Citations

AbstractAchievement of a complete response (CR) in multiple myeloma (MM) correlates with improvement in survival outcomes; however, its impact on prognostic variables at baseline outside of clinical trial settings is not well described. We sought to determine the impact of achieving a CR within 2 years from diagnosis, its effect on the prognostic value of fluorescence in situ hybridization (FISH) and International Staging System (ISS) risk, and examined additional predictors of outcome among those achieving a CR in a routine clinical setting. We evaluated 1869 newly diagnosed MM patients who had ≥ 2 monoclonal protein immunofixation studies in the serum and urine available within 24 months from diagnosis, categorizing those with ≥ 2 negative serum and urine immunofixations as achieving CR. With a landmark at 24 months, median progression‐free survival (PFS) for CR versus non‐CR patients was 29.8 versus 20.9 months (p ≤ .0002); median overall survival (OS) was 104 versus 70 months (p < .0001). The impact of achieving a CR was retained after adjusting for FISH, ISS, sex, transplant status, and involved heavy chain. Baseline FISH and ISS stage were not associated with PFS or OS among patients achieving a CR. The following variables were found as predictors of inferior OS within the CR cohort: age > 75 years, male gender, hypoalbuminemia, and non‐immunoglobulin G involved heavy chain. Our study confirms that achievement of CR within 2 years from diagnosis is associated with improvement in survival outcomes and neutralization of the impact of FISH and ISS risk, thereby confirming observations from the clinical trial setting among a clinical practice cohort.

AbstractThromboses are prevalent in POEMS syndrome, but few risk factors for POEMS‐associated thrombosis have been identified. The objective of this study is to identify novel risk factors for POEMS‐associated thrombosis. In this retrospective cohort of 230 POEMS patients, 27% developed thrombosis. Arterial events were slightly more common than venous. Stroke accounted for 26% of all thromboses and 53% of arterial events. There were differences in baseline features between the thrombosis group and the no thrombosis group, and these were driven by patients with arterial thrombosis. Risk factors for arterial thrombosis included thrombocytosis, elevated hemoglobin/hematocrit, extravascular volume overload, and splenomegaly. Hyperprolactinemia appeared to be a risk factor for venous thrombosis. The risk of thrombosis was most striking among men with elevated hemoglobin (32% vs. 5%, p < .001) and hematocrit (42% vs. 5%, p < .001) compared to men without. Most thromboses occurred prior to POEMS directed therapy, and most that occurred during therapy happened within 3 months of diagnosis. Twenty‐one percent of patients with thrombosis had recurrence. In recognition of high overall rates of thrombosis in this population, all patients with POEMS syndrome should receive prophylactic antiplatelet therapy, and clinicians should consider anticoagulation in patients with risk factors for POEMS‐associated thrombosis.

Abstract Introduction POEMS syndrome is a rare disease associated with a plasma cell dyscrasia with limited information regarding the role of ASCT. Small single institution series have demonstrated deep and durable responses after ASCT along with neurological improvement. Despite these benefits, ASCT is thought to have higher treatment related morbidity and mortality, limiting its use. We describe the outcomes from an international multicenter database of patients with POEMS syndrome undergoing ASCT. Methods We performed a retrospective analysis using the Center for International Blood and Marrow Transplant Research (CIBMTR) database to evaluate the outcomes of patients undergoing ASCT for POEMS syndrome. Standard descriptive methods were used to report patient characteristics. Univariate and multivariate analysis were performed to identify predicators for non-relapse mortality (NRM), relapse, progression-free and overall survival (PFS, OS). NRM was compared between POEMS and multiple myeloma (MM) patients who underwent ASCT during the same time period. Results Between 2008-2018, 331 pts with POEMS syndrome who underwent ASCT were identified. The median age was 51 years, with 66% males. Racial distribution was 65% Caucasians, 19% African American, 5% other, and 10% missing. Pre-transplant characteristics included 70% patients had Karnofsky score &lt;90, and 50% had HCT-CI ≥ 3, reflecting underlying disease severity and symptoms. The most common comorbidity was pulmonary (52%). Only 14% of patients were in very good partial response or better at the time of ASCT and 72 (22%) patients underwent ASCT without prior treatment. The median time from diagnosis to ASCT was 7 months and 74% underwent ASCT within 12 months of diagnosis. The most common mobilization strategy was GCSF +/- plerixafor in 50% of pts and 87% of pts received conditioning with 200mg/m2 of Melphalan. The median follow up was 48 (range 3-137) months. At day 100, NRM was 0.9 % (95% CI: 0.2-2.2%). At 4 years, NRM was 4.9% (95% CI: 2.6-7.9%), relapse 15.4% (95% CI 11.3-20.1%), PFS 79.7% (95% CI 74.5-84.3%) and OS 92% (95% CI 89.2-95.6%). Subsequent neoplasms were seen in 16 (5%) with 4 myeloid malignancy and 12 solid tumors. On multivariate analysis, age ≥ 60 years was associated with greater hazards of mortality, HR 2.6 (95% CI 1.2-5.6), p 0.01. The figure shows the comparable NRM between POEMS and MM (p 0.31). Conclusions: We report outcomes of the largest ASCT series of POEMS patients. Despite a high HCT-CI and low functional status among patients with POEMS syndrome, no difference in NRM was seen when compared to MM. Post-transplant outcomes were excellent and support single center data on the role of ASCT in this rare disease. Figure 1 Figure 1. Disclosures Kansagra: Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Alynylam: Membership on an entity's Board of Directors or advisory committees; Cota Health: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees. Dispenzieri: Alnylam: Research Funding; Pfizer: Research Funding; Sorrento Therapeutics: Consultancy; Takeda: Research Funding; Oncopeptides: Consultancy; Janssen: Consultancy, Research Funding. Kumar: Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; BMS: Consultancy, Research Funding; Oncopeptides: Consultancy; Beigene: Consultancy; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Honoraria; Novartis: Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Carsgen: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Qazilbash: Bristol-Myers Squibb: Other: Advisory Board; NexImmune: Research Funding; Janssen: Research Funding; Biolline: Research Funding; Oncopeptides: Other: Advisory Board; Angiocrine: Research Funding; Amgen: Research Funding. Shah: GSK: Consultancy; Karyopharm: Consultancy; Oncopeptides: Consultancy; Indapta Therapeutics: Consultancy; Janssen: Research Funding; Nektar: Research Funding; Bluebird Bio: Research Funding; Teneobio: Research Funding; CareDx: Consultancy; BMS/Celgene: Research Funding; Sanofi: Consultancy; Sutro Biopharma: Research Funding; CSL Behring: Consultancy; Poseida: Research Funding; Precision Biosciences: Research Funding; Amgen: Consultancy; Kite: Consultancy. D'Souza: Sanofi, Takeda, Teneobio, CAELUM, Prothena: Research Funding; Imbrium, Pfizer, BMS: Membership on an entity's Board of Directors or advisory committees; Janssen, Prothena: Consultancy.

Abstract Background: There has been a steady improvement in the survival of patients with multiple myeloma (MM) due to better understanding of the pathophysiology, use of novel agents, and risk-adapted therapy. These improvements were largely observed in clinical trials and tertiary center populations and questions remain about the generalizability of these findings to patients in community settings. Here, we compared the experience of patients seen at Mayo Clinic, Rochester (MAYO) and those followed in the Surveillance, Epidemiology, and End Results Program (SEER), to gain a better understanding of current trends in survival. Methods: We studied all patients with MM diagnosed between 01/2004 and 12/2018 seen at MAYO and those followed in SEER (18 registry research data 2000-2018, 11/2020 submission). For comparison with SEER, MAYO patients who were alive at the end of SEER follow-up (12/31/2018) were censored. For the estimation of relative survival, patients alive at the end of 2019 were censored to align with the published United States general population rate tables. Overall survival (OS) estimates were calculated using the method described by Kaplan and Meier. Multivariable-adjusted proportional hazards regression models were used to assess the association between the 5-year interval of diagnosis and overall survival. Expected OS estimates were calculated based on United States general population rate tables from the Human Mortality Database using a conditional approach. Standardized mortality ratios (SMR) were calculated by dividing the number of observed deaths by the number of expected deaths in age- and sex-matched general United States population controls. Linear regression models were fit to test for trends in SMRs over time. Results: The median age at diagnosis was 3 years lower in patients seen at MAYO compared to patients followed in SEER. The proportion of patients 75 years and older at the time of diagnosis was higher in SEER (26.3%) compared to MAYO (15.3%). Median OS was 6.7 years (95% CI 6.3-7.1) for MAYO compared to 4.6 years (95% CI 4.5-4.7) in SEER (Figure 1). When stratifying OS by year of diagnosis (in 5-year-intervals: 2004-2008, 2009-2013, 2014-2018), improvements were seen in both patient populations over time, albeit to a greater extent in patients seen at MAYO (Figures 2 and 3). The results were consistent after adjusting for age and sex in both MAYO and SEER. There were improvements in OS across all three 5-year intervals and age groups in both patient populations. In MAYO, these improvements were most pronounced during the second 5-year interval for younger patients (&lt; 65 years) and more pronounced during the last 5-year interval for older patients (&gt; 65 years). In SEER, the improvements were more gradual across the three 5-year intervals, but it was noted that the relative improvements in younger patients were greater than in older patients during the last 5-year interval. Early mortality decreased over time in both patient populations: from 11% to 6% at MAYO and from 23% to 16% in SEER (Figure 4). To examine the observed improvements in the context of the survival trends of the general population, we stratified the SMRs by patient population, age at diagnosis, and year of diagnosis, and a lack of improvement in excess mortality was observed among older patients (&gt;75 years) in both populations over time (Figure 5). Three- and five-year overall survival estimates were higher in patients seen at MAYO compared to patients followed in SEER, but the survival advantage diminished with increasing follow-up time (Figure 6). On further sub-group analysis within MAYO patients, excess mortality was observed for all International staging system (ISS) stages and patients with high-risk (HR) cytogenetics. Stratifying the SMRs by age and risk group, decreases in excess mortality were most pronounced among older patients, particularly those with indolent disease (Figure 7). Conclusions: Survival outcomes in MM continued to improve in both patient populations. These improvements were more pronounced in MAYO compared to SEER, which may be partially explained by differences in access to specialized care. The most pronounced improvements were observed among younger patients and those with favorable disease characteristics. Future efforts need to focus on improving therapies for patients with unfavorable disease characteristics and on increasing access to specialized care in community settings. Figure 1 Figure 1. Disclosures Kapoor: Glaxo SmithKline: Research Funding; Takeda: Research Funding; Sanofi: Research Funding; Amgen: Research Funding; Sanofi: Consultancy; Pharmacyclics: Consultancy; Ichnos Sciences: Research Funding; BeiGene: Consultancy; Regeneron Pharmaceuticals: Research Funding; AbbVie: Research Funding; Karyopharm: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy. Dingli: Alexion: Consultancy; Apellis: Consultancy; Janssen: Consultancy; Novartis: Research Funding; GSK: Consultancy; Sanofi: Consultancy. Gertz: Ionis Pharmaceuticals: Other: Advisory Board; Aurora Biopharma: Other: Stock option; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy. Lin: Novartis: Consultancy; Celgene: Consultancy, Research Funding; Juno: Consultancy; Takeda: Research Funding; Gamida Cell: Consultancy; Vineti: Consultancy; Merck: Research Funding; Bluebird Bio: Consultancy, Research Funding; Legend: Consultancy; Sorrento: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding. Dispenzieri: Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding; Takeda: Research Funding; Oncopeptides: Consultancy; Alnylam: Research Funding; Pfizer: Research Funding. Kumar: Tenebio: Research Funding; Amgen: Consultancy, Research Funding; Oncopeptides: Consultancy; Bluebird Bio: Consultancy; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Novartis: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Beigene: Consultancy; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Antengene: Consultancy, Honoraria; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.

Abstract Background: trALL is an important secondary primary malignancy (SPM) that has recently been appreciated. While patients (pts) with MM have an 8%-17% risk of developing an SPM while on lenalidomide (R) maintenance following autologous stem cell transplant (ASCT), trALL has been rarely observed. Little is known about the characteristics of trALL in pts with MM compared to pts who had other malignancies prior to the development of trALL. We define tALL as any prior exposure to cytotoxic chemotherapy and/or radiation for another malignancy, and herein, we report a comparative analysis of characteristics and outcomes of pts with trALL with and without MM from the Mayo Clinic Cancer Center (MCCC). Methods: We performed a systematic search in the 3-site MCCC registry and included all pts diagnosed and received at least 1 cycle of ALL-directed therapy and/or underwent allogeneic transplantation (AlloHCT) for ALL between 2007-2020. All cases of trALL in this series are B-ALL. Comparisons of characteristics between trALL patients with and without MM were made using a Wilcoxon rank sum test (continuous variables) or Fisher's exact test (categorical variables). Time-to-event variables were compared using unadjusted Cox proportional hazards regression models. Results: 70 trALL pts (14 MM [20%], 56 non-MM [80%]) were identified during the study period. The median age at trALL diagnosis was 63.9 (range 47-71) for MM pts and 63.1 (range 18.2-84) for non-MM pts. Median follow-up from trALL diagnosis was 1.42 years (range 0.02-10.6 years). The most common prior non-MM malignancies among tALL pts were breast (28.6%), lymphoma (17.9%), myeloid (17.9%), and GU/GYN (14.3%). Amongst the 14 MM pts, 100% (n=10) had ISS-I disease, 8 (57%) had IgG K MM, 1 (n=10) had high risk cytogenetics, 8 (57.1%) received R-based induction , 4 (28.6%) received CyBorD induction, 4(28.6%) received VRD induction, 3 (21.4%) received RD induction. 10 (71.4%) pts were actively on R when they developed trALL, 8 (57.1%) pts received prior ASCT. The median time to develop trALL following ASCT for MM was 46.3 months (m), (95% CI 20.4-67.6), 12 (85.7%) pts received R maintenance with a median duration of 53m (95% CI 16.9-121). The median time to develop trALL after initiation of R maintenance was 61.2m (95% CI 16.9-123.4). The most common trALL induction regimen received was HyperCVAD which was used in 71.4% of MM pts and 51.8% of non-MM pts. In comparison to non-MM pts, MM patients had a significantly lower WBC at diagnosis (Median: 2.0 vs. 5.8, P=0.005),no t(9;22) BCR/ABL1 cytogenetics (0.0% vs. 35.7%, P=0.008), a higher frequency of hypodiploid/near-triploid (Ho-Tri) cytogenetics (42.9% vs. 12.5%, P=0.009), and a lower frequency of prior radiation therapy (7.1% vs. 44.6%, P=0.012). MM pts had a higher frequency of AlloHCT for trALL (71.4% vs. 42.9%, P=0.075) and were more commonly in complete response (CR) at transplant (100.0% vs. 70.8%, P=0.078). No trALL in MM pts were Ph-like ALL. There was a statistically significant difference in time to development of trALL between previous malignancy locations (P=0.018), with GU/GYN (Median: 9 years) having the longest time and myeloid (Median: 3 years) having the shortest time; MM was 6 years. In the overall pt cohort, 56 (80%) pts achieved a complete response after induction and 60% (n=25) were minimal residual disease (MRD)+ after induction. Pts with MM had a significantly lower likelihood of being MRD+ after induction (OR=0.09, P=0.015). Overall, 24.3% of pts relapsed after induction therapy for trALL; 39 (55.5%) died after trALL diagnosis including 43% (n=35) who died after AlloHCT. Although pts with MM tended to have better outcomes compared to non-MM trALL pts in terms of overall survival after trALL diagnosis (Figure 1A), survival after AlloHCT (Figure 1B), relapse rate after trALL diagnosis and non-relapse mortality after AlloHCT, none of these findings were statistically significant in this small cohort (Figure 1C). Conclusion: trALL is a unique SPM that can occur in pts with MM. It is associated with Ho-Tri cytogenetics and is BCR/ABL1 negative. The majority of MM pts that developed trALL had undergone prior ASCT and were on R maintenance when they developed trALL. Despite being more likely to have adverse cytogenetics features, MM-associated trALL has similar survival compared to non-MM-associated trALL which speaks to the poor survival outcomes of this SPM. Further research on trALL in MM pts is merited. Figure 1 Figure 1. Disclosures Litzow: Amgen: Research Funding; Pluristem: Research Funding; AbbVie: Research Funding; Actinium: Research Funding; Astellas: Research Funding; Omeros: Other: Advisory Board; Jazz: Other: Advisory Board; Biosight: Other: Data monitoring committee. Bergsagel: Janssen: Consultancy. Fonseca: Scientific Advisory Board: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Caris Life Sciences: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; Bayer: Consultancy; Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy; BMS: Consultancy; Mayo Clinic in Arizona: Current Employment; Juno: Consultancy; Kite: Consultancy; Aduro: Consultancy; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy; Novartis: Consultancy; Merck: Consultancy; Sanofi: Consultancy; Pharmacyclics: Consultancy; Janssen: Consultancy. Dispenzieri: Takeda: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Murthy: CRISPR Therapeutics: Research Funding. Ailawadhi: GSK: Consultancy, Research Funding; Sanofi: Consultancy; Pharmacyclics: Consultancy, Research Funding; Takeda: Consultancy; Medimmune: Research Funding; Xencor: Research Funding; Genentech: Consultancy; Janssen: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Cellectar: Research Funding; Beigene: Consultancy; BMS: Consultancy, Research Funding; AbbVie: Consultancy; Karyopharm: Consultancy; Ascentage: Research Funding. Foran: actinium: Research Funding; taiho: Honoraria; bms: Honoraria; servier: Honoraria; pfizer: Honoraria; novartis: Honoraria; OncLive: Honoraria; abbvie: Research Funding; boehringer ingelheim: Research Funding; takeda: Research Funding; trillium: Research Funding; aptose: Research Funding; revolution medicine: Honoraria; syros: Honoraria; sanofi aventis: Honoraria; certara: Honoraria; gamida: Honoraria; kura: Research Funding; h3bioscience: Research Funding; aprea: Research Funding; sellas: Research Funding; stemline: Research Funding.

Abstract Background: Systemic light chain (AL) amyloidosis is a clonal plasma cell disorder characterized by deposition of misfolded immunoglobulin light chain products in vital organs, causing their dysfunction. All therapies used to treat AL patients are adapted from multiple myeloma (MM) and customized to the typically frail AL population. Hence, it is important to identify novel therapeutic targets for these patients. MicroRNAs (miRNAs) are short, non-coding RNAs that regulate gene expression and have a role in cancer development and progression. MiRNAs can be purified from serum, plasma and bone marrow (BM) and may be used as biomarkers to distinguish between patients and healthy individuals. Moreover, miRNA-mRNA interactions may determine the molecular mechanism involved in AL pathogenesis and may suggest novel therapeutic approaches. To date, knowledge about circulating or BM miRNAs involved in AL amyloidosis is lacking. Aims: To decipher specific miRNA expression profiles in AL amyloidosis compared to MM patients and healthy controls (HC) and to examine how miRNAs are involved in AL pathogenesis. Methods: miRNA expression profile was determined using the nCounter assay (NanoString technologies). RNA-Seq data was downloaded from GEO database (GSE175384), and was used to detect potential miRNA-mRNA targets, and enriched biological pathways by the bioinformatics tool Ingunity Pathway Analysis (IPA). MiRNA and gene expression profiles were validated by qRT-PCR in 60 AL, 60 MM and 10 HC samples. The effect of aberrantly expressed miRNAs on potential molecular targets was analyzed in ALMC1 cells by transfecting the cells with miRNA mimic, following qRT-PCR, Western blot analysis and Annexin-PI staining. Results: BM and plasma miRNAs were differentially expressed in AL amyloidosis compared to MM or HC. MiRs-9a-5p, 181a-5p, 199a-3p, 130a-3p, 145-5p and 301a-3p were differentially expressed between AL and MM samples and may be used as biomarkers for distinguish AL amyloidosis from MM. Moreover, we found that the differentially expressed miRNAs and mRNA in AL patients regulates key signaling pathways related to cell cycle and anti-apoptosis mechanisms including cytokine signaling, oxidative phosphorylation (OXPHOS), NFkB signaling, activation of MAPK and PI3K/AKT pathways, which are all linked to cancer cell growth, proliferation and therapeutic resistance, and therefore may be used as a therapeutic targets. Specifically, our analysis showed that genes related to mitochondrial activity were upregulated in AL patients (Figure 1), particularly the anti-apoptotic BCL2 family genes (BCL2, MCL1, and BCL2L1). MCL1 and BCL2L1 are predicted targets of miR-181a-5p that was downregulated in BM and plasma samples of AL patients compared to MM patients, indicating a possible interaction between these molecules. MiR-9-5p, which was also found to be downregulated in AL BM and plasma samples compared to MM patients, is predicted to have an indirect effect on the BCL2 family members through CREB molecule (Figure 1). The biological significance of miR-9-5p and miR-181a-5p was evaluated, by transfecting ALMC1 cell line with miRNA mimics. Overexpression of these miRNAs led to downregulation of the BCL2 family anti-apoptotic genes and induced apoptosis by Annexin V staining. These findings might explain the biological mechanism by which AL patients respond to the BCL2 inhibitor, venetoclax, as recently reported (Sidiqi et al, BCJ, 2020). Conclusions: We provide insight into the molecular mechanisms mediated by miRNAs and the aberrant expression of oncogenic/tumor suppressor genes. The differential expression of miRNAs in AL amyloidosis may be used to understand disease pathogenesis and predict risk of progression to AL amyloidosis among patients with known plasma cell disorders. Additionally, signaling pathways involved in AL amyloidosis, mediated by miRNAs, may assist in tailoring more specific treatments. Figure 1 Figure 1. Disclosures Dispenzieri: Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Pfizer: Research Funding; Alnylam: Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding.

Abstract Introduction: Multiple gene expression profile assays have successfully prognosticated the overall survival (OS) outcomes of patients with Newly Diagnosed Multiple Myeloma (NDMM) and are now available for use in clinical practice. The genes included in these profiles encompass several aspects of cancer biology broadly such as cell-cycle biology, energy metabolism, migration, adhesion, immune evasion etc. Since altered energy metabolism is one of the hallmarks of all cancer cells, our goal was to take a deep-dive into specific genes associated with intracellular central carbon energy metabolism (CCEM) pathways such as oxidative phosphorylation (OxPhos) as well as glycolysis and lactate fermentation (Glyco-Lac) in MM cells to determine their impact on the pathogenesis and prognosis of MM patients. Methods: Gene expression level data via RNA sequencing from the COMMPASS dataset (made available by the Multiple Myeloma Research Foundation (MMRF)) was utilized. The expression levels of all genes associated with the OxPhos (N = 118) and Glyco-Lac (N = 34) pathways were evaluated in CD138+ cells derived from patients with NDMM. Each gene was dichotomized into low and high expression groups -based on their expression level above and below the median fragments per kilobase of transcript per million (FPKM), respectively. The prognostic significance of dichotomizing each of the 152 genes in this NDMM cohort was evaluated by levels of their hazard ratios (HRs) for OS determined by the log-rank method. Genes from the OxPhos and Glyco-Lac pathways were selected based on their significant negative impact on OS, wide representation of their biologic activity throughout the pathway and high independence from each other. This resulted in the selection of 12 distinct genes of interest. A scoring system consisting of assigning a point for every gene where their FPKM was above the median yielded a minimum of 0 and a maximum of 12 for the set of genes in the OxPhos and Glyco-Lac pathways to create an energy metabolism score (EMS). Patients were then categorized into "low" (0-8) or "high" (9-12) EMS groups. In addition, patients were designated as having high-risk cytogenetics if they had any of the following: t(4;14), t(14;16), t(14;20), del17p, and Amp 1q. Survival analysis was performed using the Kaplan-Meier survival analysis and compared via the log-rank method. Finally, the distribution of the EMS score among patients within a spectrum of plasma cell disorders such as, monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma and MM as well as normal plasma cells was assessed using a previously published transcriptome dataset (GSE6477). Results: A total of 766 patients were included in this study. The selected genes included in this scoring system and their biological relevance in the OxPhos and Glyco-Lac pathways are depicted in Figure A. The distribution of low and high EMS groups across ISS stage and cytogenetic risk are depicted in Figure B and C respectively. The median OS (mOS) and PFS for the high (N = 248) vs. low (N = 518) EMS groups was 55 vs. 94 months (HR: 2.41; (95%CI: 1.85-3.14); P &lt;0.0001) (Figure D) and 24 vs. 42 months (HR: 1.74; (95%CI: 1.42-2.13); P &lt;0.0001). Patients with ISS 2 stage disease categorized as having a high or low EMS score had a similar mOS to patients with ISS 3 and ISS 1 stage disease respectively (Figure E). Similarly, the mOS was similar among patients with standard risk and high-risk cytogenetics when categorized by low and high EMS (Figure F). Finally, the relative expression of most of the 12 select CCEM genes (Figure G) and the probability of a high EMS score increased among patients along the spectrum of plasma cell disorders (Normal plasma cell -&gt; MGUS -&gt; SMM -&gt; MM) (Figure H). Conclusions: The expression levels of specific genes associated with the activity of intracellular CCEM pathways such as glycolysis, lactate fermentation and oxidative phosphorylation in plasma cells provides evidence for the impact of cellular energy metabolism on the pathogenesis and survival outcomes of MM. This provides an opportunity for developing future studies aimed at understanding the energy metabolism pathways of plasma cell malignancies in greater detail so as to exploit them for diagnostic and therapeutic purposes in MM. Figure 1 Figure 1. Disclosures Kumar: Novartis: Research Funding; Amgen: Consultancy, Research Funding; Beigene: Consultancy; Carsgen: Research Funding; Merck: Research Funding; Antengene: Consultancy, Honoraria; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Roche-Genentech: Consultancy, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Dispenzieri: Alnylam: Research Funding; Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding. Kapoor: AbbVie: Research Funding; Takeda: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding. Dingli: Apellis: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; GSK: Consultancy; Novartis: Research Funding; Alexion: Consultancy. Lin: Gamida Cell: Consultancy; Takeda: Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Juno: Consultancy; Novartis: Consultancy; Legend: Consultancy; Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Sorrento: Consultancy; Merck: Research Funding; Vineti: Consultancy. Gertz: Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Aurora Biopharma: Other: Stock option; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy. Fonseca: Aduro: Consultancy; Kite: Consultancy; Juno: Consultancy; Merck: Consultancy; Takeda: Consultancy; Caris Life Sciences: Membership on an entity's Board of Directors or advisory committees; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; AbbVie: Consultancy; Scientific Advisory Board: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; Mayo Clinic in Arizona: Current Employment; Amgen: Consultancy; BMS: Consultancy; Celgene: Consultancy; Bayer: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; GSK: Consultancy.

Abstract Background: MASS-FIX is a screening method for serum and urine monoclonal proteins in multiple myeloma and related plasma cell disorders, which uses immunoglobulin enrichment coupled with matrix-assisted laser desorption ionization time-of-flight mass-spectrometry (MALDI-TOF). In addition to superior sensitivity over conventional gel-based techniques, MASS-FIX can distinguish therapeutic monoclonal antibodies (MoAb) from patient's M protein. As the utilization of therapeutic MoAbs increases, it is essential to understand the persistence pattern of these therapeutic antibodies in the serum. We designed this study to evaluate the duration of daratumumab detection by MASS-FIX in the serum of treated patients. Methods: We used a prospectively maintained database at Mayo clinic to identify patients with multiple myeloma and related plasma cell disorders who were treated with a daratumumab-containing regimen anytime during their disease course and had serial MASS-FIX data available after discontinuation of daratumumab. A univariate analysis was performed to assess for factors that may impact the clearance of daratumumab. Results: We included 125 patients with plasma cell disorders who received daratumumab as first or subsequent line of treatment between March 15 th, 2016, and March 4 th, 2020. The median age was 60.2 years and 57% were male. The most common diagnoses were multiple myeloma (70%) and light chain amyloidosis (18%). Daratumumab-based treatments were initiated after a median of 28.8 (IQR: 6.4-76.3) months from initial diagnosis. The most common regimen used was daratumumab, bortezomib and dexamethasone (23%); 26% underwent transplant after daratumumab-based induction. The median duration of treatment with a daratumumab-based regimen was 208 (IQR: 99-479) days. The median follow-up from the time of daratumumab discontinuation was 457 (95% CI: 346-NR) days. By last follow up, daratumumab was not detected by MASS-FIX in 93 (74%) patients but remained detectable in 32 (26%) patients. The median time from daratumumab discontinuation to disappearance of daratumumab by MASS-FIX was 160 (IQR: 107-233) days. On univariate analysis, the presence of ≥0.5 grams of urine protein was associated with earlier disappearance of daratumumab on MASS-FIX [risk ratio (RR): 2.0, P=0.02). The median time from daratumumab discontinuation to disappearance of daratumumab on MASS-FIX was 116 (95%CI: 76-160) days in patients with urine protein ≥0.5 grams and 203 (95%CI: 162-216) days in patients with urine protein &lt;0.5 grams (P=0.02). There was no association between the time to disappearance of daratumumab by MASS-FIX and old age ≥70 (RR: 0.9, P=0.81], male gender (RR: 0.9, P=0.60), eGFR &lt;60 (RR: 1.0, P=0.98), daratumumab schedule (every 1/2 weeks vs &gt;2weeks) (RR: 1.0, P=0.97), treatment duration (&lt;200 days vs ≥200 days) ( RR: 1.0, P=0.95), or transplantation status (RR: 1.0, P=0.98). Conclusion: The therapeutic monoclonal antibody daratumumab remains detectable in the serum of treated patients by MASS-FIX for several months after discontinuation and the duration varies between individual patients. This data has implications for diagnostic and monitoring testing and may provide guidance for reuse of daratumumab in clinical trials and practice. Proteinuria is associated with earlier disappearance of daratumumab by MASS-FIX and may have implications in patients with amyloidosis and monoclonal immunoglobulin deposition disease (MIDD). Further studies are needed to identify additional factors associated with the timing of disappearance. Disclosures Murray: Mayo Clinic: Other: Has received patents for the Mass-Fix technology which has been licensed to the Binding Site with potential royalties.. Dispenzieri: Takeda: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Kapoor: Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Gertz: Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Aurora Biopharma: Other: Stock option; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring. Dingli: Alexion: Consultancy; Novartis: Research Funding; Apellis: Consultancy; Janssen: Consultancy; Sanofi: Consultancy; GSK: Consultancy. Kumar: Antengene: Consultancy, Honoraria; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Merck: Research Funding; Roche-Genentech: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Oncopeptides: Consultancy; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Carsgen: Research Funding; Tenebio: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.

Abstract INTRODUCTION POEMS syndrome is a paraneoplastic disorder that results in multi-organ disease, and Vascular endothelial growth factor (VEGF) is associated with disease activity. There is evidence that the cytokine Interleukin- 6 (IL-6) stimulates VEGF production in several cancer cell lines. It has also been suggested that patients with POEMS syndrome experience symptoms improvement when IL-6 levels are low. Our study aims to understand the role of IL-6 and whether it is a contributor to disease activity in POEMS syndrome. METHODS We conducted a retrospective study of patients (pts) seen at Mayo Clinic within 1 year of diagnosis for POEMS syndrome with an IL-6 level within 3 months of diagnosis between 01/01/2011-05/31/2021 were included. Our database comprised 358 pts,7 were excluded because did not have official diagnosis of POEMS syndrome. Two hundred and ninety-nine pts did not have IL-6 testing within 90 days of diagnosis and were excluded. Clinical data was abstracted from our electronic medical record. Descriptive statistics were used for IL-6 levels. The majority of IL-6 laboratory testing for pts utilized the same reference range. A minority of pts had alternate reference ranges; thus, all IL-6 values and reference ranges were fold-corrected to have a unified reference to determine elevation in IL-6. High IL-6 was considered any value above the normal range, also analyzed pts in quartiles and deciles. Hematologic, VEGF and PET response criteria were utilized to group pts into responders or non-responders. Time to progression (TTP) and overall survival (OS) was calculated using the Kaplan Meier method. Differences between curves were by log rank. Statistical analysis was conducted via JMP software package (SAS, Cary, NC, USA). Univariate analysis was done to determine the prognostic value of IL-6. Statistical significance is considered with p-values &lt;0.05. RESULTS 52 patients from among 352 met criteria and were included for analysis. Twenty-one patients (40%) had elevated IL-6 levels (IQR 5.67, 22.6) at the time of diagnosis. The fold elevation about normal was typically not very high, with a median of 3.1-fold elevation (IQR 1.3, 4.4; and range 1.0, 8.3). The percentage of males in the high IL-6 versus the normal Il-6 group were 90% versus 65%, p=0.03. Compared to normal IL-6, those with elevated IL-6 values had more instances of hepatomegaly (43% vs 16%, p=0.03), ascites (28% vs 6%, p=0 .04), abnormal DLCO (26% vs 3%, p=0.03), mixed bone lesions (57% vs 29%, p= 0.04), and lower serum albumin (range 2.3-3.5 vs 2.5-4.5 g/dL, p=0.0008).There was a trend for lower VEGF values among the high IL-6 group, but this did not meet statistical significance (median 250 vs 438 pg/mL). There was no significant difference in the time to progression between pts with high versus normal IL-6 levels (HR 1.36; p=0.456). Overall survival was significantly longer in pts with normal IL-6 compared to pts with high IL-6 levels (Median OS 67.4 vs 47.8 months, p=0.02). Forty-two pts were evaluated for VEGF response after treatment; there was a significant improvement in time to progression (85.5 vs 14.9 months, p=0.03) in pts who were VEGF responders. Among pts evaluable for a hematologic response (n=15), time to progression in pts with baseline high IL6 was longer in hematologic responders compared to non-responders (p=0.02). Conclusion Although OS was longer for pts with normal IL-6, elevated IL-6 at the time of diagnosis does not prevent pts from achieving disease remission. The study demonstrates that response to treatment rather than interleukin-6 levels in pts with POEMS syndrome is more prognostic. This study is an important initial step into understanding the utility of IL-6 in POEMS syndrome. Figure 1 Figure 1. Disclosures Gertz: Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Aurora Biopharma: Other: Stock option; Ionis Pharmaceuticals: Other: Advisory Board; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria. Kumar: Oncopeptides: Consultancy; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Merck: Research Funding; Antengene: Consultancy, Honoraria; Tenebio: Research Funding; Novartis: Research Funding; Roche-Genentech: Consultancy, Research Funding; Carsgen: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Dingli: GSK: Consultancy; Novartis: Research Funding; Janssen: Consultancy; Sanofi: Consultancy; Apellis: Consultancy; Alexion: Consultancy. Lin: Janssen: Consultancy, Research Funding; Merck: Research Funding; Novartis: Consultancy; Legend: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Vineti: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding; Sorrento: Consultancy; Gamida Cell: Consultancy; Takeda: Research Funding. Kapoor: Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Dispenzieri: Pfizer: Research Funding; Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Alnylam: Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding.

Abstract Introduction: Smoldering multiple myeloma (SMM) prognostication models routinely used in clinical practice were developed for use at diagnosis. However, retrospective studies have shown that in SMM patients the risk of progression to multiple myeloma (MM) decreases over time. Therefore, this study assessed whether the Mayo 2018 and IMWG 2020 scores could be used dynamically to risk stratify patients post-diagnosis, and whether they could identify SMM patients with evolving disease. Methods: We retrospectively studied 704 SMM patients diagnosed between January 2000 to January 2020. Patients with a baseline FLCr ≥100 and involved FLC ≥10 mg/dL or baseline bone marrow plasma cells ≥60% were excluded. We collected serial laboratory data and available pathology data and re-applied the Mayo 2018 and IMWG 2020 SMM risk stratification models at annual landmark timepoints up to 5 years post SMM diagnosis. Survival analyses were performed using the Kaplan-Meier method. Time to progression (TTP) was defined as time from diagnosis or landmark timepoint to treatment initiation for MM or systemic AL amyloidosis. Cox proportional hazards models were used to estimate hazard ratios. A two-sided p-value &lt;0.05 was considered statistically significant. Results: At SMM diagnosis, 271 (38%) patients were low risk, 228 (32%) were intermediate risk, and 205 (29%) were high risk per the Mayo 2018 score. Applying the IMWG 2020 score at diagnosis, 90 (34%) of patients were low risk, 111 (42%) were low-intermediate risk, 54 (21%) were intermediate risk, and 9 (3%) were high risk. The Mayo 2018 and IMWG 2020 risk scores was re-assessed annually post-diagnosis in patients without progression (respective sample sizes: n=430 and n=197 at year 1 landmark, n=326 and n=143 at year 2 landmark, n=260 and n=106 at year 3 landmark, n=203 and n=73 patients at year 4 landmark). The Mayo 2018 and IMWG 2020 models reliably stratified patients based on progression risk post diagnosis (as shown in Figure 1 and Figure 2, respectively). As shown in Figure 1, if only diagnostic values were used in risk categorization with the Mayo 2018 model, the TTP between risk categories became less distinct over time. However, when follow-up laboratory values were used to re-stratify patients, the TTP between risk categories was more consistent over time. The respective 2-year progression risk in Mayo 2018 high-risk versus IMWG 2020 intermediate-high risk patients was 51% versus 62% at the 1-year landmark, 60% versus 65% at the 2-year landmark, 47% versus 62% at the 3-year landmark, and 47% versus 45% at the 4-year landmark. To assess the prognostic significance of an increase in SMM risk category, we stratified patients based on whether the SMM risk category at follow-up had increased versus was stable or decreased compared to the baseline SMM risk stratification. We found that patients evolving to a risk category during follow up consistently had an increased risk of progression compared to patients with a stable/decreased risk categorization using both the Mayo 2018 (HR 3.34, 95% CI 2.04-5.48, p&lt;0.001 at 2-year landmark; HR 3.41, 95% CI 2.05-5.68, p&lt;0.001 at 3-year landmark; HR 2.69, 95% CI 1.34-5.38, p=0.005 at 4-year landmark) and IMWG 2020 (HR 2.32, 95% CI 1.42-3.77, p&lt;0.001 at 1-year landmark; HR 3.10, 95% CI 1.69-5.70, p&lt;0.001 at 2-year landmark; HR 2.50, 95% CI 1.30-4.78, p=0.004 at 3-year landmark; HR 2.26, 95% CI 0.91-5.60, p=0.072 at 4-year landmark) risk models. However, patients categorized as Mayo 2018 high-risk at follow-up had a similar risk of progression regardless of whether the baseline risk categorization was low-intermediate versus high-risk (HR 0.87, 95% CI 0.51-1.48, p=0.606 at 2-year landmark; HR 1.01, 95% CI 0.59-1.73, p=0.972 at 3-year landmark; HR 0.75, 95% CI 0.34-1.65, p=0.467 at 4-year landmark). Conclusions: Our findings support the use of the Mayo 2018 and IMWG 2020 scores post-diagnosis. We showed that patients migrating to a higher risk category have an increased risk of progression. This suggests that if patients evolve to a high-risk score during follow-up, they should be considered for an early intervention treatment approach. Figure 1 Figure 1. Disclosures Kapoor: Sanofi: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Karyopharm: Consultancy; Cellectar: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Dispenzieri: Pfizer: Research Funding; Janssen: Consultancy, Research Funding; Alnylam: Research Funding; Takeda: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy. Gertz: Aurora Biopharma: Other: Stock option; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Ionis Pharmaceuticals: Other: Advisory Board. Dingli: Janssen: Consultancy; Sanofi: Consultancy; Apellis: Consultancy; Novartis: Research Funding; Alexion: Consultancy; GSK: Consultancy. Kumar: Tenebio: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Novartis: Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Bluebird Bio: Consultancy; Roche-Genentech: Consultancy, Research Funding; Merck: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Antengene: Consultancy, Honoraria; Oncopeptides: Consultancy; Beigene: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.