BCMA targeting chimeric antigen receptor (CAR) T cell therapy has shown deep and durable responses in multiple myeloma. However, relapse following therapy is frequently observed, and mechanisms of resistance remain ill-defined. Here, we perform single cell genomic characterization of longitudinal samples from a patient who relapsed after initial CAR T cell treatment with lack of response to retreatment. We report selection, following initial CAR T cell infusion, of a clone with biallelic loss of BCMA acquired by deletion of one allele and a mutation that creates an early stop codon on the second allele. This loss leads to lack of CAR T cell proliferation following the second infusion and is reflected by lack of soluble BCMA in patient serum. Our analysis suggests the need for careful detection of BCMA gene alterations in multiple myeloma cells from relapse following CAR T cell therapy.

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).

PURPOSE: Multiple myeloma (MM) is accompanied by heterogeneous somatic alterations. The overall goal of this study was to describe the genomic landscape of myeloma using deep whole-genome sequencing (WGS) and develop a model that identifies patients with long survival. METHODS: We analyzed deep WGS data from 183 newly diagnosed patients with MM treated with lenalidomide, bortezomib, and dexamethasone (RVD) alone or RVD + autologous stem cell transplant (ASCT) in the IFM/DFCI 2009 study (ClinicalTrials.gov identifier: NCT01191060 ). We integrated genomic markers with clinical data. RESULTS: We report significant variability in mutational load and processes within MM subgroups. The timeline of observed activation of mutational processes provides the basis for 2 distinct models of acquisition of mutational changes detected at the time of diagnosis of myeloma. Virtually all MM subgroups have activated DNA repair–associated signature as a prominent late mutational process, whereas APOBEC signature targeting C>G is activated in the intermediate phase of disease progression in high-risk MM. Importantly, we identify a genomically defined MM subgroup (17% of newly diagnosed patients) with low DNA damage (low genomic scar score with chromosome 9 gain) and a superior outcome (100% overall survival at 69 months), which was validated in a large independent cohort. This subgroup allowed us to distinguish patients with low- and high-risk hyperdiploid MM and identify patients with prolongation of progression-free survival. Genomic characteristics of this subgroup included lower mutational load with significant contribution from age-related mutations as well as frequent NRAS mutation. Surprisingly, their overall survival was independent of International Staging System and minimal residual disease status. CONCLUSION: This is a comprehensive study identifying genomic markers of a good-risk group with prolonged survival. Identification of this patient subgroup will affect future therapeutic algorithms and research planning.

Osteolytic lesions (OL) characterize symptomatic multiple myeloma. The mechanisms of how malignant plasma cells (PC) cause OL in one region while others show no signs of bone destruction despite subtotal infiltration remain unknown. We report on a single-cell RNA sequencing (scRNA-seq) study of PC obtained prospectively from random bone marrow aspirates (BM) and paired imaging-guided biopsies of OL. We analyze 148,630 PC from 24 different locations in 10 patients and observe vast inter- and intra-patient heterogeneity based on scRNA-seq analyses. Beyond the limited evidence for spatial heterogeneity from whole-exome sequencing, we find an additional layer of complexity by integrated analysis of anchored scRNA-seq datasets from the BM and OL. PC from OL are characterized by differentially expressed genes compared to PC from BM, including upregulation of genes associated with myeloma bone disease like DKK1, HGF and TIMP-1 as well as recurrent downregulation of JUN/FOS, DUSP1 and HBB. Assessment of PC from longitudinally collected samples reveals transcriptional changes after induction therapy. Our study contributes to the understanding of destructive myeloma bone disease.

Multiple myeloma (MM) is a heterogeneous disease characterized by significant genomic instability. Recently, a causal role for the AID/APOBEC deaminases in inducing somatic mutations in myeloma has been reported. We have identified APOBEC/AID as a prominent mutational signature at diagnosis with further increase at relapse in MM. In this study, we identified upregulation of several members of APOBEC3 family (A3A, A3B, A3C, and A3G) with A3G, as one of the most expressed APOBECs. We investigated the role of APOBEC3G in MM and observed that A3G expression and APOBEC deaminase activity is elevated in myeloma cell lines and patient samples. Loss-of and gain-of function studies demonstrated that APOBEC3G significantly contributes to increase in DNA damage (abasic sites and DNA breaks) in MM cells. Evaluation of the impact on genome stability, using SNP arrays and whole genome sequencing, indicated that elevated APOBEC3G contributes to ongoing acquisition of both the copy number and mutational changes in MM cells over time. Elevated APOBEC3G also contributed to increased homologous recombination activity, a mechanism that can utilize increased DNA breaks to mediate genomic rearrangements in cancer cells. These data identify APOBEC3G as a novel gene impacting genomic evolution and underlying mechanisms in MM.

PURPOSE: Multiple myeloma (MM) is characterized by copy number abnormalities (CNAs), some of which influence patient outcomes and are sometimes observed only at relapse(s), suggesting their acquisition during tumor evolution. However, the presence of micro-subclones may be missed in bulk analyses. Here, we use single-cell genomics to determine how often these high-risk events are missed at diagnosis and selected at relapse. MATERIALS AND METHODS: We analyzed 81 patients with plasma cell dyscrasias using single-cell CNA sequencing. Sixty-six patients were selected at diagnosis, nine at first relapse, and six in presymptomatic stages. A total of 956 newly diagnosed patients with MM and patients with first relapse MM have been identified retrospectively with required cytogenetic data to evaluate enrichment of CNA risk events and survival impact. RESULTS: A total of 52,176 MM cells were analyzed. Seventy-four patients (91%) had 2-16 subclones. Among these patients, 28.7% had a subclone with high-risk features (del(17p), del(1p32), and 1q gain) at diagnosis. In a patient with a subclonal 1q gain at diagnosis, we analyzed the diagnosis, postinduction, and first relapse samples, which showed a rise of the high-risk 1q gain subclone (16%, 70%, and 92%, respectively). In our clinical database, we found that the 1q gain frequency increased from 30.2% at diagnosis to 43.6% at relapse (odds ratio, 1.78; 95% CI, 1.58 to 2.00). We subsequently performed survival analyses, which showed that the progression-free and overall survival curves were superimposable between patients who had the 1q gain from diagnosis and those who seemingly acquired it at relapse. This strongly suggests that many patients had 1q gains at diagnosis in microclones that were missed by bulk analyses. CONCLUSION: These data suggest that identifying these scarce aggressive cells may necessitate more aggressive treatment as early as diagnosis to prevent them from becoming the dominant clone.