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Key Points The initiation of myeloma is mediated by the interaction of environmental factors and inherited genetic events that, when combined with the normal physiological processes that are necessary to generate antibody diversity, result in genetic changes that lead to the immortalization of a myeloma-propagating cell. Chief among these events are chromosomal translocations and hyperdiploidy. Based on their distribution in most clonal cells, chromosomal translocations that are generated by aberrant class switch recombination have been suggested to be initiating events occurring early in the disease process. As a result of these translocations, oncogenes can be placed under the control of the strong enhancers of the immunoglobulin gene loci, leading to their increased expression. The interaction of normal plasma cells with their supportive microenvironment is crucial for plasma cell longevity. A characteristic feature of myeloma cells is the requirement for an intimate relationship with the bone marrow microenvironment, where plasma cells are nurtured in specialized niches that facilitate the growth of the myeloma clone. Derangement of these interactions is important in the immortalization of a myeloma-propagating cell. The basic premise underlying the progression of myeloma is that multiple mutations in different pathways collaborate to deregulate the intrinsic biology of the plasma cell, changing it in ways that lead to the features of myeloma. The immortalized cell then acquires additional genetic hits over time, thus leading to the clinically recognized features of myeloma and eventually to the development of treatment resistance and an ability to grow in the peripheral blood as a leukaemic phase. It is becoming increasingly clear that the molecular events acquired during myeloma progression are not acquired in a linear fashion but instead through branching, nonlinear pathways, similar to the mechanism suggested by Darwin to explain the evolution of species. Therefore, a further level of the genetic complexity of myeloma is based on intraclonal heterogeneity at the level of a myeloma-propagating cell. The genetic lesions that lead to myeloma are best considered within the categories of inherited variation, translocations, copy number abnormalities, mutations, and methylation and miRNA abnormalities. The net biological impact of such events is to modify the behaviour of the myeloma-propagating cell, resulting in the key molecular hallmarks of myeloma. The treatments that are used for myeloma include steroids, alkylating agents, the immunomodulatory drugs thalidomide and lenalidomide, proteasome inhibitors and autologous stem cell transplantation. Current therapeutic aims are to induce and maintain long-term remission. Future approaches based on personalized medicine strategies will involve targeted therapies combined with molecular-diagnostic strategies. The presence of intraclonal heterogeneity has important effects on the clinical application of both standard and targeted treatment strategies but provides a model system within which to assess their optimum use. This review discusses some of the new insights on the development of multiple myeloma that can be gained from considering the evolution of this disease from a Darwinian perspective. Based on the clinical features of myeloma and related malignancies of plasma cells, it has been possible to generate a model system of myeloma progression from a normal plasma cell through smouldering myeloma to myeloma and then plasma cell leukaemia. Using this model system we can study at which points the genetic alterations identified through whole-tumour molecular analyses function in the initiation and progression of myeloma. Further genetic complexity, such as intraclonal heterogeneity, and insights into the molecular evolution and intraclonal dynamics in this model system are crucial to our understandings of tumour progression, treatment resistance and the use of currently available and future treatments.

Deciphering Multiple Myeloma evolution in the whole bone marrow is key to inform curative strategies. Here, we perform spatial-longitudinal whole-exome sequencing, including 140 samples collected from 24 Multiple Myeloma patients during up to 14 years. Applying imaging-guided sampling we observe three evolutionary patterns, including relapse driven by a single-cell expansion, competing/co-existing sub-clones, and unique sub-clones at distinct locations. While we do not find the unique relapse sub-clone in the baseline focal lesion(s), we show a close phylogenetic relationship between baseline focal lesions and relapse disease, highlighting focal lesions as hotspots of tumor evolution. In patients with ≥3 focal lesions on positron-emission-tomography at diagnosis, relapse is driven by multiple distinct sub-clones, whereas in other patients, a single-cell expansion is typically seen ( p  < 0.01). Notably, we observe resistant sub-clones that can be hidden over years, suggesting that a prerequisite for curative therapies would be to overcome not only tumor heterogeneity but also dormancy. Spatially and temporally resolved data can improve our understanding of evolution and treatment resistance in multiple myeloma (MM). Here, the authors analyse spatial and longitudinal heterogeneity in MM patients using multi-region sequencing, and identify subclones associated with relapse and therapy resistance.

The tumor microenvironment (TME) is increasingly appreciated as an important determinant of cancer outcome, including in multiple myeloma (MM). However, most myeloma microenvironment studies have been based on bone marrow (BM) aspirates, which often do not fully reflect the cellular content of BM tissue itself. To address this limitation in myeloma research, we systematically characterized the whole bone marrow (WBM) microenvironment during premalignant, baseline, on treatment, and post-treatment phases. Between 2004 and 2019, 998 BM samples were taken from 436 patients with newly diagnosed MM (NDMM) at the University of Arkansas for Medical Sciences in Little Rock, Arkansas, United States of America. These patients were 61% male and 39% female, 89% White, 8% Black, and 3% other/refused, with a mean age of 58 years. Using WBM and matched cluster of differentiation (CD)138-selected tumor gene expression to control for tumor burden, we identified a subgroup of patients with an adverse TME associated with 17 fewer months of progression-free survival (PFS) (95% confidence interval [CI] 5-29, 49-69 versus 70-82 months, χ2 p = 0.001) and 15 fewer months of overall survival (OS; 95% CI -1 to 31, 92-120 versus 113-129 months, χ2 p = 0.036). Using immunohistochemistry-validated computational tools that identify distinct cell types from bulk gene expression, we showed that the adverse outcome was correlated with elevated CD8+ T cell and reduced granulocytic cell proportions. This microenvironment develops during the progression of premalignant to malignant disease and becomes less prevalent after therapy, in which it is associated with improved outcomes. In patients with quantified International Staging System (ISS) stage and 70-gene Prognostic Risk Score (GEP-70) scores, taking the microenvironment into consideration would have identified an additional 40 out of 290 patients (14%, premutation p = 0.001) with significantly worse outcomes (PFS, 95% CI 6-36, 49-73 versus 74-90 months) who were not identified by existing clinical (ISS stage III) and tumor (GEP-70) criteria as high risk. The main limitations of this study are that it relies on computationally identified cell types and that patients were treated with thalidomide rather than current therapies. In this study, we observe that granulocyte signatures in the MM TME contribute to a more accurate prognosis. This implies that future researchers and clinicians treating patients should quantify TME components, in particular monocytes and granulocytes, which are often ignored in microenvironment studies.

PARP inhibitors can induce synthetic lethality in tumors characterized by homologous recombination deficiency (HRD), which can be detected by evaluating genome-wide loss of heterozygosity (LOH). Multiple myeloma (MM) is a genetically unstable tumor and we hypothesized that HRD-related LOH (HRD-LOH) could be detected in patient samples, supporting a potential role for PARP inhibition in MM. Using results from targeted next-generation sequencing studies (FoundationOne® Heme), we analyzed HRD-LOH in patients at all disease stages (MGUS (n = 7), smoldering MM (SMM, n = 30), newly diagnosed MM (NDMM, n = 71), treated MM (TRMM, n = 64), and relapsed MM (RLMM, n = 234)) using an algorithm to identify HRD-LOH segments. We demonstrated HRD-LOH in MM samples, increasing as disease progresses. The extent of genomic HRD-LOH correlated with high-risk disease markers. Outcome of RLMM patients, the biggest clinical group, was analyzed and patients with HRD-LOH above the third quartile (≥5% HRD-LOH) had significantly worse progression-free and overall survival than those with lower levels (p < 0.001). Mutations in key homologous recombination genes account for some, but not all, of the cases with an excess of HRD-LOH. These data support the further evaluation of PARP inhibitors in MM patients, particularly in the relapsed setting with a high unmet need for new treatments.

Multiple Myeloma is an incurable plasma cell malignancy with a poor survival rate that is usually treated with immunomodulatory drugs (iMiDs) and proteosome inhibitors (PIs). The malignant plasma cells quickly become resistant to these agents causing relapse and uncontrolled growth of resistant clones. From whole genome sequencing (WGS) and RNA sequencing (RNA-seq) studies, different high-risk translocation, copy number, mutational, and transcriptional markers can be identified. One of these markers, PHF19 , epigenetically regulates cell cycle and other processes and is already studied using RNA-seq. In this study, we generate a large (325,025 cells and 49 patients) single cell multi-omic dataset and jointly quantify ATAC- and RNA-seq for each cell and matched genomic profiles for each patient. We identify an association between one plasma cell subtype with myeloma progression that we call relapsed/refractory plasma cells (RRPCs). These cells are associated with chromosome 1q alterations, TP53 mutations, and higher expression of PHF19 . We also identify downstream regulation of cell cycle inhibitors in these cells, possible regulation by the transcription factor (TF) PBX1 on chromosome 1q, and determine that PHF19 may be acting primarily through this subset of cells. Translocations and copy number variations that affect multiple myeloma (MM) have not been investigated at the single cell level. Here, single cell multi-omics reveal the relationship between epigenetic regulation and cytogenetic events that lead to the increase of cell proliferation in MM.

Multiple myeloma (MM) is a devastating plasma cell malignancy characterized by the expansion of aberrant monoclonal plasma cells in the bone marrow, leading to severe clinical manifestations and poor prognosis, particularly in relapsed/refractory cases. Identifying novel therapeutic targets is crucial to improve treatment outcomes in these patients. In this study, we investigated the role of the protein arginine methyltransferase 1 (PRMT1) in MM pathogenesis and explored its potential as a therapeutic target. We observed that PRMT1, responsible for most asymmetric di-methylation in cells, exhibited the highest expression among PRMT family members in MM cell lines and primary MM cells. Importantly, PRMT1 expression was significantly elevated in relapsed/refractory patients compared to newly diagnosed patients. High expression of PRMT1 expression was strongly associated with poor prognosis. We found that genetic or enzymatic inhibition of PRMT1 impaired MM cell growth, induced cell cycle arrest, and triggered cell death. Treatment with MS023, a potent PRMT type I inhibitor, demonstrated a robust inhibitory effect on the viability of primary cells isolated from newly diagnosed and proteasome inhibitor-relapsed/refractory patients in a dose-dependent manner. Suppression of PRMT1 downregulated genes related to cell division and upregulated genes associated with apoptosis pathway. We also found that genes related to immune response and lymphocyte activation were significantly upregulated in PRMT1-suppressed cells. Notably, the activation status of T cells was strikingly enhanced upon co-culturing with PRMT1-KO MM cells. In vivo studies using a xenograft model revealed that targeting PRMT1 by either CRISPR/Cas9-mediated knockout or MS023 treatment significantly attenuated MM tumor growth and prolonged the survival of tumor-bearing mice. Histological analysis further confirmed increased apoptotic cell death in MS023-treated tumors. Collectively, our findings establish PRMT1 as an indispensable and novel therapeutic vulnerability in MM. The elevated expression of PRMT1 in relapsed/refractory patients underscores its potential as a target for overcoming treatment resistance. Moreover, our results highlight the efficacy of MS023 as a promising therapeutic agent against MM, offering new avenues for therapeutic approaches in relapsed/refractory MM.

Background Multiple myeloma (MM) patients with t(14;20) have a poor prognosis and their outcome has not improved following the introduction of bortezomib (Bzb). The mechanism underlying the resistance to proteasome inhibitors (PIs) for this subset of patients is unknown. Methods IC50 of Bzb and carfilzomib (CFZ) in human myeloma cell lines (HMCLs) were established by MTT assay. Gene Expression profile (GEP) analysis was used to determine gene expression in primary myeloma cells. Immunoblotting analysis was performed for MAFb and caspase family proteins. Immunofluorescence staining was used to detect the location of MAFb protein in MM cells. Lentiviral infections were used to knock-down MAFb expression in two lines. Apoptosis detection by flow cytometry and western blot analysis was performed to determine the molecular mechanism MAFb confers resistance to proteasome inhibitors. Results We found high levels of MAFb protein in cell lines with t(14;20), in one line with t(6;20), in one with Igλ insertion into MAFb locus, and in primary plasma cells from MM patients with t(14;20). High MAFb protein levels correlated with higher IC50s of PIs in MM cells. Inhibition of GSK3β activity or treatment with Bzb or CFZ prevented MAFb protein degradation without affecting the corresponding mRNA level indicating a role for GSK3 and proteasome inhibitors in regulation of MAFb stability. Silencing MAFb restored sensitivity to Bzb and CFZ, and enhanced PIs-induced apoptosis and activation of caspase-3, − 8, − 9, PARP and lamin A/C suggesting that high expression of MAFb protein leads to insensitivity to proteasome inhibitors. Conclusion These results highlight the role of post-translational modification of MAFb in maintaining its protein level, and identify a mechanism by which proteasome inhibitors induced stabilization of MAFb confers resistance to proteasome inhibitors, and provide a rationale for the development of targeted therapeutic strategies for this subset of patients.

Background Immunotherapy is now standard of care for multiple myeloma (MM), where the most common targets are B cell maturation antigen, CD38, and G protein-coupled receptor class C group 5 member D (GPRC5D). However, additional novel targets are needed to counter tumor heterogeneity, therefore new strategies to identify additional targets are also required. Methods We utilized multi-omics data from two large datasets A framework that utilized prior knowledge of cell surface potential, expression in healthy organs, and expression level in MM cells was established to define novel immunotherapeutic targets. High confidence targets were prioritized for myeloma populations and subgroups, validated with flow cytometry and immunoblotting. Results Novel population-level candidate targets such as ITGA4 and LAX1, as well as subtype-specific targets including ROBO3 in t(4;14), CD109 in t(14;16), CD20 in t(11;14), CD180 in hyperdiploidy, GPRC5D in 1q gain, and ADAM28 in biallelic TP53 samples were identified. Candidate target surface expression was validated by flow cytometry and CRISPR-Cas9 knock-out models. Sub-clonal differences in expression were noted, using single-cell RNA-seq data. Additionally, alternative splicing of existing immunotherapy targets, such as FCRL5,  was noted as a potential mechanism of antigen loss . Conclusions Our study presents a methodology to identify novel candidate immunotherapy targets. We also use known genomic data to identify subtype-specific targets that could be used either as complementary or alternative targets to existing treatments. We show that immunotherapy targets can have heterogenous expression within a patient, which can affect treatment efficacy. Taken together, our study establishes a robust methodology to identify novel therapeutic targets in MM, revealing critical insights that will inform the development of current and next-generation immunotherapies.

We propose DEGAS (Diagnostic Evidence GAuge of Single cells), a novel deep transfer learning framework, to transfer disease information from patients to cells. We call such transferrable information “impressions,” which allow individual cells to be associated with disease attributes like diagnosis, prognosis, and response to therapy. Using simulated data and ten diverse single-cell and patient bulk tissue transcriptomic datasets from glioblastoma multiforme (GBM), Alzheimer’s disease (AD), and multiple myeloma (MM), we demonstrate the feasibility, flexibility, and broad applications of the DEGAS framework. DEGAS analysis on myeloma single-cell transcriptomics identified PHF19 high myeloma cells associated with progression. Availability: https://github.com/tsteelejohnson91/DEGAS .

Background Multiple Myeloma (MM) is a hematological malignancy with genomic heterogeneity and poor survival outcome. Apart from the central role of genetic lesions, epigenetic anomalies have been identified as drivers in the development of the disease. Methods Alterations in the DNA methylome were mapped in 52 newly diagnosed MM (NDMM) patients of six molecular subgroups and matched with loci-specific chromatin marks to define their impact on gene expression. Differential DNA methylation analysis was performed using DMAP with a ≥10% increase (hypermethylation) or decrease (hypomethylation) in NDMM subgroups, compared to control samples, considered significant for all the subsequent analyses with p<0.05 after adjusting for a false discovery rate. Results We identified differentially methylated regions (DMRs) within the etiological cytogenetic subgroups of myeloma, compared to control plasma cells. Using gene expression data we identified genes that are dysregulated and correlate with DNA methylation levels, indicating a role for DNA methylation in their transcriptional control. We demonstrated that 70% of DMRs in the MM epigenome were hypomethylated and overlapped with repressive H3K27me3. In contrast, differentially expressed genes containing hypermethylated DMRs within the gene body or hypomethylated DMRs at the promoters overlapped with H3K4me1, H3K4me3, or H3K36me3 marks. Additionally, enrichment of BRD4 or MED1 at the H3K27ac enriched DMRs functioned as super-enhancers (SE), controlling the overexpression of genes or gene-cassettes. Conclusions Therefore, this study presents the underlying epigenetic regulatory networks of gene expression dysregulation in NDMM patients and identifies potential targets for future therapies.