Cozen, Wendy

Multiple myeloma (MM) is a neoplasm thought to arise from a damaged germinal center B-cell that progresses to a plasma cell clone arising in bone marrow. MM comprises 20% of all hematologic cancer deaths. Persons of African ancestry (AA) have a 1.5 to 2-fold higher risk compared to individuals of European ancestry (EA). Genetically driven differences in hematopoiesis may lead to variation in the levels white blood cell (WBC) subsets which could, in turn, be associated with MM etiology. There are differences in genetic determinants of WBC traits between EA and AA populations, with possible implications for the racial disparity in risk. We tested the above hypothesis using Mendelian randomization (MR), an approach that leverages genetic determinants of specific traits (i.e. WBC counts) to estimate their effects on the risk of an outcome; and a transcriptome-wide association study (TWAS), which utilizes genetic predictors of gene expression to identify susceptibility genes. These analytic approaches were applied to data from the African American Multiple Myeloma Study (AAMMS) consisting of 1813 cases and 8871 AA cancer-free controls to examine how differences in heritable WBC gene expression profiles influence MM risk. Genetic determinants of variation in WBC subsets in AA were obtained from the literature and supplemented with new genome-wide association findings in AA subjects from the UK Biobank cohort (n=6108). Odds ratios (OR) for MM per 1 standard deviation (SD) increase in each WBC phenotype were estimated using independent (linkage disequilibrium (LD) r2<0.10) variants with P<10-6 as genetic instruments. Analyses based on variants associated with WBC traits in AA populations did not identify any statistically-significant associations between MM risk and WBC overall (p=0.81, using 15 SNPs) or subsets (lymphocytes, monocytes, eosinophils, neutrophils and basophils, p>0.05 for each). However, when we applied genetic determinants of WBC identified in 330,000 cancer-free EA UK Biobank participants (P<10-8, replication P<0.05, LD r2<0.05), a statistically significant inverse relationship emerged between increasing lymphocyte counts and MM risk (OR=0.80, 95% CI: 0.66-0.97, p=0.02, using 385 SNPs), as well as increasing basophil counts (OR=0.63, 95% CI: 0.41-0.96, p=0.03, using 140 SNPs). Next, we examined the association between WBC gene expression profiles and MM risk in AAMMS data. We applied published and validated ancestry-specific models developed using the PrediXcan approach, which leverage germline genetic and transcriptomic data from the Multi-Ethnic Study of Atherosclerosis (MESA) (Mogil et al. PMID: 30096133). The primary TWAS used gene expression models trained in AA subjects (n=233), with sensitivity analyses using models developed in AA and Hispanic subjects (n=585). The TWAS significance threshold was based on the number of genes with significant germline prediction models (p<0.05 and R2 ≥0.05) in AA, corresponding to P < 0.05/2700 = 1.85×10-5. The expression of two genes was significantly associated with MM risk: KANK1at 9p24.3 (P = 1.01×10-5) and DNAJC27at 2p23.3 (P = 1.56×10-5). KANK1is a candidate tumor suppressor gene for renal cell carcinoma and has recently been associated with MM risk in AA [Du, Blood 2017 130:3058]. Here we provide additional evidence for its role in MM etiology via gene expression-mediated mechanisms. DNAJC27 (previously known as RBJ) is a novel MM risk gene linked to constitutive activation of ERK in solid tumors. We also identified two suggestively associated genes: PRR14 (P = 1.34×10-4; combined AA-Hispanic sample: P = 1.56×10-6), which has been linked to MM risk in EA populations, and PARP16 (P = 9.46×10-5). To our knowledge this is the first study to comprehensively examine variation in WBC traits and gene expression profiles with respect to MM risk in AA. Our TWAS analysis leveraged data from the largest collection of genetic and gene expression data in AA, enabling ancestry-matched inference and identification of two novel risk genes. Although the limited availability of genetic instruments for WBC limited the power of MR analysis, findings using variants identified in European populations may offer some insight into trans-ethnic etiologic pathways and contribute to risk stratification strategies using genetic and blood cell count biomarkers. Future studies, particularly with MGUS-free controls, are needed to validate these results. Disclosures Song: Millennium Pharmaceuticals Inc: Employment. Rand:Ancestry.com: Employment. Ailawadhi:Cellectar: Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy; Pharmacyclics: Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy. Nooka:Takeda: Honoraria, Other: advisory board participation; Janssen: Honoraria, Other: advisory board participation; GSK: Honoraria, Other: advisory board participation; Spectrum pharmaceuticals: Honoraria, Other: advisory board participation; Adaptive technologies: Honoraria, Other: advisory board participation; Amgen: Honoraria, Other: advisory board participation; Celgene: Honoraria, Other: advisory board participation; BMS: Honoraria, Other: advisory board participation. Singhal:Bureau of Millennium/Takeda, Celgene, Janssen, Celgene, Bristol-Myers Squibb and Bluebird: Speakers Bureau. van Rhee:Takeda: Consultancy; Sanofi Genzyme: Consultancy; Castleman Disease Collaborative Network: Consultancy; EUSA: Consultancy; Adicet Bio: Consultancy; Kite Pharma: Consultancy; Karyopharm Therapeutics: Consultancy. Mehta:Millennium/Takeda, Celgene; stock in Celgene, Bristol-Myers Squibb and Bluebird: Speakers Bureau. Wolf:Takeda: Consultancy; Celgene: Consultancy; Novartis: Consultancy; Janssen: Consultancy; Amgen: Consultancy. Martin:Roche and Juno: Consultancy; Amgen, Sanofi, Seattle Genetics: Research Funding. Fiala:Incyte: Research Funding. Terebelo:Jannsen: Speakers Bureau; Celgene: Honoraria; Newland Medical Asociates: Employment. Anderson:Bristol-Myers Squibb: Other: Scientific Founder; Oncopep: Other: Scientific Founder; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Sanofi-Aventis: Other: Advisory Board. Vij:Bristol-Myers Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Genentech: Honoraria; Janssen: Honoraria; Karyopharm: Honoraria; Sanofi: Honoraria; Takeda: Honoraria, Research Funding. Bernal-Mizrachi:TAKEDA: Research Funding; Kodikas Therapeutic Solutions, Inc: Equity Ownership; Winship Cancer Institute: Employment, Patents & Royalties. Morgan:Amgen, Roche, Abbvie, Takeda, Celgene, Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Other: research grant, Research Funding. Zonder:Celgene Corporation: Consultancy, Honoraria, 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; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Intellia: Consultancy, Membership on an entity's Board of Directors or advisory committees; Caelum: Consultancy, Membership on an entity's Board of Directors or advisory committees; Alnylam: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees. Huff:Member of Safety Monitoring Board for Johnson and Johnson: Membership on an entity's Board of Directors or advisory committees; Karyopharm, Sanofi, MiDiagnostics: Consultancy. Lonial:Karyopharm: Consultancy; Takeda: Consultancy, Research Funding; Amgen: Consultancy; BMS: Consultancy; Janssen: Consultancy, Research Funding; GSK: Consultancy; Celgene Corporation: Consultancy, Research Funding; Genentech: Consultancy. Orlowski:Poseida Therapeutics, Inc.: Research Funding.

Background Genome-wide association studies (GWAS) conducted in populations of European ancestry (EA) have identified and confirmed 23 germline susceptibility loci for multiple myeloma (MM). The effect sizes of single nucleotide polymorphisms (SNPs) at these loci are small, therefore combining them into a single summary measure, known as a polygenic risk score (PRS), may provide a more meaningful risk factor. We have previously shown a PRS comprised of the 23 SNPs for MM contributes to increased risk of MM, with a 2.7-fold increase for highest vs. lowest PRS quintiles. Whether the MM-PRS is also associated with overall survival (OS) in MM cases has not been evaluated. We examined the association between MM-PRS and OS in two EA studies. Methods The first study consisted of 2,179 EA MM cases from ten studies included in the Multiple Myeloma Working Group within the International Lymphoma Consortium (InterLymph). Cases were diagnosed between 1970 and 2015 and genotyped using multiple platforms (Oncoarray, Affymetrix, Human660W-quad Beadchip, and Illumina arrays); 885 cases also had stage [based on International Staging System (ISS)] available. Each of the GWAS was subjected to rigorous standard quality control independently (prior to imputation via the Michigan imputation server based on the Haplotype Reference Consortium (HRC). The second study consisted of 515 newly diagnosed EA MM cases from CoMMpass (Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profile), diagnosed from 2011-2013, who had whole genome sequencing (WGS) performed on germline DNA. The WGS data was used to call common germline genetic variants through the Mayo Clinic bioinformatics pipeline. Briefly, genetic variants were detected with GenomeGPS, aligned to the hg19 reference genome, called using the GATK (V3.6) Haplotype Caller, and merged for multiple-sample joint calling. To reduce the false positive variants, variant quality score recalibration (VQSR) was applied for both SNPs and INDELs. After quality control, 458 EA samples remained. Follow-up was available for both studies and consisted of time from MM diagnosis date until death or date of last known follow-up. The PRS was constructed from the 23 MM SNPs using the published per allele odds ratio associated with MM risk. The published log odds ratios for each SNP were multiplied by the number of risk alleles (0, 1, 2) for the corresponding SNP, and summed, resulting in a unique score per person. Kaplan-Meier curves and Cox proportional hazard models were used to assess the association between PRS with MM OS considering two models: 1) adjusted for age, sex, study and 2) additional adjustment by stage (ISS). Hazard ratios (OR) and 95% confidence intervals (CI) were estimated. The PRS was evaluated both as a continuous variable, per standard deviation (SD), and as a categorical variable (quintiles). Results MM cases (N=2,179) in the InterLymph study were 59% male and 41% female and the median age was 61.0 years (26-90 years). Median follow-up time was 57.2 months (1.0-509.0 months) with 868 reported deaths. MM cases with stage information available consisted of 20% stage I (n=178), 53% stage II (n=466), and 27% stage III (n=241). No association was observed between PRS and OS in MM patients regardless of adjustment for stage (continuous PRS (HR: 1.03, 95% CI: 0.83-1.28, P=0.80) or by quintile PRS (p>0.05)) (Table). The CoMMpass EA MM cases (n=458) had similar distributions for sex (61% male and 39% females) but were slightly older 65 years (27-93 years) and had shorter follow-up time (median=39.75 months (0.13-77.2)) with 117 deaths. Stage was available for 96% of CoMMpass cases including 36% stage I (n=159), 33% stage II (n=146), and 31% stage III (n=134). We also observed no association of PRS and OS in the CoMMpass study (HR=1.02, 95% CI: 0.72 -1.46, P= 0.89), adjusted for age, sex, and stage (Table). Discussion A PRS score for MM risk is not associated with OS for MM cases in two EA populations. Given that prior studies have shown association of genetic variation with MM survival, efforts to identify additional loci associated with OS or MM specific survival are warranted. Future studies should also consider germline variants impact on molecular subtypes, specific therapies, and outcomes. Disclosures Kumar: Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: 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 Background Outcomes for patients with chronic myeloid leukemia (CML) have improved in recent years. Nonetheless, survival disparities persist between various patient subgroups. There have been limited reports of ethnic variations in CML outcomes, with limited data on ethnic minorities (Hispanics and Asians), who are the fastest growing ethnic subgroups in the Unites States. We undertook a large Surveillance Epidemiology and End Results (SEER) based analysis to describe outcome disparities in different subgroups of CML patients, with a specific focus on various ethnicities. Methods SEER 17 Registry data (1973-2010) was utilized. Adult (>18 years) patients with confirmed diagnosis of CML were eligible. To avoid bias of under representation by ethnic minorities, analysis was restricted to patients with a diagnosis date of 1992 or later (SEER expansion). Cases that received a diagnosis at death certificate/autopsy, no follow-up records, or lacking age at diagnosis, sex, or race/ethnicity documentation were excluded. Cox proportional hazards models, adjusted for confounding variables, were used to evaluate association between patient characteristics and overall survival (OS). All statistical tests were two-sided with a significance level of 0.05, utilizing the SAS software (v9.2). Results The final analysis included 10,356 CML patients (5,943 males; 57.4%, 4,413 females; 42.6%). Age group cohorts included: 18-44 years (2,592; 25%), 45-54 years (1,706; 16.5%), 55-64 years (1,817; 17.6%), 65-74 years (1,876; 18.1%), and ≥75 years (2,365; 22.8%). Patients were stratified by race/ethnicity: White (7,292; 70.4%), African-American (AA) (1,143; 11%), Hispanic (1,163; 11.2%), Asian (697; 6.7%), and Native American (61; 0.6%). For survival analysis, Native Americans were excluded due to their small numbers. Patients were also stratified based on year of diagnosis (1992-1999, 2000-2004 and 2005-2010) to study the impact of evolving therapeutics on CML outcomes. Median age at diagnosis was significantly different among ethnicities (p<0.001) with Hispanics the youngest (47 years) and Whites the oldest (63 years) (Figure 1). There were more Hispanic and AA CML patients reported in recent years in the database than those in 1992-1999 or 2000-2004 (p<0.001). Survival analysis revealed that for all patients, females had a significantly better median OS than males (7.8 years vs. 6.4 years; p<0.001). Among the different age cohorts, median OS got progressively worse with increasing age at diagnosis (p<0.001), with a median OS of 15+ years in 18-44 year cohort vs. 2.3 years in patients ≥75 years. Patients diagnosed more recently had a better median OS (1992-1999: 4.5 years vs. 2000-2004: 7.7 years vs. 2005-2010: 9.8 years; p<0.001). AA had the worst median OS among all ethnicities, which was significantly worse than Whites (reference) (5.8 years vs. 7.4 years; p<0.001). Asians had a median OS of 6.4 years and Hispanics 6 years. In a multivariate model using race, age at diagnosis, year of diagnosis, sex and marital status, a significant interaction was noted between year of diagnosis and race, with all racial subgroups showing improvement in 5-year survival in more recent time periods (p=0.001) (Figure 2). A significant interaction was also noted between year of diagnosis and age, with a progressive improvement in 5-year survival noted across all age groups in more recent years (p<0.001) (Figure 3). Conclusions We present a population-based study of outcomes in CML with the largest representation of ethnic minorities reported so far. We noted a higher number of AA and Hispanic patients reported to the SEER database in recent years. Hispanic patients had a significantly younger age at diagnosis, which could mean longer treatment duration over the lifetime of a patient. AA patients had the worst median OS among all ethnicities, although all ethnicities and age groups were noted to have progressive improvement in outcomes in more recent years of diagnosis. The incremental benefit in outcomes was seen most for Asians and least for Whites. These results will help in better understanding of ethnic influences on disease biology and clinical behavior as well as optimal triaging of healthcare resources. Disclosures: Off Label Use: The abstract shows scientific information on SAR245409 which is an investigational product developed by Sanofi. This investigational product is not approved by any health authority for any indication.

Abstract Background. The incidence of non-Hodgkin lymphoma (NHL) has increased dramatically since at least the 1950s, and only a fraction of this increase can be explained by established risk factors. During this timeframe, there has been a major increase in the use of blood transfusions, anesthesia, and invasive surgical procedures, all of which can impact immune function. Methods. We conducted a population-based case-control study from 1998–2000 using SEER cancer registries in Detroit, Iowa, Los Angeles and Seattle. NHL cases (N=759) were newly diagnosed, HIV-negative, and aged 20–74 years. Controls (N=589) were identified through random digit dialing (<65 years old) and Medicare files (age 65 years and older), and were frequency matched to cases on sex, age, race, and study site. Data on history of blood transfusions, anesthetics (general and regional), and surgeries (type, frequency, and age for 21 anatomic regions) >1 year before diagnosis (or date of enrollment for controls) were collected during in-person interviews. Unconditional logistic regression was used to estimate the odds ratio (OR) and 95% confidence intervals (CI), adjusted for the matching factors. NHL subtypes (follicular and diffuse) were designated according to SEER cancer registry pathology reports, and risk of each subtype was estimated using polychotomous logistic regression. Results. History of blood transfusion was weakly associated with increased risk of NHL (OR=1.26; 95% CI 0.91–1.73), and the elevated risk was specific to transfusions first given 5 to 29 years before diagnosis (OR=1.69; 95% CI 1.08–2.62). Risk was also specific to blood transfusions given for a medical indication (OR=2.09; 95% CI 1.03–4.26), while transfusions given for trauma, obstetric or surgical indications were not associated with risk. Exposure to general or regional anesthesia (OR=1.35 for 24+ times compared to 0–6; 95% CI 0.91–2.02) and total number of surgeries (OR=1.22 for 7+ surgeries compared to 0; 95% CI 0.77–1.93) were weakly and positively associated with risk of NHL, although neither association achieved statistical significance. Results were similar for general versus regional anesthesia. In analysis of surgeries at specific anatomic sites, there were no associations with NHL risk, except for a suggestive positive association for surgery involving the appendix, stomach or bowel (OR=1.24; 95% CI 0.98–1.58). When blood transfusion, anesthesia, and total number of surgeries were included in the same model, ORs for time since first transfusion and total number of surgeries remained unchanged, while the association for anesthesia weakened. These results were generally similar for both diffuse and follicular subtypes, with the exception that total number of surgeries showed a suggestive positive association with follicular (OR=1.61 for 7+ surgeries compared to 0; 95% CI 0.74–3.51) but not diffuse NHL. Conclusion: History of blood transfusion was associated with an increased risk of NHL. Total number of surgeries, type of surgery, and use of anesthesia were only weakly associated with risk, although the suggestive positive association for number of surgeries with follicular lymphoma warrants further investigation.

Abstract Small lymphocytic lymphoma (SLL) is an incurable indolent lymphoma, and there are relatively few prognostic biomarkers for this important NHL subtype. We evaluated the hypothesis that inherited variability in cytokine and immune-related genes was associated with overall survival in SLL. We genotyped 73 SNPs in 44 candidate genes in 140 SLL patients aged 20–70 years who participated in a population-based case-control study conducted from 1998–2000 through the Surveillance, Epidemiology, and End Results (SEER) cancer registries in Detroit, Seattle, Iowa, and Los Angeles. DNA was extracted from a venous blood sample or mouthwash buccal cell sample. All genotyping was conducted at the National Cancer Institute Core Genotyping Facility using the Taqman platform. Histology, stage, presence of B-symptoms, first course of therapy, date of last follow-up, and vital status were derived from linkage to registry databases at each study site in the spring of 2005. Cox proportional hazards analysis was used to estimate the hazard ratio (HR) and 95% confidence interval for the association between individual SNPs and overall survival, adjusted for age, demographic and clinical factors. Multiple simultaneous modeling strategies were used to identify the best summary multi-SNP risk score to predict survival. At last follow-up, there were 45 deaths in 140 patients (32%). The median follow-up of the 95 surviving patients was 58 months (range 24–75 months). In multivariate modeling, SNPs in IL13 (rs1800925; HRCC=2.36, 1.24–4.49), IL7R (rs1494555; HRGG =2.20, 0.84–5.76), and TNF-alpha (rs1800630; HRAC/AA=1.73, 0.95–3.17) were the strongest and most robust predictors of survival. Two or more deleterious genotypes from these three SNPs increased the risk of death (HR=2.2, 1.2–4.1) compared with one or fewer deleterious genotypes (p=0.009). Three groups (low, intermediate, and high risk) were defined by combining the SNP score and a clinical/demographic score. The 5-year Kaplan-Meier survival estimates for these groups were 85%, 65%, and 11%, respectively. Compared to patients with a low risk score, patients with intermediate (HR=2.5, 1.2–5.1) or high (HR=11, 4.3–27.7) risk scores had poorer overall survival (p=3.9 x 10−8). Our preliminary results suggest that SNPs in IL13, IL7R, and TNF-alpha alone and in combination predict overall survival in SLL, lending support to the hypothesis that host genetic background is a promising class of prognostic biomarkers in SLL.

Abstract DLBCL is a curable subtype of non-Hodgkin lymphoma, although a significant number of patients do not achieve a remission or they relapse with conventional chemotherapy. While clinical variables (e.g., IPI), tumor (somatic) genetic alterations, and gene expression profiling have all been shown to predict outcome, there remains a need for additional prognostic biomarkers. One understudied class of biomarkers is host genetic background. We evaluated the hypothesis that germline variability in 73 SNPs from 44 candidate immune genes was associated with overall survival in DLBCL. We addressed this hypothesis in 365 DLBCL patients aged 20–70 years who participated in a population-based case-control study conducted from 1998–2000 (prior to the use of R-CHOP) through the Surveillance, Epidemiology, and End Results (SEER) cancer registries in Detroit, Seattle, Iowa, and Los Angeles. Germline DNA was extracted from a venous blood sample or mouthwash buccal cell sample, which was collected a median of 4.8 months after diagnosis in this population-based study. All genotyping was conducted at the National Cancer Institute Core Genotyping Facility using the Taqman platform, and was successful in over 95% of the DNA samples for the SNPs evaluated. Histology, stage, presence of B-symptoms, first course of therapy, date of last follow-up, and vital status were derived from linkage to registry databases at each study site in the spring of 2005. Cox proportional hazards analysis was used to evaluate the association between individual SNPs, adjusted for age, demographic and clinical factors. Parallel modeling strategies were used to identify the best summary multi-SNP risk score to predict survival. At a median follow-up of 56 months (range, 27-78 months) for surviving patients, there were 96 deaths in 365 patients (26%). In multivariate modeling, SNPs in IL1A (rs1800587; HRCT/TT=1.90, 1.26–2.87), IL6 (rs1800795; HRGG=1.48, 0.99–2.23), IL-10 (rs1800896; HRAG/GG=1.48, 0.91–2.38), and IFNGR2 (rs2070385; HRAG/GG=1.35, 0.86–2.11) were the strongest and most robust predictors of overall survival. A summary score of the number of deleterious genotypes from these four genes in combination with clinical and demographic variables was strongly associated with survival (p=9.3 x 10−12); Kaplan-Meier 5-year survival estimates for low, intermediate, and high risk patients were 89%, 68%, and 47% respectively. In conclusion, host genetic background as measured by germline polymorphisms in immune genes including IL1A, IL6, IL10, and IFNGR2 were associated with overall survival in DLBCL after accounting for clinical and demographic factors. These promising results require confirmation and need further evaluation in patients treated with R-CHOP in conjunction with tumor and other prognostic biomarkers.

Abstract Background: Persons of African ancestry (AA) have a 2-3-fold higher risk of multiple myeloma (MM) than persons of European ancestry (EA). Like other B-cell malignancies, genome-wide association scans (GWAS) have identified MM risk variants in the HLA region in persons of EA. We conducted a case-control analysis with data from the National Marrow Donor Program (NMDP)1comprising MM patients typed for bone marrow transplant to donor controls matched by race-ethnicity, and found associations between specific HLA alleles/haplotypes and MM risk that varied by race and ethnicity. To confirm our results and identify additional novel signals, we have now investigated associations between HLA alleles and haplotypes and MM risk in the African American Multiple Myeloma Study (AAMMS) Cohort. Methods: The source of subjects was the AAMMS, in which AA MM patients were identified from 10 cancer centers and 4 Surveillance, Epidemiology and End-Results (SEER) Program cancer registries in order to identify genetic risk factors for MM among AAs. A GWAS was conducted using the Illumina Human Core BeadChip array on DNA samples from 1,305 AA MM patients in the AAMMS comparing results to those from 7,078 AA controls with GWAS data generated from the Illumina 1MDuo2. The major histocompatibility complex (MHC) region single nucleotide polymorphisms (SNPs) were imputed to classical HLA variants using HIBAG. Unconditional logistic regression was used to estimate HLA associations, adjusting for sex, age and the first 2 principal components. P-values were adjusted for false discovery rate (FDR) for each locus group. Results: We did not identify any single HLA alleles associated with MM risk among AAs. However, several B*07:02-containing haplotypes were associated with MM risk (odds ratios [OR] ranging from 2.38 to 2.64 and FDR P-values ranging from 1.43 x 10-6 to 3.57 x 10-8). We found associations between MM risk and genotypes containing DRB3*02:02, including DRB3*02:02~DRB1*11:01+ DRB3*02:02~DRB1*11:01 (OR=1.93, PFDR= 9.36 x 10-5) similar to those observed in the NMDP study1. Novel findings included associations between MM risk and HLA Class I haplotypes B*53:01+ B*57:01 (OR=1.94, PFDR= 0.003) and C04:01~B*53:01+C*06:02~B*57:01 (OR=1.96, PFDR= 0.0050). Results from an ongoing meta-analysis between the two data sets (one based on an imputed GWAS and one based on NMDP HLA typing) will be presented. Conclusions: This study is the second to examine HLA alleles and risk of MM among AA's and is by far the largest. We confirmed a previously observed association between an HLA Class II DRB3 variant and MM risk and confirmed an association with B*07 haplotypes previously observed among EAs1. We also identified novel associations between other HLA Class I haplotypes and MM risk in AA's. Because HLA is highly polymorphic, many HLA alleles are rare variants for which genetic associations are difficult to detect without very large sample sizes. Further investigation with large sample sizes will be necessary to refine these associations in order to better identify the underlying causal alleles and determine the functional significance of these HLA associations. 1Beksac M, Gragert L, Fingerson S, et al.: HLA polymorphism and risk of multiple myeloma.Leukemia. 2016 Jul 27. doi: 10.1038/leu.2016.199. 2Rand KA, Song C, Hwang AE, et al. Genetic susceptibility markers of multiple myeloma in African-Americans. Abstract # 2030, 56th Annual American Society of Hematology Meeting, San Francisco, California, 2014. Disclosures Ailawadhi: Pharmacyclics: Consultancy; Novartis: Consultancy; Amgen Inc: Consultancy; Takeda Oncology: Consultancy. Nooka:Spectrum, Novartis, Onyx pharmaceuticals: Consultancy. Zonder:Pharmacyclics: Other: DSMC membership; Prothena: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Lonial:BMS: Consultancy; Novartis: Consultancy; Millenium: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Merck: Consultancy; Celgene: Consultancy; BMS: Consultancy; Novartis: Consultancy; Onyx: Consultancy; Janssen: Consultancy; Onyx: Consultancy.

Abstract Multiple myeloma (MM) is 2-3 times more common among African-Americans compared to non-Hispanic whites. The 2-3-fold increased risk among family members of cases suggests a genetic contribution to risk. Genome-wide association studies (GWAS) in populations of European ancestry have identified seven novel risk loci at 2p23.3 (rs6746082), 3q26.2 (rs10936599), 3p22.1 (rs1052501), 6p21.32 (rs2285803), 7p15.3 (rs4487645), 17p11.2 (rs4273077) and 22q13.1 (rs877529) (Broderick, et al. Nat Genet, 2011, Chubb, et al. Nat Genet, 2013), three of which were replicated in another European series (Martino et al., Br J Haematol, 2012). Here we examined the index signals and conducted fine-mapping for each locus in a case-control study of 1,049 multiple myeloma cases and 7,084 controls of African ancestry to identify better markers of risk and novel independent loci in seven previously reported regions in this high risk population. Incident cases were recruited from 10 clinical centers and SEER cancer registries from 2011 to 2013 and genotyped using the Illumina HumanCore GWAS array. Control data were obtained from previous genome-wide studies of breast and prostate cancer, genotyped using the Illumina 1M-Duo in 4425 male controls from the African Ancestry Prostate Cancer Consortium (consisting of 14 independent studies) and 2632 female controls from a breast cancer GWAS of African-American women (consisting of 9 independent studies). Imputation to 1000 Genomes (March 2012 release) was conducted for regions around six of the previously identified single nucleotide polymorphisms [SNPs] (the HLA region harboring rs2285803 is still being imputed, results will be presented). A case-control analysis of SNPs/indels >1% frequency within 250 kb of each index variant was conducted using unconditional multivariable logistic regression adjusting for age, sex and five leading principal components. Region-specific alpha levels were determined through permutation tests. The minimum alpha level across the six regions was α=0.002. All previously reported risk variants were common in African-Americans (minor allele frequency [MAF] >0.05). For five of the six SNPs, we had ≥94% power to detect the same effect observed in non-Hispanic whites, and 64% power for the less common variant rs10936599 (MAF=0.07). We observed directionally consistent effects (odds ratio [OR]>1) for the six risk variants tested, with three replicating at p≤0.05 (7p15.3, p=1.4x10-7; 17p11.2, p=0.05; 22q13.1, p=0.02). For three of the six regions, we observed better markers of risk in African-Americans that were correlated with the index SNP in Europeans (7p15.3, rs56333627, p=1.5x10-5, r2=0.89; 17p11.2, rs34562254, p=2.9x10-3, r2=0.90; 22q13.1, rs2092410, p=1.1x10-4 r2=.71). The missense variant identified in the 17p11.2 region (rs34562254, Pro251Leu) is located in TNFRSF13B, which encodes the protein TACI, a B cell surface receptor which plays a role in B cell maturation, apoptosis and antibody production by inducing activation of transcription factors including NFAT and NFκβ. In addition, there is evidence suggesting that TACI is involved in MM pathogenesis. Our results demonstrate that many of the risk loci for MM found in European ancestry populations are also risk loci in men and women of African ancestry and that by fine-mapping, we are able to identify variants that better capture risk in populations of African ancestry. Disclosures Terebelo: Celgene Corp: Membership on an entity's Board of Directors or advisory committees. Lonial:Millennium: The Takeda Oncology Company: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Onyx Pharmaceuticals: Consultancy, Research Funding.

Abstract Abstract 757 Background: Chronic lymphocytic leukemia (CLL) is the most common leukemia seen in adults. Previous population-based research in CLL has not represented the current ethnic makeup and diversity within the US population. We undertook a large Surveillance Epidemiology and End Results (SEER) based analysis to assess disparities in outcome among different ethnic subgroups of CLL patients, so that therapeutic resources can be utilized effectively. Methods: The SEER-18 Registry (1973–2009) was used to retrieve a population of 60,293 patients with established diagnosis of CLL (Histology code: 9823). The cohort was restricted to adults (>18 yrs) diagnosed after January 1, 1992, since ethnic minorities were underrepresented in SEER prior to that. Cases reported in death certificate/autopsy, those without a confirmatory diagnosis, those with ethnicity recorded as unknown/other or those that did not have follow up post diagnosis were excluded. Using Cox proportional hazards models, adjusted for confounding variables, association between patient characteristics and survival (overall; OS and CLL-specific; CLLSS) was evaluated. Analysis was performed utilizing the SAS software (v9.2). All statistical tests were two-sided with a significance level of 5%. Results: A total of 37,834 patients (22,581 males; 60%, 15,253 females; 40%) were included in the final analysis. Age group (yr) cohorts included: 18–44 (861; 2%) 45–54 (3,587; 9%), 55–64 (7,684; 20%), 65–74 (10,966; 29%), and ≥75 (14,736; 39%). For survival trends over time, stratification by year of diagnosis was used: 1992–1999 (9,837; 26%), 2000–2004 (14,129; 37%), 2005–2009 (13,868; 37%). Stratification by race/ethnicity included: White (32,980; 87%), African-American (AA: 2,486; 7%), Hispanic (1,536; 4%), Asian (737; 2%), and Native American (NA: 95; 0.25%). Median age ranged from 68 yr (AA and Asian) to 71 yr (Whites) (Figure 1). For survival analysis, NA ethnic group was excluded due to their small numbers. Females had a significantly better median OS (8.3 yr vs. 6.4 yr; p<0.001) as well as CLLSS (p<0.001) than males, when evaluated for the whole population and across different age groups. Both, OS and CLLSS progressively and significantly (p<0.001) declined with advancing age. Progressive significant improvement was seen in OS over time across cohorts by year of diagnosis (6.3 yr, 7.3 yr, 7.4 yr; p<0.001). This improvement in OS persisted over time for age groups <75 yr, but for ≥75 yr, the improvement was lost in the most recent time period cohort (2005–2009). The percentage of patients dying of CLL has decreased progressively over time suggesting an improvement in therapy. Among various ethnicities, Asians had the best (7.5 yr) and AA had the worst (4.8 yr) OS (p=0.006) (Figure 2) and CLLSS (p<0.001). In a multivariate model, AA continued to have the worst OS across all age groups (p<0.001), while Whites had the best OS in age groups <75 yr and Asians had the best among patients ≥75 yrs. Percentage of patients dying from CLL was highest in AA across age groups, but lowest for Whites in age groups <75 yr, while in Hispanics in patients ≥75 yr. Trends in CLLSS were noted to be more heterogeneous among ethnicities than trends in OS. Conclusions: This report presents the largest population-based analysis of patient characteristics including ethnicity and survival in CLL in the era of novel therapeutic agents. Older patients had worse OS among all ethnic subgroups. Progressive improvement in CLLSS was noted over time suggesting a possible impact of new therapeutics, however this was not seen in ≥75 yr patients. AA patients had the worst OS among all ethnicities and age groups. This survival difference was most significant and pronounced in younger patients, which has important implications. For example, this survival disadvantage may represent poor access to optimal healthcare warranting development of new initiatives directed towards this ethnic minority. On the other hand discrete biological variants may underlie the more aggressive disease biology in younger AA patients underscoring the need to further investigate and delineate the molecular biology of CLL in ethnic minorities. Studies of outcome disparities are important not only for evaluating disease characteristics but also management needs of specific patient populations and are critical for designing programs to deliver optimal healthcare to ethnically diverse populations. Disclosures: No relevant conflicts of interest to declare.