Norio Shiba

The landscape of somatic mutations in Down syndrome–related myeloid disorders

Transient abnormal myelopoiesis (TAM) is a myeloid proliferation resembling acute megakaryoblastic leukemia (AMKL), mostly affecting perinatal infants with Down syndrome. Although self-limiting in a majority of cases, TAM may evolve as non-self-limiting AMKL after spontaneous remission (DS-AMKL). Pathogenesis of these Down syndrome–related myeloid disorders is poorly understood, except for GATA1 mutations found in most cases. Here we report genomic profiling of 41 TAM, 49 DS-AMKL and 19 non-DS-AMKL samples, including whole-genome and/or whole-exome sequencing of 15 TAM and 14 DS-AMKL samples. TAM appears to be caused by a single GATA1 mutation and constitutive trisomy 21. Subsequent AMKL evolves from a pre-existing TAM clone through the acquisition of additional mutations, with major mutational targets including multiple cohesin components (53%), CTCF (20%), and EZH2, KANSL1 and other epigenetic regulators (45%), as well as common signaling pathways, such as the JAK family kinases, MPL, SH2B3 (LNK) and multiple RAS pathway genes (47%).

An empirical Bayesian framework for somatic mutation detection from cancer genome sequencing data

Recent advances in high-throughput sequencing technologies have enabled a comprehensive dissection of the cancer genome clarifying a large number of somatic mutations in a wide variety of cancer types. A number of methods have been proposed for mutation calling based on a large amount of sequencing data, which is accomplished in most cases by statistically evaluating the difference in the observed allele frequencies of possible single nucleotide variants between tumours and paired normal samples. However, an accurate detection of mutations remains a challenge under low sequencing depths or tumour contents. To overcome this problem, we propose a novel method, Empirical Bayesian mutation Calling (https://github.com/friend1ws/EBCall), for detecting somatic mutations. Unlike previous methods, the proposed method discriminates somatic mutations from sequencing errors based on an empirical Bayesian framework, where the model parameters are estimated using sequencing data from multiple non-paired normal samples. Using 13 whole-exome sequencing data with 87.5–206.3 mean sequencing depths, we demonstrate that our method not only outperforms several existing methods in the calling of mutations with moderate allele frequencies but also enables accurate calling of mutations with low allele frequencies (≤10%) harboured within a minor tumour subpopulation, thus allowing for the deciphering of fine substructures within a tumour specimen.

NUP98-NSD1 gene fusion and its related gene expression signature are strongly associated with a poor prognosis in pediatric acute myeloid leukemia.

The cryptic t(5;11)(q35;p15.5) creates a fusion gene between the NUP98 and NSD1 genes. To ascertain the significance of this gene fusion, we explored its frequency, clinical impact, and gene expression pattern using DNA microarray in pediatric acute myeloid leukemia (AML) patients. NUP98‐NSD1 fusion transcripts were detected in 6 (4.8%) of 124 pediatric AML patients. Supervised hierarchical clustering analyses using probe sets that were differentially expressed in these patients detected a characteristic gene expression pattern, including 18 NUP98‐NSD1‐negative patients (NUP98‐NSD1‐like patients). In total, a NUP98‐NSD1‐related gene expression signature (NUP98‐NSD1 signature) was found in 19% (24/124) and in 58% (15/26) of cytogenetically normal cases. Their 4‐year overall survival (OS) and event‐free survival (EFS) were poor (33.3% in NUP98‐NSD1‐positive and 38.9% in NUP98‐NSD1‐like patients) compared with 100 NUP98‐NSD1 signature‐negative patients (4‐year OS: 86.0%, 4‐year EFS: 72.0%). Interestingly, t(7;11)(p15;p15)/NUP98‐HOXA13, t(6;11)(q27;q23)/MLL‐MLLT4 and t(6;9)(p22;q34)/DEK‐NUP214, which are known as poor prognostic markers, were found in NUP98‐NSD1‐like patients. Furthermore, another type of NUP98‐NSD1 fusion transcript was identified by additional RT‐PCR analyses using other primers in a NUP98‐NSD1‐like patient, revealing the significance of this signature to detect NUP98‐NSD1 gene fusions and to identify a new poor prognostic subgroup in AML.

CBL mutations in juvenile myelomonocytic leukemia and pediatric myelodysplastic syndrome

Divergent cytotoxic effects of PKC412 in combination with conventional antileukemic agents in FLT3 mutation-positive versus negative leukemia cell lines. Leukemia 2007; 21: 1005–1014. 5 Kim H-G, Lee KW, Cho Y-Y, Kang NJ, Oh S-M, Bode AM et al. Mitogenand stress-activated kinase 1-mediated histone H3 phosphorylation is crucial for cell transformation. Cancer Res 2008; 68: 2538–2547. 6 Srinivasa SP, Doshi PD. Extracellular signal-regulated kinase and p38 mitogen-activated protein kinase pathways cooperate in mediating cytokine-induced proliferation of a leukemic cell line. Leukemia 2002; 16: 244–253. 7 Parmar S, Katsoulidis E, Verma A, Li Y, Sassano A, Lal L et al. Role of the p38 mitogen-activated protein kinase pathway in the generation of the effects of imatinib mesylate (STI571) in BCR-ABLexpressing cells. J Biol Chem 2004; 279: 25345–25352. 8 Dumka D, Puri P, Carayoi N, Balachandran H, Schuster K, Verma AK et al. Activation of the p38 MAP kinase pathway is essential for the antileukemic effects of dasatinib. Leuk Lymphoma 2009; 50: 2017–2029.

High expression of EVI1 and MEL1 is a compelling poor prognostic marker of pediatric AML

EVI1 and MEL1 are homolog genes whose transcriptional activations by chromosomal translocations are known in small subsets of leukemia. From gene expression profiling data of 130 Japanese pediatric acute myeloid leukemia (AML) patients, we found that EVI1 and MEL1 were overexpressed in ~30% of patients without obvious translocations of these gene loci, and that their high expression was significantly associated with inferior survival. High EVI1 expression was detected mainly in myelomonocytic-lineage (designated as e-M4/M5 subtype) leukemia with MLL rearrangements and in megakaryocytic-lineage (designated as e-M7 subtype) leukemia, and its prognostic association was observed in the e-M4/M5 subtype but not in the e-M7 subtype. On the other hand, high MEL1 expression was detected in myelocytic-lineage (designated as e-M0/M1/M2 subtype) and e-M4/M5 subtype leukemia without MLL rearrangements, and its prognostic association was independent from the subtypes. Because of their subtype-dependent and mutually exclusive expression, a combined evaluation of their high expression enabled a clear distinction of patients with inferior survival (P<0.00001 in event-free survival (EFS) and overall survival (OS)). This association was confirmed by quantitative reverse transcription PCR analysis of an independent cohort of 81 patients (P=0.00017 in EFS, P=0.00028 in OS). We propose that the combined estimation of EVI1 and MEL1 expression will be an effective method to predict the prognosis of pediatric AML.

Whole-exome sequencing reveals the spectrum of gene mutations and the clonal evolution patterns in paediatric acute myeloid leukaemia.

Acute myeloid leukaemia (AML) is a molecularly and clinically heterogeneous disease. Targeted sequencing efforts have identified several mutations with diagnostic and prognostic values in KIT, NPM1, CEBPA and FLT3 in both adult and paediatric AML. In addition, massively parallel sequencing enabled the discovery of recurrent mutations (i.e. IDH1/2 and DNMT3A) in adult AML. In this study, whole‐exome sequencing (WES) of 22 paediatric AML patients revealed mutations in components of the cohesin complex (RAD21 and SMC3), BCORL1 and ASXL2 in addition to previously known gene mutations. We also revealed intratumoural heterogeneities in many patients, implicating multiple clonal evolution events in the development of AML. Furthermore, targeted deep sequencing in 182 paediatric AML patients identified three major categories of recurrently mutated genes: cohesion complex genes [STAG2, RAD21 and SMC3 in 17 patients (8·3%)], epigenetic regulators [ASXL1/ASXL2 in 17 patients (8·3%), BCOR/BCORL1 in 7 patients (3·4%)] and signalling molecules. We also performed WES in four patients with relapsed AML. Relapsed AML evolved from one of the subclones at the initial phase and was accompanied by many additional mutations, including common driver mutations that were absent or existed only with lower allele frequency in the diagnostic samples, indicating a multistep process causing leukaemia recurrence.

DNMT3A mutations are rare in childhood acute myeloid leukaemia, myelodysplastic syndromes and juvenile myelomonocytic leukaemia

Acute myeloid leukaemia (AML) is a complex disease caused by mutations and deregulated gene expression, leading to increased proliferation and decreased differentiation of haematopoietic progenitor cells. Contemporary treatments have resulted in 5-year event-free survival rates of almost 60% for paediatric AML (Pui et al, 2011). Recently, a whole genome sequencing study of AML uncovered recurrent mutations of an epigenetic regulator, the DNA methyltransferase 3A (DNMT3A) gene, in approximately 20% of adult AML patients (Ley et al, 2010; Yamashita et al, 2010; Yan et al, 2011). In these studies, DNMT3A mutations were frequently associated with FLT3-internal tandem duplication (ITD), nucleophosmin 1 (NPM1) and isocitrate dehydrogenase 1 (IDH1) mutations (Ley et al, 2010; Yan et al, 2011). DNMT3A mutations were also found in adult myelodysplastic syndromes (MDS) (8%, 12/150) (Walter et al, 2011), AML secondary to myeloproliferative neoplasms (MPNs) (14%, 5/35), myelofibrosis (15%, 3/20) and polycythaemia vera (7%, 2/30) (Stegelmann et al, 2011). DNMT3A is involved in epigenetic regulation of genes by enzymatic de novo addition of methyl groups to the cytosine residue of CpG dinucleotides. DNMT3A mutations were significantly enriched with a cytogenetic profile associated with intermediate risk, including a normal cytogenetic profile, as well as the M4 and M5 subtypes, according to the French-AmericanBritish (FAB) classification system (Ley et al, 2010; Yan et al, 2011). In AML patients with a normal karyotype and FLT3-ITD, patients with DNMT3A gene mutations showed a worse prognosis than those without DNMT3A gene mutations (Ley et al, 2010; Yan et al, 2011); however, the frequency and clinical impact of DNMT3A gene mutations in paediatric AML and myeloproliferative neoplasms (MPN) remain uncertain. We searched for DNMT3A gene mutations in 149 AMLs who were treated on the Japanese Childhood AML Cooperative protocol, AML 99 (range: 0–15 years old, M0: 5, M1: 23, M2: 44, M3: 13, M4: 22, M5: 21, M6: 1, M7: 17, unclassified: three patients), 40 juvenile myelomonocytic leukaemias (JMMLs; range: 2 months to 8 years), 24 myelodysplastic syndromes (MDSs) and 20 paediatric therapyrelated leukaemia/MDSs (t-Leuk/MDSs, range: 1–17 years). FLT3-ITD and NPM1 gene alterations have been reported in these 149 AML patients (Shimada et al, 2007, 2008). Total RNA extracted from the bone marrow or peripheral blood samples at diagnosis was reverse transcribed to cDNA with a cDNA Synthesis Kit (Amersham Bioscience, Tokyo, Japan). DNMT3A mutations were thus far reported to be almost exclusively involved in exons 16-23 (especially codon R882 in exon 23) (Ley et al, 2010; Yamashita et al, 2010; Stegelmann et al, 2011; Walter et al, 2011; Yan et al, 2011); thus, we confined our analysis to these exons. cDNA was amplified using the following primers: DNMT3A cDNA 15F, 5¢-CAGGTGCTTTTGCGTGGAGTGT-3¢ and 19R, 5¢-ATGC AGGAGGCGGTAGAACTCA-3¢, 17F, 5¢-AAGATCATGTACGTCGGGGA-3¢ and 22R, 5¢-CTTTGCCCTGCTTTA TGGAG-3¢ and 20F, 5¢-CCCTGTGATGATTGATGCCA-3¢ and 23R, 5¢-GTATTTCCGCCTCTGTG-GTT-3¢ for AML samples. For JMML, MDS and t-Leuk/MDS, we confined our analysis to exon 23, including the hotspot of codon R882, of the DNMT3A gene using the following primers: DNMT3A DNA 23F, 5¢-AGAACTAAGCAGGGCC-TCAGAGGA-3¢ and 23R, 5¢-GTATTTCCGCCTCTGTGGTT-3¢. Subsequently, direct sequencing was performed on a DNA sequencer (ABI 310; Applied Biosystems, Foster City, CA, USA) using a BigDye terminator cycle sequencing kit (Applied Biosystems). The study adhered to the principles of the Helsinki Declaration, and was conducted under the regulations enacted by the Ethics Board of Gunma Children’s Medical Centre. No DNMT3A mutations were detected in any AML patients in our study. Recently, DNMT3A mutations have been reported in paediatric AML patients (Ho et al, 2011; Thol et al, 2011). Only two patients were identified (both 15 years old). Combined with these and our data, the frequency of DNMT3A mutations is extremely rare (2/524, 0Æ4%) in childhood AML. Furthermore, we did not identify DNMT3A mutations in MDS, JMML or paediatric t-Leuk/MDS. These findings were not compatible with those of adult MDS and MPN, suggesting that the frequency of DNMT3A gene mutations depends on age. On the other hand, we found FLT3-ITD in 20 (13%) of 149 AML patients; however, no NPM1 mutations were found (Shimada et al, 2007, 2008). Nine AML patients with FLT3ITD were found to lack DNMT3A mutation. DNMT3A mutations have been correlated with FLT3-ITD and NPM1 in adult AML, but not in paediatric AML. Although patients with DNMT3A mutations have been associated with FAB-M4, M5, especially MLL-negative M5, no mutations in these paediatric M4/M5 patients were found in this study. DNMT3A mutations have not been detected in any adult AML with favourable cytogenetics, including t(8;21) and inv(16) (Ley et al, 2010; Yan et al, 2011). Higher frequencies of t(8;21) and inv(16) in Correspondence

EVI1 overexpression is a poor prognostic factor in pediatric patients with mixed lineage leukemia-AF9 rearranged acute myeloid leukemia

The ecotropic viral integration site-1 gene (EVI1) encodes a zinc finger protein that functions as a transcriptional regulator of hematopoietic stem cell self-renewal and long-term multilineage repopulating activity.1,2 The mixed lineage leukemia gene (MLL) rearrangements [i.e. t(11q23)] occur at high frequency in pediatric acute myeloid leukemia (AML) patients with EVI1 overexpression,3 and EVI1 is a transcriptional target of MLL oncoproteins.4 EVI1 overexpression has been reported in up to 10% of patients with AML and is associated with an adverse prognosis. However, the prognostic value of EVI1 overexpression has been studied mostly in adult AML.5–9 Only two studies have examined EVI1 overexpression in pediatric AML, but a detailed analysis according to the type of leukemia was not performed because of the small sample size.3,10 Recent data from an international consortium, including those from our group, suggest that pediatric MLL-rearranged AML can be divided into certain risk groups on the basis of different translocation partners.11 However, clinical outcome data leading to risk stratification of the MLL-rearranged subgroups are still scarce and further investigation is necessary to identify new prognostic factors. Here, we retrospectively examined EVI1 expression levels and clinical outcomes of pediatric MLL-rearranged AML patients treated in the Japanese Pediatric Leukemia/Lymphoma Study Group (JPLSG) AML-05 study. After excluding patients with acute promyelocytic leukemia, Down syndrome, secondary AML, myeloid/natural killer cell leukemia and myeloid sarcoma, 485 AML patients were enrolled in the AML-05 study. Overall, 42 patients were excluded, mainly because of misdiagnosis. Details of the treatment schedules and risk stratification were described in previous publication.12 This study was conducted in accordance with the principles set down in the Declaration of Helsinki and was approved by the Ethics Committees of all participating institutions. All patients, or the patients’ parents/guardians, provided written informed consent. RNA obtained from diagnostic bone marrow samples was used to analyze the expression of EVI1 using a previously established EVI1 quantitative real-time polymerase chain reaction assay that covers the various EVI1 splice variants.7 Event-free survival (EFS) was defined as the time from the diagnosis of AML to the last follow up or the first event (failure to achieve remission, relapse, secondary malignancy, or any cause of death). In this study, most of the events were relapses (n=23) and the rest were deaths with sepsis (n=1) and acute respiratory distress syndrome (n=1). Overall survival (OS) was defined as the time from the diagnosis of AML to any cause of death. All tests were two-tailed and P<0.05 was considered statistically significant. Among 443 eligible AML patients, 69 were diagnosed as MLL-rearranged AML and diagnostic samples from 50 patients were analyzed for EVI1 mRNA expression. No significant differences in the characteristics and clinical outcomes were observed between these 50 patients and the 19 patients who did not have EVI1 data [EFS (P=0.20), OS (P=0.45)]. EVI1 expression levels were dichotomized based on a cut off of 0.1 relative to SKOV3, an ovarian carcinoma cell line overexpressing EVI1: values higher than 0.1 were defined as EVI1+ and those lower than 0.1 or undetectable were defined as EVI1−, as described in a previous study.7 EVI1+ was present in 18 patients (36%). EVI1 expression levels in different MLL translocation partners relative to that in SKOV3 cells are shown in Online Supplementary Figure S1. The clinical features of EVI1+ and EVI1− patients are summarized in Table 1. EVI1+ patients were significantly older (P=0.03) and had a higher WBC count (P=0.01) at the time of diagnosis than EVI1− patients. Most of the MLL-rearranged AML cases were classified as FAB-M5 or FAB-M4. Specifically, most EVI1− patients (84%) presented with FAB-M5 morphology, which was less frequent in EVI1+ patients (22%), consistent with the findings of a previous study.8 EVI1+ was not correlated with sex or MLL translocation partners. The frequency of FLT3-ITD was significantly higher in EVI1+ patients (P=0.04). We also analyzed CEBPA and NPM1 mutations, which are established favorable prognostic factors; however, none of the patients harbored these mutations, except for one EVI1− patient harboring double CEBPA mutations. Table 1. Characteristics of patients categorized according to EVI1 expression status. Next, clinical outcomes were compared between EVI1+ patients and EVI1− patients (Figure 1). In the MLL-rearranged AML cohort (n=50), EVI1+ patients had a significantly worse EFS than EVI1− patients (P<0.0001) (Figure 1A). However, OS did not differ significantly between the two groups (P=0.054) (Figure 1B). Among several types of MLL-rearrangements, MLL-AF9 was the most common translocation (n=29, 58%) (Table 1). Therefore, clinical outcomes in the cohort of MLL-AF9 positive patients were compared between EVI1+ patients (n=11) and EVI1−patients (n=18). The results showed significant differences in EFS (P<0.0001) and OS (P=0.0008) (Figure 1C and D). By contrast, no differences in EFS (P=0.36) or OS (P=0.57) were observed among patients with MLL-rearranged AML after excluding MLL-AF9 positive patients (Figure 1E and F). The clinical outcomes associated with each type of MLL-rearrangement could not be analyzed because of the small sample size. Multivariate Cox regression analysis, including FLT3-ITD, WBC count, and age identified EVI1+ as the only prognostic factor predicting poor EFS in the total cohort of MLL-rearranged AML (hazard ratio (HR), 4.94; P<0.01) and in the MLL-AF9 positive cohort (HR, 33.81; P<0.01), but not OS (Online Supplementary Table S1). Figure 1. Kaplan-Meier survival curves of event-free survival (EFS) and overall survival (OS) from the time of diagnosis according to EVI1 expression status. (A) Kaplan-Meier estimates of EFS in the cohort of MLL-rearranged AML in EVI1+ and EVI1− patients. ... These results suggest that EVI1 overexpression is an independent adverse prognostic factor because of its association with reduced remission duration in pediatric patients with MLL-rearranged AML, especially in patients harboring MLL-AF9. A recent large study identified several novel prognostic MLL-rearranged subgroups, including a favorable-risk MLL-AF1q positive subgroup and a poor-risk MLL-AF6 positive subgroup.11 However, MLL-AF9 positive patients are categorized as an intermediate risk group, and this subgroup may be dichotomized as a favorable and poor-risk subgroup based on EVI1 expression levels. Pretreatment screening for EVI1 expression should be considered in patients with MLL-rearranged AML to enable better risk assessment and alternative consolidation therapies to be considered. Our results need to be confirmed in larger studies because of the limited case numbers. From a biological viewpoint, the ‘evil’-like adverse effects of EVI1 in patients with MLL-AF9-positive AML were partially elucidated in a recent study in which EVI1 positive cells harboring MLL-AF9 showed distinct morphological, molecular, and mechanistic differences from EVI1 negative cells.13 Moreover, EVI1 overexpression has been linked to CD52 overexpression, which could be a therapeutic target for monoclonal antibody treatment.14 Further investigation is required to identify novel prognostic factors in the various subgroups of MLL-rearranged AML and to develop therapeutic strategies effective for patients with EVI1 overexpression.

CSF3R and CALR mutations in paediatric myeloid disorders and the association of CSF3R mutations with translocations, including t(8; 21)

Mutations in the colony‐stimulating factor 3 receptor (CSF3R) and calreticulin (CALR) genes have been reported in a proportion of adults with myeloproliferative disease. However, little is known about CSF3R or CALR mutations in paediatric myeloid disorders. We analysed CSF3R exons 14 and 17, and CALR exon 9, using direct sequencing in samples of paediatric acute myeloid leukaemia (AML; n = 521), juvenile myelomonocytic leukaemia (JMML; n = 40), myelodysplastic syndrome (MDS; n = 20) and essential thrombocythaemia (ET; n = 21). CSF3R mutations were found in 10 (1·92%) of 521 patients with AML; two in exon 14 (both missense mutations resulting in p.T618I) and eight in exon 17 (three frameshift mutations: p.S715X, p.Q774R, and p.S783Q; and five novel missense mutations: p.Q754K, p.R769H, p.L777F, p.T781I, and S795R). All of the patients with mutations in CSF3R exon 17 had chromosomal translocations, including four with t(8;21). At the time of reporting, seven of these ten patients are alive; three have died, due to side effects of chemotherapy. No CSF3R mutations were found in cases of MDS, JMML or ET. The only mutation found in the CALR gene was a frameshift (p.L367 fs) in one ET patient. We discuss the potential impact of these findings for the leukaemogenesis and clinical features of paediatric myeloid disorders.

SETBP1 mutations in juvenile myelomonocytic leukaemia and myelodysplastic syndrome but not in paediatric acute myeloid leukaemia.

Juvenile myelomonocytic leukaemia (JMML) is a rare myeloproliferative disorder that is characterized by excessive myelomonocytic proliferation (Loh, 2011). Gene mutations in the components of the RAS signalling pathways are a hallmark of JMML and are considered to be central to the pathogenesis of JMML. Mutations in NRAS, KRAS, PTPN11, NF1, and CBL genes are found in approximately 75–85% of patients with JMML and are implicated in the aberrant RAS signalling (Loh, 2011). These mutations are also associated with congenital abnormalities, such as cardio–facio–cutaneous syndrome (KRAS), Noonan syndrome (PTPN11), neurofibromatosis (NF1), and Noonan-like syndrome (CBL). However, no other mutations have been identified in the remaining approximately 20% of patients with JMML. In this regard, massively parallel sequencing technology has recently identified recurrent somatic mutations in SETBP1 in atypical chronic myeloid leukaemia (aCML) (Piazza et al, 2012). Of the 70 patients with aCML that were examined, 17 (24%) were found to carry SETBP1 mutations. These mutations clustered between codons 858 and 871, all located in the SKI-homologous region of SETBP1. Identical nucleotide alterations have been reported in Schinzel–Giedion syndrome (Hoischen et al, 2010), a rare congenital disorder that is characterized by severe mental retardation, distinctive facial features, and higher than normal prevalence of tumours, notably neuroepithelial neoplasia (Schinzel & Giedion, 1978). This report prompted us to search for possible SETBP1 mutations in JMML or other paediatric haematological malignancies. To assess the clinical significance of SETBP1 mutations in paediatric leukaemias, we analysed a total of 414 patients with paediatric leukaemia/myelodysplastic syndrome (MDS) that comprised 42 patients with primary JMML, 24 with MDS, 22 with therapy-related leukaemia, 68 with infant acute lymphoblastic leukaemia (ALL), and 258 with de novo acute myeloid leukaemia (AML), including 10 patients with acute promyelocytic leukaemia (APL) and 22 with acute megakaryoblastic leukaemia (AMKL). The median age at diagnosis of JMML was 1 year and 10 months (range, 2 months to 8 years and 4 months), with 27 males and 15 females. MDS included 9 patients with refractory anaemia (RA), 14 with RA with an excess of blasts, and 1 with secondary MDS. The genomic region of the SETBP1 gene, containing codons 858–871 with the mutation hotspots D868 and G870 in the SKI-homologous region, was amplified using polymerase chain reaction (PCR) with the following primer sequences: forward, 5′-ACCAAAACCCAAAAGGGAAT3′; reverse, 5′-CGGTTTTGCAGGCTTTTC-3′. Purified PCR products were sequenced using an ABI PRISM 3130 Genetic Analyser (Applied Biosystems, Branchburg, NJ). Mutations in RAS, PTPN11, and CBL have been previously reported in JMML (Shiba et al, 2010). The present study adhered to the principles of the Helsinki Declaration and was conducted under the regulations outlined by the Ethics Board of Gunma Children’s Medical Centre. SETBP1 mutations were found in 2 of the 42 patients with JMML (4 8%; Gly870Arg in JMML 2, Ser869Arg in JMML 24) and one of the 24 patients with MDS (4 2%; Ile871Thr in MDS 3) but not in the 22 patients with secondary AML, 68 with infant ALL, or 258 with de novo paediatric AML, including 10 patients with APL and 22 with AMKL (Fig 1A). The origin of the mutations was not determined due to the lack of appropriate normal tissue samples. In all 3 patients with SETBP1 mutations, a chromatogram exclusively showed a mutated sequence, indicating that the mutations were heterozygous (Fig 1A). Although one of the 2 JMML patients with an SETBP1 mutation survived after unrelated cord blood transplantation, the other died following relapse 4 months after undergoing related peripheral blood stem cell transplantation (Table I). In contrast, the MDS patient who had an SETBP1 mutation was initially diagnosed with neuroblastoma at the age of 6 years. He was subsequently treated with chemotherapy and autologous bone marrow transplantation and achieved complete remission (CR). However, 3 years after the initial diagnosis, blast cells appeared in his peripheral blood and he was diagnosed with secondary MDS. Chromosomal analysis of the bone marrow cells revealed 45, XY, 15, der(7)t(7;15)(p13;q15), add(18)(q21) and add(20)(p13). He received chemotherapy with etoposide and cytarabine; however, he did not achieve CR. He died of haemorrhagic shock 18 months after being diagnosed with secondary MDS. Mutations in NRAS, KRAS, PTPN11 and CBL genes were found in 21%, 4 8%, 38% and 12% of patients with JMML respectively, in our study (Fig 1B) (Shiba et al, 2010). Although almost all of the NRAS, KRAS, PTPN11 and CBL mutations occurred in a mutually exclusive manner, SETBP1 mutations were found in patients with PTPN11 or NRAS mutations (Table I and Fig 1B). This finding suggests that both gene mutations associated with the RAS pathway and SETBP1 mutations can cooperate in the pathogenesis of JMML. Correspondence