Rajkumar, S. Vincent

Abstract BACKGROUND: The introduction of novel agents and proteasome inhibitors, and advances in high dose therapy administration has made an impact on the survival outcomes for MM patients. However, HRMM still remains a therapeutic challenge with poor prognosis. Even with aggressive approaches such as the Total Therapy protocols, patients with poor genomic risk have a 2-year event-free survival of ~50% (Nair et al, Blood 2010). A randomized Phase I/II trial was designed to evaluate the efficacy of adding immunotherapy into the first line for HRMM patients, comparing lenalidomide, bortezomib and dexamethasone (RVD) with or without addition of elotuzumab (Elo), a humanized monoclonal antibody that binds to SLAMF7/CS1. We are reporting on the Phase I portion of the study. PATIENTS & METHODS: The objective of Phase I was to determine the maximum tolerated dose (MTD) of RVD-Elo. Both low/standard risk MM and HRMM patients were eligible. HRMM was defined by one or more of the following: (1) poor risk genomics by the Arkansas 70-gene model, (2) translocation (14;16), translocation (14;20) and/or deletion (17p) by florescent in-situ hybridization (FISH), (3) primary plasma cell leukemia and (4) serum LDH > 2 times normal levels. The treatment consisted of induction chemotherapy for 8 cycles with RVD-Elo (lenalidomide 25 mg orally days 1-14 of every 21-day cycle; bortezomib 1.3 mg/m2 subcutaneously days 1,4,8,11; dexamethasone 20 mg orally days 1,2,4,5,8,9,11,12; elotuzumab 10 mg/kg intravenously days 1,8,15 cycles 1-2 then days 1,11 cycles 3-8) followed by dose-attenuated RVD-Elo maintenance (lenalidomide 25 mg orally days 1-14; bortezomib 1.0 mg/m2 subcutaneously days 1,8,15; dexamethasone 12 mg orally days 1,8,15; elotuzumab 10 mg/kg intravenously days 1,15) until disease relapse, progression or intolerance. Adverse events (AE) were recorded as per the NCI CTCAEv4.0. RESULTS: Eight newly diagnosed MM patients were enrolled on the Phase I run-in study. Six patients (Figure 1) were evaluable for dose limiting toxicities (DLT) during Cycle 1 as per protocol. The median age of patients was 67 years (range: 56-79 years), with 67% ≥65 years, Hgb was less than 10 g/dL in 50%, creatinine was greater than 2 mg/dL in all patients. ISS stage distribution was 17% (I), 33% (II) and 50% (III). Deletion 13 was observed in 1 patient (17%). The most common AEs (all grades) were fatigue (100%), peripheral sensory neuropathy (83%), edema (83%), lymphopenia (66%) and leukopenia (50%). The most common Grade 3 AEs were peripheral sensory neuropathy (33%), one of which was a DLT, neutropenia (17%) and thrombocytopenia (17%). One Grade 4 lymphopenia was observed. All 6 patients have completed 8 cycles of RVD-Elo induction therapy and 5 patients have completed at least 4 cycles of RVD-Elo maintenance. Overall median days on therapy per cycle were 13 days during induction and 20 days per cycle during maintenance. Dose adjustments were made in 83% of patients for bortezomib, 83% for lenalidomide and 33% for dexamethasone. There were no dose reductions for elotuzumab, although three patients had 1 event each of dose delays/missed dosing attributable to AE/SAE from RVD. Efficacy data will be released at the time that the phase II study of RVD +/- Elo is mature. Discussion/Conclusion: The RVD-Elo is a safe well-tolerated regimen for newly diagnosed MM patients without major additive AE/SAE beyond what is already known about RVD. This is the first report of the only phase I experience combining the triple-drug regimen RVD with the monoclonal antibody Elotuzumab for newly diagnosed MM. Support: NCI grants CA32102, CA38926, CA180821, CA31946, CA21076, CA180799, CA21115, CA180820 and in part by Bristol-Myers Squibb Company Disclosures Usmani: Celgene Corporation: Consultancy, Honoraria, Research Funding; Millennium: Consultancy, Honoraria; Onyx: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy; Array BioPharma: Research Funding; Janssen: Research Funding; Pharmacyclics: Research Funding. Off Label Use: Lenalidomide in newly diagnosed multiple myeloma patients. Ailawadhi:Millennium: Honoraria. Shah:Onyx Pharmaceuticals: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Millennium Pharmaceuticals: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Array: Consultancy, Research Funding. Rosenzweig:Celgene: Speakers Bureau. Durie:IRC J&J: Membership on an entity's Board of Directors or advisory committees; Celgene Corp: Expert Board Committee Other; IRC Onyx: Membership on an entity's Board of Directors or advisory committees; DMC Millennium: Membership on an entity's Board of Directors or advisory committees. Orlowski:Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Onyx Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium: The Takeda Oncology Company: Membership on an entity's Board of Directors or advisory committees, Research Funding; Spectrum Pharmaceuticals: Research Funding; JW Pharmaceutical: Research Funding; Array BioPharma: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees; Janssen Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees.

Abstract Background: Proliferation rate of plasma cells (PC) is a powerful tool in evaluating all types of monoclonal gammopathies, predicting for progression as well as survival in all phases of the disease. A flow cytometry (FC)-based method to delineate the cell cycle of clonotypic PCs and determine the proportion in S-phase was developed. This method replaces a labor-intensive slide based methodology, but the prognostic power of this FC approach has not been clearly elucidated. Methods: A total of 1061 patients who had bone marrow (BM) FC PC proliferation analysis at Mayo Clinic, Rochester from May 2012 to December 2013 were studied. These included MGUS/ SMM (n=134), newly diagnosed (NMM; n=88), plateau in response (>=PR; n=544), and stable disease (n=38), and relapsed disease (RMM; n=257). PC proliferation was measured by 8-color FC using antibodies to CD19, CD38, CD138, CD45, and cytoplasmic kappa and lambda Ig light chains, and DAPI DNA staining. The DNA content of the abnormal, clonotypic PCs was specifically analyzed and the %S-phase was determined by measuring the proportion of cells between G0/G1 and G2/M. All studies collected 5x105 events on BD FACSCanto II instruments and analysis was performed with BD FACSDiva software. The CV of the DAPI staining of G0/G1 lymphocytes as an internal control population was always less than 3.5. Patients with fewer than 300 PCs for assessment of %SP were designated as 0%. Results: The median follow up from testing for the entire cohort was 13 months (95% CI; 12.7, 13.3); 156 (15%) had died. The proportion of patients with adequate numbers of plasma cells available for %SP estimation and the median (IQR) %SP for the different groups are as shown in table. As expected, patients with MGUS/SMM and those in a response state had slightly lower proportions of patients with sufficient PCs to estimate %SP. The clinical features and outcomes were further analyzed using two cutoffs, %SP ≥1 and ≥2, in the different patient groups. Among most of the disease groups, especially the newly diagnosed MM and relapsed disease, %SP was prognostic for OS using both cutoffs (Table). Among the NMM in univariate analysis, %SP ≥2, B2microglobulin >5.5, age >70 and creatinine > 2 mg/dl were all significant, but only B2microglobulin >5.5 retained significance in multivariable analysis. Among the RMM, in univariate analysis, %SP ≥2, B2microglobulin >5.5, HR FISH (t4; 14, t14;16, t14;20 & del17p) and LDH >221 were all significant, but only %SP ≥2 was significant in multivariable analysis. Conclusion: The %S-phase of clonal PCs determined by FC is of prognostic value in patients with MM, in all disease phases. This is particularly relevant among patients with relapsed disease, where it is independent of some of the other known poor prognostic factors such as high risk FISH. This is in sharp contrast with recent studies that have shown no prognostic value for slide based labeling index in patients treated with novel agents. Abstract 2053. Table MGUS/SMM NMM >=PR SD Relapse N 134 88 544 38 257 N (%) with PCs measurable for proliferation 103 (77%) 84 (96%) 245 (45%) 31 (82%) 210 (82%) %SP (IQR) 0.3(0.1-0.7) 0.8 (0.4- 1.5) 0(0- 0.9) 0.8(0.3-1.3) 1.2(0.4- 2.7) OS (%SP >1 vs. rest) NS NR for either(P<0.01) NR for either (P<0.001) NR for either(P=0.02) 19 vs. NR(P<0.001) OS (%SP >2 vs. rest) NS NR for either (P=0.03) 20 vs. NR(P<0.001) NR for either(P=NS) 16 vs. NR(P<0.001) Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Abstract Background: Previous studies have demonstrated inferior overall survival (OS) among patients with AL amyloidosis who have bone marrow plasmacytosis (BMPC) >10%. It is well recognized that AL patients who achieve the deepest hematologic responses have superior organ response and OS rate. Methods: We designed a study to determine if BMPC% affects CR rate post ASCT and whether pre-transplant induction therapy improves response rate and OS among patients with a higher baseline BMPC burden. Results: Among 415 AL patients who underwent ASCT at Mayo Clinic, Rochester within 12 months of diagnosis, 116 (28%) had BMPC>10% at diagnosis. The median age was 57.2 years. The median follow up for surviving patients was 67.3 months. There was no statistically significant difference in age, gender, time from diagnosis to transplant, or use of attenuated conditioning regimen between groups with high (>10%) and low (≤ 10%) bone marrow involvement. The high BMPC group tended to receive more induction chemotherapy before ASCT, and presented with greater value of albumin, beta-2 microglobulin and difference in serum free light chain (dFLC). A higher CR rate was observed in low BMPC group (44.6% versus 26.7%, p=0.0013). In patients with high BMPC, a higher CR rate (33.9% versus 17.7%, p<0.05) was seen in those who received pre-ASCT induction therapy compared with no induction therapy. Among 3 groups of patients who had: no pre-ASCT therapy; steroid only as induction; and induction chemotherapy, the 5-year OS rates were 50.5%, 40% & 67.5%, respectively, p<0.03. Conclusions: Lower bone marrow burden at diagnosis yielded a deeper response following ASCT. Compared to no therapy, patients who were treated with steroid only pre-ASCT had an inferior OS, but other induction regimens appeared to improve survival. These data would support the concept that using induction therapy prior to ASCT conditioning among patients with higher tumor burden may be of value. Figure 1. In BMPC > 10% at diagnosis, OS comparison between induction therapies pre-ASCT Figure 1. In BMPC > 10% at diagnosis, OS comparison between induction therapies pre-ASCT Figure 2. Figure 2. Figure 3. Figure 3. Disclosures Kumar: Celgene: Research Funding; Celgene, Millenium, Sanofi, Skyline, BMS, Onyx, Noxxon,: Other: Consultant, no compensation,; Sanofi: Research Funding; AbbVie: Research Funding; Millenium/Takeda: Research Funding; Onyx: Research Funding; Skyline, Noxxon: Honoraria; Janssen: Research Funding. Gertz:Celgene: Honoraria; millenium: Consultancy, Honoraria; Onyx: Honoraria; Novartis: Honoraria; Smith Kline: Honoraria.

Abstract Background: Multiple myeloma (MM) cells evade apoptosis through multiple mechanisms thus enabling it to evade therapy. The Bcl2 family of anti-apoptotic proteins is aberrantly expressed in MM cell lines and patient cells. Yet, pharmacological intervention of this family appears to have significant activity only in molecular subgroups of MM patients. This clearly suggests alternate mechanisms of overcoming apoptotic signals in MM cells in addition to the Bcl2 family, through proteins such as IAPs. We have previously shown that simultaneous inhibition of the three major IAP proteins, namely cIAP1, cIAP2 and XIAP is required to induce pronounced apoptosis in MM cells. However, IAP inhibition results in apoptosis in only some MM cell lines and patient cells. Given that levels of Bcl2 family proteins are unaffected by IAP inhibition, we hypothesized that combined inhibition of the IAP proteins using a SMAC mimetic LCL161 and the Bcl2 family proteins using a pan-Bcl2 inhibitor obatoclax (OBX) will lead to more pronounced and synergistic cell death in a broader subgroup of MM patients. Methods: LCL161 was synthesized by Novartis Inc. (Basel, Switzerland). OBX was purchased from Selleckchem (Houston, USA). Stock solutions were made in DMSO, and subsequently diluted in RPMI-1640 medium for use. MM cell lines were cultured in RPMI 1640 containing 10% fetal bovine serum (20% serum for primary patient cells) supplemented with L-Glutamine, penicillin, and streptomycin. Cytotoxicity was measured using the MTT viability assay and proliferation using thymidine uptake. Apoptosis was measured using flow cytometry upon cell staining with Annexin V-FITC and propidium iodide (PI) for cell lines and patient cells. Immunoblotting was done on cell extracts at various time points following incubation with the drugs in order to study the cell signaling pathways and a Results: LCL161/OBX combination induced synergistic cytotoxicity and anti-proliferative effects on a broad range of human MM cell lines, including drug resistant cell lines like DOX40 and MM1R. Components of the bone marrow microenvironment including bone marrow stromal cells and tumor promoting cytokines (VEGF, IGF and IL6) were unable to protect MM cells from the effects of the drug combination. We saw a time dependent increase in apoptosis, with the combination inducing significantly more apoptosis than either of the single agents alone. Examining the mechanism of action of the drug combination showed clear inhibition of the IAP proteins, activation of caspases 9, 8, 3 and Bid by LCL161 and the combination and up regulation of the pro-apoptotic proteins Bim, Bid, Puma and Noxa and accumulation of LC3-II by OBX and the combination. Using chloroquine along with the OBX, we were able to demonstrate that OBX induced protective autophagy and the addition of LCL161 was able to overcome this protective effect induced after single agent OBX treatment. Since protective autophagy can be induced by the ER stress response, we then examined the expression levels of proteins involved in this pathway. We observed clear induction of ER stress mediated UPR pathway by both the drugs. However, LCL161 and OBX induced different branches of the UPR pathway. OBX activated the ATF6 and pErk/peif2α/ATF4 branches of the UPR, both of which have been implicated in cell survival during ER stress. ATF4 under irrecoverable ER stress can lead to increase in transcription of CHOP and cause apoptosis. We therefore examined levels of CHOP and observed no induction of CHOP post treatment with either of the drugs or the combination. LCL161, however differentially modulated the IRE1 branch of the UPR by down regulating Xbp-1 splicing, which is a pro survival activity of IREI and up regulating pJNK, which indicated a pro-apoptotic activity induced by IRE1 post irrecoverable ER stress This indicated that the ER stress induced apoptosis is triggered by LCL161, which might be important to overcome the ER induced protective effects induced by OBX. Conclusion: Taken together, our studies indicate that LCL161/OBX combination induces synergistic cell death through modulation of apoptosis, authophagy and the ER stress response. Disclosures No relevant conflicts of interest to declare.

Abstract Background: Patients with light chain amyloidosis (AL) often have delayed diagnosis and present with significant symptomatology; this may result in decreased quality of life (QOL). With improving treatment options providing longer survival, it is increasingly important to assess QOL. However there is paucity of data in the literature addressing QOL in AL patients. We prospectively employ a "Hematology Patient Reported Symptom Screen" (HPRSS) which consists of three questions about fatigue, pain and overall QOL. The aim of this study is to understand if HPRSS parameters predict various clinical outcomes. Methods: Eligibility for this retrospective study was as follows: 1) New diagnosis of AL between 2009-2014; 2) baseline HPRSS documented in the medical record; and 3) at least a year of follow-up, which included either death within or follow-up through 12 months after diagnosis. The HPRSS questions were rated on a 1-10 scale, with 10 being the worst for fatigue and pain, and 10 being the best for overall QOL. Scores were abstracted from visits at time of diagnosis, and at 12 months +/- 1 month post-diagnosis. We considered a 2-point difference in serial scores a "change" over time. Results: For the 302 patients in this study, the baseline median scores [interquartile range] for fatigue, pain, and QOL were 6 [3,7], 2 [0,5] and 5 [3,8], respectively. Median overall survival (OS) was 39.1 months, with 102 deaths in the first year. There were significant differences in baseline HPRSS between those who lived longer than one year and the early death patients in the domains of fatigue (5 [IQR 3, 7] vs. 7 [IQR 5, 8], p<0.0001) and QOL (6 [IQR 4, 8] vs. 5 [IQR 3, 7], p=0.006), but not in pain (2 [IQR 0, 5] vs. 2 [IQR 0, 5]). There were significant baseline differences in the early death group for alkaline phosphatase, bilirubin, creatinine, and Mayo stage. Patients who received ASCT had the best baseline fatigue 4 [2.5,6] and QOL 7 [5,8] scores and were significantly different from those who did not receive ASCT [fatigue p<0.0001) and QOL (p<0.0001)] On univariate analysis fatigue and QOL were prognostic for OS. On multivariate analysis Mayo 2012 staging, autologous stem cell transplant and baseline fatigue remained independently prognostic. When analyses were restricted to the 125 patients with HPRSS measurements at 12 months, we found that over time QOL scores improved significantly 6 [IQR 3.5, 8] to 7 [IQR 5, 8] (two sided Wilcoxon signed rank p=0.01), but fatigue (5 [IQR 2, 5] to 4.5 [IQR 3, 6]) and pain scores (2 [IQR 0 ,4] to 1.5 [IQR 0, 4]) did not. Patients with worse baseline parameters tended to have improvement in QOL by 12 months while those with the best baseline parameters tended to decline in QOL although not statistically significant. When we included the 102 patients who died within 12 months to the comparison, the early death patients had the worst baseline parameters and there were significant differences across all 4 groups for most characteristics (Table 1). There was no association between achieving hematologic or organ response with change in QOL. Conclusion: Asking patients with AL to rate their fatigue and QOL using a 10-point scale has predictive value. Patient reported fatigue at diagnosis is an independent prognostic factor for survival. Survival at one year was associated with significant improvement in QOL. Table 1. Baseline parameters between patients with early death and/or survive 12 months. Grouped by Patient Reported QOL at 12 months Relative to Baseline Dead by 12 months, n=102 Improved, n=44 Stable, n=55 Worsened, n=26 pa HPRSS scores [IQR] Baseline QOL Baseline fatigue Baseline pain 12 month QOL 12 month fatigue 12 month pain 5 [3,7] 7 [5,8] 2 [0,5] NA NA NA 4 [3-5] b,c,d6 [4-8] b,c2 [0-4] 7 [6-9] b,d4 [1.25-6] 1 [0-3] 7 [4-8] 4 [2-7] 2 [1-5] 7 [4-8] 5 [3-6] 2 [0-4] 8 [7-10] 2.5 [0-5.25] 2 [0-6.25] 5 [3-7] 5 [3-6] 2.5 [1-4] <0.0001 <0.0001 NS NS 0.001 NS dFLC, mg/dL 48 (2.89-726) 30 (1.1-494) 19 (36-455) 22 (0.2-2097) 0.008 Troponin, ng/mL 0.065 (<0.01-0.84) 0.02 (<0.01-1.6) 0.01 (<0.01-0.19) 0.01 (<0.01-0.14) <0.0001 NT-proBNP pg/mL 5222 (159-70,000) 1766 (26-16868) 1381 (24-19180) 496 (56-2973) <0.0001 Received Transplant (%) 4 (4) 13 (33) 36 (50) 13 (50) 0.0002 a Significant by Wilcoxon across all 4 categories; b Significant difference between Improved and Worsened; c Significant difference between Improved and Stable; d Significant difference between Worsened and Stable Disclosures Kumar: Millenium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Abbvie: Research Funding; Janssen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Novartis: Research Funding; Onyx: Consultancy, Research Funding. Thompson:Kite Pharma: Research Funding.

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

Abstract Background: Outcome studies for the unique cohort of young patients with multiple myeloma (MM) are sparse. In general, MM is a heterogenous disease with the genetic signature being one of the major determinants of prognosis. We have recently reported on improvement in overall survival (OS) of young patients with the use of novel agents, but the maximal survival gain has been achieved by integrating autologous stem cell transplant (SCT) to our current approach. Herein, we report on outcomes of patients with MM who were 50 years or younger at diagnosis and stratified by fluorescence in situ hybridization (FISH) results. Our study focuses on t(11;14) myeloma as its prognostic impact remains unclear with the use of novel agents upfront. Methods: Out of 1384 patients with MM, evaluated consecutively at Mayo Clinic, Rochester, MN between 1/1/2000 and 12/31/2011, 290 (21%) were 50 years or younger at diagnosis. Interphase FISH, performed within 100 days of diagnosis of MM, was utilized to stratify patients as high-risk [deletion 17p, t(14;16), t(14;20) or t(4;14)] or standard-risk [normal FISH, trisomies, t(11;14), t(6;14) or monosomy13/deletion 13q]. FISH results were available in 125 young patients that comprise the cohort of interest in the current study. OS from diagnosis was estimated by the Kaplan-Meier method. Results: Median age at diagnosis of MM was 47 years (range: 22 to 50 years) and 58% of the patients were male. At the time of data cut-off (7/31/2014), 45 (36%) patients had died with 90% of all known causes of deaths (n=39) being MM related. FISH abnormalities were noted in 114 (91%) patients. At diagnosis, 46%, 30% and 24% patients were categorized as International Staging System (ISS) stage I, II and III, respectively. The estimated median follow up was 60 months (95% CI: 54-67) and the 5-year OS rate was 69% [median 86 months (95% CI: 76-108)]. Standard (n=100; 80%) and high (n=25; 20%) risk patients had a median OS of 89 months (95% CI: 76-108) and 77.6 months (95% CI: 42-130), respectively (p=0.87). In order to further investigate the similar outcomes between these broad risk-groups with typically diverse disease course, we assessed the outcomes based on the common genetic abnormalities (Table 1) within each of the 2 categories. Presence of t(11;14) (n=37; 29%) was associated with a significantly shorter median OS (76 months) compared to patients with trisomic and normal FISH profile (n=46) (91 months, p=0.01; Figure 1). Patients with t(11;14) also had a significantly shorter median OS compared to those with other standard-risk FISH abnormalities (median OS 96 months, p=0.02). Presence of t(11;14) was not associated with higher plasma cell labeling index (PCLI, p=0.29) or worse ISS stage (p=0.99) compared to patients without t(11;14). OS survival of patients with t(11;14) was similar to those with high risk features (median 76.2 vs. 77.6 months, p=0.32). Of 24 (65%) patients with t(11;14) who underwent SCT, 79% had early SCT (within 12 months from diagnosis). Median OS was 79.4 months (95% CI: 36-108) vs. not reached (NR) (95% CI: 27-NR), respectively (p=0.79) in early versus late SCT. Twenty-one (57%) and 13 (35%) patients with t(11;14) received initial immunomodulatory drugs or bortezomib-based therapies, respectively. Those receiving frontline bortezomib had a higher median OS (76.2 months, 95% CI 76-79) compared to 64.8 months (95% CI 32-108) with other initial agents although it did not reach statistical significance (p=0.78). Conclusion: Presence of t(11;14) is associated with an inferior OS compared to patients with normal FISH, trisomies, or other standard risk abnormalities in young patients with MM. Given, the inherent biases associated with a retrospective study from a referral institution, our findings require external validation. However, our data suggest that our current therapeutic approaches in managing young patients with this unique genetic signature are inadequate. Table 1FISHn(%)Median OS in months (95% CI)t(11;14)37(29)76.2 (53.5-107.7)Trisomies35(28)91.3 (76.4-NR)13/del(13q)11(9)NR (32-NR)Normal11(9)95.5 (45.4-95.6)t(4;14)11(9)NR (40.1-NR)del(17p)/-1710(8)42 (19.2-129.6)t(14;16)4(3)77.6 (42.4-NR)Others6(5)NR (11.5-NR) Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Abstract Although multiple myeloma is clinically defined as the accumulation of clonal, malignant plasma cells in the bone marrow, the disease shows significant heterogeneity with regard to morphology, progression and therapeutic response. Our hypothesis is that this heterogeneity likely is due, in part, to germline genetic polymorphisms that contribute significantly to an individual’s disease course and response. In particular, individuals deficient in the repair of DNA damage are not only at high risk for developing cancer, but also could show DNA repair dependent responses associated with DNA damaging therapeutic agents. In this study we examined the association of functional genetic polymorphisms in the DNA repair genes, XRCC1 (SNP positions 280, 399) and ERCC2 (SNP positions 312, 751), with toxicities and clinical outcomes in the ECOG, 3 arm chemotherapeutic trial, E9486 [A-VBMCP, B-VBMCP+Cylophosphamide, C- VBMCP+interferon]. DNA from 359 patients was genotyped and examined for association with response, toxicities, blood counts, bone pathology, and survival parameters. Notably, in the interferon arm of the trial significant associations were observed in progression free survival and polymorphisms of XRCC399 (AA median survival 51 months versus AG/GG median survival of 33 months; p=,008), ERCC751 (AA/AC median survival 33 months versus CC median survival of 48 months; p=.05), and ERCC312 (AA median survival 49 months versus AG/GG median survival of 34 months; p=.02). Hazard ratios ranged form 1.7 to 2.05 for survival differences associated with DNA repair genes in this arm. Interestingly, T cell counts are known to be impacted by interferon; and DNA repair polymorphisms in this arm were also associated with CD8+ T cell counts. While this represents a single arm of one clinical trial, it is intriguing to consider the impact of genetic polymorphisms on DNA repair in light of chemotherapeutic agents that may affect cells of the immune system. Previous studies from the ECOG Myeloma Committee of the E9486 trial show highly significant associations of survival and immune status in myeloma patients. Our results suggest genetic polymorphisms in DNA repair genes may influence clinical outcome in certain therapeutic regimens. Genetic polymorphisms in these DNA repair genes are currently being completed in 800 patients of the SW9321 SWOG/ECOG intergroup trial and additional association studies will be included in the presentation.

Abstract Background:A goal of “post-genomic” cancer care is development of specific, affordable, reliable and rapid next-generation sequencing-based assays determining prognosis, therapeutic selection and minimal disease monitoring, replacing older technologies in the diagnostic and monitoring workup. In this regard, we designed and deployed a custom gene panel for identification of mutations, copy-number changes and clonal frequency in multiple myeloma (MM) samples. Methods: The MM Mutation Panel Version 2.0 (M3P 2.0)1 includes 1271 amplicons from 77 genes that are either mutated in MM (genes with a published mutation incidence ≥3%), represent critical pathophysiological pathways, are targetable with small molecule-based therapies and/or are associated with drug resistance (eg. XBP-1, CRBN, IZKF, IRF4). The amplicons are spread across 21 chromosomes, allowing the identification of copy-number changes in these regions. Results: We have sequenced 38 MM cases (150 will be presented) with paired tumor-germline DNA samples, using only 20ng of DNA for library preparation. Patients (Pts) included 29 untreated and 9 MM pts with multi drug refractory disease. Coverage depth averaged 964X. Hyperdiploid MM was successfully identified in 45% of cases, del(13q) in 34%, del(1p) in 18%, del(17p) in 8% and gain of 1q in 13%. Array CGH in representative cases confirmed concordance with semiconductor sequencing. Overall, 71 exonic missense and 3 nonsense mutations were detected, and 7 frameshift indels. In 89% of the pts a mutation in at least one M3P2.0 gene was identified (range 1-8). 92% of mutations were predicted damaging (Provean, Polyphene-2 or SIFT). Most commonly mutated were KRAS (37%), NRAS (21%), BRAF (13%), TP53, CDKN1B, DIS3 (each 11%), FAM46C, STAT3, and IRF4 (each 8%). The MEK-ERK pathway was mutated in 61% of cases and in 3 cases more than one gene in this pathway (NRAS, KRAS, BRAF) was simultaneously mutated. Six mutations in BRAF were identified in 5 untreated pts, 3 of them known to be activating and targetable (Val600E). Other commonly mutated pathways were the NFKB pathway in 24% of pts and the Cyclin D pathway, mutated in 16% of cases. Genes of the cereblon pathway (CRBN, IRF4, IKZF3), essential for the action of lenalidomide (len) were mutated in 5 Pts. One newly diagnosed and len refractory Pt harbored a subclonal CRBN mutation (Asn316Lys, allelic fraction [AF] 20%) as well as 4 clonal IRF4 mutations within the DNA binding domain of the gene (Lys89Asn (AF 78%), Lys77Glu, Ser48Arg and Cys49Ser (AF 80% each). Another IRF4 mutated (Lys123Arg, AF 90%) hemodialysis dependent Pt was responsive to dose adapted treatment of len and dexamethasone (dex). Mutations in the C2H2-type 3 region of IKZF3 in a len resistant (Gly191Arg, AF 48%) pt occured as well as in a len and dex responsive (Arg242Gly, AF 52%) Pt. Furthermore, we identified a truncating XBP1 mutation (p.Leu232*, 97% AF) in a Pt refractory to bortezomib. One patient harbored a mutation in the steroid receptor NR3C1 (Pro255Leu, 22% variant reads). Finally, integrated mutation and copy-number data identified biallelic deletions of CDKN2C and FAM46C in a multi drug refractory Pt. Mutation and/or copy-number losses in both alleles were found in DIS3 in 4 Pts, in CYLD, TP53 and TRAF3 in 2 Pts and in CARD11, CDKN2A, CDKN1B, RB1and STAT3 in one Pt each. Conclusion: In summary, we report the initial results from 38 MM Pts using a custom MM sequencing panel which employs small amounts of DNA requiring very few cells and providing deep coverage in clinically meaningful timeframes. Our findings frequently include prognostically significant information, actionable targets and mutations in genes related to drug resistance. Targeted mutation profiling will likely become part of the clinical workup in MM and our M3P2.0 mutation panel is a suitable tool to provide information needed to guide precision therapy and to set the basis for individually tailored treatment decisions. 1. Kortuem KM. et al. Development Of a 47 Gene Sequencing Panel For Common Mutations Present In Multiple Myeloma: Preliminary Results In 77 p53 Deleted Patients, ASH 2013. Disclosures Stewart: Celgene: Consultancy; Bristol Myers Squibb: Consultancy; Array BioPharma: Consultancy; Sanofi: Consultancy; Takeda Pharmaceuticals International Co.: Research Funding; Novartis: Consultancy. Bruins:OncoSpire: Salary support Other. Vasmatzis:OncoSpire: Salary Support Other. Kumar:Celgene: Consultancy, Research Funding; Millennium: The Takeda Oncology Co.: Consultancy, Research Funding; Onyx Pharmaceuticals: Consultancy, Research Funding; Sanofi-Aventis: Consultancy, Research Funding; Array BioPharma: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Skyline Diagnostics: Membership on an entity's Board of Directors or advisory committees. Fonseca:Medtronic, Otsuka, Celgene, Genzyme, BMS, Lilly, Onyx, Binding Site, Millennium, AMGEN: Consultancy, patent for the prognostication of MM based on genetic categorization of the disease. He also has sponsored research from Cylene and Onyx Other, Research Funding. Bergsagel:MundiPharma: Research Funding; OncoEthix: Research Funding; Constellation Pharmaceutical: Research Funding; Novartis: Research Funding.

Abstract Background: Both MM specific and patient specific parameters place patients at risk for death. Patient frailty has been delineated primarily by age and ECOG performance score (PS) and secondarily with creatinine, eGFR, and the International Staging System (ISS), which reflect both renal function and disease burden. In an attempt to improve upon these commonly used measures, a frailty score for elderly patients that combines functional status [Activity of Daily Living (ADL) and Instrumental Activity of Daily living scores], comorbidities [Charlson comorbidity index (CCI)] and age has been developed by the IMWG. Incorporation of these tools into a busy clinical practice is challenging due to time constraints. Therefore, the identification of frail patients with an easily applicable, rapid and objective tool remains a challenge and an unmet need. A reliable, non-invasively assessable, biochemical marker of frailty would be an ideal tool to identify patients at higher risk of death. It was our goal to determine the role of NT-proBNP, a well-established cardiovascular risk biomarker, as a marker of frailty in patients with MM and in predicting overall survival (OS). Methods: Patients were elegible for this retrospective study if they were seen at the Mayo Clinic, Rochester, MN within 30 days of their myeloma diagnosis during the interval between 1/1/2007 and 12/31/2011. As part of the Mayo Clinic registration, all patients complete forms containing their past medical history, symptoms, and ADLs. Data from that first visit was abstracted and used to calculate a CCI. We excluded all patients with a concomitant diagnosis of light-chain AL amyloidosis. NT-proBNP concentration was measured in frozen sera collected within 30 days of diagnosis. NT-proBNP assay was run on the E170 Modular analyzer (Roche Diagnostics, Penzberg, Germany). We evaluated the prognostic role of NT-proBNP and these indices on OS using the Kaplan-Meier method. Results: Among the 351 consecutive patients satisfying entry criteria, median age was 65 years (range 22-95), 33% were ≥70 years, and 56% were male. Twenty-eight percent were ISS stage III, 13% had a creatinine ≥2 mg/dL, 19% had PS ≥2, and 11% had ADL score ≥2, and 30% CCI ≥2. The median value of NT-proBNP was 109 ng/L (interquartile range: 30-375 ng/L). NT-proBNP concentrations differed in the three ISS stages (median: 122 ng/L stage I, 190 ng/L stage II and 1822 ng/L stage III, P<0.0001). Median OS was 5.6 years. The best cutoff of NT-proBNP predicting OS at one year was 301 ng/L (sensitivity: 57.88%, specificity: 74.29%; AUC=0.668) and distinguished two groups with different OS (median not reached vs. 35 months, P<0.0001). Variables predictive for OS are shown in the Table and included PS, age, CCI, ISS, NT-proBNP. On multivariate analysis, ISS and NT-proBNP were independent of each other as long as age, PS and/or CCI were excluded from the model. NT-proBNP withstood these clinical variables better than did ISS (data not shown). We built two different models (table). In model 1, NT-proBNP >301 ng/L was an independent predictor of survival while age ≥70 and PS ≥2 and CCI were not significant. However, if we considered ISS stage instead of NT-proBNP in the same model, ISS stage was not significant. Conclusions: In this unselected cohort of patients with newly diagnosed multiple myeloma, NT-proBNP was a useful predictor of survival independent of age and PS. The threshold of 301 ng/L is remarkably similar to the well-established cutoff for heart failure of 300 ng/L. NT-proBNP outperformed the CCI and the ISS as risk factors. NT-proBNP is a widely available biomarker that could be added to the panel of laboratory tests of newly diagnosed MM patients and serve as a simple means of determining patient frailty in a busy clinical practice. Table. Results of univariate and multivariate analysis of various prognostic factors (NS, not significant; NI, not included). Univariate Multivariate Multivariate RR (95% CI) P Model 1 P Model 2 P PS ≥2 3.4 (2.4-4.8) <0.0001 2.5 (1.7-3.6) <0.0001 2.8 (1.9-4.0) <0.0001 Age ≥70 2.7 (1.9-3.6) <0.0001 2.1 (1.5-2.9) <0.0001 1.9 (1.3-2.7) 0.0003 CCI >=2 1.9 (1.4-2.6) <0.0001 NS NS 1.5 (1.0-2.0) 0.03 ISS stage 1.1 (1.1-1.8) 0.0004 NI NI NS NS NT-proBNP >301 ng/L 2.3 (1.7-3.2) <0.0001 1.6 (1.1-2.2) 0.007 NI NI Disclosures Merlini: Janssen-Cilag: Honoraria; Prothena: Honoraria; Millennium-Takeda: Honoraria; Pfizer: Honoraria. Kumar:Janssen: Research Funding; Celgene: Research Funding; Sanofi: Research Funding; Millenium/Takeda: Research Funding; AbbVie: Research Funding; Onyx: Research Funding; Celgene, Millenium, Sanofi, Skyline, BMS, Onyx, Noxxon,: Other: Consultant, no compensation,; Skyline, Noxxon: Honoraria.