Kumar, Shaji

Abstract Abstract 1808 Background: Approximately 50% of the Multiple Myeloma (MM) cases are associated with hyperdiploidy (Hyperdiploid MM, HDMM), usually of the odd numbered chromosomes. The majority of the remaining patients with MM have translocations involving the immunoglobulin heavy chain (IgH) locus on chromosome 14q32 (Translocated MM, TMM).(Fonseca R, Leukemia 2009;23:2210-21) However, most of these estimates are from studies done in predominantly white populations. MM is approximately two fold more common in blacks, and results from the phase 3 study of lenalidomide and dexamethasone suggested that blacks may have better outcome. (Rajkumar SV, Lancet Oncol 2010;11(1):29-37) Goals: The purpose of this study was to determine the cytogenetic characteristics and outcome of MM in blacks, and to compare this with a similar population of white patients seen during the same time period. Methods: We studied African American and African patients with MM diagnosed from May 2002 through June 2010 at John H. Stroger, Jr. Hospital of Cook County (CC), Chicago, IL and comparable Caucasian population seen at Mayo Clinic (MC), Rochester, MN between these dates with available cytogenetic studies (karyotyping and/or fluorescent in situ hybridization (FISH) data) at diagnosis. The results between both populations were then compared. Results: 65 blacks (25 men and 40 women) and 490 Caucasians (290 men and 200 women) with MM were studied. Karyotyping was available in 98% of patients from both cohorts, and FISH was available for 35% and 64% of the CC and MC cohorts, respectively. A molecular classification was possible in 16 (25%) of the CC cohort (12 HDMM, 4 TMM) and 294 (60%) of the MC cohort (38% HDMM, 22% TMM). In the remaining patients, both tests were normal or showed changes not definitive for either IgH translocations or hyperdiploidy. At diagnosis, abnormal cytogenetics by karyotyping was present in 25/65 (38%) of the CC cohort and 154/479 (32%) of the MC cohort. The median overall survival (OS) from diagnosis for the CC and MC cohorts was similar at 64 months. The median OS was significantly shorter for those with an abnormal cytogenetics; 35 months vs. 65 months in the CC cohort (P0.03) and 49 months vs. not reached for the MC cohort (P < 0.01). OS was superior among patients in the CC cohort initially treated with an immunomodulatory agent (IMiD) containing regimen (65 months vs. 35 months for those receiving a bortezomib or other non-IMiD containing regimens (P=0.02; Figure 1). Similarly, in the MC cohort, patients receiving an IMiD based regimen had a superior OS (not reached vs. 42 months; P < 0.001). The use of immunomodulatory therapy did not differ across cytogenetic types. Conclusions: The current study suggests that IgH translocations were less frequently seen in blacks compared with what is typically reported in the literature. This may explain the relatively better survival reported in blacks compared with whites in recent trials. We found a significantly superior outcome in blacks treated initially with regimens containing immunomodulatory agents compared to other regimens. Disclosures: No relevant conflicts of interest to declare.

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 Background WM remains an incurable cancer despite recent advances. While a phase II trial has demonstrated efficacy of dexamethasone, rituximab and cyclophosphamide (DRC) in the treatment-naïve (TN) patients, this regimen has not been studied systematically in the relapsed/refractory (R/R) setting. Recent data has suggested the MYD88mutation status in WM patients can serve as a predictive marker with therapies such as ibrutinib. We examined the efficacy and tolerability of up to 6 cycles of DRC, with focus on R/R population and activity of this regimen with respect to the patients' MYD88L265Pstatus. Methods Records of WM patients seen consecutively at Mayo Clinic campuses in Rochester, Arizona and Florida from 01/2007 to 12/2014 were reviewed. MYD88L265P status, as assessed by AS-PCR, was recorded when available. Data obtained from symptomatic patients treated with DRC (dexamethasone 20 mg intravenously followed by rituximab 375 mg/m2 intravenously on day 1 and cyclophosphamide 100 mg/m2 orally bid on days 1 to 5) were analyzed. Time-to-event analyses were performed from DRC therapy using the Kaplan-Meier method. We used the Consensus response criteria (6th International Workshop). Results Of 100 symptomatic patients who received DRC, 50 had R/R WM (40% refractory) and 50 were TN. Table 1 shows the patients' baseline characteristics. In the R/R population, DRC was 2nd line (range 2-8) therapy in 58% of patients. The median IgM levels declined from 3,870 mg/dL to 1,846 mg/dL (p=0.0001) at best response. Median follow-up from DRC was 51 months (95% CI: 38-55). The median time-to-best response was 6.8 (0.5-28) months. Overall response rate (ORR) was 87% [VGPR 4%, PR 64%, MR 19%]. Four patients (9%) achieved SD and 2 patients (4%) had PD. Of the sixteen deaths (32%) noted at time of analysis, 11 were related to progressive disease. The median disease-specific survival (DSS) from DRC was not reached (NR) (95% CI: NR-NR). The median progression-free survival (PFS) and time-to-next-therapy (TTNT) were 32 months (95% CI: 15-51) and 50 months (95% CI: 35-60), respectively. In contrast, in the TN patients the median IgM levels declined from 4,130 mg/dL to 1,250 mg/dL (p=0.0001) at best response; median time to best response was 11 (0.6-47) months; median follow-up from DRC was 30 months (95% CI: 21-36). ORR was 96% [VGPR 17% (n=8), PR 70% (n=32), MR 9% (n=4)]. Of the 7 deaths (14%) at time of analysis, 4 were related to WM progression. Median DSS from DRC was NR (95% CI: NR-NR); median PFS and TTNT were 34 months (95% CI: 23-NR) and NR (95% CI: 37-NR), respectively. Among 29 genotyped patients in whom MYD88 mutation status was available, MYD88L265P was present in 25 patients (8 of 10 TN and 17 of 19 R/R patients). The response rates and the time-to-event outcomes were similar in the MYD88L265P and wild-type patients. Grade ≥3 adverse effects included neutropenia (20%), thrombocytopenia (7%) and infections (3%). Conclusions Similar to the frontline setting, DRC is an active and well-tolerated salvage regimen. In contrast to ibrutinib, DRC offers a less expensive, limited-duration treatment option, with preliminary data suggesting activity independent of patients' MYD88 mutation status. Disclosures Ailawadhi: Pharmacyclics: Consultancy; Novartis: Consultancy; Amgen Inc: Consultancy; Takeda Oncology: Consultancy. Kumar:Glycomimetics: Consultancy; Sanofi: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; Onyx: Consultancy, Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Kesios: Consultancy; Array BioPharma: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy. Dispenzieri:Jannsen: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; pfizer: Research Funding; Celgene: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; Alnylam: Research Funding; GSK: Membership on an entity's Board of Directors or advisory committees. Ansell:BMS, Seattle Genetics, Merck, Celldex and Affimed: Research Funding. Kapoor:Amgen: Research Funding; Celgene: Research Funding; Takeda: Research Funding.

Abstract Abstract 4078 Background: Cytokine stimulated signaling pathways contribute to multiple myeloma (MM) disease progression and in acquired resistance to current treatment options making MM an incurable malignancy. It is very well documented that HGF is a cytokine that is secreted by bone marrow stromal cells which has an autocrine and paracrine role in the disease progression in a myeloma setting. HGF binds to its receptor tyrosine kinase on MM cells, MET and this binding at the extracellular domain results in activation of MET which interacts with several of its target proteins resulting in increased survival, increased proliferation, cell cycle progression, motility, migration and invasion. In normal bone marrows, co-expression of MET and its ligand HGF is a rarity whereas co-expression is a common feature of MM. Elevated levels of HGF have been observed in serum and bone marrows of MM patients with a negative correlation to disease progression. In addition, increased HGF levels cause abnormal and reduced bone formation in patients. HGF gene levels in MM samples have been observed to be significantly up regulated in myeloma cells when compared to normal cells. Recently, studies have identified that HGF facilitates the MM cells to adhere to fibronectin, a bone marrow matrix protein, thereby positively impacting MM cell invasion and proliferation. Overall, HGF and its receptor mediated pathway influences tumor progression in myeloma by targeting several different aspects of the disease biology and hence is a very attractive and potentially very important target for improving treatment regimens in a myeloma setting. Methods: MK2461 was synthesized by Merck Inc. (Whitehouse Station, NJ, USA). Stock solutions were made using DMSO and working stock solutions were made using RPMI 1640 media containing 10% fetal bovine serum (20% serum for primary patient cells) supplemented with L-Glutamine, penicillin, and streptomycin. MTT assay was performed to study drug induced cytotoxicity and thymidine uptake was used as a measure to study differences in proliferation. Flow cytometry using Annexin V-FITC and propidium iodide (PI) was used to measure drug induced apoptosis in cell lines and patient cells. In order to study the mechanism of action of the drug, immunoblotting studies were performed on lysates made from cell lines incubated with the drug for various durations. Results: MK2461 treatment led to dose and time dependent cytotoxicity in a few myeloma cell lines (OPM2, DOX40, RPMI8226 and LR5) but not in others (MM1S, MM1R, H929 and U266). The IC50 values for the sensitive lines varied from 1μ M (OPM2) to 10μ M (DOX40, RPMI8226 and LR5). However, MK2461 significantly inhibited the proliferation of MM cells at sub IC50 concentrations in all cell lines tested except MM1S. This inhibition of proliferation was observed when cells were co-cultured with stromal cells or cytokines, namely VEGF, IL6 or HGF. Culturing MM cells with increasing doses of HGF was still unable to protect them from drug induced inhibition of proliferation. MK2461 was able to induce time dependent increase in apoptosis (as measured by annexin/PI), decrease in proliferation (as measured by BrdU assay) and induction of cell cycle arrest in the drug sensitive cell lines. This effect was not observed in MM1S cells. Exploring the mechanism of action of the drug indicated that MK2461 treatment led to down regulation of pc-Met, pGab1, pAkt and pErk in both the drug sensitive (OPM2) and drug resistant (MM1S) cell lines. However, proteins down stream of Akt in the PI3K/Akt pathway, namely pGSK3β, p70S6K, Bcl2, cyclin E and cyclin D3 were down regulated only in OPM2 cells. On the contrary, we observed up-regulation of these proteins in the drug resistant cell line offering a possible explanation for the drug resistant phenotype. We have also examined combinations of MK2461 with inhibitors of PI3K/Akt pathway. Conclusion: These studies demonstrate significant in-vitro activity of MK2461 in MM. Our results suggest the presence of two populations one very sensitive to MK2461 and one insensitive. Differential effects on the signaling pathways provide important clues to the mechanisms of action of c-met inhibitors in myeloma. The results form the basis for clinical evaluation of MK2461 in MM. Disclosures: Kumar: Celgene: Consultancy, Research Funding; Millennium: Research Funding; Merck: Consultancy, Research Funding; Novartis: Research Funding; Genzyme: Consultancy, Research Funding; Cephalon: Research Funding.

Abstract Abstract 370 Background: Light chain (AL) amyloidosis is characterized by the deposition of amyloid derived from immunoglobulin light chains in various organs. Autologous peripheral blood stem cell transplantation (SCT) is a commonly used and effective treatment for AL. For patients (pts) undergoing this procedure, a proportion of pts receive treatment similar to induction therapy employed in pts with myeloma undergoing SCT. However, the significance of induction therapy and its impact on the overall survival (OS) in AL is unknown. We conducted this study to ascertain the role of pre-SCT therapy on the post-transplant outcomes in AL. Patients and methods: 435 pts with AL who underwent SCT at our institution between March 1996 and May 2010 form the study group. Groups were compared using Fisher's exact test or t-test, and survival was calculated using Kaplan Meier method. Survival curves were compared using log rank test. Result: The median (range) age of pts at the time of SCT was 57.4 years (26-75); 260 (60%) were males. The median (range) duration from AL diagnosis to SCT was 4 mos (1-87), and 284 (65%) pts were alive at the time of analysis. Melphalan 200/m2 (271 pts) or Mel/TBI (17 pts) was used for conditioning in 66% pts, whereas the remaining one-third had reduced doses of melphalan (100-160 mg/m2). The median OS for pts that received pre-SCT therapy (N=286) compared with those who did not (N=149) was 94.7 and 96.5 months, respectively (P=0.6) (Fig 1). Among the group of pts who underwent pre-SCT therapy and were evaluable for response, the median OS for those with a hematologic response (N=42) and no hematologic response (N=42) was 82.1 and 51 months (P=0.2), respectively (Fig 2). Conclusion: Our study demonstrates no difference in the OS of AL patients who received a pre-SCT therapy compared with those who received a SCT after their diagnosis of AL. In patients receiving pre-SCT therapy, there was a trend towards reduced OS among those with no hematologic response to pre-transplant therapy, but this difference was not significant. Disclosure: Kumar: Celgene: Consultancy, Research Funding; Millennium: Research Funding; Merck: Consultancy, Research Funding; Novartis: Research Funding; Genzyme: Consultancy, Research Funding; Cephalon: Research Funding. Dispenzieri:Celgene: Honoraria, Research Funding; Binding Site: Honoraria.

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 Abstract 3554 Introduction: The role of SCT in the management of Ig light chain (AL) amyloidosis remains undefined. Patients: We report 422 patients (Table 1) who received SCT for AL amyloidosis to compare outcomes of patients treated before January 2006 with those of patients treated from January 2006 until December 1, 2009. Results: Day 100 all-cause mortality decreased over this time period from 12% to 7% (P=.09) figure 1. Survival at 2 years increased from 78% to 82%. Figure 2 The major determinants of early mortality (before day 100) were the presence of cardiac involvement with amyloid and increased levels of cardiac biomarkers, lower serum albumin, higher serum creatinine, and a higher number of organs involved. (Table 2) On multivariate survival analysis, higher levels of serum troponin T and N-terminal pro–brain natriuretic peptide were the only predictors of early mortality after SCT. Conclusion: Improved supportive care and refined patient selection has improved the safety margin for patients undergoing SCT; short-term mortality showed a more than 40% decrease after 2005. Recognition of this decrease in mortality is important for physicians caring for these patients as they weigh the pros and cons of SCT vs novel agent-based treatment in management of amyloidosis. Disclosures: Gertz: Celgene: Honoraria; Millenium: Honoraria, Membership on an entity's Board of Directors or advisory committees. Lacy:Celgene: Research Funding. Dispenzieri:Celgene: Honoraria, Research Funding; Binding Site: Honoraria. Kumar:Celgene: Consultancy, Research Funding; Millennium: Research Funding; Merck: Consultancy, Research Funding; Novartis: Research Funding; Genzyme: Consultancy, Research Funding; Cephalon: Research Funding.

Abstract Multiple myeloma (MM) is characterized by significant genetic diversity at subclonal levels that likely plays a defining role in the heterogeneity of tumor progression, clinical aggressiveness and drug sensitivity. Such heterogeneity is a driving factor in the evolution of MM, from founder clones through outgrowth of subclonal fractions. DNA Sequencing studies on MM samples have indeed demonstrated such heterogeneity in subclonal architecture at diagnosis based on recurrent mutations in pathologically relevant genes that may ultimately to lead to relapse. However, no study so far has reported a predictive gene expression signature that can identify, distinguish and quantify drug sensitive and drug-resistant subpopulations within a bulk population of myeloma cells. In recent years, our laboratory has successfully developed a gene expression profile (GEP)-based signature that could not only distinguish drug response of MM cell lines, but also was effective in stratifying patient outcomes when applied to GEP profiles from MM clinical trials using proteasome inhibitors (PI) as chemotherapeutic agents. Further, we noted myeloma cell lines that responded to the drug often contained residual sub-population of cells that did not respond, and likely were selectively propagated during drug treatment in vitro, and in patients. In this study, we performed targeted qRT-PCR analysis of single cells using a gene panel that included PI sensitivity genes and gene signatures that could discriminate between low and high-risk myeloma followed by intensive bioinformatics and statistical analysis for the classification and prediction of PI response in individual cells within bulk multiple myeloma tumors. Fluidigm's C1 Single-Cell Auto Prep System was used to perform automated single-cell capture, processing and cDNA synthesis on 576 pre-treatment cells from 12 cell lines representing a wide range of PI-sensitivity and 370 cells from 7 patient samples undergoing PI treatment followed by targeted gene expression profiling of single cells using automated, high-throughput on-chip qRT-PCR analysis using 96.96 Dynamic Array IFCs on the BioMark HD System. Probability of resistance for each individual cell was predicted using a pipeline that employed the machine learning methods Random Forest, Support Vector Machine (radial and sigmoidal), LASSO and kNN (k Nearest Neighbor) for making single-cell GEP data-driven predictions/ decisions. The weighted probabilities from each of the algorithms were used to quantify resistance of each individual cell and plotted using Ensemble forecasting algorithm. Using our drug response GEP signature at the single cell level, we could successfully identify distinct subpopulations of tumor cells that were predicted to be sensitive or resistant to PIs. Subsequently, we developed a R Statistical analysis package (http://cran.r-project.org), SCATTome (Single Cell Analysis of Targeted Transcriptome), that can restructure data obtained from Fluidigm qPCR analysis run, filter missing data, perform scaling of filtered data, build classification models and successfully predict drug response of individual cells and classify each cell's probability of response based on the targeted transcriptome. We will present the program output as graphical displays of single cell response probabilities. This package provides a novel classification method that has the potential to predict subclonal response to a variety of therapeutic agents. Disclosures Kumar: Skyline: Consultancy, Honoraria; BMS: Consultancy; Onyx: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Novartis: Research Funding; Takeda: Consultancy, Research Funding; Celgene: Consultancy, Research Funding.

Abstract Abstract 4990 Background: Although there have been improvements in 5-year overall survival (OS) rates among patients with AL amyloidosis over the past decades, OS is still poor, and death rates within the first 3–6 months after diagnosis have not changed significantly. This retrospective study was performed to identify risk factors for and causes of death during the first 90 days following diagnosis of AL amyloidosis. Method: From July 2002 to April 2009, 301 patients with a diagnosis of AL amyloidosis who were seen at Mayo Clinic within 30 days of diagnosis were identified from the dysproteinemia database. The 100 who died within 90 days were the focus of our study. The other 201 who were alive beyond 90 days were used as a comparator group. Outside physician offices were contacted to obtain further information pertaining to treatment and cause of death for our study group. Results: Of the 100 patients with early death, median age at diagnosis was 63.7 years (range: 34.7–89.4). 25 patients were diagnosed with concurrent multiple myeloma (MM) based on MM-specific end-organ damage. Overall, the number of patients with 2, 3 and 4 organs (cardiac, renal, nerve or liver) involved with amyloidosis was 37, 15 and 4, respectively. Using the cardiac biomarker staging system, 78% of 46 evaluable patients were stage III at diagnosis followed by 22% stage II and no stage I. Table 1 describes the characteristics of the studied population. Amyloid-related deaths were identified in 61 patients with the most common cause being cardiac arrest or sudden death (33%) followed by end-organ failure (24%). Treatment was started in 50% of patients; 34% received no treatment; and no treatment information was available for the remainder. OS was 54.5 days in patients who received treatment as compared to 7.5 days in those who received no treatment (p<0.0001); outcomes were similar in the group in whom no treatment information was available and those patients who were known to have received treatment. Melphalan with dexamethasone was the most common treatment (21%) and was associated with improved OS compared to other treatments including novel agents (57 vs. 26 days, p=0.003). Outcomes were no different if the patients had received novel therapies, but numbers were small. When compared to patients who lived for more than 90 days from their diagnosis, patients with early mortality had higher median intraventricular septum (IVS) (15 vs. 13 mm, p<0.0001), lower ejection fraction (EF) (50 vs. 64%, p<0.0001), and higher troponin-T (0.125 vs. 0.01 ng/ml, p<0.0001) and NT-proBNP (9020 vs. 1292 pg/ml, p<0.0001). We also found that patients who died within 90 days of their diagnosis had significantly higher plasma cell labeling index (PCLI), uric acid, beta-2 microglobulin, involved free light chain (FLC) and creatinine. Conclusion: This study highlights the characteristics of patients who died within 90 days of diagnosis of AL amyloidosis. The majority of patients died from arrhythmia and organ failure. This implies that other interventions aside from treatment of the underlying plasma cell (PC) disorder will likely be required to change the early outcomes of this disease. Disclosures: Lacy: Celgene: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Millennium: Research Funding; Merck: Consultancy, Research Funding; Novartis: Research Funding; Genzyme: Consultancy, Research Funding; Cephalon: Research Funding. Dispenzieri:Celgene: Honoraria, Research Funding; Binding Site: Honoraria.

Abstract Background Waldenstrom macroglobulinemia (WM) is an IgM-associated lymphoplasmacytic lymphoma, first described over seven decades ago. Although WM is typically a disease of the elderly, with a median age at diagnosis of ~ 67 years, approximately 10% of patients are ≤50 years (y) of age at diagnosis. Data for young patients are sparse and the few available studies demonstrate inconsistent findings, with potential overestimation of survival owing to inclusion of patients with smoldering WM. In this case-control study, we evaluate outcomes, prognostic features and impact of changing therapies in a large cohort of young symptomatic WM patients compared to matched older patients seen over the course of the past five decades. Methods The medical records of all WM patients seen consecutively at Mayo Clinic from 01/1960 to 10/2013 were reviewed. Of 1181 patients, 140 (11.8%) were ≤ 50 y of age at diagnosis. A cohort of patients 65 y or older at diagnosis, matched 1:1 by the time of diagnosis, served as the control population. The patients were divided into 3 groups based on the timing of initiation of therapy: Group 1 (1960-1977), Group 2 (1978-1995) and Group 3 (1996-2013). The baseline characteristics were compared. Initiation of frontline therapy was used for all time-to-event analysis using the Kaplan Meier method. Results Younger patients were more likely to present with adenopathy and splenomegaly, have higher IgM levels and hyperviscosity symptoms (Table 1). The median follow-up from the frontline therapy was similar (10.7 y vs. 10 y for the control population). At the time of analysis, 91% of the deaths for the younger cases were WM-related compared to 58% in the control arm (p=0.0001). Younger patients had a better OS with a median disease-specific survival (DSS) of 15.6 y (95% CI: 13-21; 10-y OS of 77%) vs. 11 y (95% CI: 7.8-12; 10-y OS of 51%) for the older patient (p=0.0003). Among the young patients, there was no difference in the median DSS across the 3 groups (p=0.42). However, the median DSS for the control group incrementally improved (p=0.02) over the 3 time periods (Table 1). In the younger patients, no improvement in DSS was noted with the use of either frontline rituximab-based therapy compared to non-rituximab based regimens [median NR (95% CI: 7.6-NR) vs. 15.8 y (95% CI: 13-22) with other regimens, p=0.30], or frontline chlorambucil-based compared to non-chlorambucil based regimens [median 16 y (95% CI: 12-22) vs 15.6 y (95% CI: 12-NR) with other regimens, p=0.73]. In the control group, however, there was significant difference in DSS among patients who received frontline rituximab-based compared to non-rituximab based regimens [median NR (95% CI: 8.3-NR) vs 9.1 y (95% CI: 5.6-12) with other regimens, p=0.04], or frontline chlorambucil-based vs non-chlorambucil based regimens [8 y (95% CI: 5-12) vs 12.3 y (95% CI: 11-NR) in other regimens; p=0.001]. Conclusion Striking differences in presentation are evident in young WM patients compared to their older counterparts. The incorporation of rituximab to the previously existing anti-WM regimens and the transition to non-chlorambucil based regimens has resulted in substantial survival gains in the older WM population over the past five decades. However, such improvement in outcome has not yet been observed in the young patients. The majority of younger patients, despite a protracted disease course, succumb to their disease. Disclosures Ansell: BMS, Seattle Genetics, Merck, Celldex and Affimed: Research Funding. Ailawadhi:Pharmacyclics: Consultancy; Novartis: Consultancy; Amgen Inc: Consultancy; Takeda Oncology: Consultancy. Reeder:Novartis: Research Funding; Celgene: Research Funding; BMS: Research Funding; Millennium: Research Funding. Kumar:Kesios: Consultancy; Janssen: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; AbbVie: Research Funding; BMS: Consultancy; Onyx: Consultancy, Research Funding; Glycomimetics: Consultancy; Millennium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; Array BioPharma: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees. Dispenzieri:Alnylam: Research Funding; Celgene: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; pfizer: Research Funding; Jannsen: Research Funding. Kapoor:Celgene: Research Funding; Takeda: Research Funding; Amgen: Research Funding.