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Abstract Abstract 709 Background: A recent analysis of merged genome-wide and candidate gene genotypes in VTE cases and controls identified multiple tag SNPs that were strongly associated with VTE. Objective: To identify rare and/or novel functional variants by sequencing the implicated genes. Methods: Cases (n=1488) were Mayo Clinic European-American patients of non-Hispanic ancestry with objectively-diagnosed VTE in the absence of active cancer, venous catheter or antiphospholipid antibodies. Controls (n=1439) were Mayo Clinic outpatients without VTE who were frequency-matched on case age, gender, race, MI/stroke status and state of residence. For this analysis, we selected a subset of these cases and controls for sequencing to take advantage of the joint configuration of two ABO SNPs of primary interest, rs8176719 (ABO exon 6 deletion determining type O blood group) and rs2519093 (ABO intron 1 tag SNP), which were previously shown to be strongly associated with VTE (p=5.7E-12 and p=3.0E-16, respectively). We randomly sampled 82 cases and 14 controls within 3 of the 9 potential allele frequency cells (Figure). The rs8176719 alleles are -−/−- (double deletion is the common allele), –/G, and G/G (the rare allele). The rs2519093 alleles are GG (G is the common allele), AG, and AA (A is the rare allele). For each SNP, the genotypes are represented as 0, 1, or 2 copies of the minor allele. We represented the joint allelic configuration of the two SNPs with the number of copies of the rs8176719 given first as 0/0 (both with 0 copies of the minor allele), 0/1, 0/2 (0 copies of the rs8176719 SNP), 1/0 (1 copy of the rare rs8176719 SNP), 1/1/, and 1/2, and 2/0 (2 copies of the rare allele for the rs8176719 SNP and 0 copies of the rare allele of the rs2519093 SNP), 2/1, and 2/2. From the Figure one observes discrepancies between cases and controls at the 0/0, 1/1 and 2/2 combinations. We randomly sampled from these three combinations, taking one third of the case series. For each SNP, we had 28 cases with 0/0 copies of the rare allele, 27 cases with 1/1 copies of the rare allele; and 27 cases with the combination of 2/2 copies of the rare allele. We compared these 82 cases with 14 controls that do not have any of these combinations. Sixteen genes were selected for deep sequencing, including 5 genes harboring SNPs significantly associated with VTE (F5, SLC19A2, ABO, NME7, ATP1B1), 10 genes with SNPs marginally associated with VTE (C1orf114, KLKB1, SELP, F11, SCUBE1, PRKCB1, CD44, ITPR1, GFRA1, BLZF1), and CYP4V2 which reportedly confounds F11 and KLKB1. Agilent SureSelect probes were designed to capture and enrich the ∼2 Mb genomic regions of these 16 genes. Samples were multiplexed (12-plex) and sequenced using Illumina HiSeq 2000. The sequence reads were aligned to the human genome build 36 using Burrows-Wheeler Aligner, and the single nucleotide variants (SNVs) and small INDELs were called using SNVMix and GATK, respectively. For this analysis, novel ABO SNVs were tested for an association with VTE using age-, sex-adjusted logistic regression and Fisher's Exact Test. Results: 98% of the targeted regions were sequenced with > 20X coverage. On average, ∼2500 SNVs and ∼200 INDELs were detected in each sample. Fifteen novel SNVs in intron 6 and 3' of the ABO gene were associated with VTE (p<E-06) and belonged to 3 distinctive LD blocks; none were in LD with the coding or tag ABO SNPs (rs8176719; rs2519093). SNVs inside the middle LD block at the 3' of ABO are located within an enhancer and promoter histone marked with putative transcription factor binding sites. In addition, strong evidence from both ENCODE and dbEST support the middle LD block as lying within a novel transcript, probably an extension of the 3' of ABO. In addition, we discovered a novel, significant, protective, frame-shifting single base (G) deletion at ABO chr9:135120877. Conclusion: Novel ABO functional variants that are associated with VTE were identified by deep sequencing. Disclosures: Heit: Daiichi Sankyo: Consultancy, Honoraria.

Abstract Abstract 288 BACKGROUND. Chronic lymphocytic leukemia (CLL) patients with mutated IGHV genes (M-CLL) have better outcomes than patients with unmutated IGHV genes (U-CLL). It has been proposed that this difference reflects the fact that IGHV mutations alter the structure of the B-cell antigen receptor (BCR) such that it no longer binds stimulatory (auto) antigens and therefore cannot deliver trophic signals to the leukemic cells. For this theory to be correct, only replacement (R) mutations and in particular non-conservative R mutations that would more likely alter amino structure of the IGHV/D/J rearrangements would have relevance. Silent (S) mutations by definition do not change amino acid structure and could not alter antigen binding. We sought to investigate this hypothesis by analyzing the types (S, conservative R, non-conservative R) and distribution of mutations that occur in IGHVs of M-CLL clones and then comparing the time to first therapy (TTFT) in patients with different IGHV features. This analysis expanded an initial study of 1569 CLL cases in the US to include 1858 patients from Europe for a total of 3427 cases. METHODS. Using IGMT software and tools, we analyzed the rearranged IGHV sequences of 3427 cases and characterized their mutations in several respects: first, if IGHV mutations altered amino acid structure (S vs. R); second, if mutations occurred in CDRs (antigen binding domains) or FRs (scaffolds of the BCR); third, if R mutations were conservative or non-conservative as determined by charge, hydropathy, and size. TTFT for patients was examined with various combinations of the above parameters. Differences in TTFT were estimated by the method of Kaplan and Meier and assessed using the log rank test. RESULTS. First, TTFT was compared for 4 groups of patients with the following mutation profiles: no mutations; only S mutations (median 1 per sample); only R mutations (median 1 per sample); and mixed S and R mutations (median 16 per sample). These 4 categories were significantly different (P<0.0001), with the median TTFT being 2.0 yrs for no mutations; 2.6 yrs for R only; 2.8 yrs for S only; and 7.3 yrs for mixed. All comparisons used patients with no mutations (n=1234) as the reference group. We identified statistically longer TTFT (2.8 vs 2.0 yrs; P=0.04) in patients with only S mutations (n=62). Patients with only R mutations (n=218) also had superior outcomes (2.6 yrs vs. 2.0 yrs; P=0.008). There was no statistical significance in TTFT between patients with all S vs. all R mutations (2.8 yrs vs. 2.6 yrs; P=0.71). Because exploring the relevance of BCR structural change on TTFT required us to focus on a small subset of patients with only silent IGHV mutations, our sample size was small. Therefore, we expanded the group to include IGHVs with R mutations limited to the FR region (S + R in FR only; n=241) since these mutations would be unlikely to have a major impact on BCR structure, particularly sparing the binding site. When compared to patients with no mutations, this group demonstrated a significantly longer TTFT (2.8 yrs vs. 2.0 yrs, P=0.0002). This finding was upheld when not permitting any non-conservative R mutations in this group, leaving only patients with S plus conservative R mutations in FRs only (n=124); TTFT in this case was 2.8 yrs vs. 2.0 yrs, respectively (P=0.0006). CONCLUSIONS. Our findings show that patients with only S mutations have better outcomes than patients with no mutations, suggesting that a change in BCR structure that could lead to a loss of antigen binding is an unlikely reason for improved clinical course. This is further supported by the finding that the combination of only S plus conservative R mutations located solely in FRs, which probably would not result in major BCR structural changes and therefore antigen binding, is associated with a lengthened TTFT. Therefore, we suggest that the currently accepted paradigm to explain the enhanced survival of M-CLL patients needs to be re-evaluated. Disclosures: Brown: Calistoga: Consultancy, Research Funding; Celgene: Honoraria, Research Funding; Genzyme: Research Funding; GSK: Research Funding. Kipps:Igenica: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Research Funding; Abbott Industries: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; GSK: Research Funding; Gilead Sciences: Consultancy, Research Funding; Amgen: Research Funding.

Abstract Abstract 1242 Background: While bivariate interactions between Factor V Leiden, prothrombin G20201A and hereditary deficiency of antithrombin, protein C and protein S compound VTE risk, whether other gene-gene interactions are associated with VTE is largely unknown. Objective: To test novel gene-gene interactions for an association with VTE. Methods: Genome-wide scan (Illumina 660Q [557,112 SNPs]) and candidate gene (12,551 SNPs in 764 genes within the anticoagulant, procoagulant, fibrinolytic and innate immunity pathways) genotypes from 1270 non-Hispanic adults of European ancestry with objectively-diagnosed VTE (cases; no cancer, venous catheter or antiphospholipid antibodies) and 1302 controls (frequency-matched on case age, gender, race, MI/stroke status) were merged and imputed to about 2.5 million SNPs with MACH using HapMap Phase 2 (60 CEU). We tested all pairwise SNP-SNP interactions using a 2-stage procedure (fast epistasis in the first stage and age, gender, MI/stroke status and state of residence adjusted analysis using logistic regression in the second stage). Results: The mean ± standard deviation case and control ages were 54.4 ± 16.2 and 55.6 ± 15.8 years, respectively and 51% were female. Among 2.299×10^12 pairwise interactions tested, 900 million reached a p-value<E-06 and were be tested in the second stage. Of these, 2417, 278 and 22 SNP-SNP interactions reached p-values ≤1E-9, 1E–10, and1E-11 respectively; 121 SNP-SNP interactions reached the Bonferroni statistical significance threshold (≤5.555659E-11). The gene-gene pairwise interactions with p-values≤1E-11 were: (1) chromosome 3 open reading frame 70 (C3orf70) – short-chain dehydrogenase/reductase (SDR family) member 4 (DHRS4), (2) 1-acylglycerol-3-phosphate O-acyltransferase 4 (AGPAT4) - NIMA (never in mitosis gene a)-related kinase 6 (NEK6), and (3) TatD DNase domain containing 2 (TATDN2) – WAS protein family, member 3 (WASF3). No gene function data are available for C3orf70. DHRS4 encodes for a 3-ketosteroid reductase important for active steroid hormone regulation, AGPAT4 is important for signal transduction and lipid biosynthesis, NEK6 encodes for Nek6 which downregulates p53-induced cancer cell senescence, TATDN2 encodes a deoxyribonuclease, WASF3 encodes for a member of the Wiskott-Aldrich syndrome protein family which are key regulators of signal transduction and cytoskeletal reorganization in hematopoietic cells. Conclusion: Pairwise gene-gene interaction analyses suggest potential associations between VTE and novel genes for future testing in replication studies. Disclosures: Heit: Daiichi Sankyo: Consultancy, Honoraria.

Abstract Background Relatively few studies have evaluated the role of host (germline) genetics in predicting outcome in diffuse large B-cell lymphoma (DLBCL), and of these, most were small candidate gene studies without replication and/or from the pre-R-CHOP era. We report the first genome-wide association study (GWAS) of outcome in DLBCL patients treated with rituximab and anthracycline-based chemotherapy. We used two independent studies for discovery, and validated the results in two additional independent studies. Methods In the discovery phase, we conducted a meta-analysis of two GWAS studies of DLBCL patients treated with rituximab and anthracycline-based chemotherapy, the first study as part of the prospective clinical trials of the LNH2003B program (N=540) of the Lymphoma Study Association (LYSA) and the second as part of the Molecular Epidemiology Resource (N=316), a prospective observational study from the University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). Genotyping for the GWAS was performed using the Illumina 610 (LYSA) and 660 Quad (SPORE) BeadArrays (Illumina, San Diego, USA). HapMap2 was used to impute additional SNPs. Association testing was conducted assuming a log-additive genetic model and using Cox regression analyses. We calculated the hazard ratios (HRs) and 95% CIs for event-free survival (EFS), with adjustment for age, sex and age-adjusted IPI. The two studies were then combined using the fixed effects inverse variance method based on the beta estimates and standard errors from each study. From the meta-analysis, 89 SNPs were selected for validation, based on a minor allele frequency (MAF) >0.05 and LD pattern for multiple SNPs from the same region. Validation cohorts were an independent set of DLBCL patients from the SPORE (SPORE-2, N=366) and DLBCL patients from the prospective GOELAMS 075 phase III study (N=294), and validation genotyping was conducted using the Illumina VeraCode platform. We then conducted a meta-analysis of the 4 studies. We report SNPs with both a statistical significance of p<5x10-6 and effect sizes in the same direction across the 4 studies in the meta-analysis. For the latter SNPs, we also report the results for overall survival (OS), adjusted for age, sex and age-adjusted IPI. Results In the final meta-analysis of all four studies for the prediction of EFS, the top SNP was rs7765004 (MAF=0.30; HR=1.45; p=9.7 x 10-8) in the 6q21 region, which is near the MARCKS (myristoylated alanine-rich protein kinase C substrate) and HDAC2 genes. MARCKS encodes for a protein involved in cell mobility, while HDAC2 belongs to the histone deacetylase family. Additional SNPs from this region included rs6918103 (MAF=0.25; HR=1.38; p=7.6 x 10-6), which marks an EZH2 histone binding site, and rs11969684 (MAF=0.12; HR=1.43; p=3.3 x 10-5). The next hit was rs7712513 (MAF=0.31; HR=1.40; p=3.2 x 10-7), which is near arginine-fifty homeobox pseudogene 1 (ARGFXP1) on chromosome 5q23.2. This was followed by a region on chromosome 8q13.3, with the SNP rs9298183 (MAF=0.29; HR=1.41; p=1.4 x 10-6) from LOC100132891 showing the strongest association, along with 3 other SNPs from this region (rs2035376, rs6472637, and rs1600797; all p<5 x 10-6). These SNPs are near the musculin gene (MSC) a transcriptional repressor of E2A frequently silenced by promoter methylation in DLBCL. Finally, rs2253986 (MAF=0.27; HR=1.39; p=3.4 x 10-6) at chromosome 16q12.2, along with rs2253971 and rs6499810, were associated with EFS. These SNPs are located in CES5A (carboxylesterase 5A), which encodes a member of the carboxylesterase family. The family members are responsible for the hydrolysis or transesterification of various xenobiotics. The top SNPs associated with EFS also predicted OS, including rs7765004 (HR=1.41; p=1.2 x 10-5), rs7712513 (HR=1.39; p=8.4 x 10-6), rs9298183 (HR=1.36; p=3.5 x 10-5), and rs2253986 (HR=1.35; p=5.2 x 10-5). Conclusions Although our top SNPs on did not reach genome-wide significance (p<5x10-8), they showed clear consistency across the four large prospective studies and predicted both EFS and OS independently of IPI. The strongest findings were from loci on 6q21, 8q13.3, 5q23.2, and 16q12.2, and several genes from these regions are involved in methylation and xenobiotic metabolism, supporting a role for host genetic variation in these pathways in DLBCL prognosis. Disclosures: No relevant conflicts of interest to declare.

Abstract Background:Recurrent mutations in ATM, JAK1/3 and STAT5B genes have been identified in T-cell prolymphocytic leukemia (T-PLL), a mature T cell leukemia with poor survival. However, much remains to be understood regarding the dysregulated pathways involved in the pathogenesis of this aggressive disease. Here, we integrated the analyses of whole exome sequencing (WES) and transcriptomes of a cohort of 12 T-PLL samples to gain further insights into molecular mechanisms of this malignancy. Methods: Leukemic cells were isolated from peripheral blood or bone marrow samples of T-PLL patients. Tumor DNA and RNA, and germline DNA were extracted from purified leukemic T cells and bone marrow derived stromal cells, respectively. WES (n=12) and transcriptome analysis (n=10) were performed and data analyzed with published standard methods (Robinson et al. 2010 and DePristo et al. 2011) Results: 7 paired tumor and germline DNA and 5 tumor-only DNA samples were used for WES analysis. Mutations in ATM and TET2 were detected in 4 (33%) and 1 (8%) patients, respectively. JAK3 (p.M511I, p.Q501H and p.Q503H) or STAT5B (2 p.T628S and 1 p.N642H) mutations each occurred in 3 (25%) cases and were mutually exclusive, consistent with prior reports. Importantly, we found several novel mutations in genes with regulatory roles in the NOTCH signaling pathway. Specifically, 2 somatic mutations p.A3V and p.A3S in NOTCH2 and 2 other mutations (p.S244L and p.A1414V) in NOTCH4 were identified in 4 (33%) patients. One mutation was in the EGF- like and another one in the NODP domain critical for NOTCH-mediated cellular differentiation. Two (16.7%) novel missense mutations (p.G174D and p.V836I) were found in MAML2. Three missense mutations (2 p.S583N and 1 p.R190H) occurred in MAML1. Both MAML2 and MAML1 are essential cofactors of the NOTCH signaling pathway. In addition, a somatic mutation in the NOTCH signal regulator DTX2 (p.G268D) was detected. Altogether 7 (58.3%) patients harbored mutations in genes with a regulatory role in the NOTCH pathway. Among the epigenetic modifiers, we found deletions and point mutations in KDM6B and KDM6A in 4 (30%) patients including 2 codon deletions in KDM6B (p.X751Val) and 1 missense mutation each in KDM6B (p.R1016Q) and KDM6A (p.V510G). KDM6A and KDM6B are histone H3 lysine 27 demethylases known to be involved in regulation of DNA repair and play an important role in embryonic differentiation. Transcriptome analyses of 10 T-PLL cases versus normal CD3+ T cells from 5 healthy donors revealed 706 up-regulated and 655 down-regulated genes. Consistent with prior data, TCL1A and TCL1B were significantly overexpressed (23.7 and 13.1 fold, respectively). Using Ingenuity Pathway Analysis, we found PTEN Signaling, glutamate receptor, and axonal guidance signaling to be among the top 3 upregulated pathways. The top upstream regulators implicated for the up-regulated signals were FGF, Wnt/β-catenin and TNF. The top 3 down-regulated pathways were granulocyte adhesion and diapedesis, IL-17A in psoriasis and IL-10 signaling. The top regulators for the down-regulated pathways were LPS, TNF and IFNg. Wnt/β-catenin and Human embryonic stem cell pluripotency signaling were among the top 20 up-regulated pathways. Many genes involved in the regulation of Wnt signal pathway were included in the above pathways, including Wnt ligands (Wnt9A, Wnt4), transmembrane receptors (CDH1, LRP5, FZD6, FZD7, SMO), cytoplasmic factor (AXIN2), and nuclear factors (MYC, SOX12, SOX8, SOX18, CCND1). Summary: Our study identified recurrent mutations in the NOTCH signaling pathway as well as dysregulated embryonic developmental pathway, e.g. Wnt/NOTCH as newly implicated molecular mechanisms in T-PLL pathogenesis for further functional studies. Additionally, novel (KDM6A and KDM6B) and known mutations (ATM, TET2) in chromatin regulatory genes underscore the importance of epigenetic dysregulation in the tumorigenesis of T-PLL. Disclosures Parikh: Pharmacyclics: Honoraria, Research Funding. Mustjoki:Ariad: Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Ding:Merck: Research Funding.

Abstract Gene expression profiling has shown that diffuse large B-cell lymphoma (DLBCL) clusters into three major subtypes based on similarity in expression patterns to their cell of origin (COO): germinal center B-cell-like (GCB-DLBCL), activated B-cell-like DLBCL (ABC-DBLCL) and primary mediastinal B-cell lymphoma (PMBCL). These subtypes of DLBCLs are associated with distinctly different overall survival rates after standard immunochemotherapy. However, clinical and prognostic heterogeneity remains within COO subsets and strategies are needed to further stratify patients to identify and target high-risk subsets. A comprehensive genomic analysis of COO on a clinically defined set of DLBCL cases has not been performed and the aim of this study was to use whole-exome sequencing (WES) data from 58 paired tumor-normal DLBCL samples to assess association of known DLBCL genomic alterations with cell COO as well as for identification of novel and relevant genetic biomarkers. To investigate genomic alterations associated with DLBCL subsets, we analyzed WES and genome wide copy number data from 58 paired tumor-normal DLBCL tumors. Gene expression profiling or Hans classification was performed to determine DLBCL COO subtype; 31 patients were classified as GCB and 27 as non-GCB. The WES data were used to 1) assess the association of known DLBCL genomic alterations with COO, and 2) identify novel alternations associated with COO. Statistical analysis was performed and the data were ranked by significance (p≤ 0.05) within each DLBCL subtype. In total, 45 genomic abnormalities were analyzed for their association with either GCB, non-GCB or both. Mutations in CREBBP, EZH2, MEF2B, FOXO1 and REL have also been reported as GCB driver mutations and we observed GCB patients with these mutations, but the mutation clustering was not wholly associated with GCB. MYC double-hits were exclusively found in the GCB-subtype group. For the non-GCB cases we found that mutations in MAP2K3 and MYD88 were significantly associated with this subtype(p< 0.05). In addition to mutational patterns, we identified several copy number alterations (CNA) across both groups. Chromosomal losses in GCB patients were found at chromosomes 10q11.21-10q24.23, 4q12-4q35.2, 3q12.1-3q29, 4p12-4p16.3, 10p11.21-10p15.3, and 14q11.2-14q24.3 whereas gains were localized to 7q11.1-7q36.3, 7p11.2-7p22.3, and 1q21-1q32.1 (p < 0.05). No CNA was observed to directly associate with non-GCB patients, however, a loss at 9p21 and gains at 9q24.1 and 18q21.33 trended with the non-GCB subtype, supporting previous reports. Loss at 10q23.31 or a gain in 2p13-2p12 have been reported as being specific for GCB and our data confirmed the association of 10q23.31 with GCB while a gain at 2p13-2p12 (REL)was found in both subtypes. To further understand genomic differences between DLBCL subtypes, we evaluated the relative percentage of each genomic feature. 18/45 (40%) were only observed in GCB patients whereas 2/45 (5%) were specific to the non-GCB subtype. The majority (25/45, 55%) overlapped between the two subtypes. Throughout our analysis we noted that 7 non-GCB cases lacked any of the driver mutations analyzed in the study. While all cases carried mutations, they consisted of low frequency mutations that were not specifically associated with COO. 2/7 cases had a gain at 9p24.1 that included CD274 and JAK2. Because 9p24.1 gains have not been fully defined in DLBCL, we reviewed all cases and identified 4 (7%) with a 9p24.1 gain, 3 of which were non-GCB and 1 GCB. One non-GCB case was EBV+ and none of the cases showed evidence of PMBCL. Of the 9p24.1 cases, three had RNAseq data available and we found that PDL1 and JAK2 expression was elevated (12 fold p< 0.01 and 7 fold p< 0.01, respectively) when compared to the 9p24.1 normal cases (n=32). While outcome was not the focus of the study, we did note that 6/7 cases that lacked driver mutations achieved event free survival at 24 months (EFS24). Taken together, this analysis has further characterized the genetic profile of each COO subtype and has identified novel GCB CNAs which require independent replication. Additionally, we identify a subgroup of non-GCB DLBCL patients that do not harbor known driver mutations and require further genomic study to better resolve the biology of these tumors. Together, these data provide insight on the genetic heterogeneity of DLBCL and identify genetic variants that may inform subtype specific therapy. Disclosures Nowakowski: Morphosys: Research Funding; Celgene: Research Funding; Bayer: Consultancy, Research Funding. Rimsza:NCI/NIH: Patents & Royalties: L.M. Rimsza is a co-inventor on a provisional patent, owned by the NCI of the NIH, using Nanostring technology for determining cell of origin in DLBCL..

Abstract Abstract 2295 Background: While interaction between Factor V Leiden and other VTE risk exposures compound VTE risk, whether other gene-environment interactions are associated with VTE is largely unknown. Objective: To test novel gene-environment interactions for an association with VTE. Methods: Genome-wide scan (Illumina 660Q [557,112 SNPs]) and candidate gene (12,551 SNPs in 764 genes within the anticoagulant, procoagulant, fibrinolytic and innate immunity pathways) genotypes from 1270 non-Hispanic adults of European ancestry with objectively-diagnosed VTE (cases; no cancer, venous catheter or antiphospholipid antibodies) and 1302 controls (frequency-matched on case age, gender, race, MI/stroke status) were merged and imputed to 2.5 million SNPs with MACH using HapMap Phase 2 (60 CEU). We tested pairwise interactions between these SNPS and each of 7 exposures (“stress” [defined as ever hospitalized, ever surgery, ever trauma, ever transfemoral procedure or ever leg paresis], ever surgery, ever neurosurgery, ever orthopedic surgery; and among women, ever pregnant, ≥3 pregnancies and ever oral contraceptives/hormone therapy), adjusted for age, gender, MI/stroke status and state of residence, using logistic regression. Results: The mean ± standard deviation case and control ages were 54.4 ± 16.2 and 55.6 ± 15.8 years, respectively and 51% were female. Among the 7 models, a significant interaction was found between stress and A2BP1 (rs735919, OR=0.2, p=2.8E-07), ever surgery and ABCG8 (rs6709904, OR=0.27, p=2.1E-07), orthopedic surgery and SLC24A3 (rs6081599, OR=0.53, p=2.8E-07), neurosurgery and TBC1D4 (rs17064485, OR=8.5, p=3.5E-07), every pregnant and MICALCL (rs11022321, OR=0.17, p=8.3E-07), >3 pregnancies and KLRB1 (rs2536929, OR=0.31, p=1.1E-07) and ever oral contraceptives/hormone therapy and LINGO2 (rs10969259, OR=2.02, p=4.9E-07). A2BP1 plays a role in RBC shape and size, ABCG8 is associated with severe hypercholesterolemia, SLC24A3 is important for intracellular calcium homeostasis, TBC1D4 participates in cell signaling in CD4+/CD45RO+ memory T-cells, MICALCL is an extracellular signal-regulated kinase 2-binding protein, KLRB1 regulates natural killer cell function, and LINGO2 encodes a leucine-rich repeat signaling protein. Our observed interaction of VTE risk factors with these genes to compound the risk of VTE requires replication in future studies. If confirmed, functional studies will be important to determine the roles of these gene products in the causal pathway to VTE. Conclusion: VTE risk factors and SNPs within several novel genes may interact to compound the risk of VTE. Disclosures: Heit: Daiichi Sankyo: Consultancy, Honoraria.

Abstract Abstract 1814 Multiple myeloma (MM) is an incurable hematologic disorder characterized by the accumulation of plasma cells (PCs) in the bone marrow (BM). Like normal B cells and PCs, MM cells express a distinctive immunoglobulin (Ig) molecular fingerprint resulting from heavy and light chain gene rearrangements and unique mutations introduced by the somatic hypermutation (SHM) process. Detailed examination of the Ig molecule may offer insight into the etiology of B cell malignancies as well as the ontogeny of malignant transformation and ongoing genetic evolution. Because prior studies of the Ig fingerprint of MM cells have been limited in size and scope, our current understanding of MM Ig repertoire is minimal. We used massively parallel sequencing of normal and malignant PCs to interrogate: 1) DNA versus RNA (cDNA) as starting material for studies of Ig repertoire; 2) the Ig repertoire of normal and malignant PCs; and 3) intraclonal heterogeneity in MM. Bone marrow PCs (BMPCs) from an untreated MM patient and from a normal control subject were isolated by magnetic bead separation. DNA and RNA were isolated from purified cells and amplified in a multiplex PCR reaction with primers designed to capture the entire IGHV region including the heavy chain complementarity determining region 3 (HCDR3) necessary for defining clonal cells. Using Roche 454 GS-FLX Titanium chemistry and a GS FLX Titanium Genome Sequencer, over 30,000 sequence reads were obtained from each sample. Following a detailed algorithm to minimize Taq and sequencing related errors and removal of non-Ig or non-productive Ig sequences, the resulting sequences were grouped based on HCDR3 amino acid identity. Each unique HCDR3 represented one member of the repertoire and all the sequences with the same HCDR3 defined the clone size. This measurement showed that there was nearly a five-fold higher level of unique HCDR3s in normal BMPCs when the starting PCR template was DNA vs. cDNA. Thus, DNA is clearly a better starting template for repertoire analysis using deep sequencing methods. Thorough analysis of the MM DNA sample identified PCs expressing 37 different IGHV genes, and predictably, the vast majority of sequence reads (83%) had exact nucleotide identity in the IGHV and HCDR3 region (IGHV3-74 with 18 mutations in the IGHV region) thereby defining the dominant MM clone. There were also ∼5000 additional sequences that either shared an identical HCDR3 region but varied within the IGHV3-74 gene sequence (n=3975) or were identical within the IGHV3-74 sequence yet varied within the HCDR3 (n=862). These sequences were further analyzed, with sequences not present 10 or more times or not found in both the 5' and 3' directions eliminated from further scrutiny. This process revealed a total of 64 putative subclones with single point mutations in the IGHV or HCDR3 region (10–56 copies of each unique sequence representing a total of 1583 clonally related sequences). When we used a more stringent subclone frequency of ≥0.1%, 22 subclones remained. Of note, conventional Ig repertoire analysis would require sequencing ≥1000 colonies to detect MM subclones present at this frequency. Finally, 11 subclones displayed a significant number of IGHV gene nucleotide differences from the dominant MM clone despite exhibiting an identical HCDR3 region. Notably, a number of these distinguishing IGHV gene mutations are silent and thus may preserve the antigenic specificity of these clonally related cells. These subclones failed our frequency criteria but the type and quality of deviations from the clonal sequence suggest that they are not artifact and warrant further investigation. Notably, all of the putative subclones were also found in the MM cDNA cohort providing further evidence as genuine subclones. The very large number of identical MM clonal sequences is consistent with the idea that MM is a post germinal center malignancy that can no longer undergo SHM. However, we present clear evidence of MM-related subclones albeit relatively small in number. The subclone sequence deviations discovered may reflect on-going genetic evolution independent of the formal SHM mechanism. Alternatively, these subclones may indeed reflect “sister” cells generated during the original germinal center reaction that resulted in the malignant clone. In summary, our studies demonstrate the extraordinary potential of this methodology to track clonal evolution in MM and its precursor conditions over time. Disclosures: No relevant conflicts of interest to declare.

Abstract While extensive, the genetic studies of DLBCL tumors to date have primarily focused on somatic mutations that are associated with development of lymphoma, i.e., driver mutations. Identification of key genetic events that impact and/or predict response to therapy and clinical outcome of lymphoma patients has not been accomplished. In an exploratory study, we used whole-exome sequencing to identify novel biomarkers that can predict which patients have an aggressive form of DLBCL, and therefore would likely benefit from a different and more aggressive treatment plan. Using whole-exome sequencing data from 54 newly diagnosed DLBCL patients, we evaluated the association of somatic coding single nucleotide (cSNV) and copy number (CNV) variants with aggressive DLBCL. All patients were treated with R-CHOP or immunochemotherapy, and disease aggressiveness was based on relapse, with patients classified as having aggressive disease (AD) (n=13, defined as treatment failure, relapse, or progression within 24 months of diagnosis) versus non-aggressive disease (n=41, defined as achieving at least 24 months of relapse-free survival). An in-house algorithm, patternCNV was used to detect somatic CNVs. Logistic regression was used to assess statistical significance. In the cSNV analysis, 24 genes were found to be significantly (p ≤ 0.05) associated with AD. Of these genes, CIITA (p=0.01) was previously identified as a mutational target in DLBCL and is a recurrent gene fusion partner in lymphoid cancers. Metacore analyses showed that seven of these genes, including CIITA, can be placed in the same regulatory network centered around CREB1. Interestingly, the CREB binding protein (CREBBP) is a known target of pathogenic mutations in DLBCL. In the CNV analyses, we identified 245 gene amplifications and 209 gene deletions associated with AD (p ≤ 0.05). Deleted genes were localized in three major chromosomal regions, 6p22.3-6p22.1 (26 genes), 6q13-6q16.3 (31 genes), and 6q21-6q24.2 (86 genes). In the CNV amplification analysis, the genes were localized in two major chromosomal regions, 3q12.3-3q29 (90 genes) and 19q13.12-19q13.43 (122 genes). We also quantified the association of each regional deletion/amplification with patient outcome. As expected, each deleted region was univariately associated with time to relapse: 6p22.3-6p22.1 (HR = 7.19, 95% CI: 2.66-19.46, p=1.33x10-5), 6q13-6q16.3 (HR = 4.44, 95% CI: 1.74-11.32, p=6.84x10-4), and 6q21-6q24.2 (HR = 5.42, 95% CI: 2.12-13.87, p=9.23x10-5) as well as the two amplification regions: 3q12.3-3q29 (HR = 4.60, 95% CI: 1.49-14.24, p=4.27x10-3) and 19q13.12 -19q13 (HR = 13.79, 95% CI: 4.39-43.34, p=2.81x10-8). Deletions at 6q21-6q24.2 have been previously reported in DLBCL and two tumor suppressor genes associated with lymphoma pathogenesis are localized in the region, TNFAIP3 (p=0.14) and PRDM1 (p=0.02), the latter of which was significantly associated with AD. However, the genes in the 6p21 locus that were most significant (p=0.002) were SLC22A16, GPR6, SOBP, MATTL24, DDO, and REV3L. SLC22A16, which also had cSNVs in two tumors, is an organic cation transporter that has been shown to transport chemotherapeutic drugs including doxorubicin. Successful drug response has been correlated with the level of activity and expression of this transporter in tumor cells. To determine if expression of SLC22A16 would have an impact on doxorubicin transport, and may therefore impact response to R-CHOP we overexpressed either an empty vector control or SLC22A16 in OCI-Ly7 DLBCL cells, which do not express endogenous SLC22A16 mRNA. We found that OCI-Ly7 cells expressing SLC22A16 have increased 14C-doxorubicin uptake and are more sensitive to doxorubicin-induced cell death when compared to the empty vector control cells. These data suggest that loss of SLC22A16 expression through gene deletion could impact the ability of DLBCL cells to respond to therapy and indicates an aggressive form of the disease. In summary, our data are the first to use whole exome sequencing to identify genetic variants associated with aggressive DLBCL, which will require replication in additional samples. Nevertheless, our data highlight the role for somatic CNVs in patient outcome and we biologically validate the potential impact of deletions in SLC22A16 at 6p21. Disclosures: No relevant conflicts of interest to declare.

Abstract Both genome wide association studies (GWAS) of common variation and exome wide association studies (EXWAS) of rare variation have successfully identified disease susceptibility variants for a variety of diseases. One GWAS of inherited susceptibility to Acute Myeloid Leukemia (AML) has been conducted, but no EXWAS have been performed to measure risk of AML attributable to low-frequency constitutional genetic variation. We performed the first EXWAS of risk of AML as a nested case-control study in the DISCOVeRY-BMT (Determining the Influence of Susceptibility Conveying Variants Related to one-Year mortality after BMT) cohorts. The DISCOVeRY-BMT parent study examined transplant-related mortality in leukemia patients undergoing unrelated donor allogeneic BMT. To identify low frequency variants and genes contributing to increased susceptibility to AML we used genotype data from the Illumina HumanExome BeadChip typed in the DISCOVeRY-BMT cohorts; the HumanExome BeadChip contains 242,901 variants, which are mainly protein-coding variants. The optimal sequence kernel association test (SKAT-O) was used to analyze gene-level associations with risk of AML. These gene-based tests evaluate the cumulative effects of multiple single gene variants on risk of AML. Analyses were performed in all European American AML cases and two subtypes: 1) de novo AML, 2) de novo AML with normal cytogenetics. Models were adjusted for age at transplant and principal components to control for population stratification. For gene-based tests at least 2 variants with minor allele frequency (MAF) ≤ 5%, were required to be present in the gene. This yielded a total of 13,687 genes tested, and a Bonferroni corrected significance level of P<3.65 x 10-6. Association tests were performed in 1,189 AML cases reported to CIBMTR 2000-08 (Cohort 1) and 327 AML cases reported to CIBMTR from 2009-11 (Cohort 2). Controls in Cohorts 1 (n=1,986) and 2 (n= 515) were 10/10 HLA-matched unrelated donors who passed a comprehensive medical exam and deemed healthy. We used metaSKAT to combine Cohorts 1 and 2 and obtain p-values of association with AML. We present the results of gene-level tests significant in both cohorts. The likely pathogenicity of these variants was determined in silico using SIFT, PolyPhen and MutationTaster. Patient characteristics are in Table 1. DNMT3A, on chromosome 2, was associated in the gene-based test with risk of AML (Pmeta=1.70x10-9, Table 2). Three missense variants at MAF <1% comprise both overall AML and de novo AML gene-based association: exm177559 (Asn->Ser), exm177507 (Arg->His), and exm177543 (Arg->Trp). Normal cytogenetics de novo AML gene-based assocations consisted of only 2 of these variants: exm177559 and exm177507 (Table 2). While prevalence of exm177507 is <1% for all AML cases, in de novo AML with normal cytogenetics the MAF was higher at 3%. The other 2 variants had a MAF<1% irrespective of subtype. Somatically, DNMT3A is most frequently mutated in hematologic malignancies, with >30% of de novo AML cases with a normal karyotype and >10% of MDS patients having DNMT3A mutations. Although these are germline gene associations all three of the variants found have been reported somatically in hematologic malignancies. In 200 AML cases from The Cancer Genome Atlas (TCGA) p.R882H (represented as exm177507 on the exome chip) was a frequent somatic mutation (25%). Exm177543 (p.R635W) and exm177559 (p.N501S) are reported in the Catalogue of Somatic Mutations in Cancer (COSMIC) as somatic mutations involved in hematopoietic and lymphoid tissue in both cell lines and humans. Exm177507 and exm177543 show evidence of pathogenicity in all three in silico tools, while exm177559 was reported as deleterious and disease causing by Sift and MutationTaster, respectively. Our results show that multiple potentially pathogenic missense germline variants in DNMT3A comprise the gene-based association with AML, specifically de novo AML with normal cytogenetics. Given the functional nature of these variants it is possible germline risk stratification could be informative in determining AML risk, and subsequently development of AML harboring DNMT3A mutations. Confirmation of these findings in additional cohorts could have implications for individualized risk screening, prediction and prognosis. Additional cytogenetic subgroup analyses, including treatment-related AML, are underway. Disclosures Hahn: Novartis: Equity Ownership; NIH: Research Funding. McCarthy:Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Onyx: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; The Binding Site: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gamida Cell: Honoraria, Membership on an entity's Board of Directors or advisory committees. Sucheston-Campbell:NIH/NCI: Research Funding.