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: Abstract 1706 The recent study of whole-exome sequencing on MDS has revealed frequent and specific pathway mutations involving multiple components of the RNA splicing machinery, including U2AF35, SRSF2, SF3B1 and ZRSR2. The mutually exclusive manner of these mutations among MDS cases also supported that deregulated RNA splicing contributes to the pathogenesis of MDS. Interestingly, the distribution of these splicing pathway mutations shows a substantial difference with regard to disease subtypes. Thus, the SF3B1 mutations are by far the most frequent in RARS and RCMD-RS cases, and the SRSF2 mutations are more prevalent in CMML. SRSF2 is a member of the SR protein family that is commonly characterized by one or two RNA recognition motifs (RRM) and a signature serine/arginine-rich domains (RS domains). The SR proteins interact with other spliceosome components through their RS domains, among which most extensively characterized are SRSF1 (ASF/SF2) and SRSF2 (SC35). Both SR proteins bind a splicing enhancer site within the 3' target exon and also interact with the U2AF, playing an indispensable role in both constitutive and alternative splicing in most cell types. In fact, the knockout of these genes in mice results in embryonic lethality. There is emerging evidence that establishes a connection between the abnormal expression of SR proteins and the development of cancer, mainly as a result of change in the alternative splicing patterns of key transcripts. Increased expression of SR proteins usually correlates with cancer progression, as shown by elevated expression of SR proteins in ovarian cancer and breast cancer. In spite of the similarity in their functions, both proteins are thought to have distinct roles, especially in the pathogenesis of myeloid malignancies, since we found no SRSF1 mutations among 582 cases with myeloid neoplasms. On the other hand, studies have shown that increased expression of SRSF1 transforms immortal rodent fibroblasts and leads to the formation of sarcomas in nude mice, supporting the notion that SRSF1 is a proto-oncogene, whereas SRSF2 does not have transforming activity, indicating a highly specific role of SRSF1 in this type of cancer. Thus, little is known about the biological mechanism by which the SRSF2 mutations are involved in the pathogenesis of MDS, although the mutations at the P95 site are predicted to cause a significant displacement of the RS domain relative to the domain for RNA binding. So to gain an insight into the functional aspect of SRSF2 mutations, we performed sequencing analysis of mRNAs extracted from mutant (P95H) SRSF2-transduced HeLa cells in which expression of the wild-type and mutant SRSF2 were induced by doxycycline. The abnormal splicing in mutant SRSF2-transduced cells was directly demonstrated by evaluating the read counts in different fractions. Next, to investigate functional role of SRSF2 mutant, HeLa cells were transduced with lentivirus constructs expressing either the P95H SRSF2 mutant or wild-type SRSF2, and cell proliferation was examined. After the induction of gene expression, the mutant SRSF2-transduced cells showed reduced cell proliferation. In addition, we transduced P95H SRSF2 constructs into factor-dependent 32D cell lines. The expression of mutant SRSF2 protein resulted in increased apoptosis in the presence of IL-3 and also suppression of cell growth in the presence of G-CSF, which may be related to ineffective hematopoiesis, a common feature of MDS. To further clarify the biological effect of SRSF2 mutants in vivo, a highly purified hematopoietic stem cell population (CD34-c-Kit+ScaI+ Lin-) prepared from C57BL/6 (B6)-Ly5.1 mouse bone marrow was retrovirally transduced with either the mutant or wild-type SRSF2 with EGFP marking. The transduced cells were mixed with whole bone marrow cells from B6-Ly5.1/5.2 F1 mice, transplanted into lethally irradiated B6-Ly5.2 recipients, and we are now monitoring the ability of these transduced cells to reconstitute the hematopoietic system and other hematological phenotypes. Much remains, however, to be unrevealed about the functional link between the abnormal splicing of RNA species and the phenotype of myelodysplasia. Further functional studies should be warranted to understand these mechanisms in detail. In this meeting, we will present the results of our functional studies on the SRSF2 mutations and discuss the pathogenesis of MDS in terms of the alterations of splicing machinery. Disclosures: No relevant conflicts of interest to declare.

Abstract: Germ line DDX41 variants have been implicated in late-onset myeloid neoplasms (MNs). Despite an increasing number of publications, many important features of DDX41-mutated MNs remain to be elucidated. Here we performed a comprehensive characterization of DDX41-mutated MNs, enrolling a total of 346 patients with DDX41 pathogenic/likely-pathogenic (P/LP) germ line variants and/or somatic mutations from 9082 MN patients, together with 525 first-degree relatives of DDX41-mutated and wild-type (WT) patients. P/LP DDX41 germ line variants explained ∼80% of known germ line predisposition to MNs in adults. These risk variants were 10-fold more enriched in Japanese MN cases (n = 4461) compared with the general population of Japan (n = 20 238). This enrichment of DDX41 risk alleles was much more prominent in male than female (20.7 vs 5.0). P/LP DDX41 variants conferred a large risk of developing MNs, which was negligible until 40 years of age but rapidly increased to 49% by 90 years of age. Patients with myelodysplastic syndromes (MDS) along with a DDX41-mutation rapidly progressed to acute myeloid leukemia (AML), which was however, confined to those having truncating variants. Comutation patterns at diagnosis and at progression to AML were substantially different between DDX41-mutated and WT cases, in which none of the comutations affected clinical outcomes. Even TP53 mutations made no exceptions and their dismal effect, including multihit allelic status, on survival was almost completely mitigated by the presence of DDX41 mutations. Finally, outcomes were not affected by the conventional risk stratifications including the revised/molecular International Prognostic Scoring System. Our findings establish that MDS with DDX41-mutation defines a unique subtype of MNs that is distinct from other MNs.

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.

Abstract: Background Copy number alteration (CNA) is a hallmark of cancer genomes and has been implicated in the development of human cancers, including myeloid neoplasms. We developed a novel, next-generation sequencing-based platform for highly sensitive detection of CNAs with a single exon resolution, which was applied to sequencing data from 1,185 patients to delineate a comprehensive landscape of CNAs in myeloid neoplasms. Materials and Methods We enrolled 1,185 patients with different myeloid neoplasms including myelodysplastic syndromes (n = 607), myelodysplastic/myeloproliferative neoplasms (n = 80), de novo acute myeloid leukemia (AML) (n = 136), secondary AML (sAML) (n = 226), and unknown myeloid malignancies (n = 136). Whole-exome sequencing (WES) was performed on samples from 260 patients, while samples from 925 patients including pre-transplantation peripheral blood samples provided by Japan Marrow Donor Program were subjected to targeted deep sequencing. Eight cases were serially evaluated before and after progression tosAML. RNA baits for targeted deep sequencing were designed to cover 69 driver genes in myeloid neoplasms and 1,158 single-nucleotide polymorphisms (SNPs)for assessment of allelic imbalance. In WES, allelic imbalance was examined using allele frequencies of SNPs within coding regions. Focal CNAs were defined as CNAs whose lengths relative to the chromosomal arms were below 10%. Results To obtain a landscape of CNAs in coding regions, a comprehensive copy number analysis was performed on 260 patients including 136 with de novo AML and 124 with myeloid neoplasms with myelodysplasia, all of whom were studied by WES. A total of 755 CNAs (502 deletions and 253 amplifications) were identified, where 52% of the patients harbored at least one alteration. Using GISTIC 2.0 algorism, we identified 21 significantly altered regions involving known or putative driver genes (Figure 1): losses of 7q22.1 (CUX1), 12p13.2 (ETV6), 13q14 (RB1),17p13.1(TP53), and 17q11.2 (NF1), and gains of 3q26-27 (EVI1), 8q24.21 (MYC), 11q13.5-14.1(PAK1), 11q23.3 (MLL),11q24-25 (ETS1), 13q12.2 (FLT3),21q22.2 (ETS2 and ERG). We next compared the frequencies of CNAs between de novo AML and myeloid neoplasms with myelodysplasia. While chromosomes 7, 12, and 17 were commonly affected, deletions of 13q14 were significantly enriched in myeloid neoplasms with myelodysplasia (Odds ratio [OR]: 5.07, P = 0.040), and amplifications of 11q24-25 (OR: 5.54, P = 0.028), and 21q22.2 (OR: 6.10, P = 0.020) in de novo AML, suggesting a specific role of these events in each disease entity. In addition, serial sampling revealed trisomy8, deletions of 7q and 12p were recurrently acquired during leukemic transformation in patients withmyelodysplasia. Taken together, many driver genes in myeloid neoplasms were frequently targeted by CNAs includingmicrodeletions. Based on these finding, we sought to obtain a more detailed landscape of CNAs in a larger cohort. We combined copy number profiles of patients studied by targeted deep sequencing and those by WES. Of total, 1,691 CNAs (1,096 deletions and 595 amplifications) were detected, where 39% of the cases harbored at least one alteration. Microdeletionsor focal amplifications were frequently found in the significantly altered regions revealed by WES: microdeletionsof ETV6 (n = 10), NF1 (n = 8), CUX1 (n = 5), TP53 (n = 5), and amplifications of FLT3 (n = 7), ETS1 (n = 3), ETS2 (n = 3), and ERG (n = 3), validating the result obtained from a cohort studied by WES. We also identified known driver genes in myeloid neoplasms were recurrently affected with focal CNAs: microdeletions of RUNX1, BCOR, ASXL2, DNMT3A, and ZRSR2, and amplifications of GNAS, RIT1, CSF3R, and BCL11A. Among them, DNMT3A and ASXL2, located within 500 kb in chromosome 2, tended to be co-deleted (3 out of 4 cases). Focal deletions of TP53 were often affected with homozygous deletions or were accompanied by gene mutations, implying bi-allelic inactivation. High amplifications were also observed in regions including ETS1, MLL, FLT3, MYC, and PAK1, which suggest a critical role in the pathogenesis of myeloid malignancy. Conclusion We obtained the landscape of CNAs in myeloid neoplasms based on the sequencing data of 1,185 patients. Collectively, our results indicated that CNAs targeted a specific set genes including well-known drivers of myeloid malignancies, indicating a critical role inleukemogenesis. Disclosures Kanda: Otsuka Pharmaceutical: Honoraria, Research Funding. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium/Takeda: Membership on an entity's Board of Directors or advisory committees. Makishima:The Yasuda Medical Foundation: Research Funding. Maciejewski:Celgene: Consultancy, Honoraria, Speakers Bureau; Alexion Pharmaceuticals Inc: Consultancy, Honoraria, Speakers Bureau; Apellis Pharmaceuticals Inc: Membership on an entity's Board of Directors or advisory committees. Ogawa:Takeda Pharmaceuticals: Consultancy, Research Funding; Kan research institute: Consultancy, Research Funding; Sumitomo Dainippon Pharma: Research Funding.

Abstract: Abstract 458 MDS and related disorders comprise a group of myeloid neoplasms characterized by deregulated blood cell production and a predisposition to AML. Although currently, a number of gene alterations have been implicated in the pathogenesis of MDS, they do not fully explain the pathogenesis of MDS, because many of them are also found in other myeloid malignancies and roughly 20% of MDS cases have no known genetic changes. So, in order to clarify a complete registry of gene mutations in MDS and identify those discriminate MDS from other myeloid neoplasms, we performed whole-exome sequencing of 29 cases showing myelodysplasia. A total of 268 somatic mutations or 9.2 mutations per sample were identified. Among these 41 occurred in recurrent gene targets, which not only included a spectrum of known gene targets in MDS, such as TET2, EZH2, NRAS/KRAS, RUNX1, TP53 and DNMT3A, but also affected previously unknown genes that are commonly mapped to the RNA splicing pathway, including U2AF35, SRSF2 and ZRSR2. Together with additional three (SF3A1, SF3B1 and PRPF40B) found in single cases, 16 (55.2%) of the 29 discovery cases carried a mutation affecting the component of the splicing machinery. To confirm the observation, we examined 9 spliceosome genes for mutations in a large set of myeloid neoplasms (N=582) using a high-throughput mutation screen of pooled DNA followed by confirmation/identification of candidate mutations. In total, 219 mutations were identified in 209 out of the 582 specimens of myeloid neoplasms. Mutations of the splicing machinery were highly specific to diseases showing myelodysplastic features, including 19 of 23 (83%) cases with RARS, 43 of 50 (86%) RCMD-RS, 68 of 155 (44%) other MDS, 48 of 88 (55%) CMML, and 16 of 62 (26%) secondary AML with MDS features with a string preference of SF3B1 mutations to RARS and RCMD-RS and of SRSF2 to CMML, while they were rare in cases with de novo AML (N=151) and MPD (N=53). The mutations among 4 genes, U2AF35 (N = 37), SRSF2 (N = 56), SF3B1 (N = 79) and ZRSR2 (N = 23), explained most of the mutations with a much lower mutational rate for SF3A1 (N = 8), PRPF40B (N = 7), U2AF65 (N = 4) and SF1 (N = 5). Interestingly, mutations in the former three genes showed clear hot spots, indicating a gain-of-function nature of these mutations. On the other hand, two thirds of the ZRSR2 mutations are nonsense or frameshift changes causing premature truncation of the protein. Significantly, these mutations occurred in an almost completely mutually exclusive manner among mutated cases, and commonly affected those components of the splicing complex that are engaged in the 3' splice site recognition during RNA splicing, strongly indicating production of unspliced or aberrantly spliced RNA species are incriminated for the pathogenesis of MDS. In fact, when transduced into HeLa cells, the recurrent S34F U2AF35 mutant induced the increase in the production of unspliced RNA species and elicited the activation of the nonsense mediated decay pathway. Functionally, the U2AF35 mutants seemed to cause deregulated stem cell functions, because CD34(−) KSL cells transduced with various U2AF35 mutants invariably showed reduced chimerism in competitive reconstitution assay. In accordance with this, the S34F U2AF35 mutant lead to suppression of cell growth in a variety of cell types, including HeLa cells, in which expression of the mutant induced a G2/M cell cycle arrest and increased apoptosis. In conclusion, whole-exome sequencing unexpectedly revealed the high frequency of the splicing pathway mutations in MDS and related myeloid neoplasms, providing the first evidence indicating that compromised RNA splicing by gene mutations are responsible for human pathogenesis. Disclosures: Haferlach: MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

Abstract: Abstract 782 Recent genetic studies have revealed a number of novel gene mutations in myeloid malignancies, unmasking an unexpected role of deregulated histone modification and DNA methylation in both acute and chronic myeloid neoplasms. However, our knowledge about the spectrum of gene mutations in myeloid neoplasms is still incomplete. In the previous study, we analyzed 29 paired tumor-normal samples with chronic myeloid neoplasms with myelodysplastic features using whole exome sequencing (Yoshida et al., Nature 2011). Although the major discovery was frequent spliceosome mutations tightly associated with myelodysplasia phenotypes, hundreds of unreported gene mutations were also identified, among which we identified recurrent mutations involving STAG2, a core cohesin component, and also two other cohesin components, including STAG1 and PDS5B. Cohesin is a multimeric protein complex conserved across species and is composed of four core subunits, i.e., SMC1, SMC3, RAD21 and STAG proteins, together with several regulatory proteins. Forming a ring-like structure, cohesin is engaged in cohesion of sister chromatids in mitosis, post-replicative DNA repair and regulation of gene expression. To investigate a possible role of cohesin mutations in myeloid leukemogenesis, an additional 534 primary specimens of various myeloid neoplasms was examined for mutations in a total of 9 components of the cohesin and related complexes, using high-throughput sequencing. Copy number alterations in cohesin loci were also interrogated by SNP arrays. In total, 58 mutations and 19 deletions were confirmed by Sanger sequencing in 73 out of 563 primary myeloid neoplasms (13%). Mutations/deletions were found in a variety of myeloid neoplasms, including AML (22/131), CMML (15/86), MDS (26/205) and CML (8/65), with much lower mutation frequencies in MPN (2/76), largely in a mutually exclusive manner. In MDS, mutations were more frequent in RCMD and RAEB (19.5%) but rare in RA, RARS, RCMD-RS and 5q- syndrome (3.4%). Cohesin mutations were significantly associated with poor prognosis in CMML, but not in MDS cases. Cohesin mutations frequently coexisted with other common mutations in myeloid neoplasms, significantly associated with spliceosome mutations. Deep sequencing of these mutant alleles was performed in 19 cases with cohesin mutations. Majority of the cohesin mutations (16/19) existed in the major tumor populations, indicating their early origin during leukemogenesis. Next, we investigated a possible impact of mutations on cohesin functions, where 17 myeloid leukemia cell lines with or without cohesin mutations were examined for expression of each cohesin component and their chromatin-bound fractions. Interestingly, the chromatin-bound fraction of one or more components of cohesin was substantially reduced in cell lines having mutated or defective cohesin components, suggesting substantial loss of cohesin-bound sites on chromatin. Finally, we examined the effect of forced expression of wild-type cohesin on cell proliferation of cohesin-defective cells. Introduction of the wild-type RAD21 and STAG2 suppressed the cell growth of RAD21- (Kasumi-1 and MOLM13) and STAG2-defective (MOLM13) cell lines, respectively, supporting a leukemogenic role of compromised cohesin functions. Less frequent mutations of cohesin components have been described in other cancers, where impaired cohesion and consequent aneuploidy were implicated in oncogenic action. However, 23 cohesin-mutated cases of our cohort had completely normal karyotypes, suggesting that cohesin-mutated cells were not clonally selected because of aneuploidy. Alternatively, a growing body of evidence suggests that cohesin regulate gene expression, arguing for the possibility that cohesin mutations might participate in leukemogenesis through deregulated gene expression. Of additional note, the number of non-silent mutations determined by our whole exome analysis was significantly higher in 6 cohesin-mutated cases compared to non-mutated cases. Since cohesin also participates in post-replicative DNA repair, this may suggest that compromised cohesin function could induce DNA hypermutability and contribute to leukemogenesis. In conclusion, we report a new class of common genetic targets in myeloid malignancies, the cohesin complex. Our findings highlight a possible role of compromised cohesin functions in myeloid leukemogenesis. Disclosures: Haferlach: MLL Munich Leukemia Laboratory: Equity Ownership. Alpermann:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Equity Ownership.

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.