequencing was performed on 55 samples with suitable RNA. KMT2A rearrangements (KMT2Ar) were common (n = 29, 53%), 4 of which were cytogenetically cryptic. KMT2A rearrangements were more common in tAML (n = 25) but were present in tMDS (n = 4). Nearly half of these KMT2Ar cases also harbored an additional Ras/MAPK mutation. Fusions involving NUP98, RUNX1, MECOM, and ETV6 were also detected. In conclusion, we show that the mutational profile of pediatric tMN has fewer TP53 mutations and more KMT2Ar than adults, as well as a unique set of mutational signatures. These differences are likely a reflection of age-specific chemotherapeutic strategies and fewer pre-existing TP53 mutant hematopoietic clones in children. Future studies understanding the clonal evolution of pediatric tMN development will be helpful in describing pediatric tMN further. Disclosures No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2018
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  • 10
    In: Blood, American Society of Hematology, Vol. 124, No. 21 ( 2014-12-06), p. 609-609
    Abstract: Somatic mutations in the DNA methyltransferase, DNMT3A, have been identified in & gt;30% of de novo AML cases with a normal karyotype, and in & gt;10% of patients with MDS and T-ALL. To understand whether mutations in DNMT3A alter hematopoietic development, we generated a transgenic mouse model capable of overexpressing either wild type human DNMT3A or the most common DNMT3A mutation found in AML cases (R882H, a hypomorphic variant that acts as a potent dominant negative inhibitor of WT DNMT3A, D. Germain et al., Cancer Cell 2014). Full-length human cDNAs encoding WT or R882H DNMT3A were cloned into a mammalian expression vector directly downstream from a tetracycline responsive element. This allows for the inducible expression of DNMT3A upon the expression of the rtTA coactivator, and the presence of Doxycycline (Dox). A single founder line for the WT DNMT3A allele, and two founder lines for the R882H DNMT3A allele, were established in the C57Bl6/J background. The WT DNMT3A transgene overexpressed 3.5x more human DNMT3A than endogenous murine DNMT3A in bone marrow cells; R882H DNMT3A transgenic line 1 expressed at a 4.5 fold excess, and R882H line 2 at a 16 fold excess. To determine whether overexpression of the R882H allele was associated with focal DNA hypomethylation in the bone marrow cells of mice (similar to that observed in human AML samples), we used a novel CpG capture approach with bisulfite sequencing to assess 200,000 genomic regions containing ~3 million CpGs in the bone marrow cells of 3 WT C57Bl6/J mice, 3 Dnmt3a null mice, and healthy transgenic mice noted above that had been on Dox chow for either 6 months or 1 year (transgenic mice do not develop hematopoietic malignancies even after one year of transgene induction). We were able to assess 1.6 million CpGs with 10X or greater coverage in all 14 samples. The Dnmt3a null marrow samples contained 188,367 differentially methylated CpGs (average of & gt;25% difference compared to WT bone marrow, q value= & lt;0.01). Of these, 187,093 were hypomethylated ( & gt;99%); the hypomethylated CpGs were nearly identical in all three samples. Marrow cells from the two mice overexpressing the WT DNMT3A gene had only 338 differentially methylated CpGs compared to two matched rtTA control mice; of these, 337 were hypermethylated ( & gt;99%). For the two mice overexpressing the R882H allele in line 2 (16x overexpression), bone marrow cells had 2,356 differentially methylated CpGs, of which 2,316 were hypomethylated (98%). Of these CpGs, 1,745 (73%) overlapped with hypomethylated CpGs in the Dnmt3a null marrow samples, indicating that R882H overexpression causes hypomethylation in a subset of CpGs whose methylation in bone marrow cells is Dnmt3a dependent. Because none of our mice developed hematologic malignancies even after one year, but had shown significant hypomethylation in the bone marrow, we hypothesized that cooperating mutations were necessary to produce malignancy. We transduced whole bone marrow cells from four transgenic mice: WT DNMT3A Tg x rtTA; R882H-1 Tg x rtTA; R882H-2 Tg x rtTA; and rtTA only (the same samples analyzed for methylation changes in the previous paragraph) with an MSCV-derived virus containing a human FLT3-ITD cDNA, and transplanted the transduced cells into 8-10 lethally irradiated recipients. Mice of all genotypes succumbed to myeloproliferative disease, T-cell lymphoma, T-lymphoma/ALL, or T-ALL. Overall median latencies were: rtTA=155 days, WT DNMT3A Tg x rtTA=164 days, R882H Tg-1 x rtTA=108.5 days, R882H-2 Tg x rtTA=135.5 days. The average latency for T cell malignancies demonstrated even greater differences among the four genotypes: rtTA n=4, 160.8 +/- 12.49 days (SEM), WT DNMT3A Tg x rtTA n=5, 167.3 +/- 4.854, R882H Tg-1 x rtTA n=3, 124.7 +/- 17.7, R882H-2 Tg x rtTA n=4 124.5 days +/- 22.14. T malignancies derived from R882H expressing cells were especially homogeneous compared to other groups; these tumors were CD4/CD8 double positive in all hematopoietic compartments. Despite the small sample size, these results demonstrate a trend towards a decreased latency for T malignancies in R882H expressing marrow cells, using a FLT3-ITD viral transduction model. We are confirming these data with additional mice. Taken together, our results demonstrate a clear focal hypomethyation phenotype in the bone marrow cells of DNMT3A R882H overexpressing mice, which may lead to increased susceptibility to neoplastic transformation. Disclosures No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2014
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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