Next-Generation Sequencing Mutational Landscape and Clinical Features of Chinese Adults with Myeloproliferative Neoplasms

Abstract Myeloproliferative neoplasms (MPNs) include three classical subtypes: polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). Since prefibrotic primary myelofibrosis (pre-PMF) was recognized as a separate entity in the 2016 revised classification of MPN, it has been a subject of debate among experts due to its indefinite diagnosis. However, pre-PMF usually has a distinct outcome compared with either ET or overt PMF. We conducted a retrospective study of MPN patients from October 2014 to June 2020 in the Fourth Affiliated Hospital of Zhejiang University. Patients who were diagnosed with ET, pre-PMF or overt-MF according to the 2016 WHO Classification were included. We reviewed the clinical parameters, haematologic information, and genetic mutations of patients using next-generation sequencing (NGS). Mutation screening was performed in 44 patients by next-generation sequencing techniques, 84 genes and 258 mutations were detected. JAK2 was the most frequently mutated gene (25/44, 56.82%), followed by TET2 (14/44, 31.82%), KMT2C (13/44, 29.55%), and ASXL1 (10/44, 23.73%) in MPN (Figure 1-A). The VAFs of all studied genes with mutation frequencies >10% are shown in Figure 1-B. Of the 20 patients with ET, 9 (45%) were positive for the JAK2 mutation, 5 (25%) carried FAT1, 5 (25%) carried KMT2C, and 4 (20%) carried CALR. Of the 5 patients with pre-PMF, 4 (80%) carried JAK2, 3 (60%) carried EP300, and 2 (40%) carried TET2. Of the 19 patients with overt PMF, 12 (63%) carried JAK2, 10 (53%) carried TET2, 7 (37%) carried ASXL1, and 6 (32%) carried KMT2C, as reported in Figure 2. The median follow-up was 36 months for ET, 42 months for pre-PMF, and 53 months for overt PMF. Overall survival between pre-PMF, overt PMF, and ET was significantly different (P<0.001), as shown in Figure 3. During the follow-up time, only one death of ET was registered, so we analysed the impact of clinical parameters and mutational status at diagnosis on outcome in PMF, including pre-PMF and overt PMF. We performed Kaplan-Meier curves to examine the relationships between the clinical parameters and patient survival. We found that male sex (P=0.0107), MPN10 symptoms (P=0.0354), anaemia (haemoglobin<120g/L, P=0.0239), and thrombocytopenia (platelet count <100 ×10 9/L, P=0.0002) were significantly related to inferior OS (Figure 4). Pre-PMF patients exhibited higher leukocyte counts, higher LDH values, a higher frequency of splenomegaly, and a higher incidence of hypertension than ET patients. On the other hand, pre-PMF patients had higher platelet counts and haemoglobin levels than overt PMF patients. Molecular analysis revealed that the frequency of EP300 mutations was significantly increased in pre-PMF patients compared with ET and overt PMF patients. In terms of outcome, male sex, along with symptoms including MPN10, anaemia, thrombocytopenia, and KMT2A and CUX1 mutations, indicated a poor prognosis for PMF patients. In conclusion, we identified differences in the clinical, haematologic, and molecular presentations of ET, pre-PMF, and overt PMF patients, indicating that comprehensive evaluation of not only BM features but also clinical, haematologic, and molecular profiles is needed for accurate diagnosis and treatment of these three disease entities. The molecular analysis revealed that pre-PMF might be relevant to EP300 mutation, demonstrating the value of molecular examination. The results of this study indicated that comprehensive evaluation of BM features, clinical phenotypes, haematologic parameters, and molecular profiles is needed for the accurate diagnosis and treatment of ET, pre-PMF, and overt PMF patients. Acknowledgment:The research was supported by the Public Technology Application Research Program of Zhejiang, China (LGF21H080003), the Key Project of Jinhua Science and Technology Plan, China (2020XG-29 and 2020-3-011), the Academician Workstation of the Fourth Affiliated Hospital of the Zhejiang University School of Medicine (2019-2024), the Key Medical Discipline of Yiwu, China (Hematology, 2018-2020) and the Key Medical Discipline of Jinhua, China (Hematology, 2019-2021). Correspondence to: Dr Jian Huang, Department of Hematology, The Fourth Affiliated Hospital of Zhejiang University School of Medicine. N1 Shangcheng Road. Yiwu, Zhejiang, Peoples R China. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

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Next-Generation Sequencing Mutational Landscape and Clinical Features of Chinese Adults with Myeloproliferative Neoplasms

10.21203/rs.3.rs-483741/v1 ◽

2021 ◽

Author(s):

Shuna Luo ◽

Zanzan Wang ◽

Xiaofei Xu ◽

Lan Zhang ◽

Shengjie Wang ◽

...

Keyword(s):

Next Generation Sequencing ◽

Comprehensive Evaluation ◽

Myeloproliferative Neoplasms ◽

Primary Myelofibrosis ◽

Next Generation ◽

Chinese Adults ◽

Leukocyte Counts ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing

Abstract Background: Myeloproliferative neoplasms (MPNs) include three classical subtypes: polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). Since prefibrotic primary myelofibrosis (pre-PMF) was recognized as a separate entity in the 2016 revised classification of MPN, it has been a subject of debate among experts due to its indefinite diagnosis. However, pre-PMF usually has a distinct outcome compared with either ET or overt PMF. In this study, we examined the clinical, haematologic, genetic, and prognostic differences among pre-PMF, ET, and overt PMF.Methods: We retrospectively reviewed the clinical parameters, haematologic information, and genetic mutations of patients who were diagnosed with pre-PMF, ET, and overt PMF according to the WHO 2016 criteria using next-generation sequencing (NGS).Results: Pre-PMF patients exhibited higher leukocyte counts, higher LDH values, a higher frequency of splenomegaly, and a higher incidence of hypertension than ET patients. On the other hand, pre-PMF patients had higher platelet counts and haemoglobin levels than overt PMF patients. Molecular analysis revealed that the frequency of EP300 mutations was significantly increased in pre-PMF patients compared with ET and overt PMF patients. In terms of outcome, male sex, along with symptoms including MPN-10, anaemia, thrombocytopenia, and KMT2A and CUX1 mutations, indicated a poor prognosis for PMF patients.Conclusion: The results of this study indicated that comprehensive evaluation of BM features, clinical phenotypes, haematologic parameters, and molecular profiles is needed for the accurate diagnosis and treatment of ET, pre-PMF, and overt PMF patients.

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Next-Generation Sequencing (NGS) in Childhood Myeloproliferative Diseases (MPD)

Blood ◽

10.1182/blood-2018-99-118102 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 3049-3049

Author(s):

Michelina Santopietro ◽

Giovanna Palumbo ◽

Maria Luisa Moleti ◽

Anna Maria Testi ◽

Luisa Cardarelli ◽

...

Keyword(s):

Next Generation Sequencing ◽

Children And Adolescents ◽

Myeloproliferative Neoplasms ◽

Primary Myelofibrosis ◽

Advisory Board ◽

Gene Panel ◽

Driver Mutations ◽

Next Generation ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing

Abstract Driver mutations of JAK2, CALR and MPL are found in >90% of adults with BCR-ABL1-negative myeloproliferative neoplasms (MPN). In children, the presence of clonal markers ranges between 22 and 40%, and inherited forms of MPD, such as familial erythrocytosis (FE) and hereditary thrombocytosis (HT), are common. Data on the mutational spectrum and biology of childhood MPD are limited. The aims of this study were: a) to evaluate the ability of a next-generation sequencing (NGS)-based 44-gene analysis to better characterize wild type (WT) MPD, and b) to identify non-canonical and/or non-driver mutations in children and adolescents with MPD. Eighty patients (pts) aged ≤20 years (yrs) at diagnosis of MPD, observed between June 1980 and September 2015, were first investigated with standardized methods for driver mutations of MPN (JAK, MPL, CALR), for genes involved in FE (HRE, EpoR, HIF2α, HIF1α, VHL, PHD1-3, STAT5, LNK, TET2) and HT (THPO, MPL, LNK and TET2). Then, a 44-gene panel providing diagnostic information in myeloid malignancies and in rare inherited erythrocytosis/thrombocytosis (JAK2, CALR, MPL, ASXL1, CBL, C-Kit, CSF3R, CUX1, DNMT3A, ETNK1, EZH2, IDH1, IDH2, IKZF1, KRAS, LNK, NFE2, NRAS, PTPN11, RUNX1, SETBP1, SF3B1, SRSF2, TET2, TP53, U2AF1, ZRSR2, BPGM, EGLN1 (PHD2), EPAS1 (HIF2A), EPOR, GATA1, GELSOLIN, HBA1, HBA2, HBB, JAK2,MPL, RUNX1, SH2B3, SRC, THPO, VHL, WAS) was employed to better characterize these diseases. Sequencing analyses of DNA from mononuclear peripheral blood cells were performed in 57/80 pts. Eighty pts (M 41, F 39; median age at diagnosis: 149/12 yrs, range 3 months-1911/12 yrs), investigated by standardized methods, were retrospectively classified according to the WHO 2016 criteria as follows: 35 essential thrombocythemia (ET) (10 JAK2V617F, 2 CALR type1, 6 CALR type2, 1 CALR atypical, 16 WT), 9 polycythemia vera (PV) (4 JAK2V617F, 5 WT) and 3 primary myelofibrosis (PMF) (1 JAK2V617F, 2 WT). Twenty-three pts with MPLS505N or MPLV501A mutations and 10 pts with HIF mutations (3 pts) and/or anamnestic criteria of FE (7 WT) were considered HT and FE, respectively. The NGS-based 44-gene panel was applied to 57 MPD pts (11 JAK2V617F, 6 CALR, 12 MPLS505N, 2 MPLV501A, 3 HIF2α and 23 WT). According to the WHO 2016 criteria, 27 pts were ET, 14 HT, 8 FE, 7 PV and 1 PMF. By using the NGS panel, clonal markers were found in 12/23 (52%) pts with MPN WT: HBB and PDH2 in 2 FE, MPLW515_P518>KT in 1 ET pt and non-driver mutations in 9 pts (7 ET, 1 PF and 1 PV). Furthermore, two non-canonical driver mutations, MPLC322G and JAK2G301R were identified in 1 CALR type2 ET and in 1 JAK2V617FPV, respectively. An additional MPLV501M mutation was found in 1 MPLS505N HT. Taken together, among the 57 pts 18 (32%) had one (11/18=68%) or two (7/18=39%) non-driver mutations. Eight of the 34 pts (23.5%) with a clonal marker had additional non-driver mutations, that was single in 6 pts. Within the familial MPD, a single non-driver mutation was found in 3/8 FE pts (37.5%), while no mutations were detected in HT pts. Considering the functional classification of non-driver mutations, we found mutations in signaling (CBL, LNK/SH2B3, CSF3R, KIT, SETBP1) and splicing (U2AF1, ZRSR2) genes in ET and PMF pts, and mutations of epigenetic regulation genes (TET2, ASXL1, DNMT3A) in PV, FE and ET pts (Table 1). The co-occurrence of driver and non-driver mutations in the same individual is illustrated in the circos plot (Figure 1). The use of a NGS-based 44-gene panel in acquired and familial pediatric MPD enabled to identify driver and non-driver mutations, not otherwise detected by conventional methods, with a substantial proportion of MPD pts (81%) showing mutations in the genes analyzed. Interestingly, we found additional neoplastic mutations in some pts with FE. Although the utilized NGS-based panel proved useful to better characterize children and adolescents with MPD, 19% of our pts still remain without any identified clonal marker. Further targeted NGS and whole genome sequencing may enable to better define MPD children without molecular markers. Disclosures Malaspina: Sapienza University, Rome: Other: Resident in Hematology. Foà:ABBVIE: Other: ADVISORY BOARD, Speakers Bureau; CELGENE: Other: ADVISORY BOARD, Speakers Bureau; AMGEN: Other: ADVISORY BOARD; INCYTE: Other: ADVISORY BOARD; NOVARTIS: Speakers Bureau; ROCHE: Other: ADVISORY BOARD, Speakers Bureau; GILEAD: Speakers Bureau; JANSSEN: Other: ADVISORY BOARD, Speakers Bureau; CELTRION: Other: ADVISORY BOARD.

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The genetic analysis of Chinese patients with clonal cytopenias using targeted next-generation sequencing

Molecular Cytogenetics ◽

10.1186/s13039-021-00572-z ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Lijuan Zhang ◽

YuYe Shi ◽

Yue Chen ◽

Shandong Tao ◽

Wenting Shi ◽

...

Keyword(s):

Next Generation Sequencing ◽

Myelodysplastic Syndromes ◽

Rna Splicing ◽

Myeloproliferative Neoplasms ◽

Chinese Patients ◽

Newly Diagnosed ◽

Next Generation ◽

Targeted Next Generation Sequencing ◽

Significant Difference ◽

Generation Sequencing

Abstract Background Clonal hematopoiesis (CH) can be found in various myeloid neoplasms (MN), such as myelodysplastic syndromes (MDS), myelodysplastic syndromes/myeloproliferative neoplasms (MDS/MPN), also in pre-MDS conditions. Methods Cytogenetics is an independent prognostic factor in MDS, and fluorescence in-situ hybridization (FISH) can be used as an adjunct to karyotype analysis. In the past 5 years, only 35 of 100 newly diagnosed MDS and MDS/MPN patients were identified abnormalities, who underwent the FISH panel. In addition, we examined a cohort of 51 cytopenic patients suspected MDS or MDS/MPN with a 20-gene next generation sequencing (NGS), including 35 newly diagnosed MN patients and 16 clonal cytopenias of undetermined significance (CCUS) patients. Results Compared with the CCUS group, the MN group had higher male ratio (22/13 vs 10/6), cytogenetics abnormalities rate (41.4% vs 21.4%) and frequency of a series of mutations, such as ASXL1 (28.6% vs 25%), U2AF1 (25.7% vs 25%), RUNX1 (20% vs 0.0%); also, higher adverse mutations proportion (75% vs 85.2%), and double or multiple mutations (54.3% vs 43.75%). There were 7 MN patients and 4 CCUS patients who experienced cardio-cerebrovascular embolism events demonstrated a significant difference between the two groups (25% vs 20%). Ten of the 11 patients had somatic mutations, half had DNA methylation, while the other half had RNA splicing. Additionally, six patients had disease transformation, and four patients had mutated U2AF1, including two CCUS cases and two MDS-EB cases. Following up to January 2021, there was no significant difference in over survival between the CCUS and MN groups. Conclusion NGS facilitates the diagnosis of unexplained cytopenias. The monitoring and management of CCUS is necessary, also cardio-cerebrovascular embolism events in patients with CH need attention in the clinical practice.

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The Impact of Clonal Hematopoiesis of Indeterminate Potential on Survival in Patients with Newly Diagnosed Acute Myeloid Leukemia

Blood ◽

10.1182/blood-2018-99-116240 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 4359-4359

Author(s):

Koji Sasaki ◽

Rashmi Kanagal-Shamanna ◽

Guillermo Montalban-Bravo ◽

Rita Assi ◽

Kiran Naqvi ◽

...

Keyword(s):

Next Generation Sequencing ◽

Myeloid Leukemia ◽

Research Funding ◽

Newly Diagnosed ◽

Next Generation ◽

Risk Of Death ◽

Genetics Research ◽

The Impact ◽

Generation Sequencing

Abstract Introduction: Clearance of detected somatic mutations at complete response by next-generation sequencing is a prognostic marker for survival in patients with acute myeloid leukemia (AML). However, the impact of allelic burden and persistence of clonal hematopoiesis of indeterminate potential (CHIP)-associated mutations on survival remains unclear. The aim of this study is to evaluate the prognostic impact of allelic burden of CHIP mutations at diagnosis, and their persistence within 6 months of therapy. Methods: From February 1, 2012 to May 26, 2016, we reviewed 562 patients with newly diagnosed AML. Next-generation sequencing was performed on the bone marrow samples to detect the presence of CHIP-associated mutations defined as DNMT3A, TET2, ASXL1, JAK2 and TP53. Overall survival (OS) was defined as time period from the diagnosis of AML to the date of last follow-up or death. Univariate (UVA) and multivariate Cox proportional hazard regression (MVA) were performed to identify prognostic factors for OS with p value cutoff of 0.020 for the selection of variables for MVA. Landmark analysis at 6 months was performed for the evaluation of the impact of clearance of CHIP, FLT3-ITD, FLT3D835, and NPM1 mutations. Results: We identified 378 patients (74%) with AML with CHIP mutations; 134 patients (26%) with AML without CHIP mutations. The overall median follow-up of 23 months (range, 0.1-49.0). The median age at diagnosis was 70 years (range, 17-92) and 66 years (range, 20-87) in CHIP AML and non-CHIP AML, respectively (p =0.001). Of 371 patients and 127 patients evaluable for cytogenetic in CHIP AML and non-CHIP AML, 124 (33%) and 25 patients (20%) had complex karyotype, respectively (p= 0.004). Of 378 patients with CHIP AML, 183 patients (48%) had TET2 mutations; 113 (30%), TP53; 110 (29%), ASXL1; 109 (29%), DNMT3A; JAK2, 46 (12%). Of 378 patients, single CHIP mutations was observed in 225 patients (60%); double, 33 (9%); triple, 28 (7%); quadruple, 1 (0%). Concurrent FLT3-ITD mutations was detected in 47 patients (13%) and 12 patients (9%) in CHIP AML and non-CHIP AML, respectively (p= 0.287); FLT3-D835, 22 (6%) and 8 (6%), respectively (p= 0.932); NPM1 mutations, 62 (17%) and 13 (10%), respectively (p= 0.057). Of 183 patients with TET2-mutated AML, the median TET2 variant allele frequency (VAF) was 42.9% (range, 2.26-95.32); of 113 with TP53-mutated AML, the median TP53 VAF, 45.9% (range, 1.15-93.74); of 109 with ASXL1-mutated AML, the median ASXL1 VAF was 34.5% (range, 1.17-58.62); of 109 with DNMT3A-mutated AML, the median DNMT3A VAF was 41.8% (range, 1.02-91.66); of 46 with JAK2-mutated AML, the median JAK2 VAF was 54.4% (range, 1.49-98.52). Overall, the median OS was 12 months and 11 months in CHIP AML and non-CHIP AML, respectively (p= 0.564); 16 months and 5 months in TET2-mutated AML and non-TET2-mutated AML, respectively (p <0.001); 4 months and 13 months in TP53-mutated and non-TP53-mutated AML, respectively (p< 0.001); 17 months and 11 months in DNMT3A-mutated and non-DNMT3A-mutated AML, respectively (p= 0.072); 16 months and 11 months in ASXL1-mutated AML and non-ASXL1-mutated AML, respectively (p= 0.067); 11 months and 12 months in JAK2-murated and non-JAK2-mutated AML, respectively (p= 0.123). The presence and number of CHIP mutations were not a prognostic factor for OS by univariate analysis (p=0.565; hazard ratio [HR], 0.929; 95% confidence interval [CI], 0.722-1.194: p= 0.408; hazard ratio, 1.058; 95% confidence interval, 0.926-1.208, respectively). MVA Cox regression identified age (p< 0.001; HR, 1.036; 95% CI, 1.024-1.048), TP53 VAF (p= 0.007; HR, 1.009; 95% CI, 1.002-1.016), NPM1 VAF (p=0.006; HR, 0.980; 95% CI, 0.967-0.994), and complex karyotype (p<0.001; HR, 1.869; 95% CI, 1.332-2.622) as independent prognostic factors for OS. Of 33 patients with CHIP AML who were evaluated for the clearance of VAF by next generation sequencing , landmark analysis at 6 months showed median OS of not reached and 20.3 months in patients with and without CHIP-mutation clearance, respectively (p=0.310). Conclusion: The VAF of TP53 and NPM1 mutations by next generation sequencing can further stratify patients with newly diagnosed AML. Approximately, each increment of TP53 and NPM1 VAF by 1% is independently associated with 1% higher risk of death, and 2% lower risk of death, respectively. The presence of CHIP mutations except TP53 does not affect outcome. Disclosures Sasaki: Otsuka Pharmaceutical: Honoraria. Short:Takeda Oncology: Consultancy. Ravandi:Macrogenix: Honoraria, Research Funding; Seattle Genetics: Research Funding; Sunesis: Honoraria; Xencor: Research Funding; Jazz: Honoraria; Seattle Genetics: Research Funding; Abbvie: Research Funding; Macrogenix: Honoraria, Research Funding; Bristol-Myers Squibb: Research Funding; Orsenix: Honoraria; Abbvie: Research Funding; Jazz: Honoraria; Xencor: Research Funding; Orsenix: Honoraria; Sunesis: Honoraria; Amgen: Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Research Funding; Astellas Pharmaceuticals: Consultancy, Honoraria; Amgen: Honoraria, Research Funding, Speakers Bureau; Astellas Pharmaceuticals: Consultancy, Honoraria. Kadia:BMS: Research Funding; Abbvie: Consultancy; Takeda: Consultancy; Jazz: Consultancy, Research Funding; Takeda: Consultancy; Amgen: Consultancy, Research Funding; Celgene: Research Funding; Novartis: Consultancy; Amgen: Consultancy, Research Funding; BMS: Research Funding; Jazz: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Consultancy; Abbvie: Consultancy; Celgene: Research Funding. DiNardo:Karyopharm: Honoraria; Agios: Consultancy; Celgene: Honoraria; Medimmune: Honoraria; Bayer: Honoraria; Abbvie: Honoraria. Cortes:Novartis: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Astellas Pharma: Consultancy, Research Funding; Arog: Research Funding.

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