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  • 1
    In: Blood, American Society of Hematology, Vol. 132, No. Supplement 1 ( 2018-11-29), p. 1562-1562
    Abstract: Introduction Epstein-Barr virus (EBV) is a double-stranded DNA virus that infects 〉 95% of the human population and is associated with a substantial risk of cancer development. Most infections in children and adolescents are asymptomatic or result in infectious mononucleosis; however, in some patients, EBV is associated with various hematological malignancies including Burkitt lymphoma, diffuse large B-cell lymphoma (DLBCL), and extranodal NK/T-cell lymphoma. EBV infection is also present in a portion of epithelial cell neoplasms such as gastric cancer and nasopharyngeal carcinoma. Despite the large population risk of cancer associated with EBV, it is poorly understood why only a small subset of EBV-infected individuals develop neoplasms, while others do not. Patients and Methods We designed a target enrichment system to capture several EBV strains including the Akata strain, which is responsible for the majority of EBV infections in Japan. We analyzed the genomes of EBV strains in 139 patients with various EBV-associated diseases and 17 EBV-positive cell lines. Next-generation sequencing reads were aligned to the Akata reference genome to analyze nucleotide variations, copy number alterations, and structural variations including sequence insertions in the human genome. The institutional review board of Nagoya University Graduate School of Medicine approved this study. Results We identified a median of 645 single nucleotide variants (SNVs) in the EBV genomes, 78% of which affected coding sequences. SNVs in coding sequences were significantly biased toward synonymous variants, suggesting negative selection pressure. The SNVs detected in noncoding sequences were enriched in two evolutionarily conserved viral noncoding RNAs (EBER1 and EBER2), particularly in the PAX5-binding domain of EBER2. However, most SNVs identified in the EBV genome do not seem to affect the development of neoplasms, as hierarchical clustering of EBV genomes from neoplastic and non-neoplastic diseases based on SNVs revealed no significant association between the EBV strain and disease type. In addition to SNVs, we identified frequent intragenic deletions in the EBV genomes of patients with EBV-positive DLBCL (10/14, 71%), extranodal NK/T-cell lymphoma (10/23, 43%), chronic active EBV infection (27/77, 35%), and other EBV-associated neoplasms (2/7). Such deletions were also identified in several EBV-associated cell lines (6/17), but not in non-neoplastic diseases such as infectious mononucleosis (0/4) and post-transplant lymphoproliferative disorders (0/14), suggesting a unique role of these mutations in the neoplastic proliferation of EBV-infected cells. Frequent deletions were detected in BamHI A rightward transcripts microRNA clusters (31/156), which suppress viral transcription factors (BZLF1 and BRLF1) required for the lytic reactivation of EBV. Deletions also were associated with several genes essential for virus production (20/156). These observed deletions are thought to upregulate lytic cycle-associated genes, some of which benefit neoplasms by inducing genomic instability and immune escape and mitigate cell damage caused by the production of viral particles. In fact, deletion of one essential gene, BALF5, resulted in upregulation of the lytic cycle and promotion of lymphomagenesis in a xenograft model. Discussion Although the essential roles of several latency-associated genes, such as LMP-1 and EBNA-2, in EBV-mediated immortalization and transformation of human lymphocytes have long been discussed, our finding raises the possibility that lytic cycle-associated genes also contribute to lymphomagenesis. This agrees with reports that lytic cycle-associated genes are expressed in Burkitt lymphoma, DLBCL, and chronic active EBV infection, and that BZLF1-deficient lymphoblastoid cells exhibit significantly impaired tumorigenicity in mice. In addition, essential gene deletions lead to the protection of EBV-infected cells from lysis. Further studies are warranted to exploit these findings for the design of novel therapeutics for EBV-associated neoplasms. Disclosures Kiyoi: Sumitomo Dainippon Pharma Co., Ltd.: Research Funding; Novartis Pharma K.K.: Research Funding; Phizer Japan Inc.: Research Funding; Sanofi K.K.: Research Funding; Kyowa Hakko Kirin Co., Ltd.: Research Funding; Celgene Corporation: Research Funding; Eisai Co., Ltd.: Research Funding; Astellas Pharma Inc.: Research Funding; Takeda Pharmaceutical Co., Ltd.: Research Funding; Otsuka Pharmaceutical Co., Ltd.: Research Funding; Chugai Pharmaceutical Co., Ltd.: Research Funding; Nippon Shinyaku Co., Ltd.: Research Funding; FUJIFILM Corporation: Research Funding; Zenyaku Kogyo Co., Ltd.: Research Funding; Bristol-Myers Squibb: Honoraria. Nakamura:Roche/Chugai,: Research Funding; Kyowa-Kirin: Research Funding.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2018
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  • 2
    In: Nature Microbiology, Springer Science and Business Media LLC, Vol. 4, No. 3 ( 2019-01-21), p. 404-413
    Type of Medium: Online Resource
    ISSN: 2058-5276
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
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  • 3
    In: Nature Microbiology, Springer Science and Business Media LLC, Vol. 4, No. 3 ( 2019-01-30), p. 544-544
    Type of Medium: Online Resource
    ISSN: 2058-5276
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
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  • 4
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 34, No. 28 ( 2016-10-01), p. 3451-3459
    Abstract: Acute lymphoblastic leukemia (ALL) makes up a significant proportion of all pediatric cancers, and relapsed ALL is a leading cause of cancer-associated deaths in children. Identification of risk factors and druggable molecular targets in ALL can lead to a better stratification of treatments and subsequent improvement in prognosis. Patients and Methods We enrolled 59 children with relapsed or primary refractory ALL who were treated in our institutions. We primarily performed RNA sequencing (RNA-seq) using patients’ leukemic cells to comprehensively detect gene fusions and analyze gene expression profiles. On the basis of results obtained by RNA-seq, we performed genetic validation, functional analysis, and in vitro drug sensitivity testing using patients’ samples and an exogenous expression model. Results We identified a total of 26 gene fusions in 22 patients by RNA-seq. Among these, 19 were nonrandom gene fusions already described in ALL, and four of the remaining seven involved identical combination of MEF2D and BCL9. All MEF2D-BCL9–positive patients had B-cell precursor immunophenotype and were characterized as being older in age, being resistant to chemotherapy, having very early relapse, and having leukemic blasts that mimic morphologically mature B-cell leukemia with markedly high expression of HDAC9. Exogenous expression of MEF2D-BCL9 in a B-cell precursor ALL cell line promoted cell growth, increased HDAC9 expression, and induced resistance to dexamethasone. Using a primary culture of leukemic blasts from a patient, we identified several molecular targeted drugs that conferred inhibitory effects in vitro. Conclusion A novel MEF2D-BCL9 fusion we identified characterizes a novel subset of pediatric ALL, predicts poor prognosis, and may be a candidate for novel molecular targeting.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
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    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2016
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  • 5
    In: Blood, American Society of Hematology, Vol. 134, No. Supplement_1 ( 2019-11-13), p. 2973-2973
    Abstract: Background Juvenile myelomonocytic leukemia (JMML) is a rare myelodysplastic/ myeloproliferative neoplasm that occurs during infancy and early childhood. The clinical course of the disease varies widely. The majority of children require allogenic hematopoietic stem cell transplantation (HSCT) for long term survival, but the disease will eventually resolve spontaneously in ~15% of patients. Previous studies have identified clinical and molecular risk factors in JMML. More recently, three groups independently discovered that genome-wide methylation profiling using 450K Illumina array revealed that the high methylation (HM) subgroup was significantly associated with poor survival compared to the low methylation (LM) subgroup (Murakami 2018 Blood, Stieglitz 2017 Nat. Commun., Lipka 2017 Nat. Commun.). 450K could be a standard assay for stratification of JMML. However, it is now unavailable because the manufacture replaced it with EPIC array. Here, we developed a next-generation sequencing-based clinical test recapitulate 450K clustering results using the digital restriction enzyme analysis of methylation (DREAM) method (Jelinek 2012 Epigenetics). Patients and Methods We studied 99 children (67 boys and 32 girls) with JMML. All the patients were included in our previous publications. First, we assessed JMML samples with DREAM. Briefly, genomic DNA was sequentially cut with two enzymes SmaI and XmaI recognizing the same sequence, CCCGGG sites in DNA. Enzyme-treated DNA was then used to generate sequencing libraries according to the Illumina protocols, and run on an Illumina Hiseq 2500. We assessed 10 JMML samples with reduced representation bisulfite sequencing (RRBS) (Meissner 2005 Nucleic Acids Res.). In brief, purified genomic DNA was digested by the methylation-insensitive restriction enzyme MspI to generate short fragments that contain CpG dinucleotides at the ends. The CpG-rich DNA fragments (40-220 bp) were size selected, subjected to bisulfite conversion, PCR amplified and end sequenced on an Illumina Genome analyzer. Results We analyzed 99 samples using the DREAM with 8.87 (4.09-16.35) million reads (median, [range]), and determined methylation level in 62,525 (52,356-75,185) CpG sites (median [range] ). We observed a strong correlation between DREAM methylation ratio and 450K beta-value of overlapping CpG sites (Pearson r2 = 0.95 [0.913-0.962], median [range] ). We performed unsupervised consensus clustering with DREAM methylation data of 7,704 CpG sites within ±1 kb from TSS on autosomal chromosomes detected in ≥95% of the samples with imputation of the missing data using the median of each CpG site methylation level. Clustering identified two distinct subgroups, the HM subgroup (n = 35) and the LM subgroup (n = 64), matching 95% (94 of 99) with the 450K clustering results. The HM subgroup patients showed significantly poorer 5-year OS than the LM subgroup patients (41.9% [95% confidence interval {CI}], 25.3%-57.6%) vs. 71.4% [95% CI, 56.2%-82.1%] ; P = 0.00345). Discrepancies in the clustering results between DREAM and 450K were observed in only 5 patients (2 survived and 3 died); all 5 patients were reclassified as those with LM with DREAM from being HM with 450K. We also performed RRBS methylation analysis on 10 patients. Unsupervised consensus clustering using promoter-associated 4,971 CpG sites measured with RRBS identified HM (n = 5) and LM (n = 5) subgroups and completely matched with the classification made using DREAM and 450K. Then, we developed a prediction model of the methylation subgroups using a machine-learning program. We selected 85 CpG sites from 7,704 CpG sites used for unsupervised clustering of the DREAM assay that showed a distinct difference in the average methylation level ( 〉 0.3) between the HM and LM subgroups of the learning cohort (n = 70) and developed a support vector machine (SVM) model. As a validation cohort, we analyzed the remaining 29 JMML samples with a SVM model and confirmed a high matching rate with 450K clustering results (100%, 29 of 29). Conclusions We could develop a methylation test for JMML using the DREAM assay. Both the unsupervised clustering analysis and SVM model could repeat the result of 450K-based methylation classification, i.e., the HM and LM subgroups. The relatively lower cost of the DREAM assay (US$200/sample) enabled us to incorporate methylation classification in JMML in most settings. Disclosures No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2019
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  • 6
    In: Journal of Allergy and Clinical Immunology, Elsevier BV, Vol. 148, No. 2 ( 2021-08), p. 639-644
    Type of Medium: Online Resource
    ISSN: 0091-6749
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    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
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  • 7
    In: Journal of Allergy and Clinical Immunology, Elsevier BV, Vol. 138, No. 5 ( 2016-11), p. 1471-1473.e4
    Type of Medium: Online Resource
    ISSN: 0091-6749
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    Language: English
    Publisher: Elsevier BV
    Publication Date: 2016
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  • 8
    In: Blood, American Society of Hematology, Vol. 128, No. 22 ( 2016-12-02), p. 3432-3432
    Abstract: Introduction Paraneoplastic pemphigus (PNP), an autoimmune disorder that can arise from malignancies, is fatal when complicated with bronchiolitis obliterans (BO), similar to that in patients receiving hematopoietic stem cell transplantation (HSCT). Autoantibodies to the desmosome proteins envoplakin and periplakin of epithelial cell adhesion molecules are essential for diagnosing PNP. BO after HSCT is an unfavorable complication that develops in association with chronic graft-versus-host disease (cGVHD). The effectiveness of rituximab on BO has been reported, which suggests that BO after HSCT is associated with autoimmunity similar to PNP. Here we analyzed anti-envoplakin and anti-periplakin antibodies that are associated with PNP in patients with and without BO complications who developed cGVHD after HSCT. Patients and Methods We analyzed anti-envoplakin and anti-periplakin antibodies in 21 patients (11 males and 10 females) with (n = 10) or without (n = 11) BO complications who developed cGVHD following HSCT between 1988 and 2015 at our institution. The median age at the time of HSCT in patients with and without BO was 10.8 (range, 1-21) and 7.5 (range, 1-14) years, respectively. The median duration from HSCT to BO onset was 261.6 (range, 41-825) days. We analyzed anti-envoplakin and anti-periplakin antibodies in cryopreserved sera collected before and after BO or cGVHD onset using immunoprecipitation (IPP) and enzyme-linked immunosorbent assay (ELISA) for detecting both autoantibodies. Longitudinal sera were obtained from a patient with cGVHD. Fifty-eight serum samples were collected from 21 patients. Biotinylated recombinant periplakin and envoplakin were produced from cDNAs using the transcription and translation (TnT) T7 Quick Coupled Transcription/Translation System (Promega) with rabbit reticulocyte lysates. IPP and ELISA were performed using in vitro TnT products as previously reported (Muro Y, et al. Rheumatology 2012;51:1508-13). Results On SDS-polyacrylamide gel electrophoresis, biotinylated recombinant periplakin and envoplakin showed protein bands with predicted size of 190 kDa and 210 kDa, respectively. The serum samples from the PNP patient and normal control serum were examined in an ELISA titration study. These titration curves showed the possibility of quantitatively measuring these autoantibodies. Both anti-envoplakin and anti-periplakin antibodies were positive in two of 10 patients with BO at BO onset but negative in all 11 patients without BO during cGVHD. In one of the two patients with plakin family autoantibodies, titers of anti-periplakin and anti-envoplakin antibodies gradually decreased after administering rituximab five times and repeating plasmapheresis seven times and subsequently decreased to below cut-off level. Although oxygenation substantially decreased consistent with the clearance of autoantibodies, the patient died of invasive pulmonary aspergillosis during steroid tapering. In the other patient, plakin family autoantibodies in the sera became negative after administering rituximab nine times. The patient is alive, and the spirometry findings were normal 6 years after the clearance of both autoantibodies. Conclusions Our findings indicate that plakin family autoantibodies may participate in BO onset in some patients receiving HSCT. The detection of these autoantibodies in patients with BO may be a good biomarker of cGVHD, providing a rationale and target for repeated rituximab therapy. Disclosures Kojima: SANOFI: Honoraria, Research Funding.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2016
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  • 9
    In: Blood, American Society of Hematology, Vol. 128, No. 22 ( 2016-12-02), p. 1499-1499
    Abstract: Introduction: Paroxysmal nocturnal hemoglobinuria (PNH) is a nonmalignant clonal disease of hematopoietic stem cells resulting from a somatic mutation in the PIGA gene. PNH frequently manifests in association with aplastic anemia (AA), in which PIGA mutations are believed to enable escape from the immune-mediated destruction by pathogenic T cells. Recent studies using next-generation sequencing have revealed that frequent somatic PIGA mutationsin AA patients are associated with a better response to IST and prognosis (Yoshizato et al N Engl J Med. 2015; 373: 35-47). However, clinical PNH is a progressive and life-threatening disease driven by chronic hemolysis that leads to thrombosis, renal impairment, poor quality of life, and death. Large studies in adults have reported that clinical PNH developed in 10%-25% of AA patients; however; the frequency of clinical PNH in children with AA has rarely been described. Here we aimed to elucidate the pathological link between PNH and AA in children. Methods: In total, 57 children (35 boys and 22 girls) diagnosed with acquired AA at our hospital between 1992 and 2010 were retrospectively studied. Patients who underwent hematopoietic stem cell transplantation as first-line treatment within 1 year after AA diagnosis and those with clinical PNH at AA diagnosis were excluded. Flow cytometry (FCM) was used to detect PNH CD13+/CD55−/CD59− granulocytes and PNH glycophorin A+/CD55−/CD59− red blood cells (RBCs). Clinical PNH was defined as the presence of intravascular hemolysis and ≥5% PNH granulocytes or PNH RBCs. Minor PNH clones were defined as those with 〉 0.005% PNH granulocytes or 〉 0.010% PNH RBCs. We performed targeted sequencing of bone marrow samples from patients with clinical PNH that were obtained at 2 time points: at AA diagnosis and after PNH development. The panel of 184 genes for targeted sequencing included most of the genes known to be mutated in inherited bone marrow failure syndromes and myeloid cancers, as well as PIGA. Results: The median patient age at AA diagnosis was 9.3 (1.2-17.8) years, and the median follow-up period was 123 (2-228) months. A total of 43 patients were screened for PNH clones by FCM after AA diagnosis, and 21 of these with minor PNH clones were identified. The median percentages of PNH granulocytes and PNH RBCs were 0.001% (0.000%-4.785%) and 0.000% (0.000%-3.829%), respectively. During follow-up, 5 patients developed clinical PNH after adolescence (15-22 years of age). The median time between AA diagnosis and PNH development was 4.9 (3.3-7.9) years. All clinical PNH patients were treated with IST for AA, and complete and partial response after 6 months were achieved in 1 and 4 patients, respectively. Gross hemoglobinuria was present in all clinical PNH patients, but thrombosis was not observed. The size of PNH clones varied greatly among patients: PNH granulocytes and PNH RBCs were 42.96% (10.04%-59.50%) and 48.87% (15.02%-90.80%), respectively. Oral cyclosporine A and intravenous eculizumab were administered to 3 and 1 patients, respectively; all patients showed sustained response as indicated by improvement in gross hemoglobinuria and normal blood counts after treatment. The remaining 1 patient underwent bone marrow transplantation from the HLA-identical mother and was alive without any complications. Overall, the 10-year probability of developing clinical PNH was 10.2% (95%CI, 3.6-20.7). Among 43 patients screened for PNH clones at AA diagnosis, the 10-year cumulative clinical PNH incidence was significantly higher in patients with minor PNH clones than in those without minor PNH clones at AA diagnosis [29% (95% CI, 10%-51%) vs. 0% (95% CI, 0%-0%); p = 0.015]. Among all clinical PNH patients, a total of 8 somatic PIGA mutations were detected (missense, 2; splice site, 2; and frameshift, 4). However, PIGA mutations were not detected at AA diagnosis even in patients who subsequently developed clinical PNH. Conclusion: In our cohort, the percentage of patients who eventually developed clinical PNH was comparable to that reported in adults in a previous study. Furthermore, the current study showed that the presence of minor PNH clones at AA diagnosis was a risk factor for the subsequent development of clinical PNH, although the clones were not detected by targeted sequencing. Thus, pediatric AA patients with PNH clones at AA diagnosis should undergo long-term periodic monitoring for potential clinical PNH development. Disclosures Kojima: SANOFI: Honoraria, Research Funding.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2016
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 10
    In: Blood, American Society of Hematology, Vol. 134, No. Supplement_1 ( 2019-11-13), p. 4213-4213
    Abstract: Background Juvenile myelomonocytic leukemia (JMML) is a rare pediatric myelodysplastic/myeloproliferative disease. Approximately 85% of patients with JMML harbor germline and/or somatic mutations in RAS pathway genes, such as PTPN11, NF1, CBL, NRAS, and KRAS. In a subset of patients with JMML, SETBP1 and JAK3 mutations were identified as secondary mutations in addition to primary RAS mutations. These secondary mutations are associated with the disease progression and poor clinical outcome. Recently, it has been reported that subclonal SETBP1 mutation also correlates with a dismal prognosis. Therefore, we hypothesized that subclonal JAK3 mutation is present in a higher than expected number of patients with JMML and associated with poor prognosis. The aim of this study is to identify patients with subclonal SETBP1 and/or JAK3 mutations at the diagnosis using droplet digital PCR (ddPCR) and to elucidate their clinical outcomes. Patients and Methods We enrolled 128 patients with JMML and 15 with Noonan syndrome-associated myeloproliferative disorder (NS/MPD). Using bone marrow (BM) or peripheral blood derived genomic DNA, ddPCR was performed in the 143 patients to detect SETBP1 p.D868N and JAK3 p.R657Q hotspot mutations with low variant allele frequencies (VAF). The study was approved by the institutional review board of Nagoya University Graduate School of Medicine. Results To assess the false-positive rate of the ddPCR assay for each mutation, the assay was also performed in 30 healthy volunteers. Among these, the false-positive rate (mean ± standard deviation) for SETBP1 and JAK3 mutations was 0.010% ± 0.010% and 0.013% ± 0.012%, respectively. Due to the presence of false-positive droplets, the sensitivity and the quantitative linearity was evaluated for 〉 0.01% VAF. The significant correlation between the expected and the observed VAF in SETBP1 and JAK3 was observed (R-squared, 0.9923 and 0.9922, respectively). Therefore, 0.05% VAF was defined as the cut-off value in this assay. Among the 143 patients, ddPCR detected SETBP1 and JAK3 mutations in nine (6.3%) and fifteen (10.5%), respectively. SETBP1 and JAK3 mutations, including variants with low allele frequencies, were not detected in NS/MPD. Among patients with SETBP1 and/or JAK3 mutations, two and six patients harbored less than 1.0% VAF. Patients with less than 1.0% VAF in SETBP1 or JAK3 mutation exhibited a significantly poorer 2-year transplantation-free survival than those without SETBP1 and JAK3 mutations (P = 3.05 × 10-3). JMML is genetically characterized by an extremely small number of somatic mutations (an average of 0.8 mutations/exome/patient). However, we demonstrated that among 19 patients with SETBP1 and/or JAK3 mutations, five patients (26.3%) harbored both the mutations. This finding suggested a statistically significant co-occurrence of SETBP1 and JAK3 mutations in JMML. In order to determine whether SETBP1 and JAK3 mutations were present in the same clone or not, we performed colony formation assays using BM cells in one of the five patients with both SETBP1 and JAK3 mutations. This case harbored 0.9% VAF in JAK3 and 41.9% in SETBP1 in addition to 46.0% in PTPN11 mutation (c.227A 〉 C, p.E76A), respectively. In total, 93 colonies were collected and individually analyzed by Sanger sequencing, of which two colonies (2.1%) were identified with both SETBP1 and JAK3 mutations. Conclusions ddPCR is a useful tool to assess subclonal SETBP1 and JAK3 hotspot mutations and to estimate the prognosis. It would be better to start preparing for hematopoietic stem cell transplantation when patients with JMML harbored subclonal SETBP1 and/or JAK3 mutations at the diagnosis. While JMML is characterized by a paucity of somatic mutations, clones harboring SETBP1 and JAK3 mutations were identified. This finding suggests that SETBP1 and JAK3 mutation are susceptible to each other. Furthermore, the serial acquisition of SETBP1 and JAK3 mutations might correlate with the disease progression. Disclosures No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2019
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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