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Abstract Abstract 996 Background: Treatment with R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) has improved survival in diffuse large B-cell lymphoma (DLBCL) lymphoma, although a significant percentage of patients do not achieve a remission or they relapse. One potential explanation for this observation is that host pharmacogenetic background may impact metabolism, detoxification and transport of R-CHOP. However, there are few prospectively collected data that address pharmacogenetics in DLBCL, particularly for event-free and overall survival in the rituximab era. We therefore tested the hypothesis that functional candidate single nucleotide polymorphisms (SNPs) from genes involved in the metabolism of CHOP (CYP2C19, CYP3A5, ABCB1, ABCC2, ABCG2, RAC2, CYBA, NR3C1, GSTA1, GSTP1, TP53) and rituximab (FCGR2A, FCGR3A) influence prognosis in DLBCL. Methods: We genotyped 19 SNPs from 13 genes in a prospective cohort of newly diagnosed DLBCL patients with germline DNA enrolled at the Mayo Clinic and University of Iowa from 2002–2008 as part of the Molecular Epidemiology Resource of the Iowa/Mayo Lymphoma SPORE. All patients were systematically followed through 2009 for overall survival (OS) and event-free survival (EFS), defined as disease progression, retreatment or death due to any cause. All SNPs were genotyped on the Illumina Golden-Gate platform. Cox regression was used to estimate Hazard Ratios (HRs) and 95% confidence intervals (CI) for individual SNPs with OS and EFS. Each SNP was modeled with the most prevalent homozygous genotype used as the reference group. An ordinal test was used to assess the trend across genotypes, and a p<0.05 was considered statistically significant. All Cox models adjusted for International Prognostic Index (IPI) and treatment. Results: The median age at diagnosis of the 439 DLBCL patients was 62 years (range 18–92). The IPI was distributed as follows: 0–1 (34%), 2 (26%), 3 (24%) and 4–5 (16%). All patients were treated with chemotherapy, and 91% received R-CHOP. Through 2009, there were 171 events (39%) and 122 (28%) deaths, with a median follow-up for living patients of 49 months (range 1–98). The SNP rs1045642 in the ATP-binding cassette (ABC) protein gene ABCB1 was associated with OS (p=0.012). The variant T allele for ABCB1 rs1045642 (minor allele frequency (MAF)=0.47) is associated with a silent I→I substitution, and the T allele predicts low enzyme expression. Compared to CC homozygotes, patients with CT (HR=0.66, 95% CI 0.44–0.99) or TT (HR=0.53, 95% CI 0.31–0.90) genotypes had superior OS. We also observed an association of the GSTP1 SNP rs1695 with OS (p-trend=0.018). The variant G allele (MAF of 0.31) is associated with an A→V substitution, and this change predicts low enzyme expression. Compared to AA homozygotes, patients with the AG (HR=0.78, 95% CI 0.54–1.14) or GG (HR=0.39, 95% CI 0.17–0.90) genotypes had superior OS. Nearly identical associations for these two SNPS were observed with EFS. There were no significant associations with any of the other SNPs that we evaluated. Conclusions: In a large series of newly diagnosed DLBCL patients treated in the rituximab era, we found evidence that genetic variation in ABCB1 and GSTP1 is associated with improved OS and EFS after adjusting for IPI and treatment. The variant allele for ABCB1 is associated with slower enzyme activity, favorably impacting doxorubicin and vincristine pharmacodynamics, and the variant allele for GSTP1 is associated with slower detoxification of doxorubicin and vincristine, increasing bioavailability of these drugs. A comprehensive evaluation of the role of pharmacogenetics in DLBCL is warranted. Support: P50 CA97274, R01 CA129539. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 873 Each year in the United States, approximately 45,000 individuals are newly diagnosed with leukemia and 22,000 will die of the disease. Due to this poor survival, leukemia ranks fifth in person years of life lost among specific cancers. Little is known about causes, although exposure to solvents, radiation, pesticides and, to a modest extent, cigarette smoke has been implicated for some subtypes. The last comprehensive report of leukemia trends covered the period 1973–1998 [Xie Y et al, Cancer 2003]. Evaluation of recent leukemia incidence trends could provide important new etiologic insights. Using Surveillance, Epidemiology and End Results (SEER) Program data, we analyzed leukemia incidence trends in U.S. adults (≥ 20 years of age) by age, leukemia subtype (acute myeloid (AML), acute lymphoid (ALL), chronic myeloid (CML), chronic lymphoid (CLL)) sex, race, and ethnicity for the period 1987–2007. Frequencies, age-adjusted incidence rates (IR, per million), and trends were calculated along with annual percent change (APC) and corresponding 95% confidence intervals (CI). Joinpoint analyses were used to detect any significant directional changes in IRs over the period. Of 43,970 newly diagnosed cases identified, IRs increased with age and were consistently higher in males than females for all four subtypes. The highest IRs occurred for CLL (54.4), followed by AML (38.3), CML (20.6) and ALL (7.0). With regard to trends, IRs for CLL (APC -0.5; CI: -0.9, -0.1) and CML (APC -1.2; CI: -1.6, -0.8) declined over the time period; declines were observed in males and females, and by race and ethnicity. Male(M):Female(F) IR ratios remained relatively constant at approximately 2.0 and 1.7, respectively. For ALL, IRs decreased in males (APC -0.9; CI: -1.9, 0.2) but slightly increased in females (APC 0.4; CI: -1.0, 1.7), which was most notable in Hispanics (APC 4.0; CI: 1.2, 6.8). In contrast to CML and CLL, the overall M:F rate ratio for ALL decreased, although it did not reach statistical significance (p=0.08). For AML, IRs increased significantly for males (APC 1.0; CI: 0.3,1.6) and females (APC 1.7; CI: 0.7, 2.7) from 1987–2000 and 1987–2001, respectively. However, since then, AML IRs for males have been significantly decreasing by 4.2% per year (CI: -6.4, -2.1), while IRs for females have been decreasing by 1.6% per year (CI: -4.1, 0.9). Across the entire time period 1987–2007, there was a statistically significant negative trend (p=0.002) in the M:F IR ratio for AML. Decreasing IRs across many leukemias since 1987 are unlikely to reflect changes in screening or diagnostic coding practices. Instead, these observations may reflect temporal changes in etiologically relevant environmental exposures. Of note, the prevalence of cigarette smoking in the population has decreased and occupational safety practices (e.g., reducing solvent/radiation/pesticide exposure) have improved over the last several decades, which could contribute to the gradual decreases in some IRs observed. In contrast, the rapid and significant decrease noted for AML since 2000, especially following a significant increase, was striking and deserved additional scrutiny. We further consulted with our cancer registry colleagues to determine whether the introduction of myelodysplastic syndrome (MDS) as a new malignancy in SEER in 2001 could be influencing recent AML trends given the (apparently) coincidental overlap in time periods. Of note, approximately one third of MDS patients subsequently develop AML. We learned that AML following an MDS diagnosis from 2001–2009 was not reportable to SEER and therefore not counted. We are not aware that this has been documented in the literature. However, beginning for 2010 diagnoses, SEER changed this practice such that AML following MDS will be captured as a second malignancy. Based on these changes in AML surveillance, it will especially be important to monitor future trends for this malignancy. Overall, this study demonstrates the value of in-depth analyses of SEER cancer IRs and trends; analyses may reveal patterns of clinical and/or etiological importance, or, in the instance of AML, unpublished coding rule changes. Disclosures: No relevant conflicts of interest to declare.

Abstract We have recently reported that event-free survival at 24 months from diagnosis (EFS24) is a robust endpoint for assessment of disease related outcome for newly diagnosed patients with diffuse large B-cell lymphoma (DLBCL) treated with anthracycline-based immunochemotherapy (IC). Patients who achieve EFS24 following IC have a subsequent overall survival that is equivalent to the age and sex matched general population. The IPI was developed in the pre-rituximab era using OS/EFS endpoints. While the IPI is associated with outcome in the IC era, the original survival estimates for the IPI risk groups are outdated. The IPI is also a discrete risk classifier, with only 6 possible groups. Here we remodel the IPI using EFS24 as the endpoint in a large international cohort of patients treated with IC. This model provides an individual level 0-100% risk of failing to achieve EFS24 for each patient and can be used for patient prognosis, treatment stratification, and risk assessment. Methods Newly diagnosed DLBCL patients treated with immunochemotherapy from the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource, NCCTG N0489 clinical trial, GELA LNH2003B program, and a Lyon, France based hospital registry were included in the original EFS24 study. Patients with a relapse, progression, unplanned re-treatment, or death due to any cause within 730 days of diagnosis were considered a failure for the EFS24 endpoint. Patients alive and progression/relapse free at 730 days from diagnosis with no subsequent treatment following initial IC were considered a success for the EFS24 endpoint. Variables selected for potential model inclusion were the IPI components (age, stage, ECOG PS, number of extranodal sites, and LDH), as well as standard clinical variables typically reported in studies of DLBCL: presence of B-symptoms, bone marrow involvement, bulky disease (>10 cm), and sex. The IPI24, a prognostic model for EFS24, was developed using logistic regression models. Model building began by fitting the classic IPI score (0-5), then allowing individual IPI variables to carry different model weights and number of categories, followed by dropping insignificant variables, finally adding any additional significant variables. Model performance was assessed using bias corrected c-statistics, AIC, and R2 values. Model selection was done using the complete case set with multiple imputation on the full dataset used to refine parameter estimates for the final model. Results 1596 total patients were available for modeling. The median age was 62 (range 18-93) and 53% were male; 33% were IPI 0-1, 25% were IPI 2, 25% were IPI 3, and 17% were IPI of 4-5. The failure rate for achieving EFS24 was 29%. All variables but sex (p=0.33) were univariately associated with EFS24 (p<6.4x10-5). The original IPI had good prognostic ability for EFS24 (c=0.696, p=2.2x10-32). Allowing multiple categories for ECOG PS, stage, and age (continuous) improved model fit and prognostic ability (c=0.727). The number of extranodal sites was not significant when IPI variables were modeled separately and was removed from the model. Sex and bulky disease were additional significant variables when added to the model. Thus, the final IPI24 model contained the following risk predictors: male sex, ECOG PS (0 vs. 1 vs 2 vs 3-4), stage (I vs. II, vs. III vs. IV), LDH (elevated vs. normal range), bulky disease > 10cm, and age (continuous). This model resulted in improved fit and prognostic ability (c=0.749) over the standard IPI (c=0.696, bootstrap p<0.001). Model validation was performed on an additional 158 patients from the SPORE MER and showed good concordance (c=0.697). Additional validation is planned in a larger set of independent patients. Conclusion The IPI24, generated using standard clinical variables, yields an individual risk prediction for failing to achieve EFS24 following IC for treatment of DLBCL. The IPI24 has superior prognostic ability to the standard IPI and can be implemented in the clinic using a nomogram or as a simple electronic application. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 1591 Background: The serum free light chain (FLC) assay quantitates free kappa and free lambda immunoglobulin light chains. We previously showed elevated FLC are present in approximately 1 in 3 diffuse large B cell lymphoma (DLBCL) patients from both a phase II cooperative group clinical trial and a large clinic based epidemiology cohort. Approximately 10% of DLBCL patients had elevated FLC that was monoclonal in these series. Patients with monoclonal elevated FLC have very poor outcome with almost 50% of patients progressing in the first 15 months following initial treatment with immunochemotherapy. Unlike patients with polyclonal FLC elevation, where a variety of host effects may cause a rise in both kappa and lambda, it is likely the excess FLC in monoclonal patients is directly related to the tumor. DLBCL are a heterogenous group of tumors that can be classified into germinal center (GCB) or activated B cell (ABC) groupings using immunohistochemistry (IHC) staining algorithms. Here we examine the association of monoclonal free light chains with ABC vs. GCB DLBCL tumors. Methods: Newly diagnosed DLBCL patients were prospectively enrolled in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER) or NCCTG clinical trial N0489. Serum FLC was quantitated from enrollment research serum draws using the Freelite FLC assay (The Binding Site, Ltd., Birmingham, UK). Monoclonal elevated FLC was defined as an elevated kappa or lambda with a corresponding abnormal FLC ratio. Immunohistochemistry (IHC) staining was performed on paraffin tissue from research tissue microarrays (TMAs). Results: IHC tissue staining was available from 12 patients with monoclonal elevated FLC unrelated to renal failure. Germinal center markers were predominantly negative: 2 of 11 were LMO2 positive (18%), 1 of 12 was CD10 positive (8%), and zero cases out of 11 were GCET1 positive. FoxP1 was positive in 5 of 9 cases (56%) and MUM1 was positive in 4 of 12 cases (33%). By the Tally algorithm, 10 of 11 cases (91%) were ABC type DLBCL The percentage of ABC patients by the Tally algorithm in the corresponding DLBCL patients without monoclonal FLC was 45% (N=108, p=0.004). Conclusions: Approximately 10% of DLBCL patients have elevated monoclonal FLC and these patients have poor prognosis. Elevated monoclonal FLC may be a serum marker for ABC-type lymphoma, as the tumors from patients are predominantly negative for germinal center stains and ABC by the Tally algorithm. The secretion of light chains by the tumor suggests an activated B cell clone and the poor prognosis is characteristic of ABC type DLBCL and. Given the likelihood of the excess monoclonal FLC being tumor related, the potential exists for tracking of tumor response and progression via serum FLC in these patients. Replication of these findings in an additional cohort of DLBCL patients is planned. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 991 Background: The outcome of patients with DLBCL has significantly improved with the addition of rituximab to CHOP chemotherapy. While standard clinical prognostic factors such as those included in the International Prognostic Index (IPI) still predict outcome in DLBCL in R-CHOP treated patients, predicting the outcome of patients might be further refined using biological factors. We therefore tested whether pretreatment serum cytokines, that measure the biological activity of the tumor as well as the host response, could provide additional prognostic information in DLBCL patients. Methods: Newly diagnosed DLBCL patients were prospectively enrolled in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER). Serum cytokines were measured from pre-treatment blood draws using a multiplex ELISA (Upstate Cell Signaling Solutions, Lake Placid, NY). Thirty cytokines, including pro-inflammatory, Th1 and Th2 associated cytokines, were analyzed using the Luminex-100 system Version 1.7 (Luminex, Austin, TX). Data analysis was performed using the MasterPlex QT 1.0 system (MiraiBio, Alameda, CA). The assay was also performed on research serum draws from 400 non-lymphoma epidemiology controls enrolled on a corresponding lymphoma etiology case-control study. The upper limit of normal for each cytokine was defined as the 95th percentile from the control distribution. Clinical data was abstracted using a standard protocol for the MER and patients were followed systematically for event-free (progression, retreatment, or death due to any cause) and overall survival (EFS and OS, respectively). Cox proportional hazards models were used to evaluate the association between cytokines and outcome. Principal components analysis (PCA) was performed on the combined DLBCL and control cytokine dataset, agnostic to clinical characteristics and outcome, to identify cytokine profiles. Results: 206 DLBCL patients diagnosed between September 2002 and February 2008 with available serum were included. The median age was 64 years (range 20–92) and 52% were male. At a medium follow-up of 47 months (range 5–94), 75 patients (36%) had relapsed and 63 patients had died (31%). A cytokine profile was determined based on the first two principal components (PC) of the PCA analyses with PC1 corresponding to a general (host) cytokine elevation (also seen in normal controls) and PC2 corresponding to an increase predominantly in cytokines that were commonly elevated in DLBCL patients. 75 DLBCL patients (36%) had a normal cytokine profile similar to the general population of controls; 114 DLBCL patients (55%) had elevation in tumor specific cytokines (CXCL10, CXCL9, IL-2R, IL-12, IL-8, and IL-10) and 17 (8%) had a general cytokine elevation. Patients with any elevation of cytokines (tumor specific or general elevation) had a significantly worse event-free (HR=3.96, 95% CI: 2.13–7.37, p<0.00001) and overall survival (HR=3.75, 95% CI: 1.99–7.09, p<0.0001) than those with a normal cytokine profile (see figure). While the cytokine elevations were associated with advanced stage, poor performance score and elevated LDH, they were not associated with advanced age or extranodal disease and the results remained significant after adjustment for the IPI and treatment in the Cox model (EFS HR=3.11, 95% CI: 1.66–5.85, p<0.0001; OS HR=2.93, 95% CI: 1.53–5.63, p=0.001). Elevated serum cytokines also identified patients who were unlikely to complete initial therapy or who relapsed early. In low-risk patients (IPI 0–2), only 3% of patients with normal serum cytokines relapsed in the first 12 months compared to 23% of patients with elevated cytokines. Similarly in the high-risk group (IPI 3–5), none of the patients with normal cytokines relapsed in the first year compared to 43% with elevated cytokines. Conclusion: Elevated pretreatment serum cytokines, predominantly related to the malignancy, are associated with an increased likelihood of disease relapse and an inferior survival in patients with DLBCL. Furthermore, the pretreatment cytokine profile may also identify DLBCL patients at high risk for early disease relapse. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 3708 Background: Rituximab maintenance (RM) following induction therapy has been demonstrated to increase PFS in randomized trials in both first-line and relapsed settings (ECOG 1496, EORTC 20981, and most recently, PRIMA), and RM has been frequently used in clinical practice in the U.S. and other countries. We examined the various RM approaches used by practicing physicians in the U.S., factors that predicted whether RM was used, and compared the “real-world” effectiveness of RM to the outcomes of observation (Obs) following front-line R-based induction in FL patients (pts). Methods: The National LymphoCare Study is a prospective, multi-center, longitudinal, observational study that collects data on treatment and outcomes for pts diagnosed with FL in the U.S. from 2004–2007. Pts who achieved complete response (CR), partial response (PR) or stable disease (SD) following initial treatment with R-based therapy and who did not initiate second line therapy during the 215-day period following the date of last dose of initial therapy were categorized as Obs. Pts meeting the same criteria who started maintenance R treatment in the 215-day period comprise the RM group. Multivariable logistic regression analyses were performed to identify characteristics related to receiving RM. We compared RM and Obs groups in progression-free survival (PFS), time to next treatment (TTNT), and overall survival (OS) using Cox proportional hazards models controlling for confounding factors of clinical interest (sex, FLIPI risk group, treatment setting [academic vs. community], and induction therapy). PFS was defined as the number of days from the 215 day period following induction that defined the Obs and RM groups up to and including the date of disease progression as assessed by the treating physician or death from any cause. Pts who had not yet experienced a PFS event at the time of analysis were censored at the date of the most recent response assessment. Results: Of the 2,732 pts enrolled in NLCS, 1,536 pts completed R-based induction therapy. Among these,1,236 pts achieved CR/PR/SD and met other criteria described above to be included in analysis. 557 pts started RM treatment in the 215-day post-induction work up period (128 following R and 429 following R-chemo), and 679 pts were observed (125 following R and 554 following R-chemo). The mean duration of RM was 528 days, and the mean number of RM doses received was 13. 23% received Rx4 every 6 months, 20% Rx1 every 2 or 3 months, and 57% received another schedule. 14% of pts discontinued RM early (n=79). The most common reasons for early discontinuations were disease progression (29%), toxicity (11%), or death (7%). Pts who received R induction were more likely to receive RM than those who received R-chemo as induction (51% vs. 44%). Pts treated in community practices were slightly more likely to receive RM compared with those who were treated in academic centers (46% vs. 40%). In multivariable models, the most significant predictors of receiving RM were grade (I/II), stage (III/IV), geographic region (other than West), community practice setting, and R induction treatment (all p<0.05). After adjusting for FLIPI risk group, induction treatment, and clinical factors, RM significantly improved PFS (HR= 0.72; p= 0.010) and TTNT (HR= 0.74; p= 0.03). At 4 years of follow-up, 11% of pts in the combined population have died and there was no significant difference in OS between RM and Obs groups. 22% (n=124) of RM pts had received 2nd line treatment at the time of analysis, of whom 36% received R alone and 31% received R-chemo. The response rate for 2nd treatment was similar between RM and Obs groups (60% CR/PR for both groups). Conclusions: RM following front-line R-based induction was common in this period. However, a large percentage of pts received a RM schedule that was not consistent with standard published schedules reflecting variation among community practices. Nevertheless, RM use in clinical practice produced significant differences in PFS and TTNT compared to Obs. Importantly, response to second-line treatment was similar between RM and Obs groups. Additional followup is needed to determine whether RM produces OS benefits in this context. Disclosures: Sinha: Celgene: Research Funding. Zhou:RTI-HS: Employment; Novartis: Research Funding. Friedberg:Genentech: Consultancy; astellas: ; Lilly: ; Abbott/Trubion: ; Seattle Genetics: Honoraria; Cephalon: Consultancy. Hirata:Genentech Inc/Roche: Employment; Roche: Equity Ownership. Flowers:Spectrum: Consultancy, Research Funding; Millennium/Takeda: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Genentech/Roche (unpaid): Consultancy; Novartis: Research Funding; Seattle Genetics: Consultancy.

Abstract Abstract 3881 Background: Chronic lymphocytic leukemia (CLL) is largely incurable neoplasm of the blood and has one of the highest familial risks of disease among cancers. Monoclonal B-cell lymphocytosis (MBL) with a CLL immunophenotypic profile (i.e., CLL-like MBL) is a precursor state to CLL. In the general adult population, the prevalence rate of MBL is 5–9% and increases with age. This is in contrast to the 13–18% rate of MBL in first-degree relatives of CLL patients from high-risk families (defined here as families with at least two confirmed living cases of CLL). Few longitudinal studies of MBL incidence exists. One study evaluated MBL status over time in a cohort of individuals with MBL from a rural valley in Northern Italy. Our work herein will be the first to evaluate the status of MBL over time in relatives of CLL patients from high-risk families. Methods: Using a cohort of 41 high-risk CLL families, we evaluated the MBL status and clonal blood B-cell counts in 94 relatives of CLL patients at two time points at least 1 year a part. High sensitivity, multi-color flow cytometry was performed on fresh or previously frozen blood samples in three laboratories: Duke University, the US Food and Drug Administration, and Mayo Clinic. The number of cell events collected for flow cytometry evaluation varied from 1 to 5 x105 cells. To assure concordance across flow cytometry laboratories, 15 samples were evaluated at multiple labs. The concordance of MBL calling was a 100%. We defined three monotypic B-cell subsets as CLL-like MBL (CD5+ CD20dim), atypical MBL (CD5+ CD20+), and non-CLL like MBL (CD5−CD20+). Results: Of the 94 relatives, the median age at consent was 57 years (range 42–93) and 39% were male. At the initial MBL screening, 70 (74%) relatives had normal immunophenotype (NIPT) and 24 (26%) had MBL (1 atypical MBL, 3 non-CLL like MBL, and 20 CLL-like MBL). Seven of the 24 individuals with MBL had monoclonal B-cell counts available at baseline screening; median = 147.4 cells/uL (range 22.7–1663). The 94 relatives underwent repeat evaluation with a median follow up time of 1.8 years (range 1–6). At the second evaluation, we found an increase in the prevalence of MBL, with 11 of the 70 (12%) initially NIPT relatives developing a new MBL clone (10 CLL-like, 1 non-CLL like). These 11 incident MBL cases were from 9 families with 2 families each having 2 relatives changing MBL status. The median number of monoclonal B-cells in these 11 incident MBL cases was 0.58 cells/uL (range 0.38–60.3). The 23 out of the 24 relatives with baseline MBL (20 CLL-like MBL and 3 non-CLL like MBL) had a persistent MBL clone. Only 6 of these 23 individuals had monoclonal B-cell counts available at both time points, and among these 6, the clonal B-cell counts decreased at follow-up screening; median difference −64.1 cells/uL (range −1204.3– 10.5). The second evaluation of the initial atypical MBL relative had too few clonal cells for flow assessment. Conclusion: We found that our CLL-like MBL clones persisted over the period of observation in relatives from high-risk CLL families; this finding is similar to that previously reported using a population-based study conducted in Northern Italy. Notably, 12% of relatives from high-risk CLL families developed incident MBL during just 2 years of follow up. Although these MBL clones are all low count (< 1500 cells/uL), these data provide further evidence that MBL is a marker of inherited predisposition to CLL. It will be important to see how our rate of change of MBL status compares to that of the general population as we continue to follow our cohort of CLL families. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 1570 B-cell non-Hodgkin lymphoma encompasses a heterogeneous group of B-lymphocyte-derived malignancies that are characterized by chromosomal translocations involving the immunoglobulin (IG) gene loci and specific histological subtypes of disease are associated with a different spectrum of IG translocations. Marginal zone derived B cell lymphomas encompass three distinct entities: extranodal marginal zone B lymphoma (MZL) of mucosa associated lymphoid tissue (MALT), nodal MZL (NMZL), and splenic MZL (SMZL). MALT lymphoma is genetically unique and four mutually exclusive chromosomal translocations have been identified in this disease thus far. However, the known translocations are only present in a subset of cases suggesting that additional uncharacterized translocations or other genetic events may exist that contribute to disease development. In previous studies we characterized the novel t(X;14)(p11.4;q32) translocation in a patient with MALT lymphoma and found that GPR34, an orphan G-protein coupled receptor (GPCR), was highly expressed due to its juxtaposition to the IGHSA2 switch region. We then measured GPR34 mRNA expression in tissue biopsies from a panel of MALT, NMZL, SMZL, lymphoplasmacytic (LPL), diffuse large B cell (DLBCL), follicular (FL), and mantle cell (MCL) lymphomas. Expression of GPR34 was detected in all tissues examined, but was significantly increased in MALT (37 fold), LPL (23 fold), NMZL (18 fold), and SMZL (21 fold) compared to normal CD19+ B cells. GPR34 mRNA expression was also analyzed by gene expression profiling (GEP) of a panel of lymphomas or control lymphoid tissue and we confirmed elevated expression of GPR34 in the t(X;14) case and detected elevated GPR34 mRNA expression in MALT, LPL, NMZL, SMZL, and ABC DLBCL. When we grouped specimens by high and low expression of GPR34, a clear molecular subtype of SMZL could be identified and suggests that GPR34 high expressing tumors have a unique GEP. To confirm the qPCR and GEP analysis of GPR34 expression, we analyzed surface expression of GPR34 by flow cytometry of normal and malignant tissues and found that expression of GPR34 was detected on all MALT and SMZL B cells with an average DMFI of 2.08 (DMFI range 1.26–3.18, n=12) and on the JeKo-1 lymphoma B cell line (DMFI= 4.75). Analysis of CD19+ cells from normal controls (n=3) revealed a low level of GPR34 on (average DMFI =1.12). Little is known about the function of GPR34 and to further characterize the impact of GPR34 overexpression on cell signaling, OCI-LY19 lymphoma B cells and HeLa cells were transduced with GPR34 or a vector control. To determine if MAPK activity, a pathway regulated by GPCRs, was upregulated, the phosphorylation status of ERK1/2 in GPR34 or control cells was analyzed and we found that ERK1/2 was constitutively phosphorylated at significantly higher levels in GRP34 expressing cells. To further explore which signaling pathways were affected by GPR34 overexpression, GPR34 or vector control cells were transfected with an AP-1, CRE, NF-kB, E2F, SRE, NFAT, or ISRE- luciferase reporter plasmid and GPR34 expressing cells had significantly increased luciferase activity driven by AP-1 (5.35-fold), CRE (4.7-fold), NF-kB (2.6-fold), and E2F (2.1) when compared to vector control cells. To determine the biologic impact of GRP34 overexpression, the proliferation rates of vector control and GPR34 cells were compared and we found that proliferation of GPR34 WT cells was significantly higher than that seen in the control. We next tested the effect of the MEK inhibitor on proliferation and saw a dose dependent decrease in proliferation of GPR34 expressing cells. We then tested the ability of GPR34 cells to generate colony formation in a soft-agar colony formation assay. After 3 weeks of culture, the GPR34 cells had formed significantly more colonies than the vector control suggesting that overexpression of GPR34 can result in increased anchorage-independent cell growth. Taken together, our results identify a novel translocation in MALT lymphoma, emphasize a novel role for GPR34 in regulation of gene expression and tumor cell growth, and suggest that MEK inhibitors may be useful in a subset of translocation–harboring or GRP34 high-expressing tumors. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 3903 INTRODUCTION: Monoclonal B-Cell Lymphocytosis is an asymptomatic hematologic condition characterized by the presence of small populations of clonal B-cells in the blood or bone marrow occurring in 3–5% of the general population over age 40. Although MBL is considered the precursor state to CLL and other sub-types of indolent non-Hodgkin Lymphoma, most individuals with MBL will not develop a B-cell malignancy. It is unknown, however, whether individuals with MBL may be at risk for other adverse outcomes associated with CLL, such as increased risk of infection. To explore this aspect, we evaluated the risk of hospitalization for infection among patients with clinically recognized MBL and compared this to a cohort of general medicine patients and a cohort of CLL patients. METHODS: The Mayo Clinic Rochester (MCR), a tertiary referral center in rural southeastern Minnesota, is also the primary hematology center for southeastern Minnesota, northern Iowa, and western Wisconsin. There are no metropolitan areas or hematology specialty centers within a 50 mile radius. To explore the natural history of infection in a local, community dwelling cohort of individuals with clinically identified, CLL-phenotype MBL, we used the Mayo Clinic CLL database to identify all patients with newly diagnosed MBL seen in the MCR Hematology Division between January 1999 and December 2009. Analysis was limited to MBL cases who resided within 50 miles of MCR. The comparison cohort consisted of 689 adult patients also resided within 50 miles of MCR who were seen for a general medical examination between September 2002 and December 2009 and who were enrolled as controls in a case-control study of non-Hodgkin lymphoma. Rates of infection among individuals with MBL were also compared to a cohort of 174 patients with newly diagnosed CLL diagnosed in the same time interval and who resided within 50 miles of MCR. All hospitalizations in these 3 groups were audited to document hospitalization with infection including cross-referenced with the electronic Mayo Clinic infection database, which contains all culture results obtained from hospitalized patients at MCR. Serologies and viral assays (e.g. CMV viral load) were also reviewed. Patients whose cultures were negative but who were given a clinical diagnosis of infection (e.g. pneumonia) and who were treated with a full course of antibiotics were considered to have a culture negative infection. Among the cases, only hospitalizations after CLL or MBL diagnosis were considered. RESULTS: In May 2010, there were 524 individuals in the Mayo Clinic MBL/CLL Database with the diagnosis of CLL-phenotype MBL made between January 1999 – December 2009. Of these, 154 (29%) patients resided within a 50 mile radius of Mayo Clinic and were considered a local, community-based cohort of MBL patients. Median age at MBL diagnosis for these 154 patients was 70 years (range 45–94). After median follow-up of 4.2 years (range 0.3–10.6 years), 25 (16%) individuals with MBL were hospitalized with infection as compared to 20/689 (3%) individuals in the control population (odds ratio MBL relative to control=6.5; p<0.001) and 32/174 (18%) in the cohort of patients with newly diagnosed CLL (OR MBL relative to CLL=0.9; p=0.61) (Figure 1). The 25 MBL patients hospitalized for infection were hospitalized a total of 39 times (median 1 hospitalization for infection per individual). A specific infectious organism was identified by cultures or serologies in 8/39 (21%) hospitalizations among individuals with MBL, 10/27 (37%) hospitalizations for infection among controls, and 60 (63%) of the 89 hospitalizations for infection in CLL cases. Finally we performed a pooled multivariable analysis of all patients (n=1017) adjusting for age, sex, presence of MBL, diagnosis of CLL, and whether patients with CLL or MBL received treatment for CLL during follow-up. All factors were independently associated with risk of hospitalization for infection [Age (per year, OR=1.02, p=0.02), sex (male, OR=2.6, p=0.001), presence of MBL (OR=3.3, p<0.001), diagnosis of CLL (OR=3.0, p=0.002), and treatment for CLL (OR=3.3, p<0.001)]. CONCLUSIONS: In this cohort study, patients with newly diagnosed clinical-MBL had a 6.5 fold risk of hospitalization for infection relative to the control cohort. MBL was an independent risk factor for hospitalization for infection after controlling for age, sex, and treatment. Disclosures: Zent: GlaxoSmithKline: Research Funding; Genentech: Research Funding; Genzyme: Research Funding. Kay:Biothera: Research Funding; Clegene: Research Funding; Cephalon: Research Funding; Genentech: Research Funding; Glaxo Smith Kline: Research Funding; Hospira: Research Funding; Novartis: Research Funding; Supergen: Research Funding; Calistoga: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Emergent Biosolutions (Formerly Trubion): Membership on an entity's Board of Directors or advisory committees.

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..