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Abstract Background Approximately 2-8% patients with chronic lymphocytic leukemia (CLL) will transform to diffuse large B-cell lymphoma (DLBCL, Richter syndrome [RS]). Clinical characteristics and molecular markers at the time of CLL diagnosis are associated with the risk of RS; however, there are no data regarding germline genetic variations and the risk of RS. Genomewide association studies (GWAS) have shown several single-nucleotide polymorphisms (SNPs) that are associated with a higher risk of familial CLL. It is not known whether any of these polymorphisms also predispose to RS. Methods Since 2002, all consecutive patients with newly diagnosed (<9 months diagnosis) CLL at Mayo Clinic were offered enrollment into a prospective genetic epidemiology study. Patients completed extensive epidemiologic questionnaires and baseline clinical, laboratory, and biologic data were abstracted using a standard protocol. Genotyping of germline tissue at diagnosis was performed using an Illumina iSelect panel and Affymetrix 6.0 SNP chip. All patients were prospectively and longitudinally followed at defined time-points with systematic collection of data on treatments, second cancers, and RS. All patients with biopsy-proven DLBCL during follow-up were considered to have undergone transformation into RS. Time to RS was calculated from CLL diagnosis date until RS or until last follow-up date for those with no RS. SNPs were modeled in two ways: ordinal and dominant. Cox regression was used to estimate hazard ratio (HR) for individual SNPs with time to transformation. Results Thirteen of the GWAS-discovered SNPs associated with risk of developing CLL were available and genotyped on 620 CLL patients. Median age at diagnosis of CLL was 62 years (range 27-88), and 428 (69%) were male. Three hundred and ten (51%) patients were low (0) Rai stage, 271 (45%) were intermediate (I-II) Rai stage, and 22 (4%) were advanced (III-IV) Rai stage. The immunoglobulin heavy chain gene was unmutated in 189 (40%) patients; 157 (32%) patients expressed ZAP-70, 163 (29%) expressed CD38 and 104 (31%) expressed CD49d. Fluorescence in-situ hybridization (FISH) revealed that 210 (41%) patients had del13q, 90 (18%) patients had trisomy 12, 37 (7%) had del11q, 23 (5%) had del17p and 141 (28%) had no detectable FISH abnormalities. As of last follow-up, 239 (39%) patients received therapy for CLL. After a median follow-up of 5.9 years (range 0-11), 15 (2.4%) patients developed biopsy-proven RS. The median time to RS in these 15 patients was 4.5 years (range 1.0-8.7 years). The ordinal HR for the 13 SNPs tested, their corresponding genes, and p-values are shown in Table 1. Germline polymorphisms in a single SNP, rs4987852, encoding for BCL2 (chromosome 18), was significantly associated with an increased risk of RS (ordinal HR=3.9; 95% CI=1.6-9.8; p-value=0.004). This allele was present in 48/605 (8%) non-transformed CLL patients compared to 4/15 (27%) of patients with RS. Time to RS according to the Kaplan-Meier analysis for rs4987852 is shown in Figure 1. This SNP is located in a region in which t(14;18) translocation breakpoints commonly occur in follicular lymphoma and overexpression of BCL2 leads to an increased incidence of B-cell lymphomas in mice. Conclusion Our results suggest that inherited genetic polymorphisms predispose CLL patients to develop RS. Specifically, SNP (rs4987852) present on the BCL2 gene on chromosome 18 in CLL is associated with an increased risk of transformation to RS. These observations require replication in other CLL cohorts. Disclosures: Shanafelt: Genentech: Research Funding; Glaxo-Smith-Kline: Research Funding; Cephalon: Research Funding; Hospira: Research Funding; Celgene: Research Funding; Polyphenon E International: Research Funding.

Abstract Clonal hematopoiesis of indeterminate potential (CHIP) is defined as somatic mutations in clonal blood cells of individuals without any other hematological abnormalities and have been identified using whole exome sequencing (WES) from pre-specified genes. CHIP is reportedly associated with aging, reduced overall survival, cardiovascular disease, and hematologic disease, mainly myeloid cancers. Additionally, whole genome sequencing and WES studies in CLL cases have identified putative CLL driver genes with recurrent somatic variants or copy number alterations. Here, we investigate the associations of CHIP and mutations in CLL somatic driver genes with risk of CLL and MBL, a precursor to CLL. Using WES, 571 individuals from 132 CLL families were sequenced from two different sites, Mayo Clinic (92 families) and National Cancer Institute (NCI, 40 families), including 251 CLLs, 74 MBLs, and 246 unaffected relatives. DNA was extracted from buccal cells (Mayo Clinic) and peripheral blood (NCI). Allele counts from gVCF files were extracted for specific genes and analyzed. Variants were annotated using the Variant Effect Predictor in Ensembl, genome build GRCh37 (http://useast.ensembl.org/index.html). Highly-sensitive flow cytometry of the blood was used to screen for MBL. CHIP was defined as in Genovese et al., 2014 as the presence of any of the following: A) disruptive mutations in ASXL1, TET2, or PPM1D; B) missense mutation p.617F in JAK2; C) disruptive or missense mutations in DNMT3Alocalized to exons 7 to 23D) any mutations reported at least 7 times in hematological malignancies in the Catalogue of Somatic Mutations in Cancer (COSMIC); and (E) No variant allelic fraction (VAF) threshold. CLL driver genes included disruptive or missense mutations in ATM, BIRC3, MYD88, NOTCH1, SF3B1, TP53, EGR2, POT1, NFKBIE, XPO1, or FBXW7with VAF greater than 0.1. Mutations from COSMIC and CLL driver genes were excluded if the minor allele frequency in 1000 Genomes was greater than 0.5%. Data was analyzed using logistic regression adjusting for age, sex, and site. Odds ratios (OR) and 95% confidence intervals (CI) were estimated. Median age for CLL, MBL, and unaffected was 63, 61.5, and 54, respectively. The unaffected relatives were significantly younger than both the CLL and MBL groups (p<0.0001), with no difference between CLL and MBL (p=0.46). A total of 70 (12%) individuals from 54 different families had CHIP. CHIP was characterized in the majority of samples as mutations in DNMT3A, ASXL1, and TET2with 43, 9 and 8 individuals, respectively. As expected, CHIP was associated with age (p<0.001) but not sex (p=0.87). CHIP was present in 42 (17%) CLLs, 9 (12%) MBLs, and 19 (8%) unaffected relatives. There was a significant association between the presence of CHIP and CLL risk compared to unaffected relatives (OR= 2.19, 95% CI: 1.20 - 4.13, p=0.013) but not with MBL risk (OR=1.34, 95% CI: 0.54 - 3.11, p=0.51). Using the CLL driver genes, we found mutations in 119 (47%) CLL, 20 (27%) MBL, and 70 (29%) unaffected relatives. Mutations in CLL driver genes were associated with CLL risk compared to unaffected relatives (OR = 2.51, 95% CI: 1.64 - 3.87, p<0.0001), but there was no evidence for increased MBL risk (OR = 1.00). These results held when we subset the analysis to the Mayo only data where the DNA was extracted from buccal cells. This study further supports the association between mutations in CHIP related genes and risk of hematologic malignancies, in particular CLL. This is the first report of the prevalence of CHIP in MBLs. Although MBL and CHIP represent clonal population of blood cells, our data suggest the clones are different. Mutations in CLL driver genes are also associated with CLL risk but show little to no evidence with increased MBL risk. Interestingly, our unaffected relatives of CLL cases also had a high frequency of CLL driver mutations. Future studies are needed to understand these acquired mutations (both in CHIP- and CLL driver- related genes) in the unaffected to MBL to CLL continuum. Disclosures Parikh: Abbvie: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AstraZeneca: Honoraria, Research Funding; Gilead: Honoraria; Janssen: Research Funding. Ding:Merck: Research Funding. Cerhan:Jannsen: Other: Scientific Advisory Board; Celgene: Research Funding; Nanostring: Research Funding. Shanafelt:Jansen: Research Funding; Pharmacyclics: Research Funding; Genentech: Research Funding; GlaxoSmithKline: Research Funding. Kay:Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta: Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees.

Abstract PURPOSE Urgency to initiate therapy has to be weighed against the time required for screening and consenting to enroll a patient onto a clinical trial. Exclusion of patients with rapidly progressive or symptomatic disease may lead to selection of patients with less aggressive disease. We recently identified that a short diagnosis to treatment interval (DTI) is associated with adverse clinical factors and inferior outcome in patients with diffuse large B-cell lymphoma (DLBCL) (Maurer et al, JCO 2018); shorter time to treatment was also found to be associated with outcome in other aggressive lymphomas, including mantle cell lymphoma (MCL), in the National Cancer Database (Olszewski et al, BJH 2018). Here we assess the association of DTI with clinical variables and outcome in MCL from an observational cohort with validation in patients enrolled on an NCTN clinical trial. PATIENTS AND METHODS Newly diagnosed patients with MCL were prospectively enrolled in the University of Iowa/Mayo Clinic Lymphoma SPORE Molecular Epidemiology Resource (MER), now a subcohort of the Lymphoma Epidemiology of Outcomes (LEO) Cohort Study. Patients initially managed with observation were excluded. DTI was defined as the time in days from date of first lymphoma-containing biopsy to the initiation of therapy. Associations of DTI with clinical factors and outcome were examined using a 14 day split based on the previous MER study of DTI in DLBCL. Odds ratios (OR) and Cox model hazard ratios (HR) are reported. Outcome was assessed using event-free survival (EFS) where events were defined as progression/relapse, initiation of new anti-lymphoma therapy, or death due to any cause. A validation cohort was assembled from patients enrolled in CALGB (Alliance) clinical trial 50403. Protocol therapy was high dose chemotherapy with autologous hematopoietic stem cell transplantation (ASCT) consolidation and post-ASCT rituximab followed by bortezomib as either consolidation or maintenance. DTI was defined as time from diagnosis to study registration and outcome was assessed using progression-free survival (PFS) as defined on the clinical trial. RESULTS 271 patients with MCL enrolled in the MER from 2002-2015 and initiated treatment within 100 days of diagnosis. Median age at diagnosis was 64 years (range 36-76), 211 (78%) were male, and 92% were stage III-IV; MIPI was Low (41%), Intermediate (36%) and High (23%). Induction therapy was R-CHOP based (50%), B-R based (16%), HyperCVAD based (8%), 2-CDA based (11%), and other (15%). Median EFS of the cohort was 41 months (95% CI: 34-46). Median DTI was 26 days (IQR: 14-38) and 28% enrolled within 14 days of diagnosis, exhibiting a longer DTI than DLBCL patients enrolled in the MER during the same time period. Short DTI (0-14 days) was associated with adverse clinical factors including ECOG PS 2-4 (OR=5.74, 95% CI: 2.51-13.1, p<0.0001), elevated LDH (OR=2.30 95% CI: 1.25-4.22, p=0.0072), and higher MIPI score (OR=1.48, 95% CI: 1.04-2.07, p=0.025) but was not significantly associated with age, sex, B-symptoms, or stage (all p>0.30). Short DTI was also associated with inferior EFS (HR=1.78, 95% CI: 1.27-2.49, p=0.0008) which remained significant after adjusting for MIPI score (HR=1.72, 95% CI: 1.23-2.41, p=0.0016). In the validation cohort, 144 patients enrolled on 50403 within 100 days of diagnosis from 2006-2010. Median age at diagnosis was 59 years (range 29-69), 77% were male, and 97% were stage III-IV; MIPI was Low (51%), Intermediate (31%) and High (17%). Median PFS of the cohort was 84 months (95% CI: 50-109). Median DTI was 35 days (IQR: 22-46) and 11% enrolled within 14 days of diagnosis. Short DTI (0-14 days) was associated with PS (OR=9.00, 95% CI: 1.18-69.0, p=0.034) and) higher MIPI score (OR=2.09, 95% CI: 1.08-4.04, p=0.029) but not elevated LDH (OR=1.27, 95% CI: 0.43-3.74, p=0.66). Short DTI was associated with inferior PFS (HR=2.21, 95% CI:1.19-4.09, p=0.011) which remained clinically significant after adjusting for MIPI score (HR=1.85, 95% CI: 0.98-3.47, p=0.056). CONCLUSION A short diagnosis-to-treatment interval is strongly associated with adverse clinical factors and poor outcome in newly diagnosed MCL in the MER. Clinical trials are encouraged to facilitate enrollment of patients with short DTI to avoid potential selection bias. Support: U01 CA195568, P50 CA097274, U10CA180821, U10CA180882; ClinicalTrials.gov Identifier: NCT00310037 (CALGB 50403) Figure. Figure. Disclosures Maurer: Celgene: Research Funding; Nanostring: Research Funding; Morphosys: Research Funding. Kaplan:Bayer Pharmaceuticals: Consultancy. Cohen:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BioInvent: Consultancy; Takeda: Research Funding. Martin:Gilead: Consultancy; Kite: Consultancy; Seattle Genetics: Consultancy; AstraZeneca: Consultancy; Janssen: Consultancy; Bayer: Consultancy. Kahl:Abbvie: Consultancy; AstraZeneca: Consultancy; Gilead: Consultancy; Acerta: Consultancy; Juno: Consultancy; Celgene: Consultancy; Genentech: Consultancy; Seattle Genetics: Consultancy; CTI: Consultancy; ADC Therapeutics: Consultancy. Bartlett:ImaginAB: Research Funding; Bristol-Meyers Squibb: Research Funding; Novartis: Research Funding; Immune Design: Research Funding; Janssen: Research Funding; Merck & Co: Research Funding; Forty Seven: Research Funding; Novartis: Research Funding; Pharmacyclics: Research Funding; Affimed: Research Funding; Astra Zeneca: Research Funding; Pharmacyclics: Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Millennium: Research Funding; Genentech: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Cerhan:Celgene: Research Funding; Jannsen: Other: Scientific Advisory Board; Nanostring: Research Funding. Leonard:Karyopharm: Consultancy; Biotest: Consultancy; Bayer: Consultancy; Pfizer: Consultancy; ADC Therapeutics: Consultancy; Novartis: Consultancy; AstraZeneca: Consultancy; Juno: Consultancy; BMS: Consultancy; Sutro: Consultancy; MEI Pharma: Consultancy; Genentech/Roche: Consultancy; Celgene: Consultancy; Gilead: Consultancy; United Therapeutics: Consultancy.

Abstract Background MBL is a precursor state to CLL, with a prevalence of ~5-8% in the general population and 15-18% in CLL families. To date, 41 single nucleotide polymorphisms (SNPs) have been found to be associated with CLL. We previously showed that a PRS of the weighted average of the number of risk alleles of these SNPs is associated with CLL risk using cases and controls from the International Lymphoma Epidemiology (InterLymph) Consortium. We validated this score in an independent sample of CLL cases and controls from the Genetic Epidemiology of CLL (GEC) Consortium, a cohort of families with ≥2 members with CLL. In the CLL families we also reported an association between the PRS and MBL risk, where 93% of MBLs were low-count MBL. Here we evaluate the PRS in an independent sample ascertained from the Mayo Clinic Biobank. Methods The Mayo Clinic Biobank is a large-scale bio-repository of adult patients assembled to provide a wide array of health-related research studies. Biobank participants (N=2530) were screened for MBL using a highly-sensitive, 8-color (CD38, CD45, Kappa, Lambda, CD19, CD23, CD5 and CD20) flow-cytometry assay on stored cryopreserved peripheral blood mononucleotide cells. Low-count and high-count MBL were defined as those individuals who had <85% and ≥85 clonal B-cells out of total B-cells, respectively. Individuals without MBL ("controls") were frequency matched to MBLs based on age and sex, after excluding non-Caucasian and non-interpretable flow results. Participants were genotyped using the Illumina OmniExpress array. Standard genotyping quality-control metrics were applied. We computed the PRS as previously published and categorized it by quintiles based on values previously used with InterLymph controls. The middle quintile served as the reference category. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CI), adjusting for age at consent, sex, and socioeconomic status. In addition, we compared the median PRS by low-count MBL and high count MBL using the Mann-Whitney U test. Results We identified 276 MBLs overall and 2109 controls; 97% (N=267) of MBLs had low-count MBL and only 3% (N=9) had high-count MBL. We then selected 844 controls frequency matched to the MBL cases on age and sex. Family history of leukemia/lymphoma was 11.3% among MBLs overall and 8.8% among controls. The median PRS was 7.88 and 7.46 (Figure) among MBLs overall and controls, respectively. The continuous PRS had a 1.75-fold increased risk for MBL overall (CI:1.5-2.1, P=2.65x10-12). Compared to the middle quintile, the highest quintile had 2.2-fold increased risk for MBL overall (CI:1.5-3.3, P=1.46x10-4) and the lowest quintile had 0.6-fold decreased risk (CI:0.4-0.96, P=0.03). The median PRS for low-count and high count MBL were 7.86 and 8.04, respectively. The continuous PRS had a 1.75-fold increased risk for low-count MBL (CI:1.5-2.1, P=4.81x10-12) and a 1.89-fold increased risk for high-count MBL (CI:0.8-4.2, P=0.13), however, the effect is not statistically significant between high-count and low-count MBL (P=0.89). Conclusion In this independent sample, we validated our previous findings that the CLL PRS is associated with MBL risk. Although the sample size of high-count MBL was limited (N=9), there is evidence of a weak trend towards a higher PRS compared to low-count MBL and controls Larger sample size of high-count MBL is warranted in order to stratify MBL risk by low-count and high-count MBL. These results may help identify individuals at higher risk of MBL including low-count and high-count MBL, beyond the risk associated with age and family history of CLL. Figure: Polygenic risk score distribution by control and MBL status Figure. Figure. Disclosures Parikh: Janssen: Research Funding; Pharmacyclics: Honoraria, Research Funding; Gilead: Honoraria; Abbvie: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; MorphoSys: Research Funding. Cerhan:Nanostring: Research Funding; Celgene: Research Funding; Jannsen: Other: Scientific Advisory Board. Kay:Janssen: Membership on an entity's Board of Directors or advisory committees; Acerta: Research Funding; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Morpho-sys: Membership on an entity's Board of Directors or advisory committees. Shanafelt:Genentech: Research Funding; Pharmacyclics: Research Funding; GlaxoSmithKline: Research Funding; Jansen: Research Funding.

Abstract Background: The frequency of preventive health practices (PHP), including age-appropriate screening for malignancies and immunizations, and compliance with PHP guidelines in lymphoma survivors is not known. We hypothesized that lymphoma survivors are more compliant with PHP than the general population but PHP rates may differ based on patient, disease and treatment characteristics. Methods: We identified eligible lymphoma patients from the SPORE Molecular Epidemiology Resource (MER) cohort, in which they were prospectively enrolled within <9 months of diagnosis. Survivors self-reported their PHP (colon, breast, and prostate cancer screening and influenza immunization) in the 3-year follow-up questionnaire (FU3). Per US Preventative Task Force guidelines, survivors were considered eligible for colon cancer screening if they were >50 years and compliant if they had fecal occult blood test <1 year or sigmoidoscopy/colonoscopy <10 years of FU3. Eligible female survivors age 50-75 were considered compliant if they had a mammogram after lymphoma diagnosis. Since USPTF recommended against PSA for prostate cancer screening in 2012, males aged 55-69 prior to 2012 were eligible and considered compliant if PSA test was <1 years of FU3. Survivors who received influenza vaccine <1 year of FU3 were considered compliant. Chi-square test was used to compare characteristics of compliant vs non-compliant patients; p value <0.05 was considered statistically significant. Results: Of 4248 lymphoma patients enrolled in the MER from 2002 to 2012, 2038 participants completed FU3. 1105 (54%) were male. The median age at diagnosis was 61 (IQR 51-69) years. There were equal numbers of indolent (N=1002) and aggressive (N=995) histologies with follicular (N=515, 25%) and diffuse large B-cell (N=427, 21%) being the most common. Majority (N=1221, 60%) had advanced stage (Ann Arbor III-IV) disease. 469 (23%) had events prior to FU3 and majority 1777 (88%) had received lymphoma treatment prior to FU3. Of 2038 survivors who completed FU3, 1576 (79%) reported having colon cancer screening in their lifetime. 1328 (91%) of 1570 eligible survivors were compliant, 124 (9%) were not and 118 had missing information. Survivors of age >60 years (93% vs 88%, p<0.001), those with indolent lymphomas (93% vs 90%, p=0.046), or diagnosed between 2010-2012 (94% vs 90% 2002-2009, p=0.007) were more likely to be compliant. There was no difference in colon cancer screening by sex, events prior to FU3 or treatment prior to FU3. 872 (96%) of 933 female survivors reported having a breast exam and 836 (91%) had a mammogram at least once in their lifetime. 495 (96%) of 561 eligible female survivors were compliant, 23 (4%) were not and 43 had missing information. There was no difference in mammographic screening based on age (<=60 vs >60), histology (indolent vs aggressive), events prior to FU3, treatment prior to FU3 or year of diagnosis (2010-2012 vs 2002-2009). 737 (78%) of 1105 male survivors had a PSA test at least once in their lifetime. 115 (71%) of 216 eligible men were compliant, 47 (29%) were not and 54 had missing information. There was no difference in PSA screening by age (<=60 vs >60), histology (indolent vs aggressive), events prior to FU3, and treatment prior to FU3. 1818/2038 (90%) survivors had received an influenza vaccine in their lifetime. 1567 (81%) were compliant, 373 (19%) were not and 98 had missing information. Survivors >60 years of age (87% vs 75%, p<0.001) and those with indolent lymphoma (83% vs 78%, p=0.015) were more likely to be compliant. There was no difference in influenza vaccination by sex, events prior to FU3, treatment prior to FU3, and year of diagnosis (2010-2012 vs 2002-2009). As a comparison in the US general population [Figure], between 2002-2015 the highest rates published by the Center for Disease Control are 62% for colon cancer screening (2015), 75% for mammography (insured, 2003) and influenza vaccination 42% (2015). Per the American Cancer Society, the highest rate of PSA screening was 54% (2010). Conclusion: Lymphoma survivors have high compliance with PHP recommendations compared to the general population. Although older individuals and those with indolent histologies were more likely to receive influenza vaccination and colon cancer screening, this difference was not seen in breast and prostate cancer screening practices. Lymphoma treatment and events did not seem to affect the frequency of PHP among survivors. Figure. Figure. Disclosures Cerhan: Nanostring: Research Funding; Jannsen: Other: Scientific Advisory Board; Celgene: Research Funding.

Abstract Background: B-cell non-Hodgkin lymphomas (NHL) are common lymphoid malignancies in which malignant B-cells arrested at various stages of differentiation proliferate within lymph nodes and occasionally other tissues. The microenvironment that supports the growth and survival of NHL B cells consists of a complex network of immune cells and cytokines and its specific composition has been shown to have significant clinical implications. The intratumoral immune cells include effector and regulatory T (Treg) lymphocytes that are more than simple residual elements from the normal lymph node structure. We previously explored whether the extent of T cell infiltration played a role in the clinical outcome of patients with B-cell NHL and found that an increased percentage of CD4+ T cells in the diagnostic biopsy of lymphoma patients significantly correlated with an improved 5-year overall survival. We have also shown that intratumoral Treg cells significantly suppress the anti-tumor response. Based on the fact that intratumoral T-cells are important in B-cell NHL, we evaluated whether genetic variation in genes that regulate the T-cell response may be associated with lymphoma risk. Methods: We genotyped 257 single nucleotide polymorphisms (SNPs) from 50 candidate genes related to T-cell differentiation and function in a clinic-based study of 441 Caucasian NHL cases and 475 frequency matched Caucasian controls seen at the Mayo Clinic from 2002–2005. Tagging and nsSNPs were selected from HapMap. The most prevalent homozygous genotype was used as the reference group and each SNP was modeled individually as having a log-additive effect, expressed as ordinal odds ratios (OR) per variant allele and 95% confidence intervals, in an age- and sex-adjusted logistic regression analysis. We also evaluated the consistency of the findings for the most common types of B-cell NHL - diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and CLL/SLL. For gene-level analyses, we used principal components (PC) analysis using all SNPs from a gene; those PCs that explained > 90% of the variability were then modeled in a logistic regression analysis and significance was determined using a likelihood ratio test. We also evaluated the association of haplotypes from each gene with risk of NHL using the score test implemented from HAPLO.SCORE. Results. The mean age at diagnosis was 60.1 years for cases and 58% were male; among controls, the mean age at enrollment was 61.7 years and 55% were men. In the PC gene analyses, PRF1 (perforin gene - involved in cytotoxicity; p=0.004), CD276 (B7-H3 gene - involved in co-stimulation; p=0.01), TBX21 (T-bet gene – regulates Th1 cell development; p=0.02), and IL6 (p=0.02) were significant at p<0.05; haplotype analysis showed similar results, with the addition of CARD15 (NOD2 gene – regulates Th1 responses; p=0.02). There were 2 SNPs in PRF1, and both the intronic SNP rs3758562 (OR=1.38; 1.13–1.69) and the synonymous coding SNP rs885821 (OR=0.80; 0.63–1.02) were associated with NHL risk overall and for each subtype. There were 2 SNPs in CD276, and both the intronic SNP rs7176654 (OR=1.29; 1.07–1.56) and the mrna-utr SNP rs3816661 (OR=0.82; 0.68–0.99) were associated with NHL risk overall and with the CLL/SLL and follicular NHL subtypes specifically. There were 2 SNPs in TBX21, and only the mrna-utr SNP rs7502875 (OR=0.73; 0.59–0.92) was associated with NHL risk overall and for each subtype. There were 11 SNPs in IL6, and the intronic SNP rs2069835 (OR=1.88; 1.24–2.84) and the locus-region SNP rs2069824 (OR=1.73; 1.20–2.50) were each associated with NHL risk overall and each subtype. Finally, there were 9 SNPs in CARD15, with only the nonsynonymous coding SNP rs5743291 (OR=1.43; 1.02–1.98) being associated with overall NHL risk, and risk was specific to FL. Conclusions. Genetic variation in several genes that play critical roles in T-cell maturation and function was associated with lymphoma risk. These genes appeared to be associated with the differentiation and function of effector T-cells particularly Th1 and Th17 cells. These results provide potentially important insights into the role of T-cells in lymphomagenesis.

Abstract Background: Reactive oxygen species cause DNA damage and altered immunologic responses, and have been linked to the development of NHL. Diets rich in fruits and vegetables are excellent sources of antioxidants, and vitamins C, E, polyphenols, and carotenoids, along with selected micronutrients such as zinc are thought to be responsible for most of the antioxidant activity in foods. We evaluated the hypothesis that vegetables, fruits and nutrients involved in antioxidant activity would protect against developing NHL. In a secondary analysis, we also assessed heterogeneity of this hypothesis for the most common subtypes of NHL: chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL), follicular lymphoma, and diffuse large B cell lymphoma (DLBCL). Methods: We evaluated dietary antioxidant intake and NHL risk in a clinic-based study of 416 newly diagnosed NHL cases and 926 frequency-matched controls enrolled at the Mayo Clinic from 2002–2007. Usual diet two years before diagnosis/enrollment was assessed using a self-administered, 128-item food frequency questionnaire. Dietary intake of antioxidants was estimated using the Food Processor SQL system, further supplemented with data from US Department of Agriculture nutrient databases. Unconditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CI), adjusted for age, sex, residence, and total energy. NHL subtypes were centrally reviewed, and subtype-specific risks were estimated using polychotomous logistic regression. Results: The mean age at diagnosis was 60.8 years for cases and 57% were male; for controls, the mean age at enrollment was 60.8 years and 54% were men. NHL risk was inversely associated with intake of total vegetables (OR for highest compared to lowest quartile, 0.46; 95% CI 0.32–0.68; p-trend<0.001), and specifically green leafy (OR=0.54; 95% CI 0.39–0.76; p-trend<0.001) and cruciferous (OR=0.62; 95% CI 0.43–0.88; p-trend=0.02) vegetables, but not legumes or red/yellow/orange vegetables. There was no association with total fruit intake or intake of citrus fruits in particular. When modeled together, the association for green leafy vegetables was unchanged while the association for cruciferous vegetables attenuated (OR=0.75; 95% CI 0.50–1.13; p-trend=0.3). Higher intake of total vitamin A (OR=0.60; 95% CI 0.41–0.88; p-trend<0.001) and vitamin E (OR=0.53; 95% CI 0.34–0.82; p-trend<0.001), but not vitamin C, were associated with lower NHL risk. For vitamin A, there was no association with preformed Vitamin A, but there was an inverse association with beta-carotene (OR=0.56; 95% CI 0.39–0.81; p-trend<0.001); only weak inverse associations were observed for other carotenoids (lutein/zeaxanthin, lycopene, and cryptoxanthin). When modeled together, the inverse association for vitamin E was unchanged while the association for beta-carotene attenuated. For micronutrients, there were inverse associations for manganese (OR=0.60; 95% CI 0.40–0.90; p-trend=0.02), selenium (OR=0.47; 95% CI 0.27–0.80; p-trend=0.01), and zinc (OR=0.46; 95% CI 0.27–0.80; p-trend<0.001) but not copper; when modeled simultaneously, both manganese (p-trend=0.03) and zinc (p-trend=0.02) remained significantly and inversely associated with NHL risk. Further adjustment for education, family history of NHL, smoking, alcohol use, and body mass index did not alter these results. There was no NHL subtype heterogeneity for the associations with total vegetables, green leafy vegetables or vitamin E, while inverse associations were not observed for manganese and follicular lymphoma or zinc and CLL/SLL. Conclusion: Higher intakes of vegetables, particularly green leafy vegetables, vitamin E, manganese, and zinc were associated with lower risk of NHL. These finding extend a growing literature from case-control and cohort studies that support a protective role of foods and nutrients that function in antioxidant related pathways against development of NHL, and therefore may represent one of the few known modifiable risk factors for this cancer.

Abstract Abstract 775 Introduction: WW has been an initial strategy for advanced stage FL because randomized trials showed no clear benefit for immediate initiation of therapy with single agent alkylators when compared to deferring therapy (Brice, JCO 1997; Ardeshna, Lancet 2003), although a recent trial raises questions about WW in the era of rituximab (R) based frontline therapies (Ardeshna, ASH Meeting 2010). Methods: The NLCS is a prospective, multicenter, observational study collecting data on 2,738 newly diagnosed pts with FL diagnosed from 2004–2007 at 265 US sites (80% non-academic). Initial management decisions were made by the treating physician and were categorized as WW (for pts who did not receive therapy in the 90 period following diagnoses and were coded by physicians as WW) or active therapy (AT) including: R alone, R-chemotherapy (RChemo), or other. Baseline clinical factors and treatment setting were compared for WW and AT pts using multivariable logistic regression. Kaplan-Meier (KM) estimation and Cox models were used to evaluate progression-free survival (PFS), time to 2nd and 3rd line management strategy (TT2, TT3), transformation-free survival (TFS), PFS following 1st AT, and overall survival (OS). Due to differences between WW and AT groups, adjusted Cox regression models are presented for the primary analysis of study endpoints controlling for sex, community vs. academic practice site, FL grade, and FLIPI. All time to event analyses were calculated from the 90 day period following diagnosis to allow enrollment in WW, and PFS was calculated from the starting point to the clinician's recording of progressive disease (PD) or death. Results: Among 1,737 pts presenting with stage III/IV FL in the analysis population, 237 underwent WW and 1,500 received AT immediately following diagnosis including: 241 pts treated with R, 1046 with RChemo, 26 with radiation, and 187 other therapies. Multivariable logistic regression demonstrated that the following pt characteristics were predictive of selection of WW rather than initial AT: age > 60 years, no B-symptoms, FL grade 1 or 2, ECOG PS = 0, ≤1 extranodal sites involved, and LDH ≤ULN (all p < 0.05). Median PFS and TT2 were 27 and 35 months for WW, and 64 months and not reached for AT. With a median follow-up of 55 months, 17% of WW pts and 19% of AT pts have died, with no significant difference in OS between WW and AT (p = 0.31). Compared with WW, RChemo improved PFS: adjusted Hazard Ratio (HR) = 0.36, TFS: HR=0.65, TT2: HR=0.48, and TT3: HR=0.53, all p<0.01. For most of the 145 WW pts that later initiated an AT, PD was recorded as the reason for treatment (83%). ATs following WW were: R (51, 35%), RCVP (21, 14%), RCHOP (16, 11%), R + other chemo (23, 16%), investigational (15, 10%), chemo alone (9, 6%), radiation (8, 6%), BMT (1, 1%), or other therapy (1, 1%). The median PFS for R was 42 months when given at diagnosis and 55 months when given following WW. The median PFS for RChemo was 71 months when given at diagnosis and 37 months when given following WW. After adjustment for FLIPI, FL grade, sex, practice setting, and type of treatment, WW adversely affected PFS following 1st AT, H=2.02, p <0.0001. Conclusions: FL pts in the US who undergo initial WW are treated at a median of nearly 3 years. Median PFS following RChemo, but not R is shorter when utilized after period of WW than at diagnosis – albeit in different clinical circumstances. Additional follow-up is needed to assess the tradeoff of this time without therapy with as yet no observable differences in OS. Disclosures: Sinha: CELGENE: Research Funding. Friedberg:Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees. Link:Genentech: Consultancy. 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 Massively parallel sequencing analyses have revealed a common mutation within the MYD88 gene (MYD88L265P) occurring at high frequencies in many non-Hodgkin lymphomas (NHL) including the rare lymphoplasmacytic lymphoma, Waldenström’s macroglobulinemia (WM). Using whole exome sequencing, Sanger sequencing and allele-specific PCR, we validate the initial studies and detect the MYD88L265P mutation in the tumor genome of 97% of WM patients analyzed (n=39). MYD88L265P was detected at lower frequencies in other indolent lymphomas including LPL (0%), MALT (4%), nodal MZL (5%) and splenic MZL (8%); all but one MYD88L265P was heterozygous. Due to the high frequency of MYD88 mutation in WM and other NHL, and its known effects on malignant B cell survival, therapeutic targeting of MYD88 signaling pathways may be useful clinically. However, while the effects of MYD88L265P on the activity of IRAK1/4 and NF-κB are have been studied previously, we are lacking a thorough characterization of the role of intermediary signaling proteins such as TRAF6 and TAK1 on the biology of MYD88L265P-expressing B cells. A better understanding of the proteins involved in MYD88L265P signaling may lead to the development of more targeted and effective therapeutic approaches. In an attempt to identify MYD88L265P –specific therapeutic targets we first wanted to characterize the role of intermediary signaling proteins that facilitate the downstream activation of NF-κB. Upon activation of TLRs or IL-1b receptors, MYD88 forms a homodimer and recruits IRAK1/4 and TRAF6 into a complex resulting in association and phosphorylation of TAK1 followed by activation of NF-κB. We monitored the formation of a complex comprised of MYD88, IRAK1, IRAK4 and TRAF6 and immunoprecipitation of either endogenous IRAK4 or IRAK1 revealed constitutive association of IRAK with TRAF6 and MYD88L265P. To assess if the formation of a MYD88L265P/IRAK/TRAF6 complex results in downstream activation of TAK1, constitutive TAK1 phosphorylation was measured and detected in all three cell lines that express MYD88L265P. An association between TAK1 and TRAF6, another measure of TAK1 activation, was also detectable. When a similar analysis of TAK1 was performed in DLBCL cells expressing wild-type MYD88, no phosphorylation of TAK1 was detected, nor was TAK1 associated with TRAF6. IRAK1, IRAK4, TAK1, TRAF6, and MYD88 were expressed at similar levels in all cell lines studied and therefore did not contribute the differences in MYD88 complex formation observed between cell lines. These studies were further confirmed using HEK 293T cells that were transduced with either a vector control plasmid or HA-tagged MYD88WT or MYD88L265P expression plasmids. Together, these studies suggest that MYD88L265P forms a complex with IRAK and TRAF6 resulting in constitutive activation of TAK1 and NF-κB. To confirm the significance of TAK1-mediated MYD88L265P signaling on lymphoma cell growth, the effect of the selective TAK1 inhibitor, (5Z)-7-Oxozeaenol, on cell proliferation was tested. All MYD88L265P-expressing cell lines were sensitive to TAK1 inhibition in a dose-dependent manner (0-10 μM). In contrast, NHL cells expressing MYD88WT were found to be insensitive to TAK1 inhibition. We next tested the impact of the TAK1 inhibitor on a MYD88L265P positive WM patient sample. Similar to what was seen in the WM cell lines, the TAK1 inhibitor inhibited WM cell growth and survival in a dose dependent manner. Additionally, the TAK1 inhibitor significantly reduced the level of IL-10 secreted by each of the cell lines. Together, these data suggest that MYD88L265P drives cell proliferation and cytokine secretion through a TAK1-dependent mechanism. In conclusion, we are the first to validate by NGS in a large patient cohort the high prevalence and specificity of MYD88L265P in WM. Cells harboring the L265P mutation but not wild-type MYD88 exhibit constitutive signaling leading to the hyperactivation of NF-κB. We have established the role of TAK1 as an integral component of MYD88L265P signaling in both WM and DLBCL cell. Our data suggest that targeting TAK1 clinically may be an effective strategy for the treatment of WM and other lymphomas driven by MYD88L265P signaling. Disclosures: Fonseca: millennium: Consultancy; amgen: Consultancy; Binding site: Consultancy; onyx: Consultancy; medtronic: Consultancy; Genzyme: Consultancy; Otsuka: Consultancy; Celgene: Consultancy; lilly: Consultancy; Onyx: Research Funding; cylene: Research Funding.

Abstract Background: Elevated serum BLyS levels have been found in patients with both malignant and autoimmune diseases when compared to those of healthy donors, suggesting that BLyS may play a pathogenic role. While it is clear that BLyS expression is required for normal B cell development and homeostasis, the mechanistic details underlying control of BLyS expression remain to be defined. In previous work we found that a single nucleotide polymorphisms (SNP) in the BLyS promoter (−871C→T) resulted in increased BLyS transcription suggesting that genetic variation in the BLyS gene may influence its expression. Because elevated BLyS levels have been detected in patients with NHL we wanted to determine if additional SNPs in the BLyS gene were associated with high serum BLyS levels and risk of developing of NHL. Methods: We genotyped 9 tagSNPs within the BLyS gene in a clinic-based study of 441 incident Caucasian NHL cases and 475 frequency matched Caucasian controls seen at the Mayo Clinic from 2002–2005. We evaluated the association of individual SNPs as well as haplotypes from the BLyS gene with risk of NHL. We also jointly tested the main effects for all independent (r2<0.25) SNPs using a multivariate logistic regression (MLR) model. As a secondary analysis, for those SNPs showing significant results (< 5% significance), we evaluated associations between those who had all high risk alleles at the SNPs of interest compared to those who had all low risk alleles at the SNPs of interest. Additionally, we evaluated serum BLyS levels by ELISA in these same subjects. Serum BLyS levels were detemined by ELISA. Results: In the individual single SNP logistic regression analysis, 3 of the 9 tagSNPs were significant at p<0.05. Haplotype and MLR results were nonsignificant. However, when we categorized participants into low and high risk groups based on risk alleles at the three statistically significant SNPs, we found the high risk variant had an odds ratio (OR) of 2.086 (p=0.0001) for risk of B-cell NHL. When the analysis was restricted by histologic subtype we found that diffuse large B-cell lymphoma or follilcular lymphoma grade 3 had an OR of 3.163 (p=0.01), follicular lymphoma grade I/II had an OR= 2.547 (p=0.046), and chronic lymphocytic leukemia (CLL) had an OR=1.238 (p=0.13). Because there was not a significant correlation of the high risk variant with CLL, we performed an additional analysis in which we included all B cell NHL cases excluding CLL and the OR was 2.799 (p=0.0001). We next wanted to determine if serum BLyS levels correlated with either the high or low risk variant. The mean serum BLyS level in those individuals (untreated cases and controls) who carried the low risk variant at all three SNPs was significantly lower (p=0.0061) at 1.3 ng/ml (n=25, range: undetectable-4.4 ng/ml) compared to 4.3 ng/ml in those with the high risk variant (n=74, range: undetectable- 66.8 ng/ml). Conclusions: In summary, we have found that genetic variation in the BLyS gene is significantly associated with an increased risk of developing B-cell NHL, particularly follicular and large B-cell lymphoma. Further, we found that genetic variation is also associated with an increase in serum BLyS levels.Taken together, our data further highlight the role of the BLyS gene in B cell malignancies and characterization of the precise genetic and environmental mechanisms that regulate BLyS may have significant clinical impact.