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

Abstract. 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

Genomics of Smoldering Multiple Myeloma: Time for Clinical Translation of Findings?

Smoldering multiple myeloma (SMM) is an asymptomatic disorder of clonal bone marrow (BM) plasma cells (PCs) in between the premalignant condition known as monoclonal gammopathy of undetermined significance and overt multiple myeloma (MM). It is characterized by a deep biological heterogeneity that is reflected in a markedly variable progression risk among patients. Recently proposed risk stratification models mainly rely on indirect markers of disease burden and are unable to identify cases in whom clonal PCs have already undergone the “malignant switch” but major clonal expansion has not occurred yet. In the last years, the application of next-generation sequencing (NGS) techniques has led to profound advances in the understanding of the molecular bases of SMM progression, and in all likelihood, it will contribute to the needed improvement of SMM prognostication. In this Review, we describe the recent advances in characterizing the genomic landscape of SMM and intrinsic determinants of its progression, highlighting their implications in terms of understanding of tumor evolution and prognostication. We also review the main studies investigating the role of the microenvironment in this early disease stage. Finally, we mention the results of the first randomized clinical trials and discuss the potential clinical translability of the genomic insights

Functional Impact of Genomic Complexity on the Transcriptome of Multiple Myeloma

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. 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 drug sensitivity screen (DSS), interrogating the Cancer Dependency Map (DepMap) dataset after anchoring cell lines to primary tumor samples using the algorithm. 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 DSS showed that not only t(11;14) but also chr(1q)gain/amps and inactivation predicted differential expression of transcripts of the BCL2 axis and response to venetoclax. 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

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

Halting the vicious cycle within the multiple myeloma ecosystem: blocking JAM-A on bone marrow endothelial cells restores the angiogenic homeostasis and suppresses tumor progression

Interactions of malignant multiple myeloma (MM) plasma cells (MM-cells) with the microenvironment control MM-cell growth, survival, drug-resistance and dissemination. As in MM microvascular density increases in the bone marrow (BM), we investigated whether BM MM endothelial cells (MMECs) control disease progression via the junctional adhesion molecule A (JAM-A). Membrane and cytoplasmic JAM-A levels were upregulated in MMECs in 111 newly diagnosed (NDMM) and 201 relapsed-refractory (RRMM) patients compared to monoclonal gammopathy of undetermined significance (MGUS) and healthy controls. Elevated membrane expression of JAM-A on MMECs predicted poor clinical outcome. Mechanistically, addition of recombinant JAM-A to MMECs increased angiogenesis whereas its inhibition impaired angiogenesis and MM growth in 2D and 3D in vitro cell culture and chorioallantoic membrane-assays. To corroborate these findings, we treated MM bearing mice with JAM-A blocking mAb and demonstrated impaired MM progression corresponding to decreased MM-related vascularity. These findings support JAM-A as an important mediator of MM progression through facilitating MM-associated angiogenesis. Collectively, elevated JAM-A expression on bone marrow endothelial cells is an independent prognostic factor for patient survival in both NDMM and RRMM. Blocking JAM-A restricts angiogenesis in vitro, in embrio and in vivo and represents a suitable druggable molecule to halt neoangiogenesis and MM progression

Clinical significance of SF3B1 mutations in myelodysplastic syndromes and myelodysplastic/myeloproliferative neoplasms

In a previous study, we identified somatic mutations of SF3B1, a gene encoding a core component of RNA splicing machinery, in patients with myelodysplastic syndrome (MDS). Here, we define the clinical significance of these mutations in MDS and myelodysplastic/myeloproliferative neoplasms (MDS/MPN). The coding exons of SF3B1 were screened using massively parallel pyrosequencing in patients with MDS, MDS/MPN, or acute myeloid leukemia (AML) evolving from MDS. Somatic mutations of SF3B1 were found in 150 of 533 (28.1%) patients with MDS, 16 of 83 (19.3%) with MDS/MPN, and 2 of 38 (5.3%) with AML. There was a significant association of SF3B1 mutations with the presence of ring sideroblasts (P < .001) and of mutant allele burden with their proportion (P = .002). The mutant gene had a positive predictive value for ring sideroblasts of 97.7% (95% confidence interval, 93.5%-99.5%). In multivariate analysis including established risk factors, SF3B1 mutations were found to be independently associated with better overall survival (hazard ratio = 0.15, P = .025) and lower risk of evolution into AML (hazard ratio = 0.33, P = .049). The close association between SF3B1 mutations and disease phenotype with ring sideroblasts across MDS and MDS/MPN is consistent with a causal relationship. Furthermore, SF3B1 mutations are independent predictors of favorable clinical outcome, and their incorporation into stratification systems might improve risk assessment in MDS