Literature DB >> 30655366

DNMT3A mutation is associated with increased age and adverse outcome in adult T-cell acute lymphoblastic leukemia.

Jonathan Bond1,2,3, Aurore Touzart1, Stéphane Leprêtre4, Carlos Graux5, Mario Bargetzi6,7, Ludovic Lhermitte1, Guillaume Hypolite1, Thibaut Leguay8, Yosr Hicheri9, Gaëlle Guillerm10, Karin Bilger11, Véronique Lhéritier12, Mathilde Hunault13, Françoise Huguet14, Yves Chalandon6,15, Norbert Ifrah13, Elizabeth Macintyre1, Hervé Dombret16, Vahid Asnafi1, Nicolas Boissel17.   

Abstract

The prognostic implications of DNMT3A genotype in T-cell acute lymphoblastic leukemia are incompletely understood. We performed comprehensive genetic and clinico-biological analyses of T-cell acute lymphoblastic leukemia patients with DNMT3A mutations treated during the GRAALL-2003 and -2005 studies. Eighteen of 198 cases (9.1%) had DNMT3A alterations. Two patients also had DNMT3A mutations in non-leukemic cell DNA, providing the first potential evidence of age-related clonal hematopoiesis in T-cell acute lymphoblastic leukemia. DNMT3A mutation was associated with older age (median 43.9 years vs 29.4 years, P<0.001), immature T-cell receptor genotype (53.3% vs 24.4%, P=0.016) and lower remission rates (72.2% mutated vs 94.4% non-mutated, P=0.006). DNMT3A alterations were significantly associated with worse clinical outcome, with higher cumulative incidence of relapse (HR 2.33, 95% CI: 1.05-5.16, P=0.037) and markedly poorer event-free survival (HR 3.22, 95% CI: 1.81-5.72, P<0.001) and overall survival (HR 2.91, 95% CI: 1.56-5.43, P=0.001). Adjusting for age as a covariate, or restricting the analysis to patients over 40 years, who account for almost 90% of DNMT3A-mutated cases, did not modify these observations. In multivariate analysis using the risk factors that were used to stratify treatment during the GRAALL studies, DNMT3A mutation was significantly associated with shorter event-free survival (HR 2.33, 95% CI: 1.06 - 4.04, P=0.02). Altogether, these results identify DNMT3A genotype as a predictor of aggressive T-cell acute lymphoblastic leukemia biology. The GRAALL-2003 and -2005 studies were registered at http://www.ClinicalTrials.gov as #NCT00222027 and #NCT00327678, respectively. Copyright
© 2019 Ferrata Storti Foundation.

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Year:  2019        PMID: 30655366      PMCID: PMC6669163          DOI: 10.3324/haematol.2018.197848

Source DB:  PubMed          Journal:  Haematologica        ISSN: 0390-6078            Impact factor:   9.941


Introduction

Mutations in the DNA methyltransferase 3 alpha gene (DNMT3A) have been reported in a range of hematologic malignancies, most frequently in myeloid neoplasia, including acute myeloid leukemia (AML),[1-5] myelodysplastic syndromes,[6] myeloproliferative neoplasms[7] and myeloproliferative neoplasm/myelodysplastic overlap syndromes.[8,9] DNMT3A alterations in lymphoid malignancies are less common, and reports to date are confined to T-lineage disease.[10-16] In all cases, DNMT3A mutations increase in frequency with age, and are extremely rare in children and adolescents.[17-19] Multiple studies have reported that DNMT3A alterations correlate with poor outcome in AML.[1,2,4,20-22] In comparison, the prognostic influence of DNMT3A mutation in T-cell acute lymphoblastic leukemia (T-ALL) is poorly characterized. Patients with DNMT3A alterations were reported to have shorter survival in three moderately sized (55 to 93 patients) T-ALL cohorts.[9,11,13] DNMT3A status did not however independently predict prognosis in the only series for which multivariate analyses were documented, as survival effects were linked to increased rates of DNMT3A mutation in poor-risk, phenotypically immature disease.[11] While that study did document a correlation between DNMT3A alteration and survival within the immature T-ALL subgroup, this finding was not corroborated in an independent cohort of early thymic precursor (ETP) ALL cases.[12] The issue of whether DNMT3A mutation truly alters the biology of T-ALL is therefore only partially addressed by the currently available evidence. In particular, it is unclear whether the associated poor survival simply reflects the prosaic fact that patients with DNMT3A alterations are older,[11,12] and therefore do not tolerate intensive ALL treatment as well as their younger counterparts. In order to address this question, we used next-generation sequencing (NGS) to evaluate the DNMT3A genotype of a large cohort of 198 adult T-ALL patients treated as part of the multinational GRAALL-2003 and -2005 studies. We found that DNMT3A mutation strongly correlated with disease relapse and shorter survival, and that these prognostic effects were independent of patients’ age. Furthermore, we report the presence of DNMT3A mutations in non-leukemic cells in a subset of patients, providing the first evidence of age-related clonal hematopoiesis in T-ALL.

Methods

Patients

Details of the GRAALL-2003 and -2005 studies are provided in the Online Supplementary Methods. Informed consent was obtained from all patients before inclusion into the trials. Both studies were conducted in accordance with the Declaration of Helsinki and approved by local and multicenter research ethical committees. The complete study protocols are detailed in the Online Data Supplement. Both trials were registered at (NCT00222027, NCT00327678). The criteria for inclusion in the current project were a diagnosis of TALL and the availability of diagnostic material for NGS analysis of DNMT3A genotype. Survival outcomes of the 198 patients (36 from GRAALL-2003 and 162 from GRAALL-2005) who fulfilled these criteria did not differ from those of the remaining 139 T-ALL patients of the study cohorts. As expected in retro spective studies, initial white blood cell count (WBC) was higher in the study cohort. However, no differences in allogeneic stem cell transplant rate, disease-free survival, event-free survival, or overall survival were found. A full comparison of the clinical features of each group is shown in Online Supplementary Table S1.

Next-generation sequencing

Nextera XT (Illumina) DNA Libraries were prepared according to the manufacturer’s instructions and sequenced using the Illumina MiSeq sequencing system. The custom NGS panel comprised genes coding for factors involved in molecular pathways known to be mutated in T-ALL, namely cytokine receptor and RAS signaling (NRAS, KRAS, JAK1, JAK3, STAT3, STAT5B, IL7R, BRAF, NF1, SH2B3, PTPN11), hematopoietic development (RUNX1, ETV6, GATA3, IKZF1, EP300), chemical modification of histones (SUZ12, EED, EZH2, KMT2A, KMT2D, SETD2) and DNA methylation (DNMT3A, IDH1, IDH2, TET2, TET3). This panel was originally inspired by the repertoire of genes found to be preferentially altered in pediatric ETP-ALL,[23] and we have reported a subset of the results described in the current paper in a previous clinicobiological and genetic analysis of adult ETP-ALL.[24] Sequencing reads were analyzed using in-house software (Polyweb, Institut Imagine, Paris, France), and additional in-house custom filtering criteria (comprising minimum read counts and variant allele frequencies, and reference to external reference databases) were applied to minimize false-positive rates. Primers used to confirm mutations by direct sequencing are listed in Online Supplementary Table S2.

Outcome analyses

Comparisons between groups were performed with the Fisher exact and Mann-Whitney tests for categorical and continuous variables respectively. Corticosteroid sensitivity was defined as clearance of peripheral blood circulating blasts (<1 × 109/L) following steroid prophase treatment. Complete remission was defined as clearance of bone marrow blasts (<5%) following induction treatment. Overall survival was calculated from the date of inclusion in the trial to the last follow-up date, censoring patients alive at that date. Event-free survival was calculated from date of inclusion in the trial to the date of induction failure, relapse, or death, censoring patients alive in first complete remission without relapse at the last follow-up date. Cumulative incidence of relapse was calculated in patients who attained complete remission, from the date of achieving the complete remission to the date of relapse, with death in first complete remission being considered as a competing event. Univariate and bivariate analyses assessing the impact of DNMT3A mutations and age were performed with a Cox model. Variables that were significantly associated with outcome in univariate analysis were considered as covariates in multivariate Cox models. The proportional-hazards assumption was checked before conducting multivariate analyses. Statistical analyses were performed with STATA software (STATA 12.0 Corporation, College Station, TX, USA). All P values were two-sided, with P<0.05 denoting statistical significance.

Results

Analysis of DNMT3A genotype in patients with T-cell acute lymphoblastic leukemia in the GRAALL studies

We performed targeted NGS of a panel of genes, including DNMT3A, which have been described to be recurrently mutated in T-ALL. This panel included all exons of DNMT3A, thereby providing a comprehensive picture of the spectrum of alterations across this gene in T-ALL. Diagnostic DNA was available for 198 patients treated during the GRAALL-2003 and -2005 studies. A partial analysis of a subgroup of this cohort has been reported previously.[24] We detected 21 DNMT3A mutations in 18 patients (9.1%). Most alterations occurred in regions coding for defined protein functional domains, including six mutations at the R882 hotspot[1] (Figure 1A). Further details of patient-specific alterations are shown in Online Supplementary Table S3. Of note, the vast majority of detected mutations are predicted to be significantly damaging to protein function.
Figure 1.

DNMT3A mutations in T-cell acute lymphoblastic leukemia. (A) Schematic representation of the 21 mutations detected in this study. Further patient-specific details are provided in Online Supplementary Table S3. (B) Comparison of the mutational genotypes of DNMT3A altered (n=18) and DNMT3A wild-type (n=180) T-cell acute lymphoblastic leukemia. Percentage frequencies in each group are depicted. Functional categories are listed in bold.

DNMT3A mutations in T-cell acute lymphoblastic leukemia. (A) Schematic representation of the 21 mutations detected in this study. Further patient-specific details are provided in Online Supplementary Table S3. (B) Comparison of the mutational genotypes of DNMT3A altered (n=18) and DNMT3A wild-type (n=180) T-cell acute lymphoblastic leukemia. Percentage frequencies in each group are depicted. Functional categories are listed in bold. In keeping with previous reports of DNMT3A-mutated T-ALL which cited high rates of either compound heterozygosity or homozygosity,[9,11] a significant proportion of cases (8/18) had either two separate alterations, or high variant allele frequencies that were suggestive of either homozygous mutation, concomitant deletion of the wild-type (WT) allele or copy-neutral loss of heterozygosity. Comparative genomic hybridization analyses were available for 85 of the cases in this study, including 6/18 patients with DNMT3A mutations. We detected only two deletions of the DNMT3A locus, which in each case were associated with concomitant DNMT3A mutation and elevated variant allele frequencies (cases 11 and 12 in Online Supplementary Table S3). The prevalence of other mutations detected by NGS is shown in Figure 1B. DNMT3A-altered cases had an increased frequency of alterations in other genes included in the NGS panel, compared with the rest of the cohort (88.9% DNMT3A mutated vs. 64.4% DNMT3A WT, P=0.036). There were no statistically significant differences in the prevalence of mutations in any specific functional gene category, namely factors involved in cytokine receptor and RAS signaling (61.1% DNMT3A mutated vs. 41.7% DNMT3A WT, P=0.113), hematopoiesis (38.5% DNMT3A mutated vs. 12.8% DNMT3A WT, P=0.082) and chemical modification of histones (50.0% DNMT3A mutated vs. 30.0% DNMT3A WT, P=0.082). However, we did observe significant co-occurrence of DNMT3A alterations and IDH2 mutations (27.8% DNMT3A mutated vs. 2.2% DNMT3A WT, P<0.001). This association has been described previously in both AML[25] and myelodysplastic syndromes.[26]

Evidence of possible clonal hematopoiesis in DNMT3A-mutated T-cell acute lymphoblastic leukemia

DNMT3A is the most commonly altered gene in age-related clonal hematopoiesis,[27-29] and DNMT3A mutations have been detected in non-malignant cells in AML[30,31] and peripheral T-cell lymphoma.[14] We therefore tested whether DNMT3A mutations were present in non-leukemic hematopoietic cells in T-ALL patients. DNA from remission bone marrow was available for only three of the 18 patients with DNMT3A mutations. While two of these samples had a DNMT3A WT genotype (Online Supplementary Figure S1), one interesting case had evidence of DNMT3A alterations in non-leukemic bone marrow cells. At diagnosis, this patient (case 6 in Online Supplementary Table S3) had mutations in exons 14 and 15 of DNMT3A, a NOTCH1 PEST domain insertion, and an NRAS G12D substitution. Sequencing of remission DNA revealed mutation of DNMT3A exon 14 in non-leukemic cells, while NOTCH1, NRAS and DNMT3A exon 15 all presented wild-type genotypes (Figure 2A). We confirmed that the exon 14 mutation has never been reported as a polymorphic variant, while SIFT analysis () predicted this M548T substitution to be highly deleterious to protein function, with a SIFT score of 0. These results suggest that this T-ALL may have developed on a background of DNMT3A-mutated clonal hematopoiesis, and that the other genetic alterations, including the second DNMT3A mutation, were acquired at leukemic transformation.
Figure 2.

Evidence of DNMT3A mutations in non-leukemic DNA. (A) Direct sequencing of DNMT3A exons 14 and 15, NOTCH1 and NRAS in diagnostic (left panels) and remission (right panels) samples. (B) Mutational assessment of DNA extracted from leukemic and non-leukemic fractions of samples from patients with T-cell acute lymphoblastic leukemia. Sequencing results of DNMT3A and NOTCH1 in leukemic (left panels) and non-leukemic (right panels) DNA are shown. Cases are numbered according to the listing in Online Supplementary Table S3.

Evidence of DNMT3A mutations in non-leukemic DNA. (A) Direct sequencing of DNMT3A exons 14 and 15, NOTCH1 and NRAS in diagnostic (left panels) and remission (right panels) samples. (B) Mutational assessment of DNA extracted from leukemic and non-leukemic fractions of samples from patients with T-cell acute lymphoblastic leukemia. Sequencing results of DNMT3A and NOTCH1 in leukemic (left panels) and non-leukemic (right panels) DNA are shown. Cases are numbered according to the listing in Online Supplementary Table S3. In order to extend this analysis of non-leukemic DNMT3A mutation, we performed immunophenotypic sorting of two further diagnostic bone marrow samples, and extracted DNA from both the leukemic and the minor residual non-leukemic fractions. We detected a mutation in non-leukemic DNA in one patient (case 4 in Online Supplementary Table S3). Again, we confirmed that this mutation has not been reported as a polymorphism, and that the resultant P385L substitution is predicted to damage protein function, with a SIFT score of 0.02. Similar to the case with mutated remission DNA, this sample was negative for two NOTCH1 alterations detected at T-ALL diagnosis, confirming the specificity of DNMT3A mutation persistence (Figure 2B). The other tested non-leukemic DNA had a DNMT3A WT genotype (Online Supplementary Figure S2), giving an overall rate of non-leukemic DNMT3A mutant positivity of 2/5 samples from the GRAALL-2003 and -2005 studies. We also tested a further three T-ALL cases not included in this cohort, but found no evidence of non-leukemic DNMT3A mutation. This gives an overall incidence of possible clonal hematopoiesis in 2/8 T-ALL samples assessed in our laboratory. It was unfortunately not possible to obtain non-hematopoietic tissue from either of these patients, in order to exclude that these alterations were not constitutional, and to confirm definitively that these results reflect the persistence of a DNMT3A-mutated clonal hematopoietic population in these cases.

DNMT3A mutations are associated with older age and treatment resistance

A clinico-biological comparison of cases with and without DNMT3A mutations is shown in Table 1. In keeping with previous reports,[11,12] patients with mutations were considerably older than the rest of the T-ALL cohort (median age 43.9 years mutated vs. 29.4 years non-mutated, P<0.001). In addition, DNMT3A-mutated leukemias were more likely to have an immature T-receptor genotype[32] (53.3% mutated vs. 24.4% non-mutated, P=0.016), although this did not correspond to a significantly higher incidence of an ETP-ALL immunophenotype[33] (35.7% mutated vs. 20.3% non-mutated, P=0.184).
Table 1.

Characteristics and outcome of the patients according to DNMT3A genotype.

Characteristics and outcome of the patients according to DNMT3A genotype. DNMT3A mutation was notably associated with poor initial treatment response. We observed trends towards early corticosteroid resistance (66.7% mutated vs. 43.3% non-mutated, P=0.081) and induction failure (13.3% vs. 2.9%, P=0.096), and patients with DNMT3A mutations had significantly higher rates of death during induction (16.7% vs. 2.8%, P=0.027), and lower attainment of complete remission (72.2% mutated vs. 94.4% non-mutated, P=0.006). As only four patients with mutations were evaluated for minimal residual disease, we could not verify that molecular remission was similarly compromised. We found that the type of DNMT3A mutation did not significantly correlate with any individual clinico-biological parameter, suggesting that the alterations detected in this study are likely to have broadly similar biological consequences.

DNMT3A mutation correlates with poor outcome in T-cell acute lymphoblastic leukemia

The median follow-up of the cohort was 5.5 years. Prognostic analyses revealed that DNMT3A mutation was associated with an increased 5-year cumulative incidence of relapse (53.9% mutated vs. 28.7% non-mutated, P=0.037) (Figure 3A) and with 5-year event-free survival [27.8% mutated vs. 61.0% non-mutated; hazard ratio (HR) 3.22, (95% confidence interval (95% CI): 1.81-5.72, P<0.001] (Figure 3B). Patients with DNMT3A mutations also had a markedly inferior 5-year overall survival (38.8% mutated vs. 68.7% non-mutated, HR 2.91, 95% CI: 1.56-5.43, P=0.001) (Figure 3C).
Figure 3.

DNMT3A mutation correlates with poor outcome in T-cell acute lymphoblastic leukemia. Comparisons of outcomes for patients with (n=18) and without (n=180) DNMT3A mutations are shown for: (A) cumulative incidence of relapse; (B) event-free survival; and (C) overall survival. The 5-year results were as follows: cumulative incidence of relapse 53.9% mutated vs. 28.7% non-mutated; event-free survival 27.8% mutated vs. 61.0% non-mutated; overall survival 38.8% mutated vs. 68.7% non-mutated. P values are indicated.

DNMT3A mutation correlates with poor outcome in T-cell acute lymphoblastic leukemia. Comparisons of outcomes for patients with (n=18) and without (n=180) DNMT3A mutations are shown for: (A) cumulative incidence of relapse; (B) event-free survival; and (C) overall survival. The 5-year results were as follows: cumulative incidence of relapse 53.9% mutated vs. 28.7% non-mutated; event-free survival 27.8% mutated vs. 61.0% non-mutated; overall survival 38.8% mutated vs. 68.7% non-mutated. P values are indicated.

The poor prognosis of DNMT3A-mutated T-cell acute lymphoblastic leukemia is age-independent

Our and others’ data[11,12] have shown that the incidence of DNMT3A mutation in T-ALL increases with age, but previous reports have not documented whether this factor contributes to prognosis. As older patients treated during the GRAALL studies had worse outcomes due to impaired tolerance of intensive chemotherapy,[34] we considered it critical to determine to what extent age was a confounding prognostic variable. We therefore performed bivariate analyses of the effects of DNMT3A mutations and age across a series of outcome measures. These results are shown in Online Supplementary Table S4. In each case, DNMT3A genotype was still associated with significantly increased cumulative incidence of relapse (HR 2.80, 95% CI: 1.12-6.97, P=0.034), and shorter event-free survival (HR 2.62, 95% CI: 1.45–5.06, P=0.004) and overall survival (HR 2.05, 95% CI: 1.02-4.12, P=0.043). Since DNMT3A alterations were almost exclusively found in patients >40 years (16/18 cases), we also performed survival analyses that were restricted to the >40-year old subgroup, which constituted a quarter of the total cohort of patients (50/198, 25.3%). Consistent with the results of the bivariate analyses, DNMT3A mutation was associated with significantly worse 5-year cumulative incidence of relapse (58.3% mutated vs. 21.7% non-mutated, HR 3.90, 95% CI: 1.30-11.68, P=0.015) (Figure 4A), 5-year event-free survival (25.0% mutated vs. 56.7% non-mutated, HR 2.95, 95% CI: 1.37-6.32, P=0.005) (Figure 4B), and 5-year overall survival (37.5% mutated vs. 62.1% non-mutated, HR 2.35, 95% CI: 1.05-5.26, P=0.038) (Figure 4C).
Figure 4.

DNMT3A genotype predicts outcome in the age group of patients at risk of mutation. Comparisons of outcomes for patients with (n=16) and without (n=34) mutations in patients >40 years are shown for: (A) cumulative incidence of relapse; (B) event-free survival; and (C) overall survival. The 5-year results were as follows: cumulative incidence of relapse 58.3% mutated vs. 21.7% non-mutated; event-free survival, 25.0% mutated vs. 56.7% non-mutated; overall survival 37.5% mutated vs. 62.1% non-mutated. P values are indicated.

DNMT3A genotype predicts outcome in the age group of patients at risk of mutation. Comparisons of outcomes for patients with (n=16) and without (n=34) mutations in patients >40 years are shown for: (A) cumulative incidence of relapse; (B) event-free survival; and (C) overall survival. The 5-year results were as follows: cumulative incidence of relapse 58.3% mutated vs. 21.7% non-mutated; event-free survival, 25.0% mutated vs. 56.7% non-mutated; overall survival 37.5% mutated vs. 62.1% non-mutated. P values are indicated. Finally, we carried out multivariate outcome analyses in the whole cohort using the risk factors that were used to stratify treatment during the GRAALL-2003 and -2005 studies, and which were found to significantly predict prognosis in the univariate analyses. Among age, log(WBC), corticosteroid sensitivity, early chemosensitivity, and DNMT3A genotype, only DNMT3A genotype was associated with cumulative incidence of relapse in univariate analysis (data not shown). As shown in Tables 2 and 3, age, log(WBC), corticosteroid resistance along with DNMT3A genotype were significantly associated with a poor event-free survival and overall survival. In multivariate analysis adjusting for these covariates, DNMT3A mutation was still significantly associated with shorter event-free survival (HR 2.33, 95% CI: 1.06–4.04, P=0.02) (Table 2), although not with overall survival (HR 1.66, 95% CI: 0.82–3.37, P=0.16) (Table 3).
Table 2.

Prognostic impact of DNMT3A genotype on event-free survival.

Table 3.

Prognostic impact of DNMT3A genotype on overall survival.

Prognostic impact of DNMT3A genotype on event-free survival. Prognostic impact of DNMT3A genotype on overall survival. Taken together, these results provide strong evidence that DNMT3A mutation, while mostly observed in older cases, predicts a poor prognosis that is not related to the patient’s age.

Discussion

To our knowledge, this is the most extensive study of DNMT3A-mutated T-ALL yet reported. Our targeted NGS approach allowed comprehensive assessment of genotype across the entire DNMT3A locus, along with the prevalence of co-occurring genetic alterations. Our data additionally benefit from the analysis of a large cohort of patients who were uniformly treated as part of the GRAALL-2003 and -2005 studies, thereby allowing rigorous outcome comparisons between mutated and wild-type cases. Some of our results were expected, and the findings that DNMT3A mutations are more commonly present in older patients and genotypically immature leukemias are consistent with previously published data.[9,11-13] We did not, however, observe increased rates of ETP-ALL immunophenotype, as might have been predicted. We did not detect a clear association with any other genetically-defined subgroup, and there was no link to increased HOXA expression, which we have previously shown to predict outcome in immature T-ALL.[35] The detection of DNMT3A alterations in non-leukemic bone marrow suggests that some of these cases of T-ALL might have arisen from DNMT3A-mutated clonal hematopoiesis. While pre-leukemic NOTCH1 mutations have been detected in neonatal blood spot samples of pediatric patients with T-ALL,[36] to our knowledge our data provide the first potential evidence of age-related clonal hematopoiesis in T-ALL. As it was not possible to obtain non-hematopoietic tissue from either of the patients with this finding, we cannot definitively exclude that these alterations are constitutional, or might even represent an inherited cancer predisposition. Further work is necessary to investigate the incidence of clonal hematopoiesis linked to alterations in DNMT3A and other genes in T-ALL. Non-leukemic DNMT3A mutations have been seen in AML,[30,31] and it has been postulated that DNMT3A-altered immature T-ALL might arise from malignant transformation of a multipotent myeloid/lymphoid progenitor cell.[12] In keeping with this, one of the cases with a non-leukemic DNMT3A mutation in this study had expression of myeloid cell surface markers as part of an ETP-ALL phenotype, while full immunophenotypic assessment was unfortunately not possible for the other patient. The factors that may dictate the acute leukemic phenotype in clonally mutated cases remain to be clarified. For example, this might be influenced by the differentiation capacity of the cell in which the initial DNMT3A mutation occurs. In addition, it is tempting to speculate that the acquisition of specific cooperative mutations, such as the NOTCH1 mutations observed in these T-ALL cases, might act as lineage determinants. Outcome analyses revealed that DNMT3A mutation correlated with poor prognosis independently of the patients’ age in bivariate analyses. Multivariable analyses using parameters that were used to stratify treatment in the GRAALL-2003 and -2005 studies showed that DNMT3A genotype independently predicted both event-free survival and cumulative incidence of relapse. DNMT3A mutation status also independently predicted event-free survival and overall survival in bivariable analyses that incorporated our recently described oncogenetic risk classifier[37] (Online Supplementary Table S5). These results suggest that DNMT3A mutation is directly linked to aggressive T-ALL biology. As DNMT3A-altered T-ALL had higher mutation rates in other genes included in our targeted sequencing panel, it is also possible that increased genotype complexity may contribute to the more aggressive phenotype in these leukemias. This issue may be clarified by more comprehensive genomic assessment in future studies. The high rates of treatment failure observed in this study suggest that therapeutic intervention is warranted for DNMT3A-mutated cases, and that treatment intensification should be considered for the infrequent younger patients with mutations. Indeed, we have previously documented a benefit from allogeneic stem cell transplantation in first complete remission for ETP-ALL,[24] which similarly exhibits high rates of intrinsically treatment-resistant disease. As only three of the 18 DNMT3A-mutated patients in this study underwent allogeneic stem cell transplantation (data not shown), we are unable to estimate the potential benefit of such treatment in this setting. We recently reported that treatment-related toxicity in the GRAALL-2005 study increased in proportion to the patients’ age,[38] and further therapy intensification in elderly patients must therefore be considered of questionable benefit. The upper age of this study cohort was 60 years, but it is likely that the rate of mutations in older patients who do not tolerate such intensive chemotherapy is higher. Data reported for patients with AML suggest that DNMT3A mutation confers increased sensitivity to hypomethylating agents,[39] providing a rationale for evaluation of these drugs in DNMT3A-mutated T-ALL. In the longer term, it is to be hoped that investigation of the molecular mechanisms by which DNMT3A mutation alters T-ALL biology will lead to better treatments and improved outcomes for these high-risk cases.
  38 in total

1.  NOTCH1 mutation can be an early, prenatal genetic event in T-ALL.

Authors:  Minenori Eguchi-Ishimae; Mariko Eguchi; Helena Kempski; Mel Greaves
Journal:  Blood       Date:  2007-09-27       Impact factor: 22.113

2.  Gene mutation patterns and their prognostic impact in a cohort of 1185 patients with acute myeloid leukemia.

Authors:  Yang Shen; Yong-Mei Zhu; Xing Fan; Jing-Yi Shi; Qin-Rong Wang; Xiao-Jing Yan; Zhao-Hui Gu; Yan-Yan Wang; Bing Chen; Chun-Lei Jiang; Han Yan; Fei-Fei Chen; Hai-Min Chen; Zhu Chen; Jie Jin; Sai-Juan Chen
Journal:  Blood       Date:  2011-08-31       Impact factor: 22.113

3.  DNMT3A mutations in myeloproliferative neoplasms.

Authors:  F Stegelmann; L Bullinger; R F Schlenk; P Paschka; M Griesshammer; C Blersch; S Kuhn; S Schauer; H Döhner; K Döhner
Journal:  Leukemia       Date:  2011-05-03       Impact factor: 11.528

4.  Mutational spectrum analysis of chronic myelomonocytic leukemia includes genes associated with epigenetic regulation: UTX, EZH2, and DNMT3A.

Authors:  Anna M Jankowska; Hideki Makishima; Ramon V Tiu; Hadrian Szpurka; Yun Huang; Fabiola Traina; Valeria Visconte; Yuka Sugimoto; Courtney Prince; Christine O'Keefe; Eric D Hsi; Alan List; Mikkael A Sekeres; Anjana Rao; Michael A McDevitt; Jaroslaw P Maciejewski
Journal:  Blood       Date:  2011-08-09       Impact factor: 22.113

5.  DNMT3A mutations in acute myeloid leukemia.

Authors:  Timothy J Ley; Li Ding; Matthew J Walter; Michael D McLellan; Tamara Lamprecht; David E Larson; Cyriac Kandoth; Jacqueline E Payton; Jack Baty; John Welch; Christopher C Harris; Cheryl F Lichti; R Reid Townsend; Robert S Fulton; David J Dooling; Daniel C Koboldt; Heather Schmidt; Qunyuan Zhang; John R Osborne; Ling Lin; Michelle O'Laughlin; Joshua F McMichael; Kim D Delehaunty; Sean D McGrath; Lucinda A Fulton; Vincent J Magrini; Tammi L Vickery; Jasreet Hundal; Lisa L Cook; Joshua J Conyers; Gary W Swift; Jerry P Reed; Patricia A Alldredge; Todd Wylie; Jason Walker; Joelle Kalicki; Mark A Watson; Sharon Heath; William D Shannon; Nobish Varghese; Rakesh Nagarajan; Peter Westervelt; Michael H Tomasson; Daniel C Link; Timothy A Graubert; John F DiPersio; Elaine R Mardis; Richard K Wilson
Journal:  N Engl J Med       Date:  2010-11-10       Impact factor: 91.245

6.  Exome sequencing identifies somatic mutations of DNA methyltransferase gene DNMT3A in acute monocytic leukemia.

Authors:  Xiao-Jing Yan; Jie Xu; Zhao-Hui Gu; Chun-Ming Pan; Gang Lu; Yang Shen; Jing-Yi Shi; Yong-Mei Zhu; Lin Tang; Xiao-Wei Zhang; Wen-Xue Liang; Jian-Qing Mi; Huai-Dong Song; Ke-Qin Li; Zhu Chen; Sai-Juan Chen
Journal:  Nat Genet       Date:  2011-03-13       Impact factor: 38.330

7.  Early T-cell precursor leukaemia: a subtype of very high-risk acute lymphoblastic leukaemia.

Authors:  Elaine Coustan-Smith; Charles G Mullighan; Mihaela Onciu; Frederick G Behm; Susana C Raimondi; Deqing Pei; Cheng Cheng; Xiaoping Su; Jeffrey E Rubnitz; Giuseppe Basso; Andrea Biondi; Ching-Hon Pui; James R Downing; Dario Campana
Journal:  Lancet Oncol       Date:  2009-01-13       Impact factor: 41.316

8.  Analysis of TCR, pT alpha, and RAG-1 in T-acute lymphoblastic leukemias improves understanding of early human T-lymphoid lineage commitment.

Authors:  Vahid Asnafi; Kheira Beldjord; Emmanuelle Boulanger; Béatrice Comba; Patricia Le Tutour; Marie-Hélène Estienne; Frédéric Davi; Judith Landman-Parker; Pierre Quartier; Agnès Buzyn; Eric Delabesse; Françoise Valensi; Elizabeth Macintyre
Journal:  Blood       Date:  2002-11-21       Impact factor: 22.113

9.  Pediatric-inspired therapy in adults with Philadelphia chromosome-negative acute lymphoblastic leukemia: the GRAALL-2003 study.

Authors:  Françoise Huguet; Thibaut Leguay; Emmanuel Raffoux; Xavier Thomas; Kheira Beldjord; Eric Delabesse; Patrice Chevallier; Agnes Buzyn; André Delannoy; Yves Chalandon; Jean-Paul Vernant; Marina Lafage-Pochitaloff; Agnès Chassevent; Véronique Lhéritier; Elizabeth Macintyre; Marie-Christine Béné; Norbert Ifrah; Hervé Dombret
Journal:  J Clin Oncol       Date:  2009-01-05       Impact factor: 44.544

10.  Leukemic mutations in the methylation-associated genes DNMT3A and IDH2 are rare events in pediatric AML: a report from the Children's Oncology Group.

Authors:  Phoenix A Ho; Matthew A Kutny; Todd A Alonzo; Robert B Gerbing; Jason Joaquin; Susana C Raimondi; Alan S Gamis; Soheil Meshinchi
Journal:  Pediatr Blood Cancer       Date:  2011-04-18       Impact factor: 3.838

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  14 in total

1.  Activation of Notch and Myc Signaling via B-cell-Restricted Depletion of Dnmt3a Generates a Consistent Murine Model of Chronic Lymphocytic Leukemia.

Authors:  Anat Biran; Shanye Yin; Helene Kretzmer; Elisa Ten Hacken; Salma Parvin; Fabienne Lucas; Mohamed Uduman; Catherine Gutierrez; Nathan Dangle; Leah Billington; Fara Faye Regis; Laura Z Rassenti; Arman Mohammad; Gabriela Brunsting Hoffmann; Kristen Stevenson; Mei Zheng; Elizabeth Witten; Stacey M Fernandes; Eugen Tausch; Clare Sun; Stephan Stilgenbauer; Jennifer R Brown; Thomas J Kipps; John C Aster; Andreas Gnirke; Donna S Neuberg; Anthony Letai; Lili Wang; Ruben D Carrasco; Alexander Meissner; Catherine J Wu
Journal:  Cancer Res       Date:  2021-10-22       Impact factor: 13.312

2.  14q32 rearrangements deregulating BCL11B mark a distinct subgroup of T-lymphoid and myeloid immature acute leukemia.

Authors:  Danika Di Giacomo; Roberta La Starza; Paolo Gorello; Fabrizia Pellanera; Zeynep Kalender Atak; Kim De Keersmaecker; Valentina Pierini; Christine J Harrison; Silvia Arniani; Martina Moretti; Nicoletta Testoni; Giovanna De Santis; Giovanni Roti; Caterina Matteucci; Renato Bassan; Peter Vandenberghe; Stein Aerts; Jan Cools; Beat Bornhauser; Jean-Pierre Bourquin; Rocco Piazza; Cristina Mecucci
Journal:  Blood       Date:  2021-09-02       Impact factor: 22.113

Review 3.  Zebrafish models of acute leukemias: Current models and future directions.

Authors:  Brandon Molina; Jasmine Chavez; Stephanie Grainger
Journal:  Wiley Interdiscip Rev Dev Biol       Date:  2020-12-19       Impact factor: 5.814

4.  [Clonal evolution of myelodysplastic syndrome].

Authors:  B Q Luo; F Dong; M X F Ema
Journal:  Zhonghua Xue Ye Xue Za Zhi       Date:  2019-12-14

5.  Bioinformatics Analysis Identifies Key Genes and Pathways in Acute Myeloid Leukemia Associated with DNMT3A Mutation.

Authors:  Shuyi Chen; Yimin Chen; Jielun Lu; Danyun Yuan; Lang He; Huo Tan; Lihua Xu
Journal:  Biomed Res Int       Date:  2020-11-23       Impact factor: 3.411

6.  Prognostic Significance of Comprehensive Gene Mutations and Clinical Characteristics in Adult T-Cell Acute Lymphoblastic Leukemia Based on Next-Generation Sequencing.

Authors:  Hua Yin; Mei Hong; Jun Deng; Lan Yao; Chenjing Qian; Yao Teng; Tingting Li; Qiuling Wu
Journal:  Front Oncol       Date:  2022-02-24       Impact factor: 6.244

Review 7.  Alterations to DNMT3A in Hematologic Malignancies.

Authors:  Kartika Venugopal; Yang Feng; Daniil Shabashvili; Olga A Guryanova
Journal:  Cancer Res       Date:  2020-10-21       Impact factor: 13.312

8.  Epigenetic landscape analysis of lncRNAs in acute myeloid leukemia with DNMT3A mutations.

Authors:  Yu-Jun Dai; Fang Hu; Si-Yuan He; Yue-Ying Wang
Journal:  Ann Transl Med       Date:  2020-03

9.  A transcriptomic continuum of differentiation arrest identifies myeloid interface acute leukemias with poor prognosis.

Authors:  Jonathan Bond; Aleksandra Krzywon; Ludovic Lhermitte; Christophe Roumier; Anne Roggy; Mohamed Belhocine; Alexander Abdulkader Kheirallah; Patrick Villarese; Guillaume Hypolite; Francine Garnache-Ottou; Sylvie Castaigne; Nicolas Boissel; Vahid Asnafi; Claude Preudhomme; Hervé Dombret; Elisa Laurenti; Elizabeth Macintyre
Journal:  Leukemia       Date:  2020-07-13       Impact factor: 11.528

10.  TET2 and DNMT3A mutations and exceptional response to 4'-thio-2'-deoxycytidine in human solid tumor models.

Authors:  Sherry X Yang; Melinda Hollingshead; Larry Rubinstein; Dat Nguyen; Angelo B A Larenjeira; Robert J Kinders; Michael Difilippantonio; James H Doroshow
Journal:  J Hematol Oncol       Date:  2021-05-26       Impact factor: 17.388

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