Ho, Matthew

The treatment landscape of multiple myeloma (MM) has evolved considerably with the FDA-approval of at least 15 drugs over the past two decades. Together with the use of autologous stem cell transplantation, these novel therapies have resulted in significant survival benefit for patients with MM. In particular, our improved understanding of the BM and immune microenvironment has led to the development of highly effective immunotherapies that have demonstrated unprecedented response rates even in the multiple refractory disease setting. However, MM remains challenging to treat especially in a high-risk setting. A key mediator of therapeutic resistance in MM is the bone marrow (BM) microenvironment; a deeper understanding is necessary to facilitate the development of therapies that target MM in the context of the BM milieu to elicit deeper and more durable responses with the ultimate goal of long-term control or a cure of MM. In this review, we discuss our current understanding of the role the BM microenvironment plays in MM pathogenesis, with a focus on its immunosuppressive nature. We also review FDA-approved immunotherapies currently in clinical use and highlight promising immunotherapeutic approaches on the horizon.

AbstractPatients with multiple myeloma (MM) have a lower efficacy from COVID‐19 vaccination and a high rate of mortality from COVID‐19 in hospitalized patients. However, the overall rate and severity of COVID‐19 infection in all settings (including non‐hospitalized patients) and the independent impact of plasma cell‐directed therapies on outcomes needs further study. We reviewed the medical records of 9225 patients with MM or AL amyloidosis (AL) seen at Mayo Clinic Rochester, Arizona, and Florida between 12/01/2019 and 8/31/2021 and identified 187 patients with a COVID‐19 infection (n = 174 MM, n = 13 AL). The infection rate in our cohort was relatively low at 2% but one‐fourth of the COVID‐19 infections were severe. Nineteen (10%) patients required intensive care unit (ICU) admission and 5 (3%) patients required mechanical ventilation. The mortality rate among hospitalized patients with COVID‐19 was 22% (16/72 patients). Among patients that were fully vaccinated at the time of infection (n = 12), two (17%) developed severe COVID‐19 infection, without any COVID‐related death. On multivariable analysis, treatment with CD38 antibody within 6 months of COVID‐19 infection [Risk ratio (RR) 3.6 (95% CI: 1.2, 10.5), p = .02], cardiac [RR 4.1 (95% CI: 1.3, 12.4), p = .014] or pulmonary comorbidities [RR 3.6 (95% CI 1.1, 11.6); p = .029] were independent predictors for ICU admission. Cardiac comorbidity [RR 2.6 (95% CI: 1.1, 6.5), p = .038] was an independent predictor of mortality whereas MM/AL in remission was associated with lower mortality [RR 0.4 (95% CI: 0.2–0.8); p = .008].

Two Letters to Blood address the risks of COVID-19 in populations with precursors of hematological disease. In the first article, Miller and colleagues report on whether clonal hematopoiesis of intermediate potential (CHIP) is associated with adverse outcomes with COVID-19, finding no association between CHIP and 28-day mortality while providing data indirectly linking IL-6 signaling and patient outcomes. In the second article, Ho and colleagues investigate the outcomes of patients with monoclonal gammopathy of undetermined significance (MGUS) with COVID-19, reporting that one-fourth had a severe infection and that on multivariable analysis, adverse outcomes are more likely if immunoparesis is present.

Abstract Background: Patients with multiple myeloma (MM) that are refractory to a proteasome inhibitors (PI), immunomodulatory drug (IMiDs) and CD38/SLAMF7 directed monoclonal antibodies are commonly referred to as triple class refractory (TCR). This is an increasingly common clinical problem and here we present the outcomes, prognostic markers and response to therapy for patients with TCR disease. Methods: Consecutive patients with MM diagnosed between 01/01/2013 and 12/31/2018 and seen at Mayo Clinic, Rochester, MN were included in this study after institutional review board approval. Refractoriness to therapy was defined as progression or non-responsiveness (failure to achieve at least a minimal response) to therapy within 60 days of discontinuation of therapy, based on the International Myeloma Workshop Consensus definition. Patients meeting the definition for refractory disease for at least 1 PI (bortezomib, carfilzomib or ixazomib), 1 IMiD (lenalidomide, pomalidomide or thalidomide) and 1 monoclonal antibody (daratumumab, isatuximab or elotuzumab) were considered to have TCR disease and included in the study population. The first date when patients satisfied the above-mentioned criteria for TCR was used to calculate the follow-up, progression free survival (PFS) and OS for TCR disease. The mSMART 3.0 (www.msmart.org) classification was used to characterize high-risk and standard-risk cytogenetics features in interphase fluorescence in situ hybridization (FISH). The currently prevalent international myeloma working group (IMWG) criteria were used for response assessment. The Kaplan-Meier method was used for estimation of time-to-event endpoints. Reverse censoring was used for estimation of follow-up time. Cox regression was used for multivariate analyses. Wilcoxon test was used for comparison of continuous variables and Chi square test or Fisher's exact test were used to compare categorical variables, respectively Results: In this retrospective study, 249 consecutive patients with TCR status were identified. The median follow-up from diagnosis of MM till date of last follow-up was 6.8 years (95% CI: 6.3-7.3 years) and 1.9 years (95% CI: 1.6-2.4) from TCR MM to last follow-up. The median age at diagnosis of MM was 61 years (range 31-89) and at TCR was 65 years (range 32-93). The median number of lines of therapy for the entire cohort were 8 (range 1-17); the patients were exposed to a median of 5 (range 1-12) lines of therapy prior to TCR status. Baseline characteristics for the cohort are depicted in Table 1. The median time to development of triple refractory disease was 2.9 years (95% CI: 2.6-3.2 years) from diagnosis of MM. The time to TCR disease was shorter for high-risk cytogenetics at 2.3 years (95% CI: 2-2.7) compared to 3.4 years (95% CI: 3.1-4.1) with a hazard ratio (HR) of 1.8 (95% CI: 1.4-2.4) p<0.0001], Figure 1A. The median overall survival (OS) from TCR was 1.01 (95% CI: 0.9-1.3) years. High-risk cytogenetics at diagnosis of MM were associated with an inferior OS from TCR disease even after adjustment for age, and ISS stage [median 1.05 years (95% CI: 0.8-1.5) for high-risk vs 1.3 years (95% CI: 0.9-2.9) for standard-risk cytogenetics; hazard ratio 1.44 (95% CI: 1.01-2.05); p=0.04]. Of 249 patients, 227 had data available for therapy post TCR (initial therapy details post TCR status are depicted in Table 2) with a median PFS of 4 months (95% CI: 3.5-5) for the salvage therapy post attainment of TCR. Patients achieving a deeper response [≥partial response (PR)] were noted to have a significantly improved PFS with the initial therapy post TCR disease [median PFS 8.2 months (95% CI: 7.5-12.7)] compared to patients not achieving a PR [median PFS 2 months (95% CI: 1.6-2.7); HR 0.2 (95% CI: 0.13-0.27); p<0.0001], Figure 1B. Deeper response (≥PR) to initial therapy at TCR disease was associated with an improved PFS [HR 0.23 (95% CI: 0.16-0.34); p <0.0001] after adjusting for age at TCR status, ISS stage and cytogenetic risk categories at diagnosis. Conclusion: Patients with triple refractory MM have a guarded prognosis and demonstrate an underwhelming median PFS of 4 months and median OS of 1 year. Achievement of a deeper response to therapy at triple refractory status is associated with a prolonged PFS. High-risk cytogenetic features at diagnosis confer a negative prognosis in TCR patients. Newer therapies are the needed to sustain the improvement in outcomes for this group of patients. Figure 1 Figure 1. Disclosures Kapoor: Cellectar: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; BeiGene: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Karyopharm: Consultancy; Regeneron Pharmaceuticals: Research Funding; AbbVie: Research Funding; Takeda: Research Funding; Sanofi: Research Funding; Karyopharm: Research Funding; Glaxo SmithKline: Research Funding. Dispenzieri: Pfizer: Research Funding; Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Alnylam: Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding. Gertz: Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; 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. Dingli: Apellis: Consultancy; GSK: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; Novartis: Research Funding; Alexion: Consultancy. Kumar: Sanofi: Research Funding; Celgene: 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; Roche-Genentech: Consultancy, Research Funding; Beigene: Consultancy; Tenebio: Research Funding; Novartis: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Merck: Research Funding; Carsgen: Research Funding; Antengene: Consultancy, Honoraria; Oncopeptides: Consultancy; Abbvie: 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; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Introduction: The detection of abnormal protein bands (APB) different from the original monoclonal protein in patients with multiple myeloma (MM) who underwent stem cell transplantation and/or chemotherapy has been reported. These atypical serum immunofixation patterns may be monoclonal (also termed secondary monoclonal gammopathy of undetermined significance) or oligoclonal bands (OB). The prognostic significance of this phenomenon remains controversial. This systematic review and meta-analysis aimed to summarize and analyze the evidence for the association between APB with survival in MM patients. Methods: A systematic search of PubMed, Cochrane, Google Scholar, Medline-Ovid, CINAHL, and ERIC, was conducted using relevant search terms. All studies were screened using predefined selection criteria and critically appraised for quality assessment following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline. All studies that described the presence of APB, defined as monoclonal spike with heavy or light chain immunoglobulin distinct from the original paraprotein at initial diagnosis of MM, and its associations with survival were included. Studies that reported multivariate adjusted hazard ratios (HR) were further included for meta-analysis. Random-effects model was used to synthesize the pooled HR estimate for the association of APB with survival. Cochran's Q statistics and I2 tests were used to evaluate statistical heterogeneity. Results: A total of 24 out of 181 eligible studies were included for qualitative synthesis. Four studies (including 1115 patients) that reported HR estimates were included in the final meta-analysis. The random-effect summary HR for the progression-free survival among patients with APB was 0.44 (95% CI, 0.31-0.65) with no statistical heterogeneity (I2=0%, p=0.93). The pooled HR for the association with overall survival was 0.31 (95% CI, 0.14-0.66) with moderate statistical heterogeneity (I2=45%; p=0.16) for patients with APB. One study (Silva et al, 2017) only included patients with at least very good partial response while the other three studies reported similar findings of higher occurrence of APB with complete response (Tovar et al, 2013; Jo et al, 2014; Zou et al, 2014). These results are also consistent with the presumed association of APB with complete response as suggested in other studies included in qualitative review. Conclusions: This study indicated a potential prognostic value of APB for favorable outcomes in the context of both overall and progression-free survival in MM patients after treatment. Further research is needed to evaluate the prognostic impact of the sole emergence of APB irrespective of treatment response. Figure 1 Figure 1. Disclosures Jamshed: Takeda: Honoraria.