Next-Generation Sequencing for Clinical Management of Multiple Myeloma: Ready for Prime Time?

Advancements in Multiple Myeloma Research: High-Throughput Sequencing Technologies, Omics, and the Role of Artificial Intelligence

Multiple myeloma is a complex and challenging type of blood cancer that affects plasma cells in the bone marrow. In recent years, the development of advanced research techniques, such as omics approaches-which involve studying large sets of biological data like genes and proteins-and high-throughput sequencing technologies, has allowed researchers to analyze vast amounts of genetic information rapidly and gain new insights into the disease. Additionally, the advent of artificial intelligence tools has accelerated data analysis, enabling more accurate predictions and improved treatment strategies. This review aims to highlight recent research advances in multiple myeloma made possible by these novel techniques and to provide guidance for researchers seeking effective approaches in this field.

Diagnosis and Management of a Patient With Chronic Lymphocytic Leukemia and a Concurrent Plasmacytoma

Chronic lymphocytic leukemia (CLL) typically presents as an indolent disease with a benign disposition in most patients. In select patients, CLL can progress into a more aggressive disease via its original morphology, following a Richter transformation to an alternative non-Hodgkin's lymphoma, or with the concomitant development of multiple myeloma. In an extremely rare subset of individuals with CLL, an extramedullary plasmacytoma may coexist. This case report seeks to describe the diagnosis and treatment of a patient with concurrent CLL and a plasmacytoma.

Quantitative Integrative Survival Prediction in Multiple Myeloma Patients Treated With Bortezomib-Based Induction, High-Dose Therapy and Autologous Stem Cell Transplantation

PURPOSE

Given the high heterogeneity in survival for patients with multiple myeloma, it would be clinically useful to quantitatively predict the individual survival instead of attributing patients to two to four risk groups as in current models, for example, revised International Staging System (R-ISS), R2-ISS, or Mayo-2022-score.

PATIENTS AND METHODS

Our aim was to develop a quantitative prediction tool for individual patient's 3-/5-year overall survival (OS) probability. We integrated established clinical and molecular risk factors into a comprehensive prognostic model and evaluated and validated its risk discrimination capabilities versus R-ISS, R2-ISS, and Mayo-2022-score.

RESULTS

A nomogram for estimating OS probabilities was built on the basis of a Cox regression model. It allows one to translate the individual risk profile of a patient into 3-/5-year OS probabilities by attributing points to each prognostic factor and summing up all points. The nomogram was externally validated regarding discrimination and calibration. There was no obvious bias or overfitting of the prognostic index on the validation cohort. Resampling-based and external evaluation showed good calibration. The c-index of the model was similar on the training (0.76) and validation cohort (0.75) and significantly higher than for the R-ISS (P < .001) or R2-ISS (P < .01).

CONCLUSION

In summary, we developed and validated individual quantitative nomogram-based OS prediction. Continuous risk assessment integrating molecular prognostic factors is superior to R-ISS, R2-ISS, or Mayo-2022-score alone.

The Interplay between the DNA Damage Response (DDR) Network and the Mitogen-Activated Protein Kinase (MAPK) Signaling Pathway in Multiple Myeloma

The DNA damage response (DDR) network and the mitogen-activated protein kinase (MAPK) signaling pathway are crucial mechanisms for the survival of all living beings. An accumulating body of evidence suggests that there is crosstalk between these two systems, thus favoring the appropriate functioning of multi-cellular organisms. On the other hand, aberrations within these mechanisms are thought to play a vital role in the onset and progression of several diseases, including cancer, as well as in the emergence of drug resistance. Here, we provide an overview of the current knowledge regarding alterations in the DDR machinery and the MAPK signaling pathway as well as abnormalities in the DDR/MAPK functional crosstalk in multiple myeloma, the second most common hematologic malignancy. We also present the latest advances in the development of anti-myeloma drugs targeting crucial DDR- and MAPK-associated molecular components. These data could potentially be exploited to discover new therapeutic targets and effective biomarkers as well as for the design of novel clinical trials. Interestingly, they might provide a new approach to increase the efficacy of anti-myeloma therapy by combining drugs targeting the DDR network and the MAPK signaling pathway.

Liquid Biopsies as Non-Invasive Tools for Mutation Profiling in Multiple Myeloma: Application Potential, Challenges, and Opportunities

Over the last decades, the survival of multiple myeloma (MM) patients has considerably improved. However, despite the availability of new treatments, most patients still relapse and become therapy-resistant at some point in the disease evolution. The mutation profile has an impact on MM patients' outcome, while typically evolving over time. Because of the patchy bone marrow (BM) infiltration pattern, the analysis of a single bone marrow sample can lead to an underestimation of the known genetic heterogeneity in MM. As a result, interest is shifting towards blood-derived liquid biopsies, which allow for a more comprehensive and non-invasive genetic interrogation without the discomfort of repeated BM aspirations. In this review, we compare the application potential for mutation profiling in MM of circulating-tumor-cell-derived DNA, cell-free DNA and extracellular-vesicle-derived DNA, while also addressing the challenges associated with their use.

Impact of Clonal Heterogeneity in Multiple Myeloma

Multiple myeloma is characterized by a highly heterogeneous disease distribution within the bone marrow-containing skeletal system. In this review, we introduce the molecular mechanisms underlying clonal heterogeneity and the spatio-temporal evolution of myeloma. We discuss the clinical impact of clonal heterogeneity, which is thought to be one of the biggest obstacles to overcome therapy resistance and to achieve cure.

Predictors and Impact of Timing of Disease Progression Following Primary Therapy in Multiple Myeloma

In multiple myeloma (MM) significant variation in progression-free survival (PFS) and overall survival (OS) is observed. We examined the outcomes of 1557 MM patients stratified into short (<2 years), medium (between 2 and 5 years) and long (>5 years) PFS. Short PFS occurred in 758 patients (48.7%), medium in 561 patients (36.2%), and long in 238 patients (15.3%). Median post-progression PFS was 9.2 months (95% CI: 8.1-11.0) in the short PFS and 33.1 months (95% CI: 29.0-42.1; P < .001) in the long PFS group. Median post-progression OS was 26.6 months (95% CI: 23.9-29.8) in the short PFS and 87.8 months (95% CI: 71.3- NR; P < .001) in the long PFS. Worse survival in the short PFS was irrespective of high risk (HR) fluorescence in situ hybridization (FISH) features, defined as deletion 17p and/or translocation t(4;14), t(14;16), t(14;20). In a multivariable analysis short PFS was associated with HR FISH, extramedullary plasmacytoma, plasma cell labeling index ≥2% at diagnosis, nonimmunoglobulin G isotype, treatment without autologous stem cell transplantation and achieving less than very good partial remission. In conclusion, the duration of the PFS significantly influences survival, regardless of HR cytogenetic features. Therefore, it should be considered an important parameter for risk stratification in patients experiencing a relapse.

An overview of multiple myeloma: A monoclonal plasma cell malignancy's diagnosis, management, and treatment modalities

Multiple Myeloma (MM) is a plasma cell cancer with high mortality and morbidity rates. Its incidence rate has increased by 143% since 1975. Adipokines, cytokines, chemokines, and genetic variations influence the development and progression of MM. Chromosomal translocations cause mutations associated with MM. The pathogenesis of MM is complicated by novel issues like miRNAs, RANKL, Wnt/DKK1, Wnt, and OPG. Conventional diagnosis methods include bone marrow biopsy, sPEP or uPEP, sIFE and uIFE, and sFLC assay, along with advanced techniques such as FISH, SNPA, and gene expression technologies. A novel therapeutic strategy has been developed recently. Chemotherapy, hematopoietic stem cell transplantation, and a variety of drug classes in combination are used to treat patients with high-risk diseases. Alkylating agents, PIs, and IMiDs have all been developed as effective treatment options for MM in recent years. This review overviews the current recommendations for managing MGUS, SMM, MM, SP and NSMM and discusses practices in diagnosing and treating MM.

RNA-sequencing based first choice of treatment and determination of risk in multiple myeloma

Background

Immunotherapeutic targets in multiple myeloma (MM) have variable expression height and are partly expressed in subfractions of patients only. With increasing numbers of available compounds, strategies for appropriate choice of targets (combinations) are warranted. Simultaneously, risk assessment is advisable as patient's life expectancy varies between months and decades.

Methods

We first assess feasibility of RNA-sequencing in a multicenter trial (GMMG-MM5, n=604 patients). Next, we use a clinical routine cohort of untreated symptomatic myeloma patients undergoing autologous stem cell transplantation (n=535, median follow-up (FU) 64 months) to perform RNA-sequencing, gene expression profiling (GEP), and iFISH by ten-probe panel on CD138-purified malignant plasma cells. We subsequently compare target expression to plasma cell precursors, MGUS (n=59), asymptomatic (n=142) and relapsed (n=69) myeloma patients, myeloma cell lines (n=26), and between longitudinal samples (MM vs. relapsed MM). Data are validated using the independent MMRF CoMMpass-cohort (n=767, FU 31 months).

Results

RNA-sequencing is feasible in 90.8% of patients (GMMG-MM5). Actionable immune-oncological targets (n=19) can be divided in those expressed in all normal and >99% of MM-patients (CD38, SLAMF7, BCMA, GPRC5D, FCRH5, TACI, CD74, CD44, CD37, CD79B), those with expression loss in subfractions of MM-patients (BAFF-R [81.3%], CD19 [57.9%], CD20 [82.8%], CD22 [28.4%]), aberrantly expressed in MM (NY-ESO1/2 [12%], MUC1 [12.7%], CD30 [4.9%], mutated BRAF V600E/K [2.1%]), and resistance-conveying target-mutations e.g., against part but not all BCMA-directed treatments. Risk is assessable regarding proliferation, translated GEP- (UAMS70-, SKY92-, RS-score) and de novo (LfM-HRS) defined risk scores. LfM-HRS delineates three groups of 40%, 38%, and 22% of patients with 5-year and 12-year survival rates of 84% (49%), 67% (18%), and 32% (0%). R-ISS and RNA-sequencing identify partially overlapping patient populations, with R-ISS missing, e.g., 30% (22/72) of highly proliferative myeloma.

Conclusion

RNA-sequencing based assessment of risk and targets for first choice treatment is possible in clinical routine.

Comprehensive analysis of ferroptosis-related genes in immune infiltration and prognosis in multiple myeloma

Background: One particular type of cellular death that is known as ferroptosis is caused by the excessive lipid peroxidation. It is a regulated form of cell death that can affect the response of the tumor cells. Currently, it is not known if the presence of this condition can affect the prognosis of patients with multiple myeloma (MM). Methods: In this study, we studied the expression differences and prognostic value of ferroptosis-related genes (FRGs) in MM, and established a ferroptosis risk scoring model. In order to improve the prediction accuracy and clinical applicability, a nomogram was also established. Through gene enrichment analysis, pathways closely related to high-risk groups were identified. We then explored the differences in risk stratification in drug sensitivity and immune patterns, and evaluated their value in prognostic prediction and treatment response. Lastly, we gathered MM cell lines and samples from patients to confirm the expression of marker FRGs using quantitative real-time PCR (qRT-PCR). Results: The ability to predict the survival of MM patients is a challenging issue. Through the use of a risk model derived from ferroptosis, we were able to develop a more accurate prediction of the disease's prognosis. They were then validated by a statistical analysis, which showed that the model is an independent factor in the prognosis of MM. Patients of high ferroptosis risk scores had a much worse chance of survival than those in the low-risk groups. The calibration and power of the nomogram were also strong. We noted that the link between the ferroptosis risk score and the clinical treatment was suggested by the FRG's significant correlation with the immune checkpoint genes and the medication sensitivity. We validated the predictive model using qRT-PCR. Conclusion: We demonstrated the association between FRGs and MM, and developed a new risk model for prognosis in MM patients. Our study sheds light on the potential clinical relevance of ferroptosis in MM and highlights its potential as a therapeutic target for patients with this disease.

Disparity in the detection of chromosome 15 centromere in patients of African ancestry with a plasma cell neoplasm

Purpose

Fluorescence in situ hybridization (FISH) is the current gold standard assay that provides information related to risk stratification and therapeutic selection for individuals with plasma cell neoplasms. The differential hybridization of FISH probe sets in association with individuals' genetic ancestry has not been previously reported.

Methods

This retrospective study included 1224 bone marrow samples from individuals who had an abnormal plasma cell proliferative disorder FISH result and a concurrent conventional G-banded chromosome study. DNA from bone marrow samples obtained from the G-banded chromosome study was genotyped, and a biogeographical ancestry prediction was carried out.

Results

Using a cohort of individuals with a plasma cell neoplasm, we identified reduced hybridization of a chromosome 15 centromere FISH probe (D15Z4). Metaphase FISH studies of cells with 2 copies of chromosome 15 demonstrated a failure of the D15Z4 FISH probe to hybridize to one chromosome 15 centromere, revealing a false-positive monosomy 15 FISH result in some individuals. Surprisingly, individuals with a monosomy 15 FISH result had a median African ancestry of 77.2% (95% CI 74.1%-80.3%), compared with a median African ancestry of 2.2% (95% CI 2.0%-2.5%) in the non-monosomy 15 cohort (P value = 9.4 × 10-10). Thus, individuals with African ancestry had an 8.02-fold (95% CI 3.73-17.25) increased probability of having a false-positive monosomy 15 result (P value = 9.92 × 10-8).

Conclusion

This study emphasizes a concern regarding the reliability of diagnostic genomic tools and their application in interpreting genetic testing results in diverse patient populations. We discuss alternative methodologies to better represent different ancestry groups in clinical diagnostic testing.

A Novel Variant in VPS13B Underlying Cohen Syndrome

Pathogenic variants in vacuolar protein sorting 13 homolog B (VPS13B) cause Cohen syndrome (CS), a clinically diverse neurodevelopmental disorder. We used whole exome and Sanger sequencing to identify disease-causing variants in a Pakistani family with intellectual disability, microcephaly, facial dysmorphism, neutropenia, truncal obesity, speech delay, motor delay, and insomnia. We identified a novel homozygous nonsense variant c.8841G > A: p.(W2947∗) in VPS13B (NM_017890.5) which segregated with the disease. Sleep disturbances are commonly seen in neurodevelopmental disorders and can exacerbate medical issues if left untreated. We demonstrate that individuals with Cohen syndrome may also be affected by sleep disturbances. In conclusion, we expand the genetic and phenotypic features of Cohen syndrome in the Pakistani population.

Consensus for Flow Cytometry Clinical Report on Multiple Myeloma: A Multicenter Harmonization Process Merging Laboratory Experience and Clinical Needs

Flow cytometry is a highly sensitive and specific approach for discriminating between normal and clonal plasma cells in multiple myeloma. Uniform response criteria after treatment have been established by the International Myeloma Working Group and the EuroFlow Group; however, the way in which flow cytometry data are reported has suffered from no collaborative or multicentre efforts. This study, involving 8 expert laboratories and 12 clinical hematology units of the Lazio region in Italy, aims to produce a uniform and shared report among the various Centres. From the pre-analytical phase to sample processing, data acquisition, analysis, and evaluation of the potential limitations and pitfalls of the entire process, the study reaches a final conclusion shared by laboratories and clinicians according to the most updated principles and recommendations. The aim was to identify the necessary data to be included in the clinical report by using multiple-choice questionnaires at every single stage of the process. An agreement of more than 75% of the laboratories was considered mandatory for the data to be included in the report. By ensuring the operational autonomy of each laboratory, this study provides a clear report that limits subjective interpretations and highlights possible bias in the process, better supporting clinical decision-making.

Precision Medicine Approach Based on Molecular Alterations for Patients with Relapsed or Refractory Multiple Myeloma: Results from the MM-EP1 Study

BACKGROUND

Despite that cytogenetic and molecular analysis of tumor cells can rapidly identify recurring molecular abnormalities, no personalized therapy is currently available in the setting of relapsed/refractory multiple myeloma (r/r MM).

METHODS

MM-EP1 is a retrospective study aimed at comparing a personalized molecular-oriented (MO) versus a non-molecular-oriented (no-MO) approach in r/r MM. Actionable molecular targets and their associated therapies were the BRAF V600E mutation and BRAF inhibitors; t(11;14)(q13;q32) and BCL2 inhibitors; and t(4;14)(p16;q32) with FGFR3 fusion/rearrangements and FGFR3 inhibitors.

RESULTS

One hundred three highly pretreated r/r MM patients with a median age of 67 years (range 44-85) were included. Seventeen (17%) patients were treated using an MO approach with BRAF inhibitors (vemurafenib or dabrafenib, n = 6), BCL2 inhibitor (venetoclax, n = 9), or FGFR3 inhibitor (erdafitinib, n = 2). Eighty-six (86%) patients received non-MO therapies. Overall response rate was 65% in MO patients versus 58% in the non-MO group (p = 0.053). Median PFS and OS were 9 and 6 months (HR = 0.96; CI95 = 0.51-1.78; p = 0.88) and 26 and 28 months (HR = 0.98; CI95 = 0.46-2.12; p = 0.98), respectively, in MO and no-MO patients.

CONCLUSION

Despite the low number of patients treated with an MO approach, this study highlights the strengths and weakness of a molecular-targeted approach for the treatment of multiple myeloma. Widespread biomolecular techniques and improvement of precision medicine treatment algorithms could improve selection for precision medicine in myeloma.

Identification and validation of a novel cuproptosis-related gene signature in multiple myeloma

Background: Cuproptosis is a newly identified unique copper-triggered modality of mitochondrial cell death, distinct from known death mechanisms such as necroptosis, pyroptosis, and ferroptosis. Multiple myeloma (MM) is a hematologic neoplasm characterized by the malignant proliferation of plasma cells. In the development of MM, almost all patients undergo a relatively benign course from monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM), which further progresses to active myeloma. However, the prognostic value of cuproptosis in MM remains unknown. Method: In this study, we systematically investigated the genetic variants, expression patterns, and prognostic value of cuproptosis-related genes (CRGs) in MM. CRG scores derived from the prognostic model were used to perform the risk stratification of MM patients. We then explored their differences in clinical characteristics and immune patterns and assessed their value in prognosis prediction and treatment response. Nomograms were also developed to improve predictive accuracy and clinical applicability. Finally, we collected MM cell lines and patient samples to validate marker gene expression by quantitative real-time PCR (qRT-PCR). Results: The evolution from MGUS and SMM to MM was also accompanied by differences in the CRG expression profile. Then, a well-performing cuproptosis-related risk model was developed to predict prognosis in MM and was validated in two external cohorts. The high-risk group exhibited higher clinical risk indicators. Cox regression analyses showed that the model was an independent prognostic predictor in MM. Patients in the high-risk group had significantly lower survival rates than those in the low-risk group (p < 0.001). Meanwhile, CRG scores were significantly correlated with immune infiltration, stemness index and immunotherapy sensitivity. We further revealed the close association between CRG scores and mitochondrial metabolism. Subsequently, the prediction nomogram showed good predictive power and calibration. Finally, the prognostic CRGs were further validated by qRT-PCR in vitro. Conclusion: CRGs were closely related to the immune pattern and self-renewal biology of cancer cells in MM. This prognostic model provided a new perspective for the risk stratification and treatment response prediction of MM patients.

Calprotectin as new potential clinical marker for multiple myeloma

Increased levels of inflammatory cytokines in multiple myeloma (MM) patients and the role of inflammation in disease pathogenesis, have recently been considered. The aim of this study was to quantitatively evaluation of fecal calprotectin (CP) as a non-invasive biomarker for the evaluation of inflammation in patients with multiple myeloma. This study is a hospital-based case control study. MM patients referred to patients referred to medical centers of Tehran province, Iran, were identified and classified into two groups of new MM patients (n = 40) and patients undergoing treatment (n = 28). Healthy individuals were included in the study as healthy control (n = 25). Morning stool samples were collected and CP was extracted immediately. After collecting the samples, CP was measured according to ELISA method and was determined in μg/g of feces. Values ​​above 50 μg/g of feces are positive and indicate inflammation. The results revealed that there is a significant difference between groups in terms if CP mean (p = 0.001). The mean of CP among new cases, under treatment and control groups were 301.3 (SD: 141.0), 165.1 (SD: 153.9) and 36.9 (SD: 13.5), respectively. Then the groups were compared in pairs, the results showed that the new case group was significantly different from the under-treatment group (p = 0.001), and also the control group showed a significant difference with the new case group (p = 0.001) and the under-treatment group (p = 0.001) that the amount of CP in the control group was significantly lower than the other two groups. In addition, the results of the study showed a significant correlation between age and plasma cells with CP value, so that with increasing age and plasma cells, CP value also showed a significant increase. The results indicate that quantitative evaluation of CP as a non-invasive laboratory biomarker has a high potential as a clinical marker in patients with multiple myeloma and inflammation should considered as a hallmark of cancer. Further diagnostic studies are recommended.

Single-Cell RNA Sequencing for the Detection of Clonotypic V(D)J Rearrangements in Multiple Myeloma

Multiple myeloma (MM) has a highly heterogeneous genetic background, which complicates its molecular tracking over time. Nevertheless, each MM patient's malignant plasma cells (PCs) share unique V(D)J rearranged sequences at immunoglobulin loci, which represent ideal disease biomarkers. Because the tumor-specific V(D)J sequence is highly expressed in bulk RNA in MM patients, we wondered whether it can be identified by single-cell RNA sequencing (scRNA-seq). To this end we analyzed CD138⁺ cells purified from bone marrow aspirates of 19 samples with PC dyscrasias by both a standard method based on bulk DNA and by an implementation of the standard 10x Genomics protocol to detect expressed V(D)J sequences. A dominant clonotype was easily identified in each sample, accounting on average for 83.65% of V(D)J-rearranged cells. Compared with standard methods, scRNA-seq analysis proved highly concordant and even more effective in identifying clonal productive rearrangements, by-passing limitations related to the misannealing of consensus primers in hypermutated regions. We next validated its accuracy to track 5 clonal cells with absolute sensitivity in a virtual sample containing 3180 polyclonal cells. This shows that single-cell V(D)J analysis may be used to find rare clonal cells, laying the foundations for functional single-cell dissection of minimal residual disease.

The Application of NextGen Sequencing in the Diagnosis of Myeloid Neoplasms in Myeloma Patients With Cytopenia

BACKGROUND

Multiple myeloma (MM) is an incurable clonal neoplasm that usually requires long-term treatment, which may result in secondary cytopenia(s) and myeloid neoplasms. We investigated the landscape of mutations detected by NextGen sequencing (NGS) in myeloma patients with cytopenia.

METHODS AND MATERIALS

MM patients (n = 196) with cytopenia(s) and NGS results were identified and divided into 4 groups: 1) patients with myeloma only and no myeloid neoplasms; 2) patients with myeloid neoplasms but no myeloma; 3) patients with concurrent myeloma and myeloid neoplasms; and 4) patients with no myeloma or myelodysplasia.

RESULTS

The most frequently mutated genes were TP53, DNMT3A, TET2, ASXL1, and KRAS. TP53 mutations were predominantly found among patients with myeloid neoplasms with or without concomitant MM. SF3B1 and TET, the genes most commonly mutated in myelodysplastic syndromes, were less frequently identified among MM patients. ASXL1 mutations were more commonly associated with myeloid neoplasms, whereas KRAS and DNMT3A mutations were more closely associated with MM than myeloid neoplasms. RUNX1 mutations showed closer association with myeloid neoplasms. Fifty-eight patients harbored clonal myeloid gene mutations but no overt morphologic or cytogenetic abnormalities, of which 7 patients had myelodysplastic syndromes that was missed by the original pathologists. Thrombocytopenia appeared to be a more reliable marker than anemia or neutropenia to trigger work-up for myeloid neoplasms.

CONCLUSION

NGS could greatly help with diagnosing myeloid neoplasms in MM patients with cytopenia(s). The depicted gene landscape may facilitate our daily interpretation of NextGen sequencing (NGS).

Functional Impact of Genomic Complexity on the Transcriptome of Multiple Myeloma

PURPOSE

Multiple myeloma is a biologically heterogenous plasma-cell disorder. In this study, we aimed at dissecting the functional impact on transcriptome of gene mutations, copy-number abnormalities (CNA), and chromosomal rearrangements (CR). Moreover, we applied a geno-transcriptomic approach to identify specific biomarkers for personalized treatments.

EXPERIMENTAL DESIGN

We analyzed 514 newly diagnosed patients from the IA12 release of the CoMMpass study, accounting for mutations in multiple myeloma driver genes, structural variants, copy-number segments, and raw-transcript counts. We performed an in silico drug sensitivity screen (DSS), interrogating the Cancer Dependency Map (DepMap) dataset after anchoring cell lines to primary tumor samples using the Celligner algorithm.

RESULTS

Immunoglobulin translocations, hyperdiploidy and chr(1q)gain/amps were associated with the highest number of deregulated genes. Other CNAs and specific gene mutations had a lower but very distinct impact affecting specific pathways. Many recurrent genes showed a hotspot (HS)-specific effect. The clinical relevance of double-hit multiple myeloma found strong biological bases in our analysis. Biallelic deletions of tumor suppressors and chr(1q)-amplifications showed the greatest impact on gene expression, deregulating pathways related to cell cycle, proliferation, and expression of immunotherapy targets. Moreover, our in silico DSS showed that not only t(11;14) but also chr(1q)gain/amps and CYLD inactivation predicted differential expression of transcripts of the BCL2 axis and response to venetoclax.

CONCLUSIONS

The multiple myeloma genomic architecture and transcriptome have a strict connection, led by CNAs and CRs. Gene mutations impacted especially with HS-mutations of oncogenes and biallelic tumor suppressor gene inactivation. Finally, a comprehensive geno-transcriptomic analysis allows the identification of specific deregulated pathways and candidate biomarkers for personalized treatments in multiple myeloma.

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.

Minimal residual disease in multiple myeloma: current status

Multiple myeloma (MM) is a treatable plasma cell cancer with no cure. Clinical evidence shows that the status of minimal residual disease (MRD) after treatment is an independent prognostic factor of MM. MRD indicates the depth of post-therapeutic remission. In this review article, we outlined the major clinical trials that have determined the prognostic value of MRD in MM. We also reviewed different methods that were used for MM MRD assessment. Most important, we reviewed our current understanding of MM MRD biology. MRD studies strongly indicate that MRD is not a uniform declination of whole MM tumor population. Rather, MM MRD exhibits unique signatures of cytogenetic aberration and gene expression profiles, unlike those of MM cells before therapy. Diagnostic high-risk MM and low-risk MM exhibited a diversity of MRD features. Clonal evaluation may occur at the MRD stage in MM. The dynamics from the diagnostic MM to MRD correlate with the disease prognosis. Lastly, on the aspect of omics, we performed data-based analysis to address the biological features underlying the course of diagnostic-to-MRD MM. To summarize, the MRD stage of disease represents a critical step in MM pathogenesis and progression. Demonstration of MM MRD biology should help us to deal with the curative difficulties.

Chromosomal 1q21 abnormalities in multiple myeloma: a review of translational, clinical research, and therapeutic strategies

INTRODUCTION

Multiple myeloma (MM) remains an incurable disease with a median overall survival of approximately 5 years. Gain or amplification of 1q21 (1q21+) occurs in around 40% of patients with MM and generally portends a poor prognosis. Patients with MM who harbor 1q21+ are at increased risk of drug resistance, disease progression, and death. New pharmacotherapies with novel modes of action are required to overcome the negative prognostic impact of 1q21+. Areas covered: This review discusses the detection, biology, prognosis, and therapeutic targeting of 1q21+ in newly diagnosed and relapsed MM. Patients with MM and 1q21+ tend to present with higher tumor burden, greater end-organ damage, and more co-occurring high-risk cytogenetic abnormalities than patients without 1q21+. The chromosomal rearrangements associated with 1q21+ result in dysregulation of genes involved in oncogenesis. Identification and characterization of the 1q21+ molecular targets are needed to inform on prognosis and treatment strategy. Clinical trial data are emerging that addition of isatuximab to combination therapies may improve outcomes in patients with 1q21+ MM. Expert opinion: In the next 5 years, the results of ongoing research and trials are likely to focus on the therapeutic impact and treatment decisions associated with 1q21+ in MM.

Treatment Strategy for Multiple Myeloma to Improve Immunological Environment and Maintain MRD Negativity

Improving the immunological environment and eradicating minimal residual disease (MRD) are the two main treatment goals for long-term survival in patients with multiple myeloma (MM). Immunomodulatory drugs (IMiDs), monoclonal antibody drugs (MoAbs), and autologous grafts for autologous stem cell transplantation (ASCT) can improve the immunological microenvironment. ASCT, MoAbs, and proteasome inhibitors (PIs) may be important for the achievement of MRD negativity. An improved immunological environment may be useful for maintaining MRD negativity, although the specific treatment for persistent MRD negativity is unknown. However, whether the ongoing treatment should be continued or changed if the MRD status remains positive is controversial. In this case, genetic, immunophenotypic, and clinical analysis of residual myeloma cells may be necessary to select the effective treatment for the residual myeloma cells. The purpose of this review is to discuss the MM treatment strategy to "cure MM" based on currently available therapies, including IMiDs, PIs, MoAbs, and ASCT, and expected immunotherapies, such as chimeric antigen receptor T cell (CAR-T) therapy, via improvement of the immunological environment and maintenance of MRD negativity.

Minimal Residual Disease in Multiple Myeloma: Ready for Prime Time?

ABSTRACT

Minimal residual disease (MRD) techniques are essential to identify the small clonal fraction within and outside the bone marrow. In the last years, evidence regarding their prognostic role for the evaluation of the depth of response of current treatment strategies has grown rapidly. Consequently, MRD was incorporated in an increasing number of clinical trials for multiple myeloma patients, also as primary endpoint, and even to guide therapeutic choices. A robust correlation between MRD negativity and survival was established. Yet, several issues regarding MRD evaluation remain to be addressed: from the optimal and more cost-effective techniques for its assessment and its harmonization worldwide to its use in clinical practice to its impact on treatment modulation. This review focuses on the available evidence supporting the use of MRD status for the management of multiple myeloma patients and on open issues that still need an answer.

Gene expression profiling impacts treatment decision making in newly diagnosed multiple myeloma patients in the prospective PROMMIS trial

Multiple myeloma (MM) is a heterogeneous hematologic malignancy associated with several risk factors including genetic aberrations which impact disease response and survival. Thorough risk classification is essential to select the best clinical strategy to optimize outcomes. The SKY92 molecular signature classifies patients as standard- or high-risk for progression. The PRospective Observational Multiple Myeloma Impact Study (PROMMIS; NCT02911571) measures impact of SKY92 on risk classification and treatment plan. Newly diagnosed MM patients had bone marrow aspirates analyzed for SKY92. Physicians completed a questionnaire for each patient capturing risk classification, hypothetical treatment plan, and physician confidence in the treatment plan, before and after unblinding SKY92. One hundred forty seven MM patients were enrolled. Before unblinding SKY92, physicians regarded 74 (50%) patients as clinical standard-risk. After unblinding SKY92, 16 patients were re-assigned as high-risk by the physician, and for 15 of them treatment strategy was impacted, resulting in an escalated treatment plan. For the 73 (50%) clinical high-risk patients, SKY92 indicated 46 patients to be standard-risk; for 31 of these patients the treatment strategy was impacted consistent with a de-escalation of risk. Overall, SKY92 impacted treatment decisions in 37% of patients (p < 0.001). For clinical decision-making, physicians incorporated SKY92, and the final assigned clinical risk was in line with SKY92 for 89% of patients. Furthermore, SKY92 significantly increased the confidence of the physicians' treatment decisions (p < 0.001). This study shows potential added value of SKY92 in MM for treatment decision making.

Whole-genome optical mapping of bone-marrow myeloma cells reveals association of extramedullary multiple myeloma with chromosome 1 abnormalities

Extramedullary disease (EMM) represents a rare, aggressive and mostly resistant phenotype of multiple myeloma (MM). EMM is frequently associated with high-risk cytogenetics, but their complex genomic architecture is largely unexplored. We used whole-genome optical mapping (Saphyr, Bionano Genomics) to analyse the genomic architecture of CD138+ cells isolated from bone-marrow aspirates from an unselected cohort of newly diagnosed patients with EMM (n = 4) and intramedullary MM (n = 7). Large intrachromosomal rearrangements (> 5 Mbp) within chromosome 1 were detected in all EMM samples. These rearrangements, predominantly deletions with/without inversions, encompassed hundreds of genes and led to changes in the gene copy number on large regions of chromosome 1. Compared with intramedullary MM, EMM was characterised by more deletions (size range of 500 bp–50 kbp) and fewer interchromosomal translocations, and two EMM samples had copy number loss in the 17p13 region. Widespread genomic heterogeneity and novel aberrations in the high-risk IGH/IGK/IGL, 8q24 and 13q14 regions were detected in individual patients but were not specific to EMM/MM. Our pilot study revealed an association of chromosome 1 abnormalities in bone marrow myeloma cells with extramedullary progression. Optical mapping showed the potential for refining the complex genomic architecture in MM and its phenotypes.

Next-Generation Biomarkers in Multiple Myeloma: Understanding the Molecular Basis for Potential Use in Diagnosis and Prognosis

Multiple myeloma (MM) is considered to be the second most common blood malignancy and it is characterized by abnormal proliferation and an accumulation of malignant plasma cells in the bone marrow. Although the currently utilized markers in the diagnosis and assessment of MM are showing promising results, the incidence and mortality rate of the disease are still high. Therefore, exploring and developing better diagnostic or prognostic biomarkers have drawn global interest. In the present review, we highlight some of the recently reported and investigated novel biomarkers that have great potentials as diagnostic and/or prognostic tools in MM. These biomarkers include angiogenic markers, miRNAs as well as proteomic and immunological biomarkers. Moreover, we present some of the advanced methodologies that could be utilized in the early and competent diagnosis of MM. The present review also focuses on understanding the molecular concepts and pathways involved in these biomarkers in order to validate and efficiently utilize them. The present review may also help in identifying areas of improvement for better diagnosis and superior outcomes of MM.

Management of patients with difficult-to-treat multiple myeloma

Newer treatments for multiple myeloma (MM) have improved response rates and survival for many patients. However, MM remains challenging to treat due to the propensity for multiple relapses, cumulative and emergent toxicities from prior therapies and increasing genomic complexity that arises due to clonal evolution. In particular, patients with relapsed/refractory MM often require increased complexity of treatment, yet still experience poorer outcomes compared with patients who are newly diagnosed. Additionally, several patient subgroups, including those with extramedullary disease and patients who are frail and/or have multiple comorbidities, have an unfavorable prognosis and remain undertreated. This review (based on an Updates-in-Hematology session at the 25th European Hematology Association Annual Congress 2020) discusses the management of these difficult-to-treat patients with MM.

A prognostic survival model based on metabolism-related gene expression in plasma cell myeloma

Accurate survival prediction of persons with plasma cell myeloma (PCM) is challenging. We interrogated clinical and laboratory co-variates and RNA matrices of 1040 subjects with PCM from public datasets in the Gene Expression Omnibus database in training (N = 1) and validation (N = 2) datasets. Genes regulating plasma cell metabolism correlated with survival were identified and seven used to build a metabolic risk score using Lasso Cox regression analyses. The score had robust predictive performance with 5-year survival area under the curve (AUCs): 0.71 (95% confidence interval, 0.65, 0.76), 0.88 (0.67, 1.00) and 0.64 (0.57, 0.70). Subjects in the high-risk training cohort (score > median) had worse 5-year survival compared with those in the low-risk cohort (62% [55, 68%] vs. 85% [80, 90%]; p < 0.001). This was also so for the validation cohorts. A nomogram combining metabolic risk score with Revised International Staging System (R-ISS) score increased survival prediction from an AUC = 0.63 [0.58, 0.69] to an AUC = 0.73 [0.66, 0.78]; p = 0.015. Modelling predictions were confirmed in in vitro tests with PCM cell lines. Our metabolic risk score increases survival prediction accuracy in PCM.

What Is New in the Treatment of Smoldering Multiple Myeloma?

Smoldering multiple myeloma (SMM), an asymptomatic plasma cell neoplasm, is currently diagnosed according to the updated IMWG criteria, which reflect an intermediate tumor mass between monoclonal gammopathy of undetermined significance (MGUS) and active MM. However, SMM is a heterogeneous entity and individual case may go from an "MGUS-like" behavior to "early MM" with rapid transformation into symptomatic disease. This wide range of clinical outcomes poses challenges for prognostication and management of individual patients. However, initial studies showed a benefit in terms of progression or even survival for early treatment of high-risk SMM patients. While outside of clinical trials the conventional approach to SMM generally remains that of close observation, these studies raised the question of whether early treatment should be offered in high-risk patients, prompting evaluation of several different therapeutic approaches with different goals. While delay of progression to MM with a non-toxic treatment is clearly achievable by early treatment, a convincing survival benefit still needs to be proven by independent studies. Furthermore, if SMM is to be considered less biologically complex than MM, early treatment may offer the chance of cure that is currently not within reach of any active MM treatment. In this paper, we present updated results of completed or ongoing clinical trials in SMM treatment, highlighting areas of uncertainty and critical issues that will need to be addressed in the near future before the "watch and wait" paradigm in SMM is abandoned in favor of early treatment.

The molecular pathogenesis of multiple myeloma

Multiple Myeloma (MM) is characterized by uncontrolled proliferation and accumulation of clonal plasma cells within the bone marrow. However, the cell of origin is a B-lymphocyte acquiring aberrant genomic events in the germinal center of a lymph node as off-target events during somatichypermutation and class-switch recombination driven by activation-induced-deaminase. Whether pre-germinal center events are also required for transformation, and which additional events are required for disease progression is still matter of debate. As early treatment in asymptomatic phases is gaining traction in the clinic, a better understanding of the molecular pathogenesis of myeloma progression would allow stratification of patients based on their risk of progression, thus rationalizing efficacy and cost of clinical interventions. In this review, we will discuss the development of MM, from the cell of origin through asymptomatic stages such as monoclonal gammopathy of undetermined significance and smoldering MM, to the development of symptomatic disease. We will explain the genetic heterogeneity of MM, one of the major drivers of disease recurrence. In this context, moreover, we will propose how this knowledge may influence future diagnostic and therapeutic interventions.

A Journey Through Myeloma Evolution: From the Normal Plasma Cell to Disease Complexity

The knowledge of cancer origin and the subsequent tracking of disease evolution represent unmet needs that will soon be within clinical reach. This will provide the opportunity to improve patient's stratification and to personalize treatments based on cancer biology along its life history. In this review, we focus on the molecular pathogenesis of multiple myeloma (MM), a hematologic malignancy with a well-known multi-stage disease course, where such approach can sooner translate into a clinical benefit. We describe novel insights into modes and timing of disease initiation. We dissect the biology of the preclinical and pre-malignant phases, elucidating how knowledge of the genomics of the disease and the composition of the microenvironment allow stratification of patients based on risk of disease progression. Then, we explore cell-intrinsic and cell-extrinsic drivers of MM evolution to symptomatic disease. Finally, we discuss how this may relate to the development of refractory disease after treatment. By integrating an evolutionary view of myeloma biology with the recent acquisitions on its clonal heterogeneity, we envision a way to drive the clinical management of the disease based on its detailed biological features more than surrogates of disease burden.

Application of Next-Generation Sequencing for the Genomic Characterization of Patients with Smoldering Myeloma

Genomic analysis could contribute to a better understanding of the biological determinants of the evolution of multiple myeloma (MM) precursor disease and an improved definition of high-risk patients. To assess the feasibility and value of next-generation sequencing approaches in an asymptomatic setting, we performed a targeted gene mutation analysis and a genome-wide assessment of copy number alterations (CNAs) by ultra-low-pass whole genome sequencing (ULP-WGS) in six patients with monoclonal gammopathy of undetermined significance and 25 patients with smoldering MM (SMM). Our comprehensive genomic characterization highlighted heterogeneous but substantial values of the tumor fraction, especially in SMM; a rather high degree of genomic complexity, in terms of both mutations and CNAs, and inter-patient variability; a higher incidence of gene mutations and CNAs in SMM, confirming ongoing evolution; intraclonal heterogeneity; and instances of convergent evolution. ULP-WGS of these patients proved effective in revealing the marked genome-wide level of their CNAs, most of which are not routinely investigated. Finally, the analysis of our small SMM cohort suggested that chr(8p) deletions, the DNA tumor fraction, and the number of alterations may have clinical relevance in the progression to overt MM. Although validation in larger series is mandatory, these findings highlight the promising impact of genomic approaches in the clinical management of SMM.

The significance of prognostic profiling in the treatment of patients with multiple myeloma

Multiple myeloma (MM) is a hematological neoplasia characterized by clonal expansion of the most mature B lymphocytes, plasma cells (Plc), in the bone marrow (BM). Due to new treatment modalities, the 5-years survival has improved in the last 15 years, and nowdays ranges from 60-70%. The individual prognostic profile is based on the biological characteristics of the disease, clinical characteristics of patients and therapeutics response characteristics. The biological characteristics of the disease are defined by the clinical stage according to the Durie-Salmon classification and prognostic indices such the international staging system (ISS) and revised ISS (R-ISS). Numerous different mutations of prognostic significance have been discovered applying methods of molecular genetics such as next generation sequencing (NGS). The age and comorbity status of patients are the most important clinical characteristics because they are crucial for therapeutic choice and suitability for treatment with high-dose chemotherapy and autologous stem cell transplantation. The prognostic influence of therapeutic response is very important and the most powerful prognostic factors are achievements of complete remission (CR) and minimal residual disease (MRD) negativity.