Raab, Marc S

Abstract Studies have reported conflicting findings regarding the contribution of germline variants or somatic genomic drivers to racial disparities in multiple myeloma. To comprehensively investigate somatic drivers in relation to inherited genetics in multiple myeloma, we combined newly sequenced whole-genome sequencing data with publicly available datasets (total n = 1,286). Overall, we did not identify germline or somatic genomic differences that explain the different risk of developing multiple myeloma between patients with genetic similarity to African (AFR) or European (EUR) reference populations. A difference in the detectability and timing of APOBEC-associated and germinal center mutational activity was observed. Integrating epidemiologic data and mutational signature-based temporal estimates, we challenge the assumption that individuals in the AFR group develop multiple myeloma at a younger age. Finally, we demonstrate that, with equal access to efficacious therapies, patients in the AFR and EUR groups have equivalent clinical outcomes. Significance: Multiple myeloma is reported to occur at higher rates in individuals who self-identify as non-Hispanic Black. In this large dataset, genomic drivers occur at the same rate among ancestry groups, except for APOBEC mutagenesis. With equivalent therapy, clinical outcomes did not differ for patients grouped by genetic ancestry similarity.

PURPOSE This analysis aimed to contextualize the symptoms of peripheral neuropathy (PN) experienced by patients with triple-class refractory (TCR) multiple myeloma (MM) treated with elranatamab in the MagnetisMM-3 clinical trial with those experienced by patients with TCR MM receiving a new line of physician's choice of therapy in the real-world MagnetisMM-14 study. METHODS MagnetisMM-3 included 123 patients and MagnetisMM-14 included 35 who had TCR MM and were enrolled under the same eligibility criteria. Patient-reported symptoms of PN were collected monthly using the Chemotherapy-Induced Peripheral Neuropathy-20 item (CIPN20) questionnaire and compared for clinically meaningful differences across sensory, motor, and autonomic domains. Higher scores indicated worse patient-reported PN symptoms. RESULTS Baseline demographics and clinical characteristics for patients in MagnetisMM-3 and MagnetisMM-14 were generally similar. Patients in MagnetisMM-3 had a median of five ( v four in MagnetisMM-14) prior lines of therapy. In MagnetisMM-14, common index therapies included elotuzumab + pomalidomide (23%), carfilzomib + pomalidomide (19%), or carfilzomib + cyclophosphamide (19%), all with corticosteroids. Mean scores for sensory (15.8 v 14.8) and motor (14.4 v 12.2) domains of the CIPN20 were similar between MagnetisMM-3 and MagnetisMM-14 at baseline. Mean scores for the autonomic domain were 14.0 versus 21.3 at baseline, respectively. No clinically meaningful differences for any domain were found between month 6 scores or changes in scores from baseline to month 6 between MagnetisMM-3 and MagnetisMM-14 populations. CONCLUSION These findings suggest that elranatamab treatment was not associated with a worsening of patient-reported PN symptoms across the sensory, motor, and autonomic domains of the CIPN20. Moreover, PN symptoms reported with elranatamab treatment were similar to those reported with other common therapies used in real-world clinical practice for the management of MM. MagnetisMM-3 ClinicalTrials.gov identifier: NCT04649359 .

Abstract Monoclonal antibodies targeting CD38 are a therapeutic mainstay in multiple myeloma (MM). Although they have contributed to improved outcomes, most patients still experience disease relapse, and little is known about tumor-intrinsic mechanisms of resistance to these drugs. Antigen escape has been implicated as a mechanism of tumor-cell evasion in immunotherapy. Yet, it is unknown whether MM cells can develop permanent resistance to anti-CD38 antibodies by acquiring genomic events leading to biallelic disruption of the CD38 gene locus. Here, we analyzed whole-genome and whole-exome sequencing data from patients 701 newly diagnosed MM, 67 patients at relapse with naivety to anti-CD38 antibodies, and 50 patients collected at relapse after anti-CD38 antibodies. We report a loss of CD38 in 10 of 50 patients (20%) after CD38 therapy, 3 of whom exhibited a loss of both copies. Two of these cases showed convergent evolution in which distinct subclones independently acquired similar advantageous variants. Functional studies on missense mutations involved in biallelic CD38 events revealed that 2 variants, L153H and C275Y, decreased binding affinity and antibody-dependent cellular cytotoxicity of the commercial antibodies daratumumab and isatuximab. However, a third mutation, R140G, conferred selective resistance to daratumumab, while retaining sensitivity to isatuximab. Clinically, patients with MM are often rechallenged with CD38 antibodies after disease progression and these data suggest that next-generation sequencing may play a role in subsequent treatment selection for a subset of patients.

Despite significant improvements in survival of patients with multiple myeloma (MM), outcomes remain heterogeneous, and a significant proportion of patients experience suboptimal outcomes. Importantly, traditional prognostic factors based on data from patients treated with older therapies no longer capture prognosis accurately in the contemporary era of novel triplet or quadruplet therapies. Therefore, risk stratification requires refinement in the context of available and investigational treatment options in routine practice and clinical trials, respectively. The current identification of high-risk MM (HRMM) in routine practice is based on the Revised International Staging System, which stratifies patients using a combination of widely available serum biomarkers and chromosomal abnormalities assessed via fluorescence in situ hybridization. In recent years, a substantial body of evidence concerning additional clinical, biological, and molecular/genomic prognostic factors has accumulated, along with new MM risk stratification tools and consensus reports. The International Myeloma Society, along with the International Myeloma Working Group, convened an Expert Panel with the primary aim of revisiting the definition of HRMM and formulating a practical and data-driven consensus definition, based on new evidence from molecular/genomic assays, updated clinical data, and contemporary risk stratification concepts. The Panel proposes the following Consensus Genomic Staging (CGS) of HRMM which relies upon the presence of at least one of these abnormalities: (1) del(17p), with a cutoff of >20% clonal fraction, and/or TP53 mutation; (2) an IgH translocation including t(4;14), t(14;16), or t(14;20) along with 1q+ and/or del(1p32); (3) monoallelic del(1p32) along with 1q+ or biallelic del(1p32); or (4) β2 microglobulin ≥5.5 mg/L with normal creatinine (<1.2 mg/dL).

Abstract Accurate prediction of risk of progression from smoldering (SMM) to active multiple myeloma (MM) is paramount to individualized early therapeutic strategies with minimum risk of overtreatment. Current risk stratification models do not account for evolving biomarker trajectories. We assembled the largest cohort to date of 2,270 SMM patients from six international centers with longitudinal clinical and biological data to train and validate the PANGEA 2.0 risk models. Four evolving biomarkers were significantly associated with shorter time-to-progression: M-protein increase ≥0.2g/dL, involved:uninvolved serum free light chain ratio increase ≥20, creatinine increase >25%, and hemoglobin decrease ≥1.5g/dL. PANGEA 2.0 outperforms established models including the 20/2/20 and IMWG models by more accurately predicting progression (C-statistics=0.69–0.84), even without biomarker history (C-statistics=0.69–0.83) or recent bone marrow biopsy. PANGEA 2.0 is an easy-to-use, open-access tool (https://ghobrial.shinyapps.io/pangea_2_calculator) to improve and individualize SMM risk stratification. Validation tools are available to compare PANGEA 2.0 to established models (https://ghobrial.shinyapps.io/pangea_validation).

PURPOSE Outcomes for patients with newly diagnosed multiple myeloma (NDMM) are heterogenous, with overall survival (OS) ranging from months to over 10 years. METHODS To decipher and predict the molecular and clinical heterogeneity of NDMM, we assembled a series of 1,933 patients with available clinical, genomic, and therapeutic data. RESULTS Leveraging a comprehensive catalog of genomic drivers, we identified 12 groups, expanding on previous gene expression–based molecular classifications. To build a model predicting individualized risk in NDMM (IRMMa), we integrated clinical, genomic, and treatment variables. To correct for time-dependent variables, including high-dose melphalan followed by autologous stem-cell transplantation (HDM-ASCT), and maintenance therapy, a multi-state model was designed. The IRMMa model accuracy was significantly higher than all comparator prognostic models, with a c-index for OS of 0.726, compared with International Staging System (ISS; 0.61), revised-ISS (0.572), and R2-ISS (0.625). Integral to model accuracy was 20 genomic features, including 1q21 gain/amp, del 1p, TP53 loss, NSD2 translocations, APOBEC mutational signatures, and copy-number signatures (reflecting the complex structural variant chromothripsis). IRMMa accuracy and superiority compared with other prognostic models were validated on 256 patients enrolled in the GMMG-HD6 (ClinicalTrials.gov identifier: NCT02495922 ) clinical trial. Individualized patient risks were significantly affected across the 12 genomic groups by different treatment strategies (ie, treatment variance), which was used to identify patients for whom HDM-ASCT is particularly effective versus patients for whom the impact is limited. CONCLUSION Integrating clinical, demographic, genomic, and therapeutic data, to our knowledge, we have developed the first individualized risk-prediction model enabling personally tailored therapeutic decisions for patients with NDMM.

Key Points The incidence of mutations within the MAPK pathway, the CRBN pathway, and TP53 is significantly increased in drug-refractory MM. Mutations in CRBN might contribute to IMiD resistance in drug-refractory MM.