Kumar, Shaji

Introduction Amyloidosis is a disease caused by aggregates of misfolded insoluble proteins that accumulate extracellularly and impair organ function. The most common type of systemic amyloidosis is immunoglobulin light chain (AL), which typically involves the heart, kidneys, nerves, liver, gastrointestinal tract and soft tissue. Retroperitoneal involvement in the setting of systemic AL amyloidosis is rare and only published as case reports. Aim To report characteristics and outcomes of AL amyloidosis patients that had retroperitoneal deposition of amyloid in the novel agent era. Methods Retrospective study of all consecutive systemic AL amyloidosis patients with retroperitoneal involvement at all three Mayo Clinic sites and at Davidoff cancer center, a tertiary hospital in Israel. All patients were diagnosed with retroperitoneal involvement based on computerized tomography (CT) scans. All patients had biopsy proof of amyloidosis with Congo red staining. Patients that were diagnosed with localized amyloidosis of the bladder or ureter and patients that did not receive systemic treatment were excluded. Results We identified 11 patients with systemic AL amyloidosis and retroperitoneal involvement between January 2001 and December 2018. Median age at diagnosis was 65 years (range 50-72). Ten were male (91%) and one was female. Five patients had amyloid secondary to B cell lymphoma (4 Waldenstrom macroglobulinemia and 1 had follicular lymphoma). The involved light chain was lambda in 7 patients and kappa in 4 patients. All patients were diagnosed with retroperitoneal involvement of amyloidosis at presentation (not at progression). In 10 out of the 11 patients, amyloidosis in the retroperitoneum was confirmed by a core biopsy of the retroperitoneal tissue. Significant unintentional weight loss (more than 5 kg) at presentation was documented in six patients (55%). Seven patients (64%) had enlarged lymph nodes on the CT scan. Three patients had CT finding of calcifications, and the distribution pattern was diffuse in 7 patients (64%), while 4 patients presented with a mesenteric mass. Six patients (55%) had evidence of amyloid deposits in the bone marrow and 3 patients (27%) had a positive fat pad. Periorbital purpura was observed in one patient and none had macroglossia. Therapy regimens used are described in table 1. Five patients underwent an autologous stem cell transplantation (ASCT). Eight patients (72%) presented with unilateral (N=2) or bilateral (N=6) hydronephrosis and 7 had nephrostomy tubes or stents inserted. The median follow-up from stent/nephrostomy tube insertion was 33 months (IQR 8-91). Regression of the deposition was documented in one patient and one patient was able to have his nephrostomy tube removed. One patient (9%) developed end stage renal disease requiring dialysis. Data regarding hematologic response rates were available for 9 patients and all responded and achieved hematologic PR or better. The median follow-up for all surviving patients was 91 months (IQR 27-179). Seven of the patients are currently alive. The median OS from diagnosis was 150 months. Figure 1 shows typical diffuse retroperitoneal involvement of AL amyloidosis on a CT scan. Review of the literature revealed 5 cases of retroperitoneal involvement of systemic AL amyloidosis. Most were reports published before routine typing of amyloid. Four of the five cases (80%) were male. The ages ranged from 46 to 80 years. Four of the five cases (80%) presented with weight loss. Two patients had calcifications on the CT scans, and one had a large pleural effusion. Conclusions We report a multicenter case series of 11 patients diagnosed with systemic AL amyloidosis with retroperitoneal involvement, all received systemic chemotherapy. We found male predominance in our cohort. Eight patients presented with hydronephrosis, and only one patient had the nephrostomy tube removed successfully after systemic therapy. ORR was 100% and median OS from diagnosis was 150 months, suggesting that retroperitoneal deposition might confer improved prognosis compared to the general amyloid population. Disclosures Kumar: Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Merck: Consultancy, Research Funding; Dr. Reddy's Laboratories: Honoraria; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Carsgen: Other, Research Funding; Genecentrix: Consultancy; Cellectar: Other; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Adaptive Biotechnologies: Consultancy; MedImmune: Research Funding; Novartis: Research Funding; Kite Pharma: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Tenebio: Other, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments. Dispenzieri:Intellia: Research Funding; Janssen: Research Funding; Celgene: Research Funding; Takeda: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding. Dingli:Rigel: Consultancy; Bristol Myers Squibb: Research Funding; Alexion: Consultancy; Apellis: Consultancy; Millenium: Consultancy; Sanofi-Genzyme: Consultancy; Janssen: Consultancy; Karyopharm Therapeutics: Research Funding. Kapoor:Amgen: Research Funding; Sanofi: Consultancy, Research Funding; Janssen: Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria; Cellectar: Consultancy; Takeda: Honoraria, Research Funding. Gertz:DAVA oncology: Speakers Bureau; Appellis: Other: personal fee; Proclara: Other; Medscape: Other: personal fee, Speakers Bureau; Springer Publishing: Patents & Royalties; Annexon: Other: personal fee; Research to Practice: Other; Celgene: Other; Prothena: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Physicians Education Resource: Other: personal fee; Abbvie: Other; Johnson and Johnson: Speakers Bureau; Teva: Speakers Bureau; Janssen: Other: personal fee; Amgen: Other: personal fee; Alnylam: Other: personal fee; Ionis/Akcea: Other: personal fee; Aurora Bio: Other; Sanofi: Other.

Background: Multiple myeloma (MM) remains an incurable plasma cell (PC) malignancy. Despite improvements in clinical outcomes, variability in treatment response exists. Some patients experience innate resistance, while others develop resistance over the course of treatment. Identifying signatures of treatment response and resistance is essential to predicting effective treatment strategies. Given the phenotypic clonal heterogeneity observed in MM, we hypothesize that resistant and sensitive subpopulations have unique phenotypic signatures. We used mass cytometry (CyTOF) to characterize primary MM samples and correlated their phenotypic signatures with treatment response. Methods: We characterized 102 primary MM samples by CyTOF using 37 antibodies (see figure). Frozen whole BM specimens were thawed, stained with antibodies, barcoded, and analyzed on a Helios mass cytometer. Data was processed using Cytobank or Pathsetter and analyzed using t-distributed stochastic neighbor embedding (t-SNE) algorithm. T-SNE plots for CD45+ cells were created using lineage defining markers. T-SNE plots of neoplastic PCs (CD138+,CD3-,CD16-,CD19-,cytoplasmic kappa or lambda+) were created using all remaining markers. A differential analysis of each sample's clusters was performed against all other events. Z-score values, representing marker changes from the differential analysis, for each cluster were used to group similar clusters across all samples, allowing us to compare sub populations of PCs between patients (see figure). From these groups of clusters with similar changes in markers, we calculated the proportion of cells with increases or decreases in markers for each sample. Results were compared to IMWG 90-day response criteria using a random forest model. Results: We performed mass cytometry on 102 samples from 68 unique MM patients. Median age was 66 years (range 34-95) with a 1.5:1 male:female ratio. 37 (36%) had NDMM, 55 (54%) had RRMM, 2 (2%) had SMM and 8 cases (8%) had unknown status. FISH studies revealed 47 (46%) had hyperdiploidy without a recurrent primary IgH rearrangement, 31 (30%) had t(11;14), 13 (13%) had t(4;14), 5 (5%) had 14;16 or 14;20, 3 (3%) had hyperhaploidy and 3 (3%) had an undefined primary. 54 (53%) had 1q gain/amp, 22 (22%) had TP53 deletion, 22 (22%) had a MYC rearrangement and 71% had high mSMART risk. Nearly all patients received an immunomodulatory compound, a proteasome inhibitor and dexamethasone. 2 (2%) had complete response (CR), 10 (9.8%) very good partial response (VGPR), 36 (35%) had partial response (PR), 14 (14%) had minimal response (MR), 13 (13%) had stable disease (SD) and 17 (17%) had progressive disease (PD). Characterization of CD45+ cells identified a relatively conserved and reproducible map from each patient. Notable differences included an ~2-fold reduction in the percentage of total B cells (CD45+,CD3-,CD19+)/total CD45+ cells in cases with high risk mSMART, RRMM and TP53 deletion compared to cases with standard risk, NDMM or normal TP53 status. Similar B-cell reductions were found in RRMM vs. NDMM samples from matched-patients. In contrast to the conserved t-SNE structure of the CD45+ population, the neoplastic PC population displayed dramatically reduced t-SNE structural consistency. Heterogeneity between patient samples and between the same patient samples over time was observed. We focused our analysis on 22 patients with serial samples. The proportion of each t-SNE group present in each patient sample was calculated and then correlated to the 90-day response metric. We identified a phenotypic group whose proportion increased in relation to disease progression (R2=0.85). This group had elevated BCL-2, pSTAT3, CD56 levels and reduced CD45 and CD81 levels. Evaluating individual markers, we found an increase in the proportion of cells with elevated BCL-2, pS6, Ki67, and IKZF1 levels in relation to disease progression. We also observed an increase in the proportion of cells with reduced pCREB levels and a reduction in the proportion of cells with reduced CD147 levels in relation to disease progression. Conclusions: We have utilized CyTOF to characterize phenotypic and functional markers in MM cells on a single cell level and can identify unique subgroups that change in relation to disease progression. Future analysis will correlate phenotypic signatures with ISS stage, mSMART risk, cytogenetic abnormality and type of treatment. Figure 1 Disclosures Kumar: Kite Pharma: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; MedImmune: Research Funding; Karyopharm: Consultancy; Merck: Consultancy, Research Funding; Carsgen: Other, Research Funding; Cellectar: Other; Novartis: Research Funding; Adaptive Biotechnologies: Consultancy; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genecentrix: Consultancy; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Tenebio: Other, Research Funding; BMS: Consultancy, Research Funding; Dr. Reddy's Laboratories: Honoraria.

Background: Lytic bone lesions are one of the most common clinical characteristics of patients with multiple myeloma (MM) and identification of bone lesions help distinguish between patients with smoldering multiple MM and active MM. Given this, the most recent update of the diagnostic criteria for MM incorporates advanced imaging approaches for distinguishing between the two entities. Several small retrospective studies have compared conventional skeletal survey (SS) with whole-body low dose computed tomography (WBLDCT) scan or the CT portion of a positron emission tomography (PET) scan. Conducting prospective studies comparing these two modalities side by side is limited by the radiation exposure. We undertook this study to provide a comparison between these two imaging modalities in terms of their ability to recognize lytic bone lesions in patients with MM. Patients and methods: This was a retrospective study of consecutive patients with the diagnosis of MM treated at Mayo Cinic Hospital during 2004- 2018. Patients were included if they had a conventional skeletal survey no more than 3 months before MM diagnosis or any time after diagnosis and also had a WBLDCT or PET-CT within a 12-month period following the skeletal survey. We chose this approach since it is unlikely that a patient would have had both modalities done at the same time as part of standard of care (SOC). This approach was also facilitated by a gradual change in our SOC for skeletal imaging from conventional skeletal survey to WBLDCT. To measure the robustness of our findings, we performed a sensitivity analysis in patients who had the exam ≤6 months apart. Proportions were compared using a chi-square test and survival estimates were calculated using the Kaplan- Meier methodology and compared using log rank test. Results: The overall study cohort had 1040 patients, median age was 62 years at diagnosis (range, 24-94), 61% were male and 39% were female. The median time to the skeletal survey was 8 months from diagnosis (range, 0-160) and the median time to WBLDCT or PET-CT from SS was 2 months (0-12). A PET-CT was available in 789 (76%) of patients and WBLDCT in 251 (24%) of patients. Among the 300 patients with no lesions identified by SS, 188 (63%) had lytic lesions identified by CT, while in 60/740 (8%) patients with a positive SS did not have lytic lesions observed on the CT (p<0.0001). Overall, CT identified lytic lesions in 868 (84%) patients compared with 740 (71%) patients with lytic lesions seen on SS. Although the proportion of lytic lesions was slightly higher with PET compared to WBLDCT, the analysis did not reach statistical significance (65% vs. 56%; p = 0.17; Table 1a). After restricting the analysis to those with ≤6 months gap between low dose CT and SS (n=737), the result did not change (Table 1b). Further examination demonstrated that presence of lytic lesions by SS had no impact on OS from diagnosis, detection of lesions on the CT exam was associated with an inferior survival (112 vs. 81 months, p<0.0001). (Figure 1) Conclusion: Skeletal survey has been the screening technique of choice for evaluation of bone involvement in MM for decades. However, CT based approaches have higher sensitivity with lytic lesions identified in a higher proportion of patients. The prognostic value of lytic disease is evident with CT based detection, again suggesting that this provides a more accurate estimate of the skeletal disease burden. Low dose CT rather than conventional radiographs should be the modality of choice for monitoring disease-progression and diagnosing active multiple myeloma. Disclosures Kapoor: Cellectar: Consultancy; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria. Gertz:Abbvie: Other; Celgene: Other; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Janssen: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Johnson and Johnson: Speakers Bureau; Teva: Speakers Bureau; Annexon: Other: personal fee; Research to Practice: Other; Sanofi: Other; Proclara: Other; DAVA oncology: Speakers Bureau; Springer Publishing: Patents & Royalties; Appellis: Other: personal fee; Amgen: Other: personal fee; Prothena: Other: personal fee; Aurora Bio: Other; Alnylam: Other: personal fee; Ionis/Akcea: Other: personal fee. Dispenzieri:Takeda: Research Funding; Pfizer: Research Funding; Janssen: Research Funding; Intellia: Research Funding; Alnylam: Research Funding; Celgene: Research Funding. Dingli:Alexion: Consultancy; Janssen: Consultancy; Sanofi-Genzyme: Consultancy; Millenium: Consultancy; Bristol Myers Squibb: Research Funding; Rigel: Consultancy; Apellis: Consultancy; Karyopharm Therapeutics: Research Funding. Lin:Merck: Research Funding; Takeda: Research Funding; Legend BioTech: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Vineti: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gamida Cells: Consultancy. Kumar:Dr. Reddy's Laboratories: Honoraria; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; Novartis: Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Carsgen: Other, Research Funding; Cellectar: Other; MedImmune: Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Tenebio: Other, Research Funding; Genecentrix: Consultancy; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding.

Background: Patients with newly diagnosed MM can be quite symptomatic as a result of end organ damage related to MM as well as presence of other comorbidities in this relatively older patient population. Prior studies have shown that the performance score as well as other quality of life (QOL), frailty and comorbidities scores can have prognostic value in these patients. However, many of these questionnaires are lengthy and complex, and not practical in a busy outpatient practice. We implemented a three question symptom assessment score in 2010 in our outpatient practice. Here we present the results of the analysis looking at the impact of this measurement in patients with newly diagnosed MM. Patients and Methods: Patients seen in the outpatient Hematology practice at Mayo Clinic, Rochester MN, were asked to grade the symptoms of fatigue, pain, and QOL on a 0 to 10 scale during the past 7 days, with 10 being the worst and the QOL on a similar scale but with 10 being the best. For the purpose of the current analysis the QOL score was reversed.These three scores were added for a total score. We looked at the impact of the baseline score as well as the score after four cycles of therapy, at the time of best response, and at the time of the first progression, wherever they were available. Survival curves were generated by the Kaplan-Meier method and compared using the log rank test. The Cox proportional hazards model was used for assessment of the impact of different prognostic variables. Results: Data from 735 patients with newly diagnosed MM seen at Mayo Clinic between 2011 and 2018 were available from baseline. The median total score was 10 (0-30), and for fatigue, pain and QOL were 4, 3 and 7 respectively, all with range of 0-10. Based on the baseline scores, patients were grouped into tertiles (Group 1 with score < 8, group 2 with score 8 to 14 and group 3 with a score ≥ 15). There were 256 (34%), 272 (37%) and 207 (28%) patients in groups 1, 2 and 3 respectively. The median overall survival (OS) (95% CI) from diagnosis was NR (7.9, NR), 7.7 (6.2, NR) and 5.4 (4.2, 6.9), respectively for groups 1, 2 and 3 (P < 0.0001) (Figure 1a). The prognostic value of the score was independent of age, FISH based risk status and the ISS stage. When evaluated after 4 cycles (n=325), the OS was significantly different for the 3 groups (P<0.01) (figure 1b). We then examined the impact of the score at best response to initial therapy (n=446) on OS from that timepoint and saw similar trend, but the results were not statistically significant (P=0.09) (Figure 1c). When evaluated at the time of first disease progression, the score again identified three groups with different OS from progression (P<0.001) (Figure 1d). Conclusions:Patient-reported outcomes are associated with survival in patients with MM. This simple, easy to complete patient-reported outcome 3-item scale can be easily completed in a busy practice and is a clinically useful tool to assess potential outcomes of patients at various disease stages, including at diagnosis and at relapse. Disclosures Kumar: Adaptive Biotechnologies: Consultancy; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Kite Pharma: Consultancy, Research Funding; Novartis: Research Funding; Sanofi: Research Funding; MedImmune: Research Funding; Karyopharm: Consultancy; Tenebio: Other, Research Funding; BMS: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Cellectar: Other; Genecentrix: Consultancy; Merck: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria. Kapoor:Janssen: Research Funding; Cellectar: Consultancy; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria. Gertz:Proclara: Other; Springer Publishing: Patents & Royalties; Abbvie: Other; Celgene: Other; Aurora Bio: Other; Medscape: Other: personal fee, Speakers Bureau; Sanofi: Other; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Amgen: Other: personal fee; Appellis: Other: personal fee; Annexon: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Prothena: Other: personal fee; Physicians Education Resource: Other: personal fee; Research to Practice: Other; Ionis/Akcea: Other: personal fee; Alnylam: Other: personal fee. Dispenzieri:Alnylam: Research Funding; Intellia: Research Funding; Janssen: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Pfizer: Research Funding. Dingli:Rigel: Consultancy; Millenium: Consultancy; Alexion: Consultancy; Janssen: Consultancy; Apellis: Consultancy; Sanofi-Genzyme: Consultancy; Karyopharm Therapeutics: Research Funding; Bristol Myers Squibb: Research Funding. Lin:Novartis: Consultancy; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Juno: Consultancy; Legend BioTech: Consultancy; Merck: Research Funding; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding.

Introduction Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant clonal disorder, which progresses at a rate of 1% per year to multiple myeloma (MM), or other plasma-cell or lymphoid disorders. MGUS is common and occurs in approximately 3% and 5% of persons 50 and 70 years of age or older, respectively. Clinical factors reported to be associated with MGUS progression include MGUS isotype, abnormal serum free light-chain ratio (FLCr), and high serum monoclonal protein (M protein) level (>=1.5 g per deciliter). Body mass index (BMI) has also been seen associated with MGUS progression, but has not been evaluated in context of established clinical prognostic factors. Here, we evaluate the contribution of BMI to MGUS progression beyond clinical prognostic factors in a population-based study and examine differential associations by sex. Methods We studied 594 patients residing in Olmsted County Minnesota, who were identified with MGUS in a screening study conducted between1995 through 2003. Patients with light-chain MGUS were not included. Patients were screened for M-protein [normal (<1.5 g/dl) or high (≥1.5 g/dl)], FLCr [normal (0.26-1.65) or abnormal (<0.26 and/or >1.65)], and isotype (IgG, IgM, IgA, bi-clonal). Follow-up time was calculated from date of MGUS screening to date of last follow-up, death, or progression to MM or another plasma-cell or lymphoid disorder. BMI (kg/m2) was calculated using height and weight values reported close to sample date (80% of patients within 2 years), and then categorized into BMI<25 and BMI≥25. We used Cox regression to estimate the association of BMI with risk of MGUS progression to MM or another plasma-cell or lymphoid disorder, univariately, and accounting for clinical factors. Analyses were also stratified by sex. We report hazard ratios (HR) and 95% confidence intervals (CI). Results Of the 594 patients, 51% were male, and the median age at screening date was 73 (range:50-98 years). The immunoglobulin type was IgG in 71% of patients, IgM in 17%, IgA in 10%, and bi-clonal in 2%. High M protein level was observed in 22% and abnormal FLCr in 28%. BMI≥25 was observed in 67% of patients. The median follow-up time was 10.5 years (range:0-25). Over a median of 6,846 person-years, 465 patients (78%) died and 57 patients progressed and developed MM (N=39), amyloidosis (N=8), lymphoma (N=5), or Waldenstrom macroglobulinemia (N=5). The overall rate of progression was 0.87 events (CI:0.67-1.12) per 100 person-years, and higher among males (1.01, CI:0.73-1.42) than in females (0.72, CI:0.48-1.08), however, the difference was not statistically significant (P=0.24). In univariate analyses, BMI≥25 (HR=2.14, CI:1.05-4.36, P=0.04), non-IgG isotype (HR=2.84, CI:1.68-4.80, P=0.0001), high M protein (HR=2.57, CI: 1.50-4.42, P=0.001), and abnormal FLCr (HR=3.39, CI:1.98-5.82, P<0.0001) were associated with increased risk of progression (Table 1.A). These four factors were independently associated with MGUS progression in a multivariable model, with a c-statistic=0.75 (CI:0.68-0.82). When stratifying by sex, associations of BMI with progression were stronger among females than males (Table 1.B) [c-statistic=0.81 (CI:0.72-0.90) vs 0.71 (CI:0.60-0.82) for females vs. males respectively], however, a test for interaction between BMI and sex was not statistically significant (P=0.15). Conclusions In this study we found evidence that high BMI is a prognostic factor independent of isotype, M protein, and FLC ratio in the full cohort, however, this was mainly driven by the effect in females rather than males. Future studies should further investigate sex differences in evaluating prognostic factors among MGUS patients. Disclosures Dispenzieri: Intellia: Research Funding; Pfizer: Research Funding; Alnylam: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Janssen: Research Funding. Kumar:Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Cellectar: Other; Kite Pharma: Consultancy, Research Funding; Tenebio: Other, Research Funding; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; MedImmune: Research Funding; Sanofi: Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Genecentrix: Consultancy; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Carsgen: Other, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member.

Introduction High risk (HR) multiple myeloma (MM) constitutes approximately 25 % of newly diagnosed patients and is a subgroup of MM patients that is variably defined. Patients with 17p deletion are considered HR and their optimal treatment approach has not been determined. Various strategies have been suggested to improve outcomes in MM patients harboring del 17p, including tandem transplants. Recently, the long-term outcomes of the phase 3 EMN02 trial were published with the study group receiving bortezomib, cyclophosphamide and dexamethasone (VCd) induction prior to transplant. There are no data demonstrating that tandem transplant is applicable to the US population using induction containing immunomodulatory agents and bortezomib. Aim To report on outcomes of newly diagnosed MM patients with del 17p that underwent autologous stem cell transplantation (ASCT). Methods Retrospective study of all consecutive newly diagnosed MM patient with del 17p that underwent ASCT at Mayo Clinic, Rochester, Minnesota. Patients were defined by the Mayo Medical Lab as 17p deleted and included if they met the following criteria: If 50 cells in the bone marrow sample and 10 cells with the deletion were identified (20%) or if the bone marrow sample had between 20-50 total cells and 20% cells with the deletion were identified. We excluded patients that relapsed prior to ASCT (as those patients were excluded in the EMN02 trial), patients that underwent ASCT more than 12 months from the diagnosis and patients that underwent tandem ASCT (defined as two consecutive ASCT within 180 days of each other without relapse in between). Consolidation treatment was defined as treatment given after transplant for up to six 28-day cycles and maintenance was defined as all treatment given after ASCT for more than 6 months. Combined maintenance was defined as maintenance regimens that included two novel agents. Results 116 patients with MM and 17p deletion underwent ASCT at Mayo Clinic between January 2013 and April 2020. The median age at diagnosis was 62 (IQR 57-68, range 34-76) years. Forty-five (39%) patients were over 65 years. Nine patients (8%) had triple-hit MM and 34 (29%) had double-hit MM. Median follow-up of the survivors was 33 months (IQR 21-54). Consolidation therapy was given to 36 patients (31%) and maintenance was given to 91 patients (78%). Seven patients relapsed before day 100. There was no difference in the OS (P=0.72) or PFS (P=0.1) between patients that received VRd (bortezomib, lenalidomide and dexamethasone) versus VCd (bortezomib, cyclophosphamide and dexamethasone) induction (Figure 1). When comparing patients that received proteasome inhibitors (PIs)+ immunomodulatory agents (IMiDs) as induction to patients that received VCd induction, PFS was longer for patients that received the PIs + IMiDs (HR 0.53 P=0.04, 95% CI=0.3-0.98) (Figure 2), however there was no OS difference (P=0.61). Maintenance therapy was given to 94 patients (81%). There was no OS (P=0.34) or PFS (P=0.36) difference between IMiD based and PI based maintenance, but there was a PFS advantage to patients that received two drug maintenance (HR= 0.41, P=0.037, 95% CI 0.14-0.95) (Figure 2). The median OS and PFS of the entire cohort were not reached and 29 months, respectively. Conclusions The outcomes of our patients were similar to that of the single arm ASCT in the EMN02 trial, and no difference in outcomes were found between patients that received VRd and VCd induction, suggesting that tandem transplants should be considered for 17p deleted MM patients. Dual novel agent maintenance therapy is important in improving outcome. Disclosures Kapoor: Celgene: Honoraria; GlaxoSmithKline: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Cellectar: Consultancy; Takeda: Honoraria, Research Funding; Janssen: Research Funding. Kumar:Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; Cellectar: Other; Genecentrix: Consultancy; Tenebio: Other, Research Funding; Adaptive Biotechnologies: Consultancy; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; Merck: Consultancy, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Novartis: Research Funding; Carsgen: Other, Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; MedImmune: Research Funding. Dispenzieri:Pfizer: Research Funding; Takeda: Research Funding; Janssen: Research Funding; Alnylam: Research Funding; Intellia: Research Funding; Celgene: Research Funding. Dingli:Alexion: Consultancy; Sanofi-Genzyme: Consultancy; Bristol Myers Squibb: Research Funding; Janssen: Consultancy; Millenium: Consultancy; Karyopharm Therapeutics: Research Funding; Rigel: Consultancy; Apellis: Consultancy. Gertz:DAVA oncology: Speakers Bureau; Proclara: Other; Abbvie: Other; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Appellis: Other: personal fee; Research to Practice: Other; Ionis/Akcea: Other: personal fee; Celgene: Other; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; Annexon: Other: personal fee; Alnylam: Other: personal fee; Prothena: Other: personal fee; Janssen: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Aurora Bio: Other; Springer Publishing: Patents & Royalties; Sanofi: Other; Amgen: Other: personal fee.

Background: B-cell maturation antigen (BCMA) is widely expressed on normal plasma cells and malignant plasma cells in multiple myeloma (MM). MEDI2228 is an antibody-drug conjugate (ADC) that targets the extracellular domain of human BCMA with preferential binding to membrane-bound versus circulating soluble BCMA. The ADC is comprised of a fully human antibody to BCMA, site- specifically conjugated to a DNA cross-linking pyrrolobenzodiazepine (PBD) dimer via a protease-cleavable linker. After cell surface binding to BCMA, MEDI2228 is internalized and cleaved in the lysosomal compartment, releasing the active PBD, which cross-links DNA and leads to apoptotic cell death. We report the results from a phase 1, first-in-human, open-label, dose-escalation and expansion trial (NCT03489525) that evaluated the safety, pharmacokinetics (PK), and clinical activity of MEDI2228 in patients (pts) with relapsed/refractory MM (R/R MM). Methods: Eligible pts were ≥18 years old with confirmed R/R MM as defined by International Myeloma Working Group consensus criteria, had measurable disease, and had an Eastern Cooperative Oncology Group performance status ≤1. Pts had to have progressed after treatment with three classes of standard-of-care anti-myeloma drugs, including proteasome inhibitors (PIs), immunomodulatory drugs (IMiDs), and monoclonal antibodies (mAbs). Dose escalation was based on an accelerated titration design, with an mTPI-2 algorithm. During dose escalation, MEDI2228 was administered in sequentially ascending dose levels (0.0125, 0.025, 0.05, 0.1, and 0.2 mg/kg) intravenously every 3 weeks (Q3W). Due to dose-limiting toxicities (DLTs), the dose was de-escalated from 0.2 mg/kg to an intermediate dose level of 0.14 mg/kg. The primary endpoint was safety and tolerability. Secondary endpoints included assessment of preliminary efficacy, PK, and immunogenicity. Results: As of May 15, 2020, 82 pts received MEDI2228 during dose escalation and expansion. All pts had received prior therapy with an IMiD, PI, and mAb: lenalidomide, 76 (94%); pomalidomide, 68 (84%); bortezomib, 77 (95%); carfilzomib, 64 (79%); and daratumumab, 71 (87%). Pts received between 2-11 lines of prior regimens. At 0.2 mg/kg, 2 pts experienced DLTs (grade 3/4 thrombocytopenia) without bleeding; no DLTs were reported for other dose levels. The maximum tolerated dose was 0.14 mg/kg Q3W. Treatment-related adverse events (TEAEs) occurring in ≥20% of pts in the 0.14 mg/kg cohort were photophobia (53.7%), thrombocytopenia (31.7%), rash (29.3%), increased gamma-glutamyltransferase (24.4%), dry eye (19.5%), and pleural effusion (19.5%). No reports of keratopathy or visual acuity loss were observed in the 0.14 mg/kg cohort. The TEAE profiles at lower-dose levels were similar but with lower incidences compared with the 0.14 mg/kg level. Efficacy was demonstrated at all dose levels (dose, objective response rate [ORR], [n]): 0.0125 mg/kg, 33.3% [1/3]; 0.025 mg/kg, 16.7% [1/6]; 0.05 mg/kg, 33.3% [3/9]; 0.10 mg/kg, 27.8% [5/18]; 0.14 mg/kg, 61.0% [25/41]; 0.2 mg/kg, 40.0%, [2/5]. In the 0.14 mg/kg cohort, ORR was 61.0% (95% confidence interval [CI]: 44.5%, 75.8%); there were 10 (24.4%) very good partial responses (VGPRs), 15 (36.6%) partial responses, and 3 (7.3%) minimal responses. Four of the VGPR pts were immunofixation negative. Most (90.2%) pts in the 0.14 mg/kg cohort had received prior daratumumab. Median duration of response (DOR) in the 0.14 mg/kg cohort was not reached. MEDI2228 exhibited linear PK at doses of ≥0.05 mg/kg Q3W that was minimally impacted by circulating levels of soluble BCMA at baseline. There was no difference in BCMA expression by IHC in the bone marrow of responders compared with nonresponders. Thirty-six pts in the 0.14 mg/kg cohort discontinued treatment due to adverse events (n=24), progressive disease (n=8), patient decision (n=2), investigator decision (n=1), or death (n=1). Conclusion: MEDI2228 is a BCMA-targeted ADC that demonstrated clinical efficacy at all dose levels explored. MEDI2228 0.14 mg/kg Q3W had a manageable safety profile and an ORR of 61% in a heavily pretreated population with myeloma that is R/R post PI, IMiD, and mAb therapies. Disclosures Kumar: Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Tenebio: Other, Research Funding; Merck: Consultancy, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genecentrix: Consultancy; Novartis: Research Funding; Kite Pharma: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; MedImmune: Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Sanofi: Research Funding; Carsgen: Other, Research Funding; Cellectar: Other; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; Adaptive Biotechnologies: Consultancy. Bhutani:Sanofi Genzyme: Consultancy; Takeda: Other: Clinical trial funding to institute, Speakers Bureau; BMS: Other: Clinical trial funding to institute, Speakers Bureau; Amgen: Speakers Bureau; MedImmune: Other: Clinical Trial Funding to Institute; Prothena: Other: Clinical Trial Funding to Institute; Janssen: Other: Clinical Trial Funding to Institute. Spencer:Roche: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Other: Grant/Research Support; Servier: Consultancy, Other: Grant/Research Support; Janssen: Consultancy, Honoraria, Other: Grant/Research Support, Speakers Bureau; Haemalogix: Consultancy, Honoraria, Other: Grant/Research Support; Abbvie: Consultancy, Honoraria, Other: Grant/Research Support; Pfizer: Consultancy, Honoraria; Takeda: Honoraria, Other, Speakers Bureau; Secura Bio: Consultancy, Honoraria; TheraMyc: Consultancy, Honoraria; Antegene: Consultancy, Honoraria; BMS: Honoraria, Other: Grant/Research Support, Research Funding, Speakers Bureau; Pharmamar: Other. Ailawadhi:Cellectar: Research Funding; Pharmacyclics: Research Funding; Janssen: Research Funding; Takeda: Honoraria; Amgen: Research Funding; Celgene: Honoraria; Phosplatin: Research Funding; Medimmune: Research Funding; BMS: Research Funding. Kalff:Amgen: Honoraria; Janssen: Honoraria; Roche: Honoraria; Celgene: Honoraria; CSL: Honoraria. Pore:AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Gibson:AstraZeneca: Current Employment, Other: Paid as a clinical scientist contractor. Wang:AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Cheng:Astrazeneca: Current Employment, Current equity holder in private company. Williams:AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Kinneer:AstraZeneca: Current Employment, Current equity holder in publicly-traded company, Other: Personal fees; BCMA Monoclonal Antibody-Drug Conjugate: Patents & Royalties: Pending. Zonder:Intellia: Membership on an entity's Board of Directors or advisory committees, Other: Personal fees; Alnylam: Membership on an entity's Board of Directors or advisory committees, Other: Personal fees; Oncopeptide: Membership on an entity's Board of Directors or advisory committees, Other: Personal fees; Amgen: Membership on an entity's Board of Directors or advisory committees, Other: Personal fees; BMS: Consultancy, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Other: Personal fees; Janssen: Consultancy, Other: Personal fees; Prothena: Consultancy; Caelum: Consultancy; Celgene: Research Funding. Larsen:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees. Yee:Amgen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; GSK: Consultancy; Janssen: Consultancy; Karyopharm: Consultancy; Oncopeptide: Consultancy; Sanofi: Consultancy; Takeda: Consultancy, Research Funding. Dimopoulos:Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Research Funding, Speakers Bureau; BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Speakers Bureau.

Introduction: Multiple myeloma (MM) is a genetically complex and clinically heterogeneous disease. Disease biology and phenotype is heavily influenced by the tumor microenvironment and the interaction between the immune milieu and malignant plasma cell population. Understanding the molecular profile of tumor along with the immune ecosystem can provide insights into key pathways that are important in disease pathobiology. Therefore, in this study, we have used single-cell RNA-Seq (scRNA-Seq) to compare the detailed maps of the bone marrow microenvironment of patients with rapid progressing disease (PFS < 18 months) with those whose disease had not progressed at the time of analysis (PFS < 4 years) Methods: MM patients (n=18) with rapid and no progression were identified from the Multiple Myeloma Research Foundation (MMRF) CoMMpass study, a longitudinal genomic study of patients with newly diagnosed, active multiple myeloma (NCT01454297). To generate a robust scRNA-Seq profile with minimal false positive, we profiled multiple technical replicates/aliquots of viably frozen CD138-negative bone marrow cells from each patient at three medical centers/universities (Beth Israel Deaconess Medical Center, Boston, Washington University in St. Louis and Mount Sinai School of Medicine, NYC using droplet-based single-cell barcoding technique. After batch correction and normalization, the cellular clusters were identified using principal component analysis and Uniform Manifold Approximation and Projection (UMAP) approach (Becht et al, 2018). Differential expression, pathways and systems biology analysis between rapid and non-progressors revealed differences for specific cell clusters (Panigrahy, Gartung et al. 2019). To determine association of plasma cell overexpressed genes with survival in CoMMpass study, survival analysis was performed using Kaplan-Meier (K-M) approach. Results: In this study, comparative analysis was performed of the bone marrow microenvironment of patients with aggressive and indolent disease by generating single-cell profiles of ~102,207 cells from 48 samples of 18 patients with MM. The UMAP approach identified multiple transcriptionally diverse clusters of plasma (CD138+), immune (PTPRC+) and erythroid (GYPA1/2+) cells (Fig 1a). Interestingly, the analysis identified CD138+ plasma/tumors cells clusters in a subset of samples from patients with rapid -progression and these clusters depicted a high degree of inter-patient heterogeneity (Fig 1a). Further characterization of plasma tumor cells depicted significant activation (Z score >2 and P-value <.001) of pathway related to "Unfolded protein response", epithelial-mesenchymal transition (EMT), and "p38 MAPK Signaling". These rapid progressions associated with plasma cells overexpressing multiple genes (e.g., Hazard ratio (HR) CCL3=1.9 95% CI= (1.5-3.9) log-rank P=0.0004, HSPA5 HR=1.4 (1-2.6), P=0.03) that are associated with poor outcome in multiple myeloma based CoMMpass data. The bone marrow microenvironment cells formed 22 clusters, comprising of cells from myeloid, macrophages, T cells, B cells, dendritic cells, Natural Killer T (NKT) cells, and erythroid lineages. The Non-progressive patients depicted enrichment of GZMB+ T and NKT cells with overexpression of genes associated with "Natural Killer Cell Signaling", "CD28 Signaling in T Helper Cells", "NF-kB Signaling" and "Th17 Activation Pathway" (Fig1b, c). Systems biology analysis depicted significant activation of TNF, STAT4, and NFATC2 regulatory signatures in NKT cells. The analysis also observed enrichment of macrophages, several types of monocytes, and myeloid cells in the samples from patients with non-progressive disease (Fig 1d). The myeloid/monocytes cluster depicted significant activation of multiple metabolic (i.e., Glycolysis, Gluconeogenesis) and immune response (i.e. IL8) pathways (Fig 1e). In summary, this multi-site study provides insights into potentially significant differences in the transcriptomic landscape of multiple myeloma patients with rapid and non-progression of disease. The non-progressive patients depict significant enrichment of activated T cells and myeloid lineage populations, suggesting their role toward better outcomes. These findings will be further expanded by ongoing single cell analyses of the CoMMpass tissue bank under the MMRF Immune Atlas initiative. Figure 1 Disclosures Bhasin: Canomiiks Inc: Current equity holder in private company, Other: Co-Founder. Dhodapkar:Roche/Genentech: Membership on an entity's Board of Directors or advisory committees, Other; Amgen: Membership on an entity's Board of Directors or advisory committees, Other; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Other; Janssen: Membership on an entity's Board of Directors or advisory committees, Other; Kite: Membership on an entity's Board of Directors or advisory committees, Other; Lava Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other. Kumar:Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Genecentrix: Consultancy; Tenebio: Other, Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; Novartis: Research Funding; Sanofi: Research Funding; MedImmune: Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Cellectar: Other; Carsgen: Other, Research Funding; Dr. Reddy's Laboratories: Honoraria; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding.

Background: Multiple myeloma (MM) is an incurable plasma cell malignancy and genetic abnormalities contribute to disease heterogeneity and outcome. Primary abnormalities, namely recurrent immunoglobulin (Ig) heavy chain translocations and hyperdiploidy, occur early in disease course. Secondary events, such as MYC abnormalities occur upon progression. Earlier studies showed MYC abnormalities detected by FISH or by capture sequencing were independently associated with poor outcome (Walker, et al., BCJ, 2014), while recent studies using WGS did not support this finding (excluding MYC/IGL) (Mikulasova, et al. Haematologica, 2020; Misund, et al. Leukemia, 2020). We hypothesize these discrepancies are due to differences in methods and sensitivities of detection of MYC abnormalities by FISH vs. WGS. Given that MYC abnormalities often display remarkable genomic heterogeneity with numerous gene partners, reduced detection of MYC abnormalities by FISH is not unexpected. This hypothesis is supported by lower frequencies of MYC abnormalities found by FISH (15%) vs. NGS (30-35%) consistent with ~50% false-negative rate of the MYC FISH probe (Smadbeck, et al. BCJ, 2019). To better understand the role of MYC in myeloma disease outcome, we compared the MYC abnormality subtype identified by FISH or NGS vs. MYC gene expression levels and overall survival. Methods: We performed a retrospective study of newly diagnosed MM patients seen at Mayo Clinic or enrolled in the MMRF CoMMpass trial. For Mayo cases, MYC FISH results (breakapart probe, Abbott) were obtained from the Mayo Clinic Genomics database (N=1342) and mate pair sequencing (MPseq) was performed on 140 cases. For CoMMpass cases, we obtained tumor long-insert whole genome sequencing (WGS), RNA sequencing (RNAseq) for gene expression and clinical outcome data. Overall survival (OS) was defined as time from diagnosis to death from any cause or to last follow up. Survival curves were estimated using Kaplan Meier and compared using the Log-Rank test. Statistical analyses performed using SPSS and JMP with significance determined when P <0.05. Results: We first evaluated the impact of MYC abnormalities on OS when detected by FISH or NGS. In Mayo cases, OS was significantly shorter in patients with MYC abnormalities compared to patients without MYC abnormalities using FISH (5.3 vs. 8.0 years, P<0.001, N=1342). In contrast, there was no significant difference in OS between patients with or without MYC or abnormalities using MPseq or WGS in both the Mayo and CoMMpass cohorts (Mayo: 6.4 vs. and 6.9 years P=0.78, N=140; CoMMpass: 4.9 vs. and 5.1 years P=0.74, N=546). Since FISH-detected MYC abnormalities were associated with poor outcome, we evaluated differences in the types of MYC abnormalities identified FISH and genome sequencing; 270 of 658 CoMMpass cases had a MYC abnormality and 12 abnormality subgroups were identified. In the Mayo cases, FISH preferentially detected translocations and complex abnormalities and missed insertions with flanking duplicating sequences or terminal tandem duplications (TTD) that occur telomeric to MYC. Since the level of MYC expression should be a consequence of the various genomic abnormalities altering the MYC gene region, we compared MYC expression levels in relation to MYC abnormality subgroups. Highest expression was seen with MYC amplification, followed by Ig abnormalities, non-Ig abnormalities, complex deletion/duplications, proximal deletions, non-Ig insertions, terminal deletions, TTD, trisomy 8, no MYC structural variation, monosomy 8 and cases with MAX mutations had the lowest expression. Abnormalities identified by FISH had higher MYC expression (83.5 TPM) compared to cases predicted to be missed by FISH (63.2 TPM). We tested if high MYC expression, irrespective of MYC structural abnormality, was associated with differences in OS. Boxplot analysis was used to categorize MYC expression in 631 CoMMpass patients as top quartile/high MYC expression (Q4≥ 75 TPM, n=159) and bottom quartile/low MYC expression (Q1≤ 16.5 TPM, n= 158) (see Figure). OS was significantly shorter in patients with high MYC expression compared to patients with low MYC expression (4.6 vs. 5.3 years, P <0.038). Conclusion: We show that FISH detects only a subset of the MYC abnormalities detected by genome sequencing, and that FISH-detected MYC abnormalities are associated with higher MYC gene expression and decreased survival. Figure 1 Disclosures Kumar: Kite Pharma: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Dr. Reddy's Laboratories: Honoraria; Cellectar: Other; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Tenebio: Other, Research Funding; Carsgen: Other, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Merck: Consultancy, Research Funding; Genecentrix: Consultancy; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; MedImmune: Research Funding; Adaptive Biotechnologies: Consultancy.

Introduction: Since 2018, immunoenrichment-based matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), termed MASS-FIX, has replaced standard gel-based immunofixation for the detection and isotyping of serum monoclonal proteins at Mayo Clinic. MASS-FIX can readily identify N-glycosylation of involved light chains (LC N-glycosylation) by its unique, polytypic spectral pattern. LC N-glycosylation is identified more commonly in light chain amyloidosis (AL) than other plasma cell disorders (PCDs), and is associated with an increased risk of progression from MGUS to both AL and other PCDs (Dispenzieri et. al. Leukemia 2020). Herein, we report the mass spectral characteristics and distribution of diagnoses among 222 patients with LC N-glycosylation detected during a 20 month period in our clinical lab. Methods: MASS-FIX was performed on patient samples as previously described (Kohlhagen et. al. Clin Chem Lab 2020). Demographics and laboratory data, including quantitative M-spike, serum free light chains (FLC), and quantitative immunoglobulins at the time of MASS-FIX were recorded. For patients with multiple samples during the study period, only the initial MASS-FIX was evaluated. 9195 unique patients had MASS-FIX performed from 7/24/2018 to 03/06/2020. Inclusion criteria for this retrospective study included: 1) consent for record review; 2) a monoclonal protein identified on MASS-FIX; 3) an underlying PCD. Patients were considered to have negative results (2211 in total) on MASS-FIX if: 1) no monoclonal protein was identified (1081, 49%); 2) the interpretation was "cannot rule out monoclonal protein" (945, 43%); 3) multiple, nonspecific spectral peaks were identified consistent with immune reconstitution (29, 1%); or 4) the only monoclonal protein identified was consistent with a therapeutic monoclonal antibody (156, 7%). The final positive cohort consisted of 4118 patients with definitive monoclonal proteins on MASS-FIX. Results: Two-hundred and twenty-two (5%) of the 4118 patients with a positive MASS-FIX had LC N-glycosylation. 202 patients (91%) had FLC assays performed. Of these, 110 (54%) were kappa LC restricted, 22 (11%) were lambda restricted, and 70 (35%) were normal. A quantifiable M-spike was identified in 110 patients (85%) of 129 patients who had serum protein electrophoresis performed. By MASS-FIX, 139 patients (63%) had an IgG isotype, 18 (8%) an IgA, and 55 (25%) an IgM. Two of these patients had a bi-clonal pattern in which both IgG kappa and IgM kappa LCs were N-glycosylated. 12 patients (5%) had monoclonal light chains with no corresponding heavy chain. Overall, 173 (78%) of 222 patients were kappa LC restricted and 44 (22%) were lambda. 189 patients (85%) had a monoclonal pattern, 18 (8%) had a bi-clonal pattern, and 3 (1%) had a tri-clonal pattern. The most common PCD diagnoses for the 222 patients with LC N-glycosylation were MGUS (45%), multiple myeloma (MM) (31%), and immunoglobulin light chain amyloidosis (AL) (8%). The percentage of MASS-FIX positive patients with LC N-glycosylation by diagnosis, stratified by kappa and lambda LC restriction, is illustrated in Figure 1. Cold agglutinin disease (CAD) had the highest relative percentage of patients with LC N-glycosylation, regardless of LC restriction. Eighteen AL patients (5%) had LC N-glycosylation; the percentage was higher in kappa restricted (13%) than lambda restricted AL patients (2%). Of note, LC N-glycosylation was not detected in patients with plasma cell leukemia, non-AL amyloidosis with associated MGUS, POEMS Syndrome or Castleman's Disease in this cross sectional sampling of patients. Conclusions: This retrospective study demonstrates that 5% of patients in a routine clinical setting with positive MASS-FIX have glycosylated LCs. Consistent with prior observations, CAD had the highest relative percentage of LC N-glycosylated patients. The percentage of AL patients with LC N-glycosylation in this cohort is lower than previously reported for newly diagnosed AL patients (Kumar et. al. Leukemia 2019), which is not surprising given that the current cohort study is a cross sectional evaluation of patients at various stages of diagnosis and treatment rather than a prevalence study. Further study will be done to exclude the presence of latent AL in patients with N-glycosylated LC and diagnoses of MGUS, SMM, MM, and Waldenstrom's macroglobulinemia. Disclosures Gertz: Springer Publishing: Patents & Royalties; Proclara: Other; DAVA oncology: Speakers Bureau; Johnson and Johnson: Speakers Bureau; Teva: Speakers Bureau; Sanofi: Other; Research to Practice: Other; Celgene: Other; Abbvie: Other; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Amgen: Other: personal fee; Appellis: Other: personal fee; Annexon: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Prothena: Other: personal fee; Alnylam: Other: personal fee; Ionis/Akcea: Other: personal fee; Aurora Bio: Other. Kumar:Adaptive Biotechnologies: Consultancy; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Carsgen: Other, Research Funding; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Merck: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; MedImmune: Research Funding; Genecentrix: Consultancy; Tenebio: Other, Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; Novartis: Research Funding; Kite Pharma: Consultancy, Research Funding; Cellectar: Other. Kapoor:Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria; Cellectar: Consultancy. Dingli:Alexion: Consultancy; Karyopharm Therapeutics: Research Funding; Bristol Myers Squibb: Research Funding; Janssen: Consultancy; Sanofi-Genzyme: Consultancy; Apellis: Consultancy; Rigel: Consultancy; Millenium: Consultancy. Lin:Janssen: Consultancy, Research Funding; Novartis: Consultancy; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Juno: Consultancy; Legend BioTech: Consultancy; Merck: Research Funding; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding. Murray:The Binding Site: Patents & Royalties: Patent Use of Mass Spec to identify monoclonal proteins licensed to The Binding Site. Dispenzieri:Intellia: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Alnylam: Research Funding.