Citations

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 <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<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 <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.

Background: Two-year follow-up from ZUMA-1 trial for axicabtagene ciloleucel (axi-cel) CD19 chimeric antigen receptor T-cell (CART) in aggressive non-Hodgkin lymphoma (NHL) demonstrated that patients (pts) achieving complete remission (CR) as their best response have the longest progression free survival (PFS), while PFS remained poor for others. Majority of the best response are achieved by month 3 post-infusion. Moreover, a subset of pts who do not achieve CR by month 1 may still achieve CR while others will progress within months. Having a clinically available test to predict for durable response can assist clinicians in selecting pts who can be observed for continued response vs. those who may need intervention earlier. Peak CAR-T expansion has been correlated with best clinical response to axi-cel. However there is no clinically available test to quantify CART cells post treatment. Given the prolonged lymphotoxic effect of the lymphodepletion (LD) chemotherapy administered before CART infusion, we hypothesize that the peak expansion of absolute lymphocyte count (ALC, ALCpeak) after infusion likely corresponds to CART expansion. We examined for correlation between ALCpeak and clinical response at month 3 post-infusion for pts who received axi-cel. Methods: Data was collected from pts who received axi-cel between June 2016 and March 2019 at Mayo Clinic Rochester (NCT02348216, NCT03153462, and standard of care). All infused pts were included in the intention to treat analysis for response and event-free survival (EFS). Lugano 2014 criteria were used for clinical response. EFS was defined as the date of infusion until progression or death due to any cause and evaluated using Kaplan Meier curves with log-rank test. Comparison between subgroups was investigated using Fisher's exact test and Wilcoxon test for categorical and continuous variables, respectively. Statistical analysis performed using JMP Pro 14.1. Results: Of the thirty-six NHL pts treated with axi-cel, the median age was 56 yrs (range 26-65); 78% (28) were male; 44% (16) had DLBCL; the median number of prior therapies was 3 (2-6), 47% (17) had stem cell transplant. Nineteen (53%) pts received bridging therapy after leukapheresis. All pts received fludarabine and cyclophosphamide for LD chemotherapy and achieved ALC nadir by the day of CART infusion (median 0.03 x 10^9/L, range 0.01-0.11). As CART expansion were found to peak within the first two weeks in ZUMA-1 trial, we examined ALC trend over 15 days post infusion and found that ALCpeak generally happened within the same timeframe (median ALCpeak day: 9, range 6-15). At 3 months post infusion, 33.3% (12/36) of pts achieved CR, 8.3% (3/36) pts were in partial remission (PR). No correlation was found between CR response and clinical characteristics: age >60 years, stage III/IV, B symptoms, elevated LDH, IPI score 3-4, number of previous treatments, use of bridging therapy, peak CRP and ferritin. However, the ALCpeak was significantly different between CR and non-CR pts (median, range: 1.09, 0.35-2.55; 0.67, 0.15-1.03; p=0.04). Using receiver operator curve (ROC)-derived area under the curve (AUC) estimates, ALCpeak 1.08 x 10^9/L was identified as the best threshold to discriminate patients at different likelihood to achieve CR at month 3. Pts achieving ALCpeak ≥ 1.08 showed a strong increased likelihood of achieving CR at month 3 (OR 2.8; 95% CI, 1.12-6.99; P=0.02). There was no statistical difference between the ALCpeak high and low groups in terms of use of bridging therapy, occurrence of any grade or higher grade cytokine release syndrome or neurotoxicity, or the use of tocilizumab or steroid. Interestingly, for pts who had changes in clinical response from month 1 to month 3, all 3 pts who converted to CR by month 3 had ALCpeak≥1.08, while the 13 of the 15 pts who had progressed by month 3 had ALCpeak<1.08. In addition, EFS was significantly different between pts who had ALCpeak above and below 1.08 (6 months EFS rate 75% vs. 25%, respectively, Figure 1). Conclusions: We found that the ALC expansion occurred in the first 15 days post axi-cel infusion, consistent with the known time frame for CART expansion. Higher ALCpeak level in this timeframe correlated with higher likelihood of achieving CR, and is associated with conversion to CR. This study is limited by the small sample size and limited follow-up, but the results are promising for further prospective investigation in a larger cohort of patients. Disclosures Paludo: Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding; Celgene: Research Funding; Celgene: Research Funding. Ansell:Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding. Bennani:Purdue Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Adicet Bio: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Kite Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board; Seattle Genetics: Other: Advisory board; Adicet Bio: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Other: Advisory board; Purdue Pharma: Other: Advisory board. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Karyopharm: Research Funding; Rigel: Consultancy. Kapoor:Celgene: Honoraria; Janssen: Research Funding; Cellectar: Consultancy; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding. Kenderian:Novartis: Patents & Royalties, Research Funding; Tolero: Research Funding; Humanigen: Other: Scientific advisory board , Patents & Royalties, Research Funding; Lentigen: Research Funding; Morphosys: Research Funding; Kite/Gilead: Research Funding. Kumar:Takeda: Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy, 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: Based on results from the phase 3 trials, maintenance therapy after autologous stem cell transplantation has become the standard of care. While lenalidomide is typically used as the maintenance agent, patients with high risk MM are often maintained on proteasome inhibitor-based maintenance treatment. We examined the trends in maintenance use and outcomes in a large group of patients transplanted at a single institution over two decades spanning the years when maintenance gradually became standard of care. Methods: We included patients who underwent their first autologous stem cell transplantation between 2000 and 2016 in the current study. Patients who received an allogeneic SCT or a planned tandem SCT were excluded. Clinical data was extracted from the medical records or from a prospectively maintained database. Early transplant was defined as SCT within 12 months of diagnosis. High risk (HR) myeloma was defined as per IMWG criteria, based on presence of high-risk FISH abnormalities. Progression free survival and overall survival were estimated from either diagnosis as well as from the date of SCT. Results: We included 1961 patients with MM who were transplanted between January 2000 and August 2016 in the current analysis. Majority (n=1496; 76%) had an early SCT while the remaining patients were transplanted beyond 12 mos from diagnosis. Maintenance was employed in 31% of the patients, 33% of the early SCT and 23% of the delayed SCT. Proportion of patients receiving maintenance increased over the years: <1% in 2000 to 85% in 2016. The most common maintenance approach was an IMiD (56%), followed by a PI (33%) and a PI+IMiD (8%). FISH risk was available in 875 patients, all assessed within 6 months of diagnosis, and 22% were HR. Overall, maintenance was more commonly used in HR patients (64% vs. 36%), and a PI containing maintenance was more commonly used in HR (42% vs. 12%). The PFS was superior for those receiving a maintenance therapy (70 vs. 23 mos, P<0.001); NR vs. 27 mos for early SCT and 25 vs. 16 mos for delayed SCT. The impact of maintenance therapy was more evident in the HR group HR vs SR risk ratio was 2.3 without maintenance, and 1.5 with maintenance. Among the HR patients, PI based maintenance had a trend towards better outcome, while the PFS was better with non-PI maintenance among the SR patients. OS from diagnosis was also better among the early SCT group who received maintenance (99 vs. 88 mos; p=0.01); however, the OS advantage appeared most evident among the HR patients. Conclusions: The experience with maintenance therapy post autologous SCT for myeloma in a non-clinical trial setting appear to confirm the findings from the phase 3 trials. Maintenance provided benefit in patients who had a delayed SCT in our experience. The benefit appear to be particularly relevant for high risk patients, who appear to benefit from PI based regimens. In contrast, SR patients appear to benefit primarily from IMiD based regimen. Disclosures Gertz: Spectrum: Consultancy, Research Funding; Johnson and Johnson: Speakers Bureau; Amgen: Consultancy; Ionis/Akcea: Consultancy; Research to Practice: Consultancy; Appellis: Consultancy; Celgene: Consultancy; Teva: Speakers Bureau; Alnylam: Consultancy; Janssen: Consultancy; Annexon: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Medscape: Consultancy, Speakers Bureau; Prothena Biosciences Inc: Consultancy; Physicians Education Resource: Consultancy. Lacy:Celgene: Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Dingli:Millenium: Consultancy; Rigel: Consultancy; Janssen: Consultancy; alexion: Consultancy; Karyopharm: Research Funding. Kapoor:Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding; Celgene: Honoraria; Janssen: Research Funding; Cellectar: Consultancy; Sanofi: Consultancy, 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.

AbstractRisk stratification of multiple myeloma (MM) at diagnosis is critical. We examined the ability of hematopoietic indices including mean corpuscular volume (MCV), hemoglobin (Hgb), and platelet (Plt) to predict outcomes. This was a retrospective study of patients treated at Mayo Clinic between January 2004 and April 2018. We incorporated three variables (Hgb < 10 g/dL, Plt < 150 × 109/L, and MCV > 96 fL), assigning a score of 1 to each. We identified 1540 newly diagnosed MM patients, of whom 707 (46%) had a score of 0, 513 (33%) had a score of 1, 260 (17%) had a score of 2, and 60 (4%) had a score of 3. The score risk stratified patients into four groups with differing survivals. The median PFS was 32.3 months for score 0, 24.8 months for score 1, 21.7 months for score 2, and 18.3 months for score 3, for P < .001. The median OS was 80.7 months for score 0, 59.9 months for score 1, 51.7 months for score 2, and 31.3 months for score 3, P < .0001. Predictors of OS on the multivariable analysis were age ≥ 65 (HR, 1.93; P < .0001), R‐ISS stage (1‐2 vs 3) (HR, 0.48; P < .0001), and hematopoietic score (0‐2 vs 3) (HR, 0.51; P = .006). A hematopoietic score can predict survival in newly diagnosed myeloma patients.

Abstract INTRODUCTION: Our group has demonstrated that MASS-FIX is a quick, inexpensive, and accurate means to diagnose and monitor the serum and urine of patients with plasma cell disorders. Screening can be done with a MALDI-TOF MS and samples reflexed to microflow liquid chromatography coupled with electrospray ionization (ESI) and Q-TOF MS (microLC-ESI-Q-TOF MS). Because this technique provides a mass/charge (m/z) for a given patient's monoclonal protein, this method can provide greater sensitivity and specificity to monitor for complete response (CR), especially in patients receiving therapeutic monoclonal antibodies. Our goal was to assess the performance of miRAMM in patients with AL who have been classified as complete response using conventional means. METHODS: We identified 77 patients with AL who had both documented CR by immunofixation (Seibia) of the serum (SIFE), urine IFE (UIFE), and serum free light chain (FLC; The Binding Site) and paired serum samples to test by MALDI-TOF and ESI-TOF. No urine samples were available to test. Paired serum samples from baseline and approximately one year post-therapy were immunoaffinity purified using nanobodies targeting kappa, lambda, alpha, gamma and mu as previously described. For the MALDI-TOF (Bruker Microflex, LT), a range of 9,000 to 32,000 m/z was acquired. The m/z distribution was then visually inspected for the presence of a peak that was distinct from the polyclonal background in both the M+1 and M+2 light chain mass ranges. For the ESI-TOF, spectra were also collected on an TripleTOF 5600 quadrupole time-of-flight mass spectrometer (ABSciex, Vaughan ON, CA) in ESI positive mode with a Turbo V dual ion source with an automated calibrant delivery system. TOF MS scans were acquired from m/z 600−2500 with an acquisition time of 100 ms. RESULTS: Median age of the cohort was 58 (range 42, 81). Fifty-eight percent were male. No test was 100% sensitive at baseline with positive results as follows: abnormal FLC ratio, 82%; positive SIFE, 70%; 73% positive UIFE; positive serum MASS-FIX, 71%; and ESI-TOF, 79% . There was light chain isotype agreement in all cases, except for 2 patients for whom the SIFE and the FLCr disagreed. Of the 56 patients with baseline positive MASS-FIX, there was evidence of the original monoclonal protein in 5 patients (see figure for example of spectra illustrating same m/z before and after therapy). Of the 63 patients who had baseline positive ESI-TOF, there was evidence of the original monoclonal protein in 8 patients. Small unrelated monoclonal proteins were seen both by SIFE and by mass spectrometry techniques. With the spectrometry techniques, however, these transient oligoclonal bands could be distinguished from the original monoclonal protein when they shared the same isotype based on the difference in m/z. DISCUSSION: At baseline, the MALDI was able to identify the baseline monoclonal protein in a comparable number of patients as SIFE, UIFE, and FLC. Approximately 10% of patients thought to be in CR using routine screening tests were found to have persistence of their original clone by MALDI and by ESI-TOF. Small post-therapy unrelated monoclonal proteins were also seen both by IFE and by MALDI, but either the presence of a different isotype or in the case of MALDI, a different m/z, made it clear that the monoclonal protein was not related to the original clone. The sensitivity of the assay will improve significantly when we formalize the introduction of free light chain magnetic beads to capture the serum FLCs. Routine use of MASS-FIX of the urine will also increase performance characteristics. Figure. Figure. Disclosures Dispenzieri: Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Gertz:Prothena: Honoraria; celgene: Consultancy; spectrum: Consultancy, Honoraria; Teva: Consultancy; Physicians Education Resource: Consultancy; annexon: Consultancy; Apellis: Consultancy; Alnylam: Honoraria; Medscape: Consultancy; Amgen: Consultancy; janssen: Consultancy; Research to Practice: Consultancy; Abbvie: Consultancy; Ionis: Honoraria. Kumar:Novartis: Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Dingli:Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Millennium Takeda: Research Funding; Millennium Takeda: Research Funding. Kapoor:Takeda: Research Funding; Celgene: Research Funding. Russell:Vyriad: Equity Ownership.