Co-evolution of tumor and immune cells during progression of multiple myeloma

Comprehensive evaluation of methods for identifying tissues or cell types of origin of the plasma cell-free transcriptome

Plasma cell-free RNA (cfRNA) is derived from cells in various tissues and organs throughout the body and reflects the physiological and pathological conditions. Identifying the origins of cfRNA is essential for comprehending its variations. Only a few tools are designed for cfRNA deconvolution, and most studies have relied on traditional bulk RNA methods. In this study, we employed human tissue and cell transcriptomic data as reference sets and evaluated the performance of seven deconvolution methods on cfRNA. We compared the analysis results of cell types and tissues of origin of plasma cfRNA and chose to use single-cell RNA sequencing (scRNA-seq) data as reference to conduct further evaluation of deconvolution methods. Subsequently, we assessed the accuracy and robustness of the methods by utilizing simulated cfRNA data generated from scRNA-seq. We also evaluated the methods' accuracy on real plasma cfRNA data by analyzing the correlation between the predicted cell proportions and the corresponding clinical indicators. Moreover, we compared the methods' effectiveness in revealing the impacts of diseases on cells and evaluated the performance of cancer classification models based on the cell origin data they provided. In summary, our study provides valuable insights into cfRNA origin analysis, enhancing its potential in biomedical research.

Myeloma cell-intrinsic ANXA1 elevation and T cell dysfunction contribute to BCMA-negative relapse after CAR-T therapy

Multiple myeloma (MM) relapse still occurs after a durable response to anti-B cell maturation antigen (BCMA) chimeric antigen receptor-engineered T (CAR-T) cell therapy with less-defined factors. Herein, we investigated a CAR-T-exposed MM patient who relapsed after 12 months of remission by single-cell transcriptome sequencing. The bone marrow CAR-T population at relapse exhibited exhaustion and proliferation attenuation. The recurrent myeloma cells were deficient in or weakly expressed TNFRSF17 (BCMA) but possessed an identical immunoglobulin clonality to the baseline tumor. Interestingly, combined with the transcriptome profile of the myeloma strains, MM cells with BCMA negativity featured high ANXA1 expression that was identified as an inferior prognostic indicator for MM patients. At a single-cell resolution, BCMA-negative myeloma could be present in the MM patients without CAR-T cell exposure and displayed an increased level of intrinsic ANXA1 transcripts. In vitro assays unveiled that Annexin A1 (ANXA1) elevation conferred growth capacity to BCMA-negative myeloma cells via AMPKα signaling activation and disturbed CAR-T cell fitness. Blockade of Annexin A1 reduced BCMA-negative myeloma cell proliferation. Murine models further demonstrated that Annexin A1 inhibition could effectively diminish BCMA-negative myeloma that escaped from CAR-T's attack. Together, our data identified ANXA1 as a potential target for BCMA-negative myeloma clearance. The ANXA1-targeting strategy might be helpful for CAR-T treatment optimization.

Consequences of training data composition for deep learning models in single-cell biology

Foundation models for single-cell transcriptomics have the potential to augment (or replace) purpose-built tools for a variety of common analyses, especially when data are sparse. Recent work with large language models has shown that training data composition greatly shapes performance; however, to date, single-cell foundation models have ignored this aspect, opting instead to train on the largest possible corpus. We systematically investigate the consequences of training dataset composition on the behavior of deep learning models of single-cell transcriptomics, focusing on human hematopoiesis as a tractable model system and including cells from adult and developing tissues, disease states, and perturbation atlases. We find that (1) these models generalize poorly to unseen cell types, (2) adding malignant cells to a healthy cell training corpus does not necessarily improve modeling of unseen malignant cells, and (3) including an embryonic stem cell differentiation atlas during training improves performance on out-of-distribution tasks. Our results emphasize the importance of diverse training data and suggest strategies to optimize future single-cell foundation models.

Single-cell analysis of neoplastic plasma cells identifies myeloma pathobiology mediators and potential targets

Multiple myeloma is a clonal plasma cell (PC) dyscrasia that arises from precursors and has been studied utilizing approaches focused on CD138+ cells. By combining single-cell RNA sequencing (scRNA-seq) with scB-cell receptor sequencing (scBCR-seq), we differentiate monoclonal/neoplastic from polyclonal/normal PCs and find more dysregulated genes, especially in precursor patients, than we would have by analyzing bulk PCs. To determine whether this approach can identify oncogenes that contribute to disease pathobiology, mitotic arrest deficient-2 like-1 (MAD2L1) and S-adenosylmethionine synthase isoform type-2 (MAT2A) are validated as targets with drug-like molecules that suppress myeloma growth in preclinical models. Moreover, functional studies show a role of lysosomal-associated membrane protein family member-5 (LAMP5), which is uniquely expressed in neoplastic PCs, in tumor progression and aggressiveness via interactions with c-MYC. Finally, a monoclonal antibody recognizing cell-surface LAMP5 shows efficacy as an antibody-drug conjugate and in a chimeric antigen receptor-guided T-cell format. These studies provide additional insights into myeloma biology and identify potential targeted therapeutic approaches that can be applied to reverse myeloma progression.

[Advancements in artificial intelligence for the precise diagnosis and treatment of hematological malignancies]

Hematological malignancy is a highly heterogeneous disease with complex biological characteristics and diverse clinical manifestations. Therefore, precise diagnosis and treatment are crucial and urgently needed. To further improve the accuracy of diagnosis and prognostication and to promote personalized therapy, artificial intelligence (AI) has been increasingly used. This study reviewed literature published in the last 5 years and summarized the application, benefits, and drawbacks of AI in the diagnosis, treatment, and prognosis of hematologic malignancies. Although AI can effectively improve the accuracy of diagnosis and therapy, low-quality data, poor interpretability of the model, and limited clinical transformation have impeded its popularization and application. In the future, the clinical application of AI in hematologic malignancy can be accelerated by establishing standards for clinical data processing, integrating multimodal information for accurate diagnosis and prognostication, and conducting systematic clinical verification of model algorithms.

Multiple Myeloma Insights from Single-Cell Analysis: Clonal Evolution, the Microenvironment, Therapy Evasion, and Clinical Implications

Multiple myeloma (MM) is a complex and heterogeneous hematologic malignancy characterized by clonal evolution, genetic instability, and interactions with a supportive tumor microenvironment. These factors contribute to treatment resistance, disease progression, and significant variability in clinical outcomes among patients. This review explores the mechanisms underlying MM progression, including the genetic and epigenetic changes that drive clonal evolution, the role of the bone marrow microenvironment in supporting tumor growth and immune evasion, and the impact of genomic instability. We highlight the critical insights gained from single-cell technologies, such as single-cell transcriptomics, genomics, and multiomics, which have enabled a detailed understanding of MM heterogeneity at the cellular level, facilitating the identification of rare cell populations and mechanisms of drug resistance. Despite the promise of advanced technologies, MM remains an incurable disease and challenges remain in their clinical application, including high costs, data complexity, and the need for standardized bioinformatics and ethical considerations. This review emphasizes the importance of continued research and collaboration to address these challenges, ultimately aiming to enhance personalized treatment strategies and improve patient outcomes in MM.

COMMD3 Regulates Copper Metabolism via the ATOX1-ATP7A-LOX Axis to Promote Multiple Myeloma Progression

BACKGROUND

Multiple myeloma (MM) is a hematologic malignancy characterized by the clonal proliferation of plasma cells, with extramedullary myeloma (EMM) being an aggressive form involving malignant infiltration beyond the bone marrow. Copper metabolism is essential for tumor proliferation and metastasis, with copper metabolism MURR1 domain (COMMD) proteins regulating these processes and maintaining copper homeostasis. Dysregulated copper homeostasis contributes to cancer progression, including MM, with elevated copper levels linked to disease aggressiveness and poor prognosis. This study investigates the role of the COMMD3 in mediating MM cell progression, particularly its influence on copper metabolism.

METHODS

Comprehensive bioinformatics analyses were conducted on bone marrow and extramedullary samples to determine the expression of COMMD3, which was validated through in vitro and in vivo functional assays. The MM cell lines RPMI8226 and MM1S underwent lentiviral transfection for COMMD3 overexpression and knockdown. RNA sequencing was conducted on COMMD3 knockdown cells to identify differentially expressed genes. Functional assays measured cell proliferation, migration, apoptosis, and copper metabolism, with a non-obese diabetic severe combined immune-deficiency gamma (NSG) mouse xenograft model providing in vivo validation.

RESULTS

Elevated COMMD3 expression was correlated with extramedullary myeloma and poor prognosis in MM patients. COMMD3 promoted MM cell proliferation and migration, modulating intracellular copper levels, likely through the ATOX1-ATP7A-LOX copper-metabolism-related pathway. High ATOX1 expression was correlated with worse outcomes, and ATOX1 inhibition abolished COMMD3's effects.

CONCLUSIONS

This study highlights the pivotal role of COMMD3 in MM progression, particularly via the ATOX1-ATP7A-LOX axis. These findings provide insights into EMM mechanisms and position COMMD3 as a potential therapeutic target. Future research is needed to validate these findings in larger clinical cohorts and to unravel the precise molecular interactions between COMMD3 and copper metabolism proteins.

Single-cell sequencing reveals the mechanisms of multiple myeloma progression: clarity or confusion?

Multiple myeloma (MM), the second most common hematologic malignancy, is characterized by the clonal expansion of myeloma cells and accumulation of genetic lesions. MM progression is accompanied by increased aggressiveness and drug resistance. Even the goal of "cure" remains hard to reach for most patients, advances in diagnosis and treatment have allowed some to achieve durable remissions and transition to plateau phase. Single-cell sequencing, with its powerful ability to analyze cellular heterogeneity and molecular patterns at ground-breaking resolution, is informative for deciphering tumors and their microenvironment. In this review, we summarize the new insights of studies facilitated by emerging single-cell sequencing into clonal evolution, myeloma-supported microenvironment transformation, epigenetic changes, and novel prognostic and therapeutic strategies for MM, revealing the key mechanisms underlying MM progression and the direction of future efforts. With the continuous expansion of the research scope and optimization of related technologies, single-cell sequencing is expected to revolutionize our understanding of the biology and evolutionary dynamics of MM and contribute to the radical and precise improvement of treatment.

A systematic literature review on clonal evolution events preceding relapse in multiple myeloma

Despite considerable treatment advances, multiple myeloma (MM) remains an incurable hematological cancer due to treatment resistance. A systematic literature search was conducted to identify determinants for clonal evolution driving relapse and drug resistance in MM. A total of 631 non-duplicate publications were screened of which 28 articles were included for data extraction. Genetic alterations, mutational signatures, evolutionary trajectories, and non-genetic determinants were identified as key topics to characterize clonal evolution in relapsed MM. A variety of factors led to clonal diversification and increased tumor mutation burden, such as MAPK-Ras mutations and incremental changes related to chromosomal bands 1 and 17, while mutational signature analyses revealed that APOBEC activity and melphalan treatment leave a distinct impact on the clonal composition in MM genomes. To capture and dissect tumor heterogeneity, our review suggests combining methods or using technical approaches with high resolution to assess the impact of clonal evolution.

Emerging strategies to investigate the biology of early cancer

Early detection and intervention of cancer or precancerous lesions hold great promise to improve patient survival. However, the processes of cancer initiation and the normal-precancer-cancer progression within a non-cancerous tissue context remain poorly understood. This is, in part, due to the scarcity of early-stage clinical samples or suitable models to study early cancer. In this Review, we introduce clinical samples and model systems, such as autochthonous mice and organoid-derived or stem cell-derived models that allow longitudinal analysis of early cancer development. We also present the emerging techniques and computational tools that enhance our understanding of cancer initiation and early progression, including direct imaging, lineage tracing, single-cell and spatial multi-omics, and artificial intelligence models. Together, these models and techniques facilitate a more comprehensive understanding of the poorly characterized early malignant transformation cascade, holding great potential to unveil key drivers and early biomarkers for cancer development. Finally, we discuss how these new insights can potentially be translated into mechanism-based strategies for early cancer detection and prevention.

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.

scStateDynamics: deciphering the drug-responsive tumor cell state dynamics by modeling single-cell level expression changes

Understanding tumor cell heterogeneity and plasticity is crucial for overcoming drug resistance. Single-cell technologies enable analyzing cell states at a given condition, but catenating static cell snapshots to characterize dynamic drug responses remains challenging. Here, we propose scStateDynamics, an algorithm to infer tumor cell state dynamics and identify common drug effects by modeling single-cell level gene expression changes. Its reliability is validated on both simulated and lineage tracing data. Application to real tumor drug treatment datasets identifies more subtle cell subclusters with different drug responses beyond static transcriptome similarity and disentangles drug action mechanisms from the cell-level expression changes.

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.

Single-cell sequencing analysis of multiple myeloma heterogeneity and identification of new theranostic targets

Multiple myeloma (MM) is a heterogeneous and incurable tumor characterized by the malignant proliferation of plasma cells. It is necessary to clarify the heterogeneity of MM and identify new theranostic targets. We constructed a single-cell transcriptome profile of 48,293 bone marrow cells from MM patients and health donors (HDs) annotated with 7 continuous B lymphocyte lineages. Through CellChat, we discovered that the communication among B lymphocyte lineages between MM and HDs was disrupted, and unique signaling molecules were observed. Through pseudotime analysis, it was found that the differences between MM and HDs were mainly reflected in plasma cells. These differences are primarily related to various biological processes involving mitochondria. Then, we identified the key subpopulation associated with the malignant proliferation of plasma cells. This group of cells exhibited strong proliferation ability, high CNV scores, high expression of frequently mutated genes, and strong glucose metabolic activity. Furthermore, we demonstrated the therapeutic potential of WNK1 as a target. Our study provides new insights into the development of B cells and the heterogeneity of plasma cells in MM and suggests that WNK1 is a potential therapeutic target for MM.

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.

Unveiling the cellular landscape: insights from single-cell RNA sequencing in multiple myeloma

Objective

The aim of this research was to gain a thorough understanding of the processes involved in cell communication and discover potential indicators for treating multiple myeloma (MM) through the use of single-cell RNA sequencing (scRNA-seq). And explored the expression of multiple myeloma-related subgroups on metal ion-related pathways to explore the relationship between MM and metal ions.

Methods

We performed a fair examination using single-cell RNA sequencing on 32 bone marrow specimens collected from 22 individuals at different points of MM advancement and 9 individuals without any health issues. To analyze the scRNA-seq data, we employed advanced computational algorithms, including Slingshot, Monocle2, and other methodologies. Specifically, Slingshot and Monocle2 enabled us to simulate the biological functionalities of different cell populations and map trajectories of cell developmental pathways. Additionally, we utilized the UMAP algorithm, a powerful dimension reduction technique, to cluster cells and identify genes that were differentially expressed across clusters.

Results

Our study revealed distinct gene expression patterns and molecular pathways within each patient, which exhibited associations with disease progression. The analysis provided insights into the tumor microenvironment (TME), intra- and inter-patient heterogeneity, and cell-cell interactions mediated by ligand-receptor signaling. And found that multiple myeloma-related subgroups were expressed higher levels in MMP and TIMP pathways, there were some associations.

Conclusion

Our study presents a fresh perspective for future research endeavors and clinical interventions in the field of MM. The identified gene expression patterns and molecular pathways hold immense potential as therapeutic targets for the treatment of multiple myeloma. The utilization of scRNA-seq technology has significantly contributed to a more precise understanding of the complex cellular processes and interactions within MM. Through these advancements, we are now better equipped to unravel the underlying mechanisms driving the development and progression of this complex disease.

Inference of genomic lesions from single-cell RNA-seq in myeloma improves functional intraclonal and interclonal analysis

ABSTRACT

Smoldering multiple myeloma (SMM) is an asymptomatic plasma cell (PC) neoplasm that may evolve with variable frequency into multiple myeloma (MM). SMM is initiated by chromosomal translocations involving the immunoglobulin heavy-chain locus or by hyperdiploidy and evolves through acquisition of additional genetic lesions. In this scenario, we aimed at establishing a reliable analysis pipeline to infer genomic lesions from transcriptomic analysis, by combining single-cell RNA sequencing (scRNA-seq) with B-cell receptor sequencing and copy number abnormality (CNA) analysis to identify clonal PCs at the genetic level along their specific transcriptional landscape. We profiled 20 465 bone marrow PCs derived from 5 patients with SMM/MM and unbiasedly identified clonal and polyclonal PCs. Hyperdiploidy, t(11;14), and t(6;14) were identified at the scRNA level by analysis of chimeric reads. Subclone functional analysis was improved by combining transcriptome with CNA analysis. As examples, we illustrate the different functional properties of a light-chain escape subclone in SMM and of different B-cell and PC subclones in a patient affected by Wäldenstrom macroglobulinemia and SMM. Overall, our data provide a proof of principle for inference of clinically relevant genotypic data from scRNA-seq, which in turn will refine functional annotation of the clonal architecture of PC dyscrasias.

Multiple myeloma: signaling pathways and targeted therapy

Multiple myeloma (MM) is the second most common hematological malignancy of plasma cells, characterized by osteolytic bone lesions, anemia, hypercalcemia, renal failure, and the accumulation of malignant plasma cells. The pathogenesis of MM involves the interaction between MM cells and the bone marrow microenvironment through soluble cytokines and cell adhesion molecules, which activate various signaling pathways such as PI3K/AKT/mTOR, RAS/MAPK, JAK/STAT, Wnt/β-catenin, and NF-κB pathways. Aberrant activation of these pathways contributes to the proliferation, survival, migration, and drug resistance of myeloma cells, making them attractive targets for therapeutic intervention. Currently, approved drugs targeting these signaling pathways in MM are limited, with many inhibitors and inducers still in preclinical or clinical research stages. Therapeutic options for MM include non-targeted drugs like alkylating agents, corticosteroids, immunomodulatory drugs, proteasome inhibitors, and histone deacetylase inhibitors. Additionally, targeted drugs such as monoclonal antibodies, chimeric antigen receptor T cells, bispecific T-cell engagers, and bispecific antibodies are being used in MM treatment. Despite significant advancements in MM treatment, the disease remains incurable, emphasizing the need for the development of novel or combined targeted therapies based on emerging theoretical knowledge, technologies, and platforms. In this review, we highlight the key role of signaling pathways in the malignant progression and treatment of MM, exploring advances in targeted therapy and potential treatments to offer further insights for improving MM management and outcomes.

Endothelial injury and dysfunction with emerging immunotherapies in multiple myeloma, the impact of COVID-19, and endothelial protection with a focus on the evolving role of defibrotide

Patients with multiple myeloma (MM) were among the groups impacted more severely by the COVID-19 pandemic, with higher rates of severe disease and COVID-19-related mortality. MM and COVID-19, plus post-acute sequelae of SARS-CoV-2 infection, are associated with endothelial dysfunction and injury, with overlapping inflammatory pathways and coagulopathies. Existing treatment options for MM, notably high-dose therapy with autologous stem cell transplantation and novel chimeric antigen receptor (CAR) T-cell therapies and bispecific T-cell engaging antibodies, are also associated with endothelial cell injury and mechanism-related toxicities. These pathologies include cytokine release syndrome (CRS) and neurotoxicity that may be exacerbated by underlying endotheliopathies. In the context of these overlapping risks, prophylaxis and treatment approaches mitigating the inflammatory and pro-coagulant effects of endothelial injury are important considerations for patient management, including cytokine receptor antagonists, thromboprophylaxis with low-molecular-weight heparin and direct oral anticoagulants, and direct endothelial protection with defibrotide in the appropriate clinical settings.

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.

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.

Identification of biomarkers in multiple myeloma: A comprehensive study combining microarray analysis and Mendelian randomization

Despite remarkable advancements in the treatment of multiple myeloma (MM), relapse remains a challenge. However, the mechanisms underlying this disease remain unclear. This study aimed to identify potential biomarkers that could open new avenues for MM treatment. Microarray data and clinical characteristics of patients with MM were obtained from the Gene Expression Omnibus database. Differential expression analysis and protein-protein interaction (PPI) network construction were used to identify hub genes associated with MM. Predictive performance was further assessed using receiver operating characteristic curves and nomogram construction. Functional enrichment analysis was conducted to investigate possible mechanisms. Mendelian randomization (MR) was used to evaluate the causal relationship between the crucial gene and MM risk. Topological analysis of the PPI network revealed five hub genes associated with MM, with myeloperoxidase (MPO) being the key gene owing to its highest degree and area under the curve values. MPO showed significant differences between patients with MM and controls across all datasets. Functional enrichment analysis revealed a strong association between MPO and immune-related pathways in MM. MR analysis confirmed a causal relationship between MPO and the risk of MM. By integrating microarray analysis and MR, we successfully identified and validated MPO as a promising biomarker for MM that is potentially implicated in MM pathogenesis and progression through immune-related pathways.

Bone marrow stromal cells induce chromatin remodeling in multiple myeloma cells leading to transcriptional changes

The natural history of multiple myeloma is characterized by its localization to the bone marrow and its interaction with bone marrow stromal cells. The bone marrow stromal cells provide growth and survival signals, thereby promoting the development of drug resistance. Here, we show that the interaction between bone marrow stromal cells and myeloma cells (using human cell lines) induces chromatin remodeling of cis-regulatory elements and is associated with changes in the expression of genes involved in the cell migration and cytokine signaling. The expression of genes involved in these stromal interactions are observed in extramedullary disease in patients with myeloma and provides the rationale for survival of myeloma cells outside of the bone marrow microenvironment. Expression of these stromal interaction genes is also observed in a subset of patients with newly diagnosed myeloma and are akin to the transcriptional program of extramedullary disease. The presence of such adverse stromal interactions in newly diagnosed myeloma is associated with accelerated disease dissemination, predicts the early development of therapeutic resistance, and is of independent prognostic significance. These stromal cell induced transcriptomic and epigenomic changes both predict long-term outcomes and identify therapeutic targets in the tumor microenvironment for the development of novel therapeutic approaches.

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.

Identification of an angiogenesis-related risk score model for survival prediction and immunosubtype screening in multiple myeloma

BACKGROUND

Multiple myeloma (MM) is an incurable B-cell malignancy, but with the emergence of immunotherapy, a potential cure is hopeful. The individualized interaction between the tumor and bone marrow (BM) microenvironment determines the response to immunotherapy. Angiogenesis is a constant hallmark of the BM microenvironment in MM. However, little is known about the potency ability of angiogenesis-associated genes (AAGs) to regulate the immune microenvironment of MM patients.

METHODS

We comprehensively dissected the associations between angiogenesis and genomic landscapes, prognosis, and the immune microenvironment by integrating 36 AAGs. Immunohistochemistry was performed to verify the correlation between angiogenic factor expression and patient prognosis. Single-sample gene set enrichment analysis was applied to quantify the relative abundance of 28 infiltrating cells. The AAG score was constructed using the least absolute shrinkage and selection operator Cox regression model.

RESULTS

Angiogenesis was closely correlated with MM patient prognosis, and the mutation intensity of the AAGs was low. Immunohistochemistry confirmed that high microvessel density predicted poor prognosis. Three AAG clusters and two gene clusters with distinct clinical outcomes and immune characteristics were identified. The established AAG_score model performed well in predicting patient prognosis and active immunotherapy response. The high-AAG_score subgroup was characterized by reduced immune cell infiltration, poor prognosis, and inactive immunotherapy response. Multivariate analyses indicated that the AAG_score was strongly robust and independent among the prognostic variables.

CONCLUSION

This study revealed that angiogenesis is significantly related to MM patient prognosis and immune phenotype. Evaluating the AAG signature was conducive to predicting patient response to immunotherapy and guiding more efficacious immunotherapy strategies.

Global, regional, and national burden and quality of care of multiple myeloma, 1990-2019

Background

Multiple myeloma (MM) is the second most common haematologic malignancy, presenting a great disease burden on the general population; however, the quality of care of MM is overlooked. We therefore assessed gains and disparity in quality of care worldwide from 1990 to 2019 based on a novel summary indicator - the quality of care index (QCI) - and examined its potential for improvement.

Methods

Using the Global Burden of Disease 2019 data set, we calculated the QCI of MM for 195 countries and territories. We used the principal component analysis to extract the first principal component of ratios with the combinations of mortality to incidence, prevalence to incidence, disability-adjusted life years to prevalence, and years of life lost to years lived with disability as QCI. We also conducted a series of descriptive and comparative analyses of QCI disparities with age, gender, period, geographies, and sociodemographic development, and compared the QCI among countries with similar socio-demographic index (SDI) through frontier analysis.

Results

The age-standardised rates of MM were 1.92 (95% uncertainty interval (UI) = 1.68, 2.12) in incidence and 1.42 (95% UI = 1.24, 1.52) in deaths per 100 000 population in 2019, and were predicted to increase in the future. The global age-standardised QCI increased from 51.31 in 1990 to 64.28 in 2019. In 2019, New Zealand had the highest QCI at 99.29 and the Central African Republic had the lowest QCI at 10.74. The gender disparity of QCI was reduced over the years, with the largest being observed in the sub-Saharan region. Regarding age, QCI maintained a decreasing trend in patients aged >60 in SDI quintiles. Generally, QCI improved with the SDI increase. Results of frontier analysis suggested that there is a potential to improve the quality of care across all levels of development spectrum.

Conclusions

Quality of care of MM improved during the past three decades, yet disparities in MM care remain across different countries, age groups, and genders. It is crucial to establish local objectives aimed at enhancing MM care and closing the gap in health care inequality.

Neosetophomone B induces apoptosis in multiple myeloma cells via targeting of AKT/SKP2 signaling pathway

Multiple myeloma (MM) is a hematologic malignancy associated with malignant plasma cell proliferation in the bone marrow. Despite the available treatments, drug resistance and adverse side effects pose significant challenges, underscoring the need for alternative therapeutic strategies. Natural products, like the fungal metabolite neosetophomone B (NSP-B), have emerged as potential therapeutic agents due to their bioactive properties. Our study investigated NSP-B's antitumor effects on MM cell lines (U266 and RPMI8226) and the involved molecular mechanisms. NSP-B demonstrated significant growth inhibition and apoptotic induction, triggered by reduced AKT activation and downregulation of the inhibitors of apoptotic proteins and S-phase kinase protein. This was accompanied by an upregulation of p21Kip1 and p27Cip1 and an elevated Bax/BCL2 ratio, culminating in caspase-dependent apoptosis. Interestingly, NSP-B also enhanced the cytotoxicity of bortezomib (BTZ), an existing MM treatment. Overall, our findings demonstrated that NSP-B induces caspase-dependent apoptosis, increases cell damage, and suppresses MM cell proliferation while improving the cytotoxic impact of BTZ. These findings suggest that NSP-B can be used alone or in combination with other medicines to treat MM, highlighting its importance as a promising phytoconstituent in cancer therapy.

Multimodal investigation reveals the neuroprotective mechanism of Angong Niuhuang pill for intracerebral hemorrhage: Converging bioinformatics, network pharmacology, and experimental validation

ETHNOPHARMACOLOGICAL RELEVANCE

Angong Niuhuang Pill (ANP) is a traditional Chinese medicine formula that has been used clinically for many years in the treatment of cerebral hemorrhage. It is composed of ingredients such as calculus bovis, moschus, and others. Ancient texts have documented that ANP's multiple components possess properties such as heat-clearing, detoxification, and sedation, which can be effective in treating conditions such as coma and stroke. However, the underlying mechanisms of ANP's potential actions are still under investigation.

AIM OF THE STUDY

ANP is a Chinese medicine widely utilized for the treatment of intracerebral hemorrhage (ICH). However, the precise mechanism underlying the therapeutic effects remains largely elusive. The present study aims to unravel the effects and pharmacological molecular mechanisms of ANP in combatting ICH, employing a comprehensive network pharmacology approach and experimental validation.

MATERIALS AND METHODS

The molecular targets of ANP and ICH were obtained from various databases, followed by the construction of protein-protein interaction (PPI) networks using the STRING database. Further, gene ontology (GO) enrichment and Kyoto encyclopedia of genes and genomes (KEGG) analyses were conducted using the Metascape database and Cytoscape, respectively. Finally, molecular docking was performed. We performed a series of behavioral tests, immunohistochemical staining, TUNEL staining, and Western Blot to verify the effects of ANP.

RESULTS

IL-6, JUN, MMP9, IL-1β, VEGFA were the main candidate targets and were associated with fluid shear stress and atherosclerosis, TNF signaling pathway, etc. It is suggested that the potential mechanism of ANP against ICH may be mainly related to pyroptosis, inflammation. In vivo validation showed that ANP treatment significantly reduced the number of TUNEL-positive cells and ANP inhibited the activation of Iba-1 positive neurons, and suppressed the expression of inflammatory factors and pyroptosis indicators. In addition, ANP improved the cognitive level and motor ability of ICH mice.

CONCLUSION

The results of the study combined with virtual screening and experimental validation showed that ANP has an important contribution in protecting the brain from neuronal damage by regulating the pathways of inflammation and pyroptosis, laying the foundation and innovative ideas for future studies.

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.

Interleukin-1 receptor antagonist: An alternative therapy for cancer treatment

The interleukin-1 receptor antagonist (IL-1Ra) is an anti-inflammatory cytokine and a naturally occurring antagonist of the IL-1 receptor. It effectively counteracts the IL-1 signaling pathway mediated by IL-1α/β. Over the past few decades, accumulating evidence has suggested that IL-1 signaling plays an essential role in tumor formation, growth, and metastasis. Significantly, anakinra, the first United States Food and Drug Administration (FDA)-approved IL-1Ra drug, has demonstrated promising antitumor effects in animal studies. Numerous clinical trials have subsequently incorporated anakinra into their cancer treatment protocols. In this review, we comprehensively discuss the research progress on the role of IL-1 in tumors and summarize the significant contribution of IL-1Ra (anakinra) to tumor immunity. Additionally, we analyze the potential value of IL-1Ra as a biomarker from a clinical perspective. This review is aimed to highlight the important link between inflammation and cancer and provide potential drug targets for future cancer therapy.

Tumor Environment Regression Therapy Implemented by Switchable Prune-to-Essence Nanoplatform Unleashed Systemic Immune Responses

Coevolution of tumor cells and surrounding stroma results in protective protumoral environment, in which abundant vessel, stiff structure and immunosuppression promote each other, cooperatively incurring deterioration and treatment compromise. Reversing suchenvironment may transform tumors from treatment-resistant to treatment-vulnerable. However, effective reversion requires synergistic comprehensive regression of such environment under precise control. Here, the first attempt to collaboratively retrograde coevolutionary tumor environment to pre-oncogenesis status, defined as tumor environment regression therapy, is made for vigorous immune response eruption by a switchable prune-to-essence nanoplatform (Pres) with simplified composition and fabrication process. Through magnetic targeting and multimodal imaging of Pres, tumor environment regression therapy is guided, optimized and accomplished in a trinity way: Antiangiogenesis is executed to rarefy vessels to impede tumor progression. By seizing the time, cancer associated fibroblasts are eliminated to diminish collagen and loosen the stiff structure for deep penetration of Pres, which alternately functioned in deeper tumors, forming a positive feedback loop. Through this loop, immune cell infiltration, immunosuppression mitigation and immunogenic cells death induction are all fulfilled and further escalated in the regressed environment. These transformations consequently unleashed systemic immune responses and generated immune memory against carcinoma. This study provides new insights intotreatment of solid tumors.

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.

Epigenome editing in cancer: Advances and challenges for potential therapeutic options

Cancers are diseases caused by genetic and non-genetic environmental factors. Epigenetic alterations, some attributed to non-genetic factors, can lead to cancer development. Epigenetic changes can occur in tumor suppressors or oncogenes, or they may contribute to global cell state changes, making cells abnormal. Recent advances in gene editing technology show potential for cancer treatment. Herein, we will discuss our current knowledge of epigenetic alterations occurring in cancer and epigenetic editing technologies that can be applied to developing therapeutic options.

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.

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.

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.

Identification of mutation gene prognostic biomarker in multiple myeloma through gene panel exome sequencing and transcriptome analysis in Chinese population

BACKGROUND

The 5-year survival rate of multiple myeloma (MM) in China is less than 40%, with considerable individual heterogeneity. Gene mutations are important predictive biomarkers that influence MM treatment decision. The aim of our study was to uncover the clinical significance of mutated genes in MM in the Chinese population.

METHODS

Targeted exon panel sequencing was performed of 400 genes to detect the gene mutation status in plasma cells from 50 patients with MM. DAVID was used to explore the functions and pathways of mutated genes. Detection of mutant gene expression, prognosis and immune cell infiltration with GSE6477. GEO2R was utilized to identify differentially expressed genes (DEGs). Kaplan-Meier and CIBERSORT were applied to compare survival distributions and evaluate the gene expression associated with immune cell infiltration, respectively.

RESULTS

Mutations of 337 genes were identified in MM. The mutation types included SNP, INS, and DEL, but the dominant mutation type was SNP. Function and pathway analysis of mutant genes were performed to elucidate DNA modifications. We identified a total number of 660 downregulated and 587 upregulated genes from the GSE6477 dataset. Thirty-three common genes were present in both the mutant genes and DEGs. The functions and pathways of the mutated genes were enriched in myeloid cell differentiation, regulation of hemopoiesis, etc. Moreover, we found that the low expression of BCL6, BIRC3, HLA-DQA1, and VCAN was correlated with poor prognosis in MM.

CONCLUSIONS

The mutations and low expression of BCL6, BIRC3, HLA-DQA1, and VCAN were correlated with poor prognosis and immune cell infiltration in MM. This study is the first to reveal the spectrum of mutations in the Chinese population by the use of an NGS panel.

Direct-Current Electrical Detection of Surface-Acoustic-Wave-Driven Ferromagnetic Resonance

Surface acoustic waves (SAW) provide a promising platform to study spin-phonon coupling, which can be achieved by SAW-driven ferromagnetic resonance (FMR) for efficient acoustic manipulation of spin. Although the magneto-elastic effective field model has achieved great success in describing SAW-driven FMR, the magnitude of the effective field acting on the magnetization induced by SAW still remains hard to access. Here, by integrating ferromagnetic stripes with SAW devices, direct-current detection for SAW-driven FMR based on electrical rectification is reported. By analyzing FMR rectified voltage, the effective fields are straightforwardly characterized and extracted, which exhibits the advantages of better integration compatibility and lower cost than traditional methods such as vector-network analyzer-based techniques. A large nonreciprocal rectified voltage is obtained, which is attributed to the coexistence of in-plane and out-of-plane effective fields. The effective fields can be modulated by controlling the longitudinal and shear strains within the films to achieve almost 100% nonreciprocity ratio, demonstrating the potential for electrical switches. Besides its fundamental significance, this finding provides a unique opportunity for a designable spin acousto-electronic device and its convenient signal readout.

Identification of evolutionary mechanisms of myelomatous effusion by single-cell RNA sequencing

Myelomatous effusion (ME) is a rare manifestation of extramedullary multiple myeloma (MM) with limited therapeutic options and poor outcomes. The molecular mechanisms underlying ME are incompletely understood. We profiled transcriptomes of bone marrow, peripheral blood (PB), and pleural effusion/ascites from 3 patients with ME using single-cell RNA sequencing analysis. We found that ME contained a higher percentage of cytotoxic T cells, whereas PB contained a higher proportion of naive T cells. Malignant cells varied within and between sites and patients in their expression of signatures. We identified a gene module highly expressed in intramedullary and extramedullary plasma cell clusters and defined cell clusters expressing this gene set as extramedullary-initiating cells (EMICs). This gene set was associated with increased cellular proliferation, involved in p53 signaling, and related to poor prognosis in MM. The transcriptional regulators E2F1, YY1, and SMAD1 were activated in EMICs. Leukocyte immunoglobulin-like receptor subfamily B4 (LILRB4) was upregulated in extramedullary EMICs. We confirmed that LILRB4 promoted MM cell migration in vitro. This study provided insight into the evolutionary mechanisms of ME and defined EMICs and LILRB4 associated with extramedullary development.

c-FOS is an integral component of the IKZF1 transactivator complex and mediates lenalidomide resistance in multiple myeloma

BACKGROUND

The immunomodulatory drug lenalidomide, which is now widely used for the treatment of multiple myeloma (MM), exerts pharmacological action through the ubiquitin-dependent degradation of IKZF1 and subsequent down-regulation of interferon regulatory factor 4 (IRF4), a critical factor for the survival of MM cells. IKZF1 acts principally as a tumour suppressor via transcriptional repression of oncogenes in normal lymphoid lineages. In contrast, IKZF1 activates IRF4 and other oncogenes in MM cells, suggesting the involvement of unknown co-factors in switching the IKZF1 complex from a transcriptional repressor to an activator. The transactivating components of the IKZF1 complex might promote lenalidomide resistance by residing on regulatory regions of the IRF4 gene to maintain its transcription after IKZF1 degradation.

METHODS

To identify unknown components of the IKZF1 complex, we analyzed the genome-wide binding of IKZF1 in MM cells using chromatin immunoprecipitation-sequencing (ChIP-seq) and screened for the co-occupancy of IKZF1 with other DNA-binding factors on the myeloma genome using the ChIP-Atlas platform.

RESULTS

We found that c-FOS, a member of the activator protein-1 (AP-1) family, is an integral component of the IKZF1 complex and is primarily responsible for the activator function of the complex in MM cells. The genome-wide screening revealed the co-occupancy of c-FOS with IKZF1 on the regulatory regions of IKZF1-target genes, including IRF4 and SLAMF7, in MM cells but not normal bone marrow progenitors, pre-B cells or mature T-lymphocytes. c-FOS and IKZF1 bound to the same consensus sequence as the IKZF1 complex through direct protein-protein interactions. The complex also includes c-JUN and IKZF3 but not IRF4. Treatment of MM cells with short-hairpin RNA against FOS or a selective AP-1 inhibitor significantly enhanced the anti-MM activity of lenalidomide in vitro and in two murine MM models. Furthermore, an AP-1 inhibitor mitigated the lenalidomide resistance of MM cells.

CONCLUSIONS

C-FOS determines lenalidomide sensitivity and mediates drug resistance in MM cells as a co-factor of IKZF1 and thus, could be a novel therapeutic target for further improvement of the prognosis of MM patients.

Overcoming proteasome inhibitor resistance in the immunotherapy era

Proteasome inhibitors (PIs) are a fascinating class of small molecules that disrupt protein homeostasis and are highly efficacious in the blood cancer multiple myeloma. However, PIs are not curative, and overcoming PI resistance to extend patient survival remains a major unmet need. Recent strategies to overcome PI resistance, including inhibiting alternative protein homeostasis pathways and targeting the mitochondrion as a nexus of metabolic adaptation to PIs, are gaining momentum. However, these focused approaches may be surpassed or even obviated by quickly emerging immunotherapy strategies that do not selectively target PI resistance mechanisms but are highly efficacious in PI-resistant disease, nonetheless. Informed by insights from these promising areas of research moving in parallel, we propose that pharmacological strategies to enforce immunotherapeutic vulnerabilities in resistant disease may provide a unified outlook to overcome PI resistance in a 'new era' of myeloma treatment.

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.

New genetic and epigenetic insights into the chemokine system: the latest discoveries aiding progression toward precision medicine

Over the past thirty years, the importance of chemokines and their seven-transmembrane G protein-coupled receptors (GPCRs) has been increasingly recognized. Chemokine interactions with receptors trigger signaling pathway activity to form a network fundamental to diverse immune processes, including host homeostasis and responses to disease. Genetic and nongenetic regulation of both the expression and structure of chemokines and receptors conveys chemokine functional heterogeneity. Imbalances and defects in the system contribute to the pathogenesis of a variety of diseases, including cancer, immune and inflammatory diseases, and metabolic and neurological disorders, which render the system a focus of studies aiming to discover therapies and important biomarkers. The integrated view of chemokine biology underpinning divergence and plasticity has provided insights into immune dysfunction in disease states, including, among others, coronavirus disease 2019 (COVID-19). In this review, by reporting the latest advances in chemokine biology and results from analyses of a plethora of sequencing-based datasets, we outline recent advances in the understanding of the genetic variations and nongenetic heterogeneity of chemokines and receptors and provide an updated view of their contribution to the pathophysiological network, focusing on chemokine-mediated inflammation and cancer. Clarification of the molecular basis of dynamic chemokine-receptor interactions will help advance the understanding of chemokine biology to achieve precision medicine application in the clinic.

Expression analysis of TRAF2‑ and NCK‑interacting protein kinase (TNIK) and phosphorylated TNIK in papillary thyroid carcinoma

The aim of the present study was to evaluate the expression of TRAF2- and NCK-interacting kinase (TNIK) and the levels of the active form of TNIK, phosphorylated (p)-TNIK, in papillary thyroid carcinoma (PTC), and to identify and compare the levels of TNIK and p-TNIK among PTC, benign thyroid tumors and normal tissues. The levels of TNIK and p-TNIK were examined by reverse transcription-quantitative (RT-q)PCR and immunohistochemical analysis (IHC) in PTC, benign thyroid tumors and normal tissues, and their association with clinicopathological features was evaluated. First, analysis of the Gene Expression Profiling Interactive Analysis and The Cancer Genome Atlas datasets suggested that the mRNA expression of TNIK was markedly increased in PTC tissues compared with that in normal tissues. RT-qPCR analyses then indicated that the relative mRNA expression of TNIK in PTC tissues was 4.47±6.16, which was significantly higher than that in adjacent tissues 2.57±5.83. The IHC results suggested that the levels of TNIK and p-TNIK in PTC tissues were markedly elevated compared with those in benign thyroid tumors and normal tissues. The levels of p-TNIK in patients with PTC were significantly associated with extrathyroidal extension (χ²=4.199, P=0.040). Positive staining for TNIK was observed in 187 out of 202 (92.6%) cases in the cytoplasm, nucleus or cytomembrane of PTC cells. Among the 187 positive cases, cytoplasm expression was identified in 162 cases (86.6%), nuclear expression in 17 cases (9.1%) and cytomembrane expression in 8 cases (4.3%). Positive staining for p-TNIK was observed in 179 out of 202 (88.6%) cases in the nuclei, cytoplasm or cytomembrane of PTC cells. In the 179 p-TNIK-positive cases, localization in the nuclei plus cytoplasm was identified in 142 cases (79.3%), nuclear localization in 9 cases (5.0%), presence in the cytoplasm in 21 cases (11.7%) and cytomembrane localization in 7 cases (3.9%). Both TNIK and p-TNIK were upregulated in PTC tissues and p-TNIK was significantly associated with extrathyroidal extension. It may act as a crucial oncogene to participate in PTC carcinogenesis and progression.

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.

Single-cell technologies in multiple myeloma: new insights into disease pathogenesis and translational implications

Multiple myeloma (MM) is a hematological malignancy characterized by clonal proliferation of plasma cells. Although therapeutic advances have been made to improve clinical outcomes and to prolong patients' survival in the past two decades, MM remains largely incurable. Single-cell sequencing (SCS) is a powerful method to dissect the cellular and molecular landscape at single-cell resolution, instead of providing averaged results. The application of single-cell technologies promises to address outstanding questions in myeloma biology and has revolutionized our understanding of the inter- and intra-tumor heterogeneity, tumor microenvironment, and mechanisms of therapeutic resistance in MM. In this review, we summarize the recently developed SCS methodologies and latest MM research progress achieved by single-cell profiling, including information regarding the cancer and immune cell landscapes, tumor heterogeneities, underlying mechanisms and biomarkers associated with therapeutic response and resistance. We also discuss future directions of applying transformative SCS approaches with contribution to clinical translation.

Mass Cytometry reveals unique phenotypic patterns associated with subclonal diversity and outcomes in multiple myeloma

Multiple myeloma (MM) remains an incurable plasma cell (PC) malignancy. Although it is known that MM tumor cells display extensive intratumoral genetic heterogeneity, an integrated map of the tumor proteomic landscape has not been comprehensively evaluated. We evaluated 49 primary tumor samples from newly diagnosed or relapsed/refractory MM patients by mass cytometry (CyTOF) using 34 antibody targets to characterize the integrated landscape of single-cell cell surface and intracellular signaling proteins. We identified 13 phenotypic meta-clusters across all samples. The abundance of each phenotypic meta-cluster was compared to patient age, sex, treatment response, tumor genetic abnormalities and overall survival. Relative abundance of several of these phenotypic meta-clusters were associated with disease subtypes and clinical behavior. Increased abundance of phenotypic meta-cluster 1, characterized by elevated CD45 and reduced BCL-2 expression, was significantly associated with a favorable treatment response and improved overall survival independent of tumor genetic abnormalities or patient demographic variables. We validated this association using an unrelated gene expression dataset. This study represents the first, large-scale, single-cell protein atlas of primary MM tumors and demonstrates that subclonal protein profiling may be an important determinant of clinical behavior and outcome.

Dissecting molecular mechanisms of immune microenvironment dysfunction in multiple myeloma and precursor conditions

Multiple myeloma (MM) is a disease of clonally differentiated plasma cells. MM is almost always preceded by precursor conditions, monoclonal gammopathy of unknown significance (MGUS), and smoldering MM (SMM) through largely unknown molecular events. Genetic alterations of the malignant plasma cells play a critical role in patient clinical outcomes. Del(17p), t(4;14), and additional chromosomal alterations such as del(1p32), gain(1q) and MYC translocations are involved in active MM evolution. Interestingly, these genetic alterations appear strikingly similar in transformed plasma cell (PC) clones from MGUS, SMM, and MM stages. Recent studies show that effectors of the innate and adaptive immune response show marked dysfunction and skewing towards a tolerant environment that favors disease progression. The MM myeloid compartment is characterized by myeloid-derived suppressor cells (MDSCs), dendritic cells as well as M2-like phenotype macrophages that promote immune evasion. Major deregulations are found in the lymphoid compartment as well, with skewing towards immune tolerant Th17 and Treg and inhibition of CD8+ cytotoxic and CD4+ activated effector T cells. In summary, this review will provide an overview of the complex cross-talk between MM plasma cells and immune cells in the microenvironment and the molecular mechanisms promoting progression from precursor states to full-blown myeloma.

Ex vivo drug response heterogeneity reveals personalized therapeutic strategies for patients with multiple myeloma

Multiple myeloma (MM) is a plasma cell malignancy defined by complex genetics and extensive patient heterogeneity. Despite a growing arsenal of approved therapies, MM remains incurable and in need of guidelines to identify effective personalized treatments. Here, we survey the ex vivo drug and immunotherapy sensitivities across 101 bone marrow samples from 70 patients with MM using multiplexed immunofluorescence, automated microscopy and deep-learning-based single-cell phenotyping. Combined with sample-matched genetics, proteotyping and cytokine profiling, we map the molecular regulatory network of drug sensitivity, implicating the DNA repair pathway and EYA3 expression in proteasome inhibitor sensitivity and major histocompatibility complex class II expression in the response to elotuzumab. Globally, ex vivo drug sensitivity associated with bone marrow microenvironmental signatures reflecting treatment stage, clonality and inflammation. Furthermore, ex vivo drug sensitivity significantly stratified clinical treatment responses, including to immunotherapy. Taken together, our study provides molecular and actionable insights into diverse treatment strategies for patients with MM.