Landgren, C Ola

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.

Abstract Multiple myeloma (MM) with t(11;14)(CCND1;IGH) remains the only subset sensitive to the BCL2 inhibitor venetoclax. However, not all patients with t(11;14)(CCND1;IGH) respond to treatment, and some progress early after initial response. To investigate this, we examined 44 whole-genome and whole-exome sequencing data samples from 34 patients with t(11;14) MM treated with venetoclax. The presence of mutations in the RAS pathway was strongly associated with shortened progression-free survival (PFS) and was validated in an independent cohort of 21 patients with MM. The presence of 1q gain was also associated with shorter PFS in patients without RAS mutations. In 10 patients with paired prevenetoclax and postvenetoclax treatment samples, postvenetoclax progression was recurrently driven by the selection of genomic events in the BCL2/MCL1 and RAS pathways and of high-risk features (eg, loss of TP53 and CDKN2C). Overall, our study shows that comprehensive genomic profiling can identify most mechanisms underlying resistance to BCL2 inhibition in t(11;14)(CCND1;IGH) MM.

ABSTRACT Chimeric antigen receptor T-cell (CART) and T-cell engager (TCE) therapies targeting B-cell maturation antigen (BCMA) are transforming the treatment landscape for relapsed multiple myeloma (MM). However, despite impressive initial response rates, most patients eventually relapse. To investigate this unmet medical need, we applied whole-genome sequencing (WGS) to MM cells from cohorts of 102 relapsed patients treated with anti-BCMA CART and TCE therapies. Several genomic alterations were associated with clinical outcomes, particularly primary refractoriness, including high genomic complexity and mutations in genes regulating plasma cell identity, which predicted resistance to therapy. Single-cell RNA sequencing further revealed that MM cells from refractory patients exhibited high proliferation signatures and reduced expression of TNFRSF17 (encoding BCMA), while were less enriched for plasma cell–associated transcriptional programs, a phenomenon we term “plasma cell identity escape.” This profile was strongly associated with immune dysregulation of CD8 T cells including increased activation and exhaustion. This evolution of MM toward a more proliferative and lineage-divergent state, refractory to the anti-BCMA T-cell redirecting therapies, was functionally validated in preclinical MM mouse models. Collectively, our results comprehensively define the cellular and molecular mechanisms underlying primary resistance to anti-BCMA therapies.

Abstract Consumption of a Western diet and high body mass index (BMI) are risk factors for progression from premalignant phenotypes to multiple myeloma, a hematologic cancer. In the NUTRIVENTION trial (NCT04920084), we administered a high-fiber, plant-based diet (HFPBD; meals for 12 weeks, coaching for 24 weeks) to 23 participants with myeloma precursor states and elevated BMI. The intervention was feasible and improved quality of life and modifiable risk factors: metabolic (BMI, insulin resistance), microbiome (diversity, composition), and immune (inflammation, monocyte subsets). Disease progression trajectory improved (n = 2) or was stable. Findings were translated to Vk*MYC mice modeling the myeloma precursor state, in which a high-fiber diet (HFD) delayed disease progression through improved metabolism and microbiome composition, leading to increased short-chain fatty acid production that reinvigorated antitumor immunity and inhibited tumor growth. These effects from fiber consumption were independent of calorie restriction and weight loss. A HFD is a low-risk intervention that may delay progression to myeloma. Significance: A HFPBD in participants with precursor plasma cell disorders and an elevated BMI improved metabolic, microbiome, and immune biomarkers of disease. In a subset, it may delay progression to myeloma. In mouse models, a HFD delayed progression to myeloma independent of calorie restriction. See related commentary by Fairfield and Reagan, p. 623

Multiple myeloma (MM) is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). While these precursor conditions are asymptomatic, they are not entirely benign and carry a lifelong risk of progression to MM. Unlike other cancers defined by pathology, malignant transformation from MGUS or SMM to MM has so far relied on demonstration of clinical end-organ damage as morphology and cytogenetics cannot reliably distinguish them. In this study, using genomic data from 374 patients with MGUS or SMM (277 training, 97 validation), to our knowledge, we demonstrate for the first time the ability to identify malignant transformation in MGUS and SMM. We introduce the concept of genomic MM and genomic MGUS to differentiate the subsets of MGUS and SMM that are biologically malignant with genomic features indistinguishable from MM from the subset that is premalignant and unlikely to progress to malignancy. Importantly, we find that most SMM has biological features of malignant transformation indistinguishable from MM. As expected, this subset that we consider having genomic MM is associated with a high risk of progression to MM although some patients remained progression-free beyond 5 years. Conversely, 60% of MGUS and 10% of SMM have no evidence of malignant transformation (genomic MGUS), with no progression during follow-up. Integration of genomic features with the 2/20/20 International Myeloma Working Group model significantly improved the prediction of progression among genomic MM. These findings support the use of genomic criteria to refine the classification and the risk stratification in myeloma precursor conditions.

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.

Summary: The multiple myeloma treatment landscape has changed dramatically. This change, paralleled by an increase in scientific knowledge, has resulted in significant improvement in survival. However, heterogeneity remains in clinical outcomes, with a proportion of patients not benefiting from current approaches and continuing to have a poor prognosis. A significant proportion of the variability in outcome can be predicted on the basis of clinical and biochemical parameters and tumor-acquired genetic variants, allowing for risk stratification and a more personalized approach to therapy. This article discusses the principles that can enable the rational and effective development of therapeutic approaches for high-risk multiple myeloma.

AbstractThe development of novel agents has transformed the treatment paradigm for multiple myeloma, with minimal residual disease (MRD) negativity now achievable across the entire disease spectrum. Bone marrow–based technologies to assess MRD, including approaches using next-generation flow and next-generation sequencing, have provided real-time clinical tools for the sensitive detection and monitoring of MRD in patients with multiple myeloma. Complementary liquid biopsy–based assays are now quickly progressing with some, such as mass spectrometry methods, being very close to clinical use, while others utilizing nucleic acid–based technologies are still developing and will prove important to further our understanding of the biology of MRD. On the regulatory front, multiple retrospective individual patient and clinical trial level meta-analyses have already shown and will continue to assess the potential of MRD as a surrogate for patient outcome. Given all this progress, it is not surprising that a number of clinicians are now considering using MRD to inform real-world clinical care of patients across the spectrum from smoldering myeloma to relapsed refractory multiple myeloma, with each disease setting presenting key challenges and questions that will need to be addressed through clinical trials. The pace of advances in targeted and immune therapies in multiple myeloma is unprecedented, and novel MRD-driven biomarker strategies are essential to accelerate innovative clinical trials leading to regulatory approval of novel treatments and continued improvement in patient outcomes.

Abstract Smoldering multiple myeloma (SMM) is an asymptomatic clonal plasma cell disorder. SMM is distinguished from monoclonal gammopathy of undetermined significance by a much higher risk of progression to multiple myeloma (MM). There have been major advances in the diagnosis, prognosis, and management of SMM in the last few years. These include a revised disease definition, identification of several new prognostic factors, a classification based on underlying cytogenetic changes, and new treatment options. Importantly, a subset of patients previously considered SMM is now reclassified as MM on the basis of biomarkers identifying patients with an ≥80% risk of progression within 2 years. SMM has assumed greater significance on the basis of recent trials showing that early therapy can be potentially beneficial to patients. As a result, there is a need to accurately diagnose and risk-stratify patients with SMM, including routine incorporation of modern imaging and laboratory techniques. In this review, we outline current concepts in diagnosis and risk stratification of SMM, and provide specific recommendations on the management of SMM.