Abstract: Background Copy-number alterations (CNAs) and gene mutations are hallmarks of cancer genomes, and they are implicated in the development of myeloid neoplasm. However, their relationships have not been fully examined. To address this issue, we have recently developed a novel, next-generation sequencing-based platform for copy-number analysis, which enabled us to detect mutations and CNAs simultaneously. We applied this platform to around 2,000 cases with myeloid neoplasms. Aims We aimed at delineating the landscape of CNAs and their relationships with gene mutations in myeloid neoplasms. Methods We examined 2,101 cases with myeloid neoplasms by whole-exome sequencing (WES) or targeted deep sequencing. Excluding 116 samples showing low qualities of copy-number signals, we performed subsequent analysis on the remaining 1,985 cases with myelodysplastic syndromes (MDS, n = 1,102), myelodysplastic/myeloproliferative neoplasms (MDS/MPN, n = 140), de novo acute myeloid leukemia (de novo AML, n = 448), and secondary AML (sAML, n = 295). In copy-number analysis, total copy numbers and allele-specific copy numbers (ASCNs) were quantified based on sequencing depths and allelic ratios on genome-wide probes. Copy-number signals were corrected for multiple biases (e.g. GC content, ASCN, and fragment length). We also validated the performance of this platform through comparison with SNP-array karyotyping data in 115 de novo AML cases. CNAs longer than 5 Mb were regarded as arm-level CNAs, and those shorter than 5 Mb were regarded as focal CNAs. Results In total, we identified 4,141 CNAs (52.9 % of cases with at least one CNA), and 3,863 mutations (73.9 % of cases with at least one mutation). Most frequent alterations included -7/del(7q) (13.2 %), del(5q) (11.4 %), trisomy 8 (7.2 %), and del(20q) (5.2 %), and mutations of TET2 (12 .3 %), TP53 (11.3 %), ASXL1 (10.1%), and DNMT3A (9.9 %). To evaluate the difference of copy-number landscapes between de novo AML and myelodysplasia (MDS, MDS/MPN, and sAML), we compared the frequencies of CNAs between them. Uni-parental disomy (UPD) of 13q (FLT3) and 11p (WT1), and amplifications of 11q, 13q, and 21q (ERG) were more enriched in de novo AML, while der(1;7), UPD of 11q (CBL), and del(20q) were enriched in myelodysplasia, suggesting differential involvements of CNAs. We next analyzed the correlations between CNA profiles and prognosis in cases with myelodysplasia. Since TP53 status implies a large impact on both patients' prognosis and CNA profiles, we separately analyzed TP53-positive (n = 53) and negative (n = 686) cases with available survival data. In TP53-negative cases, -7/7qLOH (Hazard ratio(HR): 2.28, q 〈 0.001), and UPD of 11q (CBL) (HR: 2.60, q = 0.0034) significantly correlated with shorter overall survivals (OS), while, in TP53-positive cases, amp(11q), +19, and amp(21q) were marginally associated with shorter OS. To delineate the relationships between CNAs and mutations, we interrogated correlations between both lesions among MDS cases without TP53 alterations (n = 937). A number of significant correlations were detected, such as those between trisomy 8 and del(20q) with U2AF1 mutations (q 〈 0.05, for each), and monosomy 7 and amp(21q) with mutations of RUNX1 and NRAS (q 〈 0.01, for each). These correlations were also revealed in clustering analysis based on CNA and mutation profiles, which identified 5 unique clusters: Cluster 1 (n = 171) with trisomy 8, del(20q), and mutations of U2AF1 and ETV6, Cluster 2 (n = 43) with monosomy 7, amp(21q), and mutations of NRAS, SETBP1, and RUNX1, Cluster 3 (n = 19) with amp(1q) and amp(3q), Cluster 4 (n = 127) with those of SF3B1, TET2, and DNMT3A, and Cluster 5 (n = 50) with those of SRSF2, STAG2, ASXL1, and RUNX1. The remaining 527 cases were not assigned into any cluster due to lack of significantly correlated alterations. Finally, the temporal relationships of coexisting alterations were estimated based on their cell fractions; monosomy 7 had significantly greater cell fractions (P = 0.031) and is predicted to precede NRAS mutations, while the cell fractions of U2AF1 mutations tended to be greater than those of trisomy 8 (P = 0.063), suggesting their implications in different stages of disease progression. Conclusion An integrated analysis of CNAs and mutations in 〉 2,000 cases revealed the impacts of CNAs on disease characteristics and provided novel insight into the interplay between CNAs and mutations in the pathogenesis of MDS. Figure Disclosures Atsuta: CHUGAI PHARMACEUTICAL CO., LTD.: Honoraria; Kyowa Kirin Co., Ltd: Honoraria. Kanda:Celgene: Consultancy, Research Funding; Novartis: Research Funding; Shionogi: Consultancy, Honoraria, Research Funding; Nippon-Shinyaku: Research Funding; Taiho: Research Funding; Asahi-Kasei: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Research Funding; Eisai: Consultancy, Honoraria, Research Funding; Eisai: Consultancy, Honoraria, Research Funding; Dainippon Sumitomo: Consultancy, Honoraria, Research Funding; Otsuka: Research Funding; Kyowa-Hakko Kirin: Consultancy, Honoraria, Research Funding; Ono: Consultancy, Honoraria, Research Funding; MSD: Research Funding; Chugai: Consultancy, Honoraria, Research Funding; CSL Behring: Research Funding; Taisho-Toyama: Research Funding; Tanabe Mitsubishi: Research Funding; Dainippon Sumitomo: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Kyowa-Hakko Kirin: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria; Astellas: Consultancy, Honoraria, Research Funding; Takara-bio: Consultancy, Honoraria; Novartis: Research Funding; Astellas: Consultancy, Honoraria, Research Funding; Sanofi: Research Funding; Pfizer: Research Funding; Asahi-Kasei: Research Funding; Alexion: Consultancy, Honoraria; CSL Behring: Research Funding; Takara-bio: Consultancy, Honoraria; Mochida: Consultancy, Honoraria; Taiho: Research Funding; Celgene: Consultancy, Research Funding; Tanabe Mitsubishi: Research Funding; Taisho-Toyama: Research Funding; Pfizer: Research Funding; Sanofi: Research Funding; Mochida: Consultancy, Honoraria; Alexion: Consultancy, Honoraria; Otsuka: Research Funding. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium: Membership on an entity's Board of Directors or advisory committees; Syros: Membership on an entity's Board of Directors or advisory committees. Saunthararajah:EpiDestiny: Consultancy, Equity Ownership, Patents & Royalties; Novo Nordisk: Consultancy. Miyazaki:Chugai: Research Funding; Otsuka: Honoraria; Novartis: Honoraria; Nippon-Shinyaku: Honoraria; Dainippon-Sumitomo: Honoraria; Kyowa-Kirin: Honoraria. Usuki:Boehringer-Ingelheim Japan: Other: Received Research ; Daiichi Sankyo: Other: Received Research ; SymBio Pharmaceuticals Limited.,: Other: Received Research ; Novartis: Speakers Bureau; Ono Pharmaceutical: Speakers Bureau; Takeda Pharmaceutica: Speakers Bureau; Chugai Pharmaceutical: Speakers Bureau; Nippon Shinyaku: Speakers Bureau; Mochida Pharmaceutical: Speakers Bureau; MSD K.K.: Speakers Bureau; Celgene Corporation: Other: Received Research , Speakers Bureau; Sumitomo Dainippon Pharma: Other: Received Research , Speakers Bureau; Pfizer Japan: Other: Received Research ; Stellas Pharma: Other: Received Research ; Otsuka: Other: Received Research ; Kyowa Kirin: Other: Received Research ; GlaxoSmithKline K.K.: Other: Received Research ; Sanofi K.K.: Other: Received Research ; Shire Japan: Other: Received Research ; Janssen Pharmaceutical K.K: Other: Received Research . Imada:Bristol-Meyer Squibb K.K.: Honoraria; Celgene K.K.: Honoraria; Chugai Pharmaceutical Co., Ltd.: Honoraria; Kyowa Hakko Kirin Co., Ltd.: Honoraria; Ono Pharmaceutical Co., Ltd.: Honoraria; Otsuka Pharmaceutical Co., Ltd.: Honoraria; Astellas Pharma Inc.: Honoraria; Novartis Pharma K.K.: Honoraria; Takeda Pharmaceutical Co.,LTD.: Honoraria; Nippon Shinyaku Co.,Ltd.: Honoraria. Takaori-Kondo:Kyowa Kirin: Research Funding; Pfizer: Honoraria; Janssen: Honoraria; Chugai: Research Funding; Takeda: Research Funding; Ono: Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria; Celgene: Honoraria, Research Funding. Kiguchi:Celltrion, Inc.: Research Funding; Astellas Pharmaceutical Co., Ltd.: Research Funding; Nippon Shinyaku Co., Ltd.: Research Funding; Otsuka Pharmaceutical Co., Ltd.: Research Funding; Kyowa Hakko Kirin Co., Ltd.: Research Funding; MSD CO., Ltd.: Research Funding; Novartis Pharmaceutical Co., Ltd.: Research Funding; Sumitomo Dainippon Pharmaceutical Co., Ltd.: Research Funding; Bristol-Myeres Squibb Co., Ltd.: Research Funding; Janssen Pharmaceutical Co., Ltd.: Research Funding; Celgene Co., Ltd.: Research Funding; SymBio Pharmaceutical Co., Ltd.: Research Funding; Taiho Pharmaceutical Co., Ltd.: Research Funding; Tejin Co., Ltd.: Research Funding; Sanofi K.K., Ltd.: Research Funding. Maciejewski:Alexion: Consultancy; Novartis: Consultancy. Ogawa:Asahi Genomics: Equity Ownership; Qiagen Corporation: Patents & Royalties; Dainippon-Sumitomo Pharmaceutical, Inc.: Research Funding; RegCell Corporation: Equity Ownership; ChordiaTherapeutics, Inc.: Consultancy, Equity Ownership; Kan Research Laboratory, Inc.: Consultancy.

Abstract: While germline predisposition to myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) has long been recognized mainly through rare familial and pediatric cases, it has been drawing an increasing attention, on the basis of the recent discovery of novel risk alleles for MDS/AML through studies relying on revolutionized sequencing technologies; according to these studies, it suggest that more numbers of MDS/AML cases than expected might have germline predisposition. Moreover, it is suggested that germline variations may also confer predisposition to age-related clonal hematopoiesis or "CHIP", which has been implicated in the development of MDS/AML. In this study, we explored germline predisposition to MDS and CHIP through intensive sequencing of blood samples from large cohorts of AML/MDS patients and 'hematologically' healthy individuals (HHIs), in which germline variants in 21 genes implicated in sporadic or familial MDS/AML or CHIP were interrogated among patients with MDS/AML from the Japan Marrow Donor Program (n=797) and HHIs aged 〉 60 years from Biobank Japan (n=10,852). Germline variants were referred to NCBI dbSNP Build 151 database, excluding the entries in COSMIC ver.7 and in-house database, followed by manual curations. Somatic mutations and CHIP in the 21 genes were also analyzed for MDS/AML and HHIs, respectively. In total, 30,286 germline variants, including both synonymous and non-synonymous changes, were detected in 21 genes in the entire cohort. By comparing their frequencies between in MDS/AML and HHIs, we identified 6 germline variants in showing a significant enrichment in MDS/AML. Among these most frequently observed was variants in DDX41, for which a total of 3,721 variants were detected in 3,688 HHIs. Among these, 3 variants were significantly enriched in MDS/AML, including p.A500fs (OR=13.1 [6.6-25.9] (95%CI) (n=15), p.S363del (OR=41.0, [4.3-349.5] ) (n=3), and p.Y259C (OR=34.2, [6.6-176.8]) (n=5). Of interest, 14 of 23 MDS patients with one of these alleles carried somatic DDX41 mutations, typically p.R525H, which were not found in any of HHIs, further supporting the relevance of these DDX41 risk alleles. Also including an additional 2 nonsense/splicing variants, 5 DDX41 alleles found in 25 MDS/AML patients were thought to represent germline predisposition to MDS/AML. Similarly, RUNX1 p.H85N (OR=9.10, [1.52-54.52] ) (n=2), CBL p.P782L (OR=4.27, [1.56-11.70]) (n=5), and GNAS p.H69N (OR = 2.90, [1.28-6.59] ) (n=7) showed a significant enrichment in MDS/AML. Combined, these putative risk alleles accounted for 4.6% (37/797) of sporadic MDS and sAML. None of these alleles were observed in the Caucasian population of Exome Aggregation Consortium dataset, suggesting Asian origins of these variants. We next evaluated the effects of germline variants on CHIP. CHIP mutations were detected in 929 HHIs, where DNMT3A mutations (n=290) were most prevalent, followed by TET2 (n=124) and ASXL1 (n=68) mutations. By comparing allele frequency of each of 1,276 germline variants between healthy donors with and without CHIP, we identified two haplotypes at the JAK2 and TET2 loci, defined by T/A at c.C489T/c.G2490A (JAK2) and G/G/T at c.G652A/c.G3117A/c.T4140C (TET2), which were significantly enriched in the cases carrying CHIP with the JAK2 (p.V617F) and TET2 mutations, respectively (T/A vs. C/G; OR=3.36, [1.41-8.01] for JAK2 and G/G/T vs. A/A/C; OR=1.85, [1.19-2.86] for TET2). Intriguingly, the JAK2 risk haplotype (C/G) were also enriched in MDS cases with JAK2 p.V617F mutations (T/A vs. C/G; OR=3.06, [1.26-7.60]). Similarly, the TET2 risk haplotype (G/G/T) tended to be enriched in MDS cases with TET2 mutations, although not statistically significant. Finally, variant allele frequency of JAK2 p.V617F mutations in CHIP exceeded 0.5 in 4 out of 26 JAK2 CHIP-positive patients (15%), suggesting the presence of loss of heterozygosity (LOH) in chromosome 9p. In conclusion, through a large-scale detection of germline variants in 21 common drivers of MDS/AML as well as CHIP, we identified multiple novel germline variants or haplotypes that showed a significant predisposition to the development of adult-onset MDS or CHIP, respectively. Our findings provide novel insights into the genetic basis of myeloid leukemogenesis and the development of CHIP. Disclosures Nakagawa: Sumitomo Dainippon Pharma Co., Ltd.: Research Funding. Kanda:Otsuka: Research Funding; Dainippon-Sumitomo: Consultancy, Honoraria, Research Funding; Eisai: Consultancy, Honoraria, Research Funding; Chugai: Consultancy, Honoraria, Research Funding; Nippon-Shinyaku: Research Funding; Astellas: Consultancy, Honoraria, Research Funding; Kyowa-Hakko Kirin: Consultancy, Honoraria, Research Funding; Taiho: Research Funding; Pfizer: Research Funding; MSD: Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Asahi-Kasei: Research Funding; Ono: Consultancy, Honoraria, Research Funding; Sanofi: Research Funding; Novartis: Research Funding; Shionogi: Consultancy, Honoraria, Research Funding; Taisho-Toyama: Research Funding; CSL Behring: Research Funding; Tanabe-Mitsubishi: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Mochida: Consultancy, Honoraria; Alexion: Consultancy, Honoraria; Takara-bio: Consultancy, Honoraria.

Abstract: Frequent pathway mutation involving multiple components of the RNA splicing machinery is a cardinal feature of myeloid neoplasms showing myeloid dysplasia, in which the major mutational targets include U2AF35, ZRSR2, SRSF2 and SF3B1. Among these, SF3B1 mutations were strongly associated with MDS subtypes characterized by increased ring sideroblasts, such as refractory anemia and refractory cytopenia with multiple lineage dysplasia with ring sideroblasts, suggesting the critical role of SF3B1 mutations in these MDS subtypes. However, currently, the molecular mechanism of SF3B1mutation leading to the ring sideroblasts formation and MDS remains unknown. The SF3B1 is a core component of the U2-small nuclear ribonucleoprotein (U2 snRNP), which recognizes the 3′ splice site at intron–exon junctions. It was demonstrated that Sf3b1 null mice were shown to be embryonic lethal, while Sf3b1 +/- mice exhibited various skeletal alterations that could be attributed to deregulation of Hox gene expression due to haploinsufficiency of Sf3b1. However, no detailed analysis of the functional role of Sf3b1 in hematopoietic system in these mice has been performed. So, to clarify the role of SF3B1 in hematopoiesis, we investigated the hematological phenotype of Sf3b1 +/- mice. There was no significant difference in peripheral blood counts, peripheral blood lineage distribution, bone marrow total cellularity or bone marrow lineage composition between Sf3b1 +/+ and Sf3b1 +/- mice. Morphologic abnormalities of bone marrow and increased ring sideroblasts were not observed. However, quantitative analysis of bone marrow cells from Sf3b1 +/- mice revealed a reduction of the number of hematopoietic stem cells (CD34 neg/low, cKit positive, Sca-1 positive, lineage-marker negative: CD34-KSL cells) measured by flow cytometry analysis, compared to Sf3b1 +/+ mice. Whereas examination of hematopoietic progenitor cells revealed a small decrease in KSL cell populations and megakaryocyte - erythroid progenitors (MEP) in Sf3b1 +/- mice, and common myeloid progenitors (CMP), granulocyte - monocyte progenitors (GMP) and common lymphoid progenitors (CLP) remained unchanged between Sf3b1 +/+ and Sf3b1 +/- mice. In accordance with the reduced number of hematopoietic stem cells in Sf3b1 +/- mice, the total number of colony-forming unit generated from equal number of whole bone marrow cells showed lower colony number in Sf3b1 +/- mice in vitro. Competitive whole bone marrow transplantation assay, which irradiated recipient mice were transplanted with donor whole bone marrow cells from Sf3b1 +/+ or Sf3b1 +/- mice with an equal number of competitor bone marrow cells, revealed impaired competitive whole bone marrow reconstitution capacity of Sf3b1 +/- mice in vivo. These data demonstrated Sf3b1 was required for hematopoietic stem cells maintenance. To further examine the function of hematopoietic stem cells in Sf3b1 +/- mice, we performed competitive transplantation of purified hematopoietic stem cells from Sf3b1 +/+ or Sf3b1 +/- mice into lethally irradiated mice together with competitor bone marrow cells. Sf3b1 +/- progenitors showed reduced hematopoietic stem cells reconstitution capacity compared to those from Sf3b1 +/+ mice. In serial transplantation experiments, progenitors from Sf3b1 +/- mice showed reduced repopulation ability in the primary bone marrow transplantation, which was even more pronounced after the second bone marrow transplantation. Taken together, these data demonstrate that Sf3b1 plays an important role in normal hematopoiesis by maintaining hematopoietic stem cell pool size and regulating hematopoietic stem cell function. To determine the molecular mechanism underlying the observed defect in hematopoietic stem cells of Sf3b1 +/- mice, we performed RNA-seq analysis. We will present the results of our biological assay and discuss the relation of Sf3b1 and hematopoiesis. Disclosures: No relevant conflicts of interest to declare.

Abstract: Background: Allogeneic hematopoietic stem cell transplantation (HSCT) is the only curative therapy for patients with myelodysplastic syndromes (MDS), whose benefit, however, is frequently offset by accompanying mortality and morbidity, underscoring the importance of accurate prognostication before the therapeutic choice. For this purpose, several systems, such as the International Prognostic Scoring System (IPSS), are being successfully applied to clinics, and recent genome profiling studies indicate that molecular diagnostics can further improve the prediction. Nevertheless, existing systems are based on the observation from those patients who were untreated or only supportively treated and therefore, may not successfully be applied to the prognostication of the patients who are actually treated by HSCT. Methods: We analyzed patients with MDS (N = 719) from a cohort of Japan Marrow Donor Program (JMDP) who were treated by unrelated HSCT between 2006 and 2013. Peripheral blood DNA was subjected to targeted deep sequencing in 68 major driver genes for the detection of both somatic mutations and copy number variations (CNVs) with accurate determination of their allelic burdens. Results: The median age at HSCT and observation period were 53 years old (20-66) and 372 days (2-3001), respectively. At the diagnosis, 63, 203, 163 and 65 patients have low, intermediate-1, intermediate-2 and high risk classified on the basis of IPSS, respectively (IPSS data was not available for 250 patients). The median time from diagnosis to HSCT was 274 (9-10900) days. Mutations were observed in 75% of the patients, of which TP53 was most frequently mutated (14.3%), followed by U2AF1 (13.2%), RUNX1 (12.2%), ASXL1 (11.0%) and DNMT3A (9.3%). The mean number of mutations was 2.1 per patient and the mean allelic burden was 23.4%. To evaluate karyotyping we combined metaphase cytogenetics and copy number variations using targeted sequencing data. Complex karyotype, chromosome 7 anomaly, deletion 5q, and deletion 20q were observed in 174 (24.4%), 173 (24.3%), 91 (12.8%), and 50 (7.0%) of the patients, respectively. Combined, 86.6% of the patients had one or more genetic lesions. Patients with one or more mutations or CNVs showed unfavorable overall survival (Hazard Ratio (HR) 2.46, P = 2.12 x 10-5). Univariate analysis for each gene identified mutations in TP53 (HR 2.85, P 〈 2.0 x 10-16), NRAS (HR 1.90, P = 5.4 x 10-4), ETV6 (HR 1.54, P = 0.029), CBL (HR 2.25, P = 5.3 x10-5), EZH2 (HR 1.74, P = 0.014), KRAS (HR 2.01, P = 2.0 x 10-3), U2AF2 (HR 1.97, P = 0.027), JARID2 (HR 2.09, P = 0.039), and RIT1 (HR 2.16, P = 0.023) as the unfavorable factors for the overall survival. Besides, mutations in PRPF8 had a favorable effect on overall survival (HR 0.50, P = 0.029). Then, we performed multivariate analysis with stepwise model selection of these significant mutations and clinical parameters. Mutations in TP53 (HR 2.31, P=0.015), and ETV6 (HR 2.57, P=0.015) remained significant together with complex karyotype (HR 2.15, P = 0.0063), grade of acute graft versus host disease (GVHD) (Grade I or II: HR 1.95, P = 0.011, Grade III or IV: HR 4.18, P = 7.94 x 10-5), and the number of red blood cell transfusion received before HSCT ( 〉 =10 times: HR 2.64, P = 0.027). Next, we analyzed the impact of mutations on relapse in cases who achieved complete response after HSCT (N = 423 (58.8%)). Patients with mutations in one or more genetic lesions showed unfavorable relapse free survival (HR 2.27, P = 1.65 x 10-4). Univariate analysis for each gene revealed mutations in TP53 (HR 3.09, P = 9.5 x 10-16), NRAS (HR 2.21, P = 0.0019), ETV6 (HR 1.90, P = 0.012), PRPF8 (HR 0.40, P = 0.046), and WT1 (HR 2.24, P = 0.013) were significant for the relapse free survival. Multivariate analysis and stepwise model selection identified ETV6 (HR 2.98, P = 0.011), WT1 (HR 4.01, P = 0.014), complex karyotype (HR 2.39, P = 0.0083), IPSS High (HR 6.22, P = 0.0053), and Grade III or IV acute GVHD (HR 2.91, P = 0.0071) as unfavorable factors. Conclusions: This large study of MDS cases treated by unrelated HSCT demonstrated that somatic mutations of several driver genes were novel prognostic factors for overall and relapse free survival. These genetic factors were independent of well-known prognostic makers, and therefore could be used to better guide therapy for MDS patients. Disclosures No relevant conflicts of interest to declare.

Abstract: Introduction Primary central nervous system lymphoma (PCNSL) is a rare subtype of non-Hodgkin's lymphoma. Although most cases (~95%) show histology of diffuse large B-cell lymphomas (DLBCLs), PCNSL shows very different biological and clinical characteristics from systemic DLBCL. Nevertheless, our knowledge about the molecular pathogenesis of PCNSL and genetic differences between both lymphomas are still incomplete. Method To obtain a comprehensive view of the genetic alterations, including mutations in non-coding regions as well as structural variants (SVs), we performed whole-genome sequencing (WGS) of 22 PCNSL cases. Subsequently, to unravel the genetic differences between PCNSL and systemic DLBCL, we re-analyzed WGS data from systemic DLBCL cases (N = 47) generated by the Cancer Genome Atlas Network (TCGA) and Cancer Genome Characterization Initiative (CGCI) using our in-house pipeline. The mean depth of WGS for tumor samples were 49X and 37X for PCNSL and DLBCL cases, respectively. Whole-exome sequencing (WES) was also performed for an additional 37 PCNSL cases to reliably capture driver alterations and also to analyze mutational signatures in PCNSL, which were compared to those obtained from the WES data for DLBCL from TCGA (N = 49). Results WGS identified 10.5 and 5.6 mutations per mega-base on average in PCNSL and DLBCL, respectively. We first explored the density of somatic mutations and identified 64 and 33 genomic loci showing significantly high mutation densities in PCNSL and DLBCL, respectively. In PCNSL, most of these loci corresponded to known targets of somatic hypermutations (SHMs) induced by activation-induced cytidine deaminase (AID), including those for IG genes (IGK, IGH and IGL), BCL6, and PIM1, as well as those for known driver genes, such as MYD88 and CD79B. Although most of the hypermutated regions were overlapped between PCNSL and DLBCL, some regions were differentially affected by hypermutations between both lymphoma types. For example, BCL2 and SGK1 loci were frequently affected by SHMs in germinal center B-cell (GCB) DLBCL, while not in PCNSL. In terms of non-coding driver mutations, we identified frequent mutations in a PAX5 enhancer region in 8/22 (36%) of PCNSL and 18/47 (38%) of DLBCL cases. SVs were common in both lymphoma types, where 104 (PCNSL) and 57 (DLBCL) SVs were detected per sample. SV clusters were identified in 34 (PCNSL) and 13 (DLBCL) regions, of which several clusters were commonly seen in both PCNSL and DLBCL, and included IG loci, BCL6, FHIT, TOX and CDKN2A. In PCNSL, SVs were clustered within the loci for known targets of SHMs, such as BCL6, BTG2 and PIM1. As was the case with somatic mutations, the SV cluster corresponding to BCL2 was only seen in DLBCL. We then analyzed these clustered breakpoints for their proximity to known sequence motifs targeted by AID (CpG and WGCW). Breakpoints of SVs found in the targets of SHMs, including PIM1, BCL6, BTG2 and BCL2, showed an enrichment at or near the CpG, supporting the involvement of AID in the generation of these SVs. By analyzing these SV clusters, we identified several novel driver genes in PCNSL. For example, WGS and WES identified an enrichment of breakpoints of deletions (7/22) and loss-of-function mutations (6/37) in GRB2, strongly indicating its tumor suppressor role in PCNSL. We also analyzed pentanucleotide signatures of mutations in coding sequences detected by WES of PCNSL and DLBCL, taking into consideration the two adjacent bases 3' and 5' of the substitutions as well as transcription strand biases. Two predominant mutational signatures were identified in PCNSL: the AID signature characterized by C 〉 T mutations within the WRCY motif targeted by SHMs and the age-related signature involving C 〉 T transition at CpG dinucleotides. For DLBCL, an additional signature (signature 17 according to Alexandrov et al.) was detected as well, which had been reported in DLBCL with an unknown mechanistic basis. Conclusions Comprehensive genomic analyses of a large cohort of PCNSL and DLBCL cases have revealed the major targets of somatic mutations and SVs, including novel driver genes. In both PCNSL and systemic DLBCL, an enhanced AID activity is thought to be associated with generation of both SHMs and SVs, although the activity and targets of AID seem to substantially differ between both lymphoma types, suggesting distinct pathogenesis therein. Disclosures Kataoka: Boehringer Ingelheim: Honoraria; Yakult: Honoraria; Kyowa Hakko Kirin: Honoraria. Ogawa:Takeda Pharmaceuticals: Consultancy, Research Funding; Kan research institute: Consultancy, Research Funding; Sumitomo Dainippon Pharma: Research Funding.

Abstract: TP53 and RAS-pathway mutations predict very poor survival, when seen with CK and MDS/MPNs, respectively. For patients with mutated TP53 or CK alone, long-term survival could be obtained with stem cell transplantation.

Abstract: Introduction: Age-related clonal hematopoiesis (CH) has been implicated in an increased risk of myeloid neoplasms. While common driver genes mutated in CH largely overlap to those in myeloid neoplasms, a notable exception is protein phosphatase Mg2+/Mn2+dependent 1D gene (PPM1D), encoding a p53-targeting phosphatase. Although it is known to be involved in DNA damage response pathways and more frequently mutated in therapy-related myeloid neoplasms than in primary ones, its role in CH and myeloid neoplasms has not been fully understood. Aim: To identify genetic features associated with PPM1D mutations, we examined genetic profiles in the large cohorts of healthy elderly individuals and patients with myelodysplasia. Methods: We enrolled 10,826 healthy individuals ( 〉 60y) and 1,213 cases with myelodysplasia, including myelodysplastic syndromes (MDSs), myelodysplastic/myeloproliferative neoplasms (MDS/MPNs) (n=1,080), and secondary acute myeloid leukemia (sAML) (n=133), of which 567 cases were treated by hematopoietic stem cell transplantation (HSCT) through the Japan Marrow Donor Program just after sampling, and 332 of them underwent any therapy before sampling. Samples from healthy individuals were subjected to multiplex-amplicon sequencing for 22 genes, including PPM1D and other genes, related to CH or myeloid neoplasms. Myelodysplasia samples had previously been sequenced for major myeloid drivers, except for PPM1D, which was newly sequenced in this study. Results: Frequency of PPM1D mutations in myelodysplasia and healthy individuals was 3.1% and 0.42%, with a median variant allele frequency (VAF) of 0.043 and 0.056, respectively. PPM1D mutations were more frequent in cases with previous treatment (4.8%) than in those without known history of therapy (2.3%) (P=0.038). In MDS and MDS/MPN cases, 59.5% of PPM1D mutations had accompanying mutations, in which DNMT3A mutations were the most frequently identified (16.2%, n=6). These 6 cases were diagnosed with RCUD (n=1), RCMD (n=2), RAEB-2 (n=2), or CMML (n=1). The association between PPM1D and DNMT3A mutations was also seen in 7 of 45 healthy individuals with PPM1D mutations, of which one had a DNMT3A-R882 mutation. In the HSCT cohort, 192 cases harbored ≥2 mutations of the 22 CH-related genes, and the relative temporal order of these mutations was investigated using Bradley-Terry model relying on their tumor cell fractions. The estimate of PPM1D mutations tended to be smaller than that of DNMT3A mutations. To further confirm chronological order of these mutations, VAF values were compared between them in the individuals with concurrent PPM1D and DNMT3A mutations (n=13; 6 myeloid neoplasms and 7 healthy donors). In the combined cohort, the VAFs of PPM1D and DNMT3A mutations were correlated (Spearman; correlation coefficient=0.87, P=1.2x10e-5). In both neoplastic and healthy cohort, the VAFs of DNMT3A-R882 mutations were larger than those of accompanying PPM1D mutations. These findings suggest that these mutations should be acquired in the same cell populations and that DNMT3A mutations might occur prior to PPM1D mutations. With regard to copy number alterations associated with PPM1D-mutated myelodysplasia, del(5q) (16.7%) and complex(-like) karyotypes (13.9%) were among the most frequent chromosomal abnormalities. Approximately 65% of PPM1D-mutated tumor samples had normal karyotype, which was similar to PPM1D-unmutated cases. PPM1D mutations did not significantly influence overall survival, although PPM1D mutations tended to negatively affect clinical outcome among patients who were treated with HSCT (Hazard ratio, 1.61; 95% confidence interval, 0.95 to 2.70). Conclusion: PPM1D mutations were more enriched in myelodysplasia than in CH, and the median value of VAF in PPM1D mutations in CH was not significantly different from that in myelodysplasia. The size of PPM1D-mutated clones tended to be relatively smaller compared with that of clones with other mutations in myelodysplasia. PPM1D and DNMT3A mutations might be cooperatively associated in the pathogenesis of myelodysplasia and CH. Disclosures Baer: MLL Munich Leukemia Laboratory: Employment. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Atsuta:CHUGAI PHARMACEUTICAL CO., LTD.: Honoraria; Kyowa Kirin Co., Ltd: Honoraria. Miyazaki:Chugai: Research Funding; Otsuka: Honoraria; Novartis: Honoraria; Nippon-Shinyaku: Honoraria; Dainippon-Sumitomo: Honoraria; Kyowa-Kirin: Honoraria. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Ogawa:Dainippon-Sumitomo Pharmaceutical, Inc.: Research Funding; Qiagen Corporation: Patents & Royalties; Asahi Genomics: Equity Ownership; RegCell Corporation: Equity Ownership; Kan Research Laboratory, Inc.: Consultancy; ChordiaTherapeutics, Inc.: Consultancy, Equity Ownership.

Abstract: Abstract 1282 Emerging evidence is establishing a connection between MDS and spliceosome mutations. Spliceosome including SF3b1, U2AF1 and SRSF2 are frequently and exclusively mutated in myelodysplastic syndromes (MDS) and related myeloid neoplasms. Spliceosome mutations occur at varying frequencies in different disease subtypes. SF3B1 was shown to be highly associated with MDS characterized by increased ring sideroblasts and SRSF2 mutations are more prevalent in chronic myelomonocytic leukemia. In spite of the fact that the recent discovery constitutes a novel class of genomic lesions and defines an entirely new pathogenic pathway of leukaemogenesis, the pathogenesis of spliceosome mutation is not largely understood. To understanding the biological consequences of spliceosomal mutations, we previously reported mutant U2AF1 cause altered RNA splicing, and overexpressed mutant U2AF1 decrease in cell proliferarion. However, currently, no functional analysis of SRSF2 mutation has been published. SRSF2 belongs to the serine/arginine-rich (SR) protein family. SR proteins are a family of RNA binding proteins characterized by one or two RNA recognition motifs (RRMs) and a signature RS domain enriched with arginine and serine repeats (RS domain).Growing body of evidence suggests that SR protein may be directly involved in the process of carcinogenesis. Gene knockout experiment indicated SRSF2 is involved with specific pathways in regulating cell proliferation and genomic stability during mammalian organogenesis. In neck and head tumor, SRSF2 is frequently overexpressed. And upregulated SRSF2 increases missplicing and downregulates E-cadherin expression, which is an important tumor suppressor gene. Therefore SRSF2 potential function in tumorigenesis is suggested in epithelial cancers. SRSF2 mutations with MDS exclusively occur at P95 within an intervening sequence between RRM and RS domains, indicating a gain-of-function nature of these mutations. So, to clarify the biological role of SRSF2 mutations in leukemogenesis, we evaluated the oncogenic role of SRSF mutations by expressing a mutant SRSF2 allele in Jurkat cells. The cells transduced with a tumor-derived SRSF2 allele showed reduced cell proliferation and increased apoptosis compared to the mock and wild type SRSF2-transduced cells. Next we performed in vitro colony assay using a highly purified hematopoietic stem cell population (CD34-c-Kit+ScaI+ Lin-(CD34-KSL) cells) collected from C57BL/6 (B6)-Ly5.1 mouse that was retrovirally transduced with mock, mutant or wild-type SRSF2 construct. The mutant SRSF2-transduced cells showed reduced cell proliferation compared with mock- or wild-type SRSF2 transduced cells. Subsequently, we conducted bone marrow transplantaion assay. We collected CD34-KSL cells from B6-Ly5.1 mouse, and retrovirally transduce mock, mutant or wild-type SRSF2 construct, each harbouring the EGFP marker gene. And these cells were sorted by EGFP marker, and transplanted with competitor cells (B6-Ly5.1/5.2 F1 mice origin) into lethally irradiated B6-Ly5.2 mice. The wild-type SRSF2-transduced cells showed a lower reconstitution capacity than the mock-transduced cells. On the other hand, the recipients of the cells transduced with the mutant SRSF2 showed lower EGFP-positive cell chimaerism than those of the mock- or the wild-type SRSF2-transduced. Therefore, the mutant SRSF2 was indicated to have a negative effect on cellular proliferation capacity in vitro and in vivo, and a gain-of-function nature of these mutations is suggested. These results are similar to the effect of U2AF1 mutant, which we reported mutant U2AF1 transduced TF-1 and HeLa cells present with a decrease in cell proliferation and hematopoietic stem cells expressing mutant U2AF1 also displayed lower reconstitution capacity by competitive reconstitution assay in mice. So far, the mechanism responsible for the growth advantage of mutant cells in patient is unclear. We furthermore observe hematopoietic phenotype of the bone marrow transplanted model mouse. SRSF2 mutations can coexist with mutations in TET2, ASXL1 and RUNX1. Therefore we performed additionally bone marrow transplantation assay, utilizing hematopoietic cells derived from TET2 knockdown mice, as a model of multistep carcinogenesis. We will present the results of our biological assay on the SRSF2 mutations and discuss the pathogenesis of MDS. Disclosures: No relevant conflicts of interest to declare.

Abstract: ATL subtypes are further classified into molecularly distinct subsets with different prognosis by genetic profiling. PD-L1 amplifications are a strong genetic predictor for worse outcome in both aggressive and indolent ATL.

Abstract: Introduction Primary central nervous system lymphoma (PCNSL) is a rare subtype of non-Hodgkin lymphoma, of which approximately 95% are diffuse large B-cell lymphomas (DLBCLs). Despite the substantial development of intensive chemotherapy during the past two decades, overall clinical outcome of PCNSL has been poorly improved especially in elderly and so has been our knowledge about the molecular pathogenesis of PCNSL, in terms of driver alterations that are relevant to the development of PCNSL. Method To delineate the genetic basis of PCNSL pathogenesis, we performed a comprehensive genetic study. We first analyzed paired tumor/normal DNA from 35 PCNSL cases by whole-exome sequencing (WES). Significantly mutated genes identified by WES and previously known mutational targets in PCNSL and systemic DLBCL were further screened for mutations using SureSelect-based targeted deep sequencing (Agilent) in an extended cohort of PCNSL cases (N = 90). Copy number alterations (CNAs) have been also investigated using SNP array-karyotyping (N =54). We also analyzed WES and SNP array data of systemic DLBCL cases (N = 49) generated by the Cancer Genome Atlas Network (TCGA) to unravel the genetic difference between PCNSL and systemic DLBCL. Results The mean number of nonsynonymous mutations identified by WES was 183 per sample, which was comparable to the figure in systemic DLBCL and characterized by frequent somatic hypermutations (SHMs) involving non-Ig genes. A higher representation of C 〉 T transition involving CpG dinucleotides and hotspot mutations within the WRCY motif targeted by SHM further suggested the involvement of activation-induced cytidine deaminase (AID) in the pathogenesis of PCNSL. We found 12 genes significantly mutated in PCNSL (q 〈 0.1), including MYD88, PIM1, HLA-A, TMEM30A, B2M, PRDM1, UBE2A, HIST1H1C, as well as several previously unreported mutational targets in systemic DLBCL or PCNSL, such as SETD1B, GRB2, ITPKB, EIF4A2. Copy number analysis identified recurrent genomic segments affected by focal deletions (N = 27) and amplifications (N = 10), most of which included driver genes targeted by recurrent somatic mutations or known targets of focal CNAs such as CDKN2A and FHIT. Subsequent targeted sequencing finally identified a total of 107 significantly mutated genes, of which 43 were thought to be targeted by SHM according to their mutational signature and genomic distribution. Most cases with PCNSL (98%) had mutations and CNAs involving genes that are relevant to constitutive NF-KB/Toll-like receptor (TLR)/BCR activity, including those in MYD88 (80%), CD79B/A (60%), CARD11 (18%), TNFAIP3 (26%), GRB2 (24%) and ITPKB (23%). Genetic alterations implicated in escape from immunosurveillance were also frequently identified in as many as 76% of cases. Mutations of HLA-B (64%), HLA-A (36%), HLA-C (28%), B2M (14%) and CD58 (12%) were commonly detected in addition to CNAs in 6p21.32 (HLA class II), 1p13.1 (CD58) and 15q15.2 (B2M), suggesting the importance of immune escape in the pathogenesis of PCNSL. SHMs were also seen in most cases (98%), which affected not only known targets of AID including PIM1, IGLL5 and BTG2 but also previously unreported genes involved in cell proliferation, apoptosis, or B cell development. The pattern of frequently mutated genes in PNCSL was more uniform compared with that in systemic DLBCL, and similar to that found in the activated B cell subtype of DLBCL (ABC-DLBCL), which was in accordance with the previous report of immunophenotypic analysis of PCNSL. On the other hand, mutations of HLA class I genes (HLA-B, HLA-A) were more frequently mutated in PCNSL compared with ABC-type DLBCL. Conclusion WES, SNP array karyotyping and follow-up targeted sequencing of a large cohort of PCNSL cases revealed the genetic landscape of PCNSL, which were more homogeneous than that of systemic DLBCL, and thought to be involved in activation of constitutive NF-KB/TLR/BCR signaling, escape from immunosurveillance, as well as highly frequent SHMs. Disclosures No relevant conflicts of interest to declare.