Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma

Clinical implications of residual normal plasma cells within bone marrow across various disease stages in multiple myeloma

Residual normal plasma cells (NPCs), which compete with tumor plasma cells, play an important role in multiple myeloma. However, large-scale cohort studies investigating residual NPCs, especially at the minimal residual disease (MRD) phase, are currently lacking. In this study, we conducted a comprehensive investigation into the clinical significance of residual NPCs throughout the entire disease course in 1363 myeloma patients from the NICHE cohort (NCT04645199). Our results revealed that myeloma patients with high baseline NPCs ratio (≥5%) exhibited distinct indolent features, characterized by lower tumor burden, reduced frequencies of cytopenia, immunoparesis, and high-risk cytogenetics. Importantly, high residual NPCs ratio at diagnosis or relapse was independently associated with favorable survival. High absolute percentages of NPCs at undetectable MRD were related with superior clinical benefit and immune reconstitution. At MRD-positive phases, grouping based on NPCs ratio (<50%, 50-90%, ≥90%) demonstrated better risk stratification compared to residual tumor log levels. Based on the time-dependent NPCs ratio trend, we developed a dynamic MRD model that classifies patients into three groups with diverse longitudinal trends, leading to distinct prognoses. Collectively, residual NPCs serves not only as a valuable complementary biomarker for risk stratification but also provides valuable insights on reclassifications and kinetics of MRD.

Early Detection of Precursor Diseases of Multiple Myeloma

Precursor diseases of multiple myeloma (MM) are monoclonal gammopathy of uncertain significance and smoldering MM. While it is well known that a percentage of those affected by these conditions will progress to MM, it is difficult to predict who will progress and when, and guidelines for screening for these conditions are lacking. Moreover, there are various models for risk stratification, though there are ongoing efforts to improve these models in order to predict who may benefit from treatment. Finally, there are various clinical trials, both past and ongoing, expanding the scope of possible treatment options for precursor diseases.

Functional cure and long-term survival in multiple myeloma: how to challenge the previously impossible

Multiple myeloma (MM) is a heterogeneous disease with survival ranging from months to decades. The goal of 'cure' remains elusive for most patients, but has been shown to be possible, with durable remission and a transition to a plateau phase (analogous to monoclonal gammopathy of uncertain significance/smoldering myeloma). In this review, two representative cases set the stage to illustrate how this might be possible and what still needs to be determined to achieve functional disease control over a prolonged period. Several developments have emerged, such as improved diagnostics including the definitions and use of SLiM-CRAB criteria and measurable residual disease (MRD) with whole-genome/single-cell sequencing as well as other correlates to better understand disease biology. These advances enable earlier detection, more accurate risk stratification and improved personalized treatment strategies by facilitating analysis of genetic alterations and clonal heterogeneity. Whole-genome sequencing may also identify driver mutations and modes of resistance to immunotherapies as well as other targeted therapies. Today, induction with a CD38 antibody, proteasome inhibitor, immunomodulatory drug, and dexamethasone, potentially followed by autologous stem cell transplantation and lenalidomide maintenance, can be considered standard of care for transplant-eligible (TE) patients with newly diagnosed MM (NDMM). That prolonged disease control and functional cure can be achieved in non-transplant-eligible (NTE) patients is currently emerging as a distinct possibility: data from phase III trials that incorporate a CD38 antibody into the treatment of NTE NDMM patients demonstrate impressive MRD negativity rates that appear sustained over several years. While the long-term durability of chimeric antigen receptor T cells, bi-specific antibodies and other immunotherapies are being evaluated, several clinical trials are now investigating their role in frontline treatment for TE and NTE patients. These trials will address whether chimeric antigen receptor T-cell therapy will replace autologous stem cell transplantation and whether such immunotherapies will represent a truly curative option. We conclude that while cure remains elusive, the concept of operational or functional cure provides a new benchmark to strive for and is an emerging area of active and potentially achievable clinical research for MM.

Machine-learning and scRNA-Seq-based diagnostic and prognostic models illustrating survival and therapy response of lung adenocarcinoma

Lung cancer is a major cause accounting for cancer-related mortalities, with lung adenocarcinoma (LUAD) being the most prevalent subtype. Given the high clinical and cellular heterogeneities of LUAD, accurate diagnosis and prognosis are crucial to avoid overdiagnosis and overtreatment. Taking full advantage of scRNA-Seq data to resolve the tumor heterogeneities, we explored the overall landscape of LUAD microenvironment. Utilizing the stage-specific tumor cell markers, we have developed highly accurate diagnostic and prognostic models with elevated sensitivity and specificity. The diagnostic model, developed through random forest algorithms with a thirteen-gene signature, achieved an accuracy of 96.4% and an AUC of 0.993. These metrics were further demonstrated by benchmarking with available models and scoring systems in independent cohorts. Concurrently, the prognostic model, formulated via Cox regression with a six-gene signature, effectively predicted overall survival, with elevated risk scores associated with increased fractions of cancer-associated fibroblasts, and higher likelihood of immune escape and T-cell exclusion. Subsequently, two nomograms were developed to predict survival and drug responses, facilitating their integration into clinical practice. Overall, this study underscores the potential of our models for efficient, rapid, and cost-effective diagnosis and prognosis of LUAD, adaptable to multiple expression profiling platforms and quantification methods.

Genomic and immune determinants of resistance to daratumumab-based therapy in relapsed refractory multiple myeloma

Targeted immunotherapy combinations, including the anti-CD38 monoclonal antibody (MoAb) daratumumab, have shown promising results in patients with relapsed/refractory multiple myeloma (RRMM), leading to a considerable increase in progression-free survival. However, a large fraction of patients inevitably relapse. To understand this, we investigated 32 relapsed MM patients treated with daratumumab, lenalidomide, and dexamethasone (Dara-Rd; NCT03848676). We conducted an integrated analysis using whole-genome sequencing (WGS) and flow cytometry in patients with RRMM. WGS before and after treatment pinpointed genomic drivers associated with early progression, including RPL5 loss, APOBEC mutagenesis, and gain of function structural variants involving MYC and chromothripsis. Flow cytometry on 202 blood samples, collected every 3 months until progression for 31 patients, revealed distinct immune changes significantly impacting clinical outcomes. Progressing patients exhibited significant depletion of CD38-positive NK cells, persistence of T-cell exhaustion, and reduced depletion of regulatory T cells over time. These findings underscore the influence of immune composition and daratumumab-induced immune changes in promoting MM resistance. Integrating genomics and flow cytometry unveiled associations between adverse genomic features and immune patterns. Overall, this study sheds light on the intricate interplay between genomic complexity and the immune microenvironment driving resistance to Dara-Rd in patients with RRMM.

Immune dysfunction prior to and during vaccination in multiple myeloma: a case study based on COVID-19

Infection is the leading cause of death in multiple myeloma (MM). However, the cellular composition associated with immune dysfunction is not defined. We analyzed immune profiles in the peripheral blood of patients with MM (n = 28) and B-cell chronic lymphoproliferative disorders (n = 53) vs. health care practitioners (n = 96), using multidimensional and computational flow cytometry. MM patients displayed altered distribution of most cell types (41/56, 73%), particularly within the B-cell (17/17) and T-cell (20/30) compartments. Using COVID-19 as a case study, we compared the immune response to vaccination based on 64,304 data points generated from the analysis of 1099 longitudinal samples. MM patients showed limited B-cell expansion linked to lower anti-RBD and anti-S antibody titers after the first two doses and booster. The percentages of B cells and CD4+ T cells in the blood, as well as the absolute counts of B cells and dendritic cells, predicted vaccine immunogenicity at different time points. In contrast with the humoral response, the percentage and antigen-dependent differentiation of SARS-CoV-2-specific CD8+ T cells was not altered in MM patients. Taken together, this study defined the cellular composition associated with immune dysfunction in MM and provided biomarkers such as the B-cell percentage and absolute count to individualize vaccination calendars.

Identification of potential immune-related mechanisms related to the development of multiple myeloma

BACKGROUND

Although significant advances have been made in the treatment of multiple myeloma (MM), leading to unprecedented response and survival rates among patients, the majority eventually relapse, and a cure remains elusive. This situation is closely related to an incomplete understanding of the immune microenvironment, especially monocytes/macrophages in patients with treatment-naïve MM. The aim of this study was to provide insight into the immune microenvironment, especially monocytes/macrophages, in patients with treatment-naïve MM.

METHODS

This study used the single-cell RNA sequencing (scRNA-seq) data of both patients with MM and heathy donors to identify immune cells, including natural killer (NK) cells, T cells, dendritic cells (DCs), and monocytes/macrophages. Transcriptomic data and flow cytometry analysis of monocytes/macrophages were used to further examine the effect of monocytes/macrophages in treatment-naïve MM patients.

RESULTS

A significant difference was observed between the bone marrow (BM) immune cells of the healthy controls and treatment-naïve MM patients through scRNA-seq. It is noteworthy that, through an scRNA-seq data analysis, this study found that interferon (IFN)-induced NK/T cells, terminally differentiated effector memory (TEMRA) cells, T-helper cells characterized by expression of IFN-stimulated genes (ISG + Th cells), IFN-responding exhausted T cells, mannose receptor C-type 1 (MRC1) + DCs, IFN-responding DCs, MHCII + DCs, and immunosuppressive monocytes/macrophages were enriched in patients with treatment-naïve MM. Significantly, transcriptomic data of monocytes/macrophages demonstrated that "don't eat me"-related genes and IFN-induced genes increase in treatment-naïve MM patients. Furthermore, scRNA-seq, transcriptomic data, and flow cytometry also showed an increased proportion of CD16 + monocytes/macrophages and expression level of CD16. Cell-cell communication analysis indicated that monocytes/macrophages, whose related important signaling pathways include migration inhibitory factor (MIF) and interleukin 16 (IL-16) signaling pathway, are key players in treatment-naïve MM patients.

CONCLUSIONS

Our findings provide a comprehensive and in-depth molecular characterization of BM immune cell census in MM patients, especially for monocytes/macrophages. Targeting macrophages may be a novel treatment strategy for patients with MM.

DeepIMAGER: Deeply Analyzing Gene Regulatory Networks from scRNA-seq Data

Understanding the dynamics of gene regulatory networks (GRNs) across diverse cell types poses a challenge yet holds immense value in unraveling the molecular mechanisms governing cellular processes. Current computational methods, which rely solely on expression changes from bulk RNA-seq and/or scRNA-seq data, often result in high rates of false positives and low precision. Here, we introduce an advanced computational tool, DeepIMAGER, for inferring cell-specific GRNs through deep learning and data integration. DeepIMAGER employs a supervised approach that transforms the co-expression patterns of gene pairs into image-like representations and leverages transcription factor (TF) binding information for model training. It is trained using comprehensive datasets that encompass scRNA-seq profiles and ChIP-seq data, capturing TF-gene pair information across various cell types. Comprehensive validations on six cell lines show DeepIMAGER exhibits superior performance in ten popular GRN inference tools and has remarkable robustness against dropout-zero events. DeepIMAGER was applied to scRNA-seq datasets of multiple myeloma (MM) and detected potential GRNs for TFs of RORC, MITF, and FOXD2 in MM dendritic cells. This technical innovation, combined with its capability to accurately decode GRNs from scRNA-seq, establishes DeepIMAGER as a valuable tool for unraveling complex regulatory networks in various cell types.

Dual role of signaling pathways in myeloma requires cell type-specific targeting of ligand-receptor interactions

ABSTRACT

Although most patients with multiple myeloma respond to treatment initially, therapy resistance develops almost invariably, and only a subset of patients show durable responses to immunomodulatory therapies. Although the immune microenvironment has been extensively studied in patients with myeloma, its composition is currently not used as prognostic markers in clinical routine. We hypothesized that the outcome of immune signaling pathway engagement can be highly variable, depending on which 2 cellular populations participate in this interaction. This would have important prognostic and therapeutic implications, suggesting that it is crucial for immune pathways to be targeted in a specific cellular context. To test this hypothesis, we investigated a cohort of 25 patients with newly diagnosed multiple myeloma. We examined the complex regulatory networks within the immune compartment and their impact on disease progression. Analysis of immune cell composition and expression profiles revealed significant differences in the B-cell compartment associated with treatment response. Transcriptional states in patients with short time to progression demonstrated an enrichment of pathways promoting B-cell differentiation and inflammatory responses, which may indicate immune dysfunction. Importantly, the analysis of molecular interactions within the immune microenvironment highlights the dual role of signaling pathways, which can either be associated with good or poor prognosis depending on the cell types involved. Our findings therefore argue that therapeutic strategies targeting ligand-receptor interactions should take into consideration the composition of the microenvironment and the specific cell types involved in molecular interactions.

Loss of GABARAP mediates resistance to immunogenic chemotherapy in multiple myeloma

ABSTRACT

Immunogenic cell death (ICD) is a form of cell death by which cancer treatments can induce a clinically relevant antitumor immune response in a broad range of cancers. In multiple myeloma (MM), the proteasome inhibitor bortezomib is an ICD inducer and creates durable therapeutic responses in patients. However, eventual relapse and resistance to bortezomib appear inevitable. Here, by integrating patient transcriptomic data with an analysis of calreticulin (CRT) protein interactors, we found that GABA type A receptor-associated protein (GABARAP) is a key player whose loss prevented tumor cell death from being perceived as immunogenic after bortezomib treatment. GABARAP is located on chromosome 17p, which is commonly deleted in patients with high risk MM. GABARAP deletion impaired the exposure of the eat-me signal CRT on the surface of dying MM cells in vitro and in vivo, thus reducing tumor cell phagocytosis by dendritic cells and the subsequent antitumor T-cell response. Low GABARAP was independently associated with shorter survival in patients with MM and reduced tumor immune infiltration. Mechanistically, we found that GABARAP deletion blocked ICD signaling by decreasing autophagy and altering Golgi apparatus morphology, with consequent defects in the downstream vesicular transport of CRT. Conversely, upregulating autophagy using rapamycin restored Golgi morphology, CRT exposure, and ICD signaling in GABARAPKO cells undergoing bortezomib treatment. Therefore, coupling an ICD inducer, such as bortezomib, with an autophagy inducer, such as rapamycin, may improve patient outcomes in MM, in which low GABARAP in the form of del(17p) is common and leads to worse outcomes.

Tumor initiation and early tumorigenesis: molecular mechanisms and interventional targets

Tumorigenesis is a multistep process, with oncogenic mutations in a normal cell conferring clonal advantage as the initial event. However, despite pervasive somatic mutations and clonal expansion in normal tissues, their transformation into cancer remains a rare event, indicating the presence of additional driver events for progression to an irreversible, highly heterogeneous, and invasive lesion. Recently, researchers are emphasizing the mechanisms of environmental tumor risk factors and epigenetic alterations that are profoundly influencing early clonal expansion and malignant evolution, independently of inducing mutations. Additionally, clonal evolution in tumorigenesis reflects a multifaceted interplay between cell-intrinsic identities and various cell-extrinsic factors that exert selective pressures to either restrain uncontrolled proliferation or allow specific clones to progress into tumors. However, the mechanisms by which driver events induce both intrinsic cellular competency and remodel environmental stress to facilitate malignant transformation are not fully understood. In this review, we summarize the genetic, epigenetic, and external driver events, and their effects on the co-evolution of the transformed cells and their ecosystem during tumor initiation and early malignant evolution. A deeper understanding of the earliest molecular events holds promise for translational applications, predicting individuals at high-risk of tumor and developing strategies to intercept malignant transformation.

Mechanisms of resistance to bispecific T-cell engagers in multiple myeloma and their clinical implications

ABSTRACT

Bispecific T-cell engagers (TCEs) are revolutionizing patient care in multiple myeloma (MM). These monoclonal antibodies, that redirect T cells against cancer cells, are now approved for the treatment of triple-class exposed relapsed/refractory MM (RRMM). They are currently tested in earlier lines of the disease, including in first line. Yet, primary resistance occurs in about one-third of patients with RRMM, and most responders eventually develop acquired resistance. Understanding the mechanisms of resistance to bispecific TCE is thus essential to improve immunotherapies in MM. Here, we review recent studies investigating the clinical and molecular determinants of resistance to bispecific TCE. Resistance can arise from tumor-intrinsic or tumor-extrinsic mechanisms. Tumor-intrinsic resistance involves various alterations leading to the loss of the target antigen, such as chromosome deletions, point mutations, or epigenetic silencing. Loss of major histocompatibility complex (MHC) class I, preventing MHC class I: T-cell receptor (TCR) costimulatory signaling, was also reported. Tumor-extrinsic resistance involves abundant exhausted T-cell clones and several factors generating an immunosuppressive microenvironment. Importantly, some resistance mechanisms impair response to 1 TCE while preserving the efficacy of others. We next discuss the clinical implications of these findings. Monitoring the status of target antigens in tumor cells and their immune environment will be key to select the most appropriate TCE for each patient and to design combination and sequencing strategies for immunotherapy in MM.

Construction of the prediction model for multiple myeloma based on machine learning

INTRODUCTION

The global burden of multiple myeloma (MM) is increasing every year. Here, we have developed machine learning models to provide a reference for the early detection of MM.

METHODS

A total of 465 patients and 150 healthy controls were enrolled in this retrospective study. Based on the variable screening strategy of least absolute shrinkage and selection operator (LASSO), three prediction models, logistic regression (LR), support vector machine (SVM), and random forest (RF), were established combining complete blood count (CBC) and cell population data (CPD) parameters in the training set (210 cases), and were verified in the validation set (90 cases) and test set (165 cases). The performance of each model was analyzed using receiver operating characteristic (ROC) curve, calibration curves, and decision curve analysis (DCA). Accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the ROC curve (AUC) were applied to evaluate the models. Delong test was used to compare the AUC of the models.

RESULTS

Six parameters including RBC (1012/L), RDW-CV (%), IG (%), NE-WZ, LY-WX, and LY-WZ were screened out by LASSO to construct the model. Among the three models, the AUC of RF model in the training set, validation set, and test set were 0.956, 0.892, and 0.875, which were higher than those of LR model (0.901, 0.849, and 0.858) and SVM model (0.929, 0.868, and 0.846). Delong test showed that there were significant differences among the models in the training set, no significant differences in the validation set, and significant differences only between SVM and RF models in the test set. The calibration curve and DCA showed that the three models had good validity and feasibility, and the RF model performed best.

CONCLUSION

The proposed RF model may be a useful auxiliary tool for rapid screening of MM patients.

Autoimmune Diseases and Plasma Cells Dyscrasias: Pathogenetic, Molecular and Prognostic Correlations

Multiple myeloma and monoclonal gammopathy of undetermined significance are plasma cell dyscrasias characterized by monoclonal proliferation of pathological plasma cells with uncontrolled production of immunoglobulins. Autoimmune pathologies are conditions in which T and B lymphocytes develop a tendency to activate towards self-antigens in the absence of exogenous triggers. The aim of our review is to show the possible correlations between the two pathological aspects. Molecular studies have shown how different cytokines that either cause inflammation or control the immune system play a part in the growth of immunotolerance conditions that make it easier for the development of neoplastic malignancies. Uncontrolled immune activation resulting in chronic inflammation is also known to be at the basis of the evolution toward neoplastic pathologies, as well as multiple myeloma. Another point is the impact that myeloma-specific therapies have on the course of concomitant autoimmune diseases. Indeed, cases have been observed of patients suffering from multiple myeloma treated with daratumumab and bortezomib who also benefited from their autoimmune condition or patients under treatment with immunomodulators in which there has been an arising or worsening of autoimmunity conditions. The role of bone marrow transplantation in the course of concomitant autoimmune diseases remains under analysis.

Immune status and selection of patients for immunotherapy in myeloma: a proposal

ABSTRACT

Newer immune-based approaches based on recruitment and redirection of endogenous and/or synthetic immunity such as chimeric antigen receptor T cells or bispecific antibodies are transforming the clinical management of multiple myeloma (MM). Contributions of the immune system to the antitumor effects of myeloma therapies are also increasingly appreciated. Clinical malignancy in MM originates in the setting of systemic immune alterations that begin early in myelomagenesis and regional changes in immunity affected by spatial contexture. Preexisting and therapy-induced changes in immune cells correlate with outcomes in patients with MM including after immune therapies. Here, we discuss insights from and limitations of available data about immune status and outcomes after immune therapies in patients with MM. Preexisting variation in systemic and/or regional immunity is emerging as a major determinant of the efficacy of current immune therapies as well as vaccines. However, MM is a multifocal malignancy. As with solid tumors, integrating spatial aspects of the tumor and consideration of immune targets with the biology of immune cells may be critical to optimizing the application of immune therapy, including T-cell redirection, in MM. We propose 5 distinct spatial immune types of MM that may provide an initial framework for the optimal application of specific immune therapies in MM: immune depleted, immune permissive, immune excluded, immune suppressed, and immune resistant. Such considerations may also help optimize rational patient selection for emerging immune therapies to improve outcomes.

Smoldering multiple myeloma: taking the narrow over the wide path?

ABSTRACT

Smoldering multiple myeloma (MM) is an asymptomatic clonal plasma cell condition considered as a premalignant entity that may evolve over time to symptomatic MM. Based on a "poorly defined" risk of progression, some well-intended investigators proposed prospective interventional trials for these individuals. We believe this may be a harmful intervention and favor a close "wait and watch" approach and rather enroll these patients in dedicated observational biological studies aiming to better identify patients who will evolve to MM, based on their plasma cells' biology, including genomics, epigenetics, and the immune microenvironment.

1q amplification and PHF19 expressing high-risk cells are associated with relapsed/refractory multiple myeloma

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.

Multiplex immunohistochemistry elucidates increased distance between cytotoxic T cells and plasma cells in relapsed myeloma, and identifies Lag-3 as the most common checkpoint receptor on cytotoxic T cells of myeloma patients

A dysfunctional immune tumor microenvironment facilitates disease progression in multiple myeloma (MM). Using multiplex immunohistochemistry (mIHC), we describe the quantitative and qualitative changes in CD3+CD8+ cytotoxic T cells and assess their proximity to malignant plasma cells (PC) in patients with monoclonal gammopathy of undetermined significance (MGUS), and newly diagnosed (ND) and relapsed and/or refractory (RR) MM. Formalin-fixed, paraffin-embedded trephine sections from patients with MGUS (N=32), NDMM (N=65), and RRMM (N=59) were sequentially stained for CD138, CD3, CD8, and checkpoint receptors (CPR) Tim-3, Lag-3, and PD-1. The Halo® image analysis platform was used for cell segmentation and phenotyping, facilitating enumeration of cytotoxic T cells and analysis of proximity to PC. The percentage of CD8+ cytotoxic T cells in proximity to PC is greater in patients with NDMM than patients with RRMM (at 50 μm distance, 90.8% vs. 81.5%; P=0.038). There is a trend for more CD3+ T cells in MGUS (P=0.08) but no difference was observed in the prevalence of CD8+ cytotoxic T cells (P=0.48). Lag-3 is the most common CPR expressed on cytotoxic T cells in myeloma (P<0.0001), while PD-1 is the most common CPR on CD8- T cells of patients with MGUS and RRMM. Our study is the first to report on the spatial relationship between T cells and PC using mIHC on FFPE bone marrow trephine sections from patients with PC dyscrasia. The proximity of T cells to PC during early stages of MM, and overexpression of Lag-3, validate the move of immune therapeutic strategies, including T-cell engagers and checkpoint inhibitors, to upfront treatment or in early-line treatment of MM.

Single-cell multiomic dissection of response and resistance to chimeric antigen receptor T cells against BCMA in relapsed multiple myeloma

Markers that predict response and resistance to chimeric antigen receptor (CAR) T cells in relapsed/refractory multiple myeloma are currently missing. We subjected mononuclear cells isolated from peripheral blood and bone marrow before and after the application of approved B cell maturation antigen-directed CAR T cells to single-cell multiomic analyses to identify markers associated with resistance and early relapse. Differences between responders and nonresponders were identified at the time of leukapheresis. Nonresponders showed an immunosuppressive microenvironment characterized by increased numbers of monocytes expressing the immune checkpoint molecule CD39 and suppressed CD8+ T cell and natural killer cell function. Analysis of CAR T cells showed cytotoxic and exhausted phenotypes in hyperexpanded clones compared to low/intermediate expanded clones. We identified potential immunotherapy targets on CAR T cells, like PD1, to improve their functionality and durability. Our work provides evidence that an immunosuppressive microenvironment causes resistance to CAR T cell therapies in multiple myeloma.

Exploring natural killer cell-related biomarkers in multiple myeloma: a novel nature killer cell-related model predicting prognosis and immunotherapy response using single-cell study

BACKGROUND

Natural killer cells (NKs) may be involved in multiple myeloma (MM) progression. The present study elucidated the correlation between NKs and the progression of MM using single-cell binding transcriptome probes to identify NK cell-related biomarkers.

METHODS

Single-cell analysis was performed including cell and subtype annotation, cell communication, and pseudotime analysis. Hallmark pathway enrichment analysis of NKs and NKs-related differentially expressed genes (DEGs) were conducted using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction (PPI) networks. Then, a risk model was structured based on biomarkers identified through univariate Cox regression analysis and least absolute shrinkage and selection operator regression analysis and subsequently validated. Additionally, correlation of clinical characteristics, gene set enrichment analysis, immune analysis, regulatory network, and drug forecasting were explored.

RESULTS

A total of 13 cell clusters were obtained and annotated, including 8 cell populations that consisted of NKs. Utilizing 123 PPI network node genes, 8 NK-related DEGs were selected to construct a prognostic model. Immune cell infiltration results suggested that 11 immune cells exhibited marked differences in the high and low-risk groups. Finally, the model was used to screen potential drug targets to enhance immunotherapy efficacy.

CONCLUSION

A new prognostic model for MM associated with NKs was constructed and validated. This model provides a fresh perspective for predicting patient outcomes, immunotherapeutic response, and candidate drugs.

CD8 effector T cells enhance teclistamab response in BCMA-exposed and -naïve multiple myeloma

ABSTRACT

Teclistamab, a B-cell maturation antigen (BCMA)- and CD3-targeting bispecific antibody, is an effective novel treatment for relapsed/refractory multiple myeloma (R/RMM), but efficacy in patients exposed to BCMA-directed therapies and mechanisms of resistance have yet to be fully delineated. We conducted a real-world retrospective study of commercial teclistamab, capturing both clinical outcomes and immune correlates of treatment response in a cohort of patients (n = 52) with advanced R/RMM. Teclistamab was highly effective with an overall response rate (ORR) of 64%, including an ORR of 50% for patients with prior anti-BCMA therapy. Pretreatment plasma cell BCMA expression levels had no bearing on response. However, comprehensive pretreatment immune profiling identified that effector CD8+ T-cell populations were associated with response to therapy and a regulatory T-cell population associated with nonresponse, indicating a contribution of immune status in outcomes with potential utility as a biomarker signature to guide patient management.

Impact of Clonal Heterogeneity in Multiple Myeloma

Multiple myeloma is characterized by a highly heterogeneous disease distribution within the bone marrow-containing skeletal system. In this review, we introduce the molecular mechanisms underlying clonal heterogeneity and the spatio-temporal evolution of myeloma. We discuss the clinical impact of clonal heterogeneity, which is thought to be one of the biggest obstacles to overcome therapy resistance and to achieve cure.

Immune-Pathogenesis of Myeloma

This research indicates that monoclonal gammopathy of undetermined significance (MGUS) and myeloma may stem from chronic immune activation and inflammation, causing immune dysfunction and spatial immune exclusion. As the conditions progress, a shift toward myeloma involves ongoing immune impairment, affecting both innate and adaptive immunity. Intriguingly, even in advanced myeloma stages, susceptibility to immune effector cells persists. This insight highlights the intricate interplay between immune responses and the development of these conditions, paving the way for potential therapeutic interventions targeting immune modulation in the management of MGUS and myeloma.

A patient with minimal myeloma treatment who survived for 20 years

Not available.

Approach to High-Risk Multiple Myeloma

Improving the outcome of high-risk myeloma (HRMM) is a key therapeutic aim for the next decade. To achieve this aim, it is necessary to understand in detail the genetic drivers underlying this clinical behavior and to target its biology therapeutically. Advances have already been made, with a focus on consensus guidance and the application of novel immunotherapeutic approaches. Cases of HRMM are likely to have impaired prognosis even with novel strategies. However, if disease eradication and minimal disease states are achieved, then cure may be possible.

Single-cell analysis of the CD8+ T-cell compartment in multiple myeloma reveals disease specific changes are chiefly restricted to a CD69- subset suggesting potent cytotoxic effectors exist within the tumor bed

Multiple myeloma (MM) is an incurable disease of the bone marrow (BM) characterized by the uncontrolled proliferation of neoplastic plasma cells. While CD8+ T cells have an established role in disease control, few studies have focused on these cells within the MM tumor microenvironment (TME). We analyzed CD8+ T cells in the BM and peripheral blood (PB) of untreated patients with MM and non-myeloma controls using flow cytometry, mass cytometry and single-cell RNA sequencing, using several novel bioinformatics workflows. Inter-tissue differences were most evident in the differential expression of Granzymes B and K, which were strongly associated with two distinct subsets of CD8+ T cells delineated by the expression of CD69, accounting for roughly 50% of BM-CD8+ T cells of all assessed cohorts. While few differences were observable between health and disease in the BM-restricted CD8CD69+ T-cell subset, the CD8+CD69- T-cell subset in the BM of untreated MM patients demonstrated increased representation of highly differentiated effector cells and evident compositional parallels between the PB, absent in age-matched controls, where a marked reduction of effector cells was observed. We demonstrate the transcriptional signature of BM-CD8+ T cells from patients with MM more closely resembles TCR-activated CD8+ T cells from age-matched controls than their resting counterparts.

Advances and challenges in cancer immunoprevention and immune interception

Invasive cancers typically evade immune surveillance through profound local and systemic immunosuppression, preventing their elimination or control. Targeting immune interventions to prevent or intercept premalignant lesions, before significant immune dysregulation has occurred, may be a more successful strategy. The field of cancer immune interception and prevention is nascent, and the scientific community has been slow to embrace this potentially most rational approach to reducing the global burden of cancer. This may change due to recent promising advances in cancer immunoprevention including the use of vaccines for the prevention of viral cancers, the use of cancer-associated antigen vaccines in the setting of precancers, and the development of cancer-preventative vaccines for high-risk individuals who are healthy but carry cancer-associated heritable genetic mutations. Furthermore, there is increasing recognition of the importance of cancer prevention and interception by national cancer organizations. The National Cancer Institute (NCI) recently released the National Cancer Plan, which includes cancer prevention among the top priorities of the institute. The NCI's Division of Cancer Prevention has been introducing new funding opportunities for scientists with an interest in the field of cancer prevention: The Cancer Prevention-Interception Targeted Agent Discovery Program and The Cancer Immunoprevention Network. Moreover, the Human Tumor Atlas Network is spearheading the development of a precancer atlas to better understand the biology of pre-invasive changes, including the tissue microenvironment and the underlying genetics that drive carcinogenesis. These data will inform the development of novel immunoprevention/immuno-interception strategies. International cancer foundations have also started recognizing immunoprevention and immune interception with the American Association for Cancer Research, Cancer Research UK and the Society for Immunotherapy of Cancer each implementing programming focused on this area. This review will present recent advances, opportunities, and challenges in the emerging field of cancer immune prevention and immune interception.

The bone ecosystem facilitates multiple myeloma relapse and the evolution of heterogeneous drug resistant disease

Multiple myeloma (MM) is an osteolytic malignancy that is incurable due to the emergence of treatment resistant disease. Defining how, when and where myeloma cell intrinsic and extrinsic bone microenvironmental mechanisms cause relapse is challenging with current biological approaches. Here, we report a biology-driven spatiotemporal hybrid agent-based model of the MM-bone microenvironment. Results indicate MM intrinsic mechanisms drive the evolution of treatment resistant disease but that the protective effects of bone microenvironment mediated drug resistance (EMDR) significantly enhances the probability and heterogeneity of resistant clones arising under treatment. Further, the model predicts that targeting of EMDR deepens therapy response by eliminating sensitive clones proximal to stroma and bone, a finding supported by in vivo studies. Altogether, our model allows for the study of MM clonal evolution over time in the bone microenvironment and will be beneficial for optimizing treatment efficacy so as to significantly delay disease relapse.

SOHO State of the Art Updates and Next Questions: Diagnosis and Management of Monoclonal Gammopathy of Undetermined Significance and Smoldering Multiple Myeloma

Monoclonal proteins are common, with a prevalence in the United States around 5% and the incidence increases with age. Although most patients are asymptomatic, the vast majority of cases are caused by a clonal plasma cell disorder. Monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM) are asymptomatic precursor conditions with variable risk of progression to multiple myeloma (MM). In recent years, significant progress has been made to better understand the factors that lead to the development of symptoms and progression to myeloma. In this review, we summarize the current diagnosis treatment guidelines for MGUS and SMM and highlight recent advances that underscore a shifting paradigm in the evaluation and management of plasma cell precursor conditions.

Bone marrow inflammation in haematological malignancies

Tissue inflammation is a hallmark of tumour microenvironments. In the bone marrow, tumour-associated inflammation impacts normal niches for haematopoietic progenitor cells and mature immune cells and supports the outgrowth and survival of malignant cells residing in these niche compartments. This Review provides an overview of our current understanding of inflammatory changes in the bone marrow microenvironment of myeloid and lymphoid malignancies, using acute myeloid leukaemia and multiple myeloma as examples and highlights unique and shared features of inflammation in niches for progenitor cells and plasma cells. Importantly, inflammation exerts profoundly different effects on normal bone marrow niches in these malignancies, and we provide context for possible drivers of these divergent effects. We explore the role of tumour cells in inflammatory changes, as well as the role of cellular constituents of normal bone marrow niches, including myeloid cells and stromal cells. Integrating knowledge of disease-specific dynamics of malignancy-associated bone marrow inflammation will provide a necessary framework for future targeting of these processes to improve patient outcome.

Regulatory T cells hamper the efficacy of T-cell-engaging bispecific antibody therapy

T-cell-engaging bispecific antibodies (T-BsAb) have produced impressive clinical responses in patients with relapsed/refractory B-cell malignancies, although treatment failure remains a major clinical challenge. Growing evidence suggests that a complex interplay between immune cells and tumor cells is implicated in the mechanism of action and therefore, understanding immune regulatory mechanisms might provide a clue for how to improve the efficacy of T-BsAb therapy. Here, we investigated the functional impact of regulatory T (Treg) cells on anti-tumor immunity elicited by T-BsAb therapy. In a preclinical model of myeloma, the activation and expansion of Treg cells in the bone marrow were observed in response to anti-B-cell maturation antigen (BCMA) T-BsAb therapy. T-BsAb triggered the generation of induced Treg cells from human conventional CD4 cells after co-culture with tumor cells. Moreover, T-BsAb directly activated freshly isolated circulating Treg cells, leading to the production of interleukin-10 and inhibition of T-BsAb-mediated CD8 T-cell responses. The activation of Treg cells was also seen in bone marrow samples from myeloma patients after ex vivo treatment with T-BsAb, further supporting that T-BsAb have an impact on Treg homeostasis. Importantly, transient ablation of Treg cells in combination with T-BsAb therapy dramatically improved effector lymphocyte activities and disease control in the preclinical myeloma model, leading to prolonged survival. Together, this information suggests that therapy-induced activation of Treg cells critically regulates anti-tumor immunity elicited by T-BsAb therapy, with important implications for improving the efficacy of such treatment.

Different evasion strategies in multiple myeloma

Multiple myeloma is the second most common malignant hematologic malignancy which evolved different strategies for immune escape from the host immune surveillance and drug resistance, including uncontrolled proliferation of malignant plasma cells in the bone marrow, genetic mutations, or deletion of tumor antigens to escape from special targets and so. Therefore, it is a big challenge to efficiently treat multiple myeloma patients. Despite recent applications of immunomodulatory drugs (IMiDS), protease inhibitors (PI), targeted monoclonal antibodies (mAb), and even hematopoietic stem cell transplantation (HSCT), it remains hardly curable. Summarizing the possible evasion strategies can help design specific drugs for multiple myeloma treatment. This review aims to provide an integrative overview of the intrinsic and extrinsic evasion mechanisms as well as recently discovered microbiota utilized by multiple myeloma for immune evasion and drug resistance, hopefully providing a theoretical basis for the rational design of specific immunotherapies or drug combinations to prevent the uncontrolled proliferation of MM, overcome drug resistance and improve patient survival.

Integrative analysis of neuroblastoma by single-cell RNA sequencing identifies the NECTIN2-TIGIT axis as a target for immunotherapy

Pediatric patients with high-risk neuroblastoma have poor survival rates and urgently need more effective treatment options with less side effects. Since novel and improved immunotherapies may fill this need, we dissect the immunoregulatory interactions in neuroblastoma by single-cell RNA-sequencing of 24 tumors (10 pre- and 14 post-chemotherapy, including 5 pairs) to identify strategies for optimizing immunotherapy efficacy. Neuroblastomas are infiltrated by natural killer (NK), T and B cells, and immunosuppressive myeloid populations. NK cells show reduced cytotoxicity and T cells have a dysfunctional profile. Interaction analysis reveals a vast immunoregulatory network and identifies NECTIN2-TIGIT as a crucial immune checkpoint. Combined blockade of TIGIT and PD-L1 significantly reduces neuroblastoma growth, with complete responses (CR) in vivo. Moreover, addition of TIGIT+PD-L1 blockade to standard relapse treatment in a chemotherapy-resistant Th-ALKF1174L/MYCN 129/SvJ syngeneic model induces CR. In conclusion, our integrative analysis provides promising targets and a rationale for immunotherapeutic combination strategies.

Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies

Bone marrow trephine biopsy is crucial for the diagnosis of multiple myeloma. However, the complexity of bone marrow cellular, morphologic, and spatial architecture preserved in trephine samples hinders comprehensive evaluation. To dissect the diverse cellular communities and mosaic tissue habitats, we developed a superpixel-inspired deep learning method (MoSaicNet) that adapts to complex tissue architectures and a cell imbalance aware deep learning pipeline (AwareNet) to enable accurate detection and classification of rare cell types in multiplex immunohistochemistry images. MoSaicNet and AwareNet achieved an AUC of >0.98 for tissue and cellular classification on separate test datasets. Application of MoSaicNet and AwareNet enabled investigation of bone heterogeneity and thickness as well as spatial histology analysis of bone marrow trephine samples from monoclonal gammopathies of undetermined significance (MGUS) and from paired newly diagnosed and posttreatment multiple myeloma. The most significant difference between MGUS and newly diagnosed multiple myeloma (NDMM) samples was not related to cell density but to spatial heterogeneity, with reduced spatial proximity of BLIMP1+ tumor cells to CD8+ cells in MGUS compared with NDMM samples. Following treatment of patients with multiple myeloma, there was a reduction in the density of BLIMP1+ tumor cells, effector CD8+ T cells, and regulatory T cells, indicative of an altered immune microenvironment. Finally, bone heterogeneity decreased following treatment of patients with multiple myeloma. In summary, deep learning-based spatial mapping of bone marrow trephine biopsies can provide insights into the cellular topography of the myeloma marrow microenvironment and complement aspirate-based techniques.

SIGNIFICANCE

Spatial analysis of bone marrow trephine biopsies using histology, deep learning, and tailored algorithms reveals the bone marrow architectural heterogeneity and evolution during myeloma progression and treatment.

Novel Insights into the Initiation, Evolution, and Progression of Multiple Myeloma by Multi-Omics Investigation

The evolutionary history of multiple myeloma (MM) includes malignant transformation, followed by progression to pre-malignant stages and overt malignancy, ultimately leading to more aggressive and resistant forms. Over the past decade, large effort has been made to identify the potential therapeutic targets in MM. However, MM remains largely incurable. Most patients experience multiple relapses and inevitably become refractory to treatment. Tumor-initiating cell populations are the postulated population, leading to the recurrent relapses in many hematological malignancies. Clonal evolution of tumor cells in MM has been identified along with the disease progression. As a consequence of different responses to the treatment of heterogeneous MM cell clones, the more aggressive populations survive and evolve. In addition, the tumor microenvironment is a complex ecosystem which plays multifaceted roles in supporting tumor cell evolution. Emerging multi-omics research at single-cell resolution permits an integrative and comprehensive profiling of the tumor cells and microenvironment, deepening the understanding of biological features of MM. In this review, we intend to discuss the novel insights into tumor cell initiation, clonal evolution, drug resistance, and tumor microenvironment in MM, as revealed by emerging multi-omics investigations. These data suggest a promising strategy to unravel the pivotal mechanisms of MM progression and enable the improvement in treatment, both holistically and precisely.

Bispecific BCMA/CD24 CAR-T cells control multiple myeloma growth

Anti-multiple myeloma B cell maturation antigen (BCMA)-specific chimeric antigen receptor (CAR) T-cell therapies represent a promising treatment strategy with high response rates in myeloma. However, durable cures following anti-BCMA CAR-T cell treatment of myeloma are rare. One potential reason is that a small subset of minimal residual myeloma cells seeds relapse. Residual myeloma cells following BCMA-CAR-T-mediated treatment show less-differentiated features and express stem-like genes, including CD24. CD24-positive myeloma cells represent a large fraction of residual myeloma cells after BCMA-CAR-T therapy. In this work, we develop CD24-CAR-T cells and test their ability to eliminate myeloma cells. We find that CD24-CAR-T cells block the CD24-Siglec-10 pathway, thereby enhancing macrophage phagocytic clearance of myeloma cells. Additionally, CD24-CAR-T cells polarize macrophages to a M1-like phenotype. A dual-targeted BCMA-CD24-CAR-T exhibits improved efficacy compared to monospecific BCMA-CAR-T-cell therapy. This work presents an immunotherapeutic approach that targets myeloma cells and promotes tumor cell clearance by macrophages.

Clearing soluble MIC reverses the impaired function of natural killer cells from patients with multiple myeloma

BACKGROUND

Major histocompatibility complex (MHC) class I chain-related protein (MIC) is a stress-induced ligand released from multiple myeloma (MM) cells during progression, and soluble MIC impairs natural killer group 2D (NKG2D) activating receptor-mediated recognition and function of natural killer (NK) cells. However, whether clearing soluble MIC with a monoclonal antibody (mAb) can restore NK cell activity of MM patients remains undetermined.

METHODS

We analyzed The Cancer Genome Atlas (TCGA) Multiple Myeloma Research Foundation (MMRF) CoMMpass data set to examine the prognostic significance of MIC expression in MM. We examined the level of soluble MIC in paired peripheral blood (PB) and bone marrow (BM) plasma of patients with MM at diagnosis by ELISA. We evaluated the correlation between the level of soluble MIC and immunophenotype of NK cells from MM patients by multicolor flow cytometry. We also generated MIC-overexpressing MM cell line and characterized the cytotoxic function of patient NK cells in the presence of soluble MIC, and examined the impact of clearing soluble MIC with a humanized mAb (huB10G5).

RESULTS

We characterize the importance of MICA in MM by revealing the significantly better overall survival of patients with high MICA expression from TCGA MMRF CoMMpass data set. The level of soluble MICA is more highly elevated in MM than in precursor stages, and the concentration of soluble MICA is higher in BM plasma than in PB. The concentration of soluble MICA in BM was correlated with myeloma burden, while it was negatively correlated with the frequency of NKG2D+ NK cells in diagnostic BM aspirates of MM patients. Soluble MICA downregulated NKG2D expression and decreased cytotoxicity of MM patient NK cells ex vivo, which were reversed by a humanized soluble MIC-clearing mAb (huB10G5) with enhanced degranulation of NK cells.

CONCLUSIONS

Our findings indicate targeting soluble MIC with huB10G5 might be a viable therapeutic approach to promote NKG2D-dependent cellular immunotherapy outcome in MM.

Comprehensive Single-Cell Immune Profiling Defines the Patient Multiple Myeloma Microenvironment Following Oncolytic Virus Therapy in a Phase Ib Trial

PURPOSE

Our preclinical studies showed that the oncolytic reovirus formulation pelareorep (PELA) has significant immunomodulatory anti-myeloma activity. We conducted an investigator-initiated clinical trial to evaluate PELA in combination with dexamethasone (Dex) and bortezomib (BZ) and define the tumor immune microenvironment (TiME) in patients with multiple myeloma treated with this regimen.

PATIENTS AND METHODS

Patients with relapsed/refractory multiple myeloma (n = 14) were enrolled in a phase Ib clinical trial (ClinicalTrials.gov: NCT02514382) of three escalating PELA doses administered on Days 1, 2, 8, 9, 15, and 16. Patients received 40 mg Dex and 1.5 mg/m2 BZ on Days 1, 8, and 15. Cycles were repeated every 28 days. Pre- and posttreatment bone marrow specimens (IHC, n = 9; imaging mass cytometry, n = 6) and peripheral blood samples were collected for analysis (flow cytometry, n = 5; T-cell receptor clonality, n = 7; cytokine assay, n = 7).

RESULTS

PELA/BZ/Dex was well-tolerated in all patients. Treatment-emergent toxicities were transient, and no dose-limiting toxicities occurred. Six (55%) of 11 response-evaluable patients showed decreased paraprotein. Treatment increased T and natural killer cell activation, inflammatory cytokine release, and programmed death-ligand 1 expression in bone marrow. Compared with nonresponders, responders had higher reovirus protein levels, increased cytotoxic T-cell infiltration posttreatment, cytotoxic T cells in significantly closer proximity to multiple myeloma cells, and larger populations of a novel immune-primed multiple myeloma phenotype (CD138+ IDO1+HLA-ABCHigh), indicating immunomodulation.

CONCLUSIONS

PELA/BZ/Dex is well-tolerated and associated with anti-multiple myeloma activity in a subset of responding patients, characterized by immune reprogramming and TiME changes, warranting further investigation of PELA as an immunomodulator.

Genomic and immune determinants of resistance to anti-CD38 monoclonal antibody-based therapy in relapsed refractory multiple myeloma

Anti-CD38 antibody therapies have transformed multiple myeloma (MM) treatment. However, a large fraction of patients inevitably relapses. To understand this, we investigated 32 relapsed MM patients treated with daratumumab, lenalidomide, and dexamethasone (Dara-Rd; NCT03848676 ). Whole genome sequencing (WGS) before and after treatment pinpointed genomic drivers associated with early progression, including RPL5 loss and APOBEC mutagenesis. Flow cytometry on 202 blood samples, collected every three months until progression for 31 patients, revealed distinct immune changes significantly impacting clinical outcomes. Progressing patients exhibited significant depletion of CD38+ NK cells, persistence of T cell exhaustion, and reduced depletion of T-reg cells over time. These findings underscore the influence of immune composition and daratumumab-induced immune changes in promoting MM resistance. Integrating genomics and flow cytometry unveiled associations between adverse genomic features and immune patterns. Overall, this study sheds light on the intricate interplay between genomic complexity and the immune microenvironment driving resistance to Dara-Rd.

Randomized Phase II Trial of Dendritic Cell/Myeloma Fusion Vaccine with Lenalidomide Maintenance after Upfront Autologous Hematopoietic Cell Transplantation for Multiple Myeloma: BMT CTN 1401

PURPOSE

Vaccination with dendritic cell (DC)/multiple myeloma (MM) fusions has been shown to induce the expansion of circulating multiple myeloma-reactive lymphocytes and consolidation of clinical response following autologous hematopoietic cell transplant (auto-HCT).

PATIENTS AND METHODS

In this randomized phase II trial (NCT02728102), we assessed the effect of DC/MM fusion vaccination, GM-CSF, and lenalidomide maintenance as compared with control arms of GM-CSF and lenalidomide or lenalidomide maintenance alone on clinical response rates and induction of multiple myeloma-specific immunity at 1-year posttransplant.

RESULTS

The study enrolled 203 patients, with 140 randomized posttransplantation. Vaccine production was successful in 63 of 68 patients. At 1 year, rates of CR were 52.9% (vaccine) and 50% (control; P = 0.37, 80% CI 44.5%, 61.3%, and 41.6%, 58.4%, respectively), and rates of VGPR or better were 85.3% (vaccine) and 77.8% (control; P = 0.2). Conversion to CR at 1 year was 34.8% (vaccine) and 27.3% (control; P = 0.4). Vaccination induced a statistically significant expansion of multiple myeloma-reactive T cells at 1 year compared with before vaccination (P = 0.024) and in contrast to the nonvaccine arm (P = 0.026). Single-cell transcriptomics revealed clonotypic expansion of activated CD8 cells and shared dominant clonotypes between patients at 1-year posttransplant.

CONCLUSIONS

DC/MM fusion vaccination with lenalidomide did not result in a statistically significant increase in CR rates at 1 year posttransplant but was associated with a significant increase in circulating multiple myeloma-reactive lymphocytes indicative of tumor-specific immunity. Site-specific production of a personalized cell therapy with centralized product characterization was effectively accomplished in the context of a multicenter cooperative group study. See related commentary by Qazilbash and Kwak, p. 4703.

Genomic and immune signatures predict clinical outcome in newly diagnosed multiple myeloma treated with immunotherapy regimens

Despite improving outcomes, 40% of patients with newly diagnosed multiple myeloma treated with regimens containing daratumumab, a CD38-targeted monoclonal antibody, progress prematurely. By integrating tumor whole-genome and microenvironment single-cell RNA sequencing from upfront phase 2 trials using carfilzomib, lenalidomide and dexamethasone with daratumumab ( NCT03290950 ), we show how distinct genomic drivers including high APOBEC mutational activity, IKZF3 and RPL5 deletions and 8q gain affect clinical outcomes. Furthermore, evaluation of paired bone marrow profiles, taken before and after eight cycles of carfilzomib, lenalidomide and dexamethasone with daratumumab, shows that numbers of natural killer cells before treatment, high T cell receptor diversity before treatment, the disappearance of sustained immune activation (that is, B cells and T cells) and monocyte expansion over time are all predictive of sustained minimal residual disease negativity. Overall, this study provides strong evidence of a complex interplay between tumor cells and the immune microenvironment that is predictive of clinical outcome and depth of treatment response in patients with newly diagnosed multiple myeloma treated with highly effective combinations containing anti-CD38 antibodies.

Personalized Medicine's Coming of Age: One Drug, One Patient

A dendritic cell/myeloma fusion vaccine, given with lenalidomide and GM-CSF, did not result in a statistically significant increase in CR rates at 1 year posttransplant but was associated with a significant increase in circulating multiple myeloma-reactive lymphocytes indicative of tumor-specific immunity. See related article by Chung et al., p. 4784.

γδ T cells: origin and fate, subsets, diseases and immunotherapy

The intricacy of diseases, shaped by intrinsic processes like immune system exhaustion and hyperactivation, highlights the potential of immune renormalization as a promising strategy in disease treatment. In recent years, our primary focus has centered on γδ T cell-based immunotherapy, particularly pioneering the use of allogeneic Vδ2+ γδ T cells for treating late-stage solid tumors and tuberculosis patients. However, we recognize untapped potential and optimization opportunities to fully harness γδ T cell effector functions in immunotherapy. This review aims to thoroughly examine γδ T cell immunology and its role in diseases. Initially, we elucidate functional differences between γδ T cells and their αβ T cell counterparts. We also provide an overview of major milestones in γδ T cell research since their discovery in 1984. Furthermore, we delve into the intricate biological processes governing their origin, development, fate decisions, and T cell receptor (TCR) rearrangement within the thymus. By examining the mechanisms underlying the anti-tumor functions of distinct γδ T cell subtypes based on γδTCR structure or cytokine release, we emphasize the importance of accurate subtyping in understanding γδ T cell function. We also explore the microenvironment-dependent functions of γδ T cell subsets, particularly in infectious diseases, autoimmune conditions, hematological malignancies, and solid tumors. Finally, we propose future strategies for utilizing allogeneic γδ T cells in tumor immunotherapy. Through this comprehensive review, we aim to provide readers with a holistic understanding of the molecular fundamentals and translational research frontiers of γδ T cells, ultimately contributing to further advancements in harnessing the therapeutic potential of γδ T cells.

Good Cop, Bad Cop: Profiling the Immune Landscape in Multiple Myeloma

Multiple myeloma (MM) is a dyscrasia of plasma cells (PCs) characterized by abnormal immunoglobulin (Ig) production. The disease remains incurable due to a multitude of mutations and structural abnormalities in MM cells, coupled with a favorable microenvironment and immune suppression that eventually contribute to the development of drug resistance. The bone marrow microenvironment (BMME) is composed of a cellular component comprising stromal cells, endothelial cells, osteoclasts, osteoblasts, and immune cells, and a non-cellular component made of the extracellular matrix (ECM) and the liquid milieu, which contains cytokines, growth factors, and chemokines. The bone marrow stromal cells (BMSCs) are involved in the adhesion of MM cells, promote the growth, proliferation, invasion, and drug resistance of MM cells, and are also crucial in angiogenesis and the formation of lytic bone lesions. Classical immunophenotyping in combination with advanced immune profiling using single-cell sequencing technologies has enabled immune cell-specific gene expression analysis in MM to further elucidate the roles of specific immune cell fractions from peripheral blood and bone marrow (BM) in myelomagenesis and progression, immune evasion and exhaustion mechanisms, and development of drug resistance and relapse. The review describes the role of BMME components in MM development and ongoing clinical trials using immunotherapeutic approaches.

Unravelling the imbalanced Th17-like cell differentiation by single-cell RNA sequencing in multiple myeloma

Multiple myeloma (MM) is a bone marrow resident hematological malignancy. T helper (Th) cells play an essential role in maladjustment of immune function and promotion of myeloma cell proliferation and survival, which has not been fully elucidated. Here, we compared transcriptome profiles of CD4+ T cells in bone marrow samples of 3 healthy individuals and 10 MM patients before and after treatment using single-cell RNA sequencing. CD4+ T cells were divided into 7 clusters. Imbalanced Th17-like cell differentiation was indicated in MM based on bioinformation analyses, which involved IL2-STAT5 pathways and transcription factors NKFB1, RELA, STAT3, and GTF2A2. Pseudotime trajectory analysis of CD4+ T cell clusters further uncovered the enhanced transition of Th17-like to regulatory T (Treg) cells in MM, which was featured by expression changes of PLAC8, NKFB1, RELA, STAT3, and STAT1 along with the developmental path. Reduced cell-cell interaction between MM cells and CD4+ naïve/recently activated naïve T cells via CD74-APP might lead to imbalanced Th17-like cell differentiation. Checkpoints via TIGIT-NECTIN3 and LGALS9-CD47 in Treg and MM cells were also identified. Our study reveals imbalanced differentiation pattern of Th17-like cells and the immunosuppressive profiles in connection with MM cells, which might help to shed light on CD4+ T cell function in MM.

Identification of a novel cuproptosis-related gene signature for multiple myeloma diagnosis

BACKGROUND

Multiple myeloma (MM) ranks second among the most prevalent hematological malignancies. Recent studies have unearthed the promise of cuproptosis as a novel therapeutic intervention for cancer. However, no research has unveiled the particular roles of cuproptosis-related genes (CRGs) in the prediction of MM diagnosis.

METHODS

Microarray data and clinical characteristics of MM patients were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed gene analysis, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms were applied to identify potential signature genes for MM diagnosis. Predictive performance was further assessed by receiver operating characteristic (ROC) curves, nomogram analysis, and external data sets. Functional enrichment analysis was performed to elucidate the involved mechanisms. Finally, the expression of the identified genes was validated by quantitative real-time polymerase chain reaction (qRT-PCR) in MM cell samples.

RESULTS

The optimal gene signature was identified using LASSO and SVM-RFE algorithms based on the differentially expressed CRGs: ATP7A, FDX1, PDHA1, PDHB, MTF1, CDKN2A, and DLST. Our gene signature-based nomogram revealed a high degree of accuracy in predicting MM diagnosis. ROC curves showed the signature had dependable predictive ability across all data sets, with area under the curve values exceeding 0.80. Additionally, functional enrichment analysis suggested significant associations between the signature genes and immune-related pathways. The expression of the genes was validated in MM cells, indicating the robustness of these findings.

CONCLUSION

We discovered and validated a novel CRG signature with strong predictive capability for diagnosing MM, potentially implicated in MM pathogenesis and progression through immune-related pathways.

Growth and dormancy control of myeloma cells by mesenchymal stem cells

Bone marrow mesenchymal stem cells (MSCs) may have contrasting impacts on the progression of multiple myeloma (MM). Priming normal MSCs, by culturing them with MM cells, mimics the MSC-induced MM growth. We studied the contrasting effects of conditioned medium (CM) from unprimed or primed MSCs on growth of MM cells from newly diagnosed cases. We elucidated potential molecular pathways using global gene expression profiling and focused on the role of the mTOR2 component, RICTOR, as a novel mediator of dormancy in MM. Primed MSCs CM consistently increased proportions of proliferating cells and supported MM growth in 3-day (n = 20) and 10-day (n = 12) cultures, effects that were partially mediated through the IGF1 axis. In contrast, unprimed MSCs CM inhibited growth of MM cells in cases mainly from stages I/II MM. The genes most overexpressed in MM cells treated with primed MSCs CM were associated with cell cycle, DNA-damage repair, and proliferation; genes most overexpressed in MM cells treated with unprimed MSCs CM were associated with dormancy pathways including RICTOR (mTOR2 pathway), CXCR4, and BCL2. RICTOR protein level was induced by unprimed MSCs CM and was lower in KI67+ proliferating MM cells treated with primed MSCs CM. RICTOR was underexpressed in clinical relapse samples compared with baseline samples of the same patients. Inhibiting RICTOR expression in primary MM cells promoted their growth, and enforced expression of RICTOR in MM cell lines inhibited their growth. Our findings suggest that, after prolonged interactions with MM cells, bone marrow MSCs shift from MM-repressive to MM-permissive. AVAILABILITY OF DATA AND MATERIALS: Our institutional GEP data of MM cells from newly diagnosed patients used to show RICTOR expression have been deposited at Gene Expression Omnibus (GEO: GSE2658, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE2658).

Essential procedures of single-cell RNA sequencing in multiple myeloma and its translational value

Multiple myeloma (MM) is a malignant neoplasm characterized by clonal proliferation of abnormal plasma cells. In many countries, it ranks as the second most prevalent malignant neoplasm of the hematopoietic system. Although treatment methods for MM have been continuously improved and the survival of patients has been dramatically prolonged, MM remains an incurable disease with a high probability of recurrence. As such, there are still many challenges to be addressed. One promising approach is single-cell RNA sequencing (scRNA-seq), which can elucidate the transcriptome heterogeneity of individual cells and reveal previously unknown cell types or states in complex tissues. In this review, we outlined the experimental workflow of scRNA-seq in MM, listed some commonly used scRNA-seq platforms and analytical tools. In addition, with the advent of scRNA-seq, many studies have made new progress in the key molecular mechanisms during MM clonal evolution, cell interactions and molecular regulation in the microenvironment, and drug resistance mechanisms in target therapy. We summarized the main findings and sequencing platforms for applying scRNA-seq to MM research and proposed broad directions for targeted therapies based on these findings.

The immunome of mobilized peripheral blood stem cells is predictive of long-term outcomes and therapy-related myeloid neoplasms in patients with multiple myeloma undergoing autologous stem cell transplant

Upfront autologous stem cell transplant (ASCT) is the standard of care for newly diagnosed multiple myeloma (MM) patients. However, relapse is ubiquitous and therapy-related myeloid neoplasms (t-MN) post-ASCT are commonly associated with poor outcomes. We hypothesized that the enrichment of abnormal myeloid progenitors and immune effector cells (IEC) in the peripheral blood stem cells (PBSCs) is associated with a higher risk of relapse and/or development of t-MN. We performed a comprehensive myeloid and lymphoid immunophenotyping on PBSCs from 54 patients with MM who underwent ASCT. Median progression-free (PFS), myeloid neoplasm-free (MNFS), and overall survival (OS) from ASCT were 49.6 months (95% CI: 39.5-Not Reached), 59.7 months (95% CI: 55-74), and 75.6 months (95% CI: 62-105), respectively. Abnormal expression of CD7 and HLA-DR on the myeloid progenitor cells was associated with an inferior PFS, MNFS, and OS. Similarly, enrichment of terminally differentiated (CD27/CD28-, CD57/KLRG1+) and exhausted (TIGIT/PD-1+) T-cells, and inhibitory NK-T like (CD159a+/CD56+) T-cells was associated with inferior PFS, MNFS, and OS post-transplant. Our observation of abnormal myeloid and IEC phenotype being present even before ASCT and maintenance therapy suggests an early predisposition to t-MN and inferior outcomes for MM, and has the potential to guide sequencing of future treatment modalities.

Self-supervised deep clustering of single-cell RNA-seq data to hierarchically detect rare cell populations

Single-cell RNA sequencing (scRNA-seq) is a widely used technique for characterizing individual cells and studying gene expression at the single-cell level. Clustering plays a vital role in grouping similar cells together for various downstream analyses. However, the high sparsity and dimensionality of large scRNA-seq data pose challenges to clustering performance. Although several deep learning-based clustering algorithms have been proposed, most existing clustering methods have limitations in capturing the precise distribution types of the data or fully utilizing the relationships between cells, leaving a considerable scope for improving the clustering performance, particularly in detecting rare cell populations from large scRNA-seq data. We introduce DeepScena, a novel single-cell hierarchical clustering tool that fully incorporates nonlinear dimension reduction, negative binomial-based convolutional autoencoder for data fitting, and a self-supervision model for cell similarity enhancement. In comprehensive evaluation using multiple large-scale scRNA-seq datasets, DeepScena consistently outperformed seven popular clustering tools in terms of accuracy. Notably, DeepScena exhibits high proficiency in identifying rare cell populations within large datasets that contain large numbers of clusters. When applied to scRNA-seq data of multiple myeloma cells, DeepScena successfully identified not only previously labeled large cell types but also subpopulations in CD14 monocytes, T cells and natural killer cells, respectively.