RAS/RAF landscape in monoclonal plasma cell conditions.

ABSTRACT: Multiple myeloma is characterized by a huge heterogeneity at the molecular level. The RAS/RAF pathway is the most frequently mutated, in ∼50% of the patients. However, these mutations are frequently subclonal, suggesting a secondary event. Because these genes are part of our routine next-generation sequencing panel, we analyzed >10 000 patients with different plasma cell disorders to describe the RAS/RAF landscape. In this large cohort of patients, almost 61% of the patients presented a RAS/RAF mutation at diagnosis or relapse, but much lower frequencies occurred in presymptomatic cases. Of note, the mutations were different from that observed in solid tumors (higher proportions of Q61 mutations). In 29 patients with 2 different mutations, we were able to perform single-cell sequencing, showing that in most cases, mutations occurred in different subclones, suggesting an ongoing mutational process. These findings suggest that the RAS/RAF pathway is not an attractive target, both on therapeutic and residual disease assessment points of view.

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

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

High-dose melphalan treatment significantly increases mutational burden at relapse in multiple myeloma.

High-dose melphalan (HDM) improves progression-free survival in multiple myeloma (MM), yet melphalan is a DNA-damaging alkylating agent; therefore, we assessed its mutational effect on surviving myeloma cells by analyzing paired MM samples collected at diagnosis and relapse in the IFM 2009 study. We performed deep whole-genome sequencing on samples from 68 patients, 43 of whom were treated with RVD (lenalidomide, bortezomib, and dexamethasone) and 25 with RVD + HDM. Although the number of mutations was similar at diagnosis in both groups (7137 vs 7230; P = .67), the HDM group had significantly more mutations at relapse (9242 vs 13 383, P = .005). No change in the frequency of copy number alterations or structural variants was observed. The newly acquired mutations were typically associated with DNA damage and double-stranded breaks and were predominantly on the transcribed strand. A machine learning model, using this unique pattern, predicted patients who would receive HDM with high sensitivity, specificity, and positive prediction value. Clonal evolution analysis showed that all patients treated with HDM had clonal selection, whereas a static progression was observed with RVD. A significantly higher percentage of mutations were subclonal in the HDM cohort. Intriguingly, patients treated with HDM who achieved complete remission (CR) had significantly more mutations at relapse yet had similar survival rates as those treated with RVD who achieved CR. This similarity could have been due to HDM relapse samples having significantly more neoantigens. Overall, our study identifies increased genomic changes associated with HDM and provides rationale to further understand clonal complexity.

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.

IgM-MM is predominantly a pre-germinal center disorder and has a distinct genomic and transcriptomic signature from WM.

Immunoglobulin M (IgM) multiple myeloma (MM) is a rare disease subgroup. Its differentiation from other IgM-producing gammopathies such as Waldenström macroglobulinemia (WM) has not been well characterized but is essential for proper risk assessment and treatment. In this study, we investigated genomic and transcriptomic characteristics of IgM-MM samples using whole-genome and transcriptome sequencing to identify differentiating characteristics from non-IgM-MM and WM. Our results suggest that IgM-MM shares most of its defining structural variants and gene-expression profiling with MM, but has some key characteristics, including t(11;14) translocation, chromosome 6 and 13 deletion as well as distinct molecular and transcription-factor signatures. Furthermore, IgM-MM translocations were predominantly characterized by VHDHJH recombination-induced breakpoints, as opposed to the usual class-switching region breakpoints; coupled with its lack of class switching, these data favor a pre-germinal center origin. Finally, we found elevated expression of clinically relevant targets, including CD20 and Bruton tyrosine kinase, as well as high BCL2/BCL2L1 ratio in IgM-MM, providing potential for targeted therapeutics.

Biallelic loss of BCMA as a resistance mechanism to CAR T cell therapy in a patient with multiple myeloma.

BCMA targeting chimeric antigen receptor (CAR) T cell therapy has shown deep and durable responses in multiple myeloma. However, relapse following therapy is frequently observed, and mechanisms of resistance remain ill-defined. Here, we perform single cell genomic characterization of longitudinal samples from a patient who relapsed after initial CAR T cell treatment with lack of response to retreatment. We report selection, following initial CAR T cell infusion, of a clone with biallelic loss of BCMA acquired by deletion of one allele and a mutation that creates an early stop codon on the second allele. This loss leads to lack of CAR T cell proliferation following the second infusion and is reflected by lack of soluble BCMA in patient serum. Our analysis suggests the need for careful detection of BCMA gene alterations in multiple myeloma cells from relapse following CAR T cell therapy.

Clinical features associated with COVID-19 outcome in multiple myeloma: first results from the International Myeloma Society data set.

The primary cause of morbidity and mortality in patients with multiple myeloma (MM) is an infection. Therefore, there is great concern about susceptibility to the outcome of COVID-19-infected patients with MM. This retrospective study describes the baseline characteristics and outcome data of COVID-19 infection in 650 patients with plasma cell disorders, collected by the International Myeloma Society to understand the initial challenges faced by myeloma patients during the COVID-19 pandemic. Analyses were performed for hospitalized MM patients. Among hospitalized patients, the median age was 69 years, and nearly all patients (96%) had MM. Approximately 36% were recently diagnosed (2019-2020), and 54% of patients were receiving first-line therapy. Thirty-three percent of patients have died, with significant geographic variability, ranging from 27% to 57% of hospitalized patients. Univariate analysis identified age, International Staging System stage 3 (ISS3), high-risk disease, renal disease, suboptimal myeloma control (active or progressive disease), and 1 or more comorbidities as risk factors for higher rates of death. Neither history of transplant, including within a year of COVID-19 diagnosis, nor other anti-MM treatments were associated with outcomes. Multivariate analysis found that only age, high-risk MM, renal disease, and suboptimal MM control remained independent predictors of adverse outcome with COVID-19 infection. The management of MM in the era of COVID-19 requires careful consideration of patient- and disease-related factors to decrease the risk of acquiring COVID-19 infection, while not compromising disease control through appropriate MM treatment. This study provides initial data to develop recommendations for the management of MM patients with COVID-19 infection.

Genome-Wide Somatic Alterations in Multiple Myeloma Reveal a Superior Outcome Group.

PURPOSE: Multiple myeloma (MM) is accompanied by heterogeneous somatic alterations. The overall goal of this study was to describe the genomic landscape of myeloma using deep whole-genome sequencing (WGS) and develop a model that identifies patients with long survival. METHODS: We analyzed deep WGS data from 183 newly diagnosed patients with MM treated with lenalidomide, bortezomib, and dexamethasone (RVD) alone or RVD + autologous stem cell transplant (ASCT) in the IFM/DFCI 2009 study (ClinicalTrials.gov identifier: NCT01191060). We integrated genomic markers with clinical data. RESULTS: We report significant variability in mutational load and processes within MM subgroups. The timeline of observed activation of mutational processes provides the basis for 2 distinct models of acquisition of mutational changes detected at the time of diagnosis of myeloma. Virtually all MM subgroups have activated DNA repair-associated signature as a prominent late mutational process, whereas APOBEC signature targeting C>G is activated in the intermediate phase of disease progression in high-risk MM. Importantly, we identify a genomically defined MM subgroup (17% of newly diagnosed patients) with low DNA damage (low genomic scar score with chromosome 9 gain) and a superior outcome (100% overall survival at 69 months), which was validated in a large independent cohort. This subgroup allowed us to distinguish patients with low- and high-risk hyperdiploid MM and identify patients with prolongation of progression-free survival. Genomic characteristics of this subgroup included lower mutational load with significant contribution from age-related mutations as well as frequent NRAS mutation. Surprisingly, their overall survival was independent of International Staging System and minimal residual disease status. CONCLUSION: This is a comprehensive study identifying genomic markers of a good-risk group with prolonged survival. Identification of this patient subgroup will affect future therapeutic algorithms and research planning.

Summary of the 2019 Blood and Marrow Transplant Clinical Trials Network Myeloma Intergroup Workshop on Minimal Residual Disease and Immune Profiling.

The Blood and Marrow Transplant Clinical Trials Network (BMT CTN) Myeloma Intergroup has organized an annual workshop focused on minimal residual disease (MRD) testing and immune profiling (IP) in multiple myeloma since 2016. In 2019, the workshop took place as an American Society of Hematology (ASH) Friday Scientific Workshop titled "Immune Profiling and Minimal Residual Disease Testing in Multiple Myeloma." This workshop focused on 4 main topics: the molecular and immunologic evolution of plasma cell disorders, development of new laboratory- and imaging-based MRD assessment approaches, chimeric antigen receptor T cell therapy research, and statistical and regulatory issues associated with novel clinical endpoints. In this report, we provide a summary of the workshop and discuss future directions.

Genomic landscape and chronological reconstruction of driver events in multiple myeloma.

The multiple myeloma (MM) genome is heterogeneous and evolves through preclinical and post-diagnosis phases. Here we report a catalog and hierarchy of driver lesions using sequences from 67 MM genomes serially collected from 30 patients together with public exome datasets. Bayesian clustering defines at least 7 genomic subgroups with distinct sets of co-operating events. Focusing on whole genome sequencing data, complex structural events emerge as major drivers, including chromothripsis and a novel replication-based mechanism of templated insertions, which typically occur early. Hyperdiploidy also occurs early, with individual trisomies often acquired in different chronological windows during evolution, and with a preferred order of acquisition. Conversely, positively selected point mutations, whole genome duplication and chromoplexy events occur in later disease phases. Thus, initiating driver events, drawn from a limited repertoire of structural and numerical chromosomal changes, shape preferred trajectories of evolution that are biologically relevant but heterogeneous across patients.

Deciphering the chronology of copy number alterations in Multiple Myeloma.

Multiple myeloma (MM) and its precursor condition MGUS are characterized by chromosomal aberrations. Here, we comprehensively characterize the order of occurrence of these complex genomic events underlying MM development using 500 MGUS, and MM samples. We identify hyperdiploid MM (HMM) and non-HMM as genomically distinct entities with different evolution of the copy number alterations. In HMM, gains of 9,15 or 19 are the first and clonal events observed as clonal even at MGUS stage. These events are thus early and may underlie initial transformation of normal plasma cells to MGUS cells. However, CNAs may not be adequate for progression to MM except in 15% of the patients in whom the complex subclonal deletion events are observed in MM but not MGUS. In NHMM, besides the driver translocations, clonal deletion of 13 and 1q gain are early events also observed in MGUS. We combined this information to propose a timeline for copy number alteration.

A multiple myeloma classification system that associates normal B-cell subset phenotypes with prognosis.

Despite the recent progress in treatment of multiple myeloma (MM), it is still an incurable malignant disease, and we are therefore in need of new risk stratification tools that can help us to understand the disease and optimize therapy. Here we propose a new subtyping of myeloma plasma cells (PCs) from diagnostic samples, assigned by normal B-cell subset associated gene signatures (BAGS). For this purpose, we combined fluorescence-activated cell sorting and gene expression profiles from normal bone marrow (BM) Pre-BI, Pre-BII, immature, naïve, memory, and PC subsets to generate BAGS for assignment of normal BM subtypes in diagnostic samples. The impact of the subtypes was analyzed in 8 available data sets from 1772 patients' myeloma PC samples. The resulting tumor assignments in available clinical data sets exhibited similar BAGS subtype frequencies in 4 cohorts from de novo MM patients across 1296 individual cases. The BAGS subtypes were significantly associated with progression-free and overall survival in a meta-analysis of 916 patients from 3 prospective clinical trials. The major impact was observed within the Pre-BII and memory subtypes, which had a significantly inferior prognosis compared with other subtypes. A multiple Cox proportional hazard analysis documented that BAGS subtypes added significant, independent prognostic information to the translocations and cyclin D classification. BAGS subtype analysis of patient cases identified transcriptional differences, including a number of differentially spliced genes. We identified subtype differences in myeloma at diagnosis, with prognostic impact and predictive potential, supporting an acquired B-cell trait and phenotypic plasticity as a pathogenetic hallmark of MM.

Genomic patterns of progression in smoldering multiple myeloma.

We analyzed whole genomes of unique paired samples from smoldering multiple myeloma (SMM) patients progressing to multiple myeloma (MM). We report that the genomic landscape, including mutational profile and structural rearrangements at the smoldering stage is very similar to MM. Paired sample analysis shows two different patterns of progression: a "static progression model", where the subclonal architecture is retained as the disease progressed to MM suggesting that progression solely reflects the time needed to accumulate a sufficient disease burden; and a "spontaneous evolution model", where a change in the subclonal composition is observed. We also observe that activation-induced cytidine deaminase plays a major role in shaping the mutational landscape of early subclinical phases, while progression is driven by APOBEC cytidine deaminases. These results provide a unique insight into myelomagenesis with potential implications for the definition of smoldering disease and timing of treatment initiation.

Therapeutic vulnerability of multiple myeloma to MIR17PTi, a first-in-class inhibitor of pri-miR-17-92.

The microRNA (miRNA) cluster miR-17-92 is oncogenic and represents a valuable therapeutic target in c-MYC (MYC)-driven malignancies. Here, we developed novel LNA gapmeR antisense oligonucleotides (ASOs) to induce ribonuclease H-mediated degradation of MIR17HG primary transcripts and consequently prevent biogenesis of miR-17-92 miRNAs (miR-17-92s). The leading LNA ASO, MIR17PTi, impaired proliferation of several cancer cell lines (n = 48) established from both solid and hematologic tumors by on-target antisense activity, more effectively as compared with miR-17-92 inhibitors. By focusing on multiple myeloma (MM), we found that MIR17PTi triggers apoptosis via impairment of homeostatic MYC/miR-17-92 feed-forward loops (FFLs) in patient-derived MM cells and induces MYC-dependent synthetic lethality. We show that alteration of a BIM-centered FFL is instrumental for MIR17PTi to induce cytotoxicity in MM cells. MIR17PTi exerts strong in vivo antitumor activity in nonobese diabetic severe combined immunodeficient mice bearing clinically relevant models of MM, with advantageous safety and pharmacokinetic profiles in nonhuman primates. Altogether, MIR17PTi is a novel pharmacological tool to be tested in early-phase clinical trials against MM and other MYC-driven malignancies.

Long intergenic non-coding RNAs have an independent impact on survival in multiple myeloma.

Although long intergenic non-coding RNAs (lincRNA) role in various cancers is described, their significance in Multiple Myeloma (MM) remains poorly defined. Here we have studied the lincRNA profile and their clinical impact in MM. We performed RNA-seq on MM cells from 308 newly diagnosed and uniformly treated patients, 16 normal plasma cells and utilized RNA-seq data from 532 newly diagnosed patients from CoMMpass study to analyze for lincRNAs. We observed 869 differentially expressed lincRNAs in MM compared to normal plasma cells. We identified 14 lincRNAs associated with PFS and calculated a risk score to stratify patients. The median PFS between high vs low-risk groups was 17 months vs not-reached (NR); and OS 30 months vs NR, respectively (p < 0.0001 for both). In the independent validation dataset between high and low-risk groups, PFS was 27 vs 42 months (HR 2.06 [1.44-2.96]; p < 0.0005); and 4-year OS 62% vs 86% (HR 2.76 [1.51-5.05]; p < 0.0005) confirming significant clinical relevance of lincRNA in MM. Importantly, lincRNA signature was able to further identify patients with significant differential outcomes within each low and high-risk categories identified using standard risk categorization including cytogenetic/FISH, ISS, and MRD negative or positive. Our results suggest that lincRNAs have an independent effect on MM outcome and provide a rationale to evaluate its molecular and biological impact.

A Web-based Game for Teaching Facial Expressions to Schizophrenic Patients.

BACKGROUND: Recognizing facial expressions is an important social skill. In some psychological disorders such as schizophrenia, loss of this skill may complicate the patient's daily life. Prior research has shown that information technology may help to develop facial expression recognition skills through educational software and games. OBJECTIVES: To examine if a computer game designed for teaching facial expressions would improve facial expression recognition skills of patients with schizophrenia. METHODS: We developed a website composed of eight serious games. Thirty-two patients were given a pre-test composed of 21 facial expression photographs. Eighteen patients were in the study group while 14 were in the control group. Patients in the study group were asked to play the games on the website. After a period of one month, we performed a post-test for all patients. RESULTS: The median score of the correct answers was 17.5 in the control group whereas it was 16.5 in the study group (of 21) in pretest. The median post-test score was 18 in the control group (p=0.052) whereas it was 20 in the study group (p<0.001). CONCLUSIONS: Computer games may be used for the purpose of educating people who have difficulty in recognizing facial expressions.

ILF2 Is a Regulator of RNA Splicing and DNA Damage Response in 1q21-Amplified Multiple Myeloma.

Amplification of 1q21 occurs in approximately 30% of de novo and 70% of relapsed multiple myeloma (MM) and is correlated with disease progression and drug resistance. Here, we provide evidence that the 1q21 amplification-driven overexpression of ILF2 in MM promotes tolerance of genomic instability and drives resistance to DNA-damaging agents. Mechanistically, elevated ILF2 expression exerts resistance to genotoxic agents by modulating YB-1 nuclear localization and interaction with the splicing factor U2AF65, which promotes mRNA processing and the stabilization of transcripts involved in homologous recombination in response to DNA damage. The intimate link between 1q21-amplified ILF2 and the regulation of RNA splicing of DNA repair genes may be exploited to optimize the use of DNA-damaging agents in patients with high-risk MM.