- Email: [email protected]
DNMT3A R882 mutations in patients with cytogenetically normal acute myeloid leukemia and myelodysplastic syndrome
YBCMD-01794; No. of pages: 6; 4C: Blood Cells, Molecules and Diseases xxx (2014) xxx–xxx
Contents lists available at ScienceDirect
Blood Cells, Molecules and Diseases journal homepage: www.elsevier.com/locate/bcmd
DNMT3A R882 mutations in patients with cytogenetically normal acute myeloid leukemia and myelodysplastic syndrome Doaa El Ghannam a,⁎, Mona M. Taalab b, Hayam F. Ghazy c, Asmaa F. Eneen d a
Departments of Clinical Pathology, Faculty of Medicine, Mansoura University, Egypt Clinical Hematology Unit, Internal Medicine Department, Faculty of Medicine, Mansoura University, Mansoura, Egypt Medical Oncology Unit, Internal Medicine Department, Faculty of Medicine, Mansoura University, Mansoura, Egypt d Internal Medicine Department, Faculty of Medicine, Mansoura University, Mansoura, Egypt b c
a r t i c l e
i n f o
Article history: Submitted 31 December 2013 Revised 7 January 2014 Available online xxxx (Communicated by M. Lichtman, M.D., 07 January 2014) Keywords: DNMT3A Acute myeloid leukemia Myelodysplastic syndrome Oncogenes Leukemogenesis
a b s t r a c t Several molecular markers have been described that help to classify patients with acute myeloid leukemia (AML), a heterogeneous hematopoietic tissue neoplasm, into risk groups. We determined the frequency of DNMT3A mutations, their associations with clinical and molecular characteristics and outcome, in primary, cytogenetically-normal AML (CN-AML) and CN-myelodysplastic syndrome (MDS). A total of 63 CN-AML and 16 CN-MDS patients were analyzed for mutations in DNMT3A, codon R822 by direct sequencing and mutation of NPM1 and FLT3/ITD. DNMT3A mutations were found in 17/63 (27%) of CN-AML and in 1/16 (6.3%) of CNMDS patients. Patients with DNMT3A mutations were older (p = 0.047), had higher white blood cell (WBC) counts (p = 0.046), more often belonged to FAB groups M4 and M5 (p = 0.017), and were more associated with NPM1 mutations (p = 0.017), than those with wild-type DNMT3A. DNMT3A-mutated patients had shorter overall disease survival (p b 0.001) and disease-free survival (p = 0.014) when the entire patient cohort was considered, which remained significant in multivariate analysis. We conclude that DNMT3A R882 mutations are recurrent molecular aberrations in CN-AML, less frequent in CN-MDS, and that testing for R882 mutations may provide a useful tool for refining risk classification of CN-AML. Crown Copyright © 2014 Published by Elsevier Inc. All rights reserved.
Introduction Tumorigenesis is known to be a multistep process, which is the result of cellular genetic mutations and epigenetic changes [1]. The distinct components of epigenetic machinery such as DNA methylation, covalent modifications of histones, and noncoding RNAs have been described as controllers of gene expression and may contribute to leukemogenesis [2]. DNA methylation plays an essential role in development, differentiation, genomic stability, X-inactivation, and
Abbreviations: AML, acute myeloid leukemia; BMA, bone marrow aspiration; CD, cluster of differentiation; CI, confidence interval; CMML, chronic myelomonocytic leukemia; CN, cytogenetically normal; CR, complete remission; DFS, disease free survival; DNA, desoxypentosenucleic acid; DNMT, DNA methyltransferases; dNTP, deoxynucleoside triphosphate; FAB, French–American–British classification; FLT3/ITD, FMS-like tyrosine kinase 3 internal tandem duplication; Hb, hemoglobin; HDACs, histone deacetylases; HLA-DR, human leukocyte antigen DR; HMT, histone methyltransferase; HP1, heterochromatin protein; HR, hazard ratio; ID, induction death; MDS, myelodysplastic syndrome; MTase, methyltransferase; NPM1, nucleophosmin 1; OS, overall survival; PCR, polymerase chain reaction; PWWP, proline-tryptophan-tryptophan-proline; RA/RARS, refractory anemia/refractory anemia with ringed sideroblasts; RAEB, refractory anemia with excess blasts; RCMD/RCMD-RS, refractory cytopenia with multiple dysplasia/refractory cytopenia with multiple dysplasia with ringed sideroblasts; RD, refractory disease; SD, standard deviation; WBC, white blood cells; WT, wild type; ZNF, zinc finger. ⁎ Corresponding author. E-mail address: [email protected] (D. El Ghannam).
imprinting by specific regulation of gene expression [1]. DNA methylation occurs by an enzymatic addition of a methyl group at the carbon 5 position of cytosine in the context of cytosine-guanine dinucleotides [3]. The transfer of methyl groups from S-adenosylmethionine to cytosine is a heritable process that is catalyzed by several DNA methyltransferases (DNMTs) during cell replication [1]. There are at least three different DNMTs involved in cellular DNA methylation: DNMT1, DNMT3A, and DNMT3B [4]. DNMT1 is the most abundant and preferentially replicates existing DNA methylation patterns, whereas DNMT3A and DNMT3B are responsible for establishing de novo DNA methylation. All three DNMTs are constitutively expressed at different levels in most human tissues. Overexpression of DNMTs and its association with altered DNA methylation have been observed in tumors including leukemias [3]. DNMT3A contains three main structure domains: an ADD (ATRX, DNMT3, and DNMT3L)-type zinc finger (ZNF) domain, a PWWP (proline-tryptophan-tryptophan-proline) domain and the methyltransferase (MTase) domain [5]. The PWWP domain is responsible for targeting the enzyme to nucleic acid, while the ZNF domain mediates protein–protein interactions with the transcription factors Myc and RP58, the heterochromatin protein HP1, histone deacetylases (HDACs), and the histone methyltransferase (HMT) [6]. Mutations in DNMT3A have been identified in patients with AML, myelodysplastic syndromes (MDS), and myeloproliferative neoplasms
1079-9796/$ – see front matter. Crown Copyright © 2014 Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.bcmd.2014.01.004
Please cite this article as: D. El Ghannam, et al., Blood Cells Mol. Diseases (2014), http://dx.doi.org/10.1016/j.bcmd.2014.01.004
2
D. El Ghannam et al. / Blood Cells, Molecules and Diseases xxx (2014) xxx–xxx
Table 1 Patients' characteristics of the studied groups.
Data
CN-AML (n = 63)
Age (years)
mutations have been associated with a negative impact on overall survival (OS). Thol et al. [7] reported that DNMT3A mutations were associated with shorter overall survival (OS) in cytogenetically diverse patients with AML, who are younger than 60 years and with lower complete remission (CR) rates and shorter OS in a CN-AML subset. In this study we investigated the frequency and prognostic impact of DNMT3A mutations in a cohort of 63 CN-AML and 16 CN-MDS patients and analyzed its interaction with other prognostic markers.
CN-MDS (n = 16)
47.1 ± 10.
64.2 ± 9.2
Males
35 (55.6%)
11 (68.8%)
Females
28 (44.4%)
5 (31.3%)
73.4 ± 58.6
5.28 ± 2.0
Sex 9
TLC (×10 /l) Hb (g/dl) 9
Platelets (×10 /l)
8.5 ± 2.4
7.3 ± 1.7
138 ± 167
64.4 ± 34.8
Blasts (%)
70 ± 21
FAB
Patients and methods Patients
7.1 ± 5.2
M1:
14 (22.2%)
RA/RARS:
2 (12.5%)
M2:
14 (22.2%)
RCMD/RCMD-RS:
6 (37.5%)
M4:
15 (23.8%)
RAEB-1:
4 (25.0%)
M5:
14 (22.2%)
RAEB-2:
4 (25.0%)
M6:
6 (9.5%)
CMML:
0 (0%)
TLC: total leucocytic count, Hb: hemoglobin concentration, RAEB: refractory anemia with excess blasts. Age, TLC, Hb, platelets and blasts were presented by mean ± SD. Sex and FAB subtypes were presented by number and percentages.
(MPN) [7–11]. In AML, all three DNMT enzymes are reportedly overexpressed in malignant blasts compared with normal marrow (BM) cells and contribute to leukemogenesis by mediating tumor suppressor gene silencing [3]. Preliminary data show that the incidence of these mutations in AML ranges from 4.1% in a Japanese study [12], 9% in a study with Chinese patients [13], and about 15–25% in Western studies [7,8,14,15]. These possible ethnogeographic differences in the incidence of DNMT3A mutations should be better characterized. Eighteen different mutations were found in these studies, most of them missense mutations. The majority of mutated DNMT3A (DNMT3A) is located in exon 23. The “hotspot” mutation occurs at the amino position 882, resulting in the replacement of arginine by histidine (R882H), cysteine (R882C), serine (R882S), or phenylalanine (R882P) [16]. The exact mechanisms by which DNMT3A mutations act in AML are still unclear, since the global pattern of methylation in the genome of such patients with AML does not appear to be significantly changed [8]. Less is known about the frequency and the prognostic impact of DNMT3A mutations in MDS. However, one study suggests that mutations are less frequent than in AML [11]. Ley et al. [8] first reported that DNMT3A
We have studied 63 marrow samples from CN-AML patients at diagnosis and prior to any chemotherapy. They were 35 males and 28 females with mean age, 47.08 ± 10.00 years. Marrow samples from 16 patients with CN-myelodysplastic syndrome (mean age, 64.19 ± 9.17 years) were also analyzed. To analyze the incidence of DNMT3A mutations in healthy controls, blood samples from 20 healthy blood donors (18 to 60 years of age) were obtained from the Institute of blood transfusion center. Patients with antecedent hematologic diseases or therapy-related AML were excluded. Diagnosis and classification of AML and MDS were made according to the French–American–British (FAB) Cooperative Group Criteria (Table 1). This study was approved by the institutional review board of Mansoura University, and written informed consent was obtained from all participants from October 2012 to March 2013.
Treatment protocol AML patients received the standard ‘3 + 7’ induction chemotherapy protocol: doxorubicin (45 mg/m2/day) for 3 days and cytarabine (100 mg/m2/day as a continuous 24 h intravenous infusion) for 7 days [17]. Marrow aspiration was done between 21 and 28 days after initiation of chemotherapy to demonstrate morphological remission. Consolidation comprised three to four courses of high-dose cytosine arabinoside (3 g/m2 every 12 h on days 1, 3 and 5; total, 18 g/m2). Patients were followed once every 3 months with clinical examination and complete blood cell counts. Marrow examination was done if there was any doubt of a relapse on clinical examination or blood smear. Patients with MDS were treated with azacitidine (75 mg/m2/d subcutaneously for 7 days every 28 days) for 4 months [18].
Table 2 The DNMA3A mutation patterns in CN-AML and CN-MDS patients. Code
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Age
55 52 33 59 59 51 47 54 54 46 59 56 46 46 51 55 47 58
Sex
Female Male Male Male Male Female Female Female Female Female Female Female Male Male Male Male Male Male
TLC
85.0 48.0 80.0 115.0 115.0 75.0 85.0 62.0 62.0 88.0 70.0 56.0 84.5 84.5 80.0 130.0 220.0 56
FAB
M5 M4 M2 M6 M6 M5 M4 M5 M5 M4 M4 M5 M5 M5 M2 M4 M4 RAEB1
DNMT3A mutation Location
DNA change
Protein change
23 23 23 23 23 23 23 23 23 23 13 23 23 23 23 8 23 23
c.2645C N A c.2646G N A c.2646G N A c.2645C N T c.2645C N T c.2646G N A c.2645C N T c.2646G N A c.2646G N A c.2645C N T 1477delA c.2646G N A c.2646G N A c.2646G N A c.2645C N T 958CT c.2646G N A c.2646G N A
p.R882S p.R882H p.R882H p.R882C p.R882C p.R882H p.R882C p.R882H p.R882H p.R882C p.R882H p.R882H p.R882H p.R882H p.R882C p.R882C p.R882H p.R882H
Chemo-response
Result
RD CR CR CR CR ID ID CR CR RD CR CR ID CR CR CR CR –
Died Alive Alive Alive Alive Died Died Alive Alive Alive Died Alive Died Died Alive Alive Alive Alive
CR: complete remission; ID: induction death; RD: refractory disease.
Please cite this article as: D. El Ghannam, et al., Blood Cells Mol. Diseases (2014), http://dx.doi.org/10.1016/j.bcmd.2014.01.004
D. El Ghannam et al. / Blood Cells, Molecules and Diseases xxx (2014) xxx–xxx
3
Fig. 1. Sequences of the mutated DNMT3A R882. A: wild type sequence; B: R882C mutation; C: R882H mutation. Mutations are indicated with black arrows and yellow background. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
94 °C for 30 s, annealing at 59 °C for 30 s, and an extension at 72 °C for 30 s.
Cytogenetic analysis Pretreatment cytogenetic analyses of marrow or blood were performed by G-banding technique and karyotyped according to the International System for Human Cytogenetic Nomenclature. A minimum of 20 metaphases was required to be examined for a patient to be classified as having normal cytogenetics [19].
Immunophenotype analysis A panel of mAbs to myeloid-associated antigens, including CD13, CD33, CD11b, CD15, CD14, and CD41a, as well as lymphoid-associated antigens, including CD2, CD5, CD7, CD19, CD10, and CD20, and lineage nonspecific antigens HLA-DR, CD34, and CD56, were used to characterize the phenotypes of the leukemia cells, as described previously [19].
Automated sequencing of codon R882 By using ABI prism 310 genetic analyzer Version 2.0 (Applied Biosystems, Foster City, USA) with 50 cm capillaries and POP6 polymer (Applied Biosystems). Cycle sequencing was carried on PCR products labeled with 3.2 pmol of the forward primer using Big Dye Terminator ready reaction kit with total volume of 20 μL. The reaction mix was prepared following the instructions provided by the manufacturer. Twenty-five cycles of denaturation, annealing, and extension at 94 °C for 10 s, 55–62 °C for 5 s, and 60 °C for 4 min were carried out. Purification of the products was done to remove excess dye by isopropanol before electrophoresis on the ABI Prism 310 genetic analyzer. Electropherograms were compared to the reference sequence (NM 022552). Altered sequencing results were confirmed by reverse strand sequencing.
DNMT3A mutation analysis DNA isolation and polymerase chain reaction Genomic DNA was extracted from marrow cell samples using QIA amp DNA kit for DNA extraction provided by QIAGEN (Quiagen Inc., Chatsworth, CA, USA). DNA fragment spanning the codon R882 (exon 23) was amplified by polymerase chain reaction (PCR) using the following primers: 5′-TTTGGTTTCCCAGTCCACTATAC-3′ (forward), and 5′CCAGCAGTCTCTGCCTC-3′ (reverse). PCR was performed in 25-mL volume in the presence of 1 × PCR buffer (Invitrogen, Merelbeke, Belgium), 0.2 mmol/L of each dNTP, 2.5 mmol/L of MgCl2, 0.4 mmol/L of both forward and reverse primers, 1 U Taq polymerase (MBI Fermentas, Canada), and 50 ng genomic DNA. PCR reactions were carried out on a 7000 Thermo cycler (Applied Biosystems, Foster City, CA, USA). The temperature cycling protocol consisted of an initial denaturation step at 95 ºC for 5 min, followed by 40 cycles of denaturation at
Screening of NPM1 gene mutation and FLT3/ITD For NPM1mutation analysis, NPM1 exon-12 was amplified by genomic PCR using primers NPM1 11f: 5′-CTGGTAGAATGAAAAATAGAT-3′ (6 FAM labeled), and NPM1 12r: 5′-CTTGGCAATAGAACCTGGAC-3′ (Applied Biosystems, USA). PCR reactions were performed in a total volume of 25 μL containing 20–50 ng of extracted DNA (1 μl), 10 pmol of each primer (Applied Biosystems), 12.5 mL of Maxima hot start PCR master mix 2 × (Thermo Scientific) (containing Maxima hot Taq DNA polymerase, hot start PCR buffer, 400 μM of each dNTP, and 4 mM Mg + 2), and the reaction was completed to 25 mL using molecular grade water. The amplification was carried out in a GeneAmp PCR System 9700 (Applied Biosystems, Foster City, CA) using the following steps: preactivation at 95 °C for 4 min, 35 cycles at 94 °C for 30 s, 56 °C for 30 s and 72 °C for 60 s, and post extension steps; 94 °C for 30 s and 60 °C for 45 s.
Table 3 DNMT3A mutations according to patients' characteristics. CN-AML (n = 63) Age (years) Sex TLC (X109/L) Hb (g/dL) Platelets (X109/L) Blasts (%) FAB FLT3/ITD NPM1 Low risk High risk
Males Females
M1, M2, M6 M4, M5
DNMT3A-mutated (n = 17)
DNMT3A-wild (n = 46)
p
51.2 ± 6.6 9 (52.9%) 8 (47.1%) 97.5 ± 44 8.3 ± 2.8 132 ± 134. 73. ± 24. 0 (0%), 3 (17.6%), 2 (11.8%) 6 (35.3%), 6 (35.3%) 5 (29.4%) 9 (52.9%) 5 (29.4%) 12 (70.6%)
45.6 ± 11. 26 (56.5%) 20 (43.5%) 64.5 ± 61 8.5 ± 2.3 140 ± 180 69 ± 21 14 (30.4%), 11 (23.9%), 4 (8.7%) 9 (19.6%), 8 (17.4%) 8 (17.4%) 10 (21.7%) 7 (15.2%) 39 (84.8%)
0.047 0.800
Age, TLC, Hb, platelets and blasts are presented by mean ± SD. Sex and FAB are presented by number and percentages.
Please cite this article as: D. El Ghannam, et al., Blood Cells Mol. Diseases (2014), http://dx.doi.org/10.1016/j.bcmd.2014.01.004
0.046 0.780 0.869 0.572 0.017 0.295 0.017 0.203
4
D. El Ghannam et al. / Blood Cells, Molecules and Diseases xxx (2014) xxx–xxx
Results Prevalence and spectrum of DNMT3A mutations Missense mutations of DNMT3A exon 23 (R882) were identified in 17 CN-AML (27%) and 1 (6.3%) CN-MDS patients. The most common mutation was R882H (n = 11; 61.1%), followed by R882C (n = 6; 33.3%), and R882S (n = 1; 5.6%). R882 mutations were not present in healthy controls (Table 2, Fig. 1). Correlation of DNMT3A mutations with patient characteristics and other molecular abnormalities
Fig. 2. Overall survival according to DNMT3A mutations in CN-AML patients.
To detect FLT3/ITD, exon-14 and exon-15 were amplified using primers 11f (5′ GCAATTTAGGTATGAAAGCCAGC-3′), and 12r (5′-CTTT CAGCATTTTGACGGCAACC-3′) (Applied Biosystems, USA). PCR reactions were performed in a total volume of 25 μL containing the same contents used as in the NPM1 PCR above apart from FLT3 primers. The amplification was carried out in a GeneAmp PCR System 9700 (Applied Biosystems, Foster City, CA) using the following steps: preactivation at 95 °C for 4 min, 30 cycles at 95 °C for 30 s, 62 °C for 30 s and 72 °C for 30 s, and final extension at 72 °C for 5 min. Statistical Methods The statistical analysis of data was done by using Excel program and SPSS (statistical package for social science) program (SPSS, Inc, Chicago, IL) version 16. Kolmogorov–Smirnov test was done to test the normality of data distribution. Significant data was considered to be nonparametric. Qualitative data were presented as frequency and percentage. Chi square test was used to compare groups. Quantitative data were presented as mean and standard deviation. For comparison between two groups, Student's t-test, and Mann–Whitney test (for non parametric data) were used. Kaplan–Meier test was used for survival analysis and the statistical significance of differences among curves was determined by log-rank test. The Cox proportional hazard regression model was chosen to assess the independent prognostic factor affecting overall survival. N.B.: p is significant if ≤0.05 at confidence interval of 95%
We evaluated the correlation of clinical and genetic characteristics with DNMT3A mutations in all patients (Table 3). CN-AML patients who harbored a mutation in DNMT3A were older (p = 0.047), had higher white blood cell (WBC) counts (p = 0.046) at diagnosis and more frequently belonged to FAB groups M4 and M5 (p = 0.017), as compared with DNMT3A wild- type. To investigate the interaction of gene mutations in the pathogenesis of adult AML, mutational screening of NPM1 and FLT3 genes was performed in all patients. Among the studied cohort, 32 (50.8%) showed additional molecular abnormalities at diagnosis. NPM1 mutations (NPM1) were more common among DNMT3A mutated than in DNMT3A-WT patients (52.9% vs 21.7%; p = 0.017). There was no significant difference in the incidence of FLT3-ITD, among patients with DNMT3A mutation as compared with DNMT3A-WT (29.4% vs 17.4%; p = 0.29). Patients were then subdivided into high (presence of FLT3-ITD regardless of NPM1 status or the absence of FLT3-ITD and NPM1-WT) and low (absence of FLT3-ITD and NMP1-mutated)-molecular-risk groups. Impact of DNMT3A mutation on response to therapy and clinical outcome Of the 63 CN-AML patients undergoing conventional intensive induction chemotherapy, 43 (68.3%) achieved complete remission (CR). The probability of achieving CR was similar between patients with and without DNMT3A mutations (70.6% vs 67.4%, p = 0.81). However, the patients with DNMT3A mutations had a trend of higher relapse rate than those without (41.2% vs 23.9%; p = 0.17). With a median follow-up of 17 months (range, 0.1–32), patients harboring DNMT3A mutations had shorter OS (14.6 vs 28.0; p b 0.001) and DFS (13.8 vs 24.2 months; p = 0.014) than DNMT3A-WT patients (Figs. 2, 3). We also observed that NPM1/FLT3 high-risk group with mutated DNMT3A had a significantly shorter OS (14.1 vs 27.7 months; p b 0.001) and DFS (11.1 vs 23.6 months; p b 0.001) compared with patients with wild-type DNMT3A. However, no significant prognostic effects were found when analyzing the influence of DNMT3A mutations in NPM1/FLT3 low-risk group (OS: 15.0 vs 27.7 months; p = 0.16, DFS: 15.2 vs 26.0 months; p = 0.19) (Table 4, Figs. 4, 5). In multivariate Cox proportional hazards regression analyses after adjusting for other known prognostic factors such as age, total leukocyte count (TLC), hemoglobin, platelet count, blast %, FLT3-ITD and NPM1 risk status and DNMT3A mutations. DNMT3A mutations remained an independent adverse prognostic marker for OS (HR: 3.3; 95% CI: 2.7 to 9.0; p = 0.001) and DFS (HR: 5.4; 95% CI: 3.3 to 9.2; p b 0.001) (Table 5). Discussion
Fig. 3. Disease-free survival according to DNMT3A mutations in CN-AML patients.
In light of recently detected new molecular factors, a refinement of the existing classifications by adding new factors will hopefully enable us to specify prognostic statements, prospectively evaluate the impact of different treatments on long-term outcomes, and establish predictive factors for individually tailored treatment options and improvement of survival in all patients with AML.[20] The rate of R882 mutations (27%) in our patients was lower than the report of Ley et al. [8] (22.1%
Please cite this article as: D. El Ghannam, et al., Blood Cells Mol. Diseases (2014), http://dx.doi.org/10.1016/j.bcmd.2014.01.004
D. El Ghannam et al. / Blood Cells, Molecules and Diseases xxx (2014) xxx–xxx
5
Table 4 Overall and disease free survival according to DNMT3A mutation status in good and poor prognostic groups in AML patients. FLT3 NPM1 Risk status
Low High
Survival
OS DFS OS DFS
DNMT3A-mutated (n = 17)
DNMT3A-wild (n = 46)
Cumulative survival (%)
Mean (months)
CI 95%
73.9 64.6 45.5 27.3
15.0 15.2 14.1 11.1
6.9 8.8 8.9 9.2
23.0 21.6 19.2 12.9
p Log-rank (Mantel–Cox)
Cumulative Survival (%)
Mean (months)
CI 95%
66.7 50.0 66.7 75.0
27.6 26.0 27.6 23.5
25.5 23.2 25.3 21.0
29.8 28.7 29.9 26.0
0.157 0.186 b0.001 b0.001
Cumulative survival: cumulative proportion surviving at 24 months. CI 95%: confidence interval at 95%, OS: overall survival. DFS: disease-free survival.
for total AML patients and 36.7% for CN-AML patients) and similar to those of Thol et al. [7] (27.2% in CN-AML patients). Hou et al. [21] reported an incidence of 22.9% in CN-AML. Yamashita et al. [22] reported a low incidence of DNMT3A mutations in a Japanese population (4.1%). The differences in patient populations could be related to ethnic background and methods used. The catalytic activity of DNMT3A protein relies on the methyl transferase (MTase) domain, which contains ten blocks of conserved amino acid motifs [23,24]. The R882 residue, located in front of motif X [24,25], participates in the homodimerization and activation of the protein [26]. Mutations at R882 residue inhibit both DNA binding and catalytic activity [22,23]. However, it is possible that R882 mutations alter functions of DNMT3A that are not yet fully understood, including its ability to bind to other proteins involved in transcriptional regulation and localization to chromatin regions containing methylated DNA [27–30]. DNMT3A R882 mutations were more prevalent at older age in accordance with others' findings [16] and associated with significantly increased blood leukocyte number at diagnosis compared to the patients without this mutation, which is in agreement with this finding as reported in other studies [8,12,13,16,31,32]. Furthermore, DNMT3A R882 mutations were found more frequently in monoblastic leukemia compared to other phenotypes. This result further confirmed the specificity of DNMT3A R882 mutations in monocytic lineage [8,13]. Survival analysis of DNMT3A mutated compared with wild-type patients in all investigated patients with CN-AML showed a negative prognostic effect of DNMT3A mutations for OS and DFS that remained significant in multivariate analysis after adjusting for other known prognostic factors. This finding indicates that DNMT3A mutations are probably relevant to the pathogenesis of AML. Similarly, Ley et al. [8] and Thol et al. [7] found that in the CN-AML subgroup, DNMT3A mutations were associated with a lower CR rate and shorter OS in multivariable analyses. Our results differ from those reported by Marcucci et al. [33], who found no significant association between, R882-DNMT3A mutations and DFS or OS in younger patients.
The primary goal of our analysis was to evaluate the impact of DNMT3A mutations on patient outcome such as, OS and DFS, in a uniformly treated cohort of patients with AML in the context of other known prognostic markers. Mutations of NPM1/FLT3 genes have been described in these patients, and patients with mutated NPM1 in the absence of FLT3-ITD have been identified as a favorable risk group [34]. Interestingly, DNMT3A mutations have no prognostic effect on low-risk patients, while it confers a negative prognosis on the high-risk group (FLT3-ITD or wild-type NPM1/wild-type FLT3). Ley et al. [8] had similar results in that DNMT3A mutations were associated with shorter OS, specifically in patients with FLT3-ITD. The reason for the selective prognostic effect of DNMT3A mutations in NPM1/ FLT3 high-risk patients is unclear. This may be contributed to by the differences in disease biology of NPM1/FLT3 high-risk and low-risk patients that may provide a different molecular context in which mutated DNMT3A may have different effects. First, it is known that NPM1mutated AML is mostly negative for the stem-cell marker CD34 [35], whereas NPM1 wild-type patients mostly express CD34. Second, NPM1-mutated AML is rather sensitive to differentiation-inducing agents [36] in contrast to NPM1 wild-type AML. These data suggest that NPM1-mutated AML originates at or has characteristics of a more differentiated stage of hematopoiesis that is more susceptible to current treatment protocols than NPM1 wild-type patients. R882 mutation was also identified in one CN-MDS patient (RAEB). The mutation rate of 2.6% in our study is lower than the reported mutation rate of 8.0% by Walter et al. [11]. Our data demonstrate that DNMT3A mutations are present in myeloid malignancies other than AML. However, in CN-MDS the frequency of the mutation is significantly lower than in AML. The patient with this mutation had a shorter overall survival than patients without as confirmed from Walter et al. [11]. The low frequency of DNMT3A mutations in MDS did not allow any formal assessment of clinical and molecular associations or prognostic evaluation, but our data suggest a possible negative prognostic impact, as already described for mutations in CN-AML as patients with the mutations had a shorter overall survival and more frequently progressed to
Fig. 4. Overall survival according to DNMT3A mutations in high-risk group.
Fig. 5. Disease-free survival according to DNMT3A mutations in high-risk group.
Please cite this article as: D. El Ghannam, et al., Blood Cells Mol. Diseases (2014), http://dx.doi.org/10.1016/j.bcmd.2014.01.004
6
D. El Ghannam et al. / Blood Cells, Molecules and Diseases xxx (2014) xxx–xxx
Table 5 Multivariate analysis for overall and disease-free survival in AML patients. Overall-survival
Disease-free survival
Covariates
p
HR
95% CI
p
HR
95% CI
Age (years) TLC (x109/L) Hemoglobin (g/dL) Platelets Blasts (%) FLT3 and NPM1 risk status DNMT mutation
0.588 0.807 0.174 0.207 0.581 0.187 0.001
1.01 1.00 1.20 1.00 1.00 2.51 3.26
0.96 0.99 0.92 0.99 0.98 0.54 2.70
0.80 0.38 0.39 0.74 0.97 0.093 b0.001
0.99 1.00 1.11 1.00 1.00 3.88 5.38
0.93 0.99 0.86 0.99 0.97 0.746 3.32
1.07 1.01 1.58 1.00 1.03 5.71 8.98
1.05 1.01 1.44 1.00 1.02 7.43 9.22
AML. Thus, DNMT3A mutations might be involved in the progression of the disease. Conflict of interest The authors report no conflict of interest. References [1] M. Esteller, Epigenetics in cancer, N. Engl. J. Med. 358 (2008) 1148–1159. [2] P.A. Jones, S.B. Baylin, The epigenomics of cancer, Cell 128 (23 2007) 683–692. [3] S. Mizuno, T. Chijiwa, T. Okamura, K. Akashi, Y. Fukumaki, Y. Niho, H. Sasaki, Expression of DNA methyltransferases DNMT1, 3A, and 3B in normal hematopoiesis and in acute and chronic myelogenous leukemia, Blood 97 (2001) 1172–1179. [4] A. Pezzi, L. Moraes, V. Valim, B. Amorin, G. Melchiades, F. Oliveira, M.A. da Silva, U. Matte, M.S. Pombo-de-Oliveira, R. Bittencourt, L. Daudt, L. Silla, DNMT3A mutations in patients with acute myeloid leukemia in South Brazil, Adv. Hematol. (2012) 697691. [5] C. Brenner, F. Fuks, DNA methyltransferases: facts, clues, mysteries, Curr. Top. Microbiol. Immunol. 301 (2006) 45–66. [6] T. Chen, E. Li, Establishment and maintenance of DNA methylation patterns in mammals, Curr. Top. Microbiol. Immunol. 301 (2006) 179–201. [7] F. Thol, F. Damm, A. Lüdeking, C. Winschel, K. Wagner, M. Morgan, H. Yun, G. Göhring, B. Schlegelberger, D. Hoelzer, M. Lübbert, L. Kanz, W. Fiedler, H. Kirchner, G. Heil, J. Krauter, A. Ganser, M. Heuser, Incidence and prognostic influence of DNMT3A mutations in acute myeloid leukemia, J. Clin. Oncol. 20 (29) (2011) 2889–2896. [8] T.J. Ley, L. Ding, M.J. Walter, M.D. McLellan, T. Lamprecht, D.E. Larson, C. Kandoth, J.E. Payton, J. Baty, J. Welch, C.C. Harris, C.F. Lichti, R.R. Townsend, R.S. Fulton, D.J. Dooling, D.C. Koboldt, H. Schmidt, Q. Zhang, J.R. Osborne, L. Lin, M. O'Laughlin, J.F. McMichael, K.D. Delehaunty, S.D. McGrath, L.A. Fulton, V.J. Magrini, T.L. Vickery, J. Hundal, L.L. Cook, J.J. Conyers, G.W. Swift, J.P. Reed, P.A. Alldredge, T. Wylie, J. Walker, J. Kalicki, M.A. Watson, S. Heath, W.D. Shannon, N. Varghese, R. Nagarajan, P. Westervelt, M.H. Tomasson, D.C. Link, T.A. Graubert, J.F. DiPersio, E.R. Mardis, R.K. Wilson, DNMT3A mutations in acute myeloid leukemia, N. Engl. J. Med. 363 (2010) 2424–2433. [9] M.Y. Shah, J.D. Licht, DNMT3A mutations in acute myeloid leukemia, Nat. Genet. 43 (2011) 289–290. [10] F. Stegelmann, L. Bullinger, R.F. Schlenk, P. Paschka, M. Griesshammer, C. Blersch, S. Kuhn, S. Schauer, H. Döhner, K. Döhner, DNMT3A mutations in myeloproliferative neoplasms, Leukemia 25 (2011) 1217–1219. [11] M.J. Walter, L. Ding, D. Shen, J. Shao, M. Grillot, M. McLellan, R. Fulton, H. Schmidt, J. Kalicki-Veizer, M. O'Laughlin, C. Kandoth, J. Baty, P. Westervelt, J.F. DiPersio, E.R. Mardis, R.K. Wilson, T.J. Ley, T.A. Graubert, Recurrent DNMT3A mutations in patients with myelodysplastic syndromes, Leukemia 25 (2011) 1153–1158. [12] J.K. Cowell, L. Hawthorn, The application of microarray technology to the analysis of the cancer genome, Curr Mol Med. 7 (2007) 103–120. [13] X.J. Yan, J. Xu, Z.H. Gu, C.M. Pan, G. Lu, Y. Shen, J.Y. Shi, Y.M. Zhu, L. Tang, X.W. Zhang, W.X. Liang, J.Q. Mi, H.D. Song, K.Q. Li, Z. Chen, S.J. Chen, Exome sequencing identifies somatic mutations of DNA methyltransferase gene DNMT3A in acute monocytic leukemia, Nat. Genet. 43 (2011) 309–315. [14] A.F. Ribeiro, M. Pratcorona, C. Erpelinck-Verschueren, V. Rockova, M. Sanders, S. Abbas, M.E. Figueroa, A. Zeilemaker, A. Melnick, B. Löwenberg, P.J. Valk, R. Delwel, Mutant DNMT3A: a marker of poor prognosis in acute myeloid leukemia, Blood 119 (2012) 5824–5831. [15] J.P. Patel, M. Gönen, M.E. Figueroa, H. Fernandez, Z. Sun, J. Racevskis, P. Van Vlierberghe, I. Dolgalev, S. Thomas, O. Aminova, K. Huberman, J. Cheng, A. Viale, N.D. Socci, A. Heguy, A. Cherry, G. Vance, R.R. Higgins, R.P. Ketterling, R.E. Gallagher, M. Litzow, M.R. van den Brink, H.M. Lazarus, J.M. Rowe, S. Luger, A. Ferrando, E. Paietta, M.S. Tallman, A. Melnick, O. Abdel-Wahab, R.L. Levine, Prognostic relevance of integrated genetic profiling in acute myeloid leukemia, N. Engl. J. Med. 366 (2012) 1079–1089.
[16] J. Lin, D.M. Yao, J. Qian, Q. Chen, W. Qian, Y. Li, J. Yang, C.Z. Wang, H.Y. Chai, Z. Qian, G.F. Xiao, W.R. Xu, Recurrent DNMT3A R882 mutations in Chinese patients with acute myeloid leukemia and myelodysplastic syndrome, PLoS One 6 (2011) e26906. [17] J. Greer, M. Baer, M. Kinnery, Acute myelogenous leukemia, in: G. Lee, J. Foester, J. Leukens, F. Pareskerva, J. Greer, G. Rogers (Eds.), Wintrobe's Clinical Hematology, 12th ed., Lippincott Williams and Wilkins, Philadelphia, 2009, pp. 2045–2062. [18] L.R. Silverman, J.F. Holland, R.S. Weinberg, B.P. Alter, R.B. Davis, R.R. Ellison, E.P. Demakos, C.J. Cornell Jr., R.W. Carey, C. Schiffer, Effects of treatment with 5-azacytidine on the in vivo and in vitro hematopoiesis in patients with myelodysplastic syndromes, Leukemia 7 (Suppl. 1) (1993) 21–29. [19] Guidelines for cancer cytogenetics, in: F. Mittelmann (Ed.), Supplement to An International System for Human Cytogenetic Nomenclature, Karger, Basel, Switzerland, 1995. [20] C. Röllig, M. Bornhäuser, C. Thiede, F. Taube, M. Kramer, B. Mohr, W. Aulitzky, H. Bodenstein, H.J. Tischler, R. Stuhlmann, U. Schuler, F. Stölzel, M. von Bonin, H. Wandt, K. Schäfer-Eckart, M. Schaich, G. Ehninger, Long-term prognosis of acute myeloid leukemia according to the new genetic risk classification of the European Leukemia Net recommendations: evaluation of the proposed reporting system, J. Clin. Oncol. 29 (2011) 2758–2765. [21] H.A. Hou, Y.Y. Kuo, C.Y. Liu, W.C. Chou, M.C. Lee, C.Y. Chen, L.I. Lin, M.H. Tseng, C.F. Huang, Y.C. Chiang, F.Y. Lee, M.C. Liu, C.W. Liu, J.L. Tang, M. Yao, S.Y. Huang, B.S. Ko, S.C. Hsu, S.J. Wu, W. Tsay, Y.C. Chen, H.F. Tien, DNMT3A mutations in acute myeloid leukemia: stability during disease evolution and clinical implications, Blood 119 (2012) 559–568. [22] Y. Yamashita, J. Yuan, I. Suetake, H. Suzuki, Y. Ishikawa, Y.L. Choi, T. Ueno, M. Soda, T. Hamada, H. Haruta, S. Takada, Y. Miyazaki, H. Kiyoi, E. Ito, T. Naoe, M. Tomonaga, M. Toyota, S. Tajima, A. Iwama, H. Mano, Array-based genomic resequencing of human leukemia, Oncogene 29 (2010) 3723–3731. [23] H. Gowher, P. Loutchanwoot, O. Vorobjeva, V. Handa, R.Z. Jurkowska, T.P. Jurkowski, A. Jeltsch, Mutational analysis of the catalytic domain of the murine Dnmt3a DNA-(cytosine C5)-methyltransferase, J. Mol. Biol. 357 (2006) 928–941. [24] J. Turek-Plewa, P.P. Jagodziński, The role of mammalian DNA methyltransferases in the regulation of gene expression, Cell. Mol. Biol. Lett. 10 (2005) 631–647. [25] D. Jia, R.Z. Jurkowska, X. Zhang, A. Jeltsch, X. Cheng, Structure of Dnmt3a bound to Dnmt3L suggests a model for de novo DNA methylation, Nature 449 (7159) (2007) 248–251. [26] T. Deng, Y. Kuang, L. Wang, J. Li, Z. Wang, J. Fei, An essential role for DNA methyltransferase 3a in melanoma tumorigenesis, Biochem. Biophys. Res. Commun. 387 (2009) 611–616. [27] E. Hervouet, F.M. Vallette, P.F. Cartron, Dnmt3/transcription factor interactions as crucial players in targeted DNA methylation, Epigenetics 4 (2009) 487–499. [28] Y.A. Wang, Y. Kamarova, K.C. Shen, Z. Jiang, M.J. Hahn, Y. Wang, S.C. Brooks, DNA methyltransferase-3a interacts with p53 and represses p53-mediated gene expression, Cancer Biol. Ther. 4 (2005) 1138–1143. [29] C. Brenner, R. Deplus, C. Didelot, A. Loriot, E. Viré, C. De Smet, A. Gutierrez, D. Danovi, D. Bernard, T. Boon, P.G. Pelicci, B. Amati, T. Kouzarides, Y. de Launoit, L. Di Croce, F. Fuks, Myc represses transcription through recruitment of DNA methyltransferase corepressor, EMBO J. 24 (2005) 336–346. [30] P.A. Jones, G. Liang, Rethinking how DNA methylation patterns are maintained, Nat. Rev. Genet. 10 (2009) 805–811. [31] J. Marková, P. Michková, K. Burčková, J. Březinová, K. Michalová, A. Dohnalová, J.S. Maaloufová, P. Soukup, A. Vítek, P. Cetkovský, J. Schwarz, Prognostic impact of DNMT3A mutations in patients with intermediate cytogenetic risk profile acute myeloid leukemia, Eur. J. Haematol. 88 (2012) 128–135. [32] F. Thol, C. Winschel, A. Lüdeking, H. Yun, I. Friesen, F. Damm, K. Wagner, J. Krauter, M. Heuser, A. Ganser, Rare occurrence of DNMT3A mutations in myelodysplastic syndromes, Haematologica 96 (2011) 1870–1873. [33] G. Marcucci, K.H. Metzeler, S. Schwind, H. Becker, K. Maharry, K. Mrózek, M.D. Radmacher, J. Kohlschmidt, D. Nicolet, S.P. Whitman, Y.Z. Wu, B.L. Powell, T.H. Carter, J.E. Kolitz, M. Wetzler, A.J. Carroll, M.R. Baer, J.O. Moore, M.A. Caligiuri, R.A. Larson, C.D. Bloomfield, Age-related prognostic impact of different types of DNMT3A mutations in adults with primary cytogenetically normal acute myeloid leukemia, J. Clin. Oncol. 30 (2012) 742–750. [34] R.F. Schlenk, K. Döhner, J. Krauter, S. Fröhling, A. Corbacioglu, L. Bullinger, M. Habdank, D. Späth, M. Morgan, A. Benner, B. Schlegelberger, G. Heil, A. Ganser, H. Döhner, Mutations and treatment outcome in cytogenetically normal acute myeloid leukemia, N. Engl. J. Med. 358 (2008) 1909–1918. [35] B. Falini, C. Mecucci, E. Tiacci, M. Alcalay, R. Rosati, L. Pasqualucci, R. La Starza, D. Diverio, E. Colombo, A. Santucci, B. Bigerna, R. Pacini, A. Pucciarini, A. Liso, M. Vignetti, P. Fazi, N. Meani, V. Pettirossi, G. Saglio, F. Mandelli, F. Lo-Coco, P.G. Pelicci, M.F. Martelli, Cytoplasmic nucleophosmin in acute myelogenous leukemia with a normal karyotype, N. Engl. J. Med. 352 (2005) 254–266. [36] R.F. Schlenk, K. Döhner, M. Kneba, K. Götze, F. Hartmann, F. Del Valle, H. Kirchen, E. Koller, J.T. Fischer, L. Bullinger, M. Habdank, D. Späth, S. Groner, B. Krebs, S. Kayser, A. Corbacioglu, A. Anhalt, A. Benner, S. Fröhling, H. Döhner, Gene mutations and response to treatment with all-trans retinoic acid in elderly patients with acute myeloid leukemia, Haematologica 94 (2009) 54–60.
Please cite this article as: D. El Ghannam, et al., Blood Cells Mol. Diseases (2014), http://dx.doi.org/10.1016/j.bcmd.2014.01.004
Contents lists available at ScienceDirect
Blood Cells, Molecules and Diseases journal homepage: www.elsevier.com/locate/bcmd
DNMT3A R882 mutations in patients with cytogenetically normal acute myeloid leukemia and myelodysplastic syndrome Doaa El Ghannam a,⁎, Mona M. Taalab b, Hayam F. Ghazy c, Asmaa F. Eneen d a
Departments of Clinical Pathology, Faculty of Medicine, Mansoura University, Egypt Clinical Hematology Unit, Internal Medicine Department, Faculty of Medicine, Mansoura University, Mansoura, Egypt Medical Oncology Unit, Internal Medicine Department, Faculty of Medicine, Mansoura University, Mansoura, Egypt d Internal Medicine Department, Faculty of Medicine, Mansoura University, Mansoura, Egypt b c
a r t i c l e
i n f o
Article history: Submitted 31 December 2013 Revised 7 January 2014 Available online xxxx (Communicated by M. Lichtman, M.D., 07 January 2014) Keywords: DNMT3A Acute myeloid leukemia Myelodysplastic syndrome Oncogenes Leukemogenesis
a b s t r a c t Several molecular markers have been described that help to classify patients with acute myeloid leukemia (AML), a heterogeneous hematopoietic tissue neoplasm, into risk groups. We determined the frequency of DNMT3A mutations, their associations with clinical and molecular characteristics and outcome, in primary, cytogenetically-normal AML (CN-AML) and CN-myelodysplastic syndrome (MDS). A total of 63 CN-AML and 16 CN-MDS patients were analyzed for mutations in DNMT3A, codon R822 by direct sequencing and mutation of NPM1 and FLT3/ITD. DNMT3A mutations were found in 17/63 (27%) of CN-AML and in 1/16 (6.3%) of CNMDS patients. Patients with DNMT3A mutations were older (p = 0.047), had higher white blood cell (WBC) counts (p = 0.046), more often belonged to FAB groups M4 and M5 (p = 0.017), and were more associated with NPM1 mutations (p = 0.017), than those with wild-type DNMT3A. DNMT3A-mutated patients had shorter overall disease survival (p b 0.001) and disease-free survival (p = 0.014) when the entire patient cohort was considered, which remained significant in multivariate analysis. We conclude that DNMT3A R882 mutations are recurrent molecular aberrations in CN-AML, less frequent in CN-MDS, and that testing for R882 mutations may provide a useful tool for refining risk classification of CN-AML. Crown Copyright © 2014 Published by Elsevier Inc. All rights reserved.
Introduction Tumorigenesis is known to be a multistep process, which is the result of cellular genetic mutations and epigenetic changes [1]. The distinct components of epigenetic machinery such as DNA methylation, covalent modifications of histones, and noncoding RNAs have been described as controllers of gene expression and may contribute to leukemogenesis [2]. DNA methylation plays an essential role in development, differentiation, genomic stability, X-inactivation, and
Abbreviations: AML, acute myeloid leukemia; BMA, bone marrow aspiration; CD, cluster of differentiation; CI, confidence interval; CMML, chronic myelomonocytic leukemia; CN, cytogenetically normal; CR, complete remission; DFS, disease free survival; DNA, desoxypentosenucleic acid; DNMT, DNA methyltransferases; dNTP, deoxynucleoside triphosphate; FAB, French–American–British classification; FLT3/ITD, FMS-like tyrosine kinase 3 internal tandem duplication; Hb, hemoglobin; HDACs, histone deacetylases; HLA-DR, human leukocyte antigen DR; HMT, histone methyltransferase; HP1, heterochromatin protein; HR, hazard ratio; ID, induction death; MDS, myelodysplastic syndrome; MTase, methyltransferase; NPM1, nucleophosmin 1; OS, overall survival; PCR, polymerase chain reaction; PWWP, proline-tryptophan-tryptophan-proline; RA/RARS, refractory anemia/refractory anemia with ringed sideroblasts; RAEB, refractory anemia with excess blasts; RCMD/RCMD-RS, refractory cytopenia with multiple dysplasia/refractory cytopenia with multiple dysplasia with ringed sideroblasts; RD, refractory disease; SD, standard deviation; WBC, white blood cells; WT, wild type; ZNF, zinc finger. ⁎ Corresponding author. E-mail address: [email protected] (D. El Ghannam).
imprinting by specific regulation of gene expression [1]. DNA methylation occurs by an enzymatic addition of a methyl group at the carbon 5 position of cytosine in the context of cytosine-guanine dinucleotides [3]. The transfer of methyl groups from S-adenosylmethionine to cytosine is a heritable process that is catalyzed by several DNA methyltransferases (DNMTs) during cell replication [1]. There are at least three different DNMTs involved in cellular DNA methylation: DNMT1, DNMT3A, and DNMT3B [4]. DNMT1 is the most abundant and preferentially replicates existing DNA methylation patterns, whereas DNMT3A and DNMT3B are responsible for establishing de novo DNA methylation. All three DNMTs are constitutively expressed at different levels in most human tissues. Overexpression of DNMTs and its association with altered DNA methylation have been observed in tumors including leukemias [3]. DNMT3A contains three main structure domains: an ADD (ATRX, DNMT3, and DNMT3L)-type zinc finger (ZNF) domain, a PWWP (proline-tryptophan-tryptophan-proline) domain and the methyltransferase (MTase) domain [5]. The PWWP domain is responsible for targeting the enzyme to nucleic acid, while the ZNF domain mediates protein–protein interactions with the transcription factors Myc and RP58, the heterochromatin protein HP1, histone deacetylases (HDACs), and the histone methyltransferase (HMT) [6]. Mutations in DNMT3A have been identified in patients with AML, myelodysplastic syndromes (MDS), and myeloproliferative neoplasms
1079-9796/$ – see front matter. Crown Copyright © 2014 Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.bcmd.2014.01.004
Please cite this article as: D. El Ghannam, et al., Blood Cells Mol. Diseases (2014), http://dx.doi.org/10.1016/j.bcmd.2014.01.004
2
D. El Ghannam et al. / Blood Cells, Molecules and Diseases xxx (2014) xxx–xxx
Table 1 Patients' characteristics of the studied groups.
Data
CN-AML (n = 63)
Age (years)
mutations have been associated with a negative impact on overall survival (OS). Thol et al. [7] reported that DNMT3A mutations were associated with shorter overall survival (OS) in cytogenetically diverse patients with AML, who are younger than 60 years and with lower complete remission (CR) rates and shorter OS in a CN-AML subset. In this study we investigated the frequency and prognostic impact of DNMT3A mutations in a cohort of 63 CN-AML and 16 CN-MDS patients and analyzed its interaction with other prognostic markers.
CN-MDS (n = 16)
47.1 ± 10.
64.2 ± 9.2
Males
35 (55.6%)
11 (68.8%)
Females
28 (44.4%)
5 (31.3%)
73.4 ± 58.6
5.28 ± 2.0
Sex 9
TLC (×10 /l) Hb (g/dl) 9
Platelets (×10 /l)
8.5 ± 2.4
7.3 ± 1.7
138 ± 167
64.4 ± 34.8
Blasts (%)
70 ± 21
FAB
Patients and methods Patients
7.1 ± 5.2
M1:
14 (22.2%)
RA/RARS:
2 (12.5%)
M2:
14 (22.2%)
RCMD/RCMD-RS:
6 (37.5%)
M4:
15 (23.8%)
RAEB-1:
4 (25.0%)
M5:
14 (22.2%)
RAEB-2:
4 (25.0%)
M6:
6 (9.5%)
CMML:
0 (0%)
TLC: total leucocytic count, Hb: hemoglobin concentration, RAEB: refractory anemia with excess blasts. Age, TLC, Hb, platelets and blasts were presented by mean ± SD. Sex and FAB subtypes were presented by number and percentages.
(MPN) [7–11]. In AML, all three DNMT enzymes are reportedly overexpressed in malignant blasts compared with normal marrow (BM) cells and contribute to leukemogenesis by mediating tumor suppressor gene silencing [3]. Preliminary data show that the incidence of these mutations in AML ranges from 4.1% in a Japanese study [12], 9% in a study with Chinese patients [13], and about 15–25% in Western studies [7,8,14,15]. These possible ethnogeographic differences in the incidence of DNMT3A mutations should be better characterized. Eighteen different mutations were found in these studies, most of them missense mutations. The majority of mutated DNMT3A (DNMT3A) is located in exon 23. The “hotspot” mutation occurs at the amino position 882, resulting in the replacement of arginine by histidine (R882H), cysteine (R882C), serine (R882S), or phenylalanine (R882P) [16]. The exact mechanisms by which DNMT3A mutations act in AML are still unclear, since the global pattern of methylation in the genome of such patients with AML does not appear to be significantly changed [8]. Less is known about the frequency and the prognostic impact of DNMT3A mutations in MDS. However, one study suggests that mutations are less frequent than in AML [11]. Ley et al. [8] first reported that DNMT3A
We have studied 63 marrow samples from CN-AML patients at diagnosis and prior to any chemotherapy. They were 35 males and 28 females with mean age, 47.08 ± 10.00 years. Marrow samples from 16 patients with CN-myelodysplastic syndrome (mean age, 64.19 ± 9.17 years) were also analyzed. To analyze the incidence of DNMT3A mutations in healthy controls, blood samples from 20 healthy blood donors (18 to 60 years of age) were obtained from the Institute of blood transfusion center. Patients with antecedent hematologic diseases or therapy-related AML were excluded. Diagnosis and classification of AML and MDS were made according to the French–American–British (FAB) Cooperative Group Criteria (Table 1). This study was approved by the institutional review board of Mansoura University, and written informed consent was obtained from all participants from October 2012 to March 2013.
Treatment protocol AML patients received the standard ‘3 + 7’ induction chemotherapy protocol: doxorubicin (45 mg/m2/day) for 3 days and cytarabine (100 mg/m2/day as a continuous 24 h intravenous infusion) for 7 days [17]. Marrow aspiration was done between 21 and 28 days after initiation of chemotherapy to demonstrate morphological remission. Consolidation comprised three to four courses of high-dose cytosine arabinoside (3 g/m2 every 12 h on days 1, 3 and 5; total, 18 g/m2). Patients were followed once every 3 months with clinical examination and complete blood cell counts. Marrow examination was done if there was any doubt of a relapse on clinical examination or blood smear. Patients with MDS were treated with azacitidine (75 mg/m2/d subcutaneously for 7 days every 28 days) for 4 months [18].
Table 2 The DNMA3A mutation patterns in CN-AML and CN-MDS patients. Code
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Age
55 52 33 59 59 51 47 54 54 46 59 56 46 46 51 55 47 58
Sex
Female Male Male Male Male Female Female Female Female Female Female Female Male Male Male Male Male Male
TLC
85.0 48.0 80.0 115.0 115.0 75.0 85.0 62.0 62.0 88.0 70.0 56.0 84.5 84.5 80.0 130.0 220.0 56
FAB
M5 M4 M2 M6 M6 M5 M4 M5 M5 M4 M4 M5 M5 M5 M2 M4 M4 RAEB1
DNMT3A mutation Location
DNA change
Protein change
23 23 23 23 23 23 23 23 23 23 13 23 23 23 23 8 23 23
c.2645C N A c.2646G N A c.2646G N A c.2645C N T c.2645C N T c.2646G N A c.2645C N T c.2646G N A c.2646G N A c.2645C N T 1477delA c.2646G N A c.2646G N A c.2646G N A c.2645C N T 958CT c.2646G N A c.2646G N A
p.R882S p.R882H p.R882H p.R882C p.R882C p.R882H p.R882C p.R882H p.R882H p.R882C p.R882H p.R882H p.R882H p.R882H p.R882C p.R882C p.R882H p.R882H
Chemo-response
Result
RD CR CR CR CR ID ID CR CR RD CR CR ID CR CR CR CR –
Died Alive Alive Alive Alive Died Died Alive Alive Alive Died Alive Died Died Alive Alive Alive Alive
CR: complete remission; ID: induction death; RD: refractory disease.
Please cite this article as: D. El Ghannam, et al., Blood Cells Mol. Diseases (2014), http://dx.doi.org/10.1016/j.bcmd.2014.01.004
D. El Ghannam et al. / Blood Cells, Molecules and Diseases xxx (2014) xxx–xxx
3
Fig. 1. Sequences of the mutated DNMT3A R882. A: wild type sequence; B: R882C mutation; C: R882H mutation. Mutations are indicated with black arrows and yellow background. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
94 °C for 30 s, annealing at 59 °C for 30 s, and an extension at 72 °C for 30 s.
Cytogenetic analysis Pretreatment cytogenetic analyses of marrow or blood were performed by G-banding technique and karyotyped according to the International System for Human Cytogenetic Nomenclature. A minimum of 20 metaphases was required to be examined for a patient to be classified as having normal cytogenetics [19].
Immunophenotype analysis A panel of mAbs to myeloid-associated antigens, including CD13, CD33, CD11b, CD15, CD14, and CD41a, as well as lymphoid-associated antigens, including CD2, CD5, CD7, CD19, CD10, and CD20, and lineage nonspecific antigens HLA-DR, CD34, and CD56, were used to characterize the phenotypes of the leukemia cells, as described previously [19].
Automated sequencing of codon R882 By using ABI prism 310 genetic analyzer Version 2.0 (Applied Biosystems, Foster City, USA) with 50 cm capillaries and POP6 polymer (Applied Biosystems). Cycle sequencing was carried on PCR products labeled with 3.2 pmol of the forward primer using Big Dye Terminator ready reaction kit with total volume of 20 μL. The reaction mix was prepared following the instructions provided by the manufacturer. Twenty-five cycles of denaturation, annealing, and extension at 94 °C for 10 s, 55–62 °C for 5 s, and 60 °C for 4 min were carried out. Purification of the products was done to remove excess dye by isopropanol before electrophoresis on the ABI Prism 310 genetic analyzer. Electropherograms were compared to the reference sequence (NM 022552). Altered sequencing results were confirmed by reverse strand sequencing.
DNMT3A mutation analysis DNA isolation and polymerase chain reaction Genomic DNA was extracted from marrow cell samples using QIA amp DNA kit for DNA extraction provided by QIAGEN (Quiagen Inc., Chatsworth, CA, USA). DNA fragment spanning the codon R882 (exon 23) was amplified by polymerase chain reaction (PCR) using the following primers: 5′-TTTGGTTTCCCAGTCCACTATAC-3′ (forward), and 5′CCAGCAGTCTCTGCCTC-3′ (reverse). PCR was performed in 25-mL volume in the presence of 1 × PCR buffer (Invitrogen, Merelbeke, Belgium), 0.2 mmol/L of each dNTP, 2.5 mmol/L of MgCl2, 0.4 mmol/L of both forward and reverse primers, 1 U Taq polymerase (MBI Fermentas, Canada), and 50 ng genomic DNA. PCR reactions were carried out on a 7000 Thermo cycler (Applied Biosystems, Foster City, CA, USA). The temperature cycling protocol consisted of an initial denaturation step at 95 ºC for 5 min, followed by 40 cycles of denaturation at
Screening of NPM1 gene mutation and FLT3/ITD For NPM1mutation analysis, NPM1 exon-12 was amplified by genomic PCR using primers NPM1 11f: 5′-CTGGTAGAATGAAAAATAGAT-3′ (6 FAM labeled), and NPM1 12r: 5′-CTTGGCAATAGAACCTGGAC-3′ (Applied Biosystems, USA). PCR reactions were performed in a total volume of 25 μL containing 20–50 ng of extracted DNA (1 μl), 10 pmol of each primer (Applied Biosystems), 12.5 mL of Maxima hot start PCR master mix 2 × (Thermo Scientific) (containing Maxima hot Taq DNA polymerase, hot start PCR buffer, 400 μM of each dNTP, and 4 mM Mg + 2), and the reaction was completed to 25 mL using molecular grade water. The amplification was carried out in a GeneAmp PCR System 9700 (Applied Biosystems, Foster City, CA) using the following steps: preactivation at 95 °C for 4 min, 35 cycles at 94 °C for 30 s, 56 °C for 30 s and 72 °C for 60 s, and post extension steps; 94 °C for 30 s and 60 °C for 45 s.
Table 3 DNMT3A mutations according to patients' characteristics. CN-AML (n = 63) Age (years) Sex TLC (X109/L) Hb (g/dL) Platelets (X109/L) Blasts (%) FAB FLT3/ITD NPM1 Low risk High risk
Males Females
M1, M2, M6 M4, M5
DNMT3A-mutated (n = 17)
DNMT3A-wild (n = 46)
p
51.2 ± 6.6 9 (52.9%) 8 (47.1%) 97.5 ± 44 8.3 ± 2.8 132 ± 134. 73. ± 24. 0 (0%), 3 (17.6%), 2 (11.8%) 6 (35.3%), 6 (35.3%) 5 (29.4%) 9 (52.9%) 5 (29.4%) 12 (70.6%)
45.6 ± 11. 26 (56.5%) 20 (43.5%) 64.5 ± 61 8.5 ± 2.3 140 ± 180 69 ± 21 14 (30.4%), 11 (23.9%), 4 (8.7%) 9 (19.6%), 8 (17.4%) 8 (17.4%) 10 (21.7%) 7 (15.2%) 39 (84.8%)
0.047 0.800
Age, TLC, Hb, platelets and blasts are presented by mean ± SD. Sex and FAB are presented by number and percentages.
Please cite this article as: D. El Ghannam, et al., Blood Cells Mol. Diseases (2014), http://dx.doi.org/10.1016/j.bcmd.2014.01.004
0.046 0.780 0.869 0.572 0.017 0.295 0.017 0.203
4
D. El Ghannam et al. / Blood Cells, Molecules and Diseases xxx (2014) xxx–xxx
Results Prevalence and spectrum of DNMT3A mutations Missense mutations of DNMT3A exon 23 (R882) were identified in 17 CN-AML (27%) and 1 (6.3%) CN-MDS patients. The most common mutation was R882H (n = 11; 61.1%), followed by R882C (n = 6; 33.3%), and R882S (n = 1; 5.6%). R882 mutations were not present in healthy controls (Table 2, Fig. 1). Correlation of DNMT3A mutations with patient characteristics and other molecular abnormalities
Fig. 2. Overall survival according to DNMT3A mutations in CN-AML patients.
To detect FLT3/ITD, exon-14 and exon-15 were amplified using primers 11f (5′ GCAATTTAGGTATGAAAGCCAGC-3′), and 12r (5′-CTTT CAGCATTTTGACGGCAACC-3′) (Applied Biosystems, USA). PCR reactions were performed in a total volume of 25 μL containing the same contents used as in the NPM1 PCR above apart from FLT3 primers. The amplification was carried out in a GeneAmp PCR System 9700 (Applied Biosystems, Foster City, CA) using the following steps: preactivation at 95 °C for 4 min, 30 cycles at 95 °C for 30 s, 62 °C for 30 s and 72 °C for 30 s, and final extension at 72 °C for 5 min. Statistical Methods The statistical analysis of data was done by using Excel program and SPSS (statistical package for social science) program (SPSS, Inc, Chicago, IL) version 16. Kolmogorov–Smirnov test was done to test the normality of data distribution. Significant data was considered to be nonparametric. Qualitative data were presented as frequency and percentage. Chi square test was used to compare groups. Quantitative data were presented as mean and standard deviation. For comparison between two groups, Student's t-test, and Mann–Whitney test (for non parametric data) were used. Kaplan–Meier test was used for survival analysis and the statistical significance of differences among curves was determined by log-rank test. The Cox proportional hazard regression model was chosen to assess the independent prognostic factor affecting overall survival. N.B.: p is significant if ≤0.05 at confidence interval of 95%
We evaluated the correlation of clinical and genetic characteristics with DNMT3A mutations in all patients (Table 3). CN-AML patients who harbored a mutation in DNMT3A were older (p = 0.047), had higher white blood cell (WBC) counts (p = 0.046) at diagnosis and more frequently belonged to FAB groups M4 and M5 (p = 0.017), as compared with DNMT3A wild- type. To investigate the interaction of gene mutations in the pathogenesis of adult AML, mutational screening of NPM1 and FLT3 genes was performed in all patients. Among the studied cohort, 32 (50.8%) showed additional molecular abnormalities at diagnosis. NPM1 mutations (NPM1) were more common among DNMT3A mutated than in DNMT3A-WT patients (52.9% vs 21.7%; p = 0.017). There was no significant difference in the incidence of FLT3-ITD, among patients with DNMT3A mutation as compared with DNMT3A-WT (29.4% vs 17.4%; p = 0.29). Patients were then subdivided into high (presence of FLT3-ITD regardless of NPM1 status or the absence of FLT3-ITD and NPM1-WT) and low (absence of FLT3-ITD and NMP1-mutated)-molecular-risk groups. Impact of DNMT3A mutation on response to therapy and clinical outcome Of the 63 CN-AML patients undergoing conventional intensive induction chemotherapy, 43 (68.3%) achieved complete remission (CR). The probability of achieving CR was similar between patients with and without DNMT3A mutations (70.6% vs 67.4%, p = 0.81). However, the patients with DNMT3A mutations had a trend of higher relapse rate than those without (41.2% vs 23.9%; p = 0.17). With a median follow-up of 17 months (range, 0.1–32), patients harboring DNMT3A mutations had shorter OS (14.6 vs 28.0; p b 0.001) and DFS (13.8 vs 24.2 months; p = 0.014) than DNMT3A-WT patients (Figs. 2, 3). We also observed that NPM1/FLT3 high-risk group with mutated DNMT3A had a significantly shorter OS (14.1 vs 27.7 months; p b 0.001) and DFS (11.1 vs 23.6 months; p b 0.001) compared with patients with wild-type DNMT3A. However, no significant prognostic effects were found when analyzing the influence of DNMT3A mutations in NPM1/FLT3 low-risk group (OS: 15.0 vs 27.7 months; p = 0.16, DFS: 15.2 vs 26.0 months; p = 0.19) (Table 4, Figs. 4, 5). In multivariate Cox proportional hazards regression analyses after adjusting for other known prognostic factors such as age, total leukocyte count (TLC), hemoglobin, platelet count, blast %, FLT3-ITD and NPM1 risk status and DNMT3A mutations. DNMT3A mutations remained an independent adverse prognostic marker for OS (HR: 3.3; 95% CI: 2.7 to 9.0; p = 0.001) and DFS (HR: 5.4; 95% CI: 3.3 to 9.2; p b 0.001) (Table 5). Discussion
Fig. 3. Disease-free survival according to DNMT3A mutations in CN-AML patients.
In light of recently detected new molecular factors, a refinement of the existing classifications by adding new factors will hopefully enable us to specify prognostic statements, prospectively evaluate the impact of different treatments on long-term outcomes, and establish predictive factors for individually tailored treatment options and improvement of survival in all patients with AML.[20] The rate of R882 mutations (27%) in our patients was lower than the report of Ley et al. [8] (22.1%
Please cite this article as: D. El Ghannam, et al., Blood Cells Mol. Diseases (2014), http://dx.doi.org/10.1016/j.bcmd.2014.01.004
D. El Ghannam et al. / Blood Cells, Molecules and Diseases xxx (2014) xxx–xxx
5
Table 4 Overall and disease free survival according to DNMT3A mutation status in good and poor prognostic groups in AML patients. FLT3 NPM1 Risk status
Low High
Survival
OS DFS OS DFS
DNMT3A-mutated (n = 17)
DNMT3A-wild (n = 46)
Cumulative survival (%)
Mean (months)
CI 95%
73.9 64.6 45.5 27.3
15.0 15.2 14.1 11.1
6.9 8.8 8.9 9.2
23.0 21.6 19.2 12.9
p Log-rank (Mantel–Cox)
Cumulative Survival (%)
Mean (months)
CI 95%
66.7 50.0 66.7 75.0
27.6 26.0 27.6 23.5
25.5 23.2 25.3 21.0
29.8 28.7 29.9 26.0
0.157 0.186 b0.001 b0.001
Cumulative survival: cumulative proportion surviving at 24 months. CI 95%: confidence interval at 95%, OS: overall survival. DFS: disease-free survival.
for total AML patients and 36.7% for CN-AML patients) and similar to those of Thol et al. [7] (27.2% in CN-AML patients). Hou et al. [21] reported an incidence of 22.9% in CN-AML. Yamashita et al. [22] reported a low incidence of DNMT3A mutations in a Japanese population (4.1%). The differences in patient populations could be related to ethnic background and methods used. The catalytic activity of DNMT3A protein relies on the methyl transferase (MTase) domain, which contains ten blocks of conserved amino acid motifs [23,24]. The R882 residue, located in front of motif X [24,25], participates in the homodimerization and activation of the protein [26]. Mutations at R882 residue inhibit both DNA binding and catalytic activity [22,23]. However, it is possible that R882 mutations alter functions of DNMT3A that are not yet fully understood, including its ability to bind to other proteins involved in transcriptional regulation and localization to chromatin regions containing methylated DNA [27–30]. DNMT3A R882 mutations were more prevalent at older age in accordance with others' findings [16] and associated with significantly increased blood leukocyte number at diagnosis compared to the patients without this mutation, which is in agreement with this finding as reported in other studies [8,12,13,16,31,32]. Furthermore, DNMT3A R882 mutations were found more frequently in monoblastic leukemia compared to other phenotypes. This result further confirmed the specificity of DNMT3A R882 mutations in monocytic lineage [8,13]. Survival analysis of DNMT3A mutated compared with wild-type patients in all investigated patients with CN-AML showed a negative prognostic effect of DNMT3A mutations for OS and DFS that remained significant in multivariate analysis after adjusting for other known prognostic factors. This finding indicates that DNMT3A mutations are probably relevant to the pathogenesis of AML. Similarly, Ley et al. [8] and Thol et al. [7] found that in the CN-AML subgroup, DNMT3A mutations were associated with a lower CR rate and shorter OS in multivariable analyses. Our results differ from those reported by Marcucci et al. [33], who found no significant association between, R882-DNMT3A mutations and DFS or OS in younger patients.
The primary goal of our analysis was to evaluate the impact of DNMT3A mutations on patient outcome such as, OS and DFS, in a uniformly treated cohort of patients with AML in the context of other known prognostic markers. Mutations of NPM1/FLT3 genes have been described in these patients, and patients with mutated NPM1 in the absence of FLT3-ITD have been identified as a favorable risk group [34]. Interestingly, DNMT3A mutations have no prognostic effect on low-risk patients, while it confers a negative prognosis on the high-risk group (FLT3-ITD or wild-type NPM1/wild-type FLT3). Ley et al. [8] had similar results in that DNMT3A mutations were associated with shorter OS, specifically in patients with FLT3-ITD. The reason for the selective prognostic effect of DNMT3A mutations in NPM1/ FLT3 high-risk patients is unclear. This may be contributed to by the differences in disease biology of NPM1/FLT3 high-risk and low-risk patients that may provide a different molecular context in which mutated DNMT3A may have different effects. First, it is known that NPM1mutated AML is mostly negative for the stem-cell marker CD34 [35], whereas NPM1 wild-type patients mostly express CD34. Second, NPM1-mutated AML is rather sensitive to differentiation-inducing agents [36] in contrast to NPM1 wild-type AML. These data suggest that NPM1-mutated AML originates at or has characteristics of a more differentiated stage of hematopoiesis that is more susceptible to current treatment protocols than NPM1 wild-type patients. R882 mutation was also identified in one CN-MDS patient (RAEB). The mutation rate of 2.6% in our study is lower than the reported mutation rate of 8.0% by Walter et al. [11]. Our data demonstrate that DNMT3A mutations are present in myeloid malignancies other than AML. However, in CN-MDS the frequency of the mutation is significantly lower than in AML. The patient with this mutation had a shorter overall survival than patients without as confirmed from Walter et al. [11]. The low frequency of DNMT3A mutations in MDS did not allow any formal assessment of clinical and molecular associations or prognostic evaluation, but our data suggest a possible negative prognostic impact, as already described for mutations in CN-AML as patients with the mutations had a shorter overall survival and more frequently progressed to
Fig. 4. Overall survival according to DNMT3A mutations in high-risk group.
Fig. 5. Disease-free survival according to DNMT3A mutations in high-risk group.
Please cite this article as: D. El Ghannam, et al., Blood Cells Mol. Diseases (2014), http://dx.doi.org/10.1016/j.bcmd.2014.01.004
6
D. El Ghannam et al. / Blood Cells, Molecules and Diseases xxx (2014) xxx–xxx
Table 5 Multivariate analysis for overall and disease-free survival in AML patients. Overall-survival
Disease-free survival
Covariates
p
HR
95% CI
p
HR
95% CI
Age (years) TLC (x109/L) Hemoglobin (g/dL) Platelets Blasts (%) FLT3 and NPM1 risk status DNMT mutation
0.588 0.807 0.174 0.207 0.581 0.187 0.001
1.01 1.00 1.20 1.00 1.00 2.51 3.26
0.96 0.99 0.92 0.99 0.98 0.54 2.70
0.80 0.38 0.39 0.74 0.97 0.093 b0.001
0.99 1.00 1.11 1.00 1.00 3.88 5.38
0.93 0.99 0.86 0.99 0.97 0.746 3.32
1.07 1.01 1.58 1.00 1.03 5.71 8.98
1.05 1.01 1.44 1.00 1.02 7.43 9.22
AML. Thus, DNMT3A mutations might be involved in the progression of the disease. Conflict of interest The authors report no conflict of interest. References [1] M. Esteller, Epigenetics in cancer, N. Engl. J. Med. 358 (2008) 1148–1159. [2] P.A. Jones, S.B. Baylin, The epigenomics of cancer, Cell 128 (23 2007) 683–692. [3] S. Mizuno, T. Chijiwa, T. Okamura, K. Akashi, Y. Fukumaki, Y. Niho, H. Sasaki, Expression of DNA methyltransferases DNMT1, 3A, and 3B in normal hematopoiesis and in acute and chronic myelogenous leukemia, Blood 97 (2001) 1172–1179. [4] A. Pezzi, L. Moraes, V. Valim, B. Amorin, G. Melchiades, F. Oliveira, M.A. da Silva, U. Matte, M.S. Pombo-de-Oliveira, R. Bittencourt, L. Daudt, L. Silla, DNMT3A mutations in patients with acute myeloid leukemia in South Brazil, Adv. Hematol. (2012) 697691. [5] C. Brenner, F. Fuks, DNA methyltransferases: facts, clues, mysteries, Curr. Top. Microbiol. Immunol. 301 (2006) 45–66. [6] T. Chen, E. Li, Establishment and maintenance of DNA methylation patterns in mammals, Curr. Top. Microbiol. Immunol. 301 (2006) 179–201. [7] F. Thol, F. Damm, A. Lüdeking, C. Winschel, K. Wagner, M. Morgan, H. Yun, G. Göhring, B. Schlegelberger, D. Hoelzer, M. Lübbert, L. Kanz, W. Fiedler, H. Kirchner, G. Heil, J. Krauter, A. Ganser, M. Heuser, Incidence and prognostic influence of DNMT3A mutations in acute myeloid leukemia, J. Clin. Oncol. 20 (29) (2011) 2889–2896. [8] T.J. Ley, L. Ding, M.J. Walter, M.D. McLellan, T. Lamprecht, D.E. Larson, C. Kandoth, J.E. Payton, J. Baty, J. Welch, C.C. Harris, C.F. Lichti, R.R. Townsend, R.S. Fulton, D.J. Dooling, D.C. Koboldt, H. Schmidt, Q. Zhang, J.R. Osborne, L. Lin, M. O'Laughlin, J.F. McMichael, K.D. Delehaunty, S.D. McGrath, L.A. Fulton, V.J. Magrini, T.L. Vickery, J. Hundal, L.L. Cook, J.J. Conyers, G.W. Swift, J.P. Reed, P.A. Alldredge, T. Wylie, J. Walker, J. Kalicki, M.A. Watson, S. Heath, W.D. Shannon, N. Varghese, R. Nagarajan, P. Westervelt, M.H. Tomasson, D.C. Link, T.A. Graubert, J.F. DiPersio, E.R. Mardis, R.K. Wilson, DNMT3A mutations in acute myeloid leukemia, N. Engl. J. Med. 363 (2010) 2424–2433. [9] M.Y. Shah, J.D. Licht, DNMT3A mutations in acute myeloid leukemia, Nat. Genet. 43 (2011) 289–290. [10] F. Stegelmann, L. Bullinger, R.F. Schlenk, P. Paschka, M. Griesshammer, C. Blersch, S. Kuhn, S. Schauer, H. Döhner, K. Döhner, DNMT3A mutations in myeloproliferative neoplasms, Leukemia 25 (2011) 1217–1219. [11] M.J. Walter, L. Ding, D. Shen, J. Shao, M. Grillot, M. McLellan, R. Fulton, H. Schmidt, J. Kalicki-Veizer, M. O'Laughlin, C. Kandoth, J. Baty, P. Westervelt, J.F. DiPersio, E.R. Mardis, R.K. Wilson, T.J. Ley, T.A. Graubert, Recurrent DNMT3A mutations in patients with myelodysplastic syndromes, Leukemia 25 (2011) 1153–1158. [12] J.K. Cowell, L. Hawthorn, The application of microarray technology to the analysis of the cancer genome, Curr Mol Med. 7 (2007) 103–120. [13] X.J. Yan, J. Xu, Z.H. Gu, C.M. Pan, G. Lu, Y. Shen, J.Y. Shi, Y.M. Zhu, L. Tang, X.W. Zhang, W.X. Liang, J.Q. Mi, H.D. Song, K.Q. Li, Z. Chen, S.J. Chen, Exome sequencing identifies somatic mutations of DNA methyltransferase gene DNMT3A in acute monocytic leukemia, Nat. Genet. 43 (2011) 309–315. [14] A.F. Ribeiro, M. Pratcorona, C. Erpelinck-Verschueren, V. Rockova, M. Sanders, S. Abbas, M.E. Figueroa, A. Zeilemaker, A. Melnick, B. Löwenberg, P.J. Valk, R. Delwel, Mutant DNMT3A: a marker of poor prognosis in acute myeloid leukemia, Blood 119 (2012) 5824–5831. [15] J.P. Patel, M. Gönen, M.E. Figueroa, H. Fernandez, Z. Sun, J. Racevskis, P. Van Vlierberghe, I. Dolgalev, S. Thomas, O. Aminova, K. Huberman, J. Cheng, A. Viale, N.D. Socci, A. Heguy, A. Cherry, G. Vance, R.R. Higgins, R.P. Ketterling, R.E. Gallagher, M. Litzow, M.R. van den Brink, H.M. Lazarus, J.M. Rowe, S. Luger, A. Ferrando, E. Paietta, M.S. Tallman, A. Melnick, O. Abdel-Wahab, R.L. Levine, Prognostic relevance of integrated genetic profiling in acute myeloid leukemia, N. Engl. J. Med. 366 (2012) 1079–1089.
[16] J. Lin, D.M. Yao, J. Qian, Q. Chen, W. Qian, Y. Li, J. Yang, C.Z. Wang, H.Y. Chai, Z. Qian, G.F. Xiao, W.R. Xu, Recurrent DNMT3A R882 mutations in Chinese patients with acute myeloid leukemia and myelodysplastic syndrome, PLoS One 6 (2011) e26906. [17] J. Greer, M. Baer, M. Kinnery, Acute myelogenous leukemia, in: G. Lee, J. Foester, J. Leukens, F. Pareskerva, J. Greer, G. Rogers (Eds.), Wintrobe's Clinical Hematology, 12th ed., Lippincott Williams and Wilkins, Philadelphia, 2009, pp. 2045–2062. [18] L.R. Silverman, J.F. Holland, R.S. Weinberg, B.P. Alter, R.B. Davis, R.R. Ellison, E.P. Demakos, C.J. Cornell Jr., R.W. Carey, C. Schiffer, Effects of treatment with 5-azacytidine on the in vivo and in vitro hematopoiesis in patients with myelodysplastic syndromes, Leukemia 7 (Suppl. 1) (1993) 21–29. [19] Guidelines for cancer cytogenetics, in: F. Mittelmann (Ed.), Supplement to An International System for Human Cytogenetic Nomenclature, Karger, Basel, Switzerland, 1995. [20] C. Röllig, M. Bornhäuser, C. Thiede, F. Taube, M. Kramer, B. Mohr, W. Aulitzky, H. Bodenstein, H.J. Tischler, R. Stuhlmann, U. Schuler, F. Stölzel, M. von Bonin, H. Wandt, K. Schäfer-Eckart, M. Schaich, G. Ehninger, Long-term prognosis of acute myeloid leukemia according to the new genetic risk classification of the European Leukemia Net recommendations: evaluation of the proposed reporting system, J. Clin. Oncol. 29 (2011) 2758–2765. [21] H.A. Hou, Y.Y. Kuo, C.Y. Liu, W.C. Chou, M.C. Lee, C.Y. Chen, L.I. Lin, M.H. Tseng, C.F. Huang, Y.C. Chiang, F.Y. Lee, M.C. Liu, C.W. Liu, J.L. Tang, M. Yao, S.Y. Huang, B.S. Ko, S.C. Hsu, S.J. Wu, W. Tsay, Y.C. Chen, H.F. Tien, DNMT3A mutations in acute myeloid leukemia: stability during disease evolution and clinical implications, Blood 119 (2012) 559–568. [22] Y. Yamashita, J. Yuan, I. Suetake, H. Suzuki, Y. Ishikawa, Y.L. Choi, T. Ueno, M. Soda, T. Hamada, H. Haruta, S. Takada, Y. Miyazaki, H. Kiyoi, E. Ito, T. Naoe, M. Tomonaga, M. Toyota, S. Tajima, A. Iwama, H. Mano, Array-based genomic resequencing of human leukemia, Oncogene 29 (2010) 3723–3731. [23] H. Gowher, P. Loutchanwoot, O. Vorobjeva, V. Handa, R.Z. Jurkowska, T.P. Jurkowski, A. Jeltsch, Mutational analysis of the catalytic domain of the murine Dnmt3a DNA-(cytosine C5)-methyltransferase, J. Mol. Biol. 357 (2006) 928–941. [24] J. Turek-Plewa, P.P. Jagodziński, The role of mammalian DNA methyltransferases in the regulation of gene expression, Cell. Mol. Biol. Lett. 10 (2005) 631–647. [25] D. Jia, R.Z. Jurkowska, X. Zhang, A. Jeltsch, X. Cheng, Structure of Dnmt3a bound to Dnmt3L suggests a model for de novo DNA methylation, Nature 449 (7159) (2007) 248–251. [26] T. Deng, Y. Kuang, L. Wang, J. Li, Z. Wang, J. Fei, An essential role for DNA methyltransferase 3a in melanoma tumorigenesis, Biochem. Biophys. Res. Commun. 387 (2009) 611–616. [27] E. Hervouet, F.M. Vallette, P.F. Cartron, Dnmt3/transcription factor interactions as crucial players in targeted DNA methylation, Epigenetics 4 (2009) 487–499. [28] Y.A. Wang, Y. Kamarova, K.C. Shen, Z. Jiang, M.J. Hahn, Y. Wang, S.C. Brooks, DNA methyltransferase-3a interacts with p53 and represses p53-mediated gene expression, Cancer Biol. Ther. 4 (2005) 1138–1143. [29] C. Brenner, R. Deplus, C. Didelot, A. Loriot, E. Viré, C. De Smet, A. Gutierrez, D. Danovi, D. Bernard, T. Boon, P.G. Pelicci, B. Amati, T. Kouzarides, Y. de Launoit, L. Di Croce, F. Fuks, Myc represses transcription through recruitment of DNA methyltransferase corepressor, EMBO J. 24 (2005) 336–346. [30] P.A. Jones, G. Liang, Rethinking how DNA methylation patterns are maintained, Nat. Rev. Genet. 10 (2009) 805–811. [31] J. Marková, P. Michková, K. Burčková, J. Březinová, K. Michalová, A. Dohnalová, J.S. Maaloufová, P. Soukup, A. Vítek, P. Cetkovský, J. Schwarz, Prognostic impact of DNMT3A mutations in patients with intermediate cytogenetic risk profile acute myeloid leukemia, Eur. J. Haematol. 88 (2012) 128–135. [32] F. Thol, C. Winschel, A. Lüdeking, H. Yun, I. Friesen, F. Damm, K. Wagner, J. Krauter, M. Heuser, A. Ganser, Rare occurrence of DNMT3A mutations in myelodysplastic syndromes, Haematologica 96 (2011) 1870–1873. [33] G. Marcucci, K.H. Metzeler, S. Schwind, H. Becker, K. Maharry, K. Mrózek, M.D. Radmacher, J. Kohlschmidt, D. Nicolet, S.P. Whitman, Y.Z. Wu, B.L. Powell, T.H. Carter, J.E. Kolitz, M. Wetzler, A.J. Carroll, M.R. Baer, J.O. Moore, M.A. Caligiuri, R.A. Larson, C.D. Bloomfield, Age-related prognostic impact of different types of DNMT3A mutations in adults with primary cytogenetically normal acute myeloid leukemia, J. Clin. Oncol. 30 (2012) 742–750. [34] R.F. Schlenk, K. Döhner, J. Krauter, S. Fröhling, A. Corbacioglu, L. Bullinger, M. Habdank, D. Späth, M. Morgan, A. Benner, B. Schlegelberger, G. Heil, A. Ganser, H. Döhner, Mutations and treatment outcome in cytogenetically normal acute myeloid leukemia, N. Engl. J. Med. 358 (2008) 1909–1918. [35] B. Falini, C. Mecucci, E. Tiacci, M. Alcalay, R. Rosati, L. Pasqualucci, R. La Starza, D. Diverio, E. Colombo, A. Santucci, B. Bigerna, R. Pacini, A. Pucciarini, A. Liso, M. Vignetti, P. Fazi, N. Meani, V. Pettirossi, G. Saglio, F. Mandelli, F. Lo-Coco, P.G. Pelicci, M.F. Martelli, Cytoplasmic nucleophosmin in acute myelogenous leukemia with a normal karyotype, N. Engl. J. Med. 352 (2005) 254–266. [36] R.F. Schlenk, K. Döhner, M. Kneba, K. Götze, F. Hartmann, F. Del Valle, H. Kirchen, E. Koller, J.T. Fischer, L. Bullinger, M. Habdank, D. Späth, S. Groner, B. Krebs, S. Kayser, A. Corbacioglu, A. Anhalt, A. Benner, S. Fröhling, H. Döhner, Gene mutations and response to treatment with all-trans retinoic acid in elderly patients with acute myeloid leukemia, Haematologica 94 (2009) 54–60.
Please cite this article as: D. El Ghannam, et al., Blood Cells Mol. Diseases (2014), http://dx.doi.org/10.1016/j.bcmd.2014.01.004