Reeder, Craig B.

Abstract Purpose: IgM monoclonal gammopathy of undetermined significance (MGUS) and Waldenström macroglobulinemia (WM) represent a disease spectrum with highly varied therapeutic management, ranging from observation to chemoimmunotherapy. The current classification relies solely on clinical features and does not explain the heterogeneity that exists within each of these conditions. Further investigation is warranted to shed light on the biology that may account for the clinical differences. Experimental Design: We used bone marrow (BM) clonal CD19+ and/or CD138+ sorted cells, matched BM supernatant, and peripheral blood serum from 32 patients (7 MGUS, 25 WM) to perform the first multi-omics approach including whole-exome sequencing, RNA sequencing, proteomics, metabolomics, and mass cytometry. Results: We identified three clusters with distinct pathway activation, immune content, metabolomic, and clinical features. Cluster 1 included only patients with WM and was characterized by transcriptional silencing of genes involved in cell cycle and immune response, enrichment of mitochondrial metabolism, infiltration of senescent T effector memory cells, and aggressive clinical behavior. Genetic/structural alterations of TNFAIP3 were distinct events of this cluster. Cluster 2 comprised both MGUS and WM patients with upregulation of inflammatory response, senescence and glycolysis signatures, increased activated T follicular helper and T regulatory cells, and indolent clinical behavior. Cluster 3 also included both MGUS and WM patients and exhibited intermediate features, including proliferative and inflammatory signaling, as well as glycolysis and mitochondrial metabolism. Conclusions: We have identified three distinct molecular clusters, suggesting a potential biologic classification that may have therapeutic implications.

Abstract Minimal residual disease (MRD) assays allow response assessment in patients with multiple myeloma (MM), and negativity is associated with improved survival outcomes. The role of highly sensitive next generation sequencing (NGS) MRD in combination with functional imaging remains to be validated. We performed a retrospective analysis on MM patients who underwent frontline autologous stem cell transplant (ASCT). Patients were evaluated at day 100 post-ASCT with NGS MRD and positron emission tomography (PET-CT). Patients with ≥ 2 MRD measurements were included in a secondary analysis for sequential measurements. 186 patients were included in the analysis. At day 100, 45 (24.2%) patients achieved MRD negativity at a sensitivity threshold of 10− 6. MRD negativity was the most predictive factor for longer time to next treatment (TTNT). Negativity rates did not differ according to MM subtype, R-ISS Stage nor cytogenetic risk. PET-CT and MRD positivity had poor agreement. Patients with sustained MRD negativity had longer TTNT, regardless of baseline risk characteristics. Our results show that the “real world” ability to measure deeper and sustainable responses distinguishes a subpopulation of patients with better outcomes. Achieving MRD negativity was the strongest prognostic marker and could help guide therapy-related decisions and serve as a response marker for clinical trials.

LBA7564 Background: Patients with r/r B-NHL have a dismal prognosis. DIAL (Dual Immunomodulation in Aggressive Lymphoma) was a multi-center randomized phase II study testing the efficacy of nivolumab (PD-1 inhibitor) plus varlilumab (CD27 agonist) in this population. Methods: Patients were randomized (1:1) to nivolumab (240 mg IV every 2 weeks for 4 months, 480 mg IV monthly thereafter; group 1) alone or combined with varlilumab (3 mg/kg IV monthly; group 2). Cross-over (group 1 to 2) was allowed for progression. Primary endpoint was overall response (ORR) per LYRIC criteria. A sample size of 48 patients per arm would provide 80% power to detect increase in ORR from 25% to 45% using a one-sided test (p = 0.15). Pre-specified interim analysis occurred after half of the patients completed first radiologic assessment. Secondary endpoints included overall survival (OS), progression-free survival (PFS), and adverse events (AEs). Exploratory endpoints included tumor genomic assessment and immune profiling of blood and tumor. Results: 53 patients were enrolled (27 in group 1; 26 in group 2). Interim analysis included 24 patients from each arm. Mean age was 65.2 years, 34 (70.8%) were male, and 36 (75%) received prior CAR-T cell therapy. Baseline characteristics were balanced between arms. Grade ≥ 3 AEs were observed in 8 (33.3%) and 7 (30.4%) of patients in groups 1 and 2, respectively. Common AEs (> 5%) of any grade included fatigue, lymphopenia, diarrhea, rash. There were no treatment-associated deaths. Toxicity profile was similar between arms. Table summarizes efficacy outcomes. ORR was achieved in 6 patients (12.5%), not statistically different between arms; 4 responses were complete. Seven patients crossed over (1 responded after crossing). Median OS (8.6 vs 7.3 months; p = 0.39) and PFS (2.7 vs 1.4 months; p = 0.06) were similar between arms. Subgroup analysis of patients with prior CAR-T cell therapy showed similar ORR (5/36; 14%), not statistically different between arms. Correlative analysis results will be presented at conference. The trial met futility criterion on interim analysis and enrollment ceased based on pre-specified stopping rule. Conclusions: Dual immunomodulatory therapy did not enhance anti-tumor activity in patients with aggressive B-NHL compared to nivolumab alone. Response rates were low and consistent with previous data using PD-1 inhibitors in this population. Prior therapy with CAR-T cell does not seem to sensitize patients to PD-1 blockade. Toxicity profile was acceptable and dual therapy did not increase the rate of AEs. Clinical trial information: NCT03038672. [Table: see text]

e19562 Background: Considerable healthcare resource utilization and financial burden have been associated with the treatment of Waldenstrom Macroglobulinemia (WM); however, the impact of health insurance status on patient outcomes has not been explored. We aimed to assess the insurance-based outcome relationship in WM using the National Cancer Database (NCDB). Methods: We analyzed patient-level data obtained from the NCDB, a database representing more than 70% of newly diagnosed cancer cases nationwide. All newly diagnosed WM cases (n = 8540) between 2004 to 2017 were identified. Only patients who underwent treatment were included. Insurance status was recorded by assessing the primary payer at the time of diagnosis. Due to Medicare eligibility criteria, age-based (< 65 and ≥65 years) stratified analysis was conducted. Cox proportional hazards model was utilized to analyze survival. Time-to-event analysis was conducted based on date-of-diagnosis using the Kaplan-Meier method and log-rank test. Results: Analysis was conducted on 3878 patients after meeting inclusion criteria, with a median follow-up time of 54.6 months. Among patients < 65 years (n = 1249; median age: 58 years; male: 62.4%), those with non-private insurance had inferior survival on multivariate analysis (Table) after adjusting for patient demographics, comorbidities, income, education, treatment center characteristics, and treatment start time. Significant overall survival (OS) differences were seen in those < 65 years (log-rank p < 0.001), with 5-year OS highest among patients with private insurance 91.2%, compared to Medicaid 79.8%, uninsured 77.4%, and Medicare 70.2%. In patients < 65 years, compared to private insurance, uninsured patients were more likely to be of Black race, reside in lower income areas, and be treated at non-academic centers (all p < 0.05). Both Medicaid and Medicare patients < 65 years were more likely to have a higher Charlson-Deyo comorbidity index (> 1) and live in areas of lower educational attainment and household income compared to private insurance (all p < 0.05). In patients ≥65 years (n = 2629; median age: 75 years; 60.6% males), no insurance-based OS (log-rank p = 0.096) differences were seen. Conclusions: Based on our study, significant insurance-based disparities exist in WM, where patients < 65 years old who are uninsured, or non-privately insured are at a higher risk of mortality. While the root cause of these differences is not fully elucidated, efforts should focus on ensuring that all patients have equal access to care regardless of primary payer status.[Table: see text]

Abstract Background: Treatment for multiple myeloma (MM) patients refractory to proteasome inhibitors (PIs), immunomodulatory agents (IMiDs), and monoclonal antibodies remains an unmet need. Belantamab mafodotin is a first in class antibody drug conjugates (ADCs) in MM utilizing a humanized monoclonal antibody targeting B cell maturation antigen (BCMA) conjugated to a microtubule-disrupting monomethyl auristatin F. The efficacy of belantamab in relapsed refractory MM (RRMM) patients has been reported in several randomized clinical trials. However, clinical trials have restricted patients' eligibilty. We report the "real world" efficacy and safety of belanatmab in patients treated at all three Mayo Clinic sites. Methods: We retrospectively reviewed all consecutive MM patients that received at least one dose of belantamab outside a clinical trial. The primary endpoints were PFS and OS, and the secondary endpoints included overall response rates (ORR) and safety. Results: Thirty-seven RRMM patients were treated with belantamab between September 2020 and June 2021. The median age at diagnosis was 61 (range 37-83) and 64% were male. The median age at belantamab administration was 67 (IQR 59-74) and 14 patients (38%) were 70 years or older. Fifteen of 34 patients (44%) had high-risk FISH and 13 patients of 33 (39%) had ISS 3. Two patients had a creatinine of &gt;2.5 mg/dL, and one patient was on dialysis. All three received full dose belantmab (2.5 mg/kg). The median time from diagnosis to belantamab initiation was 7 years (IQR 4-11), and the median prior lines of therapy was 8 (IQR 7-11). Twenty-seven patients (73%) underwent an autologous stem cell transplantation prior to belantamab therapy, and all patients were penta refractory (IMiD, PI, and anti CD38). Seven patients (19%) received CAR-T therapy prior to belantamab. The median number of belantamab doses administered was 3 (range 1-6). Thirty-one (84%) received belantamab monotherapy and 6 patients (16%) received belantamab in combination [pomalidomide (n=3), cyclophosphamide (n=2), or thalidomide (n=1)]. The overall response (ORR) rate to belantamab was 33% (out of 36 evaluable patients). Two patients (6%) achieved complete response (CR), 3 patients (8%) achieved very good partial response (VGPR), and 7 patients (19%) achieved partial response (PR). At data cutoff 20 patients (54%) are alive. Seventeen patients died of MM complications. The median follow-up was 6 months (IQR 3.5-7). The median PFS and OS for the whole cohort was 2 months (95% CI 1-3) and 7 months (95% CI 3--NR), respectively. Two patients died within the first cycle of belantamab (due to PD), and overall, 12 died within 100 days of belantamab therapy, all due to disease progression. Eleven patients (30%) were hospitalized during belantamab therapy. The reasons for hospitalization were related to MM in 4 patients (one patient with malignant ascites, one with hypercalcemia, 2 patients for pain management). Three patients were hospitalized due to thrombocytopenia (related to disease), and one due to an infusion-related reaction (IRR). Other reasons for hospitalization were infection (soft tissue abscess, n=1), proctitis (n=1) and tumor lysis (n=1). Keratopathy developed in 16 patients (43%). Keratopathy was grade 1 in 6 patients, grade 2 in 7 patients, and grade 3 in 3 patients. Only one patient had corneal erosions and 6 patients reported decreased visual acuity, (1 grade 3 keratopathy, 4 had grade 2 keratopathy, and 1 had grade 1 keratopathy). Two patients had IRR. Two patients reported gaining 3.5 kg each after therapy with belantamab was discontinued. Conclusions: The response rates are similar to those reported in randomized clinical trials. The role of belantamab in the era of other BCMA directed therapy (CAR-T, BiTEs) remains unclear. Disclosures Dispenzieri: Janssen: Consultancy, Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Alnylam: Research Funding; Takeda: Research Funding. Kumar: Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Oncopeptides: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Honoraria; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Bluebird Bio: Consultancy; Roche-Genentech: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Dingli: Novartis: Research Funding; GSK: Consultancy; Janssen: Consultancy; Sanofi: Consultancy; Alexion: Consultancy; Apellis: Consultancy. Kapoor: Cellectar: Consultancy; BeiGene: Consultancy; Sanofi: Consultancy; Ichnos Sciences: Research Funding; Karyopharm: Consultancy; Amgen: Research Funding; Pharmacyclics: Consultancy; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Gertz: Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; 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; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Aurora Biopharma: Other: Stock option.