Single-cell profiling of tumour evolution in multiple myeloma - opportunities for precision medicine

Exploring cellular diversity in lung adenocarcinoma epithelium: Advancing prognostic methods and immunotherapeutic strategies

Immunotherapy has brought significant advancements in the treatment of lung adenocarcinoma (LUAD), but identifying suitable candidates remains challenging. In this study, we investigated tumour cell heterogeneity using extensive single-cell data and explored the impact of different tumour cell cluster abundances on immunotherapy in the POPLAR and OAK immunotherapy cohorts. Notably, we found a significant correlation between CKS1B+ tumour cell abundance and treatment response, as well as stemness potential. Leveraging marker genes from the CKS1B+ tumour cell cluster, we employed machine learning algorithms to establish a prognostic and immunotherapeutic signature (PIS) for LUAD. In multiple cohorts, PIS outperformed 144 previously published signatures in predicting LUAD prognosis. Importantly, PIS reliably predicted genomic alterations, chemotherapy sensitivity and immunotherapy responses. Immunohistochemistry validated lower expression of immune markers in the low-PIS group, while in vitro experiments underscored the role of the key gene PSMB7 in LUAD progression. In conclusion, PIS represents a novel biomarker facilitating the selection of suitable LUAD patients for immunotherapy, ultimately improving prognosis and guiding clinical decisions.

Peripheral immune profiling of soft tissue sarcoma: perspectives for disease monitoring

Studying the tumor microenvironment and surrounding lymph nodes is the main focus of current immunological research on soft tissue sarcomas (STS). However, due to the restricted opportunity to examine tumor samples, alternative approaches are required to evaluate immune responses in non-surgical patients. Therefore, the purpose of this study was to evaluate the peripheral immune profile of STS patients, characterize patients accordingly and explore the impact of peripheral immunotypes on patient survival. Blood samples were collected from 55 STS patients and age-matched healthy donors (HD) controls. Deep immunophenotyping and gene expression analysis of whole blood was analyzed using multiparametric flow cytometry and real-time RT-qPCR, respectively. Using xMAP technology, proteomic analysis was also carried out on plasma samples. Unsupervised clustering analysis was used to classify patients based on their immune profiles to further analyze the impact of peripheral immunotypes on patient survival. Significant differences were found between STS patients and HD controls. It was found a contraction of B cells and CD4 T cells compartment, along with decreased expression levels of ICOSLG and CD40LG; a major contribution of suppressor factors, as increased frequency of M-MDSC and memory Tregs, increased expression levels of ARG1, and increased plasma levels of IL-10, soluble VISTA and soluble TIMD-4; and a compromised cytotoxic potential associated with NK and CD8 T cells, namely decreased frequency of CD56dim NK cells, and decreased levels of PRF1, GZMB, and KLRK1. In addition, the patients were classified into three peripheral immunotype groups: "immune-high," "immune-intermediate," and "immune-low." Furthermore, it was found a correlation between these immunotypes and patient survival. Patients classified as "immune-high" exhibited higher levels of immune-related factors linked to cytotoxic/effector activity and longer survival times, whereas patients classified as "immune-low" displayed higher levels of immune factors associated with immunosuppression and shorter survival times. In conclusion, it can be suggested that STS patients have a compromised systemic immunity, and the correlation between immunotypes and survival emphasizes the importance of studying peripheral blood samples in STS. Assessing the peripheral immune response holds promise as a useful method for monitoring and forecasting outcomes in STS.

Increased PVR Expression on Bone Marrow Macrophages May Promote Resistance to TIGIT Blockade in Multiple Myeloma

PURPOSE

TIGIT blockade in our ex vivo model of bone marrow (BM) reduced the number of malignant plasma cells (PC) in only half of patients with multiple myeloma. Here, we wanted to investigate whether increased expression of TIGIT ligands may inhibit T-cell immune response promoting resistance to TIGIT blockade.

EXPERIMENTAL DESIGN

We first characterized the number and phenotype of BM macrophages in different stages of the disease by multiparameter flow cytometry. We assessed the effect of TIGIT ligands on PC survival by performing experiments in the ex vivo BM model and analyzed changes in gene expression by using NanoString technology and real-time PCR.

RESULTS

The frequency of BM macrophages was significantly decreased in multiple myeloma, which was accompanied by changes in their immunophenotype. Moreover, we found a higher number of malignant PC in ex vivo BM cells cultured onto the poliovirus receptor (PVR) and nectin-2 compared with control, suggesting that both ligands may support PC survival. In addition, the presence of PVR, but not nectin-2, overcame the therapeutic effect of TIGIT blockade or exogenous IL2. Furthermore, exogenous IL2 increased TIGIT expression on both CD4+ and CD8+ T cells and, indirectly, PVR on BM macrophages. Consistently, PVR reduced the number of cytotoxic T cells and promoted a gene signature with reduced effector molecules.

CONCLUSIONS

IL2 induced TIGIT on T cells in the BM, in which increased PVR expression resulted in cytotoxic T-cell inhibition, promoting PC survival and resistance to TIGIT blockade.

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

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

Gene mutations in newly diagnosed multiple myeloma patients detected by next-generation sequencing technology

Background

Multiple myeloma (MM) is a heterogeneous plasma-derived hematopoietic malignancy with complex genetic mutation contributing to the pathogenesis. Though gene sequencing has been applied in MM, genetic features from Chinese MM patients are reported less. We investigated the genetic mutation of newly diagnosed multiple myeloma (NDMM) patients and explore its correlation with cytogenetic abnormalities detected by fluorescence in situ hybridization (FISH).

Methods

A total of 206 patients with NDMM were enrolled. After enriching plasma cells with CD138 magnetic beads, 92 MM-related target gene mutations were detected by the Illumina sequencing platform, and six common genetic abnormalities were detected by FISH.

Results

162 cases (78.6%) had at least one gene mutation detected by NDMM. The top 5 mutated genes were KRAS, NRAS, TRAF3, BRAF, and TP53. Cytogenetic abnormalities detected by FISH have a certain correlation with gene mutations, t(11;14) translocations are often accompanied by CCND1 and TP53 mutations, KLHL6 in t(4;14), SP140, CDKN1B and PRKD2 in t(14;16) and t(14;20) translocations. The mutation ratio was higher for EGR1, while lower of CCND1 in patients with gain 1q21. The TP53 mutation was more likely in patients with 17p deletion. The gene mutation affects the pathway of the RNA process is more frequently occurring in males and age less than 70 years patients. The International Staging System (ISS) Stage III correlated with gene mutations in the NK-κB pathway while Revised ISS (R-ISS) Stage III correlated with the DNA damage repair pathway.

Conclusions

There are various gene mutations in NDMM patients, mainly RAS/MAPK and NF-κB pathway gene pathways.

Integrating machine learning and single-cell analysis to uncover lung adenocarcinoma progression and prognostic biomarkers

The progression of lung adenocarcinoma (LUAD) from atypical adenomatous hyperplasia (AAH) to invasive adenocarcinoma (IAC) involves a complex evolution of tumour cell clusters, the mechanisms of which remain largely unknown. By integrating single-cell datasets and using inferCNV, we identified and analysed tumour cell clusters to explore their heterogeneity and changes in abundance throughout LUAD progression. We applied gene set variation analysis (GSVA), pseudotime analysis, scMetabolism, and Cytotrace scores to study biological functions, metabolic profiles and stemness traits. A predictive model for prognosis, based on key cluster marker genes, was developed using CoxBoost and plsRcox (CPM), and validated across multiple cohorts for its prognostic prediction capabilities, tumour microenvironment characterization, mutation landscape and immunotherapy response. We identified nine distinct tumour cell clusters, with Cluster 6 indicating an early developmental stage, high stemness and proliferative potential. The abundance of Clusters 0 and 6 increased from AAH to IAC, correlating with prognosis. The CPM model effectively distinguished prognosis in immunotherapy cohorts and predicted genomic alterations, chemotherapy drug sensitivity, and immunotherapy responsiveness. Key gene S100A16 in the CPM model was validated as an oncogene, enhancing LUAD cell proliferation, invasion and migration. The CPM model emerges as a novel biomarker for predicting prognosis and immunotherapy response in LUAD patients, with S100A16 identified as a potential therapeutic target.

Clonal competition assays identify fitness signatures in cancer progression and resistance in multiple myeloma

Multiple myeloma (MM) is a genetically heterogeneous disease and the management of relapses is one of the biggest clinical challenges. TP53 alterations are established high-risk markers and are included in the current disease staging criteria. KRAS is the most frequently mutated gene affecting around 20% of MM patients. Applying Clonal Competition Assays (CCA) by co-culturing color-labeled genetically modified cell models, we recently showed that mono- and biallelic alterations in TP53 transmit a fitness advantage to the cells. Here, we report a similar dynamic for two mutations in KRAS (G12A and A146T), providing a biological rationale for the high frequency of KRAS and TP53 alterations at MM relapse. Resistance mutations, on the other hand, did not endow MM cells with a general fitness advantage but rather presented a disadvantage compared to the wild-type. CUL4B KO and IKZF1 A152T transmit resistance against immunomodulatory agents, PSMB5 A20T to proteasome inhibition. However, MM cells harboring such lesions only outcompete the culture in the presence of the respective drug. To better prevent the selection of clones with the potential of inducing relapse, these results argue in favor of treatment-free breaks or a switch of the drug class given as maintenance therapy. In summary, the fitness benefit of TP53 and KRAS mutations was not treatment-related, unlike patient-derived drug resistance alterations that may only induce an advantage under treatment. CCAs are suitable models for the study of clonal evolution and competitive (dis)advantages conveyed by a specific genetic lesion of interest, and their dependence on external factors such as the treatment.

Deciphering lung adenocarcinoma prognosis and immunotherapy response through an AI-driven stemness-related gene signature

Lung adenocarcinoma (LUAD) is a leading cause of cancer-related deaths, and improving prognostic accuracy is vital for personalised treatment approaches, especially in the context of immunotherapy. In this study, we constructed an artificial intelligence (AI)-driven stemness-related gene signature (SRS) that deciphered LUAD prognosis and immunotherapy response. CytoTRACE analysis of single-cell RNA sequencing data identified genes associated with stemness in LUAD epithelial cells. An AI network integrating traditional regression, machine learning, and deep learning algorithms constructed the SRS based on genes associated with stemness. Subsequently, we conducted a comprehensive exploration of the connection between SRS and both intrinsic and extrinsic immune environments using multi-omics data. Experimental validation through siRNA knockdown in LUAD cell lines, followed by assessments of proliferation, migration, and invasion, confirmed the functional role of CKS1B, a top SRS gene. The SRS demonstrated high precision in predicting LUAD prognosis and likelihood of benefiting from immunotherapy. High-risk groups classified by the SRS exhibited decreased immunogenicity and reduced immune cell infiltration, indicating challenges for immunotherapy. Conversely, in vitro experiments revealed CKS1B knockdown significantly impaired aggressive cancer phenotypes like proliferation, migration, and invasion of LUAD cells, highlighting its pivotal role. These results underscore a close association between stemness and tumour immunity, offering predictive insights into the immune landscape and immunotherapy responses in LUAD. The newly established SRS holds promise as a valuable tool for selecting LUAD populations likely to benefit from future clinical stratification efforts.

Toll-like receptor signaling in multiple myeloma cells promotes the expression of pro-survival genes B-cell lymphoma 2 and MYC and modulates the expression of B-cell maturation antigen

Infections are common in plasma cell cancer multiple myeloma (MM) due to disease-related immune deficiencies and cancer treatment. Myeloma cells express Toll-like receptors (TLRs), and TLR activation has been shown to induce proliferative and pro-survival signals in cancer cells. MM is a complex and heterogeneous disease, and expression levels of TLRs as well as downstream signaling components are likely to differ between patients. Here, we show that in a large cohort of patients, TLR1, TLR4, TLR6, TLR9, and TLR10 are the most highly expressed in primary CD138+ cells. Using an MM cell line expressing TLR4 and TLR9 as a model, we demonstrate that TLR4 and TLR9 activation promoted the expression of well-established pro-survival and oncogenes in MM such as MYC, IRF4, NFKB, and BCL2. TLR4 and TLR9 activation inhibited the efficacy of proteasome inhibitors bortezomib and carfilzomib, drugs used in the treatment of MM. Inhibiting the autophagosome-lysosome protein degradation pathway by hydroxychloroquine (HCQ) diminished the protective effect of TLR activation on proteasome inhibitor-induced cytotoxicity. We also found that TLR signaling downregulated the expression of TNFRSF17, the gene encoding for B-cell maturation antigen (BCMA). MYC, BCL2, and BCL2L1 were upregulated in approximately 50% of primary cells, while the response to TLR signaling in terms of TNFRSF17 expression was dichotomous, as an equal fraction of patients showed upregulation and downregulation of the gene. While proteasome inhibitors are part of first-line MM treatment, several of the new anti-MM immune therapeutic drugs target BCMA. Thus, TLR activation may render MM cells less responsive to commonly used anti-myeloma drugs.

The numerous facets of 1q21+ in multiple myeloma: Pathogenesis, clinicopathological features, prognosis and clinical progress (Review)

Multiple myeloma (MM) is a malignant neoplasm characterized by the clonal proliferation of abnormal plasma cells (PCs) in the bone marrow and recurrent cytogenetic abnormalities. The incidence of MM worldwide is on the rise. 1q21+ has been found in ~30-40% of newly diagnosed MM (NDMM) patients.1q21+ is associated with the pathophysiological mechanisms of disease progression and drug resistance in MM. In the present review, the pathogenesis and clinicopathological features of MM patients with 1q21+ were studied, the key data of 1q21+ on the prognosis of MM patients were summarized, and the clinical treatment significance of MM patients with 1q21+ was clarified, in order to provide reference for clinicians to develop treatment strategies targeting 1q21+.

From spear to trident: Upgrading arsenal of CAR-T cells in the treatment of multiple myeloma

Multiple myeloma (MM), marked by abnormal proliferation of plasma cells and production of monoclonal immunoglobulin heavy or light chains in the majority of patients, has traditionally been associated with poor survival, despite improvements achieved in median survival in all age groups since the introduction of novel agents. Survival has significantly improved with the development of new drugs and new treatment options, such as chimeric antigen receptor T-cell therapy (CAR-T), which have shown promise and given new hope in MM therapy. CARs are now classified as first-, second-, and third-generation CARs based on the number of monovalent to trivalent co-stimulatory molecules incorporated into their design. The scope of this review was relatively narrow because it was mainly about a comparison of the literature on the clinical application of CAR-T therapy in MM. Thus, our goal is to provide an overview of the new advances of CAR-T cells in the cure of MM, so in this review we looked at the progress of the clinical use of CAR-T cells in MM to try to provide a reference for their clinical use when managing MM.

Immunophenotypic profile defines cytogenetic stability and unveils distinct prognoses in patients with newly-diagnosed multiple myeloma (NDMM)

Prognostic significance of multiple immune antigens in multiple myeloma has been well established. However, a level of uncertainty remains regarding the intrinsic relationship between immunophenotypes and cytogenetic stability and precise risk stratification. To address these unresolved issues, we conducted a study involving 1389 patients enrolled in the National Longitudinal Cohort of Hematological Diseases in China (NCT04645199). Our results revealed that the correlation between antigen expression and cytogenetics is more prominent than cytopenia or organ dysfunction. Most immune antigens, apart from CD38, CD138, and CD81, exhibit significant associations with the incidence of at least one cytogenetic abnormality. In turn, we identified CD138-low/CD27-neg as specific adverse immunophenotypic profile, which remaining independent impact on progression-free survival (HR, 1.49; P = 0.007) and overall survival (HR, 1.77; P < 0.001) even in the context of cytogenetics. Importantly, CD138-low/CD27-neg profile was also associated with inferior survival after first relapse (P < 0.001). Moreover, the antigen expression profiles were not strictly similar when comparing diagnosis and relapse; in particular, the CD138-low/CD27-neg pattern was notably increased after disease progression (19.1 to 29.1%; P = 0.005). Overall, our study demonstrates that diverse immune profiles are strongly associated with cytogenetic stability, and a specific immunophenotype (CD138-low/CD27-neg) could effectively predict prognoses across different disease stages.

Microfluidic platform for omics analysis on single cells with diverse morphology and size: A review

BACKGROUND

Microfluidic techniques have emerged as powerful tools in single-cell research, facilitating the exploration of omics information from individual cells. Cell morphology is crucial for gene expression and physiological processes. However, there is currently a lack of integrated analysis of morphology and single-cell omics information. A critical challenge remains: what platform technologies are the best option to decode omics data of cells that are complex in morphology and size?

RESULTS

This review highlights achievements in microfluidic-based single-cell omics and isolation of cells based on morphology, along with other cell sorting methods based on physical characteristics. Various microfluidic platforms for single-cell isolation are systematically presented, showcasing their diversity and adaptability. The discussion focuses on microfluidic devices tailored to the distinct single-cell isolation requirements in plants and animals, emphasizing the significance of considering cell morphology and cell size in optimizing single-cell omics strategies. Simultaneously, it explores the application of microfluidic single-cell sorting technologies to single-cell sequencing, aiming to effectively integrate information about cell shape and size.

SIGNIFICANCE AND NOVELTY

The novelty lies in presenting a comprehensive overview of recent accomplishments in microfluidic-based single-cell omics, emphasizing the integration of different microfluidic platforms and their implications for cell morphology-based isolation. By underscoring the pivotal role of the specialized morphology of different cells in single-cell research, this review provides robust support for delving deeper into the exploration of single-cell omics data.

A tower of babel of acronyms? The shadowlands of MGUS/MBL/CHIP/TCUS

With the advent of outperforming and massive laboratory tools, such as multiparameter flow cytometry and next-generation sequencing, hematopoietic cell clones with putative abnormalities for a variety of blood malignancies have been appreciated in otherwise healthy individuals. These conditions do not fulfill the criteria of their presumed cancer counterparts, and thus have been recognized as their precursor states. This is the case of monoclonal gammopathy of unknown significance (MGUS), the first blood premalignancy state described, preceding multiple myeloma (MM) or Waldenström macroglobulinemia (WM). However, in the last 2 decades, an increasing list of clonopathies has been recognized, including monoclonal B cell lymphocytosis (MBL), which antecedes chronic lymphocytic leukemia (CLL), clonal hematopoiesis of indeterminate potential (CHIP) for myeloid neoplasms (MN), and T-cell clones of uncertain significance (TCUS) for T-cell large chronic lymphocytic leukemia (LGLL). While for some of these entities diagnostic boundaries are precisely set, for others these are yet to be fully defined. Moreover, despite mostly considered of "uncertain significance," they have not only appeared to predispose to malignancy, but also to be capable of provoking set of immunological and cardiovascular complications that may require specialized management. The clinical implications of the aberrant clones, together with the extensive knowledge generated on the pathogenetic events driving their evolution, raises the question whether earlier interventions may alter the natural history of the disease. Herein, we review this Tower of Babel of acronyms pinpointing diagnostic definitions, differential diagnosis, and the role of genomic profiling of these precursor states, as well as potential interventional strategies.

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).

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.

A digital twin model for evidence-based clinical decision support in multiple myeloma treatment

The treatment landscape for multiple myeloma (MM) has experienced substantial progress over the last decade. Despite the efficacy of new substances, patient responses tend to still be highly unpredictable. With increasing cognitive burden that is introduced through a complex and evolving treatment landscape, data-driven assistance tools are becoming more and more popular. Model-based approaches, such as digital twins (DT), enable simulation of probable responses to a set of input parameters based on retrospective observations. In the context of treatment decision-support, those mechanisms serve the goal to predict therapeutic outcomes to distinguish a favorable option from a potential failure. In the present work, we propose a similarity-based multiple myeloma digital twin (MMDT) that emphasizes explainability and interpretability in treatment outcome evaluation. We've conducted a requirement specification process using scientific literature from the medical and methodological domains to derive an architectural blueprint for the design and implementation of the MMDT. In a subsequent stage, we've implemented a four-layer concept where for each layer, we describe the utilized implementation procedure and interfaces to the surrounding DT environment. We further specify our solutions regarding the adoption of multi-line treatment strategies, the integration of external evidence and knowledge, as well as mechanisms to enable transparency in the data processing logic. Furthermore, we define an initial evaluation scenario in the context of patient characterization and treatment outcome simulation as an exemplary use case for our MMDT. Our derived MMDT instance is defined by 475 unique entities connected through 438 edges to form a MM knowledge graph. Using the MMRF CoMMpass real-world evidence database and a sample MM case, we processed a complete outcome assessment. The output shows a valid selection of potential treatment strategies for the integrated medical case and highlights the potential of the MMDT to be used for such applications. DT models face significant challenges in development, including availability of clinical data to algorithmically derive clinical decision support, as well as trustworthiness of the evaluated treatment options. We propose a collaborative approach that mitigates the regulatory and ethical concerns that are broadly discussed when automated decision-making tools are to be included into clinical routine.

The prognostic utility of dynamic risk stratification at disease progression in patients with multiple myeloma

OBJECTIVES

There may be a shift in risk stratification at progression compared to that at diagnosis in patients with multiple myeloma (MM). We aimed to evaluate whether re-staging and stage migration is of prognostic impact.

METHODS

Real-world data from the National Longitudinal Cohort of Hematologic Diseases-multiple myeloma were collected; 263 consecutive patients demonstrating disease progression were finally included. Staging at diagnosis and re-staging at progression were performed using the International Staging System (ISS) and Revised International Staging System (RISS).

RESULTS

Based on ISS re-staging, the median post-progression survival (mPPS) of patients with stage I, II, and III was 44.2, 21.7, and 11.6 months, respectively (P < 0.0001). Based on RISS re-staging, the mPPS of patients with stage I, II, and III was 50.3, 22.2, and 11.4 months, respectively (P < 0.0001). The mPPS in patients with improved, maintained, and deteriorated ISS stage migration from diagnosis was 33.6, 20.9, and 16 months, respectively (P = 0.0051) and that with improved, maintained, and deteriorated RISS stage migration was 48.4, 23.1, and 13.9 months, respectively (P < 0.001). Compared to patients with maintained or improved disease stage, those with deteriorated ISS/RISS migration showed significantly higher incidence of Del(17P) at progression and worse PPS. Multivariate analyses indicated both re-staging and stage migration by ISS/RISS at progression were independent predictors for PPS.

CONCLUSIONS

We demonstrated that ISS/RISS re-staging showed superior prognostic utility over ISS/RISS staging in predicting PPS. Patients with deteriorated stage migration or maintained advanced stage at progression may need more individualized treatment.

Revolutionizing cancer immunotherapy in solid tumor: CAR engineering and single-cell sequencing insights

The global increase in cancer incidence presents significant economic and societal challenges. While chimeric antigen receptor-modified T cell (CAR-T) therapy has demonstrated remarkable success in hematologic malignancies and has earned FDA approval, its translation to solid tumors encounters faces significant obstacles, primarily centered around identifying reliable tumor-associated antigens and navigating the complexities of the tumor microenvironment. Recent developments in single-cell RNA sequencing (scRNA-seq) have greatly enhanced our understanding of tumors by offering high-resolution, unbiased analysis of cellular heterogeneity and molecular patterns. These technologies have revolutionized our comprehension of tumor immunology and have led to notable progress in cancer immunotherapy. This mini-review explores the progress of chimeric antigen receptor (CAR) cell therapy in solid tumor treatment and the application of scRNA-seq at various stages following the administration of CAR cell products into the body. The advantages of scRNA-seq are poised to further advance the investigation of the biological characteristics of CAR cells in vivo, tumor immune evasion, the impact of different cellular components on clinical efficacy, the development of clinically relevant biomarkers, and the creation of new targeted drugs and combination therapy approaches. The integration of scRNA-seq with CAR therapy represents a promising avenue for future innovations in cancer immunotherapy. This synergy holds the potential to enhance the precision and efficacy of CAR cell therapies while expanding their applications to a broader range of malignancies.

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.

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

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

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.

Lysin (K)-specific demethylase 1 inhibition enhances proteasome inhibitor response and overcomes drug resistance in multiple myeloma

BACKGROUND

Multiple myeloma (MM) is an incurable plasma cell malignancy, accounting for approximately 1% of all cancers. Despite recent advances in the treatment of MM, due to the introduction of proteasome inhibitors (PIs) such as bortezomib (BTZ) and carfilzomib (CFZ), relapses and disease progression remain common. Therefore, a major challenge is the development of novel therapeutic approaches to overcome drug resistance, improve patient outcomes, and broaden PIs applicability to other pathologies.

METHODS

We performed genetic and drug screens to identify new synthetic lethal partners to PIs, and validated candidates in PI-sensitive and -resistant MM cells. We also tested best synthetic lethal interactions in other B-cell malignancies, such as mantle cell, Burkitt's and diffuse large B-cell lymphomas. We evaluated the toxicity of combination treatments in normal peripheral blood mononuclear cells (PBMCs) and bone marrow stromal cells (BMSCs). We confirmed the combo treatment' synergistic effects ex vivo in primary CD138+ cells from MM patients, and in different MM xenograft models. We exploited RNA-sequencing and Reverse-Phase Protein Arrays (RPPA) to investigate the molecular mechanisms of the synergy.

RESULTS

We identified lysine (K)-specific demethylase 1 (LSD1) as a top candidate whose inhibition can synergize with CFZ treatment. LSD1 silencing enhanced CFZ sensitivity in both PI-resistant and -sensitive MM cells, resulting in increased tumor cell death. Several LSD1 inhibitors (SP2509, SP2577, and CC-90011) triggered synergistic cytotoxicity in combination with different PIs in MM and other B-cell neoplasms. CFZ/SP2509 treatment exhibited a favorable cytotoxicity profile toward PBMCs and BMSCs. We confirmed the clinical potential of LSD1-proteasome inhibition in primary CD138+ cells of MM patients, and in MM xenograft models, leading to the inhibition of tumor progression. DNA damage response (DDR) and proliferation machinery were the most affected pathways by CFZ/SP2509 combo treatment, responsible for the anti-tumoral effects.

CONCLUSIONS

The present study preclinically demonstrated that LSD1 inhibition could provide a valuable strategy to enhance PI sensitivity and overcome drug resistance in MM patients and that this combination might be exploited for the treatment of other B-cell malignancies, thus extending the therapeutic impact of the project.

Monoclonal B-cell lymphocytosis, monoclonal gammopathy of undetermined significance, and T-cell clones of uncertain significance: are these premalignant conditions sharing a common identity?

Monoclonal B-cell lymphocytosis, monoclonal gammopathy of undetermined significance, and T-cell clones of uncertain significance are three premalignant conditions characterised by the presence of small clonal cell expansions in individuals without symptoms or signs that distinguish the related overt malignancies (chronic lymphocytic leukaemia, multiple myeloma, and T-cell large granular lymphocytic leukaemia). As most individuals with these precursor states never progress to malignancies, considerable interest has arisen in comprehending the steps involved in the progression to malignancy, providing more accurate models to investigate potential mechanisms of early blood cancer identification, prevention, and, possibly, intervention. Single-cell technologies and recent progress in high-throughput sequencing and multiomics approaches have contributed to a better definition of the pathophysiological mechanisms of these premalignant conditions, moving our knowledge in the field forward. In this Viewpoint, we analyse the seemingly shared biological trajectories in these precursor haematological malignancies in search of common pathogenetic events. In particular, we address the issue of interactions between expanding clones and their immune ecosystem, offering new clues that might prompt innovative ideas and inspire further investigations to understand the cellular and molecular dynamics entailing progression into overt malignant disease. The relationships between the non-leukaemic microenvironmental cells and the leukaemic counterpart, and the primary drivers of their initial clonal expansion, represent shared biologies that suggest a common identity among the premalignant conditions considered in this Viewpoint.

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.

Rapid, High-Throughput Single-Cell Multiplex In Situ Tagging (MIST) Analysis of Immunological Disease with Machine Learning

The cascade of immune responses involves activation of diverse immune cells and release of a large amount of cytokines, which leads to either normal, balanced inflammation or hyperinflammatory responses and even organ damage by sepsis. Conventional diagnosis of immunological disorders based on multiple cytokines in the blood serum has varied accuracy, and it is difficult to distinguish normal inflammation from sepsis. Herein, we present an approach to detect immunological disorders through rapid, ultrahigh-multiplex analysis of T cells using single-cell multiplex in situ tagging (scMIST) technology. scMIST permits simultaneous detection of 46 markers and cytokines from single cells without the assistance of special instruments. A cecal ligation and puncture sepsis model was built to supply T cells from two groups of mice that survived the surgery or died after 1 day. The scMIST assays have captured the T cell features and the dynamics over the course of recovery. Compared with cytokines in the peripheral blood, T cell markers show different dynamics and cytokine levels. We have applied a random forest machine learning model to single T cells from two groups of mice. Through training, the model has been able to predict the group of mice through T cell classification and majority rule with 94% accuracy. Our approach pioneers the direction of single-cell omics and could be widely applicable to human diseases.

Noncoding RNAs in the crosstalk between multiple myeloma cells and bone marrow microenvironment

Multiple myeloma (MM) is the second most common hematological malignancy; however, it remains incurable, and the underlying pathogenesis and mechanisms of drug resistance remain unclear. It is widely recognized that the bone marrow microenvironment plays a crucial role in regulating the immune response, inducing drug resistance, and promoting tumor proliferation and invasion in MM, and thus serves as a potential therapeutic target. Among the various signaling loops between myeloma cells and components of the microenvironment, noncoding RNAs are emerging as crucial regulators of intercellular communication within the microenvironment. Noncoding RNAs, such as microRNAs, long noncoding RNAs, circular RNAs, and PIWI-interacting RNAs, have been associated with numerous biological processes involved in myeloma cell growth, survival, migration, invasion, and drug resistance. This review summarizes recent advances in the regulatory mechanisms of noncoding RNAs involved in the interaction between the MM bone marrow microenvironment and discusses the therapeutic potential of noncoding RNAs in MM.

Amp(1q) and tetraploidy are commonly acquired chromosomal abnormalities in relapsed multiple myeloma

Long-term disease control in multiple myeloma (MM) is typically an unmet medical need, and most patients experience multiple relapses. Fluorescence in situ hybridization (FISH) is the standard technique to detect chromosomal abnormalities (CAs), which are important to estimate the prognosis of MM and the allocation of risk adapted therapies. In advanced stages, the importance of CAs needs further investigation. From 148 MM patients, two or more paired samples, at least one of which was collected at relapse, were analyzed by FISH. Using targeted next-generation sequencing, we molecularly investigated samples harboring relapse-associated CAs. Sixty-one percent of the patients showed a change in the cytogenetic profile during the disease course, including 10% who acquired high-risk cytogenetics. Amp(1q) (≥4 copies of 1q21), driven by an additional increase in copy number in patients who already had 3 copies of 1q21, was the most common acquired CA with 16% affected patients. Tetraploidy, found in 10% of the samples collected at the last time-point, was unstable over the course of the disease and was associated with TP53 lesions. Our results indicate that cytogenetic progression is common in relapsed patients. The relatively high frequency of amp(1q) suggests an active role for this CA in disease progression.

Periplocin Overcomes Bortezomib Resistance by Suppressing the Growth and Down-Regulation of Cell Adhesion Molecules in Multiple Myeloma

Multiple myeloma (MM) is an incurable hematological malignant disorder of bone marrow. Patients with MM receive multiple lines of chemotherapeutic treatments which often develop bortezomib (BTZ) resistance and relapse. Therefore, it is crucial to identify an anti-MM agent to overcome the BTZ resistance of MM. In this study, we screened a library of 2370 compounds against MM wild-type (ARP1) and BTZ-resistant type (ARP1-BR) cell lines and found that periplocin (PP) was the most significant anti-MM natural compound. We further investigated the anti-MM effect of PP by using annexin V assay, clonogenic assays, aldefluor assay, and transwell assay. Furthermore, RNA sequencing (RNA-seq) was performed to predict the molecular effects of PP in MM followed by verification through qRT-PCR and Western blot analysis. Moreover, ARP1 and ARP1-BR xenograft mice models of MM were established to confirm the anti-MM effects of PP invivo. The results showed that PP significantly induced apoptosis, inhibited proliferation, suppressed stemness, and reduced the cell migration of MM. The expression of cell adhesion molecules (CAMs) was suppressed upon PP treatment in vitro and in vivo. Overall, our data recommend PP as an anti-MM natural compound with the potential to overcome BTZ resistance and downregulate CAMs in MM.

Prognostic Relevance of Multi-Antigenic Myeloma-Specific T-Cell Assay in Patients with Monoclonal Gammopathies

Multiple Myeloma (MM) typically originates from underlying precursor conditions, known as Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering Multiple Myeloma (SMM). Validated risk factors, related to the main features of the clonal plasma cells, are employed in the current prognostic models to assess long-term probabilities of progression to MM. In addition, new prognostic immunologic parameters, measuring protective MM-specific T-cell responses, could help to identify patients with shorter time-to-progression. In this report, we described a novel Multi-antigenic Myeloma-specific (MaMs) T-cell assay, based on ELISpot technology, providing simultaneous evaluation of T-cell responses towards ten different MM-associated antigens. When performed during long-term follow-up (mean 28 months) of 33 patients with either MGUS or SMM, such deca-antigenic myeloma-specific immunoassay allowed to significantly distinguish between stable vs. progressive disease (p < 0.001), independently from the Mayo Clinic risk category. Here, we report the first clinical experience showing that a wide (multi-antigen), standardized (irrespective to patients' HLA), MM-specific T-cell assay may routinely be applied, as a promising prognostic tool, during the follow-up of MGUS/SMM patients. Larger studies are needed to improve the antigenic panel and further explore the prognostic value of MaMs test in the risk assessment of patients with monoclonal gammopathies.

In Situ Polymerization of Aniline Derivative in Vivo for NIR-II Phototheranostics of Tumor

Natural biopolymers can be controllably in situ synthesized in organisms and play important roles in biological activities. Inspired by this, the manipulation of in situ biosynthesis of functional polymers in vivo will be an important way to obtain materials for meeting biological requirements. Herein, in situ biosynthesis of functional conjugated polymer at the tumor site was achieved via the utilization of specific tumor microenvironment (TME) characteristics for the first time. Specially, a water-soluble aniline dimer derivative (N-(3-sulfopropyl) p-aminodiphenylamine, SPA) was artfully in situ polymerized into polySPA (PSPA) nanoparticles at the tumor site, which was activated via the catalysis of hydrogen peroxide (H₂O₂) overexpressed in TME to produce hydroxyl radical (•OH) by coinjected horseradish peroxidase (HRP). Benefiting from outstanding near-infrared (NIR)-II absorption of PSPA, the in situ polymerization process can be validly monitored by photoacoustic (PA) signal at the NIR-II region. Meanwhile, in situ polymerization would induce the size of polymeric materials from small to large, improving the distribution and retention of PSPA at the tumor site. On the combination of NIR-II absorption of PSPA and the size variation induced by polymerization, such polymerization can be applied for tumor-specific NIR-II light mediated PA image and photothermal inhibition of tumors, enhancing the precision and efficacy of tumor phototheranostics. Therefore, the present work opens the way to manipulate TME-activated in situ biosynthesis of functional conjugated polymer at the tumor site for overcoming formidable challenges in tumor theranostics.

The cellular biology of plasma cells: Unmet challenges and opportunities

Plasma cells and the antibodies they secrete are paramount for protection against infection but can also be implicated in diseases including autoantibody-mediated disease and multiple myeloma. Plasma cell terminal differentiation relies on a transcriptional switch and on important morphological changes. The cellular and molecular mechanisms underlying these processes are partly understood and how plasma cells manage to survive for long periods of time while secreting large quantities of antibodies remains unclear. In this review we aim to put in perspective what is known about plasma cell cellular biology to highlight the challenges faced by this field of research but also to illustrate how new opportunities may arise from the study of the fundamental mechanisms sustaining plasma cell survival and function.

Dynamic single-cell RNA-seq analysis reveals distinct tumor program associated with microenvironmental remodeling and drug sensitivity in multiple myeloma

BACKGROUND

Multiple myeloma (MM) is a hematological malignancy characterized by clonal proliferation of malignant plasma cells. Despite extensive research, molecular mechanisms in MM that drive drug sensitivity and clinic outcome remain elusive.

RESULTS

Single-cell RNA sequencing was applied to study tumor heterogeneity and molecular dynamics in 10 MM individuals before and after 2 cycles of bortezomib-cyclophosphamide-dexamethasone (VCD) treatment, with 3 healthy volunteers as controls. We identified that unfolded protein response and metabolic-related program were decreased, whereas stress-associated and immune reactive programs were increased after 2 cycles of VCD treatment. Interestingly, low expression of the immune reactive program by tumor cells was associated with unfavorable drug response and poor survival in MM, which probably due to downregulation of MHC class I mediated antigen presentation and immune surveillance, and upregulation of markers related to immune escape. Furthermore, combined with immune cells profiling, we uncovered a link between tumor intrinsic immune reactive program and immunosuppressive phenotype in microenvironment, evidenced by exhausted states and expression of checkpoint molecules and suppressive genes in T cells, NK cells and monocytes. Notably, expression of YBX1 was associated with downregulation of immune activation signaling in myeloma and reduced immune cells infiltration, thereby contributed to poor prognosis.

CONCLUSIONS

We dissected the tumor and immune reprogramming in MM during targeted therapy at the single-cell resolution, and identified a tumor program that integrated tumoral signaling and changes in immune microenvironment, which provided insights into understanding drug sensitivity in MM.

A narrative review for platelets and their RNAs in cancers: New concepts and clinical perspectives

Recent years have witnessed a growing body of evidence suggesting that platelets are involved in several stages of the metastatic process via direct or indirect interactions with cancer cells, contributing to the progression of neoplastic malignancies. Cancer cells can dynamically exchange components with platelets in and out of blood vessels, and directly phagocytose platelets to hijack their proteome, transcriptome, and secretome, or be remotely regulated by metabolites or microparticles released by platelets, resulting in phenotypic, genetic, and functional modifications. Moreover, platelet interactions with stromal and immune cells in the tumor microenvironment lead to alterations in their components, including the ribonucleic acid (RNA) profile, and complicate the impact of platelets on cancers. A deeper understanding of the roles of platelets and their RNAs in cancer will contribute to the development of anticancer strategies and the optimization of clinical management. Encouragingly, advances in high-throughput sequencing, bioinformatics data analysis, and machine learning have allowed scientists to explore the potential of platelet RNAs for cancer diagnosis, prognosis, and guiding treatment. However, the clinical application of this technique remains controversial and requires larger, multicenter studies with standardized protocols. Here, we integrate the latest evidence to provide a broader insight into the role of platelets in cancer progression and management, and propose standardized recommendations for the clinical utility of platelet RNAs to facilitate translation and benefit patients.

Deep transfer learning enables lesion tracing of circulating tumor cells

Liquid biopsy offers great promise for noninvasive cancer diagnostics, while the lack of adequate target characterization and analysis hinders its wide application. Single-cell RNA sequencing (scRNA-seq) is a powerful technology for cell characterization. Integrating scRNA-seq into a CTC-focused liquid biopsy study can perhaps classify CTCs by their original lesions. However, the lack of CTC scRNA-seq data accumulation and prior knowledge hinders further development. Therefore, we design CTC-Tracer, a transfer learning-based algorithm, to correct the distributional shift between primary cancer cells and CTCs to transfer lesion labels from the primary cancer cell atlas to CTCs. The robustness and accuracy of CTC-Tracer are validated by 8 individual standard datasets. We apply CTC-Tracer on a complex dataset consisting of RNA-seq profiles of single CTCs, CTC clusters from a BRCA patient, and two xenografts, and demonstrate that CTC-Tracer has potential in knowledge transfer between different types of RNA-seq data of lesions and CTCs.

High precision, high throughput generation of droplets containing single cells

The Poisson limit is a major problem for the isolation of single cells in different single-cell technologies and applications. In droplet-based single-cell assays, a scheme that is increasingly popular, the intrinsic randomness during single-cell encapsulation in droplets requires most of the created droplets to be empty, which has a profound impact on the efficiency and throughput of such techniques, and on the predictability of the combinatory droplet assays. Here we present a simple passive microfluidic system overcoming this limitation with unprecedented efficacy, allowing the generation of single-cell droplets for a wide range of operating conditions, with extremely high throughput (more than 22 000 single-cell loaded droplets per minute) and with an extremely low fault ratio (doublets or empty droplets), applicable to any cells and deformable particles. This versatile technique will shift the paradigm of single-cell encapsulation and will impact single-cell sequencing, rare cell isolation, multicellular/bead studies in immunology or cancer biology, etc.

MSC Senescence-Related Genes Are Associated with Myeloma Prognosis and Lipid Metabolism-Mediated Resistance to Proteasome Inhibitors

BACKGROUND

Complex carcinogenic mechanisms and the existence of tumour heterogeneity in multiple myeloma (MM) prevent the most commonly used staging system from effectively interpreting the prognosis of patients. Since the microenvironment plays an important role in driving tumour development and MM occurs most often in middle-aged and elderly patients, we hypothesize that ageing of bone marrow mesenchymal stem cells (BM-MSCs) may be associated with the progression of MM.

METHODS

In this study, we collected the transcriptome data on MM from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Differentially expressed genes in both senescent MSCs and MM tumour cells were considered relevant damaged genes. GO and KEGG analyses were applied for functional evaluation. A PPI network was constructed to identify hub genes. Subsequently, we studied the damaged genes that affected the prognosis of MM. Least absolute shrinkage and selection operator (lasso) regression was used to identify the most important features, and a risk model was created. The reliability of the risk model was evaluated with the other 3 GEO validation cohorts. In addition, ROC analysis was used to evaluate the novel risk model. An analysis of immune checkpoint-related genes, tumour immune dysfunction and exclusion (TIDE), and immunophenotypic scoring (IPS) were performed to assess the immune status of risk groups. pRRophetic was utilized to predict the sensitivity to administration of chemotherapeutic agents.

RESULTS

We identified that MAPK, PI3K, and p53 signalling pathways were activated in both senescent MSCs and tumour cells, and we also located hub genes. In addition, we constructed a 14-gene prognostic risk model, which was analysed with the ROC and validated in different datasets. Further analysis revealed significant differences in predicted risk values across the International Staging System (ISS) stage, sex, and 1q21 copy number. A high-risk group with higher immunogenicity was predicted to have low proteasome inhibitor sensitivity and respond poorly to immunotherapy. Lipid metabolism pathways were found to be significantly different between high-risk and low-risk groups. A nomogram was created by combining clinical data, and the optimization model was further improved. Finally, real-time qPCR was used to validate two bortezomib-resistant myeloma cell lines, and the test confirmed that 10 genes were detected to be expressed in resistant cell lines with the same trend as in the high-risk cohort compared to nonresistant cells.

CONCLUSION

Fourteen genes related to ageing in BM-MSCs were associated with the prognosis of MM, and by combining this genotypic information with clinical factors, a promising clinical prognostic model was established.

Single cell characterization of myeloma and its precursor conditions reveals transcriptional signatures of early tumorigenesis

Multiple myeloma is a plasma cell malignancy almost always preceded by precursor conditions, but low tumor burden of these early stages has hindered the study of their molecular programs through bulk sequencing technologies. Here, we generate and analyze single cell RNA-sequencing of plasma cells from 26 patients at varying disease stages and 9 healthy donors. In silico dissection and comparison of normal and transformed plasma cells from the same bone marrow biopsy enables discovery of patient-specific transcriptional changes. Using Non-Negative Matrix Factorization, we discover 15 gene expression signatures which represent transcriptional modules relevant to myeloma biology, and identify a signature that is uniformly lost in abnormal cells across disease stages. Finally, we demonstrate that tumors contain heterogeneous subpopulations expressing distinct transcriptional patterns. Our findings characterize transcriptomic alterations present at the earliest stages of myeloma, providing insight into the molecular underpinnings of disease initiation.

Current perspectives on interethnic variability in multiple myeloma: Single cell technology, population pharmacogenetics and molecular signal transduction

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This review discusses the emerging single cell technologies and applications in Multiple myeloma (MM), population pharmacogenetics of MM, resistance to chemotherapy, genetic determinants of drug-induced toxicity, molecular signal transduction.

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The role(s) of epigenetics and noncoding RNAs including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) that influence the risk and severity of MM are also discussed.

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It is understood that ethnic component acts as a driver of variable response to chemotherapy in different sub-populations globally.

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This review augments our understanding of genetic variability in ‘myelomagenesis’ and drug-induced toxicity, myeloma microenvironment at the molecular and cellular level, and developing precision medicine strategies to combat this malignancy.

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The emerging single cell technologies hold great promise for enhancing our understanding of MM tumor heterogeneity and clonal diversity.

Multiple myeloma (MM) is an aggressive cancer characterised by malignancy of the plasma cells and a rising global incidence. The gold standard for optimum response is aggressive chemotherapy followed by autologous stem cell transplantation (ASCT). However, majority of the patients are above 60 years and this presents the clinician with complications such as ineligibility for ASCT, frailty, drug-induced toxicity and differential/partial response to treatment. The latter is partly driven by heterogenous genotypes of the disease in different subpopulations. In this review, we discuss emerging single cell technologies and applications in MM, population pharmacogenetics of MM, resistance to chemotherapy, genetic determinants of drug-induced toxicity, molecular signal transduction, as well as the role(s) played by epigenetics and noncoding RNAs including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) that influence the risk and severity of the disease. Taken together, our discussions further our understanding of genetic variability in ‘myelomagenesis’ and drug-induced toxicity, augment our understanding of the myeloma microenvironment at the molecular and cellular level and provide a basis for developing precision medicine strategies to combat this malignancy.

Hotspots and trends in multiple myeloma bone diseases: A bibliometric visualization analysis

Objective: This study aims to explore the research hotspots and trends of multiple myeloma bone disease in the past 20 years by bibliometric visualization analysis.

Methods: With the Web of Science Core Collection database as the data source, the relevant publications of multiple myeloma bone disease from 2002 to 2021 are retrieved. These data are analyzed using software CiteSpace 5.8.R3 and Scimago Graphica 1.0.24, together with the Online Analysis Platform of Literature Metrology.

Results: A total of 6,168 published research papers, including 4668 articles and 1500 review papers, are included in this study. Generally speaking, annual publications and citations are on the rise, especially in recent 2 years. The majority of these papers are published in the United States, with Mayo Clinic being the greatest contributor. The most productive journal and author are Blood and Terpos E, respectively, while the most frequently co-cited reference, author and journal are Rajkumar et al., 2014, Lancet Oncol, Kyle RA and Blood, respectively. The major research subject categories are oncology and hematology. The “disease diagnosis”, “prognosis evaluation”, “pathogenesis”, “imaging technology” and “targeted therapy” are recent research frontiers. The burst keywords “transplantation”, “progression”, “activation”, “lenalidomide”, “flow cytometry”, “drug resistance”, “management” and “mesenchymal stem cell” reflect the latest research hotspots.

Conclusion: This study reveals the research hotspots and trends of multiple myeloma bone disease through bibliometric visualization analysis, and provides a valuable reference for further research.

A novel medication decision gene signature predicts response to individualized therapy and prognosis outcomes in hepatocellular carcinoma patients

Molecular targeted therapy has shown potential in hepatocellular carcinoma (HCC) patients, and immunotherapy applications are developing rapidly. However, clinical guidance for making individualized therapy decisions for HCC patients remains lacking. MDH (Medication Decision in HCC) gene signatures comprising 70 genes were screened using transcriptomic data from multikinase inhibitor (TKI)-resistant HCC cells and HCC patient-derived xenograft model (PDX) models. Four MDH subtypes with distinct biological and clinical characteristics were defined by unsupervised cluster analysis of HCC data from The Cancer Genome Atlas (TCGA) database. To facilitate individualized and reasonable clinical guidance for each HCC patient, we constructed the MDH score. Comprehensive analysis suggested high MDH scores were associated with TKI resistance, a high proportion of stromal cell infiltration and poor survival outcomes. We recommend concomitant stromal activity intervention and immunotherapy for this type of HCC. Moreover, low MDH scores indicate TKI sensitivity, and a combination of targeted and immunotherapy is recommended. The nomogram constructed by iteration least absolute shrinkage and selection operator (LASSO) Cox regression analysis successfully predicted 3- or 5-year survival outcomes and mortality risks of HCC patients. In conclusion, TKI resistance model-based MDH gene signatures provide novel insight into potential mechanisms of drug resistance and heterogeneity in HCC. Integrative analysis plus a simplified decision model may aid personalized treatment and prognostic assessment among HCC patients.

The Urgent Need for Precision Medicine in Cancer and Its Microenvironment: The Paradigmatic Case of Multiple Myeloma

Precision medicine is particularly relevant for cancer and microenvironment deconvolution for therapeutic purposes in hematological and non-hematological malignancies [...].

Single-cell transcriptome sequencing reveals potential novel combination of biomarkers for antibody-based cancer therapeutics in hepatocellular carcinoma

Background: Antibody-based cancer therapeutics is developing rapidly in recent years for its advantages in precisely targeting the tumor cells. However, tumor-specific cell surface antigens are still lacking, and the heterogeneity of tumor mass greatly impeded the development of effective drugs.

Methods: In the present study, single-cell RNA sequencing was used to dissect tumor heterogeneity in human hepatocellular carcinoma (HCC). Tissues from different spatial regions including the tumor, para-tumor, and distant normal liver tissues were dissociated into single cells, and the gene expressions were compared in a different subpopulation of cells from these regions and validated in independent cohorts.

Results: A total of 28 cell clusters with different distribution patterns and gene expression profiles were identified within a heterogenous tumor and its paired liver tissues. Differentially expressed genes encoding the plasma membrane in cells with hepatic lineage were further extracted from single-cell transcriptome sequencing and validated in TCGA database. A 3-gene signature was identified to be significantly upregulated in dominant HCC tumor cell subpopulations with prognostic significance and validated in multiple independent patient cohorts.

Conclusion: The composition of the three plasma membrane proteins on the surface of HCC tumor cells within a heterogenous tumor might indicate poor prognostic tumor subpopulations during cancer evolution and potential therapeutic targets.

The Role of Clonal Evolution on Progression, Blood Parameters, and Response to Therapy in Multiple Myeloma

Introduction

A variety of biomarkers are considered for diagnosis (e.g., β2-microgobulin, albumin, or LDH) and prognosis [e.g., cytogenetic aberrations detected by fluorescence in situ hybridization (FISH)] of multiple myeloma (MM). More recently, clonal evolution has been established as key. Little is known on the clinical implications of clonal evolution.

Methods

We performed in-depth analyses of 25 patients with newly diagnosed MM with respect to detailed clinical information analyzing blood samples collected at several time points during follow-up (median follow-up: 3.26 years since first diagnosis). We split our cohort into two subgroups: with and without new FISH clones developing in the course of disease.

Results

Each subgroup showed a characteristic chromosomal profile. Forty-three percent of patients had evidence of appearing new clones. The patients with new clones showed an increased number of translocations affecting chromosomes 14 (78% vs. 33%; p = 0.0805) and 11, and alterations in chromosome 4 (amplifications and translocations). New clones, on the contrary, were characterized by alterations affecting chromosome 17. Subsequent to the development of the new clone, 6 out of 9 patients experienced disease progression compared to 3 out of 12 for patients without new clones. Duration of the therapy applied for the longest time was significantly shorter within the group of patients developing new clones (median: 273 vs. 406.5 days; p = 0.0465).

Discussion

We demonstrated that the development of new clones, carrying large-scale alterations, was associated with inferior disease course and shorter response to therapy, possibly affecting progression-free survival and overall survival as well. Further studies evaluating larger cohorts are necessary for the validation of our results.

Clonal evolution after treatment pressure in multiple myeloma: heterogenous genomic aberrations and transcriptomic convergence

We investigated genomic and transcriptomic changes in paired tumor samples of 29 in-house multiple myeloma (MM) patients and 28 patients from the MMRF CoMMpass study before and after treatment. A change in clonal composition was found in 46/57 (82%) of patients, and single-nucleotide variants (SNVs) increased from median 67 to 86. The highest increase in prevalence of genetic aberrations was found in RAS genes (60% to 72%), amp1q21 (18% to 35%), and TP53 (9% to 18%). The SBS-MM1 mutation signature was detected both in patients receiving high and low dose melphalan. A total of 2589 genes were differentially expressed between early and late samples (FDR < 0.05). Gene set enrichment analysis (GSEA) showed increased expression of E2F, MYC, and glycolysis pathways and a decreased expression in TNF-NFkB and TGFbeta pathways in late compared to early stage. Single sample GSEA (ssGSEA) scores of differentially expressed pathways revealed that these changes were most evident in end-stage disease. Increased expression of several potentially targetable genes was found at late disease stages, including cancer-testis antigens, XPO1 and ABC transporters. Our study demonstrates a transcriptomic convergence of pathways supporting increased proliferation and metabolism during disease progression in MM.

Multiple myeloma with high-risk cytogenetics and its treatment approach

Despite substantial advances in anti-myeloma treatments, early recurrence and death remain an issue in certain subpopulations. Cytogenetic abnormalities (CAs) are the most widely accepted predictors for poor prognosis in multiple myeloma (MM), such as t(4;14), t(14;16), t(14;20), gain/amp(1q21), del(1p), and del(17p). Co-existing high-risk CAs (HRCAs) tend to be associated with an even worse prognosis. Achievement of sustained minimal residual disease (MRD)-negativity has recently emerged as a surrogate for longer survival, regardless of cytogenetic risk. Information from newer clinical trials suggests that extended intensified treatment can help achieve MRD-negativity in patients with HRCAs, which may lead to improved outcomes. Therapy should be considered to include a 3- or 4-drug induction regimen (PI/IMiD/Dex or PI/IMiD/Dex/anti-CD38 antibody), auto-transplantation, and consolidation/maintenance with lenalidomide ± a PI. Results from ongoing clinical trials for enriched high-risk populations will reveal the precise efficacy of the investigated regimens. Genetic abnormalities of MM cells are intrinsic critical factors determining tumor characteristics, which reflect the natural course and drug sensitivity of the disease. This paper reviews the clinicopathological features of genomic abnormalities related to adverse prognosis, focusing on HRCAs that are the most relevant in clinical practice, and outline current optimal therapeutic approaches for newly diagnosed MM with HRCAs.

The Dynamics of Nucleotide Variants in the Progression from Low-Intermediate Myeloma Precursor Conditions to Multiple Myeloma: Studying Serial Samples with a Targeted Sequencing Approach

Simple Summary

Multiple myeloma (MM), characterized by the expansion of plasma cells in the bone marrow, is the second most common hematological malignancy. This incurable cancer is consistently preceded by non-malignant asymptomatic precursor conditions known as monoclonal gammopathy of undetermined significance (MGUS) and/or smoldering multiple myeloma (SMM). These pre-stages are relatively frequent, but only a select percentage of them will progress to MM. However, it is still not possible to individually predict when and which patients will develop MM. Therefore, this study aimed to investigate the mutational profile in the progression in serial bone marrow samples with a custom targeted sequencing panel, designed to detect variants in myeloma-related genes. Remarkably, almost all variants identified in the MM samples were also already present in the pre-stages, sometimes even many years before the progression. These results provide new important insights into the molecular mechanisms of the precursor conditions and progression to MM.

Abstract

Multiple myeloma (MM), or Kahler’s disease, is an incurable plasma cell (PC) cancer in the bone marrow (BM). This malignancy is preceded by one or more asymptomatic precursor conditions, monoclonal gammopathy of undetermined significance (MGUS) and/or smoldering multiple myeloma (SMM). The molecular mechanisms and exact cause of this progression are still not completely understood. In this study, the mutational profile underlying the progression from low–intermediate risk myeloma precursor conditions to MM was studied in serial BM smears. A custom capture-based sequencing platform was developed, including 81 myeloma-related genes. The clonal evolution of single nucleotide variants and short insertions and deletions was studied in serial BM smears from 21 progressed precursor patients with a median time of progression of six years. From the 21 patients, four patients had no variation in one of the 81 studied genes. Interestingly, in 16 of the 17 other patients, at least one variant present in MM was also detected in its precursor BM, even years before progression. Here, the variants were present in the pre-stage at a median of 62 months before progression to MM. Studying these paired BM samples contributes to the knowledge of the evolutionary genetic landscape and provides additional insight into the mutational behavior of mutant clones over time throughout progression.