Vachon, Celine M.

Abstract Monoclonal gammopathies, including multiple myeloma (MM), represent a group of plasma cell (PC) disorders that comprise of mostly incurable hematopoietic malignancies with an increasing incidence in the US. Previous epidemiological studies demonstrated a 2-3 fold higher incidence of monoclonal gammopathy of undetermined significance (MGUS) and a similarly higher incidence of MM along with a ~4-year younger age of onset among African Americans (AA) compared to European Americans (EAs) (Fonseca, Leukemia, 2017). This suggests a possible ancestral-associated genetic predisposition of AAs to the development of monoclonal gammopathies (Landgren, Blood, 2006). When access to care is equal, AAs have a better overall survival compared to EAs suggesting that AAs may have a genetic predisposition that renders them better responders to treatment or have more favorable cytogenetic subtypes of MM (Waxman, Blood, 2010). Previous efforts to understand this disparity have relied on self-reported race rather than genetic ancestry. We hypothesize that quantifying genetic ancestry is necessary to fully understand the genetic mechanisms of racial disparities of monoclonal gammopathies. We describe our study of 881 patients with monoclonal gammopathies who had undergone uniform testing to identify MM-specific cytogenetic abnormalities. DNA from the bone marrow samples was genotyped on the Precision Medicine Research Array. Biogeographical ancestry was assessed using the Geographic Population Structure Origins tool, which provides the ancestral breakdown of 36 admixture components for each individual representing different geographic regions and outputs admixture proportions corresponding to those ancestries (Elhaik, Nat Commun, 2014). We evaluated whether an increase in the percentage of African Ancestry altered the odds of any primary cytogenetic abnormality. We demonstrated that a 10% increase in the percentage of African ancestry was associated with a 6% increase in the odds of detecting either an t(11;14), t(14;16) or t(14;20) (odds ratio = 1.06, 95% CI: 1.02 - 1.11; p-value = 0.05). Although we observed an increase in the odds of each of the individual translocations with 10% increase in African ancestry, l t(11;14) (OR=1.03) t(14;16) (OR=1.11) and t(14;20) (OR=1.10), these three abnormalities were combined to achieve greater statistical power. The differences in cytogenetic abnormalities were most striking among individuals with ≥80.0% African (n=120) compared to individuals with <0.1% African ancestry (n=235). Using these cutoff values comparing the ≥80.0% and <0.1% African ancestry cohorts, there was a higher prevalence of t(11;14), t(14;16) and t(14;20) (51% vs. 33%, respectively, p-value=0.008) and a lower prevalence of trisomies (with or without IgH translocations) (48.3% vs. 61.3%, respectively, p-value=0.066). In addition, the ≥80% African ancestry cohort also displayed a slightly lower prevalence of monosomy 13/13q deletion compared to the cohort with <0.1% African ancestry (34.2% vs. 38.7%, respectively, p-value=0.021). Further, we observed a significantly higher prevalence in the proportion of females with monoclonal gammopathies among the ≥80% African ancestry cohort compared to the cohort with <0.1% African ancestry (56.7% vs. 42.1%, respectively, p-value=0.028). We complement our past studies that relied on self-reported race and characterized patients' demographic and uniformly collected cytogenetic data in relation to genetically defined African ancestry. We demonstrate the prevalence of having one of three specific subtypes (i.e., t(11;14), t(14;16), or t(14;20)) was significantly higher in those with highest (≥80%) compared to lowest (<0.1%) African ancestry demonstrating African ancestry is associated with a subtype distribution of MM that differs from non-African individuals. These differences were only revealed after analysis of individuals with the highest and lowest percentage of African ancestry. Since 38.3% of the individuals with ≥80% African ancestry have the favorable t(11;14) translocation (in comparison to 26.8% of <0.1% African individuals), this finding may explain improved survival with equal access to care. Understanding the genetic mechanisms of this disparity is a fundamental step to understanding differences in incidence and outcomes of patients with monoclonal gammopathies. Disclosures Elhaik: DNA Diagnostics Center: Consultancy. Baird:DNA Diagnostics Center: Employment. Cerhan:Jannsen: Other: Scientific Advisory Board; Nanostring: Research Funding; Celgene: Research Funding. Stewart:Amgen Inc., BMS, Celgene, Takeda, Roche, Seattle Genetics, Janssen, Ono: Consultancy; Amgen Inc., Celgene, Roche, Seattle Genetics: Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Kumar:Novartis: Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding.

Abstract Introduction The 2-3 fold excess risk of multiple myeloma (MM) among family members of cases suggests a heritable contribution to risk. Recently, a genome-wide association study (GWAS) identified two genome-wide significant and one promising novel loci associated with multiple myeloma risk. To confirm these associations and identify additional novel risk loci, we performed a four-center, genome-wide association meta-analysis. Methods A fixed effects model was used for the meta-analysis which included a total of 1248 cases and 1485 controls, all of European descent, genotyped and analyzed at four separate centers with samples contributed by 10 studies. After quality control and imputation using the 1000 Genomes Project, the analysis included ∼9.5 million variants (λ=1.024). Associations between (single nucleotide polymorphisms) SNP genotypes and MM risk were evaluated under a log-additive model of inheritance, with each study adjusting for age, sex, and up to 10 principal components to control for population stratification. Promising results were replicated in an independent set of 1587 cases and 1770 controls using TaqMan, for a total of 2835 and 3255 cases and controls, respectively, in a combined meta-analysis. Results The discovery meta-analysis did not reveal any genome-wide significant associations (defined as p<5 x 10-8). We used a novel pruning algorithm to identify the top 35 most promising single nucleotide polymorphisms (SNPs) to advance to replication. We successfully genotyped 22 SNPs in the replication set. In the combined discovery and replication meta-analysis, rs1345359 at 12q23.1 was the most strongly associated SNP (P=9 x 10-8, Table 1). The variant allele C was associated with reduced risk (odds ratio discovery set [OR]= 0.69, OR replication set = 0.78, OR combined = 0.74). A second locus at 20q13.2 (rs150220835), was associated with a two-fold increased risk (P=1.22 x 10-6), a borderline increased risk (P=0.0900) and 45% increased risk (P=2.44 X 10-5) in the discovery, replication, and combined analysis sets respectively (Table 1). We also confirmed the association between MM risk and two previously published SNPs (rs4487645, p=0.0007and rs105251, p=0.0044) (Broderick et al., Nat. Genet., 2011). The third previously suggested SNP (rs6746082) was of nominal significance (p=0.0517) in the meta-analysis. Discussion We confirmed the association between MM risk and two previously published SNPs and identified a possible association with a novel SNP in chromosome 12q23.1 (rs1345359). This SNP is not located in a gene nor associated with biofeatures in ENCODE, thus further examination of correlated SNPs is necessary to identify a functional SNP linked to this locus. We also found suggestive evidence for a second locus at 20q13.2 requiring additional replication. Larger studies would improve risk variant discovery for this rare hematologic malignancy. Disclosures: Wolf: Celgene: Honoraria, Research Funding; Millenium: Honoraria; Onyx: Honoraria. Anderson:Celgene, Millennium, BMS, Onyx: Membership on an entity’s Board of Directors or advisory committees; Acetylon, Oncopep: Scientific Founder , Scientific Founder Other.

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 KaLwRij/C57Bl (KaLwRij, “Kal-ridge”) is a spontaneous mutant mouse strain predisposed to monoclonal gammopathy of uncertain significance (MGUS) and parallels many features of human pathology including progression to multiple myeloma (MM). In African Americans, an increased prevalence of MM is due to an increased risk of MGUS development (rather than increased rate of progression from MGUS) and is likely therefore mediated by germline MGUS risk alleles. In both humans and mice, the genetic basis for MGUS/MM risk is unknown. We sought to identify the genetic basis for MGUS/MM risk in KaLwRij mice to shed light on genes or pathways that might mediate risk in humans. We employed a novel integrative computational analysis, combining KaLwRij/B6 modified haplotype block analysis and low-power human MM/control single nucleotide polymorphism (SNP) data. We used high-density SNP arrays to establish genetic distances of KaLwRij from 11 another diverse inbred strains and confirmed close homology to parent C57Bl/6. Haplotype block analysis identified genetic loci that diverged from C57Bl/6 and included over 500 genes. We filtered the haplotype list using previously published RNA expression data from the bone marrow of C57Bl/6 and KaLwRij mice, to identify 71 differentially expressed genes. As a final filter, we used SNP data from a genome wide association study (GWAS) of human Caucasian MM case and normal volunteer samples (∼300 each) to identify SNPs differentially represented in MM patients. Combining these sets yielded four (4) candidate genes. Our top candidate, Samsn1 (Hacs1), is a negative regulator of B-cell activation and interestingly, was first identified as a gene differentially expressed in MM. Strikingly, we found that KaLwRij mice had a complete germline deletion of the Samsn1 gene. Samsn1 is expressed within the hematopoetic compartment, including B-cells, macrophages, and osteoclasts (OC), key cell types that participate in MM pathology. Consistent with the reported inhibitory function of SAMSN1, KaLwRij had enhanced naïve B-cell response and constitutive Lyn phosphorylation. Further, we found that KaLwRij macrophages and OC also have constitutive Lyn activation consistent activation of cytokine signaling pathways in stromal cells. Absence of Samsn1 may lead to unregulated B-cell and macrophage/OC activation, priming both a pro-tumor bone microenvironment and B-cells for development of MGUS and predisposition to MM. Our approach focused on germline loci rather than malignant cell genetic alterations, advancing our understanding of host predisposition. Identification of the gene or genes predisposing patients to MGUS/MM will provide novel targets for identifying at-risk individuals and will potentially allow the develop of preventative therapeutics for MM. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 2443 Background: There is strong and consistent evidence that a genetic component contributes to the etiology of chronic lymphocytic leukemia (CLL). A recent genome-wide association (GWA) study of CLL identified genetic variants located on chromosomes 2q13, 2q37.1, 6p25, 11q24, 15q23, and 19q13 that increased the risk of CLL within a European population. We replicated 5 of these 6 loci in an independent sample of CLL cases and controls from the United States. We now investigate whether these loci also influences MBL, a reported precursor condition of CLL. In addition, a follow-up analysis of the initial GWA study identified four more CLL-susceptibility loci on 2q37.3, 8q24.21, 15q21.3, and 16q24.1. Herein, we also evaluate the association of these four loci with risk of CLL. Methods: Peripheral blood samples were obtained from three ongoing studies: the Genetic Epidemiology CLL (GEC) Consortium, the Mayo Clinic non-Hodgkin lymphoma (NHL)/ CLL study, and the Mayo Clinic Biobank. We implemented rigorous genotyping quality-control measures, and successfully genotyped a total of 407 CLL patients, 965 controls, and 60 MBLs from these studies. Within each locus, the previously reported single nucleotide variants (SNPs) or variants in high linkage disequilibrium (LD) with the previously reported SNPs were evaluated with risk of MBL or CLL. Tests for association was done using the Cochran-Armitage trend test, and unconditional logistic regression was used to estimate odds ratios (ORs) and corresponding 95% confidence intervals (CIs) for CLL or MBL risk Results: In our evaluation of the six initially reported CLL-susceptibility loci (2q13, 2q37.1, 6p25, 11q24, 15q23, and 19q13) with MBL risk, we found three of the six had suggestive associations (p-value < 0.20) with ORs comparable to and in the same direction as those observed from CLL risk. Our strongest finding was with rs13397985 at locus 2q37.1 (OR= 1.56; 95% CI: 1.05, 2.31; p-trend = 0.041), followed by rs17483466 at locus 2q13 (OR= 1.49; 95% CI: 0.99, 2.24; p-trend = 0.074). As expected given our previously reported findings with CLL risk, the association between rs11083846 on chromosome 19q13 and MBL risk was not significant (p-trend = 0.70). Of the four recently reported CLL-susceptibility loci SNPs located on 2q37.3, 8q24.21, 15q21.3, and 16q24.1, we found all to be associated with CLL risk but one. Specifically, the strongest association was seen for locus 8q24.21 (best tagged SNP rs1021955; OR = 1.37; 95% CI: 1.10, 1.70; p-trend = 0.005), followed by locus 16q24.1 (best tagged SNP rs305065; OR= 0.77; 95% CI: 0.61, 0.97; p-trend = 0.024). However, we found no associations for locus 15q21.3 for the previously reported SNP nor for any SNPs in LD with the previously reported SNP. Conclusions: Our MBL results provide additional robust genetic evidence that MBL is a precursor to CLL and that it shares similar underlying genetic predisposition. Also our results confirm three of the four recently reported CLL-susceptibility loci and further support the role of a genetic basis in the etiology of CLL. More research is needed to elucidate the potential manner in which these genetic loci function in CLL or MBL. Disclosures: No relevant conflicts of interest to declare.

Abstract Background: It is well established that the incidence of skin cancers in patients with CLL are significantly elevated compared to age- and sex- matched controls. However, little is known about the characteristics of CLL patients who develop skin cancer. Herein, we evaluate the associations of CLL clinical and prognostic characteristics, along with UV radiation exposure, with risk of first skin cancer following CLL diagnosis. Methods: Newly diagnosed CLL patients from Minnesota, Iowa, and Wisconsin were enrolled in the Mayo Clinic case-control study from 2002-2015 and systematically followed in the Iowa/Mayo Lymphoma SPORE. Clinical and prognostic CLL data were obtained from the Mayo Clinic CLL database, and skin cancer clinical data were abstracted from medical records using a standard protocol. The CLL international prognostic index (CLL-IPI) was computed using a weighted average of five independent CLL prognostic factors (IGHV mutational status, serum b2-microglobulin, Rai stage, age, and FISH 17p deletion/TP53 status). Self-reported history of midday sun exposure at various ages (birth to age 12; 13 to 21 years; 22 to 40 years, and 41+ years) was obtained from a risk factor questionnaire. For each age, we asked the extent of mid-day sun as: practically no exposure (under 3 hours per week), little exposure (4-7 hours per week), moderate exposure (8 to 14 hours per week) and extensive exposure (15+ hours per week). Midday sun exposure was modeled as an ordinal covariate. To evaluate associations with risk of skin cancer following CLL diagnosis, we calculated time from date of CLL diagnosis to date of first skin cancer, death, or last known follow-up. We used Cox regression analysis to estimate hazard ratios (HRs) and 95% CIs. CLL treatment was considered a time-dependent covariate. Results: Among 846 CLL patients enrolled, the median age at diagnosis was 63 years (range 28-91), 68% were male, 7% had Rai stage III-IV at diagnosis. Based on the CLL-IPI, 42% were categorized as low risk, 33% as intermediate risk, and 25% as high or very-high risk. 109 CLL cases (13%) had one or more reported skin cancers at or prior to CLL diagnosis. Melanoma was observed in 19 (2%) cases and non-melanoma was in 90 (11%) cases. At a median follow-up of 7 years from CLL diagnosis, 165 patients (20%) had one or more skin cancers after CLL diagnosis. Among these patients, 49 had skin cancer before CLL diagnosis. The most frequent skin cancer was squamous cell carcinoma (59%), followed by basal cell (31%), melanoma (5%), and Merkel cell (1%). 552 (65%) of the 846 patients returned a questionnaire. Significant associations of clinical and prognostic characteristics with risk of first skin cancer were observed for age (HR=1.35 per 10 year increase, 95% CI=1.17-1.56, P<0.001), male sex (HR=1.38, 95% CI 0.98-1.96, p=0.07), prior history of skin cancer (HR=4.19, 95% CI=2.98-5.88, P<0.001), and CLL-IPI (HR=1.26, 95% CI= 1.03-1.54, P=0.026, after adjusting for age, sex, and prior skin cancer). Of note, the risk of first skin cancer in those CLL patients categorized as very high via CLL-IPI had 2.28 fold risk (95% CI 1.02-5.11). Midday sun exposures for each of the ages considered showed no evidence of association with risk of first skin cancer (all P>0.05). 50 CLL patients were treated prior to first skin cancer following CLL diagnosis; we observed no evidence of association between treatment and risk of first skin cancer (HR=1.44, 95% CI= 0.93-1.92, P=0.12). Conclusion: CLL patients who are at an increased risk of skin cancer following CLL diagnosis are those who either have had a prior history of skin cancer or a more aggressive CLL disease at diagnosis, according to CLL IPI. Routine skin cancer screening is currently recommended for CLL patients. Our data suggest that more frequent screening would be particularly important among patients with aggressive CLL and who have a prior history of skin cancer. Unexpectedly, we found no evidence of association of skin cancer risk with UV radiation following CLL diagnosis or with CLL treatment. Further investigation is needed to determine whether other factors increase the risk of skin cancer following CLL diagnosis. Disclosures Shanafelt: Genentech: Research Funding; GlaxoSmithkKine: Research Funding; Janssen: Research Funding; Celgene: Research Funding; Cephalon: Research Funding; Pharmacyclics: Research Funding; Hospira: Research Funding.

Abstract We and others previously demonstrated an increased risk of monoclonal gammopathy of undetermined significance (MGUS) in first-degree relatives of multiple myeloma (MM) and MGUS patients, underscoring a familial component to this disease. However, MM is known to be a collection of cytogenetically distinct diseases, with 40-50% of MM cases having a reciprocal translocation involving the IgH locus on chromosome 14q32 and in many of the remaining patients, trisomies. In a small proportion of cases, both IgH abnormalities and trisomies are found in the same clone. These MM cytogenetic subtypes are associated with differential prognosis. Whether there are differences in familial risk by cytogenetic subtypes is not known. Patients with MM were recruited from the Mayo Clinic Hematology practice in Rochester, Minnesota (MN) between 2005 and 2015. Serum samples were collected from first-degree relatives and subjected to electrophoresis and immunofixation for MGUS determination. Age- and sex-specific rates of MGUS from the population-based Olmsted County, MN, prevalence study were used as expected rates for the calculation of risk ratios (RRs) for comparisons of first-degree relatives. Cytogenetic subtypes were classified by FISH testing performed in the clinic and categorized into groups defined by IgH translocation , trisomy, intermediate/ high-risk disease (t(4;14), t(14;16), t(14;20), and del17p). Further, the distribution of cytogenetic subtypes was compared between MM cases with and without evidence of MGUS in first degree relatives using Chi square tests. Analyses were also subset to MM probands diagnosed in MN. There were a total of 442 MM probands, with 1235 first-degree relatives recruited and eligible for the study. MGUS was detected in 78 relatives, for an age- and sex-adjusted prevalence of 6.1% (4.7%-7.5%). Analyses comparing prevalence of MGUS in first degree relatives to population-based rates from Olmsted County showed a 2.5-fold (95% CI=1.9-3.0) increased prevalence. When performing analyses among MN probands only (RR=2.9; 95% CI=2.1-3.8), results were similar. Of the 442 probands, 310 had FISH performed on plasma cells (identified by cIG staining; cIg-FISH) at diagnosis. Of these cases, 49% had a trisomy, 23% had an IgH translocation, and 9% had both. Although the proportion of trisomies and IgH translocations were 4-6% higher among MM probands with a relative with MGUS compared to those without, these differences were not statistically significant (Table 1). MM probands with a first degree relative with MGUS also had a similar proportion of cytogenetic subtypes that are considered of intermediate or high risk compared to those MM without a family history (26.9% vs 25.2%) (p=0.79) (Table 1). When restricted to MM probands from MN, results remained non-statistically significant (Table 1). We showed an increased risk of MGUS in first-degree relatives of MM cases, implying shared environment and/or genetics underlying this malignancy. However, we did not find an association between family history of MGUS in MM probands and the cytogenetic subtypes examined. Larger cohorts are needed to examine if a relationship exists between cytogenetic subtypes of MM and familial risk. Disclosures Kumar: Noxxon Pharma: Consultancy, Research Funding; Array BioPharma: Consultancy, Research Funding; AbbVie: Research Funding; Onyx: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Glycomimetics: Consultancy; Kesios: Consultancy; Janssen: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Research Funding; BMS: Consultancy.

Abstract Multiple myeloma (MM) is a malignancy of plasma B-cells that is invariably preceded by monoclonal gammopathy of undetermined significance (MGUS), a pre-neoplastic plasma cell proliferative disorder. C57Bl/KaLwRij (KaLwRij) is a spontaneous inbred mouse strain predisposed to benign idiopathic paraproteinemia (BIP), a plasma cell dyscrasia that parallels many features of human pathology including progression to myeloma. In both humans and mice, the genetic basis for MGUS/MM risk is unknown. We sought to identify the genetic basis for MGUS/MM risk in KaLwRij mice to shed light on genes or pathways that mediate disease risk in humans. Using an integrative approach, we combined KaLwRij x B6 haplotype analysis (418 genes) and a MM patient association study (180 genes) to identify five candidate genes likely to contribute to both murine BIP-susceptibility and human MM risk. Surprisingly, we found KaLwRij mice had homozygous germline deletion of one of the five candidate genes, Samsn1, a putative negative regulator of B-cell activation. Consistent with the reported inhibitory function of SAMSN1 in B-cells, KaLwRij mice had enhanced naïve B-cell response in vitro following stimulation with IL4 and LPS and in vivo following immunization. We found that re-expression of Samsn1 in KaLwRij-derived myeloma cell line 5TGM1 decreased MM tumor growth in vitro, suggesting that loss of Samsn1 contributes to tumor growth in part through a cell intrinsic mechanism. Importantly, germline risk alleles may also influence cell types beyond the pre-malignant B-cells. It is established that the host environment also plays a critical role in supporting myeloma growth in KaLwRij mice. We found that Samsn1 is highly expressed in macrophages, but not in other MM-supportive cell types including osteoclasts and bone marrow stromal cells. Myeloma-associated macrophages play critical roles in supporting tumor growth and are broadly classified as anti-tumor M1 macrophages and tumor-promoting M2 macrophages. Microarray analysis of macrophages from B6 and KaLwRij mice prior to onset of BIP revealed three differentially expressed genes, but only one, Samsn1, is conserved in the human genome. We found that both unpolararized primary peritoneal and MCSF cultured bone marrow macrophages from healthy KaLwRij mice had markedly elevated expression of pro-tumorigenic M2 macrophage markers FIZZ1 and YM1 compared to B6 controls, despite the absence of activating cytokines. To confirm that loss of Samsn1 influenced macrophage activation and M2 polarization, we obtained bone marrow macrophages from mice with a targeted deletion of Samsn1 and found that unpolarized Samsn1-/- cells had similarly increased pro-tumor M2 macrophage marker expression. To evaluate the biologic significance of Samsn1 loss in macrophages on MM tumor growth, we established 5TGM1 MM tumors and injected M2 polarized macrophages from B6, KaLwRij, or Samsn1-/- mice. We found that MM tumor burden was markedly enhanced by the addition of a Samsn1-/- or KaLwRij macrophages compared to wild type macrophages. Thus, we found that loss of Samsn1 in macrophages enhances M2 polarization, prior to MGUS/MM development and can promote established myeloma tumor growth. Together, this data suggests that Samsn1 is a gene contributing to BIP-susceptibility in KaLwRij mice through mutually exclusive functions in multiple cell types including B-cells and macrophages. It is likely that SAMSN1 and its pathway members contribute to human MM progression, and may represent a point for preventative therapeutic intervention. Disclosures No relevant conflicts of interest to declare.

Abstract Introduction: Several B-cell malignancies, including chronic lymphocytic leukemia (CLL) and multiple myeloma (MM), are known to have a familial component to disease risk. Although several common inherited genetic variants have been found to be associated with risk of these malignancies, a large proportion of the heritability remains unexplained. Here we set out to identify rare high-penetrance susceptibility variants for CLL and MM using the established Mayo Clinic family study of B-cell malignancies. Methods: We performed exome sequencing on germ line DNA of 106 families with either two or more members with CLL (n=93 families) or two or more members with MM or monoclonal gammopathy of undetermined significance (MGUS) (n=13 families) using Aglient capture kits. All samples were sequenced on an Illumina HiSeq2000. Bioinformatics analyses leveraged the following software packages: Novoalign, Picard, The Genome Analysis Toolkit (GATK), and the Biological Reference Repository (bioR). Quality control filters were implemented; subjects with mis-specified relationships were removed as were variants with <95% call rate or <20x coverage, and those variants identified as sequencing artifacts. To identify potentially functional single nucleotide variants, the following was required a) uncommon in public databases, b) cosegregating variants in multiple families, c) variants to be highly conserved and in coding regions, and d) functional prediction status of deleterious (SIFT score), damaging (PolyPhen score), and a moderate, or high variant impact (SNPEffect). The association of these variants with risk was then evaluated in large samples of cases and controls in genome-wide association studies (GWAS). Results: In the CLL familial cohort, there were 443 individuals (160 with CLL, 73 with monoclonal B cell lymphocytosis (MBL), and 210 relatives without CLL or MBL) sequenced; and in the MM cohort, there were 39 individuals (13 with MM, 13 with MGUS and 13 without MM or MGUS) sequenced. A total of 61,992 single nucleotide variants passed quality control filters in the CLL cohort and 39,456 single nucleotide variants in the MM cohort. From these, we identified 32 variants in the CLL cohort and 39 variants in the MM cohort that were cosegregating in multiple CLL or MM families, respectively, and were predicted to affect protein structure or function. Of these, one CLL variant was within 1 Mb of a known GWAS-discovered locus. Moreover, there were seven CLL and four MM variants that were within 1 Mb of single nucleotide polymorphisms (SNPs) that had statistical significance between p<10-4 and p<10-6 in GWAS. Finally, there were 3 variants found to be common between CLL and MM families (see Table). Conclusions: Through whole exome sequencing, we identified a number of rare, highly penetrant predisposition variants for CLL and MM. Several of these variants were common to both B-cell malignancies providing evidence of shared genetic components; one variant may be a functional driver of the GWAS-discovered loci. These identified variants provide a list for future validation studies. Table: Exome variants common in both Chronic Lymphocytic Leukemia and Multiple Myeloma SNP ID rs41314099 rs61754114 rs143025033 Chromosome 17 6 7 Gene WSCD1 BACH2 TNS3 Penetrance (CLL) 0.70 0.75 0.80 Penetrance (MM) 1.00 0.80 0.75 Allele Frequency (CLL) 0.015 0.025 0.017 Allele Frequency (MM) 0.077 0.077 0.058 1000 Genome Frequency (European) 0.010 0.020 0.010 SIFT Term Deleterious Deleterious Deleterious PolyPhen Term Probably Damaging Probably Damaging Probably Damaging SNP: Single Nucleotide Polymorphism; CLL: Chronic Lymphocytic Leukemia; MM: Multiple Myeloma; Penetrance is defined as proportion of individuals carrying the alternate allele that are also affected; SIFT: Sorting Intolerant From Tolerant, predicts whether an amino acid substitution affects protein function; PolyPhen: Polymorphism Phenotyping, predicts possible impact of an amino acid substitution on the structure of a human protein Disclosures No relevant conflicts of interest to declare.

Abstract Abstract 4000 Background: We have previously reported that there is an increased risk of monoclonal gammopathy of undetermined significance (MGUS) in first-degree relatives of patients with multiple myeloma (Vachon CM. Blood 2009 114: 785–790). There are several cytogenetic subtypes of myeloma, and there are no data on whether certain cytogenetic subtypes of myeloma are more frequently associated with familial MGUS. Methods: We studied patients with myeloma who participated in the familial MGUS study in whom presence or absence of MGUS in the first-degree relatives had been ascertained (Vachon CM. Blood 2009 114: 785–790). Probands were seen at the Mayo Clinic Hematology/Oncology practice (Rochester, MN, USA) between February 2006 and September 2007. Cytogenetic data was acquired via electronic medical record abstraction of fluorescence in-situ hybridization (FISH) lab reports, and used to categorize patients into one of nine cytogenetic subgroups: trisomy(ies), t(6;14), t(11;14), t(4;14), t(14;16), t(14;20), Mixed (those with trisomy(ies) and an IgH translocation), other cytogenetic abnormalities (in the absence of trisomy(ies) or IgH translocation), and normal (Kumar S. Blood 2012;119:2100–2105). We examined whether a difference in the distribution of the six primary cytogenetic categories of myeloma existed between probands with a family history of MGUS and/or myeloma and those without. Results and Conclusions: Of the 248 patients invited to participate, FISH data (with sufficient plasma cells) was available on 119 participants to establish the primary molecular cytogenetic classification of myeloma. All had available information regarding family history of MGUS and multiple myeloma. 27 had an affected first-degree relative with MGUS, and 92 did not. Distributions of cytogenetic subtypes in the two groups are shown in Table 1. IgH translocated MM was more common in myeloma patients who lacked an affected first-degree relative compared to those with familial MGUS (19% vs 30%, P=0.32) Interestingly, the t(11;14) subtype was more common in myeloma patients without familial MGUS compared to those with an first-degree relative with MGUS (19.6% vs 7.4%, P=0.24). The differences in Table 1 did not reach statistical significance, possibly due to the small numbers of individuals with a family history in this sample. However, the distribution (Table 1) suggests that the distribution of cytogenetic subtypes may be different in myeloma that is not associated with familial MGUS compared with myeloma in which a familial tendency is detected. IgH translocated MM appears to have a lower risk of familial tendency. Further investigation is needed to estimate the risk of familial MGUS within each cytogenetic subtype. Disclosures: Kumar: Merck: Consultancy, Honoraria; Millennium: Research Funding; Celgene: Consultancy, Research Funding; Novartis: Research Funding; Genzyme: Research Funding.