Single-cell genetic analysis reveals the composition of initiating clones and phylogenetic patterns of branching and parallel evolution in myeloma

The genomic profiling of high-risk smoldering myeloma patients treated with an intensive strategy unveils potential markers of resistance and progression

Smoldering multiple myeloma (SMM) precedes multiple myeloma (MM). The risk of progression of SMM patients is not uniform, thus different progression-risk models have been developed, although they are mainly based on clinical parameters. Recently, genomic predictors of progression have been defined for untreated SMM. However, the usefulness of such markers in the context of clinical trials evaluating upfront treatment in high-risk SMM (HR SMM) has not been explored yet, precluding the identification of baseline genomic alterations leading to drug resistance. For this reason, we carried out next-generation sequencing and fluorescent in-situ hybridization studies on 57 HR and ultra-high risk (UHR) SMM patients treated in the phase II GEM-CESAR clinical trial (NCT02415413). DIS3, FAM46C, and FGFR3 mutations, as well as t(4;14) and 1q alterations, were enriched in HR SMM. TRAF3 mutations were specifically associated with UHR SMM but identified cases with improved outcomes. Importantly, novel potential predictors of treatment resistance were identified: NRAS mutations and the co-occurrence of t(4;14) plus FGFR3 mutations were associated with an increased risk of biological progression. In conclusion, we have carried out for the first time a molecular characterization of HR SMM patients treated with an intensive regimen, identifying genomic predictors of poor outcomes in this setting.

Approach to High-Risk Multiple Myeloma

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

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.

Phenotype-structured model of intra-clonal heterogeneity and drug resistance in multiple myeloma

Multiple myeloma (MM) is a genetically complex hematological cancer characterized by the abnormal proliferation of malignant plasma cells in the bone marrow. This disease progresses from a premalignant condition known as monoclonal gammopathy of unknown significance (MGUS) through sequential genetic alterations involving various genes. These genetic changes contribute to the uncontrolled growth of multiple clones of plasma cells. In this study, we present a phenotype-structured model that captures the intra-clonal heterogeneity and drug resistance in multiple myeloma (MM). The model accurately reproduces the branching evolutionary pattern observed in MM progression, aligning with a previously developed multiscale model. Numerical simulations reveal that higher mutation rates enhance tumor phenotype diversity, while access to growth factors accelerates tumor evolution and increases its final size. Interestingly, the model suggests that further increasing growth factor access primarily amplifies tumor size rather than altering clonal dynamics. Additionally, the model emphasizes that higher mutation frequencies and growth factor availability elevate the chances of drug resistance and relapse. It indicates that the timing of the treatment could trajectory of tumor evolution and clonal emergence in the case of branching evolutionary pattern. Given its low computational cost, our model is well-suited for quantitative studies on MM clonal heterogeneity and its interaction with chemotherapeutic treatments.

Cell competition and cancer from Drosophila to mammals

Throughout an individual's life, somatic cells acquire cancer-associated mutations. A fraction of these mutations trigger tumour formation, a phenomenon partly driven by the interplay of mutant and wild-type cell clones competing for dominance; conversely, other mutations function against tumour initiation. This mechanism of 'cell competition', can shift clone dynamics by evaluating the relative status of clonal populations, promoting 'winners' and eliminating 'losers'. This review examines the role of cell competition in the context of tumorigenesis, tumour progression and therapeutic intervention.

Bispecific CS1-BCMA CAR-T cells are clinically active in relapsed or refractory multiple myeloma

Multiple myeloma (MM) bears heterogeneous cells that poses a challenge for single-target immunotherapies. Here we constructed bispecific CS1-BCMA CAR-T cells aiming to augment BCMA targeting with CS1. Sixteen patients with relapsed or refractory (RR) MM received CS1-BCMA CAR-T infusion. Six patients (38%) had cytokine release syndrome, which was of grade 1-2 in 31%. No neurological toxicities were observed. The most common severe adverse events were hematological, including leukopenia (100%), neutropenia (94%), lymphopenia (100%) and thrombocytopenia (31%). Three patients with solitary extramedullary disease (sEMD) did not respond. At a median follow-up of 246 days, 13 patients (81%) had an overall response and attained minimal residual disease-negativity, and six (38%) reached a stringent complete response (sCR). Among the 13 responders, 1-year overall survival and progression-free survival were 72.73% and 56.26%, respectively. Four patients maintained sCR with a median duration of 17 months. Four patients experienced BCMA+ and CS1+ relapse or progression. One patient responded after anti-BCMA CAR-T treatment failure. Lenalidomide maintenance after CAR-T infusion and the resistance mechanism of sEMD were preliminarily explored in three patients. CAR-T cells persisted at a median of 406 days. Soluble BCMA could serve as an ideal biomarker for efficacy monitoring. CS1-BCMA CAR-T cells were clinically active with good safety profiles in patients with RRMM. Clinical trial registration: This study was registered on ClinicalTrials.gov, number NCT04662099.

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.

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.

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.

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.

Antibody-Drug Conjugates for Multiple Myeloma: Just the Beginning, or the Beginning of the End?

Multiple myeloma is a malignancy of immunoglobulin-secreting plasma cells that is now often treated in the newly diagnosed and relapsed and/or refractory settings with monoclonal antibodies targeting lineage-specific markers used either alone or in rationally designed combination regimens. Among these are the anti-CD38 antibodies daratumumab and isatuximab, and the anti-Signaling lymphocytic activation molecule family member 7 antibody elotuzumab, all of which are used in their unconjugated formats. Single-chain variable fragments from antibodies also form a key element of the chimeric antigen receptors (CARs) in the B-cell maturation antigen (BCMA)-targeted CAR T-cell products idecabtagene vicleucel and ciltacabtagene autoleucel, which are approved in the advanced setting. Most recently, the bispecific anti-BCMA and T-cell-engaging antibody teclistamab has become available, again for patients with relapsed/refractory disease. Another format into which antibodies can be converted to exert anti-tumor efficacy is as antibody-drug conjugates (ADCs), and belantamab mafodotin, which also targets BCMA, represented the first such agent that gained a foothold in myeloma. Negative results from a recent Phase III study have prompted the initiation of a process for withdrawal of its marketing authorization. However, belantamab remains a drug with some promise, and many other ADCs targeting either BCMA or other plasma cell surface markers are in development and showing potential. This contribution will provide an overview of some of the current data supporting the possibility that ADCs will remain a part of our chemotherapeutic armamentarium against myeloma moving forward, and also highlight areas for future development.

Clinical characteristics and prognostic significance of immunoglobulin isotype switch in patients with multiple myeloma

Immunoglobulin (Ig) isotype switching in multiple myeloma (MM) is a rare form of clonal evolution. The aim of this study was to investigate the clinical features and prognostic significance of Ig isotype switching by observing Ig transformation in patients with relapse. A retrospective analysis was performed on 506 patients with newly diagnosed MM who were treated at our hospital from February 2005 to February 2020. The patients who experienced relapse were divided into the following four groups according to Ig phenotype: original paraprotein, complete isotype switching, light chain escape (LCE),and non-secretory clinical relapse. For comparative purposes with the original paraprotein group, the last three groups were pooled as the transformation group. Among the 506 included patients, 376 (74.3%) relapsed. Among them, 13/376 (3.5%) patients exhibited Ig isotype switching, including 3 with complete isotype switching, 3 with LCE, and 7 with non-secretory clinical relapse. Eleven remained sensitive to therapy, exhibiting at least a partial response. Seven patients survived for at least 20 months after relapse. The median overall survival time of the LCE, clinical relapse, and complete isotype switching groups were 6, 20, and 76 months, respectively, after recurrence. The clinical manifestations and Ig phenotypes of MM recurrence were different from those at the initial diagnosis in the 13 patients exhibiting Ig isotype switching. These differences vividly conveyed the heterogeneity of the clonal populations and provides direct clinical evidence for MM clonal evolution.

Immune Checkpoint Inhibitor Related Rheumatological Complications: Cooperation between Rheumatologists and Oncologists

In cancer, immune checkpoint inhibitors (ICIs) improve patient survival but may lead to severe immune-related adverse events (irAEs). Rheumatic irAEs are a distinct entity that are much more common in a real-life than in clinical trial reports due to their unspecific symptoms and them being a rare cause of hospitalization. This review focuses on an interdisciplinary approach to the management of rheumatic irAEs, including cooperation between oncologists, rheumatologists, and immunologists. We discuss the immunological background of rheumatic irAEs, as well as their unique clinical characteristics, differentiation from other irAEs, and treatment strategies. Importantly, steroids are not the basis of therapy, and nonsteroidal anti-inflammatory drugs should be administered in the front line with other antirheumatic agents. We also address whether patients with pre-existing rheumatic autoimmune diseases can receive ICIs and how antirheumatic agents can interfere with ICIs. Interestingly, there is a preclinical rationale for combining ICIs with immunosuppressants, particularly tumor necrosis factor α and interleukin 6 inhibitors. Regardless of the data, the mainstay in managing irAEs is interdisciplinary cooperation between oncologists and other medical specialties.

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.

Genetic Alterations in Members of the Proteasome 26S Subunit, AAA-ATPase (PSMC) Gene Family in the Light of Proteasome Inhibitor Resistance in Multiple Myeloma

For the treatment of Multiple Myeloma, proteasome inhibitors are highly efficient and widely used, but resistance is a major obstacle to successful therapy. Several underlying mechanisms have been proposed but were only reported for a minority of resistant patients. The proteasome is a large and complex machinery. Here, we focus on the AAA ATPases of the 19S proteasome regulator (PSMC1-6) and their implication in PI resistance. As an example of cancer evolution and the acquisition of resistance, we conducted an in-depth analysis of an index patient by applying FISH, WES, and immunoglobulin-rearrangement sequencing in serial samples, starting from MGUS to newly diagnosed Multiple Myeloma to a PI-resistant relapse. The WES analysis uncovered an acquired PSMC2 Y429S mutation at the relapse after intensive bortezomib-containing therapy, which was functionally confirmed to mediate PI resistance. A meta-analysis comprising 1499 newly diagnosed and 447 progressed patients revealed a total of 36 SNVs over all six PSMC genes that were structurally accumulated in regulatory sites for activity such as the ADP/ATP binding pocket. Other alterations impact the interaction between different PSMC subunits or the intrinsic conformation of an individual subunit, consequently affecting the folding and function of the complex. Interestingly, several mutations were clustered in the central channel of the ATPase ring, where the unfolded substrates enter the 20S core. Our results indicate that PSMC SNVs play a role in PI resistance in MM.

Immunogenic cell death triggered by impaired deubiquitination in multiple myeloma relies on dysregulated type I interferon signaling

Introduction

Proteasome inhibition is first line therapy in multiple myeloma (MM). The immunological potential of cell death triggered by defects of the ubiquitin-proteasome system (UPS) and subsequent perturbations of protein homeostasis is, however, less well defined.

Methods

In this paper, we applied the protein homeostasis disruptors bortezomib (BTZ), ONX0914, RA190 and PR619 to various MM cell lines and primary patient samples to investigate their ability to induce immunogenic cell death (ICD).

Results

Our data show that while BTZ treatment triggers sterile type I interferon (IFN) responses, exposure of the cells to ONX0914 or RA190 was mostly immunologically silent. Interestingly, inhibition of protein de-ubiquitination by PR619 was associated with the acquisition of a strong type I IFN gene signature which relied on key components of the unfolded protein and integrated stress responses including inositol-requiring enzyme 1 (IRE1), protein kinase R (PKR) and general control nonderepressible 2 (GCN2). The immunological relevance of blocking de-ubiquitination in MM was further reflected by the ability of PR619-induced apoptotic cells to facilitate dendritic cell (DC) maturation via type I IFN-dependent mechanisms.

Conclusion

Altogether, our findings identify de-ubiquitination inhibition as a promising strategy for inducing ICD of MM to expand current available treatments.

Integrative Analysis of Bulk RNA-Seq and Single-Cell RNA-Seq Unveils Novel Prognostic Biomarkers in Multiple Myeloma

Molecular heterogeneity has great significance in the disease biology of multiple myeloma (MM). Thus, the analysis combined single-cell RNA-seq (scRNA-seq) and bulk RNA-seq data were performed to investigate the clonal evolution characteristics and to find novel prognostic targets in MM. The scRNA-seq data were analyzed by the Seurat pipeline and Monocle 2 to identify MM cell branches with different differentiation states. Marker genes in each branch were uploaded to the STRING database to construct the Protein-Protein Interaction (PPI) network, followed by the detection of hub genes by Cytoscape software. Using bulk RNA-seq data, Kaplan-Meier (K-M) survival analysis was then carried out to determine prognostic biomarkers in MM. A total of 342 marker genes in two branches with different differentiation states were identified, and the top 20 marker genes with the highest scores in the network calculated by the MCC algorithm were selected as hub genes in MM. Furthermore, K-M survival analysis revealed that higher NDUFB8, COX6C, NDUFA6, USMG5, and COX5B expression correlated closely with a worse prognosis in MM patients. Moreover, ssGSEA and Pearson analyses showed that their expression had a significant negative correlation with the proportion of Tcm (central memory cell) immune cells. Our findings identified NDUFB8, COX6C, NDUFA6, USMG5, and COX5B as novel prognostic biomarkers in MM, and also revealed the significance of genetic heterogeneity during cell differentiation in MM prognosis.

Correlation of plasma cell assessment by phenotypic methods and molecular profiles by NGS in patients with plasma cell dyscrasias

Background

Next-generation sequencing (NGS) detects somatic mutations in a high proportion of plasma cell dyscrasias (PCD), but is currently not integrated into diagnostic routine. We correlated NGS data with degree of bone marrow (BM) involvement by cytomorphology (BMC), histopathology (BMH), and multiparameter flow cytometry (MFC) in 90 PCD patients.

Methods

Of the 90 patients the diagnoses comprised multiple myeloma (n = 77), MGUS (n = 7), AL-amyloidosis (n = 4) or solitary plasmocytoma (n = 2). The NGS panel included eight genes CCND1, DIS3, EGR1, FAM46C (TENT5C), FGFR3, PRDM1, TP53, TRAF3, and seven hotspots in BRAF, IDH1, IDH2, IRF4, KRAS, NRAS.

Results

Mutations were detected in 64/90 (71%) of cases. KRAS (29%), NRAS (16%) and DIS3 (16%) were most frequently mutated. At least one mutation/sample corresponded to a higher degree of BM involvement with a mean of 11% pathologic PC by MFC (range, 0.002–62%), and ~ 50% (3–100%) as defined by both BMC and BMH.

Conclusions

The probability of detecting a mutation by NGS in the BM was highest in samples with > 10% clonal PC by MFC, or > 20% PC by BMC/ BMH. We propose further evaluation of these thresholds as a practical cut-off for processing of samples by NGS at initial PCD diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01346-1.

Multiple Myeloma Therapy: Emerging Trends and Challenges

Multiple myeloma (MM) is a complex hematologic malignancy characterized by the uncontrolled proliferation of clonal plasma cells in the bone marrow that secrete large amounts of immunoglobulins and other non-functional proteins. Despite decades of progress and several landmark therapeutic advancements, MM remains incurable in most cases. Standard of care frontline therapies have limited durable efficacy, with the majority of patients eventually relapsing, either early or later. Induced drug resistance via up-modulations of signaling cascades that circumvent the effect of drugs and the emergence of genetically heterogeneous sub-clones are the major causes of the relapsed-refractory state of MM. Cytopenias from cumulative treatment toxicity and disease refractoriness limit therapeutic options, hence creating an urgent need for innovative approaches effective against highly heterogeneous myeloma cell populations. Here, we present a comprehensive overview of the current and future treatment paradigm of MM, and highlight the gaps in therapeutic translations of recent advances in targeted therapy and immunotherapy. We also discuss the therapeutic potential of emerging preclinical research in multiple myeloma.

The yin–yang effects of immunity: From monoclonal gammopathy of undetermined significance to multiple myeloma

Multiple myeloma (MM) is the third most common malignant neoplasm of the hematological system. It often develops from monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM) precursor states. In this process, the immune microenvironment interacts with the MM cells to exert yin and yang effects, promoting tumor progression on the one hand and inhibiting it on the other. Despite significant therapeutic advances, MM remains incurable, and the main reason for this may be related to the complex and variable immune microenvironment. Therefore, it is crucial to investigate the dynamic relationship between the immune microenvironment and tumors, to elucidate the molecular mechanisms of different factors in the microenvironment, and to develop novel therapeutic agents targeting the immune microenvironment of MM. In this paper, we review the latest research progress and describe the dual influences of the immune microenvironment on the development and progression of MM from the perspective of immune cells and molecules.

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.

Tracking Clonal Evolution of Multiple Myeloma Using Targeted Next-Generation DNA Sequencing

Clonal evolution drives treatment failure in multiple myeloma (MM). Here, we used a custom 372-gene panel to track genetic changes occurring during MM progression at different stages of the disease. A tumor-only targeted next-generation DNA sequencing was performed on 69 samples sequentially collected from 30 MM patients. The MAPK/ERK pathway was mostly affected with KRAS mutated in 47% of patients. Acquisition and loss of mutations were observed in 63% and 37% of patients, respectively. Four different patterns of mutation evolution were found: branching-, mutation acquisition-, mutation loss- and a stable mutational pathway. Better response to anti-myeloma therapy was more frequently observed in patients who followed the mutation loss-compared to the mutation acquisition pathway. More than two-thirds of patients had druggable genes mutated (including cases of heavily pre-treated disease). Only 7% of patients had a stable copy number variants profile. Consequently, a redistribution in stages according to R-ISS between the first and paired samples (R-ISS″) was seen. The higher the R-ISS″, the higher the risk of MM progression and death. We provided new insights into the genetics of MM evolution, especially in heavily pre-treated patients. Additionally, we confirmed that redefining R-ISS at MM relapse is of high clinical value.

The Route of the Malignant Plasma Cell in Its Survival Niche: Exploring “Multiple Myelomas”

Growing evidence points to multiple myeloma (MM) and its stromal microenvironment using several mechanisms to subvert effective immune and anti-tumor responses. Recent advances have uncovered the tumor-stromal cell influence in regulating the immune-microenvironment and have envisioned targeting these suppressive pathways to improve therapeutic outcomes. Nevertheless, some subgroups of patients include those with particularly unfavorable prognoses. Biological stratification can be used to categorize patient-, disease- or therapy-related factors, or alternatively, these biological determinants can be included in a dynamic model that customizes a given treatment to a specific patient. Genetic heterogeneity and current knowledge enforce a systematic and comprehensive bench-to-bedside approach. Given the increasing role of cancer stem cells (CSCs) in better characterizing the pathogenesis of solid and hematological malignancies, disease relapse, and drug resistance, identifying and describing CSCs is of paramount importance in the management of MM. Even though the function of CSCs is well-known in other cancer types, their role in MM remains elusive. With this review, we aim to provide an update on MM homing and resilience in the bone marrow micro milieu. These data are particularly interesting for clinicians facing unmet medical needs while designing novel treatment approaches for MM.

Cancer evolution: special focus on the immune aspect of cancer

Cancer is an evolutionary disease. Intra-tumor heterogeneity (ITH), which describes the diversity within individual tumors, sets the foundation for evolution. The fitness of tumor cells is determined by their microenvironment, which exerts intense selection pressure that generally favors cells with survival and proliferation advantages. It has been revealed that host immunity dramatically influences the evolutionary trajectory of cancer. As technologies advance, a refined map of the immune system's involvement in cancer evolution has gradually come to our knowledge. Here we specifically view cancer through the lens of evolutionary immunological biology. We will cover the neoplastic evolution under immunosurveillance, including how the host immunity shapes the tumor evolutionary trajectory and how progressive tumors modulate the host immunity to survive. A comprehensive understanding of the interplay between cancer evolution and cancer immunity provides clues to combating cancer strategically.

Single-cell RNA-seq reveals clonal diversity and prognostic genes of relapsed multiple myeloma

Background

Multiple myeloma (MM) is a clinically and biologically heterogeneous plasma‐cell malignancy. Despite extensive research, disease heterogeneity and relapse remain a big challenge in MM therapeutics. We tried to dissect this disease and identify novel biomarkers for patient stratification and treatment outcome prediction by applying single‐cell technology.

Methods

We performed single‐cell RNA sequencing (scRNA‐seq) and variable‐diversity‐joining regions‐targeted sequencing (scVDJ‐seq) concurrently on bone marrow samples from a cohort of 18 patients with newly diagnosed MM (NDMM; n = 12) or refractory/relapsed MM (RRMM; n = 6). We analysed the malignant clonotypes using scVDJ‐seq data and conducted data integration and cell‐type annotation through the CCA algorithm based on gene expression profiling. Furthermore, we identified disease status‐specific genes and modules by comparison of NDMM and RRMM datasets and explored the findings in a larger MM cohort from the MMRF CoMMpass study.

Results

We found that all the myeloma cells in either diagnosed or relapsed samples were dominated by a major clone, with a few subclones in several samples (n = 5). Next, we investigated the universal transcriptional features of myeloma cells and identified eight meta‐programs correlated with this disease, especially meta‐programs 1 and 8 (M1 and M8), which were the most significant and related to cell cycle and stress response, respectively. Furthermore, we classified the malignant plasma cells into eight clusters and found that the cell numbers in clusters 2/6/7 were exclusively higher in relapsed samples. Besides, we identified several attractive candidates for biomarkers (e.g. SMAD1 and STMN1) associated with disease progression and relapse in our dataset and related to overall survival in the CoMMpass dataset.

Conclusions

Our data provide insights into the heterogeneity of MM as well as highlight the relevance of intra‐tumour heterogeneity and discover novel biomarkers that might be a potent therapy.

Single-Cell Sequencing Technologies in Precision Oncology

Single-cell sequencing technologies are revolutionizing cancer research and are poised to become the standard for translational cancer studies. Rapidly decreasing costs and increasing throughput and resolution are paving the way for the adoption of single-cell technologies in clinical settings for personalized medicine applications. In this chapter, we review the state of the art of single-cell DNA and RNA sequencing technologies, the computational tools to analyze the data, and their potential application to precision oncology. We also discuss the advantages of single-cell over bulk sequencing for the dissection of intra-tumor heterogeneity and the characterization of subclonal cell populations, the implementation of targeted drug repurposing approaches, and describe advanced methodologies for multi-omics data integration and to assess cell signaling at single-cell resolution.

Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application

Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. Extensive clinical and genomic studies have revealed biomarkers, risk factors, pathways, and targets of AD in the past decade. However, the exact molecular basis of AD development and progression remains elusive. The emerging single-cell sequencing technology can potentially provide cell-level insights into the disease. Here we systematically review the state-of-the-art bioinformatics approaches to analyze single-cell sequencing data and their applications to AD in 14 major directions, including 1) quality control and normalization, 2) dimension reduction and feature extraction, 3) cell clustering analysis, 4) cell type inference and annotation, 5) differential expression, 6) trajectory inference, 7) copy number variation analysis, 8) integration of single-cell multi-omics, 9) epigenomic analysis, 10) gene network inference, 11) prioritization of cell subpopulations, 12) integrative analysis of human and mouse sc-RNA-seq data, 13) spatial transcriptomics, and 14) comparison of single cell AD mouse model studies and single cell human AD studies. We also address challenges in using human postmortem and mouse tissues and outline future developments in single cell sequencing data analysis. Importantly, we have implemented our recommended workflow for each major analytic direction and applied them to a large single nucleus RNA-sequencing (snRNA-seq) dataset in AD. Key analytic results are reported while the scripts and the data are shared with the research community through  GitHub. In summary, this comprehensive review provides insights into various approaches to analyze single cell sequencing data and offers specific guidelines for study design and a variety of analytic directions. The review and the accompanied software tools will serve as a valuable resource for studying cellular and molecular mechanisms of AD, other diseases, or biological systems at the single cell level.

Bringing precision oncology to cellular resolution with single-cell genomics

Single-cell sequencing technologies have undergone rapid development and adoption by the scientific community in the past 5 years, fueling discoveries about the etiology, pathogenesis, and treatment responsiveness of individual tumor cells within cancer ecosystems. Most of the advancements in our understanding of cancer with these new technologies have focused on basic tumor biology. However, the knowledge produced by these and other studies are beginning to provide biomarkers and drug targets for clinically-relevant subpopulations within a tumor, creating opportunities for the development of biologically-informed, clone-specific combination treatment strategies. Here we provide an overview of the development of the field of single-cell cancer sequencing and provide a roadmap for shepherding these technologies from research tools to diagnostic instruments that provide high-resolution, treatment-directing details of tumors to clinical oncologists.

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

Multiple myeloma (MM) is a haematological malignancy of plasma cells characterized by substantial intraclonal genetic heterogeneity. Although therapeutic advances made in the past few years have led to improved outcomes and longer survival, MM remains largely incurable. Over the past decade, genomic analyses of patient samples have demonstrated that MM is not a single disease but rather a spectrum of haematological entities that all share similar clinical symptoms. Moreover, analyses of samples from monoclonal gammopathy of undetermined significance and smouldering MM have also shown the existence of genetic heterogeneity in precursor stages, in some cases remarkably similar to that of MM. This heterogeneity highlights the need for a greater dissection of underlying disease biology, especially the clonal diversity and molecular events underpinning MM at each stage to enable the stratification of individuals with a high risk of progression. Emerging single-cell sequencing technologies present a superlative solution to delineate the complexity of monoclonal gammopathy of undetermined significance, smouldering MM and MM. In this Review, we discuss how genomics has revealed novel insights into clonal evolution patterns of MM and provide examples from single-cell studies that are beginning to unravel the mutational and phenotypic characteristics of individual cells within the bone marrow tumour, immune microenvironment and peripheral blood. We also address future perspectives on clinical application, proposing that multi-omics single-cell profiling can guide early patient diagnosis, risk stratification and treatment strategies.

The Molecular Subtype of Adult Acute Lymphoblastic Leukemia Samples Determines the Engraftment Site and Proliferation Kinetics in Patient-Derived Xenograft Models

In acute lymphoblastic leukemia (ALL), conventional cell lines do not recapitulate the clonal diversity and microenvironment. Orthotopic patient-derived xenograft models (PDX) overcome these limitations and mimic the clinical situation, but molecular stability and engraftment patterns have not yet been thoroughly assessed. We herein describe and characterize the PDX generation in NSG mice. In vivo tumor cell proliferation, engraftment and location were monitored by flow cytometry and bioluminescence imaging. Leukemic cells were retransplanted for up to four passages, and comparative analyses of engraftment pattern, cellular morphology and genomic hotspot mutations were conducted. Ninety-four percent of all samples were successfully engrafted, and the xenograft velocity was dependent on the molecular subtype, outcome of the patient and transplantation passage. While BCR::ABL1 blasts were located in the spleen, KMT2A-positive cases had higher frequencies in the bone marrow. Molecular changes appeared in most model systems, with low allele frequency variants lost during primary engraftment. After the initial xenografting, however, the PDX models demonstrated high molecular stability. This protocol for reliable ALL engraftment demonstrates variability in the location and molecular signatures during serial transplantation. Thorough characterization of experimentally used PDX systems is indispensable for the correct analysis and valid data interpretation of preclinical PDX studies.

Spatial patterns of tumour growth impact clonal diversification in a computational model and the TRACERx Renal study

Genetic intra-tumour heterogeneity fuels clonal evolution, but our understanding of clinically relevant clonal dynamics remain limited. We investigated spatial and temporal features of clonal diversification in clear cell renal cell carcinoma through a combination of modelling and real tumour analysis. We observe that the mode of tumour growth, surface or volume, impacts the extent of subclonal diversification, enabling interpretation of clonal diversity in patient tumours. Specific patterns of proliferation and necrosis explain clonal expansion and emergence of parallel evolution and microdiversity in tumours. In silico time-course studies reveal the appearance of budding structures before detectable subclonal diversification. Intriguingly, we observe radiological evidence of budding structures in early-stage clear cell renal cell carcinoma, indicating that future clonal evolution may be predictable from imaging. Our findings offer a window into the temporal and spatial features of clinically relevant clonal evolution.

Genome Instability in Multiple Myeloma: Facts and Factors

Multiple myeloma (MM) is a malignant neoplasm of terminally differentiated immunoglobulin-producing B lymphocytes called plasma cells. MM is the second most common hematologic malignancy, and it poses a heavy economic and social burden because it remains incurable and confers a profound disability to patients. Despite current progress in MM treatment, the disease invariably recurs, even after the transplantation of autologous hematopoietic stem cells (ASCT). Biological processes leading to a pathological myeloma clone and the mechanisms of further evolution of the disease are far from complete understanding. Genetically, MM is a complex disease that demonstrates a high level of heterogeneity. Myeloma genomes carry numerous genetic changes, including structural genome variations and chromosomal gains and losses, and these changes occur in combinations with point mutations affecting various cellular pathways, including genome maintenance. MM genome instability in its extreme is manifested in mutation kataegis and complex genomic rearrangements: chromothripsis, templated insertions, and chromoplexy. Chemotherapeutic agents used to treat MM add another level of complexity because many of them exacerbate genome instability. Genome abnormalities are driver events and deciphering their mechanisms will help understand the causes of MM and play a pivotal role in developing new therapies.

Plasma cell dependence on histone/protein deacetylase 11 reveals a therapeutic target in multiple myeloma

The clinical utility of histone/protein deacetylase (HDAC) inhibitors in combinatorial regimens with proteasome inhibitors for patients with relapsed and refractory multiple myeloma (MM) is often limited by excessive toxicity due to HDAC inhibitor promiscuity with multiple HDACs. Therefore, more selective inhibition minimizing off-target toxicity may increase the clinical effectiveness of HDAC inhibitors. We demonstrated that plasma cell development and survival are dependent upon HDAC11, suggesting this enzyme is a promising therapeutic target in MM. Mice lacking HDAC11 exhibited markedly decreased plasma cell numbers. Accordingly, in vitro plasma cell differentiation was arrested in B cells lacking functional HDAC11. Mechanistically, we showed that HDAC11 is involved in the deacetylation of IRF4 at lysine¹⁰³. Further, targeting HDAC11 led to IRF4 hyperacetylation, resulting in impaired IRF4 nuclear localization and target promoter binding. Importantly, transient HDAC11 knockdown or treatment with elevenostat, an HDAC11-selective inhibitor, induced cell death in MM cell lines. Elevenostat produced similar anti-MM activity in vivo, improving survival among mice inoculated with 5TGM1 MM cells. Elevenostat demonstrated nanomolar ex vivo activity in 34 MM patient specimens and synergistic activity when combined with bortezomib. Collectively, our data indicated that HDAC11 regulates an essential pathway in plasma cell biology establishing its potential as an emerging theraputic vulnerability in MM.

Longitudinal single-cell analysis of a myeloma mouse model identifies subclonal molecular programs associated with progression

Molecular programs that underlie precursor progression in multiple myeloma are incompletely understood. Here, we report a disease spectrum-spanning, single-cell analysis of the Vκ*MYC myeloma mouse model. Using samples obtained from mice with serologically undetectable disease, we identify malignant cells as early as 30 weeks of age and show that these tumours contain subclonal copy number variations that persist throughout progression. We detect intratumoural heterogeneity driven by transcriptional variability during active disease and show that subclonal expression programs are enriched at different times throughout early disease. We then show how one subclonal program related to GCN2 stress response is progressively activated during progression in myeloma patients. Finally, we use chemical and genetic perturbation of GCN2 in vitro to support this pathway as a therapeutic target in myeloma. These findings therefore present a model of precursor progression in Vκ*MYC mice, nominate an adaptive mechanism important for myeloma survival, and highlight the need for single-cell analyses to understand the biological underpinnings of disease progression.

Clonal phylogeny and evolution of critical cytogenetic aberrations in multiple myeloma at single cell level by QM-FISH

Single-cell analysis is of significant importance in delineate the exact phylogeny of subclonal population and in discovering subtle diversification. So far studies of intratumor heterogeneity and clonal evolution in multiple myeloma (MM) were largely focused at the bulk tumor population level. Here, we performed quantitative multi-gene fluorescence in situ hybridization (QM-FISH) in 129 longitudinal samples of 57 MM patients. All the patients had newly-diagnosed and relapsed paired samples. An expanded cohort of 188 MM patients underwent conventional FISH (cFISH) to validate the cytogenetic evolution in bulk tumor level. 43 of 57 patients (75.4%) harbored three or four cytogenetic clones at diagnosis. We delineated the phylogeny of subclonal tumor population and derived the evolutionary architecture in each patient. Patients with clonal stabilization had a significantly improved OS than those with other evolutionary patterns (median OS, 71.2 vs. 39.7 vs. 35.2 vs. 25.5 months, for stable, differential, branching and linear patterns, respectively, p=0.001). Besides, a high degree of consistency and complementarity across QM-FISH and cFISH was observed in evaluation of cytogenetic evolution pattern in MM. Survival after relapse were greater influenced by the presence of high-risk aberrations at relapse (hazard ratio =2.07) rather than present at diagnosis (hazard ratio=1.55). This study shows that QM-FISH is a valuable tool to elucidate the clonal architecture at single cell level. Clonal evolution pattern is of prognostic significance, highlighting the need for repeated cytogenetic evaluation in relapsed MM.

A bispecific CAR-T cell therapy targeting BCMA and CD38 in relapsed or refractory multiple myeloma

Background

BCMA-specific chimeric antigen receptor-T cells (CAR-Ts) have exhibited remarkable efficacy in refractory or relapsed multiple myeloma (RRMM); however, primary resistance and relapse exist with single-target immunotherapy. Bispecific CARs are proposed to mitigate these limitations.

Methods

We constructed a humanized bispecific BM38 CAR targeting BCMA and CD38 and tested the antimyeloma activity of BM38 CAR-Ts in vitro and in vivo. Twenty-three patients with RRMM received infusions of BM38 CAR-Ts in a phase I trial.

Results

BM38 CAR-Ts showed stronger in vitro cytotoxicity to heterogeneous MM cells than did T cells expressing an individual BCMA or CD38 CAR. BM38 CAR-Ts also exhibited potent antimyeloma activity in xenograft mouse models. In the phase I trial, cytokine release syndrome occurred in 20 patients (87%) and was mostly grade 1–2 (65%). Neurotoxicity was not observed. Hematologic toxicities were common, including neutropenia in 96% of the patients, leukopenia in 87%, anemia in 43% and thrombocytopenia in 61%. At a median follow-up of 9.0 months (range 0.5 to 18.5), 20 patients (87%) attained a clinical response and minimal residual disease-negativity (≤ 10^–4 nucleated cells), with 12 (52%) achieving a stringent complete response. Extramedullary plasmacytoma was eliminated completely in 56% and partially in 33% and of 9 patients. The median progression-free survival was 17.2 months. Two relapsed patients maintained BCMA and CD38 expression on MM cells. Notably, BM38 CAR-Ts cells were detectable in 77.8% of evaluable patients at 9 months and 62.2% at 12 months.

Conclusion

Bispecific BM38 CAR-Ts were feasible, safe and significantly effective in patient with RRMM.

Trial registration: Chictr.org.cn ChiCTR1800018143.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13045-021-01170-7.

Clonal Evolution of Multiple Myeloma-Clinical and Diagnostic Implications

Plasma cell dyscrasias are a heterogeneous group of diseases characterized by the expansion of bone marrow plasma cells. Malignant transformation of plasma cells depends on the continuity of events resulting in a sequence of well-defined disease stages, from monoclonal gammopathy of undetermined significance (MGUS) through smoldering myeloma (SMM) to symptomatic multiple myeloma (MM). Evolution of a pre-malignant cell into a malignant cell, as well as further tumor progression, dissemination, and relapse, require development of multiple driver lesions conferring selective advantage of the dominant clone and allowing subsequent evolution under selective pressure of microenvironment and treatment. This process of natural selection facilitates tumor plasticity leading to the formation of genetically complex and heterogenous tumors that are notoriously difficult to treat. Better understanding of the mechanisms underlying tumor evolution in MM and identification of lesions driving the evolution from the premalignant clone is therefore a key to development of effective treatment and long-term disease control. Here, we review recent advances in clonal evolution patterns and genomic landscape dynamics of MM, focusing on their clinical implications.

The Immunity-malignancy equilibrium in multiple myeloma: lessons from oncogenic events in plasma cells

Multiple myeloma (MM) is a malignancy of plasma cells (PC) that grow within the bone marrow and maintain massive immunoglobulin (Ig) production. Disease evolution is driven by genetic lesions, whose effects on cell biology and fitness underlie addictions and vulnerabilities of myeloma cells. Several genes mutated in myeloma are strictly involved in dictating PC identity and antibody factory function. Here, we evaluate the impact of mutations in IRF4, PRDM1, and XBP1, essential transcription factors driving the B to PC differentiation, on MM cell biology and homeostasis. These factors are highly specialized, with limited overlap in their downstream transcriptional programs. Indeed, IRF4 sustains metabolism, survival, and proliferation, while PRDM1 and XBP1 are mainly responsible for endoplasmic reticulum expansion and sustained Ig secretion. Interestingly, IRF4 undergoes activating mutations and translocations, while PRDM1 and XBP1 are hit by loss-of-function events, raising the hypothesis that containment of the secretory program, but not its complete extinction, may be beneficial to malignant PCs. Finally, recent studies unveiled that also the PRDM1 target, FAM46C/TENT5C, an onco-suppressor uniquely and frequently mutated or deleted in myeloma, is directly and potently involved in orchestrating ER homeostasis and secretory activity. Inactivating mutations found in this gene and its interactors strengthen the notion that reduced secretory capacity confers advantage to myeloma cells. We believe that dissection of the evolutionary pressure on genes driving PC-specific functions in myeloma will disclose the cellular strategies by which myeloma cells maintain an equilibrium between antibody production and survival, thus unveiling novel therapeutic targets.

Integrative analysis of the genomic and transcriptomic landscape of double-refractory multiple myeloma

In multiple myeloma, novel treatments with proteasome inhibitors (PIs) and immunomodulatory agents (IMiDs) have prolonged survival but the disease remains incurable. At relapse, next-generation sequencing has shown occasional mutations of drug targets but has failed to identify unifying features that underlie chemotherapy resistance. We studied 42 patients refractory to both PIs and IMiDs. Whole-exome sequencing was performed in 40 patients, and RNA sequencing (RNA-seq) was performed in 27. We found more mutations than were reported at diagnosis and more subclonal mutations, which implies ongoing evolution of the genome of myeloma cells during treatment. The mutational landscape was different from that described in published studies on samples taken at diagnosis. The TP53 pathway was the most frequently inactivated (in 45% of patients). Conversely, point mutations of genes associated with resistance to IMiDs were rare and were always subclonal. Refractory patients were uniquely characterized by having a mutational signature linked to exposure to alkylating agents, whose role in chemotherapy resistance and disease progression remains to be elucidated. RNA-seq analysis showed that treatment or mutations had no influence on clustering, which was instead influenced by karyotypic events. We describe a cluster with both amp(1q) and del(13) characterized by CCND2 upregulation and also overexpression of MCL1, which represents a novel target for experimental treatments. Overall, high-risk features were found in 65% of patients. However, only amp(1q) predicted survival. Gene mutations of IMiD and PI targets are not a preferred mode of drug resistance in myeloma. Chemotherapy resistance of the bulk tumor population is likely attained through differential, yet converging evolution of subclones that are overall variable from patient to patient and within the same patient.

Chromothripsis as a pathogenic driver of multiple myeloma

Analysis of the genetic basis for multiple myeloma (MM) has informed many of our current concepts of the biology that underlies disease initiation and progression. Studying these events in further detail is predicted to deliver important insights into its pathogenesis, prognosis and treatment. Information from whole genome sequencing of structural variation is revealing the role of these events as drivers of MM. In particular, we discuss how the insights we have gained from studying chromothripsis suggest that it can be used to provide information on disease initiation and that, as a consequence, it can be used for the clinical classification of myeloma precursor diseases allowing for early intervention and prognostic determination. For newly diagnosed MM, the integration of information on the presence of chromothripsis has the potential to significantly enhance current risk prediction strategies and to better characterize patients with high-risk disease biology. In this article we summarize the genetic basis for MM and the role played by chromothripsis as a critical pathogenic factor active at early disease phases.

To portray clonal evolution in blood cancer, count your stem cells

Clonal evolution, the process of expansion and diversification of mutated cells, plays an important role in cancer development, resistance, and relapse. Although clonal evolution is most often conceived of as driven by natural selection, recent studies uncovered that neutral evolution shapes clonal evolution in a significant proportion of solid cancers. In hematological malignancies, the interplay between neutral evolution and natural selection is also disputed. Because natural selection selects cells with a greater fitness, providing a growth advantage to some cells relative to others, the architecture of clonal evolution serves as indirect evidence to distinguish natural selection from neutral evolution and has been associated with different prognoses for the patient. Linear architecture, when the new mutant clone grows within the previous one, is characteristic of hematological malignancies and is typically interpreted as being driven by natural selection. Here, we discuss the role of natural selection and neutral evolution in the production of linear clonal architectures in hematological malignancies. Although it is tempting to attribute linear evolution to natural selection, we argue that a lower number of contributing stem cells accompanied by genetic drift can also result in a linear pattern of evolution, as illustrated by simulations of clonal evolution in hematopoietic stem cells. The number of stem cells contributing to long-term clonal evolution is not known in the pathological context, and we advocate that estimating these numbers in the context of cancer and aging is crucial to parsing out neutral evolution from natural selection, 2 processes that require different therapeutic strategies.

Genetic and Non-Genetic Mechanisms Underlying Cancer Evolution

Simple Summary

Our manuscript summarizes the up-to-date data on the complex and dynamic nature of adaptation mechanisms and evolutionary processes taking place during cancer initiation, development and progression. Although for decades cancer has been viewed as a process governed by genetic mechanisms, it is becoming more and more clear that non-genetic mechanisms may play an equally important role in cancer evolution. In this review, we bring together these fundamental concepts and discuss how those tightly interconnected mechanisms lead to the establishment of highly adaptive quickly evolving cancers. Furthermore, we argue that in depth understanding of cancer progression from the evolutionary perspective may allow the prediction and direction of the evolutionary path of cancer populations towards drug sensitive phenotypes and thus facilitate the development of more effective anti-cancer approaches.

Abstract

Cancer development can be defined as a process of cellular and tissular microevolution ultimately leading to malignancy. Strikingly, though this concept has prevailed in the field for more than a century, the precise mechanisms underlying evolutionary processes occurring within tumours remain largely uncharacterized and rather cryptic. Nevertheless, although our current knowledge is fragmentary, data collected to date suggest that most tumours display features compatible with a diverse array of evolutionary paths, suggesting that most of the existing macro-evolutionary models find their avatar in cancer biology. Herein, we discuss an up-to-date view of the fundamental genetic and non-genetic mechanisms underlying tumour evolution with the aim of concurring into an integrated view of the evolutionary forces at play throughout the emergence and progression of the disease and into the acquisition of resistance to diverse therapeutic paradigms. Our ultimate goal is to delve into the intricacies of genetic and non-genetic networks underlying tumour evolution to build a framework where both core concepts are considered non-negligible and equally fundamental.

Structural determinants of the IRF4/DNA homodimeric complex

Interferon regulatory factor 4 (IRF4) is a key transcription factor (TF) in the regulation of immune cells, including B and T cells. It acts by binding DNA as both a homodimer and, in conjunction with other TFs, as a heterodimer. The choice of homo and heterodimeric/ DNA interactions is a critical aspect in the control of the transcriptional program and cell fate outcome. To characterize the nature of this interaction in the homodimeric complex, we have determined the crystal structure of the IRF4/ISRE homodimeric complex. We show that the complex formation is aided by a substantial DNA deformation with co-operative binding achieved exclusively through protein–DNA contact. This markedly contrasts with the heterodimeric form where DNA bound IRF4 is shown to physically interact with PU.1 TF to engage EICE1. We also show that the hotspot residues (Arg98, Cys99 and Asn102) contact both consensus and non-consensus sequences with the L1 loop exhibiting marked flexibility. Additionally, we identified that IRF4^L116R, a mutant associated with chronic lymphocytic leukemia, binds more robustly to DNA thereby providing a rationale for the observed gain of function. Together, we demonstrate key structural differences between IRF4 homo and heterodimeric complexes, thereby providing molecular insights into IRF4-mediated transcriptional regulation.

Multi-omics tumor profiling technologies to develop precision medicine in multiple myeloma

Multiple myeloma (MM), the second most common hematologic cancer, is caused by accumulation of aberrant plasma cells in the bone marrow. Its molecular causes are not fully understood and its great heterogeneity among patients complicates therapeutic decision-making. In the past decades, development of new therapies and drugs have significantly improved survival of MM patients. However, resistance to drugs and relapse remain the most common causes of mortality and are the major challenges to overcome. The advent of high throughput omics technologies capable of analyzing big amount of clinical and biological data has changed the way to diagnose and treat MM. Integration of omics data (gene mutations, gene expression, epigenetic information, and protein and metabolite levels) with clinical histories of thousands of patients allows to build scores to stratify the risk at diagnosis and predict the response to treatment, helping clinicians to make better educated decisions for each particular case. There is no doubt that the future of MM treatment relies on personalized therapies based on predictive models built from omics studies. This review summarizes the current treatments and the use of omics technologies in MM, and their importance in the implementation of personalized medicine.

Multi-omics tumor profiling technologies to develop precision medicine in multiple myeloma

Multiple myeloma (MM), the second most common hematologic cancer, is caused by accumulation of aberrant plasma cells in the bone marrow. Its molecular causes are not fully understood and its great heterogeneity among patients complicates therapeutic decision-making. In the past decades, development of new therapies and drugs have significantly improved survival of MM patients. However, resistance to drugs and relapse remain the most common causes of mortality and are the major challenges to overcome. The advent of high throughput omics technologies capable of analyzing big amount of clinical and biological data has changed the way to diagnose and treat MM. Integration of omics data (gene mutations, gene expression, epigenetic information, and protein and metabolite levels) with clinical histories of thousands of patients allows to build scores to stratify the risk at diagnosis and predict the response to treatment, helping clinicians to make better educated decisions for each particular case. There is no doubt that the future of MM treatment relies on personalized therapies based on predictive models built from omics studies. This review summarizes the current treatments and the use of omics technologies in MM, and their importance in the implementation of personalized medicine.

Analysis of Intratumoral Heterogeneity in Myelodysplastic Syndromes with Isolated del(5q) Using a Single Cell Approach

Simple Summary

Myelodysplastic syndromes (MDS) are a heterogeneous group of clonal hematopoietic stem cell malignancies characterized by ineffective differentiation of one or more bone marrow cell lineages. Only 50% of patients with de novo MDS will be found to have cytogenetic abnormalities, of which del(5q) is the most common. In 10% of MDS cases, del(5q) is found as a sole abnormality. In this work, a single cell approach was used to analyze intratumoral heterogeneity in four patients with MDS with isolated del(5q). We were able to observe that an ancestral event in one patient can appear as a secondary hit in another one, thus reflecting the high intratumoral heterogeneity in MDS with isolated del(5q) and the importance of patient-specific molecular characterization.

Abstract

Myelodysplastic syndromes (MDS) are a heterogeneous group of hematological diseases. Among them, the most well characterized subtype is MDS with isolated chromosome 5q deletion (MDS del(5q)), which is the only one defined by a cytogenetic abnormality that makes these patients candidates to be treated with lenalidomide. During the last decade, single cell (SC) analysis has emerged as a powerful tool to decipher clonal architecture and to further understand cancer and other diseases at higher resolution level compared to bulk sequencing techniques. In this study, a SC approach was used to analyze intratumoral heterogeneity in four patients with MDS del(5q). Single CD34+CD117+CD45+CD19- bone marrow hematopoietic stem progenitor cells were isolated using the C1 system (Fluidigm) from diagnosis or before receiving any treatment and from available follow-up samples. Selected somatic alterations were further analyzed in SC by high-throughput qPCR (Biomark HD, Fluidigm) using specific TaqMan assays. A median of 175 cells per sample were analyzed. Inferred clonal architectures were relatively simple and either linear or branching. Similar to previous studies based on bulk sequencing to infer clonal architecture, we were able to observe that an ancestral event in one patient can appear as a secondary hit in another one, thus reflecting the high intratumoral heterogeneity in MDS del(5q) and the importance of patient-specific molecular characterization.

Carfilzomib, lenalidomide, dexamethasone, and cyclophosphamide (KRdc) as induction therapy for transplant-eligible, newly diagnosed multiple myeloma patients (Myeloma XI+): Interim analysis of an open-label randomised controlled trial

BACKGROUND

Carfilzomib is a second-generation irreversible proteasome inhibitor that is efficacious in the treatment of myeloma and carries less risk of peripheral neuropathy than first-generation proteasome inhibitors, making it more amenable to combination therapy.

METHODS AND FINDINGS

The Myeloma XI+ trial recruited patients from 88 sites across the UK between 5 December 2013 and 20 April 2016. Patients with newly diagnosed multiple myeloma eligible for transplantation were randomly assigned to receive the combination carfilzomib, lenalidomide, dexamethasone, and cyclophosphamide (KRdc) or a triplet of lenalidomide, dexamethasone, and cyclophosphamide (Rdc) or thalidomide, dexamethasone, and cyclophosphamide (Tdc). All patients were planned to receive an autologous stem cell transplantation (ASCT) prior to a randomisation between lenalidomide maintenance and observation. Eligible patients were aged over 18 years and had symptomatic myeloma. The co-primary endpoints for the study were progression-free survival (PFS) and overall survival (OS) for KRdc versus the Tdc/Rdc control group by intention to treat. PFS, response, and safety outcomes are reported following a planned interim analysis. The trial is registered (ISRCTN49407852) and has completed recruitment. In total, 1,056 patients (median age 61 years, range 33 to 75, 39.1% female) underwent induction randomisation to KRdc (n = 526) or control (Tdc/Rdc, n = 530). After a median follow-up of 34.5 months, KRdc was associated with a significantly longer PFS than the triplet control group (hazard ratio 0.63, 95% CI 0.51-0.76). The median PFS for patients receiving KRdc is not yet estimable, versus 36.2 months for the triplet control group (p < 0.001). Improved PFS was consistent across subgroups of patients including those with genetically high-risk disease. At the end of induction, the percentage of patients achieving at least a very good partial response was 82.3% in the KRdc group versus 58.9% in the control group (odds ratio 4.35, 95% CI 3.19-5.94, p < 0.001). Minimal residual disease negativity (cutoff 4 × 10-5 bone marrow leucocytes) was achieved in 55% of patients tested in the KRdc group at the end of induction, increasing to 75% of those tested after ASCT. The most common adverse events were haematological, with a low incidence of cardiac events. The trial continues to follow up patients to the co-primary endpoint of OS and for planned long-term follow-up analysis. Limitations of the study include a lack of blinding to treatment regimen and that the triplet control regimen did not include a proteasome inhibitor for all patients, which would be considered a current standard of care in many parts of the world.

CONCLUSIONS

The KRdc combination was well tolerated and was associated with both an increased percentage of patients achieving at least a very good partial response and a significant PFS benefit compared to immunomodulatory-agent-based triplet therapy.

TRIAL REGISTRATION

ClinicalTrials.gov ISRCTN49407852.