Subclone-specific microenvironmental impact and drug response in refractory multiple myeloma revealed by single-cell transcriptomics

The Genetic and Molecular Drivers of Multiple Myeloma: Current Insights, Clinical Implications, and the Path Forward

Background

Multiple myeloma (MM) is a hematological malignancy characterized by the clonal proliferation of malignant plasma cells within the bone marrow. The disease's complexity is underpinned by a variety of genetic and molecular abnormalities that drive its progression.

Methods

This review was conducted through a state-of-The-art literature search, primarily utilizing PubMed to gather peer-reviewed articles. We focused on the most comprehensive and cited studies to ensure a thorough understanding of the genetic and molecular landscapes of MM.

Results

We detail primary and secondary alterations such as translocations, hyperdiploidy, single nucleotide variants (SNVs), copy number alterations (CNAs), gene fusions, epigenetic modifications, non-coding RNAs, germline predisposing variants, and the influence of the tumor microenvironment (TME). Our analysis highlights the heterogeneity of MM and the challenges it poses in treatment and prognosis, emphasizing the distinction between driver mutations, which actively contribute to oncogenesis, and passenger mutations, which arise due to genomic instability and do not contribute to disease progression.

Conclusion & Future Perspectives

We report key controversies and challenges in defining the genetic drivers of MM, and examine their implications for future therapeutic strategies. We discuss the importance of systems biology approaches in understanding the dependencies and interactions among these alterations, particularly highlighting the impact of double and triple-hit scenarios on disease outcomes. By advancing our understanding of the molecular drivers and their interactions, this review sets the stage for novel therapeutic targets and strategies, ultimately aiming to improve clinical outcomes in MM patients.

Gamma delta T cells in cancer therapy: from tumor recognition to novel treatments

Traditional immunotherapies mainly focus on αβ T cell-based strategies, which depend on MHC-mediated antigen recognition. However, this approach poses significant challenges in treating recurrent tumors, as immune escape mechanisms are widespread. γδ T cells, with their ability for MHC-independent antigen presentation, offer a promising alternative that could potentially overcome limitations observed in traditional immunotherapies. These cells play a role in tumor immune surveillance through a unique mechanism of antigen recognition and synergistic interactions with other immune effector cells. In this review, we will discuss the biological properties of the Vδ1 and Vδ2 T subsets of γδ T cells, their immunomodulatory role within the tumor microenvironment, and the most recent clinical advances in γδ T cell-based related immunotherapies, including cell engaging strategies and adoptive cell therapy.

Multiple myeloma long-term survivors exhibit sustained immune alterations decades after first-line therapy

The long-term consequences of cancer and its therapy on the patients' immune system years after cancer-free survival remain poorly understood. Here, we present an in-depth characterization of the bone marrow immune ecosystem of multiple myeloma long-term survivors, from initial diagnosis up to 17 years following a single therapy line and cancer-free survival. Using comparative single-cell analyses combined with molecular, genomic, and functional approaches, we demonstrate that multiple myeloma long-term survivors exhibit pronounced alterations in their bone marrow microenvironment associated with impaired immunity. These immunological alterations were frequently linked to an inflammatory immune circuit fueled by the long-term persistence or resurgence of residual myeloma cells. Notably, even in the complete absence of any detectable residual disease for decades, sustained changes in the immune system were observed, suggesting an irreversible 'immunological scarring' caused by the initial exposure to the cancer and therapy. Collectively, our study provides key insights into the molecular and cellular bone marrow ecosystem of long-term survivors of multiple myeloma, revealing both reversible and irreversible alterations in the immune compartment.

A single-cell transcriptomic map of the murine and human multiple myeloma immune microenvironment across disease stages

BACKGROUND

The long-term effectiveness of immunotherapies against Multiple Myeloma (MM) remains elusive, demonstrated by the inevitable relapse in patients. This underscores the urgent need for an in-depth analysis of the MM tumor-immune microenvironment (TME). Hereto, a representative immunocompetent MM mouse model can offer a valuable approach to study the dynamic changes within the MM-TME and to uncover potential resistance mechanisms hampering effective and durable therapeutic strategies in MM.

METHODS

We generated a comprehensive single-cell RNA-sequencing atlas of the MM-TME in bone marrow and spleen encompassing different stages of disease, using the immunocompetent 5T33MM mouse model. Through comparative analysis, we correlated our murine dataset with the pathogenesis in MM patients by reanalyzing publicly available datasets of human bone marrow samples across various disease stages. Using flow cytometry, we validated the dynamic changes upon disease progression in the 5T33MM model. Furthermore, interesting target populations, as well as the immune-boosting anti-CD40 agonist (αCD40) therapy were tested ex vivo on murine and human primary samples and in vivo using the 5T33MM model.

RESULTS

In this study, we identified the heterogenous and dynamic changes within the TME of murine and human MM. We found that the MM-TME was characterized by an increase in T cells, accompanied with an exhausted phenotype. Although neutrophils appeared to be rather innocuous at early disease stages, they acquired a pro-tumorigenic phenotype during MM progression. Moreover, conventional dendritic cells (cDCs) showed a less activated phenotype in MM, underscoring the potential of immune-boosting therapies such as αCD40 therapy. Importantly, we provided the first pre-clinical evaluation of αCD40 therapy and demonstrated successful induction of cDC- and T-cell activation, accompanied by a significant short-term anti-tumor response.

CONCLUSIONS

This resource provides a comprehensive and detailed immune atlas of the evolution in human and murine MM disease progression. Our findings can contribute to immune-based patient stratification and facilitate the development of novel and durable (immune) therapeutic strategies in MM.

LILRB4 represents a promising target for immunotherapy by dual targeting tumor cells and myeloid-derived suppressive cells in multiple myeloma

Multiple myeloma (MM) remains an incurable hematologic malignancy. Despite tremendous advances in the treatment of this disease, about 10% of patients still have very poor outcomes with a median overall survival of less than 24 months. Our study aimed to underscore the critical mechanisms pertaining to rapid disease progression and provide novel therapeutic choices for these ultrahigh-risk patients. We utilized single-cell transcriptomic sequencing to dissect the characteristic bone marrow niche of patients who survived less than 2 years (EM24). Notably, enrichment of a LILRB4high pre-mature plasma-cell cluster was observed in EM24 patients compared to patients with durable remission. This cluster exhibited aggressive proliferation and a drug-resistance phenotype. High levels of LILRB4 promoted MM clonogenicity and progression. Clinically, high expression of LILRB4 was correlated with poor prognosis in both newly diagnosed MM patients and relapsed/ refractory MM patients. ATAC-sequencing analysis identified that pronounced chromosomal accessibility caused the elevation of LILRB4 on MM cells. CRISPR-Cas9 deletion of LILRB4 alleviated the growth of MM cells, inhibited the immunosuppressive function of myeloid-derived suppressive cells (MDSC), and further rescued T-cell dysfunction in the MM microenvironment. Greater infiltration of MDSC was observed in EM24 patients. We therefore generated an innovative T-cell receptor-based chimeric antigen receptor T cell, LILRB4-STAR-T. Cytotoxicity experiments demonstrated that LILRB4-STAR-T cells efficaciously eliminated tumor cells and impeded MDSC function. In conclusion, our study elucidates that LILRB4 is an ideal biomarker and promising immunotherapy target for high-risk MM. LILRB4-STAR-T-cell immunotherapy is promising against both tumor cells and the immunosuppressive tumor microenvironment in MM.

The role of 1q abnormalities in multiple myeloma: Genomic insights, clinical implications, and therapeutic challenges

Chromosome 1q copy number variations, collectively termed +1q, are 1 of the most common cytogenetic abnormalities in multiple myeloma. 1q abnormalities are associated with overexpression of a high-risk gene signature promoting cell proliferation, apoptosis resistance, genomic instability, and treatment resistance, and acquisition or expansion of +1q subclones mediate disease development and relapse. While there remains significant controversy as to whether the presence of +1q is itself an independent driver of poor prognosis or is simply a marker of other high-risk features, +1q has recently been incorporated into multiple prognostic scoring models as a new high-risk cytogenetic abnormality. In this review, we present possible underlying genetic mechanisms of high-risk disease in +1q myeloma, implications for subclonal development, its role in modifying the tumor microenvironment, current evidence for clinical significance in newly-diagnosed and relapsed patients, and current controversies in +1q classification and prognostication.

Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones

Intratumoral cellular heterogeneity necessitates multi-targeting therapies for improved clinical benefits in advanced malignancies. However, systematic identification of patient-specific treatments that selectively co-inhibit cancerous cell populations poses a combinatorial challenge, since the number of possible drug-dose combinations vastly exceeds what could be tested in patient cells. Here, we describe a machine learning approach, scTherapy, which leverages single-cell transcriptomic profiles to prioritize multi-targeting treatment options for individual patients with hematological cancers or solid tumors. Patient-specific treatments reveal a wide spectrum of co-inhibitors of multiple biological pathways predicted for primary cells from heterogenous cohorts of patients with acute myeloid leukemia and high-grade serous ovarian carcinoma, each with unique resistance patterns and synergy mechanisms. Experimental validations confirm that 96% of the multi-targeting treatments exhibit selective efficacy or synergy, and 83% demonstrate low toxicity to normal cells, highlighting their potential for therapeutic efficacy and safety. In a pan-cancer analysis across five cancer types, 25% of the predicted treatments are shared among the patients of the same tumor type, while 19% of the treatments are patient-specific. Our approach provides a widely-applicable strategy to identify personalized treatment regimens that selectively co-inhibit malignant cells and avoid inhibition of non-cancerous cells, thereby increasing their likelihood for clinical success.

DrugFormer: Graph-Enhanced Language Model to Predict Drug Sensitivity

Drug resistance poses a crucial challenge in healthcare, with response rates to chemotherapy and targeted therapy remaining low. Individual patient's resistance is exacerbated by the intricate heterogeneity of tumor cells, presenting significant obstacles to effective treatment. To address this challenge, DrugFormer, a novel graph-augmented large language model designed to predict drug resistance at single-cell level is proposed. DrugFormer integrates both serialized gene tokens and gene-based knowledge graphs for the accurate predictions of drug response. After training on comprehensive single-cell data with drug response information, DrugFormer model presents outperformance, with higher F1, precision, and recall in predicting drug response. Based on the scRNA-seq data from refractory multiple myeloma (MM) and acute myeloid leukemia (AML) patients, DrugFormer demonstrates high efficacy in identifying resistant cells and uncovering underlying molecular mechanisms. Through pseudotime trajectory analysisunique drug-resistant cellular states associated with poor patient outcomes are revealed. Furthermore, DrugFormer identifies potential therapeutic targets, such as COX8A, for overcoming drug resistance across different cancer types. In conclusion, DrugFormer represents a significant advancement in the field of drug resistance prediction, offering a powerful tool for unraveling the heterogeneity of cellular response to drugs and guiding personalized treatment strategies.

scCrab: A Reference-Guided Cancer Cell Identification Method based on Bayesian Neural Networks

Cancer is a significant global public health concern, where early detection can greatly enhance curative outcomes. Therefore, the identification of cancer cells holds significant importance as the primary method for cancer diagnosis. The advancement of single-cell RNA sequencing (scRNA-seq) technology has made it possible to address the problem of cancer cell identification at the single-cell level more efficiently with computational methods, as opposed to the time-consuming and less reproducible manual identification methods. However, existing computational methods have shown suboptimal identification performance and a lack of capability to incorporate external reference data as prior information. Here, we propose scCrab, a reference-guided automatic cancer cell identification method, which performs ensemble learning based on a Bayesian neural network (BNN) with multi-head self-attention mechanisms and a linear regression model. Through a series of experiments on various datasets, we systematically validated the superior performance of scCrab in both intra- and inter-dataset predictions. Besides, we demonstrated the robustness of scCrab to dropout rate and sample size, and conducted ablation experiments to investigate the contributions of each component in scCrab. Furthermore, as a dedicated model for cancer cell identification, scCrab effectively captures cancer-related biological significance during the identification process.

Immunoglobulin Replacement Therapy: Insights into Multiple Myeloma Management

Immunoglobulin (Ig) replacement therapy (IgRT) consists of the administration of low-dose human polyclonal Igs for the treatment of primary and secondary hypogammaglobulinemia that are associated with recurrent infections and immune dysfunction. IgRT restores physiological antibody levels and induces an immunomodulatory effect by strengthening immune effector cells, thus reducing infections. Here, we describe the pharmacology of different Ig formulations with a particular focus on their mechanism of action as low-dose IgRT, including the direct anti-microbial effect and the immunomodulatory function. In addition, we describe the use of therapeutic Igs for the management of multiple myeloma (MM), a hematologic malignancy characterized by severe secondary hypogammaglobulinemia associated with poor patient outcome. In MM settings, IgRT prevents life-threatening and recurrent infections showing promising results regarding patient survival and quality of life. Nevertheless, the clinical benefits of IgRT are still controversial. A deeper understanding of the immune-mediated effects of low-dose IgRT will provide the basis for novel combined therapeutic options and personalized therapy in MM and other conditions characterized by hypogammaglobulinemia.

Identification of Therapy-Induced Clonal Evolution and Resistance Pathways in Minimal Residual Clones in Multiple Myeloma through Single-Cell Sequencing

PURPOSE

In multiple myeloma (MM), therapy-induced clonal evolution is associated with treatment resistance and is one of the most important hindrances toward a cure for MM. To further understand the molecular mechanisms controlling the clonal evolution of MM, we applied single-cell RNA sequencing (scRNA-seq) to paired diagnostic and posttreatment bone marrow (BM) samples.

EXPERIMENTAL DESIGN

scRNA-seq was performed on 38 BM samples from patients with monoclonal gammopathy of undetermined significance (n = 1), MM patients at diagnosis (n = 19), MM posttreatment (n = 17), and one healthy donor (HD). The single-cell transcriptome data of malignant plasma cells (PC) and the surrounding immune microenvironment were analyzed.

RESULTS

Profiling by scRNA-seq data revealed three primary trajectories of transcriptional evolution after treatment: clonal elimination in patients with undetectable minimal residual disease (MRD-) and clonal stabilization and clonal selection in detectable MRD (MRD+) patients. We noted a metabolic shift toward fatty acid oxidation in cycling-resistant PCs, whereas selective PCs favored the NF-κB pathway. Intriguingly, when comparing the genetic and transcriptional dynamics, we found a significant correlation between genetic and nongenetic factors in driving the clonal evolution. Furthermore, we identified variations in cellular interactions between malignant PCs and the tumor microenvironment. Selective PCs showed the most robust cellular interactions with the tumor microenvironment.

CONCLUSIONS

These data suggest that MM cells could rapidly adapt to induction treatment through transcriptional adaptation, metabolic adaptation, and specialized immune evasion. Targeting therapy-induced resistance mechanisms may help to avert refractory disease in MM.

Rising Prevalence of Low-Frequency PPM1D Gene Mutations after Second HDCT in Multiple Myeloma

Multiple myeloma (MM) first-line treatment algorithms include immuno-chemotherapy (ICT) induction, high-dose chemotherapy (HDCT) and autologous stem cell transplant (ASCT) consolidation, followed by lenalidomide maintenance. After these initial therapies, most patients suffer a disease relapse and require subsequent treatment lines including ICT, additional HDCT and ASCT, or novel immunotherapies. The presence of somatic mutations in peripheral blood cells has been associated with adverse outcomes in a variety of hematological malignancies. Nonsense and frameshift mutations in the PPM1D gene, a frequent driver alteration in clonal hematopoiesis (CH), lead to the gain-of-function of Wip1 phosphatase, which may impair the p53-dependent G1 checkpoint and promote cell proliferation. Here, we determined the presence of PPM1D gene mutations in peripheral blood cells of 75 subsequent myeloma patients in remission after first or second HDCT/ASCT. The prevalence of truncating PPM1D gene mutations emerged at 1.3% after first HDCT/ASCT, and 7.3% after second HDCT/ASCT, with variant allele frequencies (VAF) of 0.01 to 0.05. Clinical outcomes were inferior in the PPM1D-mutated (PPM1Dmut) subset with median progression-free survival (PFS) of 15 vs. 37 months (p = 0.0002) and median overall survival (OS) of 36 vs. 156 months (p = 0.001) for the PPM1Dmut and PPM1Dwt population, respectively. Our data suggest that the occurrence of PPM1D gene mutations in peripheral blood cells correlates with inferior outcomes after ASCT in patients with multiple myeloma.

IL-18-secreting multiantigen targeting CAR T cells eliminate antigen-low myeloma in an immunocompetent mouse model

ABSTRACT

Multiple myeloma is a plasma cell malignancy that is currently incurable with conventional therapies. Following the success of CD19-targeted chimeric antigen receptor (CAR) T cells in leukemia and lymphoma, CAR T cells targeting B-cell maturation antigen (BCMA) more recently demonstrated impressive activity in relapsed and refractory myeloma patients. However, BCMA-directed therapy can fail due to weak expression of BCMA on myeloma cells, suggesting that novel approaches to better address this antigen-low disease may improve patient outcomes. We hypothesized that engineered secretion of the proinflammatory cytokine interleukin-18 (IL-18) and multiantigen targeting could improve CAR T-cell activity against BCMA-low myeloma. In a syngeneic murine model of myeloma, CAR T cells targeting the myeloma-associated antigens BCMA and B-cell activating factor receptor (BAFF-R) failed to eliminate myeloma when these antigens were weakly expressed, whereas IL-18-secreting CAR T cells targeting these antigens promoted myeloma clearance. IL-18-secreting CAR T cells developed an effector-like T-cell phenotype, promoted interferon-gamma production, reprogrammed the myeloma bone marrow microenvironment through type-I/II interferon signaling, and activated macrophages to mediate antimyeloma activity. Simultaneous targeting of weakly-expressed BCMA and BAFF-R with dual-CAR T cells enhanced T-cell:target-cell avidity, increased overall CAR signal strength, and stimulated antimyeloma activity. Dual-antigen targeting augmented CAR T-cell secretion of engineered IL-18 and facilitated elimination of larger myeloma burdens in vivo. Our results demonstrate that combination of engineered IL-18 secretion and multiantigen targeting can eliminate myeloma with weak antigen expression through distinct mechanisms.

M2 Macrophage Classification of Colorectal Cancer Reveals Intrinsic Connections with Metabolism Reprogramming and Clinical Characteristics

Introduction

Immune cell interactions and metabolic changes are crucial in determining the tumor microenvironment and affecting various clinical outcomes. However, the clinical significance of metabolism evolution of immune cell evolution in colorectal cancer (CRC) remains unexplored.

Methods

Single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing data were acquired from TCGA and GEO datasets. For the analysis of macrophage differentiation trajectories, we employed the R packages Seurat and Monocle. Consensus clustering was further applied to identify the molecular classification. Immunohistochemical results from AOM and AOM/DSS models were used to validate macrophage expression. Subsequently, GSEA, ESTIMATE scores, prognosis, clinical characteristics, mutational burden, immune cell infiltration, and the variance in gene expression among different clusters were compared. We constructed a prognostic model and nomograms based on metabolic gene signatures identified through the MEGENA framework.

Results

We found two heterogeneous groups of M2 macrophages with various clinical outcomes through the evolutionary process. The prognosis of Cluster 2 was poorer. Further investigation showed that Cluster 2 constituted a metabolically active group while Cluster 1 was comparatively metabolically inert. Metabolic variations in M2 macrophages during tumor development are related to tumor prognosis. Additionally, Cluster 2 showed the most pronounced genomic instability and had highly elevated metabolic pathways, notably those associated with the ECM. We identified eight metabolic genes (PRELP, NOTCH3, CNOT6, ASRGL1, SRSF1, PSMD4, RPL31, and CNOT7) to build a predictive model validated in CRC datasets. Then, a nomogram based on the M2 risk score improved predictive performance. Furthermore, our study demonstrated that immune checkpoint inhibitor therapy may benefit patients with low-risk.

Discussion

Our research reveals underlying relationships between metabolic phenotypes and immunological profiles and suggests a unique M2 classification technique for CRC. The identified gene signatures may be key factors linking immunity and tumor metabolism, warranting further investigations.

Harnessing the cytotoxic granule exocytosis to augment the efficacy of T-cell-engaging bispecific antibody therapy

T-cell-engaging bispecific antibody (T-BsAb, also known as BiTE) therapy has emerged as a powerful therapeutic modality against multiple myeloma. Given that T-BsAb therapy redirects endogenous T cells to eliminate tumor cells, reinvigorating dysfunctional T cells may be a potential approach to improve the efficacy of T-BsAb. While various immunostimulatory cytokines can potentiate effector T-cell functions, the optimal cytokine treatment for T-BsAb therapy is yet to be established, partly due to a concern of cytokine release syndrome driven by aberrant interferon (IFN)-γ production. Here, we functionally screen immunostimulatory cytokines to determine an ideal combination partner for T-BsAb therapy. This approach reveals interleukin (IL)-21 as a potential immunostimulatory cytokine with the ability to augment T-BsAb-mediated release of granzyme B and perforin, without increasing IFN-γ release. Transcriptome profiling and functional characterization strongly support that IL-21 selectively targets the cytotoxic granule exocytosis pathway, but not pro-inflammatory responses. Notably, IL-21 modulates multiple steps of cytotoxic effector functions including upregulation of co-activating CD226 receptor, increasing cytotoxic granules, and promoting cytotoxic granule delivery at the immunological synapse. Indeed, T-BsAb-mediated myeloma killing is cytotoxic granule-dependent, and IL-21 priming significantly augments cytotoxic activities. Furthermore, in vivo IL-21 treatment induces cytotoxic effector reprogramming in bone marrow T cells, showing synergistic anti-myeloma effects in combination with T-BsAb therapy. Together, harnessing the cytotoxic granule exocytosis pathway by IL-21 may be a potential approach to achieve better responses by T-BsAb therapy.

Advances in single-cell sequencing technology in microbiome research

With the rapid development of histological techniques and the widespread application of single-cell sequencing in eukaryotes, researchers desire to explore individual microbial genotypes and functional expression, which deepens our understanding of microorganisms. In this review, the history of the development of microbial detection technologies was revealed and the difficulties in the application of single-cell sequencing in microorganisms were dissected as well. Moreover, the characteristics of the currently emerging microbial single-cell sequencing (Microbe-seq) technology were summarized, and the prospects of the application of Microbe-seq in microorganisms were distilled based on the current development status. Despite its mature development, the Microbe-seq technology was still in the optimization stage. A retrospective study was conducted, aiming to promote the widespread application of single-cell sequencing in microorganisms and facilitate further improvement in the technology.

Pathways to therapy resistance: The sheltering effect of the bone marrow microenvironment to multiple myeloma cells

Multiple Myeloma (MM) is a malignant expansion of plasma cells in the bone marrow (BM), resulting in a disease characterized by symptoms of end organ damage from light chain secretion, crowding of the BM, and bone lesions. Although the past two decades have been characterized by numerous novel therapies emerging, the disease remains incurable due to intrinsic or acquired drug resistance. A major player in MM's drug resistance arises from its intimate relationship with the BM microenvironment (BMME). Through stress-inducing conditions, soluble messengers, and physical adhesion to BM elements, the BMME activates numerous pathways in the myeloma cell. This not only propagates myeloma progression through survival and growth signals, but also specific mechanisms to circumvent therapeutic actions. In this review, we provide an overview of the BMME, the role of individual components in MM survival, and various therapy-specific resistance mechanisms reported in the literature.

Identification of lipid metabolism-related gene signature in the bone marrow microenvironment of multiple myelomas through deep analysis of transcriptomic data

Dysregulated lipid metabolism in the bone marrow microenvironment (BMM) plays a vital role in multiple myeloma (MM) development, progression, and drug resistance. However, the exact mechanism by which lipid metabolism impacts the BMM, promotes tumorigenesis, and triggers drug resistance remains to be fully elucidated.By analyzing the bulk sequencing and single-cell sequencing data of MM patients, we identified lipid metabolism-related genes differential expression significantly associated with MM prognosis, referred to as LMRPgenes. Using a cohort of ten machine learning algorithms and 117 combinations, LMRPgenes predictive models were constructed. Further exploration of the effects of the model risk score (RS) on the survival status, immune status of patients with BMM, and response to immunotherapy was conducted. The study also facilitated the identification of personalized therapeutic strategies targeting specified risk categories within patient cohorts.Analysis of the scRNA-seq data revealed increased lipid metabolism-related gene enrichment scores (LMESs) in erythroblasts and progenitor, malignant, and Tprolif cells but decreased LMESs in lymphocytes. LMESs were also strongly correlated with most of the 50 hallmark pathways within these cell populations. An elevated malignant cell ratio and reduced lymphocytes were observed in the high LMES group. Moreover, the LMRPgenes predictive model, consisting of 14 genes, showed great predictive power. The risk score emerged as an independent indicator of poor outcomes. Inverse relationships between the RS and immune status were noted, and a high RS was associated with impaired immunotherapy responses. Drug sensitivity assays indicated the effectiveness of bortezomib, buparlisib, dinaciclib, staurosporine, rapamycin, and MST-312 in the high-RS group, suggesting their potential for treating patients with high-RS values and poor response to immunotherapy. Ultimately, upon verification via qRT-PCR, we observed a significant upregulation of ACBD6 in NDMM group compared to the control group.Our research enhances the knowledge base regarding the association between lipid metabolism-related genes (LMRGs) and the BMM in MM patients, offering substantive insights into the mechanistic effects of the BMM mediated by LMRGs.

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.

Activated platelet-derived exosomal LRG1 promotes multiple myeloma cell growth

The hypercoagulable state is a hallmark for patients with multiple myeloma (MM) and is associated with disease progression. Activated platelets secrete exosomes and promote solid tumor growth. However, the role of platelet-derived exosomes in MM is not fully clear. We aim to study the underlying mechanism of how platelet-derived exosomes promote MM cell growth. Flow cytometry, Western blot, proteome analysis, co-immunoprecipitation, immunofluorescence staining, and NOD/SCID mouse subcutaneous transplantation model were performed to investigate the role of exosomal LRG1 on multiple myeloma cell growth. Peripheral blood platelets in MM patients were in a highly activated state, and platelet-rich plasma from MM patients significantly promoted cell proliferation and decreased apoptotic cells in U266 and RPMI8226 cells. Leucine-rich-alpha-2-glycoprotein 1 (LRG1) was significantly enriched in MM platelet-derived exosomes. Blocking LRG1 in recipient cells using LRG1 antibody could significantly eliminate the proliferation-promoting effect of platelet-derived exosomes on MM cells. And high exosomal LRG1 was associated with poor prognosis of patients with MM. Mechanistic studies revealed that LRG1 interacted with Olfactomedin 4 (OLFM4) to accelerate MM progression by activating the epithelial-to-mesenchymal transition (EMT) signaling pathway and promoting angiogenesis. Our results revealed that blocking LRG1 is a promising therapeutic strategy for the treatment of MM.

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.

Ex vivo expansion and activation of Vγ9Vδ2 T cells by CELMoDs in combination with zoledronic acid

As multiple myeloma (MM) progresses, immune effector cells decrease in number and function and become exhausted. This remains an insurmountable clinical issue that must be addressed by development of novel modalities to revitalize anti-MM immunity. Human Vγ9Vδ2 T (Vδ2+ γδ T) cells serve as the first line of defense against pathogens as well as tumors and can be expanded ex vivo from peripheral blood mononuclear cells (PBMCs) upon treatment with amino-bisphosphonates in combination with IL-2. Here, we demonstrated that next-generation immunomodulators called cereblon E3 ligase modulators (CELMoDs), as well as lenalidomide and pomalidomide, expanded Th1-like Vδ2+ γδ T cells from PBMCs in the presence of zoledronic acid (ZA). However, the expansion of Th1-like Vδ2+ γδ T cells by these immunomodulatory drugs was abolished under IL-2 blockade, although IL-2 production was induced in PBMCs. BTN3A1 triggers phosphoantigen presentation to γδ T-cell receptors and is required for γδ T-cell expansion and activation. ZA but not these immunomodulatory drugs upregulated BTN3A1 in monocytes. These results suggest that immunomodulatory drugs and ZA have cooperative roles in expansion of Th1-like Vδ2+ γδ T cells, and provide the important knowledge for clinical application of human Vδ2+ γδ T cells as effector cells.

Next-Generation Therapies for Multiple Myeloma

Recent therapeutic advances have significantly improved the outcome for patients with multiple myeloma (MM). The backbone of successful standard therapy is the combination of Ikaros degraders, glucocorticoids, and proteasome inhibitors that interfere with the integrity of myeloma-specific superenhancers by directly or indirectly targeting enhancer-bound transcription factors and coactivators that control expression of MM dependency genes. T cell engagers and chimeric antigen receptor T cells redirect patients' own T cells onto defined tumor antigens to kill MM cells. They have induced complete remissions even in end-stage patients. Unfortunately, responses to both conventional therapy and immunotherapy are not durable, and tumor heterogeneity, antigen loss, and lack of T cell fitness lead to therapy resistance and relapse. Novel approaches are under development to target myeloma-specific vulnerabilities, as is the design of multimodality immunological approaches, including and beyond T cells, that simultaneously recognize multiple epitopes to prevent antigen escape and tumor relapse.

Fluorescence in situ hybridization reveals the evolutionary biology of minor clone of gain/amp(1q) in multiple myeloma

Growing evidence suggests that gain or amplification [gain/amp(1q)] accumulates during disease progression of multiple myeloma (MM). Previous investigations have indicated that small gain/amp(1q) subclones present at the time of diagnosis may evolve into dominant clones upon MM relapse. However, the influence of a minor clone of gain/amp(1q) on MM survival, as well as the correlation between different clonal sizes of gain/amp(1q) and the chromosomal instability (CIN) of MM, remains poorly understood. In this study, we analyzed fluorescence in situ hybridization (FISH) results of 998 newly diagnosed MM (NDMM) patients. 513 patients were detected with gain/amp(1q) at diagnosis. Among these 513 patients, 55 had a minor clone (≤20%) of gain/amp(1q). Patients with a minor clone of gain/amp(1q) displayed similar survival outcomes compared to those without gain/amp(1q). Further analysis demonstrated patients with a minor clone of gain/amp(1q) exhibited a clonal architecture similar to those without gain/amp(1q). Lastly, our results showed a significant increase in the clonal size of the minor clone of gain/amp(1q), frequently observed in MM. These findings suggested that a minor clone of gain/amp(1q) might represent an earlier stage in the pathogenesis of gain/amp(1q) and propose a "two-step" process in the clonal size changes of gain/amp(1q) in MM.

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.

Prognostic Implications of Circulating Plasma Cell Percentage in Multiple Myeloma and Primary Plasma Cell Leukemia Defined by New Criteria

INTRODUCTION

The definition of primary plasma cell leukemia (pPCL) has been revised from ≥20% to ≥5% circulating plasma cells (CPC). However, the precise prognosis associated with CPC remains controversial. This study aimed to investigate prognostic biomarkers for myeloma patients based on CPC presence.

METHODS

A comprehensive analysis was conducted on 309 consecutive patients diagnosed with either multiple myeloma or pPCL, utilizing peripheral blood smears stained with Wright-Giemsa.

RESULTS

Patients were grouped by CPC percentage: 0% (221, 71.5%), 1-4% (49, 15.9%), 5-19% (16, 5.2%), ≥20% (23, 7.4%). CPC >5% correlated with unfavorable characteristics, including anemia, renal dysfunction, and advanced International Staging System. Common cytogenetic abnormalities such as 1q21 amplification, 17p deletion, and Myc rearrangement were prevalent among CPC-positive patients. Median progression-free survival (PFS) and overall survival (OS) were shorter in patients with CPC ≥5% (29.47 vs. 10.03 months; 64.10 vs. 12.30 months). Additionally, PFS and OS were shorter in CPC-positive patients without autologous hematopoietic stem cell transplantation (ASCT) and those with response < partial remission to the first-line regimen. Furthermore, an association emerged between soft tissue-related extramedullary disease and inferior PFS, while Myc rearrangement correlated with abbreviated OS.

CONCLUSION

Biological characteristics displayed greater aggressiveness in patients with positive CPC, leading to significantly shorter PFS and OS. The presence of CPC, ASCT, and overall response rate were independent prognostic factors. While no new threshold for pPCL with CPCs is proposed, Myc rearrangements and CPC positivity could serve as ultra-high-risk factors for multiple myeloma.

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.

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.

Macrophage: Hidden Criminal in Therapy Resistance

BACKGROUND

Although substantial efforts have been made by researchers to develop drugs, a disappointing reality is that the emergence of drug resistance is an unavoidable reality for the majority of patients. In recent years, emerging evidence suggests a connection between drug resistance and immune dysregulation.

SUMMARY

As a ubiquitously distributed, versatile innate immune cell, macrophages play essential roles in maintaining tissue homeostasis in a steady state. Nevertheless, it is becoming aware that macrophages undermine the action of therapeutic drugs across various disease types. Reprogramming macrophage function has been proven to be effective in restoring patient responsiveness to treatment. Herein, we comprehensively reviewed how macrophages respond to drugs and the mechanisms by which they contribute to treatment unresponsiveness in cancer, inflammatory diseases, and metabolic diseases. In addition, future prospects in macrophage-based combination therapy were discussed.

KEY MESSAGES

Targeting macrophages is a promising strategy for overcoming drug resistance in immune disorders.

T-cell infiltration and its regulatory mechanisms in cancers: insights at single-cell resolution

Tumor-infiltrating T cells recognize, attack, and clear tumor cells, playing a central role in antitumor immune response. However, certain immune cells can impair this response and help tumor immune escape. Therefore, exploring the factors that influence T-cell infiltration is crucial to understand tumor immunity and improve therapeutic effect of cancer immunotherapy. The use of single-cell RNA sequencing (scRNA-seq) allows the high-resolution analysis of the precise composition of immune cells with different phenotypes and other microenvironmental factors, including non-immune stromal cells and the related molecules in the tumor microenvironment of various cancer types. In this review, we summarized the research progress on T-cell infiltration and the crosstalk of other stromal cells and cytokines during T-cell infiltration using scRNA-seq to provide insights into the mechanisms regulating T-cell infiltration and contribute new perspectives on tumor immunotherapy.

Minor clone of del(17p) provides a reservoir for relapse in multiple myeloma

The deletion of chromosome 17p (del(17p)) is considered a crucial prognostic factor at the time of diagnosis in patients with multiple myeloma (MM). However, the impact of del(17p) on survival at different clonal sizes at relapse, as well as the patterns of clonal evolution between diagnosis and relapse and their prognostic value, has not been well described. To address these issues, we analyzed the interphase fluorescence in situ hybridization (iFISH) results of 995 newly diagnosed MM (NDMM) patients and 293 patients with MM at their first relapse. Among these patients, 197 had paired iFISH data at diagnosis and first relapse. Our analysis of paired iFISH revealed that a minor clone of del(17p) at relapse but not at diagnosis was associated with poor prognosis in MM (hazard ratio for median overall survival 1.64 vs. 1.44). Fifty-six and 12 patients developed one or more new cytogenetic abnormalities at relapse, mainly del(17p) and gain/amp(1q), respectively. We classified the patients into six groups based on the change patterns in the clonal size of del(17p) between the two time points. Patients who did not have del(17p) during follow-up showed the best outcomes, whereas those who acquired del(17p) during their disease course, experienced compromised survival (median overall survival: 61.3 vs. 49.4 months; hazard ratio =1.64; 95% confidence interval: 1.06-2.56; P<0.05). In conclusion, our data confirmed the adverse impact of a minor clone of del(17p) at relapse and highlighted the importance of designing optimal therapeutic strategies to eliminate high-risk cytogenetic abnormalities (clinicaltrials gov. identifier: NCT04645199).

An inflammatory response-related gene signature can predict the prognosis and impact the immune infiltration of multiple myeloma

Multiple myeloma (MM) is a highly heterogeneous and incurable disease. Inflammation plays a vital role in cancer genesis and progression. However, the relationship between inflammatory response-related genes (IRRGs) and the prognosis of MM patients remains unknown. We constructed a IRRGs prognosis model by least absolute shrinkage and selection operator regression analysis. Moreover, clinical multivariate regression was performed to identify clinical implications. Gene set enrichment analysis was implemented to conduct its biological properties. CIBERSORT deconvolution algorithm was utilized to calculate the immune cell infiltration in different risk groups. The flow cytometry was utilized to perform protein expression of prognostic gene. A Six-IRRGs (VCAM1, RGS1, KIT, CD81, BLNK, and BIRC3) prognostic risk model was successfully constructed and validated. The risk model was an independent predictor for overall survival. Enrichment analysis revealed autophagy and PI3K-Akt signaling pathways were enriched in the high-risk group. Furthermore, we found CD81 widely impacted on the infiltration of immune cells, especially on monocytes and macrophages2. At last, the role of CD81 in MM was confirmed to be an adverse prognostic factor in clinical. Our study explores the potential application value of IRRGs in MM. These findings may provide new insights into the treatment for MM patients.

Epigenomic Characterization of Lymphoid Neoplasms

Lymphoid neoplasms represent a heterogeneous group of disease entities and subtypes with markedly different molecular and clinical features. Beyond genetic alterations, lymphoid tumors also show widespread epigenomic changes. These severely affect the levels and distribution of DNA methylation, histone modifications, chromatin accessibility, and three-dimensional genome interactions. DNA methylation stands out as a tracer of cell identity and memory, as B cell neoplasms show epigenetic imprints of their cellular origin and proliferative history, which can be quantified by an epigenetic mitotic clock. Chromatin-associated marks are informative to uncover altered regulatory regions and transcription factor networks contributing to the development of distinct lymphoid tumors. Tumor-intrinsic epigenetic and genetic aberrations cooperate and interact with microenvironmental cells to shape the transcriptome at different phases of lymphoma evolution, and intraclonal heterogeneity can now be characterized by single-cell profiling. Finally, epigenetics offers multiple clinical applications, including powerful diagnostic and prognostic biomarkers as well as therapeutic targets.

Single-cell transcriptomic atlas throughout anti-BCMA CAR-T therapy in patients with multiple myeloma

Introduction

The emergence of chimeric antigen receptor (CAR)-T therapy targeting B cell maturation antigen (BCMA) has improved the prognosis of patients with multiple myeloma (MM); however, the majority of patients eventually experience relapse.

Methods

In this study, employing the latest single-cell RNA sequencing technology, we examined 24 bone marrow or peripheral blood samples collected throughout the course of anti-BCMA CAR-T therapy, analyzing a total of 59,725 bone marrow cells and 72,479 peripheral blood cells.

Results

Our findings reveal that tumor cells in relapsed patient exhibit higher expression levels of HSP90B1 and HSPA5, and demonstrate significantly enriched pathways regarding endoplasmic reticulum stress and unfolded protein response. In the analysis of T cells, we observed that patient with impaired effector function and increased expression of immune checkpoints in endogenous T cell are more susceptible to relapse. Notably, T cells from both the bone marrow microenvironment and peripheral blood share highly similar biological characteristics.

Discussion

Overall, this study provides a comprehensive atlas of endogenous immune cells, particularly in the relatively long term, after CAR-T therapy. It offers clinical evidence for a deeper understanding of the internal environment post CAR-T treatment and for identifying mechanisms underlying relapse.

Resolving therapy resistance mechanisms in multiple myeloma by multiomics subclone analysis

Intratumor heterogeneity as a clinical challenge becomes most evident after several treatment lines, when multidrug-resistant subclones accumulate. To address this challenge, the characterization of resistance mechanisms at the subclonal level is key to identify common vulnerabilities. In this study, we integrate whole-genome sequencing, single-cell (sc) transcriptomics (scRNA sequencing), and chromatin accessibility (scATAC sequencing) together with mitochondrial DNA mutations to define subclonal architecture and evolution for longitudinal samples from 15 patients with relapsed or refractory multiple myeloma. We assess transcriptomic and epigenomic changes to resolve the multifactorial nature of therapy resistance and relate it to the parallel occurrence of different mechanisms: (1) preexisting epigenetic profiles of subclones associated with survival advantages, (2) converging phenotypic adaptation of genetically distinct subclones, and (3) subclone-specific interactions of myeloma and bone marrow microenvironment cells. Our study showcases how an integrative multiomics analysis can be applied to track and characterize distinct multidrug-resistant subclones over time for the identification of molecular targets against them.

Computational single cell oncology: state of the art

Single cell computational analysis has emerged as a powerful tool in the field of oncology, enabling researchers to decipher the complex cellular heterogeneity that characterizes cancer. By leveraging computational algorithms and bioinformatics approaches, this methodology provides insights into the underlying genetic, epigenetic and transcriptomic variations among individual cancer cells. In this paper, we present a comprehensive overview of single cell computational analysis in oncology, discussing the key computational techniques employed for data processing, analysis, and interpretation. We explore the challenges associated with single cell data, including data quality control, normalization, dimensionality reduction, clustering, and trajectory inference. Furthermore, we highlight the applications of single cell computational analysis, including the identification of novel cell states, the characterization of tumor subtypes, the discovery of biomarkers, and the prediction of therapy response. Finally, we address the future directions and potential advancements in the field, including the development of machine learning and deep learning approaches for single cell analysis. Overall, this paper aims to provide a roadmap for researchers interested in leveraging computational methods to unlock the full potential of single cell analysis in understanding cancer biology with the goal of advancing precision oncology. For this purpose, we also include a notebook that instructs on how to apply the recommended tools in the Preprocessing and Quality Control section.

High NEK2 expression in myeloid progenitors suppresses T cell immunity in multiple myeloma

Multiple myeloma (MM) growth is supported by an immune-tolerant bone marrow microenvironment. Here, we find that loss of Never in mitosis gene A (NIMA)-related kinase 2 (NEK2) in tumor microenvironmental cells is associated with MM growth suppression. The absence of NEK2 leads to both fewer tumor-associated macrophages (TAMs) and inhibitory T cells. NEK2 expression in myeloid progenitor cells promotes the generation of functional TAMs when stimulated with MM conditional medium. Clinically, high NEK2 expression in MM cells is associated with increased CD8+ T effector memory cells, while low NEK2 is associated with an IFN-γ gene signature and activated T cell response. Inhibition of NEK2 upregulates PD-L1 expression in MM cells and myeloid cells. In a mouse model, the combination of NEK2 inhibitor INH154 with PD-L1 blockade effectively eliminates MM cells and prolongs survival. Our results provide strong evidence that NEK2 inhibition may overcome tumor immune escape and support its further clinical development.

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.

Immunophenotypic correlates of sustained MRD negativity in patients with multiple myeloma

The role of the immune microenvironment in maintaining disease remission in patients with multiple myeloma (MM) is not well understood. In this study, we comprehensively profile the immune system in patients with newly diagnosed MM receiving continuous lenalidomide maintenance therapy with the aim of discovering correlates of long-term treatment response. Leveraging single-cell RNA sequencing and T cell receptor β sequencing of the peripheral blood and CyTOF mass cytometry of the bone marrow, we longitudinally characterize the immune landscape in 23 patients before and one year after lenalidomide exposure. We compare patients achieving sustained minimal residual disease (MRD) negativity to patients who never achieved or were unable to maintain MRD negativity. We observe that the composition of the immune microenvironment in both the blood and the marrow varied substantially according to both MRD negative status and history of autologous stem cell transplant, supporting the hypothesis that the immune microenvironment influences the depth and duration of treatment response.

Intratumor microbiota: Occult participants in the microenvironment of multiple myeloma

More recently, microbiota was detected in several tumorous tissues including multiple myeloma (MM), but the roles of which is still under-studied as paucity of research on tumor biology. Moreover, we also detected the presence of microbiota in the bone marrow of patients with MM by 2bRAD-M sequencing technology, which is an incurable hematological malignancy characterized by accumulation of abnormal plasma cells in the bone marrow. However, the roles of intratumor microbiota in tumor disease remains poorly understood. In this review, we critically reviewed recent literature about microbiota in the tumorigenesis and progression of MM. Importantly, we proposed that the emergence of microbiota in the microenvironment of multiple myeloma may be attributed to microbial dysbiosis and impaired intestinal barrier, due to the increased prevalence of MM in patients with obesity and diabetes, of which the characteristic phenotype is gut microbial dysbiosis and impaired intestinal barrier. When the intestinal barrier is damaged, dysbiotic microbiota and their metabolites, as well as dysregulated immune cells, may participate in the reshaping of the local immune microenvironment, and play pivotal roles in the tumorigenesis and development of multiple myeloma, probably by migrating to the bone marrow microenvironment from intestine. We also discuss the emerging microbiological manipulation strategies to improve long-term outcomes of MM, as well as the prospective of the state-of-the-art techniques to advance our knowledge about the biological implication in the microbiome in MM.

Resolving the spatial architecture of myeloma and its microenvironment at the single-cell level

In multiple myeloma spatial differences in the subclonal architecture, molecular signatures and composition of the microenvironment remain poorly characterized. To address this shortcoming, we perform multi-region sequencing on paired random bone marrow and focal lesion samples from 17 newly diagnosed patients. Using single-cell RNA- and ATAC-seq we find a median of 6 tumor subclones per patient and unique subclones in focal lesions. Genetically identical subclones display different levels of spatial transcriptional plasticity, including nearly identical profiles and pronounced heterogeneity at different sites, which can include differential expression of immunotherapy targets, such as CD20 and CD38. Macrophages are significantly depleted in the microenvironment of focal lesions. We observe proportional changes in the T-cell repertoire but no site-specific expansion of T-cell clones in intramedullary lesions. In conclusion, our results demonstrate the relevance of considering spatial heterogeneity in multiple myeloma with potential implications for models of cell-cell interactions and disease progression.

Identifying 1q amplification and PHF19 expressing high-risk cells 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 have been identified. One of these markers, PHF19, epigenetically regulates cell cycle and other processes and has already been studied using RNA-seq. In this study a massive (325,025 cells and 49 patients) single cell multiomic dataset was generated with jointly quantified ATAC- and RNA-seq for each cell and matched genomic profiles for each patient. We identified an association between one plasma cell subtype with myeloma progression that we have called relapsed/refractory plasma cells (RRPCs). These cells are associated with 1q alterations, TP53 mutations, and higher expression of PHF19. We also identified downstream regulation of cell cycle inhibitors in these cells, possible regulation of the transcription factor (TF) PBX1 on 1q, and determined that PHF19 may be acting primarily through this subset of cells.

Single-cell profiling in multiple myeloma: insights, problems, and promises

In a short time, single-cell platforms have become the norm in many fields of research, including multiple myeloma (MM). In fact, the large amount of cellular heterogeneity in MM makes single-cell platforms particularly attractive because bulk assessments can miss valuable information about cellular subpopulations and cell-to-cell interactions. The decreasing cost and increasing accessibility of single-cell platform, combined with breakthroughs in obtaining multiomics data for the same cell and innovative computational programs for analyzing data, have allowed single-cell studies to make important insights into MM pathogenesis; yet, there is still much to be done. In this review, we will first focus on the types of single-cell profiling and the considerations for designing a single-cell profiling experiment. Then, we will discuss what have learned from single-cell profiling about myeloma clonal evolution, transcriptional reprogramming, and drug resistance, and about the MM microenvironment during precursor and advanced disease.

γδ T cells in immunotherapies for B-cell malignancies

Despite the advancements in therapy for B cell malignancies and the increase in long-term survival of patients, almost half of them lead to relapse. Combinations of chemotherapy and monoclonal antibodies such as anti-CD20 leads to mixed outcomes. Recent developments in immune cell-based therapies are showing many encouraging results. γδ T cells, with their potential of functional plasticity and their anti-tumoral properties, emerged as good candidates for cancer immunotherapies. The representation and the diversity of γδ T cells in tissues and in the blood, in physiological conditions or in B-cell malignancies such as B cell lymphoma, chronic lymphoblastic leukemia or multiple myeloma, provides the possibility to manipulate them with immunotherapeutic approaches for these patients. In this review, we summarized several strategies based on the activation and tumor-targeting of γδ T cells, optimization of expansion protocols, and development of gene-modified γδ T cells, using combinations of antibodies and therapeutic drugs and adoptive cell therapy with autologous or allogenic γδ T cells following potential genetic modifications.

Single cell clonotypic and transcriptional evolution of multiple myeloma precursor disease

Multiple myeloma remains an incurable disease, and the cellular and molecular evolution from precursor conditions, including monoclonal gammopathy of undetermined significance and smoldering multiple myeloma, is incompletely understood. Here, we combine single-cell RNA and B cell receptor sequencing from fifty-two patients with myeloma precursors in comparison with myeloma and normal donors. Our comprehensive analysis reveals early genomic drivers of malignant transformation, distinct transcriptional features, and divergent clonal expansion in hyperdiploid versus non-hyperdiploid samples. Additionally, we observe intra-patient heterogeneity with potential therapeutic implications and identify distinct patterns of evolution from myeloma precursor disease to myeloma. We also demonstrate distinctive characteristics of the microenvironment associated with specific genomic changes in myeloma cells. These findings add to our knowledge about myeloma precursor disease progression, providing valuable insights into patient risk stratification, biomarker discovery, and possible clinical applications.