Kyle, Robert A.

Introduction: Risk stratification of patients with light chain (AL) amyloidosis at diagnosis is invaluable. Currently, the Mayo 2012 staging system is mainly used to risk-stratify patients. We evaluated the role of increased mean corpuscular volume (MCV) at diagnosis in predicting survival. Methods: We conducted a retrospective study of patients with newly diagnosed AL amyloidosis seen at Mayo Clinic, Rochester between January 2006 through December 2015. The diagnosis of AL was confirmed with biopsy and the determination of organ involvement was according to consensus criteria. Staging was done according to the Mayo 2012 staging system and patients with stage III/IV were considered to have advanced stage disease. Patient and disease factors were compared for categorical and continuous variables using the χ2 and the Wilcoxon signed rank tests, respectively. Overall survival (OS) was defined as the time from diagnosis to death of any cause. Survival analysis was done using the Kaplan-Meier method. Results: A total of 1064 patients were identified and were divided into two groups: those with an MCV ≥ 96 fl (Elevated MCV, n=180) and those with an MCV <96 fl (Low MCV, n=884). The median age at diagnosis for the whole cohort was 64, with an interquartile range (IQR) of 57-71. Overall, 222 (23%) had Mayo 2012 stage 1, 199 (21%) had stage 2, 239 (25%) had stage 3, and 290 (31%) had stage 4 disease. Patients with an elevated MCV were more likely to be more than 65 years old compared to patients with a low MCV (61% vs. 44%, p<0.0001). They were also likely to have an advanced Mayo 2012 stage (68% vs. 53%, P=0.0008). The median OS was significantly lower in patients with an elevated MCV compared to patients with a low MCV (median PFS 13 months vs. 41 month, respectively, P<0.0001)(Figure 1). On a univariable analysis, predictors of OS were advanced Mayo 2012 stage (RR 3.26, P<0.001) and MCV ≥ 96 (RR 1.6, P<0.0001). On the multivariable analysis, both variables remained predictors of OS [advanced Mayo 2012 stage (RR 3.19, P<0.001) and MCV ≥ 96 (RR 1.3, P=0.016)]. Conclusion: The median OS was shorter by 28 months in newly diagnosed AL amyloidosis patients with an MCV ≥ 96 compared to patients with an MCV<96. An elevated MCV was predictive of shorter survival, independent of the Mayo Stage. This variable is easily available, measured in all newly diagnosed patients, and provides valuable prognostic information for the treating physician. Disclosures Dispenzieri: Intellia: Consultancy; Takeda: Research Funding; Pfizer: Research Funding; Janssen: Consultancy; Alnylam: Research Funding; Celgene: Research Funding; Akcea: Consultancy. Lacy:Celgene: Research Funding. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Rigel: Consultancy; Karyopharm: Research Funding. Leung:Takeda: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; Omeros: Research Funding; Aduro: Membership on an entity's Board of Directors or advisory committees. Kapoor:Sanofi: Consultancy, Research Funding; Celgene: Honoraria; Cellectar: Consultancy; Janssen: Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding. Gertz:i3Health: Other: Development of educational programs and materials; Alnylam: Consultancy; Celgene: Consultancy; Appellis: Consultancy; Teva: Speakers Bureau; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Springer Publishing: Patents & Royalties; Amyloidosis Foundation: Research Funding; Amgen: Consultancy; Medscape: Consultancy, Speakers Bureau; Physicians Education Resource: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Research to Practice: Consultancy; Ionis/Akcea: Consultancy; Prothena Biosciences Inc: Consultancy; Janssen: Consultancy; International Waldenstrom Foundation: Research Funding; Proclara: Membership on an entity's Board of Directors or advisory committees; Johnson and Johnson: Speakers Bureau; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; DAVA oncology: Speakers Bureau. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

Introduction: Vitamin D deficiency is common, with 25-50% of the population having levels below the optimal range (<20 ng/mL). Aside from its role in maintaining serum calcium and skeletal homeostasis, vitamin D has been shown to play an important role in regulation of differentiation, proliferation, apoptosis, metastatic potential and angiogenesis in a variety of malignancies. Low serum 25(OH)D levels have been associated with a worse prognosis in several malignancies, including colorectal and breast cancer, chronic lymphocytic leukemia and non-Hodgkin's lymphoma. Almost no data have been reported on vitamin D levels in light chain (AL) amyloidosis. We therefore measured vitamin D levels among AL patients and correlated levels at presentation to explore if vitamin D deficiency has any effect or association in this disease. Methods: Stored serum samples from 90 patients with newly diagnosed AL amyloidosis were obtained for vitamin D studies, which included 25-hydroxyvitamin D [25(OH)D], 1,25-dihydroxyvitamin D [1,25(OH)2D] and vitamin D binding protein (DBP). All vitamin D measurements were made by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Total 25(OH)D and 1,25(OH)2D was assessed as the additive sum of the 25(OH)D2/25(OH)D3 and 1,25(OH)2D2/1,25(OH)2D3 components, respectively. Clinical data was extracted from the electronic medical records. All calculations were made using JMP software (SAS, Cary, NC). Results: All patients were seen between June 2004 and September 2013. Median age was 63 [IQR 57-70]. Heart, kidney, nerve, liver and gastrointestinal amyloidosis was seen in 80%, 60%, 19%, 17% and 13% of patients, respectively. The median dFLC and bone marrow plasma cells were 28 (IQR 12-84) mg/dL and 10% (IQR 5-20%), respectively. The median serum 25(OH)D level was 20 ng/mL (IQR 10-29; normal >20 ng/mL), while the median serum level of 1,25(OH)2D was 23 pg/mL (IQR 14-37; normal 16-64 pg/mL for men; 16-78 pg/mL for women). 25(OH)D levels <20 ng/mL were strongly associated with renal involvement (84% renal involvement vs 42% of renal involvement for levels ≥20 ng/dL, P<0.001; Table). No other association with organ involvement was seen. Among all patients, heavy proteinuria (>5 gr/24-h) was strongly associated with low 25(OH)D, (P<0.001, Table). A weaker association was seen between 25(OH)D levels and estimated glomerular filtration rate (eGFR) (P=0.06). Seventy-eight percent of patients with 1,25(OH)2D levels below 20 pg/mL had renal involvement versus 48% in those with levels above 20 pg/mL (P=0.01). While heavy proteinuria was associated with 1,25(OH)2D (P=0.008), the association was stronger for eGFR, as no patient with an eGFR <30 ml/min/1.73 m2 had a 1,25(OH)2D level above 20 pg/mL (P<0.001). An association between vitamin D levels and low serum albumin was also seen, mainly in relation to 25(OH)D (Table). The median level of serum DBP was 58 μg/mL (IQR 36 - 120 μg/mL), significantly lower than the normal range (168-367 μg/mL). Low levels of 25(OH)D or 1,25(OH)2D were not associated with lower DBP levels. Surprisingly, patients with renal involvement had higher levels of DBP versus those without renal involvement (median 70.9 vs 48 μg/mL; P=0.03), although median levels were below normal in both groups. FISH data was available in 47 of patients (52%). Patients with 25(OH)D levels <20 ng/dL were less likely to harbor t(11;14) versus patients with 25(OH)D levels above this threshold (26% vs 64%, respectively; P=0.0095). A similar, but less significant association was seen between 1,25(OH)2D levels at a 20 pg/mL threshold and t(11;14) (35% vs 59%, P=0.09). Other associations between vitamin D and FISH abnormalities were not seen. Conclusions: Hypovitaminosis D is common among AL amyloidosis patients with renal involvement. In the general cohort, heavy proteinuria, reduced eGFR and low serum albumin were all associated with low circulating vitamin D levels. Although the majority of AL patients had low levels of DBP, urinary loss of DBP does not explain the low levels of vitamin D. Hypovitaminosis D is associated with non-t(11;14) disease, a finding which warrants further exploration. Disclosures Dispenzieri: Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Lacy:Celgene: Research Funding. Dingli:Rigel: Consultancy; Karyopharm: Research Funding; Millenium: Consultancy; Janssen: Consultancy; alexion: Consultancy. Kapoor:Cellectar: Consultancy; Celgene: Honoraria; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Janssen: Research Funding; Glaxo Smith Kline: Research Funding. Leung:Omeros: Research Funding; Aduro: Membership on an entity's Board of Directors or advisory committees; Prothena: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding. Russell:Imanis: Equity Ownership. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Gertz:Ionis/Akcea: Consultancy; Alnylam: Consultancy; Janssen: Consultancy; Celgene: Consultancy; Annexon: Consultancy; Prothena Biosciences Inc: Consultancy; Spectrum: Consultancy, Research Funding.

Background: A variety of risk factors have been described in multiple myeloma and current risk assessment incorporates ISS stage with specific FISH results and serum LDH (R-ISS). However, this model does not include all the current abnormalities described as prognostic for survival in multiple myeloma. Importantly, the impact of many of these high-risk abnormalities are not uniform. We examined if we can better integrate FISH results into a risk assessment tool to better predict the outcomes of newly diagnosed MM. Patients and methods: We studied a cohort of 1316 patients with FISH done within 6 months of diagnosis of MM, in whom results for commonly observed abnormalities were available. We specifically examined the individual impact of common translocations involving chromosome 14, MYC rearrangements, chromosome 1q gain (single or multiple duplication) and del13q/monosomy 13. A risk assessment system was developed, weighting each abnormality according to their Risk Ratio and integrating ISS stage and serum LDH into the final model construction. Overall survival was calculated from diagnosis, with those alive at last follow up being censored. Results: We first examined the impact of each of the above FISH abnormalities: 1) high risk translocations [t(4;14), t(14;16), or t(14,20)], 2) trisomies, 3) t(11;14), 4) MYCrearrangements, 5) del13q/monosomy 13, and 6) 1q gain . Each of the abnormalities, except for t(11;14), was prognostic for survival (Table 1 with the risk ratios). For 1q gain, the median OS was NR, 105 mos and 79 mos respectively for no abnormality, duplication of 1 copy and duplication of multiple copies, (p<0.001). On multivariate analysis, t(11;14) and trisomies were no longer prognostic for overall survival (Table 1). The cumulative impact of abnormalities demonstrated worsening survival in the presence of increasing numbers of abnormalities (Figure 1). Including ISS stage 3 and LDH > ULN as additional variables for prognostication indicated both were individually prognostic for OS. In a multivariate analysis, including these two and FISH abnormalities, 1q gain and LDH were not independently prognostic. The final model consisted of HR translocations, MYCrearrangements, del17p/monosomy 17, del13q/monosomy 13, and ISS stage 3. Each of these variables was weighted using their risk ratio and a composite score was developed using 998 patients for whom all variables were available (range: 0-7.9; median 1.8). Three patient groups were characterized: group 1 (0; 32%), group 2 (1-4; 58%) and group 3 (>4; 10%) with a median OS of 53 mos, 106 mos, and NR, respectively, p <0.001 (Figure 2). Conclusion: Using the most relevant FISH and laboratory factors, in a large cohort of patients, we refined the current system to develop a risk stratification system that predicts survival in patients with newly diagnosed MM treated with contemporary treatment regimens. This needs validation in future studies. Disclosures Kumar: Janssen: Consultancy, Research Funding; Takeda: Research Funding; Celgene: Consultancy, Research Funding. Gertz:International Waldenstrom Foundation: Research Funding; Annexon: Consultancy; Medscape: Consultancy, Speakers Bureau; Amyloidosis Foundation: Research Funding; Abbvie: Other: personal fees for Data Safety Monitoring board; i3Health: Other: Development of educational programs and materials; Springer Publishing: Patents & Royalties; Physicians Education Resource: Consultancy; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; Ionis/Akcea: Consultancy; Alnylam: Consultancy; Prothena Biosciences Inc: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Appellis: Consultancy; Research to Practice: Consultancy; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Amgen: Consultancy. Dispenzieri:Akcea: Consultancy; Janssen: Consultancy; Intellia: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Lacy:Celgene: Research Funding. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Rigel: Consultancy; Karyopharm: Research Funding. Kapoor:Celgene: Honoraria; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Glaxo Smith Kline: Research Funding; Takeda: Honoraria, Research Funding; Amgen: Research Funding; Cellectar: Consultancy. Leung:Prothena: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Omeros: Research Funding; Aduro: Membership on an entity's Board of Directors or advisory committees. Bergsagel:Celgene: Consultancy; Ionis Pharmaceuticals: Consultancy; Janssen Pharmaceuticals: Consultancy.

Background: Combinations of alkylating agents with proteasome inhibitors have demonstrated efficacy in newly diagnosed and relapsed multiple myeloma (MM), with melphalan or cyclophosphamide combinations being some of the commonly used regimens for initial treatment of MM. Ixazomib (Ixa) is an oral proteasome inhibitor that is approved for use in combination with lenalidomide for patients with relapsed MM. We examined if Ixa can be effectively combined with cyclophosphamide (Ctx) in order to develop a less expensive, all oral regimen for patients with relapsed MM. Patients and Methods: Patients with relapsed MM, who were proteasome inhibitor naïve OR have received less than 6 cycles of therapy with bortezomib and had a better than PR with no progression at the time of discontinuation, were enrolled. The primary objective was to determine overall response rate (ORR). Treatment consisted of Ixa 4mg PO days 1, 8, 15; Ctx 300 mg/m2 PO days 1, 8, 15, 22 and dexamethasone (Dex) 40 mg PO weekly in a 28-day cycle. Overall, 37 patients were accrued; data on 33 eligible patients were available for analysis as of July 18, 2019. Results: The median age was 71 (48-89), 61% were male and the median duration from diagnosis was 46 months (mos). Median number of prior lines of therapy was 4 (range 1-5), 76%, 42% and 67% respectively had a prior IMiD, proteasome inhibitor or stem cell transplant, respectively. At data cutoff, 22 (67%) had progressed, 4 (12%) had died and the median follow up of those alive was 21.3 mos. Fourteen patients are still receiving treatment, with median of 8.5 cycles. Most common reason for treatment discontinuation was disease progression (10 pts; 53%). The ORR was 60% including 6% CR and 24% VGPR. The median event free survival was 11.3 mos (95%CI: 9.0 - 26.8). Overall, 401 cycles have been administered across the study, with dose modifications/ hold required for Ixa, Ctx, and Dex in 9 (27%), 14 (42%), and 22 (67%) patients respectively, the most common reason being hematologic toxicity. A grade 3 or higher adverse event at least possibly attributed to the study drugs was seen in 77% of patients, hematologic in 67% and non-hematologic in 30%. (Table 1) The most commonly observed hematologic toxicities included thrombocytopenia, neutropenia, lymphopenia and anemia; for non-hematologic was nausea, diarrhea, peripheral neuropathy toxicity and fatigue. Conclusions: The combination of Ixa, Ctx and Dex (ICd) offers a convenient, all oral regimen for treatment of relapsed disease not refractory to proteasome inhibitors. The regimen has good efficacy in this group f heavily pretreated patients, with an acceptable toxicity profile. Disclosures Lacy: Celgene: Research Funding. Gertz:Ionis: Honoraria; Spectrum: Honoraria, Research Funding; Janssen: Honoraria; Celgene: Honoraria; Prothena: Honoraria; Alnylam: Honoraria. Ailawadhi:Takeda: Consultancy; Janssen: Consultancy, Research Funding; Cellectar: Research Funding; Pharmacyclics: Research Funding; Amgen: Consultancy, Research Funding; Celgene: Consultancy. Bergsagel:Janssen Pharmaceuticals: Consultancy; Celgene: Consultancy; Ionis Pharmaceuticals: Consultancy. Fonseca:AbbVie, Amgen, Bayer, Celgene, Kite, Janssen, Juno, Merck, Pharmacylics, Sanofi, Takeda: Other: Consultant/Advisor; Prognosticatin of MM based on Genetic Categorization by FISH: Patents & Royalties; Adaptive Biotechnologies: Other: Scientific Advisory Board. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Rigel: Consultancy; Karyopharm: Research Funding. Kapoor:Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding; Sanofi: Consultancy, Research Funding; Celgene: Honoraria; Cellectar: Consultancy; Janssen: Research Funding. Chanan-Khan:AbbVie: Research Funding; Pharmacyclics: Research Funding; Xencor: Research Funding; Merck: Research Funding; Jansen: Research Funding; Mayo Clinic: Employment; Ascentage: Research Funding; Millennium: Research Funding. Larsen:Janssen Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees. Russell:Imanis: Equity Ownership. Stewart:Roche: Consultancy; Seattle Genetics: Consultancy; Takeda: Consultancy; Ionis: Consultancy; Janssen: Consultancy, Research Funding; Oncopeptides: Consultancy; Ono: Consultancy; Amgen: Consultancy, Research Funding; Bristol Myers-Squibb: Consultancy; Celgene: Consultancy, Research Funding. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

Introduction: Waldenström macroglobulinemia (WM) is characterized by circulating monoclonal IgM and bone marrow infiltration with lymphoplasmacytic lymphoma (LPL) cells. Presently, there is limited data to guide prognosis or treatment options of WM based on the proportion of lymphocytes or plasma cells in the LPL population on the pathology. In this study, we aim to look at differing clinical features and outcomes of patients with WM based on the plasma cell (PC) percentage in the diagnostic bone marrow biopsy. Methods Patients with WM seen at Mayo Clinic, Rochester, MN between January 2001 and December 2017, with a bone marrow biopsy and a corresponding serum free light chain (FLC) examination at diagnosis of WM were included. The percentage of lymphocytes and PCs in the marrow biopsy was determined based on morphology ± immunohistochemistry. On immunohistochemistry, CD138 and/or MUM-1 positivity was used to quantify PCs, whereas CD20 and/or PAX5 were used to quantify lymphocytes. Patients with ≥10% PC component in the lymphoplasmacytic (LPL) cells on bone marrow biopsy were considered to have WM with excess plasma cells (WMEPC), while those with &lt;10% PCs were considered to have lymphocytic WM (LWM). Continuous variables were compared using Wilcoxon test and categorical variables were compared using Chi square test or Fisher's exact test. Time-to-next therapy (TTNT) was defined as the period from initiation of first line therapy to start of second line therapy or death due to any cause before second line therapy. Time-to-event analyses were conducted using Kaplan Meier method. Results: Of 228 evaluable patients, 147 (64%) had ≥ 10% PCs in the initial marrow biopsy. The median follow-up was 3.4 years (95% CI: 2.3-4.3 years) for LWM and 4.3 years (95% CI: 3.4-4.8 years) for WMEPC (p=0.33). The baseline characteristics of WMEPC versus LWM are depicted in Table 1. Patients with WMEPC had lower bone marrow involvement by LPL (30%) compared to LWM (60%; p&lt;0.001) at diagnosis, but the rate of symptomatic hyperviscosity was higher in WMEPC during the disease course (Table 1). The TTNT was shorter for WMEPC [2.6 years (95% CI: 1.8-4.5 years)] compared to LWM [4.5 years (95% CI 3.2-8.2)], although it did not reach statistical significance (p=0.09, Figure 1). There was a trend towards shorter OS for WMEPC [Not reached (95% CI 7.2- NR)] compared to LWM [10.7 years (95% CI 7.3 -12.1 years); p=0.28], Figure 2. Of the 228 patients, 79% (n=182) had data available for systemic therapy. The rate of PR or better with frontline therapy was higher in rates in LWM compared to WMEPC (61 % vs 42% p=0.02, Table 1). Among WMEPC cohort, patients receiving either a proteasome inhibitor (PI)-based or an immunomodulatory (IMiD)-based combination as frontline therapy (n=16) had higher rates of partial response or better (68%) compared to non-PI/non-IMiD based therapy (n=114), p=0.04. Conclusion: WM with excess plasma cells at diagnosis is associated with a trend towards shorter TTNT and OS compared to WM with &lt;10% plasma cells in the lymphoplasmacytic population at diagnosis. Our preliminary data shows higher rates of partial response or better with the use of PI/IMiD based therapy, but the small cohort size limits the strength of this finding which needs to be validated externally. Disclosures Ansell: Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Affimed: Research Funding. Gertz:Spectrum: Honoraria, Research Funding; Janssen: Honoraria; Celgene: Honoraria; Prothena: Honoraria; Alnylam: Honoraria; Ionis: Honoraria. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Rigel: Consultancy; Karyopharm: Research Funding. Nowakowski:Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding; Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding. Dispenzieri:Alnylam: Research Funding; Celgene: Research Funding; Takeda: Research Funding; Pfizer: Research Funding; Janssen: Consultancy; Intellia: Consultancy; Akcea: Consultancy. Lacy:Celgene: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Kapoor:Janssen: Research Funding; Cellectar: Consultancy; Glaxo Smith Kline: Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Sanofi: Consultancy, Research Funding; Celgene: Honoraria.

Introduction Waldenstrom macroglobulinemia (WM) is a rare, incurable, indolent non-Hodgkin lymphoma that is preceded by an IgM monoclonal gammopathy of undetermined significance (IgM MGUS). In recent years, better understanding of the pathobiology of WM and IgM MGUS has strengthened the hypothesis that they may represent different stages of the same disease. Studying the relationship between these two conditions is the essential first step to understanding the mechanisms driving the malignant transformation from IgM MGUS to WM. Recently long non-coding RNAs (lncRNAs) have garnered significant recognition for their roles in the regulation of gene expression and cellular function. lncRNA can regulate gene expression of neighboring protein-coding genes through multiple mechanisms such as by recruiting chromatin modifiers and increasing accessibility of genes to transcription proteins, or by directly binding to enhancers or promoters. Here we present the first analysis of the lncRNA expression profile in patients with WM compared to IgM MGUS. Methods Twenty-one patients with untreated WM (n=14) and IgM MGUS (n=7) seen at Mayo Clinic were included in this analysis. Malignant cells were isolated from bone marrow samples using CD19 and CD38 positive selection. Total RNA was extracted and sequencing was performed using the Illumina HiSeq4000 NGS platform. Differentially expressed lncRNAs in WM compared to IgM MGUS were defined as log2 fold change (FC) > 1.0 (upregulated) or < -1.0 (downregulated) and a false discovery rate (FDR) < 0.05. The nearest gene to each lncRNA was also identified and their gene expression was detected. Using the Ingenuity Pathway Analysis software and taking into account the transcriptional expression and known function of these genes, a correlation between cell function and disease analysis was performed. Results A total of 119 lncRNAs were differently expressed between WM and IgM MGUS (17 transcripts were upregulated in WM, while 102 were downregulated in WM). Sixteen unique genes were identified as the nearest gene to 17 upregulated lncRNAs, while 18 genes were identified as the nearest genes to the top 18 downregulated lncRNAs in WM compared to IgM MGUS. Several of the upregulated lncRNA in WM were in proximity to known oncogenes. The well-known oncogenic lncRNA PVT1 was found to be upregulated in WM compared to IgM MGUS (log2 FC 1.35, FRD 0.04). PVT1 is overexpressed in several malignancies and associated with inhibition of apoptosis and increased cell proliferation. PVT1 is in close proximity to MYC and co-expression of PVT1-MYC has been described in multiple cancers. PVT1 also potentiate MYC amplification by increasing MYC protein stability, therefore promoting malignant cell growth. The lncRNA TCB1D27, also upregulated in WM compared to IgM MGUS, is located in close proximity to the oncogene TNFRSF13B (TACI), which was found to be overexpressed in WM patients (log2 FC 1.61, FDR <0.001). TACI is a receptor for BLyS/BAFF, which modulates the development of normal B-cells and plays a role in various B-cell malignancies. In fact, BLyS/BAFF level is known to be increased in WM and to promote survival and proliferation of WM B cells. The upregulated lncRNA RP11-25K21.1 in WM is located in close proximity to the oncogene FCGR2B (CD32B), which was also upregulated in WM compared to IgM MGUS (log2 FC 1.59, FDR 0.001). Overexpression of CD32B was previously shown to be associated with inferior outcomes in DLBCL and FL patients, presumably secondary to an increased internalization and clearance of rituximab due to increased CD32B expression on malignant cells. Several other upregulated lncRNAs in WM compared to IgM MGUS are also in proximity of other oncogenes such as PCED1B, POLD3, CLLU1, and SMAD7. Finally, we considered the expression of the nearest genes and their reported cell function and association with diseases. Several genes that are known to have a role in the cell proliferation and/or neoplasm development were noted to be upregulated in WM (figure 1). Conclusion We present the first report of lncRNAs expression in WM and IgM MGUS in addition to a concurrent analysis of the gene expression of the nearest protein-coding genes. Several known oncogenes are in proximity of overexpressed lncRNAs in WM compared to IgM MGUS that could indicate potential implications in the pathobiology of these diseases and the mechanism driving the malignant transformation to WM. Disclosures Paludo: Celgene: Research Funding; Celgene: Research Funding; Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding. Dasari:The Binding Site: Patents & Royalties: US Patent Rights on Mass Spectroscopy Licensing agreement with The Binding Site, Research Funding. Kapoor:Celgene: Honoraria; Cellectar: Consultancy; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding. Ailawadhi:Amgen: Consultancy, Research Funding; Pharmacyclics: Research Funding; Takeda: Consultancy; Janssen: Consultancy, Research Funding; Cellectar: Research Funding; Celgene: Consultancy. Gertz:Amyloidosis Foundation: Research Funding; i3Health: Other: Development of educational programs and materials; Medscape: Consultancy, Speakers Bureau; Ionis/Akcea: Consultancy; Celgene: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Teva: Speakers Bureau; Alnylam: Consultancy; Prothena Biosciences Inc: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Physicians Education Resource: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Research to Practice: Consultancy; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; Springer Publishing: Patents & Royalties; International Waldenstrom Foundation: Research Funding. Novak:Celgene Coorperation: Research Funding. Ansell:Affimed: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding.

INTRODUCTION: Primary plasma cell leukemia (pPCL) is the most aggressive form of multiple myeloma (MM). Recently, pPCL has been defined by as few as >5% circulating plasma cells (cPCs) detected morphologically on a peripheral blood smear. However, this technique may not be sufficiently sensitive and is dependent on inter-observer bias to properly identify and quantify cPCs. Multiparametric flow cytometry (MFC) provides a readily available and highly sensitive method to identify and quantify cPCs. However, an optimal quantitative cutoff for cPCs by MFC to define the presence of pPCL has not been established to date. Thus, this is the first study to date that determines an optimal cutoff of cPCs/ microliter that could identity patients with pPCL at diagnosis. METHODS: We retrospectively evaluated all newly diagnosed MM patients seen at the Mayo Clinic, Rochester from January 2007 to December 2017 who had their peripheral blood samples evaluated morphologically by peripheral blood smear and immunophenotypically by MFC prior to beginning therapy. Patients with a peripheral blood smear detecting >5% cPCs were classified as having pPCL. Six-color MFC was performed on peripheral blood mononuclear cells by isolated by Ficoll gradient, and stained with antibodies to CD45, CD19, CD38, CD138 and cytoplasmic Kappa and Lambda immunoglobulin light chains. The data was collected using Becton Dickinson FacsCanto II instruments collecting 150,000 events and analyzed using the BDFacs DIVA Software. The gating strategy employed first used the expression of CD38, CD138, and cytoplasmic immunoglobulin light chains to identify all plasma cells in the specimen. The cPCs were then discriminated from polyclonal/normal plasma cells based on differential CD19 and CD45 expression. The cPCs detected were reported as the number of clonal events/150,000 collected total events and converted to the absolute number of cPCs/microliter using their absolute lymphocyte count and monocyte count determined at the time of the blood draw for cPC MFC assessment. A receiver operator curve (ROC) was performed to determine the absolute cPCs/microliter by MFC that best identified those patients with >5% cPC on their peripheral blood smear. Survival analysis was performed by the Kaplan-Meier method and differences assessed using the log rank test. RESULTS: A total of 591 patients were included in this analysis of which 59% were male and the median age was 66 years (range: 27 - 95) with 22% being 75 years of age or older. From this cohort, 133 (24%) patients had high risk FISH cytogenetics, 172 (30%) were classified as ISS 3 at diagnosis, 83 (15%) had an elevated LDH level and 61 (17%) had a plasma cell labeling index (PCLI) of 2% or greater. There were 65 (11%) patients with any amount of cPCs detectable by peripheral blood smear of which only 22 (4% of the total population) met criteria for pPCL with >5% cPCs. With MFC, 403 (68%) patients had detectable cPCs. The median number of cPCs per microliter was 0.81 (0 - 10,455) with 273 (46%) having >1 cPC/microliter. A ROC analysis determined that the presence of >50 cPCs/microliter by MFC was the optimal cutoff to identify patients with >5% cPCs by blood smear with approximately a specificity of 94% and a sensitivity of 86%. The presence of >50 cPCs/microliter by MFC was associated with higher presence of high risk FISH cytogenetics, ISS 3 classification, elevated LDH and PCLI > 2%. The median time to next treatment (TTNT) for patients with and without >5% cPCs by peripheral blood smear was 18 months vs. 30 months (P < 0.001). The median TTNT for patients with and without >50 cPCs/microliter by MFC was 19 months vs. 30 months (P < 0.01). The median overall survival (OS) for patients with and without >5% cPCs by peripheral blood smear was 25 months vs. 71 months (P < 0.001; Fig 1A). The median OS for patients with and without >50 cPCs/microliter by MFC was 38 months vs. 71 months (P < 0.01; Fig 1B). CONCLUSION: This is the largest study that attempts to identify an optimal cutoff of cPCs/microliter by MFC for diagnosing pPCL patients. The presence of >50 cPCs/microliter is an optimal cutoff by MFC that best predicts for the presence of >5% cPCs by peripheral blood smear. However, there remains discordance in the OS outcomes between the two cutoffs by different methodologies for pPCL. This could signify the presence of biological processes associated with the presence of >5% cPCs when detected by peripheral blood smear that are not captured by MFC. Disclosures Dispenzieri: Pfizer: Research Funding; Janssen: Consultancy; Intellia: Consultancy; Akcea: Consultancy; Alnylam: Research Funding; Takeda: Research Funding; Celgene: Research Funding. Dingli:Karyopharm: Research Funding; Rigel: Consultancy; Millenium: Consultancy; Janssen: Consultancy; alexion: Consultancy. Lacy:Celgene: Research Funding. Kapoor:Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding; Sanofi: Consultancy, Research Funding; Cellectar: Consultancy; Janssen: Research Funding; Celgene: Honoraria. Leung:Aduro: Membership on an entity's Board of Directors or advisory committees; Omeros: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding. Russell:Imanis: Equity Ownership. Gertz:DAVA oncology: Speakers Bureau; Ionis/Akcea: Consultancy; Alnylam: Consultancy; Prothena Biosciences Inc: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Medscape: Consultancy, Speakers Bureau; Physicians Education Resource: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Research to Practice: Consultancy; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; i3Health: Other: Development of educational programs and materials; Springer Publishing: Patents & Royalties; Amyloidosis Foundation: Research Funding; International Waldenstrom Foundation: Research Funding. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

Background: The treatment of Multiple Myeloma (MM) has evolved significantly in the past decade with the introduction of novel agents and drug combinations, thus enhancing treatment efficacy and allowing more patients to achieve complete response (CR). This has created a need to identify surrogates for depth of treatment response. Serum free light chain (sFLC) ratio normalization has been shown to be prognostic for progression free survival as well as overall survival in patients achieving a complete response to therapy. Consequently, it has been incorporated as a defining feature for stringent CR, along with lack of clonal plasma cells by immunohistochemistry (IHC) or low sensitivity flow cytometry. The routine use of multiparametric flow cytometry with higher sensitivity to detect residual disease than IHC or the older 4-color flow cytometry, has raised the question as to whether sFLC ratio is still a valid indicator of response depth. Moreover, in nearly half of the patients with an abnormal sFLC ratio after treatment, the abnormality is secondary to suppression of one or both serum light chains. Therefore, we designed a retrospective study to address these issues. Patients and Methods: This is a retrospective study using the Multiple Myeloma Database at Mayo Clinic, Rochester. We included patients who, after any line of therapy, had negative serum and urine immunofixation and absence of clonal bone marrow plasma cells by flow cytometry (PC-PRO), which has a sensitivity of >10-4. Simultaneous sFLC data was also extracted. Patients were grouped into three categories based on their sFLC ratios: 1) normal ratio (normal), 2) abnormal ratio due to suppression of the uninvolved light chain (LC), involved LC, or both (Abn-suppressed) and 3) abnormal ratio due to elevation of the involved LC (Abn-inv elevated). The primary endpoint was the median time to next treatment (TTNT), defined as the time from sample collection to the time of initiation of the subsequent therapy or time of last follow up if a subsequent line of treatment was not initiated. Results: The cohort consisted of 510 patients. 285 (56%) were males and 225 (44%) females. Median age was 61 years (IQR: 55-67). Median Follow-up was 41 months. The last treatments administered prior to data collection included stem cell transplant (SCT) (with or without maintenance) in 290 (57%) patients, and non-SCT regimens in the others. The sFLC ratio was normal in 337 (66%) and abnormal in 173 (34%) patients. Among the patients with abnormal sFLC ratios, 81 had elevated involved LC, 25 had suppression of the involved LC, 45 had suppression of the uninvolved LC and 22 had suppression of both LCs. We first examined the TTNT for the three groups and found that the TTNT was identical for those with a normal ratio and those with an abnormal ratio due to suppression of one or both light chains (Figure 1). So, we combined these two groups (Normal-Abn suppressed) and compared their outcomes to the patients with abnormal sFLC ratio due to elevated involved LC. The Abn-inv elevated group had a shorter TTNT as shown in Figure 2 (log-rank 0.06, Wilcoxon <0.01). The Abn-inv elevated group also had decreased overall survival compared to the other group (log-rank: 0.05, Wilcoxon: 0.01) (Figure 3). Conclusion: This study provides 2 important observations. First, patients with an abnormal ratio due to suppression of one or both LCs have outcomes similar to those with a normal ratio, suggesting a need to clarify the current definition of stringent CR. Second, the study suggests an important prognostic value for an abnormal sFLC ratio due to elevated involved LC, suggesting this as an important surrogate for depth of response. Disclosures Kapoor: Janssen: Research Funding; Takeda: Honoraria, Research Funding; Cellectar: Consultancy; Celgene: Honoraria; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Glaxo Smith Kline: Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Gertz:Ionis: Honoraria; Alnylam: Honoraria; Prothena: Honoraria; Celgene: Honoraria; Janssen: Honoraria; Spectrum: Honoraria, Research Funding. Lacy:Celgene: Research Funding. Dingli:Karyopharm: Research Funding; Rigel: Consultancy; Millenium: Consultancy; Janssen: Consultancy; alexion: Consultancy. Leung:Takeda: Research Funding; Aduro: Membership on an entity's Board of Directors or advisory committees; Prothena: Membership on an entity's Board of Directors or advisory committees; Omeros: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

Introduction: Several patient and disease biology characteristics that impact overall survival (OS) outcomes of patients with newly diagnosed multiple myeloma (NDMM) have been well described. However, several prior population-based registry studies in the US such as SEER and NCDB databases have demonstrated the negative prognostic impact of socio-economic (SE) factors such as low median household income based on US national census bureau data for zip code of residence as well as absence of marital support on the OS of NDMM patients. Whether such SE factors are independent of established host and disease biology related factors remains unknown due to the absence of detailed patient-level data in population-based cancer registries. Thus, we evaluated whether such SE factors independently affected the OS of NDMM patients in our institution when accounting for patient and disease biology related factors. Methods: We analyzed a retrospective cohort of consecutive NDMM patients seen at the Mayo Clinic from January 2005 to December 2015. Median household income for each patient's area of residence was estimated by matching their home zip code at diagnosis with data available through the US National Census Bureau. Median household income < $63,000 for a zip code were used to classify patients as having low income based on the National Cancer Database classification of the bottom three quartiles. Absence of marital support was considered in patients divorced, single or widowed at the time of diagnosis. Survival estimates were calculated using the Kaplan-Meier method. Patient and disease biology related factors taken into consideration included age, FISH cytogenetics, ISS stage and LDH levels. Survival estimates were compared between groups using the log-rank test. Multivariable adjusted proportional hazards regression models were fit for the association between known prognostic factors and OS. Results: A total of 2,621 MM patients were analyzed from the Mayo Clinic cohort of which 60% were male and the median age was 64 (22 - 96) years with 14% being 75 years of age or older. In this cohort, 541 (33%) patients had ISS 3 disease and 370 (22%) had high risk cytogenetics by FISH. The median OS based on estimated average household income was 65 months for the group of patients with low household income (N = 32%) and 80 months for the remainder (P = 0.001) (Fig 1A). The median OS based on marital support was 59 months for those without marital support at diagnosis (N = 21%) versus 76 months for remainder (P = 0.003) (Fig 1B). However, in a multivariable analysis that included the aforementioned SE factors and patient and disease biology characteristics , only age of 75 years or older (p < 0.001), the presence of high-risk FISH cytogenetics (p < 0.001), presence of ISS 3 disease (p < 0.001) and elevated LDH (p = 0.005) retained independent statistical significance in predicting for worse OS. Lower household income (p = 0.264) and absence of marital support (p = 0.054) were not independent predictors of worse OS. Conclusions: With the caveat of patient selection bias in a tertiary academic center, SE factors such as estimated average household income and marital support at diagnosis do not appear to impact OS of NDMM patients when considered in the context of traditional host and disease biology risk factors. These findings are in contrast to those suggested by population based registry studies; nevertheless, similar patient-level assessments should be considered in patient cohorts from non-tertiary medical centers as these results may likely be different. Disclosures Dispenzieri: Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Rigel: Consultancy; Karyopharm: Research Funding. Lacy:Celgene: Research Funding. Kapoor:Amgen: Research Funding; Glaxo Smith Kline: Research Funding; Sanofi: Consultancy, Research Funding; Celgene: Honoraria; Janssen: Research Funding; Cellectar: Consultancy; Takeda: Honoraria, Research Funding. Leung:Prothena: Membership on an entity's Board of Directors or advisory committees; Aduro: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Omeros: Research Funding. Russell:Imanis: Equity Ownership. Gertz:Medscape: Consultancy, Speakers Bureau; Research to Practice: Consultancy; Springer Publishing: Patents & Royalties; Ionis/Akcea: Consultancy; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Alnylam: Consultancy; Prothena Biosciences Inc: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Physicians Education Resource: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Proclara: Membership on an entity's Board of Directors or advisory committees; i3Health: Other: Development of educational programs and materials; Amyloidosis Foundation: Research Funding; International Waldenstrom Foundation: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

Background: Lenalidomide maintenance therapy post-autologous stem cell transplantation (ASCT) is associated with improved progression-free survival (PFS) and possibly overall survival in multiple myeloma (MM). However, almost all patients do relapse as a result of residual multiple myeloma cells that remain after the high-dose chemotherapy. In the myeloma setting it has been found that the hedgehog (Hh) pathway is essential for maintaining a subset of tumor causing stem cells. LDE 225 (Sonidegib) is a potent selective oral bioavailable antagonist of Smoothened (SMO), a component of the Hh signaling pathway. In in vitro experiments, LDE225 treatment of myeloma cell lines resulted in a modest inhibition of cell proliferation at increasing doses. When LDE225 was combined with lenalidomide, a more than additive effect was observed in terms of cell proliferation, an effect that was more pronounced in the context of myeloma cell lines growing in co-culture with marrow derived stromal cells. These findings form the basis of evaluation of LDE 225 as a strategy to enhance the activity of lenalidomide in the post-transplant maintenance setting. The minimal residual state post SCT provides the most optimal situation for evaluation of a drug that is likely to work by inhibiting the tumor cells that escaped high dose therapy. Methods: Multiple myeloma patients without evidence of progression, who were 60 - 120 days after a single autologous stem cell transplant (SCT), performed within 1 year of diagnosis were eligible for the study. Maintenance therapy was started approximately 3 months after SCT. Treatment consisted of lenalidomide 10 mg days 1-21 and LDE225 400 mg days 1-28 in 28-day cycles for a total of 18 cycles. The goal of the study was to assess toxicity of this combination, complete response rate (CR) progression free survival (PFS) at 1 and 2 year and overall survival (OS). CR and PFS were estimated using an exact binomial distribution and Kaplan Meier curves respectively. Results: A total of 28 patients were accrued from Jan 2014 to Aug 2016, 1 patient canceled prior to treatment and 1 patient was deemed ineligible resulting in 26 evaluable pts for CR and PFS. The median age of all pts (n=26) was 60 years (range 43-69) and 50% were males. Seventy-three percent of patients reported one treatment regimen prior to SCT, while 27% reported 2 or more prior regimens. The other characteristics of the patient are summarized in Table 1. Twenty seven pts received at least one cycle of treatment and are evaluable for toxicities (AE). Patients were treated for a median of 12.5 (range 1-18) cycles. While 10 pts (38.5%) completed protocol treatment (18 cycles), the remaining 16 pts went off treatment due to AEs (6, 23%), disease progression (3, 11.5%), refusal of further treatment (3, 11.5%) and other reasons (4, 15.4%). A grade 3 or higher AE at least possibly attributed to either drug was seen in 63%. Grade 3+ hematologic toxicities were noted in 30%, with 7% neutropenia and 4% thrombocytopenia. Notable grade 2+ non-hematologic toxicities with more than 5% incidence were dysgeusia 22%, alopecia 11%, and anorexia 7%. Grade 3+ non-hematologic toxicities were fatigue, myalgia and arthralgia each at 7%. The CR rate in evaluable patients was 46% (5 CRs and 7 sCRs) with a 95% CI of 27% - 66%. CR rate improved from 31% to 46%. VGPR or better improved from 42% to 85%. The 24-month PFS (time from SCT to progression or death due to any cause) was 73% (95% CI: 57.9 - 92.3%) with a median time to censoring of 38 months. Conclusion: Lenalidomide in combination with LDE225 as posttransplant maintenance therapy was associated with some toxicity but manageable. The combination improved the depth of response after autologous stem cell transplant. Long-term follow-up is needed to determine overall survival. Disclosures Lacy: Celgene: Research Funding. Dispenzieri:Celgene: Research Funding; Takeda: Research Funding; Pfizer: Research Funding; Janssen: Consultancy; Intellia: Consultancy; Akcea: Consultancy; Alnylam: Research Funding. Gertz:Ionis: Honoraria; Alnylam: Honoraria; Prothena: Honoraria; Celgene: Honoraria; Spectrum: Honoraria, Research Funding; Janssen: Honoraria. Kapoor:Glaxo Smith Kline: Research Funding; Amgen: Research Funding; Janssen: Research Funding; Cellectar: Consultancy; Takeda: Honoraria, Research Funding; Celgene: Honoraria; Sanofi: Consultancy, Research Funding. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Rigel: Consultancy; Karyopharm: Research Funding. Russell:Imanis: Equity Ownership. Kumar:Janssen: Consultancy, Research Funding; Takeda: Research Funding; Celgene: Consultancy, Research Funding. OffLabel Disclosure: Sonidegib (LDE 225) is a selective oral bioavailable antagonist of Smoothened (SMO), a component of the hedgehog signaling pathway.