Wolf, Jeffrey L.

Abstract Background: Persons of African ancestry (AA) experience a 1.5-2-fold risk of multiple myeloma (MM) compared to persons of European ancestry (EA). We assembled a set of MM patients with self-reported AA in order to evaluate the contribution of genetics to etiology in this high-risk group. Methods: Here we present the results of a meta-analysis of two GWAS in 1,813 cases and 8,871 controls of AA. We also conducted an admixture mapping scan to identify risk alleles associated with local ancestry, fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA, and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. Finally, we conducted an eQTL analysis measuring gene expression in those genes harboring a risk variant in malignant plasma cells from 292 of the patients from a single site. Results: In GWAS analysis, we identified two suggestive novel loci located at 9p24.3 and 9p13.1 at P<1 × 10-6, but no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. 20 of the 23 known EA risk variants showed directional consistency and 9 replicated at P<0.05 in AA individuals. In eight regions, we identified markers that better capture MM risk in persons of AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95%CI: 1.56, 2.11) increased MM risk compared to those with average risk (25-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P= 5.1 × 10–12). Conclusion: Our study shows that common genetic variation contributes to MM risk individuals of AA. This abstract is also being presented as Poster C040. Citation Format: Zhaohui Du, Niels Weinhold, Gregory Chi Song, Kristen A. Rand, David J. Van Den Berg, Amie E. Hwang, Xin Sheng, Victor Hom, Sikander Ailawadhi, Ajay K. Nooka, Seema Singhal, Karen Pawlish, Edward Peters, Cathryn Bock, Ann Mohrbacher, Alexander Stram, Sonja I. Berndt, William J. Blot, Graham Casey, Victoria L. Stevens, Rick Kittles, Phyllis J. Goodman, W. Ryan Diver, Anselm Hennis, Barbara Nemesure, Eric A. Klein, Benjamin A. Rybicki, Janet L. Stanford, John S. Witte, Lisa Signorello, Esther M. John, Leslie Bernstein, Antoinette Stroup, Owen W. Stephens, Maurizio Zangari, Frits Van Rhee, Andrew Olshan, Wei Zheng, Jennifer J. Hu, Regina Ziegler, Sarah J. Nyante, Sue Ann Ingles, Michael Press, John David Carpten, Stephen Chanock, Jayesh Mehta, Graham A Colditz, Jeffrey Wolf, Thomas G. Martin, Michael Tomasson, Mark A. Fiala, Howard Terebelo, Nalini Janakiraman, Laurence Kolonel, Kenneth C. Anderson, Loic Le Marchand, Daniel Auclair, Brian C.-H. Chiu, Elad Ziv, Daniel Stram, Ravi Vij, Leon Bernal-Mizrachi, Gareth J. Morgan, Jeffrey A. Zonder, Carol Ann Huff, Sagar Lonial, Robert Z. Orlowski, David V. Conti, Christopher A. Haiman, Wendy Cozen. A meta-analysis of genome-wide association study and eQTL analysis of multiple myeloma among African Americans [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr PR05.

Abstract Persons of African ancestry (AA) have a twofold higher risk for multiple myeloma (MM) compared with persons of European ancestry (EA). Genome-wide association studies (GWASs) support a genetic contribution to MM etiology in individuals of EA. Little is known about genetic risk factors for MM in individuals of AA. We performed a meta-analysis of 2 GWASs of MM in 1813 cases and 8871 controls and conducted an admixture mapping scan to identify risk alleles. We fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. In GWAS meta-analysis, we identified 2 suggestive novel loci located at 9p24.3 and 9p13.1 at P < 1 × 10−6; however, no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. Of the 23 known EA risk variants, 20 showed directional consistency, and 9 replicated at P < .05 in AA individuals. In 8 regions, we identified markers that better capture MM risk in persons with AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95% confidence interval, 1.56-2.11) increased MM risk compared with those with average risk (25%-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P = 5.1 × 10−12). Our study shows that common genetic variation contributes to MM risk in individuals with AA.

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: Multiple myeloma (MM) treatment has advanced considerably with proteasome inhibitors, immunomodulatory drugs (IMiDs), and, most recently, monoclonal antibodies. However, treatment response is quite heterogeneous, and many patients still progress even with novel combination therapies. Thus, understanding the factors that underlie response to treatment is a priority. Several somatic genomic aberrations and mutations predict poor response to therapy. However, germline variation has not previously been investigated as a predictor of treatment response in MM. We used genome-wide association and transcriptome-wide association approaches to identify germline genetic predictors of treatment response in MM. Methods: We included 510 MM patients from Mayo Clinic and 324 MM patients from UCSF diagnosed from 1999-2015. Basic demographics, laboratory values and pathology at diagnosis, type of initial therapy, duration of therapy, and follow-up were ascertained by chart review. Patients were grouped into categories of treatment based on their first line therapy: proteasome inhibitor-based regimen, IMiD based regimen, combination proteasome and IMiD based regimen, or other. Response was assessed using International Myeloma Working Group (IMWG) response criteria after 4-6 cycles of induction. As such, response was categorized into progressive disease (PD), minimal response (MR), partial response (PR), very good partial response (VGPR), or complete response (CR). Germline samples were genotyped using Illumina or Affymetrix arrays and were imputed based on the Haplotype Reference Consortium (HRC). For the genome-wide association study (GWAS), we included all SNPs with minor allele frequency >0.01 and imputation r2 of >0.5. We tested each SNP for association with treatment response using a linear regression model that adjusted for age, gender, and genetic ancestry (from principal components analysis (PCA)). To perform the transcriptome-wide association study (TWAS), we calculated predicted gene expression data using PREDIXCAN software on a reference cohort of 922 individuals with genotype and RNA expression data from peripheral blood. We then tested the association between predicted gene expression and response to therapy using linear regression models. Both the GWAS and TWAS were performed on subgroups of patients who received either proteasome inhibitors or IMiD therapies. The analyses of patients on proteasome inhibitors were adjusted for IMiD use as a covariate and analyses of patients on IMiDs were adjusted for proteasome inhibitor use. The threshold for genome-wide significance loci was set at P = 5 x 10-8 and the threshold for suggestive loci was set at P = 10-6. The threshold for significance for TWAS was set at P = 4 x 10-6 by using a Bonferroni correction for the number of genes for which genetic models of expression could be developed by PREDIXCAN. Results: Overall, 42.7% (59 of 138) of patients on proteasome inhibitors alone, 32.5% (66 of 203) of patients on IMiDs alone, and 58.1% (50 of 86) of patients on combination achieved at least a VGPR. There were no significant differences in response across centers in analyses that adjusted for age, sex and types of therapy. There were no genome wide significant loci to predict for response. We identified 8 suggestive SNPs associated with proteasome inhibitor response and 4 suggestive SNPs associated with IMiD response. TWAS identified ZNF622 as a candidate genetic modifier of proteasome inhibitor effect that was significant after correction for multiple hypothesis testing (P = 1.6 x 10-6). Higher genetically predicted expression was associated with improved response to proteasome inhibitor therapy. Among patients above the median of predicted expression of ZNF622 on proteasome inhibitors, 62.6% achieved at least VGPR; among patients at or below the median of expression, only 37.6% achieved at least VGPR. Conclusions: We identified an association between predicted expression of ZNF622 and clinical response to proteasome inhibitor therapy among MM patients. ZNF622 is a zinc finger binding protein which is known to be co-activator of B Myb activity and to affect apoptosis in response to oxidative stress. Our work highlights the potential importance of pharmacogenetic modifiers of treatment response in MM. Disclosures Shah: Nkarta: Consultancy, Membership on an entity's Board of Directors or advisory committees; Indapta Therapeutics: Equity Ownership; University of California, San Francisco: Employment; Celgene, Janssen, Bluebird Bio, Sutro Biopharma: Research Funding; Genentech, Seattle Genetics, Oncopeptides, Karoypharm, Surface Oncology, Precision biosciences GSK, Nektar, Amgen, Indapta Therapeutics, Sanofi: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Poseida: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees; Teneobio: Consultancy, Membership on an entity's Board of Directors or advisory committees. Wong:Celgene: Research Funding; Janssen: Research Funding; Roche: Research Funding; Fortis: Research Funding. Martin:Roche and Juno: Consultancy; Amgen, Sanofi, Seattle Genetics: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Takeda: Research Funding; Janssen: Consultancy, 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 Abstract 1024 Background: The MMRC is a non-profit, disease-focused consortium founded in 2004. Sixteen North American member institutions with expertise in multiple myeloma (MM) work collaboratively with the MMRC Inc. (Norwalk, CT) and numerous pharmaceutical partners to speed development of new treatment options to MM patients. In December 2007, MMRC Inc. implemented business solutions to address barriers to rapid activation of phase I-II trials and established benchmarks for initiating and conducting these studies. In December 2010, we reported significantly faster trial start up and accrual data from previous years1,2. Today, we update and expand on MMRC performance data and analysis of progress. Methods: Twenty-five (25) trials conducted within the Consortium from May 2006 to July 2011 had sufficient start up trial data for review. FPFD was defined as the time from the member institutions' receipt of the final protocol (FP) from the trial sponsor, to the time the first patient was dosed on the trial at any participating MMRC member institution. With respect to enrollment, pre-study enrollment commitment (EC) established between MMRC and the study sponsor was defined as the total number of subjects committed to receive at least one dose of study drug across all participating MMRC centers on a trial; baseline enrollment timeline (BET) was prospectively defined as the target time period to attain EC. Results: Mean time to FPFD in the recent group of trials (RG; n=18; Sept 08-Jul 11) held steady at 131 calendar days from receipt of FP as compared to 181 days for the early group of trials (EG; n=7; Jun06-Sept08) representing a 28% reduction in time to FPFD. More importantly, there was a 20% decrease in time to FPFD by all participating MMRC centers on any MMRC trial from 189 days in the RG compared to 236 days in the EG representing an important achievement especially in the Phase I/II arena. MMRC trial accrual data was available for 17/25 trials (2 EG trials were missing data and 6 RG trials continue enrolling). The pre-study mean MMRC EC was 44 subjects per trial (n=19 trials; 849 patients); the mean actual MMRC enrollment was 49 subjects per trial (n=19; 935 patients through July 11) representing a 10% over enrollment versus committed enrollment. A total of 17/19 evaluable trials (89%) met their EC; 12/19 trials met EC within BET (71%) of which 8/12 trials (67%) reached EC 34% faster than their BET (representing a mean reduction of 4.5 months). The overall pre-study mean BET for 19 trials was 13.6 months. MMRC's actual mean enrollment timeline was 12.8 months for the group of 17 evaluable trials representing improvement over the original BET by a mean of 10%. Discussion: MMRC's acceleration of clinical trials provides physicians and patients with rapid access to novel compounds; industry with data for important drug development decisions; and academic institutions with more trials of high scientific interest. Even so, our data uncovered opportunities for improvement. The submission time from receipt of the final protocol from the trial sponsor to Scientific Review Committee (SRC) took an average 30 calendar days across all trials. A reduction to half this time could make a difference to patients and therefore warrants further exploration. Conclusion: Today, drug development in multiple myeloma is fast-paced and highly competitive. MMRC's frequent review of trial metrics provides valuable insight to continually speed answers to physicians, patients and industry. Disclosures: Richardson: Multiple Myeloma Research Consortium: Annual grant in support Clinical Trial Project Management. Vij:Multiple Myeloma Research Consortium: Annual grant in support of clinical trial Project Management. Lonial:Multiple Myeloma Research Consortium: Annual grant in support of clinical trial Project Management. Siegel:Multiple Myeloma Research Consortium: Annual grant in support of clinical trial Project Management. Jakubowiak:Multiple Myeloma Research Consortium: Annual grant in support of clinical trial Project Management. Reece:Multiple Myeloma Research Consortium: Annual grant in support of clinical trial Project Management. Jagannath:Multiple Myeloma Research Consortium: Annual grant in support of clinical trial Project Management. Hofmeister:Multiple Myeloma Research Consortium: Annual grant in support of clinical trial Project Management. Stewart:Multiple Myeloma Research Consortium: Annual Grant in support of clinical trial Project Management. Wolf:Multiple Myeloma Research Consortium: Annual grant in support of clinical trial Project Management. Krishnan:Multiple Myeloma Research Consortium: Annual grant in support of clinical trial Project Management. Zimmerman:Multiple Myeloma Research Consortium: Annual grant in support of clinical trial Project Management. Kumar:Multiple Myeloma Research Consortium: Annual grant in support of clinical trial Project Management. Roy:Multiple Myeloma Research Consortium: Annual grant in support of clinical trial Project Management. Fay:Multiple Myeloma Research Consortium: Annual grant in support of clinical trial Project Management. Anderson:Multiple Myeloma Research Consortium: Annual grant in support of clinical trial Project Management.

Abstract Background: Combination regimens incorporating bortezomib (VELCADE®, Vc), lenalidomide (REVLIMID®, Rev), dexamethasone (Dex) and cyclophosphamide (Cy) (Vc–Dex, Rev–Dex, Vc–Dex–Rev [VDR], and Vc–Dex–Cy [VDC]), have all shown substantial activity in previously untreated multiple myeloma (MM). A combination of all four agents (VDCR) may result in even greater activity. This randomized multi-center 3-arm phase I/II EVOLUTION study is investigating the efficacy and safety of VDR, VDC, and VDCR as initial therapy in previously untreated MM patients (pts). We now report safety and efficacy results from the phase l dose-escalation portion of the study, which sought to determine the maximum tolerated dose (MTD) of the VDCR regimen. These results represent the first clinical data with this novel 4-drug combination that includes bortezomib, lenalidomide, an alkylator, and a corticosteroid. Methods: Pts received Vc 1.3 mg/m2 IV (d 1, 4, 8, 11), Dex 40 mg PO (d 1, 8, 15), Rev 15 mg PO (d 1–14), plus Cy 100, 200, 300, 400, or 500 mg/m2 PO (d 1, 8) for up to eight 21-d cycles, followed by Vc 1.3 mg/m2 (d 1, 8, 15, 22) for four 42-d maintenance cycles. Pts received prophylactic antibiotics, acyclovir, transfusion support and concomitant anticoagulants as required. Eligible pts wishing to receive autologous stem cell transplant (ASCT) could undergo stem cell mobilization any time after cycle 2, and discontinue therapy for ASCT any time after cycle 4. The MTD was defined as the highest dose of Cy in combination with VDR resulting in ≤1 dose-limiting toxicity (DLT) in 6 pts. A DLT was defined as: platelet count <25,000/mm3 lasting >7 days or any platelet count <10,000/mm3; grade 4 neutropenia lasting >7 days; any ≥grade 3 non-hematologic toxicity considered to be related to Cy except for inadequately treated nausea, vomiting, and diarrhea, or any toxicity resulting in a >2 week treatment delay. Results: Twenty-six pts were enrolled; 1 pt was not dosed due to a heart problem and was excluded (dose level 4) and 4 pts were not evaluable for DLT. In the 25 treated pts, median age was 61 years (range 49–79); 52% were male; 48% had ISS Stage lI and 4% Stage III disease, and 44% had KPS ≤80%. At data cut-off, 11 pts remain on treatment and 9 have undergone successful ASCT. To date, median treatment duration is 4 cycles (range 2–11). Two pts experienced DLT: 1 grade 4 febrile neutropenia at dose level 4 (Cy 400 mg/m2), and 1 grade 3 herpes zoster virus reactivation despite antiviral prophylaxis at dose level 5 (Cy 500 mg/m2). The recommended phase II dose of Cy in the VDCR regimen was the highest planned dose of 500 mg/m2. The most common treatment-emergent AEs were constipation (64%), fatigue (60%), and nausea (52%). Hematologic toxicities were acceptable, with grade 3 neutropenia in 16% of patients, grade 4 in 4%, and grade 4 thrombocytopenia in 4%. Peripheral neuropathy (56%), included 8% grade 3 but no grade 4; no deep-vein thrombosis/pulmonary embolism events were reported. Overall rate of serious AEs was 40%; the only SAE reported in >1 pt was febrile neutropenia (2 pts). Best responses to date by International Uniform Response Criteria are shown in the table. Preliminary response rates are: 100% ≥PR, 68% ≥VGPR, 32% CR/nCR, 28% CR/stringent CR and 20% sCR. Ten pts have undergone stem cell mobilization with median CD34+ yield of 4.95×106/kg. Conclusions: VDCR was well tolerated and hematologic toxicities were manageable. The current study shows that the VDCR regimen is feasible and highly active in newly diagnosed myeloma and merits further testing in clinical trials. Enrollment to the 3 arms (VDR, VDC and VDCR) of the phase ll portion of the study and testing for minimal residual disease by flow cytometry are ongoing. Best unconfirmed response to date with VDCR Dose level 1 2 3 4 5 Cyclophosphamide dose, mg/m2 100 200 300 400 500 Enrolled 3 4 4 8 7 Treated 3 4 4 7 7 Still on treatment – 1 1 2 7 Best unconfirmed response to date CR (sCR) 2 (2) 1 (1) 1 (1) 2 1 (1) VGPR (nCR) 1 – 3 (1) 4 2 PR – 3 – 1 4

Abstract Abstract 3803 Background: The MMRC is a non-profit, disease-focused consortium founded in 2004 comprised of 13 North American centers with expertise in multiple myeloma (MM). The MMRC Inc. (Norwalk, CT), MMRC's member institutions, and several pharmaceutical partners work closely to speed early development of new treatment options for MM patients. In December 2007, MMRC headquarters staff implemented multiple project management (PM) business solutions to address trial barriers that delay activation of our phase I-II clinical trials and established trial metric benchmarks considered attainable at our member institutions. In November 2009, we reported initial data1 on trial activation: MMRC trials initiated between Sep08-Jul09 (n=5) demonstrated a 38% decrease in mean time to first patient dosed (FPFD), compared with the Early Group trials (EG) initiated before PM solutions (Jun06-Sept08; n=7 trials). These results also confirmed improvement over published metrics from Dilts et al 2,3. We present additional data on time to FPFD and now enrollment, to assess impact of the MMRC PM resources and processes on trial efficiency. Methods: Twenty-one (21) trials conducted within the MMRC from May 2006 to June 2010 had sufficient trial data for review. Data were collected by MMRC-funded project managers at the clinical centers using a web-based clinical trial management system (CTMS). FPFD was defined as the time from the member institutions' receipt of the final protocol (FP) from the trial sponsor, to the time the first patient was dosed on the trial at any participating MMRC member institution. With respect to enrollment, pre-study enrollment commitment (EC) established between MMRC and the study sponsor was defined as the total number of subjects committed to receive at least one dose of study drug across all participating MMRC centers on a trial; baseline enrollment timeline (BET) was prospectively defined as the target time period to attain EC. Results: Mean time to FPFD was 181 calendar days for the early group trials (EG, n=7) and 122 days for the recent group (RG) trials (n=14, Sep08 – Jun10), representing a 32% reduction of time to FPFD in the RG. Additionally, time from final protocol to first patient dosed at all MMRC centers on a trial decreased 18% from a mean of 7.7 months (EG) to 6.3 months (RG). With respect to MMRC trial enrollment, data was available for 16/21 trials (5 EG and 11 RG). 2 EG trials were missing data and 3 RG trials were still enrolling as of June 2010. The mean MMRC pre-study EC was 39 subjects per trial (n=16 trials; 626 enrollment target); the mean actual MMRC enrollment was 49 subjects per trial (n=16; 783 enrolled through Jun 29, 2010) representing a 25% increase in actual versus committed enrollment. Two trials did not meet MMRC EC: MMRC investigators discontinued their involvement in these trials at approximately 30% target EC due to trial complexity or low patient enrollment. 14/16 evaluable trials (88%) met their EC; 11/16 trials met EC within BET (69%) of which 8/16 trials (50%) reached EC 34% faster than their BET (representing a mean reduction of 4.5 months). The overall pre-study mean BET for 16 trials was 13.1 months. MMRC's actual mean enrollment timeline was 11.3 months for the group of 14 evaluable trials representing improvement over the original BET by a mean of 1.9 months (14%). We believe FP to FPFD is a more meaningful metric beyond that of first patient consented. Moreover, we believe that if all participating trial centers focus their efforts on dosing the first patient and within a targeted timeframe, it may improve our research efforts overall. Conclusion: Development of drugs in the clinical setting has become time and resource intensive. Activating and enrolling trials promptly is a priority for drug development. The MMRC's standardization of processes and support for site-based PM resources results in improved trial metrics. MMRC member centers met or exceeded pre-specified enrollment targets in 88% of the trials analyzed to date. Ongoing monitoring of trial conduct continues to reveal areas where increased focus is needed to realize further trial efficiencies. These trial metrics and measures to improve efficiency may be applied with similar expected benefit in all oncology disciplines. Disclosures: Wear: Multiple Myeloma Research Consortium (MMRC): Employment. Richardson:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC; Millennium: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Johnson & Johnson: Membership on an entity's Board of Directors or advisory committees. Revta:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Vij:Multiple Myeloma Research Consortium (MMRC): Research Funding; Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Fiala:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Lonial:Bristo-Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millenium Pharmaceuticals Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Onyx: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Francis:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Siegel:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC; Celgene: Speakers Bureau; Millennium: Speakers Bureau. Schramm:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Jakubowiak:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC, Research Funding; Millennium: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Honoraria, Speakers Bureau; Centocor Ortho-Biotech: Honoraria, Speakers Bureau; Exelixis: Honoraria, Speakers Bureau; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Harvey:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Reece:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC; Celgene: Honoraria, Research Funding; Ortho Biotech: Honoraria, Research Funding; Merck: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Facet: Research Funding; Otsuka: Honoraria, Research Funding. Gul:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Jagannath:Celgene: Honoraria; Millenium: Honoraria; Orthobiotec: Honoraria; Onyx Pharma: Honoraria; Merck: Honoraria; Proteolix: Honoraria; Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. La:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Hofmeister:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Jansak:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Stewart:Millennium: Consultancy; Celgene: Honoraria; Multiple Myeloma Research Consortium: Member Institution of the MMRC. Hagerty:Mayo Clinic: Employment; Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Wolf:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC; Celgene: Speakers Bureau; Millennium: Speakers Bureau; Novartis: Speakers Bureau; Orthobiotech: Speakers Bureau. Davis:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Krishnan:Celgene: Speakers Bureau; Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Duarte:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Zimmerman:Millennium, Celgene: Speakers Bureau. Cisneros:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Kumar:Celgene: Consultancy, Research Funding; Millennium: Research Funding; Merck: Consultancy, Research Funding; Novartis: Research Funding; Genzyme: Consultancy, Research Funding; Cephalon: Research Funding; Bayer: Research Funding; Multiple Myeloma Research Consortium: Member Institution of the MMRC. Birgin:Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC. Ott:Multiple Myeloma Research Consortium (MMRC): Employment. Tasca:Multiple Myeloma Research Consortium (MMRC): Employment. Kelley:Multiple Myeloma Research Consortium (MMRC): Employment. Anderson:Millennium: Consultancy; Multiple Myeloma Research Consortium (MMRC): Member Institution of the MMRC; Celgene: Consultancy; Novartis: Consultancy; Onyx: Consultancy; Merck: Consultancy; Bristol-Myers Squibb: Consultancy; Acetylon: Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Giusti:Multiple Myeloma Research Consortium (MMRC): Employment.

Abstract Abstract 621 Background: Two- and three-drug regimens incorporating bortezomib (Velcade®, V), lenalidomide (Revlimid®, R), dexamethasone (D), or cyclophosphamide (C) have been shown to be effective and well tolerated in previously untreated multiple myeloma (MM). Combining all four drugs in a single regimen (VDCR) may further enhance efficacy. Published results from the phase 1 dose-escalation portion of the non-comparative, multi-center EVOLUTION study showed that the VDCR regimen was highly active and generally well tolerated (Kumar et al Leukemia 2010). Here we present updated results from the phase 2 portion of the trial, focusing on efficacy and safety of the VDCR, VDR, and VDC regimens. Methods: Previously untreated patients with measurable disease were randomized to one of four treatment groups receiving up to eight 21-d cycles of VDCR (V 1.3 mg/m2 d 1, 4, 8, 11; D 40 mg d 1, 8, 15; R 15 mg d 1–14; C 500 mg/m2 d 1, 8), VDR (VD as in VDCR but with R 25 mg d 1–14), VDC (VDC as in VDCR), or VDC-mod (as for VDC but with an additional dose of C on d 15) as induction therapy, followed by four 42-d maintenance cycles of V 1.3 mg/m2 (d 1, 8, 15, 22) (all treatment arms). Patients eligible for autologous stem cell transplant (SCT) could undergo stem cell mobilization any time after cycle 2 and SCT any time after cycle 4. The primary endpoint was the combined complete response (CR) + very good partial response (VGPR) rate; secondary endpoints included safety/tolerability, time to response, duration of response, progression-free survival, and rate of minimal residual disease (MRD) negativity. Responses were assessed according to International Myeloma Working Group (IMWG) uniform criteria using an automated computer algorithm. Adverse events (AEs) were graded using the CTCAE v3.0. Results: Patient characteristics were similar among the groups with respect to age, performance status, ISS stage, and proportion of patients with high-risk cytogenetic features. Patients received a median of 5, 6, 6, and 6 treatment cycles in the VDCR, VDR, VDC, and VDC-mod arms, respectively; 65%, 60%, 52%, and 47% of patients had dose reductions of any drug. In the VDCR, VDR, VDC, and VDC-mod arms, respectively, 52%, 62%, 58%, and 65% of patients completed treatment; 31%, 43%, 24%, and 41%, respectively, underwent SCT. In the phase 2 response-evaluable patients (n=132), all treatment regimens showed substantial efficacy, with CR+VGPR rates of 59% (VDCR), 50% (VDR), 41% (VDC), and 59% (VDC-mod) (Table) (includes pre-transplant responses only in SCT patients). Of MRD-assessed patients, 46% (21/46) of those who achieved CR (including sCR) or nCR were MRD-negative; 48% (10/21), 75% (9/12), 0% (0/7) and 33% (2/6) in the VDCR, VDR, VDC and VDC-mod arms, respectively. Median time to first response was similar across arms (range 1.6–1.8 months); median time to best response of CR+VGPR was 4.0 months (VDCR), 3.4 months (VDR), 5.1 months (VDC), and 3.1 months (VDC-mod). Median duration of response has not been reached in any arm to date. All treatment regimens were generally well tolerated. In the VDCR, VDR, VDC, and VDC-mod arms, at least one grade ≥3 AE was observed in 81%, 76%, 79%, and 88% of enrolled patients, respectively; serious AEs were experienced by 42%, 40%, 21%, and 41% of patients, and AEs resulting in study discontinuation were reported for 19%, 17%, 12%, and 6% of patients. The five most common all-grade AEs across all treatment groups were fatigue (range 47–67%), nausea (36–67%), constipation (40–62%), diarrhea NOS (42–65%), and neutropenia (19–52%). The incidence of grade ≥3 (grade ≥2) peripheral neuropathy (PN) was 13% (40%) in the VDCR arm, 14% (45%) VDR, 9% (48%) VDC, and 18% (41%) VDC-mod; there was no grade 4 PN. Rates of grade ≥3 neutropenia/thrombocytopenia were 42%/10% for VDCR, 7%/7% VDR, 36%/12% VDC, and 65%/18% VDC-mod. Conclusions: All regimens appear highly active and generally well tolerated in previously untreated MM patients. The four-drug combination did not result in a substantial increase in response rate and was associated with a modest increase in the incidence of hematologic toxicities. Continuous weekly C in the VDC regimen was associated with high response rates and rapid responses, comparable to the VDR and VDCR arms. Outcome data will be presented following longer follow-up. Disclosures: Kumar: Celgene: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Merck: Consultancy, Research Funding; Novartis: Research Funding; Genzyme: Consultancy, Research Funding; Cephalon: Research Funding; Bayer: Research Funding. Off Label Use: Lenalidomide for treatment of newly diagnosed myeloma. Flinn:Millennium Pharmaceuticals, Inc.: Research Funding. Richardson:Celgene, Millennium, Novartis, Johnson & Johnson: Membership on an entity's Board of Directors or advisory committees. Hari:Celgene: Research Funding. Callander:Millennium Pharmaceuticals, Inc.: Research Funding. Noga:Amgen: Honoraria, Research Funding, Speakers Bureau; Millennium: Consultancy, Honoraria, Research Funding, Speakers Bureau; Ortho-Centicor: Honoraria, Speakers Bureau; Cephalon: Honoraria, Research Funding, Speakers Bureau; Celgene: Honoraria, Research Funding, Speakers Bureau. Stewart:Millennium Pharmaceuticals, Inc.: Honoraria, Research Funding; Celgene: Honoraria. Rifkin:Millennium Pharmaceuticals, Inc.: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Speakers Bureau; Amgen: Speakers Bureau; Cephalon: Speakers Bureau; Dendreon: Speakers Bureau. Wolf:Millennium Pharmaceuticals: Consultancy, Honoraria, Speakers Bureau; Genentech and Multiple Myeloma Research: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Speakers Bureau; OrthoBiotech: Honoraria, Speakers Bureau; Celgene: Honoraria, Speakers Bureau. Estevam:Millennium Pharmaceuticals: Employment. Mulligan:Millennium Pharmaceuticals, Inc.: Employment. Shi:Millennium Pharmaceuticals: Employment. Webb:Millennium Pharmaceuticals: Employment.

Abstract Background: Lenalidomide (Revlimid®), an immunomodulatory drug (IMiD®), was recently approved in the US for treatment of relapsed/refractory multiple myeloma and myelodysplastic syndromes associated with a deletion 5q[31] cytogenetic abnormality. Lenalidomide also has demonstrated activity in chronic lymphocytic leukemia and cutaneous T-cell lymphoma while thalidomide, a less potent IMiD®, has activity in non-Hodgkin’s lymphoma (NHL) as both monotherapy and in combination with rituximab. Aim: To assess the safety and efficacy of lenalidomide monotherapy in subjects with relapsed/refractory indolent NHL. Methods: Subjects with relapsed/refractory indolent NHL following at least 1 prior treatment regimen with measurable disease are eligible. Subjects receive 25 mg lenalidomide orally once daily on Days 1–21 every 28 days and continue therapy for 52 weeks as tolerated or until disease progression. Response and progression are evaluated using the IWLRC methodology. Results: As of July 25, 2006, 23 subjects of a planned 40 have enrolled and received drug. Fifteen subjects are currently evaluable for tumor response. The median age of the 15 response-evaluable subjects is 64 (54–82) and 5 are female. Histology is small lymphocytic lymphoma [SLL] (n=8), follicular center lymphoma grades 1,2 [FL] (n=5) and nodal marginal B-cell lymphoma [NML] (n=2). Median time from diagnosis to lenalidomide monotherapy is 7.6 (3–14) years and median number of prior treatment regimens per subject is 3 (1–17). Two subjects (13%) exhibited an objective partial response (PR) at four months. Both responses, one FL and one NML, occurred in subjects with substantial tumor burden of 61.8 cm2 and 80.3 cm2, respectively. The 4-month time-to-response for these indolent NHL subjects is longer than the 2-month median time-to-response in aggressive NHL subjects (n=7) following lenalidomide monotherapy. Seven patients had stable disease (SD) for a tumor control rate (TCR) of 60% and 6 had progressive disease (PD). Grade 3 or 4 adverse events occurred in 9 (39%) subjects. These were predominantly Grade 3 hematological events (neutropenia, thrombocytopenia) with only 3 subjects (13%) experiencing a Grade 4 adverse reaction (all neutropenia). Conclusion: Early results of lenalidomide monotherapy in indolent NHL show evidence of activity with a safety profile similar to that established previously in other hematological malignancies.