Mutational Spectrum, Copy Number Changes, and Outcome: Results of a Sequencing Study of Patients With Newly Diagnosed Myeloma

Linked-read whole-genome sequencing resolves common and private structural variants in multiple myeloma

Linked-read WGS can be performed without DNA purification and allows for resolution of the diverse structural variants found in MM.

Linked-read WGS can, as a standalone assay, provide comprehensive genetics in myeloma and other diseases with complex genomes.

Multiple myeloma (MM) is an incurable and aggressive plasma cell malignancy characterized by a complex karyotype with multiple structural variants (SVs) and copy-number variations (CNVs). Linked-read whole-genome sequencing (lrWGS) allows for refined detection and reconstruction of SVs by providing long-range genetic information from standard short-read sequencing. This makes lrWGS an attractive solution for capturing the full genomic complexity of MM. Here we show that high-quality lrWGS data can be generated from low numbers of cells subjected to fluorescence-activated cell sorting (FACS) without DNA purification. Using this protocol, we analyzed MM cells after FACS from 37 patients with MM using lrWGS. We found high concordance between lrWGS and fluorescence in situ hybridization (FISH) for the detection of recurrent translocations and CNVs. Outside of the regions investigated by FISH, we identified >150 additional SVs and CNVs across the cohort. Analysis of the lrWGS data allowed for resolution of the structure of diverse SVs affecting the MYC and t(11;14) loci, causing the duplication of genes and gene regulatory elements. In addition, we identified private SVs causing the dysregulation of genes recurrently involved in translocations with the IGH locus and show that these can alter the molecular classification of MM. Overall, we conclude that lrWGS allows for the detection of aberrations critical for MM prognostics and provides a feasible route for providing comprehensive genetics. Implementing lrWGS could provide more accurate clinical prognostics, facilitate genomic medicine initiatives, and greatly improve the stratification of patients included in clinical trials.

Pathogenesis and treatment of multiple myeloma

Multiple myeloma (MM) is the second‐ranking malignancy in hematological tumors. The pathogenesis of MM is complex with high heterogeneity, and the development of the disease is a multistep process. Chromosomal translocations, aneuploidy, genetic mutations, and epigenetic aberrations are essential in disease initiation and progression. The correlation between MM cells and the bone marrow microenvironment is associated with the survival, progression, migration, and drug resistance of MM cells. In recent decades, there has been a significant change in the paradigm for the management of MM. With the development of proteasome inhibitors, immunomodulatory drugs, monoclonal antibodies, chimeric antigen receptor T‐cell therapies, and novel agents, the survival of MM patients has been significantly improved. In addition, nanotechnology acts as both a nanocarrier and a treatment tool for MM. The properties and responsive conditions of nanomedicine can be tailored to reach different goals. Nanomedicine with a precise targeting property has offered great potential for drug delivery and assisted in tumor immunotherapy. In this review, we summarize the pathogenesis and current treatment options of MM, then overview recent advances in nanomedicine‐based systems, aiming to provide more insights into the treatment of MM.

High-risk disease in newly diagnosed multiple myeloma: beyond the R-ISS and IMWG definitions

Multiple myeloma (MM) is an acquired malignant plasma cell disorder that develops late in life. Although progression free and overall survival has improved across all age, race, and ethnic groups, a subset of patients have suboptimal outcomes and are labeled as having high risk disease. A uniform approach to risk in NDMM remains elusive despite several validated risk stratification systems in clinical use. While we attempt to capture risk at diagnosis, the reality is that many important prognostic characteristics remain ill-defined as some patients relapse early who were defined as low risk based on their genomic profile at diagnosis. It is critical to establish a definition of high risk disease in order to move towards risk-adapted treatment approaches. Defining risk at diagnosis is important to both effectively design future clinical trials and guide which clinical data is needed in routine practice. The goal of this review paper is to summarize and compare the various established risk stratification systems, go beyond the R-ISS and international myeloma working group risk stratifications to evaluate specific molecular and cytogenetic abnormalities and how they impact prognosis independently. In addition, we explore the wealth of new genomic information from recent whole genome/exome sequencing as well as gene expression data and review known clinical factors affecting outcome such as disease burden and early relapse as well as patient related factors such as race. Finally, we provide an outlook on developing a new high risk model system and how we might make sense of co-occurrences, oncogenic dependencies, and mutually exclusive mutations.

Structural variants shape the genomic landscape and clinical outcome of multiple myeloma

Deciphering genomic architecture is key to identifying novel disease drivers and understanding the mechanisms underlying myeloma initiation and progression. In this work, using the CoMMpass dataset, we show that structural variants (SV) occur in a nonrandom fashion throughout the genome with an increased frequency in the t(4;14), RB1, or TP53 mutated cases and reduced frequency in t(11;14) cases. By mapping sites of chromosomal rearrangements to topologically associated domains and identifying significantly upregulated genes by RNAseq we identify both predicted and novel putative driver genes. These data highlight the heterogeneity of transcriptional dysregulation occurring as a consequence of both the canonical and novel structural variants. Further, it shows that the complex rearrangements chromoplexy, chromothripsis and templated insertions are common in MM with each variant having its own distinct frequency and impact on clinical outcome. Chromothripsis is associated with a significant independent negative impact on clinical outcome in newly diagnosed cases consistent with its use alongside other clinical and genetic risk factors to identify prognosis.

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

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

The Role of DNA Repair in Genomic Instability of Multiple Myeloma

Multiple Myeloma (MM) is a B cell malignancy marked by genomic instability that arises both through pathogenesis and during disease progression. Despite recent advances in therapy, MM remains incurable. Recently, it has been reported that DNA repair can influence genomic changes and drug resistance in MM. The dysregulation of DNA repair function may provide an alternative explanation for genomic instability observed in MM cells and in cells derived from MM patients. This review provides an overview of DNA repair pathways with a special focus on their involvement in MM and discusses the role they play in MM progression and drug resistance. This review highlights how unrepaired DNA damage due to aberrant DNA repair response in MM exacerbates genomic instability and chromosomal abnormalities, enabling MM progression and drug resistance.

Capture Rate of V(D)J Sequencing for Minimal Residual Disease Detection in Multiple Myeloma

PURPOSE

Minimal residual disease (MRD) negativity is a strong predictor for outcome in multiple myeloma. To assess V(D)J clonotype capture using the updated Adaptive next-generation sequencing (NGS) MRD assay in a clinical setting, we analyzed baseline and follow-up samples from patients with multiple myeloma who achieved deep clinical responses.

EXPERIMENTAL DESIGN

A total of 159 baseline and 31 follow-up samples from patients with multiple myeloma were sequenced using the NGS MRD assay. Baseline samples were also sequenced using a targeted multiple myeloma panel (myTYPE). We estimated ORs with 95% confidence intervals (CI) for clonotypes detection using logistic regression.

RESULTS

The V(D)J clonotype capture rate was 93% in baseline samples with detectable genomic aberrations, indicating presence of tumor DNA, assessed through myTYPE. myTYPE-positive samples had significantly higher V(D)J clonotype detection rates in univariate (OR, 7.3; 95% CI, 2.8-22.6) and multivariate analysis (OR, 4.4; 95% CI, 1.4-16.9; P = 0.016). Higher disease burden was associated with higher probability of V(D)J clonotype capture, meanwhile no such association was found for age, gender, or type of heavy or light immunoglobulin chain. All V(D)J clonotypes detected at baseline were detected in MRD-positive samples indicating that the V(D)J clonotypes remained stable and did not undergo further rearrangements during follow-up. Of the 31 posttreatment samples, 12 were MRD-negative using the NGS MRD assay.

CONCLUSIONS

NGS for V(D)J rearrangements in multiple myeloma offers a reliable and sensitive method for MRD tracking with high detection rates in the clinical setting.

Multiple myeloma with high-risk cytogenetics and its treatment approach

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

Racial and ethnic differences in clonal hematopoiesis, tumor markers, and outcomes of patients with multiple myeloma

Age of onset and survival disparities exist for racial and ethnic minority patients diagnosed with MM.

Differences in somatic mutations in tumor and blood (ie, clonal hematopoiesis) may contribute to disparities in outcomes observed.

Multiple myeloma (MM) incidence, mortality, and survival vary by race and ethnicity, but the causes of differences remain unclear. We investigated demographic, clinical, and molecular features of diverse MM patients to elucidate mechanisms driving clinical disparities. This study included 495 MM patients (self-reported Hispanic, n = 45; non-Hispanic Black, n = 52; non-Hispanic White, n = 398). Hispanic and non-Hispanic Black individuals had an earlier age of onset than non-Hispanic White individuals (53 and 57 vs 63 years, respectively, P < .001). There were no differences in treatment by race and ethnicity groups, but non-Hispanic Black patients had a longer time to hematopoietic cell transplant than non-Hispanic White patients (376 days vs 248 days; P = .01). Overall survival (OS) was improved for non-Hispanic Black compared with non-Hispanic White patients (HR, 0.50; 95% CI, 0.31-0.81; P = .005), although this association was attenuated after adjusting for clinical features (HR, 0.62; 95% CI, 0.37-1.03; P = .06). Tumor mutations in IRF4 were most common in Hispanic patients, and mutations in SP140, AUTS2, and SETD2 were most common in non-Hispanic Black patients. Differences in tumor expression of BCL7A, SPEF2, and ANKRD26 by race and ethnicity were observed. Clonal hematopoiesis was detected in 12% of patients and associated with inferior OS in non-Hispanic Black patients compared with patients without clonal hematopoiesis (HR, 4.36; 95% CI, 1.36-14.00). This study provides insight into differences in molecular features that may drive clinical disparities in MM patients receiving comparable treatment, with the novel inclusion of Hispanic individuals.

Signaling Pathway and Small-Molecule Drug Discovery of FGFR: A Comprehensive Review

Targeted therapy is a groundbreaking innovation for cancer treatment. Among the receptor tyrosine kinases, the fibroblast growth factor receptors (FGFRs) garnered substantial attention as promising therapeutic targets due to their fundamental biological functions and frequently observed abnormality in tumors. In the past 2 decades, several generations of FGFR kinase inhibitors have been developed. This review starts by introducing the biological basis of FGF/FGFR signaling. It then gives a detailed description of different types of small-molecule FGFR inhibitors according to modes of action, followed by a systematic overview of small-molecule-based therapies of different modalities. It ends with our perspectives for the development of novel FGFR inhibitors.

Clinicopathologic and Genetic Features of Primary T-cell Lymphomas of the Central Nervous System: An Analysis of 11 Cases Using Targeted Gene Sequencing

Primary central nervous system lymphoma (PCNSL) of peripheral T-cell lineage (T-PCNSL) is rare, and its genetic and clinicopathologic features remain unclear. Here, we present 11 cases of T-PCNSL in immunocompetent individuals from a single institute, focusing on their genetic alterations. Seven cases were subject to targeted panel sequencing covering 120 lymphoma-related genes. Nine of the eleven cases were classified as peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS), of which one was of γδT-cell lineage. There was one case of anaplastic lymphoma kinase-positive anaplastic large cell lymphoma and another of extranodal natural killer (NK)/T-cell lymphoma (ENKTL) of αβT-cell lineage. The male to female ratio was 7 : 4 and the age ranged from 3 to 75 years (median, 61 y). Most patients presented with neurological deficits (n=10) and showed multifocal lesions (n=9) and deep brain structure involvement (n=9). Tumor cells were mostly small-to-medium, and T-cell monoclonality was detected in all nine evaluated cases. PTCL-NOS was CD4-positive (n=4), CD8-positive (n=3), mixed CD4-positive and CD8-positive (n=1), or CD4/CD8-double-negative (n=1, γδT-cell type). Cytotoxic molecule expression was observed in 4 (67%) of the 6 evaluated cases. Pathogenic alterations were found in 4 patients: one PTCL-NOS case had a frameshift mutation in KMT2C, another PTCL-NOS case harbored a truncating mutation in TET2, and another (γδT-cell-PTCL-NOS) harbored NRAS G12S and JAK3 M511I mutations, and homozygous deletions of CDKN2A and CDKN2B. The ENKTL (αβT-cell lineage) case harbored mutations in genes ARID1B, FAS, TP53, BCOR, KMT2C, POT1, and PRDM1. In conclusion, most of the T-PCNSL were PTCL-NOS, but sporadic cases of other subtypes including γδT-cell lymphoma, anaplastic lymphoma kinase-positive anaplastic large cell lymphoma, and ENKTL were also encountered. Immunophenotypic analysis, clonality test, and targeted gene sequencing along with clinicoradiologic evaluation, may be helpful for establishing the diagnosis of T-PCNSL. Moreover, this study demonstrates genetic alterations with potential diagnostic and therapeutic utility in T-PCNSL.

Amp 1q21 is more predictable with dismal survival than gain 1q21 of newly diagnosed multiple myeloma in real-world analysis

Introduction

The gain/amplification (amp) of 1q21 is one of the most common high‐risk chromosome abnormality (HRCA) in multiple myeloma (MM). The prognostic value of 1q21+ remains to be controversial on the status of gain or amp and the combination of other HRCAs.

Methods

In this retrospective study, we included 318 newly diagnosed MM (NDMM) patients who had fluorescence in situ hybridization (FISH) data and treated with novel agents in our department.

Results

Our study noted MM patients with amp 1q21 were more likely accompanied with t(4;14), t(14;16), and t(14;20). Patients with amp 1q21 presented with elder age, advanced Revised International Staging System (R‐ISS) stages, anemia, and more plasma cells in bone marrow compared to patients with gain 1q21 alone and no 1q21+. Moreover, amp 1q21 alone correlated with shorter progression‐free survival (PFS) (22.8m vs. 40.5m vs. 39.6m) and overall survival (OS) (45.2m vs. NA vs. 83.5m) compared with gain 1q21 alone and no FISH abnormalities. Although the high ratio of proteasome inhibitor and immunomodulatory drugs used in patients with amp 1q21, the overall response (ORR) was the lowest compared with no 1q21+ and gain 1q21. Multivariate analysis defined amp 1q21 as an independent prognostic marker for NDMM patients, rather than gain 1q21.

Conclusion

The amp 1q21 predict inferior treatment response and survival, especially coexisted with high‐risk IgH translocation.

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.

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.

Clinical Significance of Circulating Cell-Free DNA Detection in Multiple Myeloma: A Meta-Analysis

Circulating cell-free DNA (cfDNA) detection, a non-invasive method, appears promising for genetic analyses as well as quantitative assessment of tumor burden in patients with cancer. Although the analysis of cfDNA for clinical prognosis and monitoring disease burden in multiple myeloma (MM) has been recently studied, the results are unclear. In this meta-analysis, we explored the clinical significance of circulating cfDNA detection in patients with MM. We searched PubMed, Embase, and the Cochrane Library for eligible studies published up until July 25, 2021. Diagnostic accuracy variables were calculated and analyzed using Meta-Disc, and prognostic data were analyzed using Review Manager. Overall, seven studies comprising 235 myeloma patients met our inclusion criteria. The overall sensitivity and specificity of cfDNA to detect minimal residual disease (MRD) were 0.58 and 0.91, respectively. Moreover, higher levels of cfDNA were associated with worse progression-free survival as well as with poor overall survival. Our meta-analysis revealed that ctDNA detection has an obvious advantage in terms of MRD detection specificity, but it showed no superiority over bone marrow assessment in terms of MRD detection sensitivity, and higher levels of cfDNA were indicative of worse prognosis in patients with MM. cfDNA detection is a non-invasive method and thus shows promise as a good alternative to BM biopsies for monitoring clonal evolution and tumor burden so as to guide the treatment of patients with MM.

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

Simple Summary

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

Abstract

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

Deciphering spatial genomic heterogeneity at a single cell resolution in multiple myeloma

Osteolytic lesions (OL) characterize symptomatic multiple myeloma. The mechanisms of how malignant plasma cells (PC) cause OL in one region while others show no signs of bone destruction despite subtotal infiltration remain unknown. We report on a single-cell RNA sequencing (scRNA-seq) study of PC obtained prospectively from random bone marrow aspirates (BM) and paired imaging-guided biopsies of OL. We analyze 148,630 PC from 24 different locations in 10 patients and observe vast inter- and intra-patient heterogeneity based on scRNA-seq analyses. Beyond the limited evidence for spatial heterogeneity from whole-exome sequencing, we find an additional layer of complexity by integrated analysis of anchored scRNA-seq datasets from the BM and OL. PC from OL are characterized by differentially expressed genes compared to PC from BM, including upregulation of genes associated with myeloma bone disease like DKK1, HGF and TIMP-1 as well as recurrent downregulation of JUN/FOS, DUSP1 and HBB. Assessment of PC from longitudinally collected samples reveals transcriptional changes after induction therapy. Our study contributes to the understanding of destructive myeloma bone disease.

Pathogenic signaling in multiple myeloma

Multiple myeloma is a common hematological malignancy of plasma cells, the terminally differentiated B cells that secrete antibodies as part of the adaptive immune response. Significant progress has been made in treating multiple myeloma, but this disease remains largely incurable, and most patients will eventually suffer a relapse of disease that becomes refractory to further therapies. Moreover, a portion of patients with multiple myeloma present with disease that is refractory to all treatments from the initial diagnosis, and no current therapeutic approaches can help. Therefore, the task remains to advance new therapeutic strategies to help these vulnerable patients. One strategy to meet this challenge is to unravel the complex web of pathogenic signaling pathways in malignant plasma cells and use this information to design novel precision medicine strategies to assist these patients most at risk.

Genomic characterization of functional high-risk multiple myeloma patients

Multiple myeloma (MM) patients with suboptimal response to induction therapy or early relapse, classified as the functional high-risk (FHR) patients, have been shown to have poor outcomes. We evaluated newly-diagnosed MM patients in the CoMMpass dataset and divided them into three groups: genomic high-risk (GHR) group for patients with t(4;14) or t(14;16) or complete loss of functional TP53 (bi-allelic deletion of TP53 or mono-allelic deletion of 17p13 (del17p13) and TP53 mutation) or 1q21 gain and International Staging System (ISS) stage 3; FHR group for patients who had no markers of GHR group but were refractory to induction therapy or had early relapse within 12 months; and standard-risk (SR) group for patients who did not fulfill any of the criteria for GHR or FHR. FHR patients had the worst survival. FHR patients are characterized by increased mutations affecting the IL-6/JAK/STAT3 pathway, and a gene expression profile associated with aberrant mitosis and DNA damage response. This is also corroborated by the association with the mutational signature associated with abnormal DNA damage response. We have also developed a machine learning based classifier that can identify most of these patients at diagnosis.

KRAS and RAS-MAPK Pathway Deregulation in Mature B Cell Lymphoproliferative Disorders

KRAS mutations account for the most frequent mutations in human cancers, and are generally correlated with disease aggressiveness, poor prognosis, and poor response to therapies. KRAS is required for adult hematopoiesis and plays a key role in B cell development and mature B cell proliferation and survival, proved to be critical for B cell receptor-induced ERK pathway activation. In mature B cell neoplasms, commonly seen in adults, KRAS and RAS-MAPK pathway aberrations occur in a relevant fraction of patients, reaching high recurrence in some specific subtypes like multiple myeloma and hairy cell leukemia. As inhibitors targeting the RAS-MAPK pathway are being developed and improved, it is of outmost importance to precisely identify all subgroups of patients that could potentially benefit from their use. Herein, we review the role of KRAS and RAS-MAPK signaling in malignant hematopoiesis, focusing on mature B cell lymphoproliferative disorders. We discuss KRAS and RAS-MAPK pathway aberrations describing type, incidence, mutual exclusion with other genetic abnormalities, and association with prognosis. We review the current therapeutic strategies applied in mature B cell neoplasms to counteract RAS-MAPK signaling in pre-clinical and clinical studies, including most promising combination therapies. We finally present an overview of genetically engineered mouse models bearing KRAS and RAS-MAPK pathway aberrations in the hematopoietic compartment, which are valuable tools in the understanding of cancer biology and etiology.

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.

Plasma cell myeloma: role of histopathology, immunophenotyping, and genetic testing

Myeloma is a malignant neoplasm of plasma cells with complex pathogenesis. Diagnosis and risk stratification require the integration of histology, radiology, serology, and genetic data. Bone marrow biopsies are essential for myeloma diagnosis by providing material for histologic and cytologic assessment as well as immunophenotypic and genetic studies. Flow cytometry and genetic studies are, in particular, becoming increasingly important for diagnosis, risk stratification, and assessment of treatment response. Myeloma has traditionally been characterized by recurrent cytogenetic abnormalities that can be divided into two subtypes: hyperdiploid, characterized by trisomies, and non-hyperdiploid, characterized by translocations involving chromosome 14. These abnormalities are thought to be primary events, initiating a premalignant state, which progresses to myeloma through the acquisition of secondary mutations. The emergence of next-generation sequencing has led to the discovery of numerous mutations and gene fusions that comprise the heterogenous genomic landscape of myeloma. As the underlying pathogenesis of myeloma continues to be delineated, possible therapeutic targets have also emerged. Herein, we describe the importance of histology, immunophenotype, and mutational analysis in the assessment of myeloma.

Machine learning and graph neural network for finding potential drugs related to multiple myeloma

An innovative voting mechanism for virtual drug screening.

Diagnosis and treatment of hairy cell leukemia as the COVID-19 pandemic continues

Hairy cell leukemia (HCL) is an indolent B-cell malignancy, usually driven by the BRAF V600E mutation. For 30 years, untreated and relapsed HCL was successfully treated with purine analogs, but minimal residual disease (MRD) remained in most patients, eventually causing relapse. Repeated purine analogs achieve decreasing efficacy and increasing toxicity, particularly to normal T-cells. MRD-free complete remissions (CRs) are more common using rituximab with purine analogs in both 1^st-line and relapsed settings. BRAF inhibitors and Ibrutinib can achieve remission, but due to persistence of MRD, must be used chronically to prevent relapse. BRAF inhibition combined with Rituximab can achieve high MRD-free CR rates. Anti-CD22 recombinant immunotoxin moxetumomab pasudotox is FDA-approved in the relapsed setting and is unique in achieving high MRD-free CR rates as a single-agent. Avoiding chemotherapy and rituximab may be important in ensuring both recovery from COVID-19 and successful COVID-19 vaccination, an area of continued investigation.

Comparison of Clinical Characteristics and Genetic Aberrations of Plasma Cell Disorders in Thailand Population

Multiple myeloma is an incurable malignancy of plasma cells resulting from impaired terminal B cell development. Almost all patients with multiple myeloma eventually have a relapse. Many studies have demonstrated the importance of the various genomic mutations that characterize multiple myeloma as a complex heterogeneous disease. In recent years, next-generation sequencing has been used to identify the genomic mutation landscape and clonal heterogeneity of multiple myeloma. This is the first study, a prospective observational study, to identify somatic mutations in plasma cell disorders in the Thai population using targeted next-generation sequencing. Twenty-seven patients with plasma cell disorders were enrolled comprising 17 cases of newly diagnosed multiple myeloma, 5 cases of relapsed/refractory multiple myeloma, and 5 cases of other plasma cell disorders. The pathogenic mutations were found in 17 of 27 patients. Seventy percent of those who had a mutation (12/17 patients) habored a single mutation, whereas the others had more than one mutation. Fifteen pathogenic mutation genes were identified: ATM, BRAF, CYLD, DIS3, DNMT3A, FBXW7, FLT3, GNA13, IRF4, KMT2A, NRAS, SAMHD1, TENT5C, TP53, and TRAF3. Most have previously been reported to be involved in the RAS/MAPK pathway, the nuclear factor kappa B pathway, the DNA-repair pathway, the CRBN pathway, tumor suppressor gene mutation, or an epigenetic mutation. However, the current study also identified mutations that had not been reported to be related to myeloma: GNA13 and FBXW7. Therefore, a deep understanding of molecular genomics would inevitably improve the clinical management of plasma cell disorder patients, and the increased knowledge would ultimately result in better outcomes for the patients.

Exonic variants in multiple myeloma patients associated with relapsed/ refractory and response to bortezomib regimens

Novel treatment in multiple myeloma represented by proteasome inhibitors, immunomodulatory drugs and monoclonal antibodies have produced a deep response. However, relapses are possible, and all classes of drugs are refractory to patients. Next-generation sequencing has improved our understanding of the multiple myeloma genome related to drug resistance and has discovered many genomic variants. Therefore, this study was conducted to investigate new variants associated with drug resistance in MM patients who relapsed and refractory to bortezomib regimen and daratumumab treatment using next-generation sequencing for whole-exome sequencing. Peripheral blood samples were collected in EDTA tubes from six patients; four were in relapsed and refractory to bortezomib regimens and daratumumab; two patients responded to bortezomib regimens. Whole-exome sequencing was performed by the MGI-DNBSEQ-G400 instrument. We identified 21 variants in multiple myeloma patients. Seventeen variants were found in relapsed and refractory multiple myeloma in 11 genes (GNAQ, PMS1, CREB1, NSUNS2, PIK3CG, ROS1, PMS2, FIT4, KDM5A, STK11 and ZFHX3). And four variants were identified in two patients with response to bortezomib regimens in 4 genes (RAF1, CREB1, ZFHX3 and INSR). We have observed several genetic variants in many genes that may have been associated with the poor prognosis and poor response to treatment in these patients. These values should be further confirmed in large sample studies using the RNA-seq technique to identify genome expression.

Epidemiology, genetics and treatment of multiple myeloma and precursor diseases

Multiple myeloma (MM) is a hematological malignancy caused by the clonal expansion of plasma cells. The incidence of MM worldwide is increasing with greater than 140 000 people being diagnosed with MM per year. Whereas 5-year survival after a diagnosis of MM has improved from 28% in 1975 to 56% in 2012, the disease remains essentially incurable. In this review, we summarize our current understanding of MM including its epidemiology, genetics and biology. We will also provide an overview of MM management that has led to improvements in survival, including recent changes to diagnosis and therapies. Areas of unmet need include the management of patients with high-risk MM, those with reduced performance status and those refractory to standard therapies. Ongoing research into the biology and early detection of MM as well as the development of novel therapies, such as immunotherapies, has the potential to influence MM practice in the future.

Targeting mutated GTPase KRAS in tumor therapies

Kirsten rat sarcoma virus oncogene (KRAS) mutation accounts for approximately 85% of RAS-driven cancers, and participates in multiple signaling pathways and mediates cell proliferation, differentiation and metabolism. KRAS has been considered as an "undruggable" target due to the lack of effective direct inhibitors, although high frequency of KRAS mutations have been identified in multiple carcinomas in the past decades. Encouragingly, the KRAS^G12C inhibitor AMG510 (sotorasib), which has been approved for treating NSCLC and CRC recently, makes directly targeting KRAS the most promising strategy for cancer therapy. To better understand the current state of KRAS inhibitors, this review summarizes the biological functions of KRAS, the structure-activity relationship studies of the small-molecule inhibitors that directly target KRAS, and highlights the therapeutic agents with improved selectivity, bioavailability and physicochemical properties. Furthermore, the combined medication that can enhance efficacy and overcome drug resistance of KRAS covalent inhibitors is also reviewed.

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.

Patient similarity network of newly diagnosed multiple myeloma identifies patient subgroups with distinct genetic features and clinical implications

The remarkable genetic heterogeneity of multiple myeloma poses a substantial challenge for proper prognostication and clinical management of patients. Here, we introduce MM-PSN, the first multiomics patient similarity network of myeloma. MM-PSN enabled accurate dissection of the genetic and molecular landscape of the disease and determined 12 distinct subgroups defined by five data types generated from genomic and transcriptomic profiling of 655 patients. MM-PSN identified patient subgroups not previously described defined by specific patterns of alterations, enriched for specific gene vulnerabilities, and associated with potential therapeutic options. Our analysis revealed that co-occurrence of t(4;14) and 1q gain identified patients at significantly higher risk of relapse and shorter survival as compared to t(4;14) as a single lesion. Furthermore, our results show that 1q gain is the most important single lesion conferring high risk of relapse and that it can improve on the current International Staging Systems (ISS and R-ISS).

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.

Artificial Intelligence in Plasma Cell Myeloma: Neural Networks and Support Vector Machines in the Classification of Plasma Cell Myeloma Data at Diagnosis

Background:

Plasma cell neoplasm and/or plasma cell myeloma (PCM) is a mature B-cell lymphoproliferative neoplasm of plasma cells that secrete a single homogeneous immunoglobulin called paraprotein or M-protein. Plasma cells accumulate in the bone marrow (BM) leading to bone destruction and BM failure. Diagnosis of PCM is based on clinical, radiologic, and pathological characteristics. The percent of plasma cells by manual differential (bone marrow morphology), the white blood cell (WBC) count, cytogenetics, fluorescence in situ hybridization (FISH), microarray, and next-generation sequencing of BM are used in the risk stratification of newly diagnosed PCM patients. The genetics of PCM is highly complex and heterogeneous with several genetic subtypes that have different clinical outcomes. National Comprehensive Cancer Network guidelines recommend targeted FISH analysis of plasma cells with specific DNA probes to detect genetic abnormalities for the staging of PCM (4.2021). Recognition of risk categories through training software for classification of high-risk PCM and a novel way of addressing the current approaches through bioinformatics will be a significant step toward automation of PCM analysis.

Methods:

A new artificial neural network (ANN) classification model was developed and tested in Python programming language with a first data set of 301 cases and a second data set of 176 cases for a total of 477 cases of PCM at diagnosis. Classification model was also developed with support vector machines (SVM) algorithm in R studio and interactive data visuals using Tableau.

Results:

The resulting ANN algorithm had 94% accuracy for the first and second data sets with a classification summary of precision (PPV): 0.97, recall (sensitivity): 0.76, f1 score: 0.83, and accuracy of logistic regression of 1.0. SVM of plasma cells versus TP53 revealed a 95% accuracy level.

Conclusion:

A novel classification model based only on specific morphological and genetic variables was developed using a machine learning algorithm, the ANN. ANN identified an association of WBC and BM plasma cell percentage with two of the high-risk genetic categories in the diagnostic cases of PCM. With further training and testing of additional data sets that include morphologic and additional genetic rearrangements, the newly developed ANN model has the potential to develop an accurate classification of high-risk categories of PCM.

Multiple Myeloma: Molecular Pathogenesis and Disease Evolution

BACKGROUND

Multiple myeloma is the second most common hematologic malignancy, which to date remains incurable despite advances in treatment strategies including the use of novel substances such as proteasome inhibitors, immunomodulatory drugs, and monoclonal antibodies.

SUMMARY

The bone marrow-based disease is preceded by the 2 sequential premalignant conditions: monoclonal gammo-pathy of undetermined significance and smoldering myeloma. Plasma cell leukemia and extramedullary disease occur, when malignant clones lose their dependency on the bone marrow. Key genetic features of these plasma cell dyscrasias include chromosomal aberrations such as translocations and hyperdiploidy, which occur during error-prone physiologic processes in B-cell development. Next-generation sequencing studies have identified mutations in major oncogenic pathways and tumor suppressors, which contribute to the pathogenesis of multiple myeloma and have revealed insights into the clonal evolution of the disease, particularly along different lines of therapy. More recently, the importance of epigenetic alterations and the role of the bone marrow microenvironment, including immune and osteogenic cells, have become evident. Key Messages: We herein review the current knowledge of the pathogenesis of multiple myeloma, which is crucial for the development of novel targeted therapeutic strategies. These can contribute to the endeavor to make multiple myeloma a curable disease.

The Significance of mRNA in the Biology of Multiple Myeloma and Its Clinical Implications

Multiple myeloma (MM) is a genetically complex disease that results from a multistep transformation of normal to malignant plasma cells in the bone marrow. However, the molecular mechanisms responsible for the initiation and heterogeneous evolution of MM remain largely unknown. A fundamental step needed to understand the oncogenesis of MM and its response to therapy is the identification of driver mutations. The introduction of gene expression profiling (GEP) in MM is an important step in elucidating the molecular heterogeneity of MM and its clinical relevance. Since some mutations in myeloma occur in non-coding regions, studies based on the analysis of mRNA provide more comprehensive information on the oncogenic pathways and mechanisms relevant to MM biology. In this review, we discuss the role of gene expression profiling in understanding the biology of multiple myeloma together with the clinical manifestation of the disease, as well as its impact on treatment decisions and future directions.

How I Treat High-risk Multiple Myeloma

Survival of multiple myeloma (MM) has significantly improved over the last decade; however, a composed group of patients (15-20%), named high-risk (HR) MM, still experience reduced survival. Both tumor biology and suboptimal/absent responses to therapy may underlie HR definition and a clear uniform identification of risk factors is crucial for a proper management of these patients. In biologic-HRMM, MRD negativity attainment and sustain, inside and outside BM, should be the primary goal and therapy should be adapted in patients with frailty to reduce toxicity and improve quality of life. MM treatment has traditionally been tailored on age and more recently frailty or comorbidities, but very rarely on the biology of the disease, mainly because of the lack of a clear benefit derived from a specific drug/combination, inhomogeneity in HR definition and lack of data coming from prospective, properly designed clinical trials. Some attempts have been successfully made recently in this direction. In this review, we are discussing the current different definitions of HR and the need for a consensus, the results of available trials in HR patients and the way through risk-adapted treatment strategies. For this purpose, we are proposing several clinical cases of difficult-to-treat patients throughout different treatment phases.

Targeted therapy of multiple myeloma

Multiple myeloma (MM) is a malignant proliferative disease of monoclonal plasma cells (PCs) and is characterized by uncontrolled proliferation of PCs and excessive production of specific types of immunoglobulins. Since PCs are terminally differentiated B cells, the World Health Organization (WHO) classifies MM as lymphoproliferative B-cell disease. The incidence of MM is 6-7 cases per 100,000 people in the world every year and the second most common cancer in the blood system. Due to the effects of drug resistance and malignant regeneration of MM cells in the microenvironment, all current treatment methods can prolong both overall and symptom-free survival rates of patients with MM but cannot cure MM. Both basic and clinical studies have proven that targeted therapy leads to a clear and significant prolongation of the survival of patients with MM, but when the disease recurs again, resistance to the previous treatment will occur. Therefore, the discovery of new targets and treatment methods plays a vital role in the treatment of MM. This article introduces and summarizes targeted MM therapy, potential new targets, and future precision medicine in MM.

[Multiple myeloma from the pathologist's perspective]

BACKGROUND

Multiple myeloma (MM) is one of the most common hematological neoplasms and accounts for approximately 1% of human cancers.

OBJECTIVES

Description of current diagnostics and classification of MM and related plasma cell neoplasms from the pathology viewpoint.

MATERIALS AND METHODS

Current knowledge regarding pathology and genetics of MM is summarized and tissue-based diagnostics following international consensus classifications and the current S3 guideline are described.

RESULTS

MM and related neoplasms are composed of malignant plasma cells that secrete a monoclonal immunoglobulin, which is an important parameter of disease activity. MM shows a multistage development. Almost all cases are preceded by a clinically inapparent precursor lesion, monoclonal gammopathy of undetermined significance (MGUS), which can progress to smoldering myeloma with a higher tumor burden, but absence of organ damage. Systemic MM needs to be discerned from the localized forms, solitary osseous and primary extramedullary plasmacytoma. MM is genetically very heterogeneous and can be broadly subdivided into two cytogenetic groups, cases with primary IGH translocations and cases with hyperdiploidy. Intratumoral genetic heterogeneity is frequently pronounced and correlates with the size of focal lesions in imaging.

CONCLUSIONS

Diagnosis of plasma cell neoplasms is done according to the criteria of the International Myeloma Working Group (IWMG) and requires interdisciplinary evaluation of clinical, serological, pathological and radiological features. In addition to clinical parameters, molecular markers, especially cytogenetic aberrations, are of great prognostic relevance.

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.

Survival prediction and treatment optimization of multiple myeloma patients using machine-learning models based on clinical and gene expression data

Multiple myeloma (MM) remains mostly an incurable disease with a heterogeneous clinical evolution. Despite the availability of several prognostic scores, substantial room for improvement still exists. Promising results have been obtained by integrating clinical and biochemical data with gene expression profiling (GEP). In this report, we applied machine learning algorithms to MM clinical and RNAseq data collected by the CoMMpass consortium. We created a 50-variable random forests model (IAC-50) that could predict overall survival with high concordance between both training and validation sets (c-indexes, 0.818 and 0.780). This model included the following covariates: patient age, ISS stage, serum B2-microglobulin, first-line treatment, and the expression of 46 genes. Survival predictions for each patient considering the first line of treatment evidenced that those individuals treated with the best-predicted drug combination were significantly less likely to die than patients treated with other schemes. This was particularly important among patients treated with a triplet combination including bortezomib, an immunomodulatory drug (ImiD), and dexamethasone. Finally, the model showed a trend to retain its predictive value in patients with high-risk cytogenetics. In conclusion, we report a predictive model for MM survival based on the integration of clinical, biochemical, and gene expression data with machine learning tools.

RNA-Sequencing-Based Transcriptomic Score with Prognostic and Theranostic Values in Multiple Myeloma

Multiple myeloma (MM) is the second most frequent hematological cancer and is characterized by the clonal proliferation of malignant plasma cells. Genome-wide expression profiling (GEP) analysis with DNA microarrays has emerged as a powerful tool for biomedical research, generating a huge amount of data. Microarray analyses have improved our understanding of MM disease and have led to important clinical applications. In MM, GEP has been used to stratify patients, define risk, identify therapeutic targets, predict treatment response, and understand drug resistance. In this study, we built a gene risk score for 267 genes using RNA-seq data that demonstrated a prognostic value in two independent cohorts (n = 674 and n = 76) of newly diagnosed MM patients treated with high-dose Melphalan and autologous stem cell transplantation. High-risk patients were associated with the expression of genes involved in several major pathways implicated in MM pathophysiology, including interferon response, cell proliferation, hypoxia, IL-6 signaling pathway, stem cell genes, MYC, and epigenetic deregulation. The RNA-seq-based risk score was correlated with specific MM somatic mutation profiles and responses to targeted treatment including EZH2, MELK, TOPK/PBK, and Aurora kinase inhibitors, outlining potential utility for precision medicine strategies in MM.

Pan-cancer evaluation of gene expression and somatic alteration data for cancer prognosis prediction

BACKGROUND

Over the past decades, approaches for diagnosing and treating cancer have seen significant improvement. However, the variability of patient and tumor characteristics has limited progress on methods for prognosis prediction. The development of high-throughput omics technologies now provides multiple approaches for characterizing tumors. Although a large number of published studies have focused on integration of multi-omics data and use of pathway-level models for cancer prognosis prediction, there still exists a gap of knowledge regarding the prognostic landscape across multi-omics data for multiple cancer types using both gene-level and pathway-level predictors.

METHODS

In this study, we systematically evaluated three often available types of omics data (gene expression, copy number variation and somatic point mutation) covering both DNA-level and RNA-level features. We evaluated the landscape of predictive performance of these three omics modalities for 33 cancer types in the TCGA using a Lasso or Group Lasso-penalized Cox model and either gene or pathway level predictors.

RESULTS

We constructed the prognostic landscape using three types of omics data for 33 cancer types on both the gene and pathway levels. Based on this landscape, we found that predictive performance is cancer type dependent and we also highlighted the cancer types and omics modalities that support the most accurate prognostic models. In general, models estimated on gene expression data provide the best predictive performance on either gene or pathway level and adding copy number variation or somatic point mutation data to gene expression data does not improve predictive performance, with some exceptional cohorts including low grade glioma and thyroid cancer. In general, pathway-level models have better interpretative performance, higher stability and smaller model size across multiple cancer types and omics data types relative to gene-level models.

CONCLUSIONS

Based on this landscape and comprehensively comparison, models estimated on gene expression data provide the best predictive performance on either gene or pathway level. Pathway-level models have better interpretative performance, higher stability and smaller model size relative to gene-level models.

From Bench to Bedside: The Evolution of Genomics and Its Implications for the Current and Future Management of Multiple Myeloma

ABSTRACT

The summation of 20 years of biological studies and the comprehensive analysis of more than 1000 multiple myeloma genomes with data linked to clinical outcome has enabled an increased understanding of the pathogenesis of multiple myeloma in the context of normal plasma cell biology. This novel data have facilitated the identification of prognostic markers and targets suitable for therapeutic manipulation. The challenge moving forward is to translate this genetic and biological information into the clinic to improve patient care. This review discusses the key data required to achieve this and provides a framework within which to explore the use of response-adapted, biologically targeted, molecularly targeted, and risk-stratified therapeutic approaches to improve the management of patients with multiple myeloma.

Prognostic and predictive biomarker developments in multiple myeloma

New approaches to stratify multiple myeloma patients based on prognosis and therapeutic decision-making, or prediction, are needed since patients are currently managed in a similar manner regardless of individual risk factors or disease characteristics. However, despite new and improved biomarkers for determining the prognosis of patients, there is currently insufficient information to utilise biomarkers to intensify, reduce or altogether change treatment, nor to target patient-specific biology in a so-called predictive manner. The ever-increasing number and complexity of drug classes to treat multiple myeloma have improved response rates and so clinically useful biomarkers will need to be relevant in the era of such novel therapies. Therefore, the field of multiple myeloma biomarker development is rapidly progressing, spurred on by new technologies and therapeutic approaches, and underpinned by a deeper understanding of tumour biology with individualised patient management the goal. In this review, we describe the main biomarker categories in multiple myeloma and relate these to diagnostic, prognostic and predictive applications.

DMG26: A Targeted Sequencing Panel for Mutation Profiling to Address Gaps in the Prognostication of Multiple Myeloma

Multiple myeloma presents with numerous primary genomic lesions that broadly dichotomize cases into hyperdiploidy or IgH translocated. Clinically, these large alterations are assessed by fluorescence in situ hybridization (FISH) for risk stratification at diagnosis. Secondary focal events, including indels and single-nucleotide variants, are also reported; however, their clinical correlates are poorly described, and FISH has insufficient resolution to assess many of them. In this study, we examined the exonic sequences of 26 genes reported to be mutated in >1% of patients with myeloma using a custom panel. We sequenced these exons to approximately 1000 times in a cohort of 76 patients from Atlantic Canada with detailed clinical correlates and in four multiple myeloma cell lines. Across the 76 patients, 255 mutations and 33 focal copy number variations were identified. High-severity mutations and mutations predicted by FATHMM-XF to be pathogenic identified patients with significantly reduced progression-free survival. These mutations were mutually exclusive from the Revised International Staging System high-risk FISH markers and were independent of all biochemical parameters of the Revised International Staging System. Applying our panel to patients classified by FISH to be standard risk successfully reclassified patients into high- and standard-risk groups. Furthermore, three patients in our cohort each had two high-risk markers; two of these patients developed plasma cell leukemia, a rare and severe clinical sequela of multiple myeloma.

Molecular and functional profiling identifies therapeutically targetable vulnerabilities in plasmablastic lymphoma

Plasmablastic lymphoma (PBL) represents a rare and aggressive lymphoma subtype frequently associated with immunosuppression. Clinically, patients with PBL are characterized by poor outcome. The current understanding of the molecular pathogenesis is limited. A hallmark of PBL represents its plasmacytic differentiation with loss of B-cell markers and, in 60% of cases, its association with Epstein-Barr virus (EBV). Roughly 50% of PBLs harbor a MYC translocation. Here, we provide a comprehensive integrated genomic analysis using whole exome sequencing (WES) and genome-wide copy number determination in a large cohort of 96 primary PBL samples. We identify alterations activating the RAS-RAF, JAK-STAT, and NOTCH pathways as well as frequent high-level amplifications in MCL1 and IRF4. The functional impact of these alterations is assessed using an unbiased shRNA screen in a PBL model. These analyses identify the IRF4 and JAK-STAT pathways as promising molecular targets to improve outcome of PBL patients.

Plasmablastic lymphoma (PBL) is an aggressive lymphoma subtype characterized by poor prognosis but the molecular knowledge of the disease is limited. Here, the authors perform whole exome sequencing and copy number determination of primary samples highlighting IRF4 and JAK-STAT pathways as therapeutic targets for PBL.

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 evolving role and utility of off-label drug use in multiple myeloma

The treatment landscape for multiple myeloma (MM) has dramatically changed over the last three decades, moving from no US Food and Drug Administration approvals and two active drug classes to over 19 drug approvals and at least eight different active classes. The advances seen in MM therapy have relied on both a structured approach to obtaining new labels and cautious off-label drug use. Although there are country and regional differences in drug approval processes, many of the basic principles behind off-label drug use in MM can be summarized into four main categories: 1) use of a therapy prior to the current approval regulations; 2) widespread use of a therapy following the release of promising clinical trial results but prior to drug approval; 3) use of a cheap therapy supported by clinical safety and efficacy data but without commercial backing; and 4) niche therapies for small well-defined patient populations where large clinical trials with sufficient power may be difficult to perform. This review takes a historical approach to discuss how off-label drug use has helped to shape the current treatment approach for MM.

Involvement of Alarmins in the Pathogenesis and Progression of Multiple Myeloma

OBJECTIVE

Multiple Myeloma (MM) is a haematological disease resulting from the neoplastic transformation of plasma cells. The uncontrolled growth of plasma cells in the bone marrow and the delivery of several cytokines causes bone erosion that often does not regress, even in the event of disease remission. MM is characterised by a multi-step evolutionary path, which starts with an early asymptomatic stage defined as monoclonal gammopathy of undetermined significance (MGUS) evolving to overt disease.

DATA SOURCES AND STUDY SELECTION

We have selected scientific publications on the specific topics "alarmis, MGUS, and MM", drawing from PubMed. The keywords we used were alarmines, MGUS, MM, and immune system.

RESULTS

The analysis confirms the pivotal role of molecules such as high-mobility group box-1, heat shock proteins, and S100 proteins in the induction of neoangiogenesis, which represents a milestone in the negative evolution of MM as well as other haematological and non-haematological tumours.

CONCLUSIONS

Modulation of the host immune system and the inhibition of neoangiogenesis may represent the therapeutic target for the treatment of MM that is capable of promoting better survival and reducing the risk of RRMM.

A Comprehensive Review of the Genomics of Multiple Myeloma: Evolutionary Trajectories, Gene Expression Profiling, and Emerging Therapeutics

Multiple myeloma (MM) is a blood cancer characterized by the accumulation of malignant monoclonal plasma cells in the bone marrow. It develops through a series of premalignant plasma cell dyscrasia stages, most notable of which is the Monoclonal Gammopathy of Undetermined Significance (MGUS). Significant advances have been achieved in uncovering the genomic aberrancies underlying the pathogenesis of MGUS-MM. In this review, we discuss in-depth the genomic evolution of MM and focus on the prognostic implications of the accompanied molecular and cytogenetic aberrations. We also dive into the latest investigatory techniques used for the diagnoses and risk stratification of MM patients.