Abstract: Follicular Lymphoma (FL) is the most common indolent lymphoma derived from light zone germinal center B cells and characterized by a t(14;18) translocation resulting in upregulation of BCL2 in over 80% of cases. This translocation alone is not sufficient for tumorogenesis, and must be combined with additional genetic mutations to transform B cells. FL is incurable and the disease course can be highly varied, with survival ranging from a few months to decades following diagnosis and treatment with standard chemoimmunotherapy. The heterogeneity of FL poses major challenges to identifying the association of genetic alterations and clinical outcome. Current WHO guidelines recommend establishing grade for each FL case with grade 3 thought to be more aggressive than 1 and 2. The genetic basis and clinical implications of grade in FL are unclear. Recent sequencing studies have identified many genes found to be recurrently mutated in FL including KMT2D and CREBBP. However, the degree to which genetic alterations cooperate with each other or contribute to clinical outcome is unclear. Based on the observed mutational rates in follicular lymphoma, we estimated 900 cases were needed to comprehensively delineate the genetic alterations that underlie histologic grade and clinical outcome. Accordingly, we enrolled a cohort of 1042 patients with newly diagnosed FL. All treated patients received rituximab-containing standard regimens. To go beyond the identification of gene-coding events, we developed a very large panel of 110 Mbp covering exonic (~40Mbp) and non-exonic regions (~70Mbp) of interest to enable a wide range of genomic analysis including mutation calling in both coding and non-coding regions, rearrangement detection, viral identification, and copy number analysis. In addition to the whole exome, we extended coverage to include introns, promoters, and untranslated regions of all known driver genes in cancer. We included the entirety of the immunoglobulin loci, T-cell receptor loci and CD3 loci to detect clonotypes and rearrangements. We also included lymphoma-relevant long non-coding RNAs, microRNAs, enhancers, and breakpoint-prone regions. For viral detection, we targeted the genomes of eight cancer-related viruses: Epstein-Barr virus, human papillomavirus, human immunodeficiency virus, hepatitis B, hepatitis C, Kaposi's sarcoma-associated herpesvirus, human T-lymphotropic virus, and Merkel cell polyomavirus. In addition, to enable high resolution identification of copy number variation (CNV) calls, the entire genome was tiled with probes spaced 10kb apart. DNA and RNA were extracted from all tumors and their paired normal samples, prepared into DNA and RNA sequencing libraries and subjected to sequencing on the Illumina platform to a targeted coverage of 150X. Somatic events were identified and further filtered to identify driver events in both coding and non-coding regions. FLs demonstrated a significant degree of genetic heterogeneity with over 100 genes mutated with a frequency of at least 2%. Nearly 100% of FL cases had a mutation in at least one chromatin-modifying gene. The most frequently mutated genes in follicular lymphoma were KMT2D, BCL2, IGLL5 and CREBBP. In addition, we identified frequent mutations in SPEN, BIRC6 and SETD2. To our knowledge, this is the first description of alterations in these genes in FL. Transcriptome analysis indicated a strong correlation between BIRC6 mutations and the previously described immune response 2 signature that is associated with a poor prognosis. We further performed unbiased clustering of genetic alterations in these FL cases. We identified a cluster that was specifically enriched in BCL6 and TP53 alterations and was strongly associated with grade 3 FLs which are predicted to have poorer outcomes with low intensity therapies. We further examined the genetic profiles of 1001 DLBCLs in comparison to this cohort of FLs. Our data indicate a continuum of highly overlapping genetic alterations with DLBCL displaying more complex patterns that included alterations in MYC, TP53 and CDKN2A (mainly copy number losses), indicating shared pathogenetic mechanisms underlying FL and DLBCL, particularly those germinal center B cell origin. Disclosures Koff: Burroughs Wellcome Fund: Research Funding; V Foundation: Research Funding; Lymphoma Research Foundation: Research Funding; American Association for Cancer Research: Research Funding. Leppä:Roche: Honoraria, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bayer: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen-Cilag: Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees. Gang:ROCHE: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees. Hsi:Abbvie: Research Funding; Eli Lilly: Research Funding; Cleveland Clinic & Abbvie Biotherapeutics Inc: Patents & Royalties: US8,603,477 B2; Jazz: Consultancy. Flowers:AbbVie: Consultancy, Research Funding; Denovo Biopharma: Consultancy; BeiGene: Consultancy, Research Funding; Burroughs Wellcome Fund: Research Funding; Eastern Cooperative Oncology Group: Research Funding; National Cancer Institute: Research Funding; V Foundation: Research Funding; Optimum Rx: Consultancy; Millenium/Takeda: Research Funding; TG Therapeutics: Research Funding; Gilead: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Karyopharm: Consultancy; AstraZeneca: Consultancy; Pharmacyclics/Janssen: Consultancy, Research Funding; Spectrum: Consultancy; Bayer: Consultancy; Acerta: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding. Neff:Enzyvant: Consultancy; EUSA Pharma: Honoraria, Membership on an entity's Board of Directors or advisory committees. Fedoriw:Alexion Pharmaceuticals: Other: Consultant and Speaker. Reddy:Genentech: Research Funding; BMS: Consultancy, Research Funding; Celgene: Consultancy; KITE Pharma: Consultancy; Abbvie: Consultancy. Mason:Sysmex: Honoraria. Behdad:Loxo-Bayer: Membership on an entity's Board of Directors or advisory committees; Thermo Fisher: Membership on an entity's Board of Directors or advisory committees; Pfizer: Other: Speaker. Burton:Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel; Celgene: Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees. Dave:Data Driven Bioscience: Equity Ownership.

Abstract: Introduction: CMML is a heterogeneous malignancy characterized by peripheral monocytosis and a propensity for AML transformation. Given the low incidence of CMML and its broad range complexity, a large disease-specific data set is necessary to discern independent co-variates predictive of disease behavior. Several prognostic models derived from smaller data sets have been developed to stratify CMML patients into distinct groups that are predictive for OS. However, the validity of these models in a large international data set has never been investigated. Here, we present the largest International CMML data base established to date and report key baseline characteristics predictive for disease outcome. We externally validate and perform a detailed statistical comparison between the International Prognostic Scoring System (IPSS), Revised (R)-IPSS, Global MD Anderson Scoring System (MDASC), MD Anderson Prognostic Score (MDAPS), Dusseldorf Score (DS), Mayo, and Spanish Scoring Systems (CPSS). Methods: Data were abstracted by each contributing institution and deposited for central data review at the Moffitt Cancer Center. Manual review of cases was performed to ensure data quality prior to analysis. Only WHO defined CMML was included. The primary objective of this study was to establish an international CMML data set and validate the above models calculated at the time of presentation to each center. All prognostic models were calculated as previously described. The Kaplan–Meier (KM) method was used to estimate median OS and the log rank test was used to compare KM survival estimates with SPSS version 21.0. Random Forest Survival (RSF) and ROC analysis was done with R. Results: Between July 1981 and June 2014, 1832 CMML patients were captured in the International CMML database. Median age at diagnosis was 70 (16-93) years with a male (67%) predominance. By the WHO classification, the majority of patients had CMML-1 (79.9% vs. 20.1%) and most patients were evenly subcategorized as MPN-CMML (49.8%) versus MDS-CMML (50.2%) by FAB criteria. Splenomegaly was demonstrable in 25%. Most patients had favorable cytogenetics by both IPSS (70%) and CPSS (67.6%) classification schemas. Mean BM blast % was 5.6 and mean monocyte count was 4.85x103/dL. Median OS of the entire data set was 31.6 months. All tested prognostic models were valid and able to predict OS (p 〈 0.0001). To compare relative model performance, 1013 complete cases with sufficient data to calculate all risk models were compared using time dependent receiver operator characteristic (ROC) curves and their area under the curves (AUC). ROC curves were calculated for OS at 36 months. The R-IPSS model had the highest AUC (0.694) while the DS model had the lowest (0.635). The difference in AUC between the R-IPSS and DS models was statistically significant (p = 0.003) whereas there was no significant difference from other models tested. To determine which models were most vulnerable to reclassification from low-risk to higher risk, we calculated a vulnerability score defined by the number of models able to up-stage low-risk disease in more than 15% of cases. Using this metric, the Mayo and MDASC scores were least vulnerable to up-staging by other models. Lastly, we used an orthogonal method for determination of variable importance (RSF for OS at 36 months). RSF is an ensemble method of classification and regression tree methodology. Ranking of variables by their weighted importance determined by this procedure identified the top five variables were hemoglobin, circulating blasts, platelet count, number of cytopenias, and karyotype. A new risk model was developed using the results of the RSF with an AUC of 0.720, which was comparable but not significantly different than other modern scoring systems. Conclusions: This represents the largest international CMML-specific data set derived from eight unique centers of excellence. All modern prognostic models were valid and performed comparably. Despite novel strategies for variable importance discovery, an improved model could not be constructed. This data suggest that the power of clinical variables has reached an asymptote and highlights the need for incorporation of molecular and other novel biological features. This data set is currently being populated with molecular data and is being leveraged to test published CMML molecular prognostic models which will be disclosed at the time of presentation. Disclosures Garcia-Manero: Epizyme, Inc: Research Funding. Fenaux:Celgene, Janssenm, Novartis: Research Funding. Kantarjian:ARIAD, Pfizer, Amgen: Research Funding. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees; Amgen Corp: Membership on an entity's Board of Directors or advisory committees; Boehringer-Ingelheim Corp: Membership on an entity's Board of Directors or advisory committees.

Abstract: Introduction: CMML is a clinically heterogeneous myeloid neoplasm hallmarked by the coexistence of dysplastic and proliferative patho-clinical features, which can include cytopenias, constitutional symptoms, splenomegaly, and leukocytosis. However, according to the FAB classification schema, CMML may be differentiated in dysplastic and proliferative subgroups only by the presence of leukocytosis in the latter (WBC ≥13 x 109/L). We hypothesize that incorporation of other clinically discriminating features may yield a more informative CMML stratification system. To address this, we propose three distinct CMML categories and explore their clinical relevance leveraging our existing international CMML database (Padron E et al. Blood Cancer J. 20151). Method: 1622 WHO-defined CMML cases diagnosed between 1973 and 2014 were collected from eight large cancer centres that include up to 80 discrete data elements as previously described1. Cases were placed into three clinically distinct groups and the Pearson Chi-Square test and the Kruskal-Wallis test were applied respectively to compare categorical and continuous characteristics. The Kaplan-Meier (KM) method was used to estimate median OS and the log rank test was used to compare survival curves.Cox models whereapplied to obtain univariate and adjusted hazard ratios. Identification of optimal cut-off values for continuous variable was supported by graphical inspection of martingale residuals from the null Cox model. Statistical analyses were done in SPSS v23 and R v.3.3.0. Results: We propose three categories to delineate clinically distinct CMML subtypes: (1) Myelodysplastic (MD)-CMML: WBC≤10 x 109/L, PB-immature myeloid cells (IMC) = 0%, no splenomegaly (2) MD/MP-CMML: WBC 10-20 x 109/L or WBC ≤10 x 109/L but PB-IMC 〉 0% and/or splenomegaly (3) Myeloproliferative (MP)-CMML: WBC 〉 20 x 109/L. A recursive partitioning approach was used to identify the WBC cut points, with splenomegaly and IMC added to more accurately depict the MPN aspect of CMML. Numbers of patients included in the MD-, MD/MP-, and MP-CMML subcategories were 319 (19.7%), 789 (48.6%) and 514 (31.7%), respectively (Table 1). According to the FAB criteria, the MD/MP group included 521 (66%) MD- (WBC ≤13 x 109/L) and 268 (34%) MP-CMML (WBC 〉 13 x 109/L) patients suggesting that the proposed classification clinically reclassifies FAB-defined CMML. Within the MD/MP group, 344 patients (21.2%) had a WBC 〈 10 x 109/L but with IMC 〉 0% and/or splenomegaly. Comparison of overall survival (OS) among proposed groups demonstrated that this classification schema was capable of discriminating the CMML natural history (Figure 1). In comparison to MD/MP-CMML, the unadjusted OS Hazard Ratio (HR) was 0.60 (95% CI 0.49-0.73) for MD-CMML and 1.57 (95% CI 1.36-1.81) for MP-CMML (p 〈 0.001 for both). This difference was retained after adjusting for BM-Blasts ( 〈 vs ≥5%), IPSS or CPSS cytogenetics (High-risk vsInterm/low-risk), and elevated levels of LDH (HR was 0.73 with 95% CI 0.57-0.93, p=0.011 for MD-CMML, and 1.33 with 95% CI 1.12-1.58, p=0.001 for MP-CMML, respectively). We next explored whether each proposed group may have distinct variables that uniquely govern its prognosis. Peripheral blood blasts 〉 5%, RBC- and PLT-transfusion-dependence predicted poor OS only in the MD and MD/MP-subcategories (p 〈 0.005), but had no impact in the MP-CMML. Male gender and elevated LDH were only significantly associated with prognosis in the MD/MP group (p 〈 0.05 and p 〈 0.005, respectively) while absolute lymphocyte count 〉 2.5 x 109/L and absolute monocyte count 〉 10 x109/L were uniquely predictive for shorter survival in the MP-CMML subcategory (p 〈 0.005). Notably, we additionally identified gene mutations that uniquely predicted prognosis in each proposed group (Table 2). Conclusions: We demonstrate that our proposed 3-group clinical classification schema is capable of independently stratifying prognosis. Further, our analysis identified clinical and genetic variables that uniquely govern each group's prognosis, suggesting independent clinical behaviour. Further investigations are warranted to validate these groups. Disclosures Jabbour: ARIAD: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Research Funding; BMS: Consultancy. Fenaux:Celgene, Janssen,Novartis, Astex, Teva: Honoraria, Research Funding. Kantarjian:Bristol-Myers Squibb: Research Funding; ARIAD: Research Funding; Amgen: Research Funding; Pfizer Inc: Research Funding; Delta-Fly Pharma: Research Funding; Novartis: Research Funding. Komrokji:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Speakers Bureau.

Abstract: Background: Chronic immune thrombocytopenia (ITP) is a complex autoimmune disease characterized by antibody mediated platelet destruction and impaired production. Sustained autoimmunity in chronic ITP appears to be due to generalized immune dysregulation including altered T cell balance with a shift toward immune activation (increased Th1/Th2 ratio) as well as decreased number and impaired function of regulatory T cells (Treg). The cause of these abnormalities has not been fully elucidated and is likely multifactorial, but genetic factors may be involved in ITP pathogenesis. Improved understanding of genetic influences could lead to novel therapeutic approaches. Aim: To identify genetic variants that may be involved in chronic ITP susceptibility and severity. Methods: Whole exome sequencing (WES) was performed on 262 samples with robust phenotype data on children with chronic ITP from the North American Chronic ITP Registry (NACIR, n= 173) and the Platelet Disorders Center at the Weill-Cornell Medical Center (n=89). All but three patients were ≤19 years old at diagnosis; 83% had primary ITP, 10% had Evans syndrome, 7% had other autoimmune disorders. Sequencing data for ITP cases of European American (EA) ancestry were compared to EA controls with platelets 〉 150 x 109/L sequenced in the Atherosclerosis Risk in Communities (ARIC) Study (N=5664) to identify candidate genes associated with ITP susceptibility. Analyses filtered variants on a minor allele frequency (MAF) 〈 0.01 as well as functionality of nonsynonymous, stop gain, splicing, stop loss, and indel variants. Both Fisher-Exact tests of single variants and Firth logistic regression for gene-based tests, accounting for an unequal proportion of cases compared to controls, were used. A Bonferroni corrected threshold based on 16,532 genes was calculated at 3.0x10-6. In a separate analysis, phenotype data for ITP cases were reviewed and cases stratified by disease severity according to second line treatment needed (Yes =139, No=113) and compared to ARIC EA controls with platelet count 〉 150 x 109/L (N=5664). Results: Several damaging variants identified in genes involved in cellular immunity had a significantly increased frequency in the EA ITP cohort (Table). The most significant associations were detected in the IFNA17 gene, which is involved in TGF-β secretion and could affect number and function of the Treg compartment. IFNA17 rs9298814 (9:21227622 A 〉 C) was identified in 26% of cases in the EA ITP cohort compared to 〈 0.01% of EA controls, and other low frequency but presumed deleterious variants were also identified in IFNA17. IFNA17 gene variants remained significant in the most severely affected patients, specifically those requiring second line therapy, providing further evidence for this gene's functional relevance in the pathogenesis and pathophysiology of ITP. Other genes with known impact on T cell number or function, including DGCR14, SMAD2 and CD83 also contained variants with increased frequency in the EA ITP cohort. IFNLR1 and REL genes were also significantly associated with need for second line ITP therapy. Analysis of this large cohort did not validate any of over 20 variants that have been previously published as candidates for ITP susceptibility or evolution to chronic ITP. Conclusion: Damaging variants in genes associated with cellular immunity have an increased frequency in children with chronic ITP compared to controls, providing further evidence for the role of T cell abnormalities in the pathophysiology of ITP. The IFNA17 and IFNLR1 genes maintained significance when the ITP cohort was stratified according to disease severity, and may be important candidate genes involved in immune regulation and sustained autoimmunity associated with chronic ITP. Table. Genes identified through WES analysis of children with chronic ITP. Gene Function Relevant to ITP Pathophysiology Minor Allele Count (MAC)Cases Controls p value EA Chronic ITP vs. EA ARIC (non-ITP) controls N=172 N=5664 IFNA17 Treg, TGF-β signaling 91 17 3.97x10-13 DGCR14 IL-17 induction 14 3 1.27x10-10 SMAD2 TGF-β signaling 1 0 5.62x10-22 CD83 Th17/Treg balance 2 3 1.67x10-6 EA Chronic ITP requiring Second Line Therapy vs. EA ARIC (non-ITP) controls N=139 N=5664 IFNLR1 Class II cytokine receptor 2 1 3.95x10-15 IFNA17 Treg, TGF-β signaling 75 17 3.40x10-7 REL T and B cell function, inflammation 2 0 1.39x10-14 Disclosures Off Label Use: Off-label use of CliniMACS purified CD34+ cells. Lambert:GSK: Consultancy; NovoNordisk: Honoraria; Hardin Kundla McKeon & Poletto: Consultancy. Recht:Baxalta: Research Funding; Kedrion: Consultancy. Bussel:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; protalex: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; rigel: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cangene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract: Myelodysplastic neoplasms (MDS) are a collection of hematopoietic disorders with widely variable prognoses and treatment options. Accurate pathologic diagnoses present challenges due to interobserver variability in interpreting morphology and quantifying dysplasia. We compared local clinical site diagnoses with central, adjudicated review from 918 participants enrolled in the ongoing National Heart, Lung, and Blood Institute National MDS Natural History Study (NCT02775383), a prospective observational cohort study of participants with suspected MDS or MDS/myeloproliferative neoplasms (MPNs). Locally, 264 (29%) were diagnosed as having MDS, 15 (2%) MDS/MPN overlap, 62 (7%) idiopathic cytopenia of undetermined significance (ICUS), 0 (0%) acute myeloid leukemia (AML) with & lt;30% blasts, and 577 (63%) other. Approximately one-third of cases were reclassified following central review with 266 (29%) diagnosed as MDS, 45 (5%) MDS/MPN overlap, 49 (5%) ICUS, 15 (2%) AML & lt;30%, and 543 (59%) other. Site miscoding errors accounted for over half (53%) of the local misdiagnoses, leaving a true misdiagnosis rate of 15% overall, 21% for MDS. Therapies were reported in 37% of patients, including 43% of patients with MDS, 49% of MDS/MPN, and 86% of AML & lt;30% blasts. Treatment rates were lower (25%) in cases with true discordance in diagnosis compared to those where local and central diagnoses agreed (40%), and receipt of inappropriate therapy occurred in 7% of misdiagnosed cases. Discordant diagnoses were frequent, which has implications for the accuracy of study-related and national registries and can lead to inappropriate therapy.

Abstract: Introduction: Patient-reported outcomes (PROs) such as quality of life (QOL) are variably affected in patients with myelodysplastic syndromes (MDS), but the heterogeneous composition of disease states grouped together as "MDS" increases the difficulty of assessing and understanding these outcomes. Moreover, little is known about the potential relationship between QOL and frailty in this population. Methods: The NHLBI MDS Natural History Study (NCT02775383) is a prospective cohort enrolling patients undergoing diagnostic work up for suspected MDS or MDS/myeloproliferative neoplasms (MPNs) in the setting of cytopenias. Untreated participants undergo bone marrow assessment with centralized histopathology review at enrollment for assignment into subcategories for longitudinal follow-up: MDS, MDS/MPN, ICUS, AML ( & lt;30% blasts), and "At-Risk" (cases with sub-threshold dysplasia or select karyotypic or genetic mutations). PRO and frailty data are collected at enrollment and every six months thereafter. PRO instruments include MDS-specific (QUALMS) and general (FACT-G, PROMIS Fatigue Short Form 7a, EQ-5D-5L) instruments, and a measure of frailty (VES-13). While no frailty instrument alone has been shown to be a substitute for comprehensive geriatric assessment, VES-13 has been successfully used in cancer-related studies for basic screening, where a score of 3 or more is considered frail (vulnerable). An analysis of variance (ANOVA) was used for the overall comparisons of mean baseline scores between diagnostic categories. Pairwise comparisons of scores between diagnostic categories and vulnerability subgroups were performed via two-sample t-tests. Results : Of 835 participants assessed for eligibility, 369 (44%) were classified as MDS, MDS/MPN, AML, ICUS or At-Risk, and further evaluated. Mean age was 72 years (standard deviation (SD)=10.7) and 68% were male. Mean baseline scores on the PRO measures are compared between diagnostic categories in the Table; scores did not differ significantly across categories. In particular, no significant differences were found between MDS and the other diagnostic categories. ICUS had similar QOL scores to MDS and MDS/MPN (e.g., means (SD) on EQ-5D-5L of 74.1 (17.8) in ICUS and 70.8 (19.4) in MDS, p=0.348) but had significantly higher scores than those for AML on EQ-5D-5L (60.7 (28.4), p=0.031). For the 216 participants with diagnostically-confirmed MDS, QOL impairment was similar to that routinely seen in other cancers; for example, the mean total FACT-G was 81.8 (SD=15.9), similar to localized breast cancer (82.4, SD=16.2), localized colorectal cancer (79.6, SD=16.1), and lung cancer with no current evidence of disease (82.6, SD=15.5; comparison means from Pearlman, Cancer, 2014). For frail/vulnerable participants with MDS or MDS/MPN (N=87), the most common reasons for vulnerability were age ≥75 years (68%), overall rating of health as poor or fair (62%), and difficulty with prolonged physical activity (90%) such as walking a quarter mile (75%) or doing heavy housework (70%). A minority also were vulnerable due to requiring help with instrumental activities of daily living (iADLS) such as shopping (28%) or managing money (16%). Mean QOL scores were compared between vulnerability subgroups (Figure). Vulnerable participants pooled over all diagnostic categories had significantly worse PROs than non-vulnerable participants for all measures (p & lt;0.001). In particular, vulnerable MDS participants scored significantly worse on the QUALMS (mean 64.4, SD=13.4) vs. non-vulnerable MDS participants (mean 72.7, SD=13.3), p & lt;0.001. Conclusions: Participants in our cohort with histologically-confirmed MDS-even low-grade MDS-had similar impairments in PROs as those with other cancers. Among those with histologically-confirmed MDS, vulnerable participants had significantly worse QOL on many measures compared to non-vulnerable participants, suggesting that this domain of function be specifically assessed in clinic. Moreover, while a "gestalt" of frailty may be inferred by observing how patients present and move in the office, these data suggest that other contributing domains, such as difficulty with prolonged physical activity and iADLs, should be evaluated explicitly. Disclosures Foran: H3Biosciences: Research Funding; Aptose: Research Funding; Kura Oncology: Research Funding; Takeda: Research Funding; Servier: Membership on an entity's Board of Directors or advisory committees; Xencor: Research Funding; Agios: Honoraria, Research Funding; Boehringer Ingelheim: Research Funding; Actinium: Research Funding; Aprea: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Trillium: Research Funding; Revolution Medicine: Consultancy; Pfizer: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding. Gore:Abbvie: Consultancy, Honoraria, Research Funding. Padron:Incyte: Research Funding; Kura: Research Funding; Novartis: Honoraria; BMS: Research Funding. Sekeres:BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda/Millenium: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Abstract: Health-related quality of life (HRQoL) and vulnerability are variably affected in patients with myelodysplastic syndromes (MDS) and other cytopenic states; however, the heterogeneity of these diseases has limited our understanding of these domains. The National Heart, Lung, and Blood Institute-sponsored MDS Natural History Study is a prospective cohort enrolling patients undergoing workup for suspected MDS in the setting of cytopenias. Untreated patients undergo bone marrow assessment with central histopathology review for assignment as MDS, MDS/myeloproliferative neoplasm (MPN), idiopathic cytopenia of undetermined significance (ICUS), acute myeloid leukemia (AML) with & lt;30% blasts, or “At-Risk.” HRQoL data are collected at enrollment, including the MDS-specific Quality of Life in Myelodysplasia Scale (QUALMS). Vulnerability is assessed with the Vulnerable Elders Survey. Baseline HRQoL scores from 449 patients with MDS, MDS/MPN, AML & lt;30%, ICUS or At-Risk were similar among diagnoses. In MDS, HRQoL was worse for vulnerable participants (eg, mean Patent-Reported Outcomes Management Information Systems [PROMIS] Fatigue of 56.0 vs 49.5; P & lt; .001) and those with worse prognosis (eg, mean Euroqol-5 Dimension-5 Level [EQ-5D-5L] of 73.4, 72.7, and 64.1 for low, intermediate, and high-risk disease; P = .005). Among vulnerable MDS participants, most had difficulty with prolonged physical activity (88%), such as walking a quarter mile (74%). These data suggest that cytopenias leading to MDS evaluation are associated with similar HRQoL, regardless of eventual diagnosis, but with worse HRQoL among the vulnerable. Among those with MDS, lower-risk disease was associated with better HRQoL, but the relationship was lost among the vulnerable, showing for the first time that vulnerability trumps disease risk in affecting HRQoL. This study is registered at www.clinicaltrials.gov as NCT02775383.

Abstract: Abstract 803 Diffuse large B-cell lymphomas (DLBCL) is the most common form of lymphoma and these tumors demonstrate a striking molecular and clinical heterogeneity. Gene expression profiling has shown that these tumors can be divided into at least two groups, activated B cell-like (ABC) and germinal B cell-like (GCB), as well as a number of other cellular processes underlying survival and tumor biology. However, the molecular mechanisms which lead to the differential gene expression patterns are not well understood. Alternative splicing is a process through which individual exons that comprise genes that are assembled into different gene isoforms with potentially different function. Alternative splicing has been shown to be a ubiquitous mechanism of gene regulation in eukaryotes and a number of cancers. The role of alternative splicing in DLBCL is unknown. We hypothesized that alternative splicing might play an important role in DLBCL. We measured genome-wide expression of over 1 million exons in 106 primary DLBCL tumors using Affymetrix Exon 1.0 ST microarrays. The same cases were also profiled for gene expression using a conventional Affymetrix Gene microarray for comparison, and further sub-classified as the molecular subgroups of DLBCL and for independent assessment of gene expression associated with known biological processes. We identified those genes as alternatively spliced which had at least one exon that was significantly different (P 〈 0.01) compared with the comparison group. Through examination of exon-level expression data, we found evidence for splicing events in over 10,000 genes that affect at least 10% of DLBCL cases. We identified over 200 genes that have differential exon usage between ABC and GCB DLBCL. The expression of selected alternatively spliced exons was confirmed by real-time PCR. We further examined the occurrence of alternative splicing in a number of cellular processes including each of the survival associated gene expression signatures. We found that alternative splicing regulates a significant number of genes underlying the survival-associated proliferation, stromal response and germinal center differentiation gene expression signatures (P 〈 10−6 in all cases). In addition, a number of processes that are known to be important in oncogenesis appeared to be highly regulated by alternative splicing including transcription factor activity, DNA-repair and apoptosis (P 〈 0.001). These data confirm that alternative splicing plays a significant role in regulating genes that are important mediators of DLBCL biology. We further investigated whether lineage-specific effects were responsible for some of the observed differences in splicing in the molecular subgroups of DLBCLs. We obtained normal resting B cells from healthy donors and stimulated them with IgM and CD40-ligand to generate activated B cells. We found that the gene-isoforms expressed highly in activated normal B cells were significantly enriched in ABC-DLBCLS (P 〈 0.01), suggesting that lineage-derived differences in isoform splicing are preserved in their malignant counterparts. Our data indicate that alternative splicing provides an additional and significant component of regulation that encompasses nearly every biological process that is known to be important in DLBCL. Future studies that examine the role gene expression will need to recognize the specific isoforms that result in proteins with altered function. Disclosures: No relevant conflicts of interest to declare.

Abstract: Abstract 433 Burkitt lymphoma (BL) is a relatively uncommon lymphoma, but is clinically important because it is curable when diagnosed properly. BL is also an important model disease for studying cancer. Chromosomal translocations of the MYC gene are a defining feature of BL. Diffuse large B cell lymphoma (DLBCL) is the most common form of lymphoma in adults and demonstrates overlapping morphology, immunophenotype and clinical behavior with BL. The genetic causes and the role of specific mutations in BL are largely unknown. Th e decoding of the human genome and the advent of high-throughput sequencing have provided rich opportunities for the comprehensive identification of the genetic causes of cancer. We began by sequencing 2 complete lymphoma tumor genomes (and paired normal tissue) derived from DLBCL and BL respectively. The pattern of somatic base alterations in both DLBCL and BL genomes indicated a predominance of G→A/C→T and A→G/T→C transitions (P 〈 10−6) suggesting that the majority of these mutations arise from endogenous processes rather than environmental exposures, as has been observed with lung cancer and tobacco. In order to comprehensively identify genes that are recurrently mutated in DLBCL and BL, we obtained a total of 95 cases of DLBCLs and 60 cases of BL. The DLBCL cases were divided into a discovery set (N=34) and a prevalence set (N=61). The Burkitt cases were also divided into discovery and prevalence sets (N=15, N=45 respectively). For each of the discovery set cases we also obtained paired normal tissue. We performed whole-exome sequencing for all of these using the Agilent solution-based system of exon capture, which uses RNA baits to target all protein coding genes (CCDS database), as well as ∼700 human miRNAs from miRBase (v13). In all, we generated over 6 GB of sequencing data using high throughput sequencing on the Illumina platform. We identified 525 candidate cancer genes that were recurrently somatically mutated in DLBCL and BL. We found that each tumor had an average of 20 gene alterations, which is fewer than most other solid tumors sequenced to date. Commonly implicated biological processes comprising these genes included signal transduction (e.g. PIK3CD, PDGFRA) and chromatin modification (e.g. MLL3, SETD2), affecting 17.2% and 14.8% of the total genetic events respectively. We found several genes related to cancer that were commonly mutated in both BL and DLBCL, including MYC, BTG1 and SETD2. Mutations in MYC were much more common in BL compared to DLBCL, suggesting that mutation of MYC might serve as an independent oncogenic mechanism in BL, in addition to chromosomal translocations. Many known cancer genes were found to be exclusively mutated in BL including SMARCA4, a gene known to regulate the expression of CD44 which is implicated in tumorigenesis. This study represents one of the first in-depth analyses of a BL genome and one of the largest applications of exome sequencing in cancer. Our data provide the most comprehensive genetic portrait of human BL to date, and provides a significant first step to identifying the genetic causes of the disease. Disclosures: No relevant conflicts of interest to declare.