AbstractThe concept of the myeloma stem cell may have important therapeutic implications, yet its demonstration has been hampered by a lack of consistency in terms and definitions. Here, we summarize the current documentation and propose single-cell in vitro studies for future translational studies. By the classical approach, a CD19−/CD45low/−/CD38high/CD138+ malignant plasma cell, but not the CD19+/CD38low/− memory B cell compartment, is enriched for tumorigenic cells that initiate myeloma in xenografted immunodeficient mice, supporting that myeloma stem cells are present in the malignant PC compartment. Using a new approach, analysis of c-DNA libraries from CD19+/CD27+/CD38− single cells has identified clonotypic memory B cell, suggested to be the cell of origin. This is consistent with multiple myeloma being a multistep hierarchical process before or during clinical presentation. We anticipate that further characterization will require single cell geno- and phenotyping combined with clonogenic assays. To implement such technologies, we propose a revision of the concept of a myeloma stem cell by including operational in vitro assays to describe the cellular components of origin, initiation, maintenance, and evolution of multiple myeloma. These terms are in accordance with recent (2012) consensus statements on the definitions, assays, and nomenclature of cancer stem cells, which is technically precise without completely abolishing established terminology. We expect that this operational model will be useful for future reporting of parameters used to identify and characterize the multiple myeloma stem cells. We strongly recommend that these parameters include validated standard technologies, reproducible assays, and, most importantly, supervised prospective sampling of selected biomaterial which reflects clinical stages, disease spectrum, and therapeutic outcome. This framework is key to the characterization of the cellular architecture of multiple myeloma and its use in precision medicine.
The multiple myeloma stem cell (MMSC) is defined as a cell within the malignant tissue that possesses the capacity to self-renew and to differentiate into the predominant lineages of myeloma plasma cells comprising the neoplasm. Self-renewal is cell division without the loss of differentiation potential, at least in some daughter cells. This concept is based on phenomenology, and MMSCs are defined experimentally by their ability to recapitulate the continuous growth of malignant tissue in vivo and/or in vitro. Experimental approaches underlie the terms “cancer-initiating cells” and “cell of origin”, which are used operationally to characterize cancer stem-cell (CSC) compartments. Several studies have analyzed the hematopoietic system by sorting a few or even single cells, tracking acquired genetic changes, and transplanting cells to determine whether subsets within the differentiating hierarchy act as CSCs.1
Hierarchical models have been described for hematological malignancies such as acute and chronic myeloid and lymphoblastic leukemia,62 and multiple myeloma (MM),127 suggesting that the malignant clone includes immature progenitors or stem cells present in the proliferating bone-marrow compartment. According to the “multistep-oncogenesis” theory, malignancies develop due to a series of molecular alterations that occur in such cells. Although this theory is appealing and, on the whole, accepted by the scientific community, many aspects of this theory require rigorous scientific questions and answers.
The practical usefulness of the hierarchical model relies on emerging insights into the pathogenesis and identification of new biomarkers. Progress in this area depends on recent technological advances that have enabled researchers to study single-cell gene expression13 and to address changes in cellular programming in a global fashion by analyzing gene mutations, expression and deregulation.1614 Lagging slightly behind this approach is the rapidly developing technology for examining the protein compartment of the cell.1917
In the present review, we have updated the latest scientific reports and propose a revision of the MMSC concept to include operational terms (Table 1), in accordance with recent (2012) consensus statements on the definitions, assays, and nomenclature of cancer stem cells, which is technically precise without completely abolishing established terminology.20
We expect this will empower the design of translational research activities based on prospectively sampled biomaterial which reflects the spectrum of clinical disease. We expect such a revision to acquire data that indirectly document the existence of multiple MMSCs and validate its impact via targeted therapy.
The stem-cell concept and the B-cell hierarchy
A normal stem cell is a unique cell type present at low frequency which can renew itself and produce progenitors of one or more specialized cell types. Beginning with the fertilized oocyte, cellular differentiation into specialized cell types, tissues, and organs follows a strict pattern. The classical view is that during such processes, cells gradually lose their capacity for self-renewal, their plasticity, and their ability to develop into different lineages.21
Stem cells may be classified into two major classes: 1) pluripotent stem cells derived from early embryos that are able to replenish all cell types in the human body, and 2) multipotent stem cells located in various organs that are dedicated to the replenishment of specific tissues such as blood. Embryonic stem cells, which are derived from the inner cell mass of the blastocyst, can be cultured in vitro nearly indefinitely. Unlike embryonic stem cells, multipotent organ restricted stem cells, which may be isolated from a variety of tissues in fetal and adult humans, are lineage specific; hematopoietic stem cells, neuronal stem cells, and hepatic stem cells are all multipotent.
In this review, we consider hematopoietic stem cells and putative CSCs as prototypes of multipotent stem cells. However, not all are multipotent; for example, ‘end-stage’ effector B cells may regain self-renewing mechanisms in order to expand and maintain immunity.2322 In normal B-cell lymphopoiesis, a number of well-characterized subpopulations have been defined by membrane marker phenotyping, as reviewed and illustrated in the upper part of Figure 1. The very early B-cell precursors develop into pro- and pre-B cells before they migrate as immature B cells into the blood to reach peripheral lymphoid organs as naive B cells.3124 Germinal and post-germinal-center centrocytes, centroblasts, memory cells, plasmablasts, and end-stage plasma cells (PCs) are included in the later stages of the mature B-cell differentiation hierarchy. Most malignant B-cell lymphomas, chronic lymphoblastic leukemias, and MMs are considered to originate from these cells following analyses of the somatic hypermutation and class switch-recombination status of the gene encoding the immunoglobulin heavy chain (IgH) which defines the hierarchical status of any clonotypic cell.3632 Further understanding of the molecular mechanisms that regulate the malignant B-cell hierarchy requires investigations of purified subpopulations or even single cells.
The phenomenon and its markers
The MMSC concept is based on phenomenology: the outcome of studies in animal and/or humans that rely on in vivo and in vitro assays. However, these assays address the future potential of the stem cell, while study outcomes address the expression of this potential.37 Therefore, identifying a stem cell by allowing it to differentiate loses the original cell; at the same time, only a limited range of responses may be evident based on the model used. All stem cell assays reveal an outcome after cells are perturbed, and it is still an open question how the stem cell phenomena should be identified at the single-cell level.
At the cellular level, MM is characterized by uncontrolled expansion of PCs in the bone marrow. In addition, cells belonging to the myeloma IgH-defined clone (clonotypic cells) which precede the PC stage have been detected in peripheral blood, lymph nodes, and bone marrow.3938363310 The earliest clonotypic cells were exclusively identified in the CD38 B-cell compartment, suggesting a potential precursor and a myeloma hierarchy. The main scientific question was whether these clonal cells were intrinsic to the maintenance of the malignant PC clone defined by membrane markers, as illustrated in the lower part of Figure 1. Functional studies supported this idea,39381110 but attempts to identify clonogenic potential in this compartment were unsuccessful,98 and it remains a controversial issue.12
As illustrated in Figure 2, MM is the clinical outcome of a multistep transformation process that includes a premalignant state, the monoclonal gammopathy of undetermined significance (MGUS).40 Two early pathways in MM oncogenesis have been identified: a nonhyperdiploid pathway characterized by translocations involving the IgH locus (14q32), and a hyperdiploid pathway.4241 IgH translocations are introduced at the MGUS state; the majority of breakpoints fall within the switch regions of the gene encoding IgH. Thus, the mechanisms and timing of translocation are those of normal IgH class switch-recombination, and define an early oncogenic event or targeting of a gene with oncogenic potential during initiation. In the hyperdiploid pathway, recurrent changes in chromosome number are considered to constitute an early event in MM oncogenesis.
MM cells display stable VDJ joining sequences, an accumulation of somatic mutations and absence of ongoing somatic hypermutation.4443 These findings support the idea that some MM cells are derived from a germinal center or post-germinal-center B cell that differentiates into a clonotypic memory B cell or a PC as illustrated in Figure 1.
In search of the MMSC
Although the malignant cells that represent terminally differentiated PCs are readily identifiable via morphological criteria, the phenotype of the MMSC is not yet known with certainty due to several observations that suggest a less-mature clonal precursor. Critically, this idea was supported by data from single-cell analyses.3633 More specifically, we identified, sorted and studied CD19/CD27/CD38 single-cell libraries of documented clonotypic cells that met all the criteria for a memory B cell, which were present in all 10 patients studied at a median frequency of 0.3% of CD19 B cells (range 0.001–1 cell per 1000 circulating cells).4645
This observation, together with contradictory MMSC studies3633118 and technological progress, motivated detailed multiparametric characterization of MMSCs and related B-cell subsets. To this end, members of the European Myeloma Network initiated a collaborative network of laboratories and scientists (MSCNET) in 2007.
As reviewed above, in 2007, the state of the art of MMSC suggested that post-germinal CD19/CD20/CD138/CD38 pre-PC B cells constituted the putative MMSC.39381110 However, some evidence pointed to a CD19/CD20/CD138/CD38 plasmablast/PC.98 It was conceivable that both or additional stem-cell compartments could be the cellular basis for the acquired oncogenetic changes that underlie myeloma initiation, maintenance, and evolution.
During the last decade, MSCNET has performed detailed studies to confirm or refute previous studies6047 and established protocols706117 to delineate the phenotypes of subpopulations of cells in randomly selected primary tumor samples and in preclinical disease models. While our investigations did not confirm that pre-PC B cells are myeloma initiating,525150 several observations suggested that further study of plasmablasts/PCs at the single cell level will be key to elucidating MMSC functions.
This suggestion is in accordance with recent studies documenting that “CD19/CD45/CD38/CD138 [PCs] are enriched for human tumorigenic myeloma cells” that regenerate detectable myeloma populations in xenografted immunodeficient mice.12 In a parallel investigation, CD19/CD38 memory B cells engrafted into human bone grafts, resulting in the repopulation of polyclonal B cells, which supports the hypothesis that memory B cells have the ability to self-renew.23 However, since few clonotypic B cells were present in these grafts, the specific questions about pre-PC B cells have not been definitively answered; these cells may be present at quantities below the limit of detection. The same limitation may pertain to the first cells of origin that depart from normal B lymphopoiesis and harbor early, but not late,50 changes in genetic, epigenetic, or other regulatory events that underlie the generation of malignant myeloma-initiating cells.
Another controversy surrounds the CD138 myeloma PCs studied in our preclinical models. These PCs exhibit engraftment and clonogenic potential in vitro (unpublished data),5251 in accordance with findings from others.5453 The nature of the CD138 and CD138 PCs in the lineage of myeloma cells remains to be determined.55
Of particular importance, MSCNET has identified a new CD19/CD45/CD138/CD38 subpopulation associated to the CD19/CD45/CD138/CD38 normal PC compartment with different gene expression in normal bone marrow, suggesting a differentiation pathway that has not yet been studied in terms of MM pathogenesis.56 Our next step will be to study the function of these compartments and patients in more detail, guided by novel technological progress in single-cell analysis, a common prospective biobank strategy, and well-characterized preclinical functional in vitro and in vivo models.
In our search, we propose a revision of the conceptual context of MMSCs to use more operational in vitro functions that will enable studies of the origin, initiation, maintenance, and evolution driven by deregulated genetic events. We anticipate that our understanding of MMSC will encompass the multiple dynamic cell compartments that are present from the initial to the final steps of the differentiation, evolution and selection of clonal PCs in myeloma.
Hallmarks: self-renewal, plasticity, and drug resistance
CSC function, a hallmark of cancer in general, is defined to include normal, specific functions such as self-renewal, plasticity, and drug resistance.69687271 Since most end-stage myeloma cells are short-lived,73 MMSCs are thought to continuously generate myeloma daughter cells by precisely balancing self-renewal and differentiation. In theory, a CSC can accomplish this balance via asymmetric cell division in which it divides to generate one progeny pool with a stem-cell phenotype (self-renewal) and another progeny pool that differentiates and gives rise to end-stage tumor cells.7574 However, stem cells can also use symmetric divisions, defined as the generation of daughter cells that acquire identical phenotypes, to self-renew or to generate differentiated progeny.75 Stem cells are thus defined by their capacity to generate more stem cells and differentiated daughter cells, rather than by symmetric production of a stem cell and a differentiated daughter at each division. The picture is even more complex in MM as some patients harbor heterogeneous populations of PCs that were most likely initiated from different populations of MMSCs within the myeloma hierarchy after many genetic lesions. Such heterogeneity may be explained by an alternative stochastic model in which all myeloma cells have the potential to self-renew, yet experience a varying probability of entering the cell cycle and finding an environment that supports subclonal evolution and heterogeneity. Future studies should therefore be based on genome-wide fingerprinting of clonal heterogeneity in order to identify factors that drive stepwise malignant transformation from normal PCs to MGUS, medullary MM, extramedullary MM, PC leukemia, and HMCL. Data from analyses of selected tissues and samples7976 will qualify biobank material for future studies of the deregulation of normal self-renewal pathways.
Novel technologies and potential strategies include single-cell analyses,5549368079 transgenic mouse models828154 in addition to the xenogene immuno compromised SCID-hu models,53 syngeneic BALB/c plasmacytoma or the 5T serie,83 and investigations of oncogene transformation in primary organoid miniature tissue culture.8784 Bmi-1, Notch, Hedgehog, and Wnt, which were initially identified based on their roles in tumor formation, have been shown to be involved in the regulation of self-renewal in normal stem cells in many tissues.9088
Since myeloma cells are influenced by the host, the microenvironment may play a key role in the initiation of myeloma and associated phenotypic changes—a phenomenon called “plasticity”, defined as altered cellular phenotype and function during deregulated differentiation. Of interest, this refers to malignant mature B cells that share features of different maturation steps, including precursors. Plasticity in MM is perhaps best illustrated by the subtyping of clinical tumor samples based on B-cell subset-associated gene signatures; tumors previously assigned to PreB-II and memory-cell subtypes of malignant PCs were associated with inferior prognoses.6057 This observation provides a new tool for generating insight into the stages of clonal plasticity associated with oncogenesis and deregulated differentiation. The mechanisms of myeloma-cell plasticity should be exploited, and their significance for the concept of MMSCs assessed.
Since a major group of patients suffer from disease recurrence or clinical relapse after chemotherapy, MM is thought to be a consequence of molecular resistance mechanisms that protect the MMSC compartments. The idea that resistant MMSCs are the source of post-therapeutic recurrence is not a new one; it was first described in studies of the stem-cell hierarchy and the self-renewal gene expression signature in leukemia with poor clinical outcome, which was also suggested to be associated with drug resistance.9491 In myeloma, it has recently been documented that the level of drug resistance is a function related to the cellular hierarchy95 and its active or dormant stage96 that we need to identify and target to overcome it. These findings highlight the potential to develop predictive, drug-specific sensitivity assays. We have taken the first step toward defining gene signatures of drug-specific resistance in pre-clinical models of HMCL.6057
Self-renewal, plasticity, and resistance have been studied in the preclinical model of HMCL, which is considered to be the most advanced and homogenous myeloma tissue available. It is important to recognize that each HMCL reflects the end stage of an individual patient’s genetic evolution and selection, but each HMCL also reflects the aggregation of stepwise oncogenic events over time, some of which may have deregulated the hallmarks of MMSCs. Although we acknowledge that this model may be irrelevant for studies of the hierarchical model, it is a tool for identifying potential markers for MMSC. Such findings should be traced back through the myeloma hierarchy in prospective qualified clinical myeloma cases, as exemplified by the MSCNET single-cell approach.49
Biological assays of MMSCs
In a conceptual context, classical stem-cell assays capture the phenomenon of a subpopulation that can propagate malignant clones indefinitely, and produce overt myeloma in vivo — the MMSCs. In an operational context, these assays indirectly seek to detect MMSCs as engrafting myeloma-initiating cells (in vivo), long-term culture-initiating cells (in vitro), or short-term sphere-forming cells (in vitro) as described in Table 1.
To date, immunodeficient mice have served as the most sensitive recipients for the growth, detection, and quantification of MMSC. Several xenografted mouse models enabled successful detection of the malignant regeneration of myeloma, usually measured via limiting dilution to identify the low frequent cells. However, the ability or failure of a cell compartment to produce myeloma in a transplanted mouse may not directly reflect the function of this compartment in patients. In this regard, the absence of the MMSC niche is a major limiting factor, as most samples include myeloma cells that have not yet completely acquired the ability to grow autonomously. To address this limitation, humanized and genetically modified mice have been designed as the state of the art fundament for functional studies of MMCS in myelomagenesis.838139128
Some studies have also evaluated MMSCs on the basis of their presumed self-renewal activity in vitro by investigating cells that initiate the sustained production of clonal myeloma cells when cultured in supportive conditions with or without stromal cells; these cells are usually subjected to analysis via limiting dilution. The generation of cellular spheres (as clusters or colonies in non-adherent liquid culture) constitutes a simple yet indirect strategy for identifying MMSCs in cell suspensions from myeloma tissue. It is unlikely that either of these in vitro systems fully replicates the three-dimensional structure and environment of myeloma in patients. On the contrary, it is likely that variables important for in vivo growth and self-renewal may not be present in in vitro investigations; the cells under study may show no or selected growth, and/or may be anomalously and rapidly induced to differentiate to an end state without prior expansion. Therefore, in vitro assays may be useless in terms of clinically meaningful predictions.
Using HMCLs as a source of MMSCs for assays of growth in vitro or in transplanted mice is also problematic. Although it is unlikely that these cells reflect the original genotype or origin of MMSCs, HMCLs contain cells that display the functions of MMSCs. Accordingly, considerable caution needs to be taken when formulating questions that will be addressed through the analysis of cells passaged in vitro. However, meta-analyses of HMCL responses to known anticancer drugs illustrate how these cells can be used to reveal associations between drug sensitivity and gene-expression profiling in cell lines from individual patients; these gene signatures of resistance have documented prognostic value.5857
Single cells, single genes, single clones
By the time MM is diagnosed, it consists of millions of myeloma cells carrying genetic abnormalities that initiate malignant proliferation, and other mutations are acquired during disease evolution. Some of these secondary mutations emerge due to selective pressure and act as “drivers”; others may be “passengers” resulting from random mutational exposures or genomic instability during many cell divisions. In theory, this instability may yield one MMSC per driver lesion. It is likely that individual MM tumors have multiple MMSCs with different phenotypes that are closely linked to the deregulated functions of self-renewal, plasticity, and drug resistance.
Initial DNA sequencing studies7876 have provided insight into mutational profiles in MM and have identified recurrent genes and potential molecular mechanisms responsible for MM initiation, maintenance, and progression. It is becoming clear that complexity beyond the landscape of mutations exists at the level of intraclonal heterogeneity, which directly affects disease progression and treatment resistance during clonal evolution and selection.78767269 Understanding these processes and characterizing these subclones will require investigations, of single or few plasma cells,9897 into the functional impact of specific genetic variants.
It will be challenging to combine gene identification and in vitro functional approaches in order to separate the true genetic drivers from the many passengers along the tracks of myelomagenesis. There is an increasing interest in defining the exact phylogeny of individual subclonal populations;80 patient-specific single-cell genetic profiling provides a potential resolution to this problem. Our original work in this area, which included the estimation of subset frequencies,46453633 also encompassed studies of differential oncogene expression in cDNA libraries from normal PCs and cases of MGUS, MM, extramedullary MM, and HMCL, as well as the prognostic impact of these differences. In brief, tissue samples were phenotyped via multiparametric flow cytometry, potential subclones were identified, and single cells (or a few cells) were sorted into individual wells containing lysis medium and followed via the global amplification of cDNA from each well. The quality of each library was confirmed via a set of highly targeted QRT-PCRs for chimeric gene fusions, deregulated genes, and single-nucleotide variants (for example, in the IgH locus). These patient-specific libraries were associated with parameters such as tissue type, disease stage, sample site, therapy, and outcome.9897 This strategy, which has been automated and optimized to have a low error rate, has been integrated into high-throughput platforms that are useful for DNA and RNA sequencing; this may yield insight into subclonal genetic architectures and phylogenies in MM.787513
We propose to combine this state of the art technique with an operational context as summarized in Table 1, in order to better define the phylogenetic relationships among clonal populations in myeloma at clinical presentation, during follow-up, and at relapse. This strategy will enable us to generate quantitative measures of stem-cell activities and functions at the level of single subclones by assessing self-renewal via the analysis of gene-expression signatures,43 plasticity via subtyping by B-cell subset-associated gene signatures,6463 and drug resistance via the assignment of gene signatures of drug resistance.6057
Summary and perspective
The term “CSC” captures the idea that a stable, minor, quiescent, and phenotypically definable subpopulation exists within the malignant tissue. This subpopulation has the potential to self-renew and to enhance tumor resistance to toxic stress, thereby propagating the cancer for prolonged or even unlimited periods of time.
This idea is supported by phenomenology, and it plays a major role in our understanding of the pathogenesis of cancer. Although this concept is also widely appreciated for MMSCs, controversy persists regarding the identification and their origin, selection, plasticity, phenotype(s), and heterogeneity in various stages of MM. The existence of MMSCs, and whether they can be documented as a well-defined and characterized entity in MM remains to be demonstrated — and it may never be. However, introducing a more operational context (as suggested in Table 1) into our descriptions may enable the acquisition of data that indirectly support the existence of MMSCs and allow clinical validation of their impact; for example, via targeted therapy. Here we have summarized results from recent experimental work within and outside MSCNET, with a focus on the identification, isolation, and characterization of MMSCs. To date, these results support the hypothesis that myeloma-initiating cells are present in the malignant PC compartment, but the cell of origin is a normal counterpart of a germinal-center B cell that differentiates into a premalignant PC compartment identified in MGUS as indicated in Figure 1. This is consistent with our current understanding of the pathogenesis of MM as a multistep, cellular, hierarchical and linear process of disease initiation, evolution, selection and clinical presentation as illustrated in Figure 2.
A revision of the MMSC concept should include operational terms as described in Table 1 that enable the design of research plans based on prospectively sampled biomaterial that reflects the clinical disease spectrum. We anticipate that such a revision will lead to the acquisition of data that indirectly documents the existence of multiple MMSCs. The ultimate validation of their existence may then be achieved via targeted therapy in clinical trials.
The revision will allow us to identify a range of specific genetic events in various B-cell and PC subsets, and to design research activities focused on targeted therapy,10099 based on prospectively sampled biomaterial from all myeloma subtypes classified at diagnosis and during follow-up. This strategy is in accordance with recent consensus statements on the definitions, assays, and nomenclature of CSCs, including a more operational nomenclature that achieves technical precision without completely abolishing established terminology.201
- Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/100/12/1451
- Funding This work on MMSC and myeloma pathogenesis and classification was supported by research funding from the EU 6th FP to MSCNET (LSHC-CT-2006-037602), the Danish Research Agency (grants no. 99 00 771, 271-05-0286, 271-05-0537, and 22-00-0314; to CHEPRE, #2101-07-0007), the Danish Cancer Society (grants no. DP 07014, DR 07017, and DP 9810009), Novo Nordic Foundation (Senior Fellowship 2001-4), KE Jensen Foundation (2005–2013), the Multiple Myeloma Research Foundation (senior grant 2003–4, contract no. 14).The Myeloma Stem Cell Network is a consortium of nine partners within the European Myeloma Network collaborating on studies of cancer stem cells in multiple myeloma. The present report is prepared by active partners in work package 1. The partners in the European Myeloma Network and MSCNET are listed at http://www.myeloma-europe.org/.
- Received November 19, 2015.
- Accepted August 30, 2016.
- Clarke MF, Dick JE, Dirks PB. Cancer stem cells - perspectives on current status and future directions: AACR Workshop on cancer stem cells. Cancer Res. 2006; 66(19):9339-9344. PubMedhttps://doi.org/10.1158/0008-5472.CAN-06-3126Google Scholar
- Dick JE. Stem cell concepts renew cancer research. Blood. 2008; 112(13):4793-807. PubMedhttps://doi.org/10.1182/blood-2008-08-077941Google Scholar
- Eppert K, Takenaka K, Lechman ER. Stem cell gene expression programs influence clinical outcome in human leukemia. Nat Med. 2011; 17(9):1086-1093. PubMedhttps://doi.org/10.1038/nm.2415Google Scholar
- Greaves M. Cancer stem cells renew their impact. Nat Med. 2011; 17(9):1046-1048. PubMedhttps://doi.org/10.1038/nm.2458Google Scholar
- Bonnet D, Dick JE. Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat Med. 1997; 3:730-737. PubMedhttps://doi.org/10.1038/nm0797-730Google Scholar
- Anderson K, Lutz C, van Delft FW. Genetic variegation of clonal architecture and propagating cells in leukaemia. Nature. 2011; 469(7330):356-361. PubMedhttps://doi.org/10.1038/nature09650Google Scholar
- Cobaleda C, Gutiêrrez-Cianca N, Perez-Losada J. A primitive hematopoietic cell is the target for the leukemic transformation in human philadelphia-positive acute lymphoblastic leukemia. Blood. 2000; 95(3):1007-1013. PubMedGoogle Scholar
- Yaccoby S, Epstein J. The proliferative potential of myeloma plasma cells manifest in the SCID-hu host. Blood. 1999; 94(10):3576-3582. PubMedGoogle Scholar
- Guikema JE, Vellenga E, Bakkus MH, Bos NA. Myeloma clonotypic B cells are hampered in their ability to undergo B-cell differentiation in vitro. Br J Haematol. 2002; 119(1):54-61. PubMedhttps://doi.org/10.1046/j.1365-2141.2002.03789.xGoogle Scholar
- Matsui W, Huff CA, Wang Q. Characterization of clonogenic multiple myeloma cells. Blood. 2004; 103(6):2332-2336. PubMedhttps://doi.org/10.1182/blood-2003-09-3064Google Scholar
- Huff CA, Matsui W. Multiple myeloma cancer stem cells. J Clin Oncol. 2008; 26(17):2895-2900. PubMedhttps://doi.org/10.1200/JCO.2007.15.8428Google Scholar
- Kim D, Park CY, Medeiros BC, Weissman IL. CD19-CD45 low/− CD38 high/CD138+ plasma cells enrich for human tumorigenic myeloma cells. Leukemia. 2012; 26(12):2530-2537. PubMedhttps://doi.org/10.1038/leu.2012.140Google Scholar
- Dey SS, Kester L, Spanjaard B, Bienko M, van Oudenaarden A. Integrated genome and transcriptome sequencing of the same cell. Nat Biotechnol. 2015; 33(3):285-289. PubMedhttps://doi.org/10.1038/nbt.3129Google Scholar
- Zong C, Lu S, Chapman AR, Xie XS. Genome-wide detection of single-nucleotide and copy-number variations of a single human cell. Science. 2012; 338(6114):1622-1626. PubMedhttps://doi.org/10.1126/science.1229164Google Scholar
- Streets AM, Zhang X, Cao C. Microfluidic single-cell whole-transcriptome sequencing. Proc Natl Acad Sci USA. 2014; 111(19):7048-7053. PubMedhttps://doi.org/10.1073/pnas.1402030111Google Scholar
- Baslan T, Kendall J, Rodgers L. Genome-wide copy number analysis of single cells. Nat Protoc. 2012; 7(6):1024-1041. PubMedhttps://doi.org/10.1038/nprot.2012.039Google Scholar
- Johnsen HE, Bøgsted M, Klausen TW. Multiparametric flow cytometry profiling of neoplastic plasma cells in multiple myeloma. Cytometry B Clin Cytom. 2010; 78(5):338-347. PubMedGoogle Scholar
- Paiva B, Almeida J, Pérez-Andrés M. Utility of flow cytometry immunophenotyping in multiple myeloma and other clonal plasma cell-related disorders. Cytometry B Clin Cytom. 2010; 78(4):239-252. PubMedGoogle Scholar
- Salonen J, Rönnholm G, Kalkkinen N, Vihinen M. Proteomic changes during B cell maturation: 2D-DIGE approach. PLoS One. 2013; 8(10):e77894. Google Scholar
- Valent P, Bonnet D, De Maria R. Cancer stem cell definitions and terminology: the devil is in the details. Nat Rev Cancer. 2012; 12(11):767-775. PubMedhttps://doi.org/10.1038/nrc3368Google Scholar
- Clements WK, Traver D. Signalling pathways that control vertebrate haematopoietic stem cell specification. Nat Rev Immunol. 2013; 13(5):336-348. PubMedhttps://doi.org/10.1038/nri3443Google Scholar
- Cooper MD. The early history of B cells. Nat Rev Immunol. 2015; 15(3):191-197. PubMedhttps://doi.org/10.1038/nri3801Google Scholar
- Luckey CJ, Bhattacharya D, Goldrath AW, Weissman IL, Benoist C, Mathis D. Memory T and memory B cells share a transcriptional program of self-renewal with long-term hematopoietic stem cells. Proc Natl Acad Sci U S A. 2006; 103(9):3304-3309. PubMedhttps://doi.org/10.1073/pnas.0511137103Google Scholar
- Shlomchik MJ, Weisel F. Germinal center selection and the development of memory B and plasma cells. Immunol Rev. 2012; 247(1):52-63. PubMedhttps://doi.org/10.1111/j.1600-065X.2012.01124.xGoogle Scholar
- Matthias P, Rolink AG. Transcriptional networks in developing and mature B-cells. Nat Rev Immunol. 2005; 5(6):497-508. PubMedhttps://doi.org/10.1038/nri1633Google Scholar
- Klein U, Dalla-Favera R. Germinal centres: role in B-cell physiology and malignancy. Nat Rev Immunol. 2008; 8(1):22-33. PubMedhttps://doi.org/10.1038/nri2217Google Scholar
- McHeyzer-Williams M, Okitsu S, Wang N. Molecular programming of B-cell memory. Nat Rev Immunol. 2011; 12(1):24-34. PubMedGoogle Scholar
- Allen CD, Okada T, Cyster JG. Germinal-center organization and cellular dynamics. Immunity. 2007; 27(2):190-202. PubMedhttps://doi.org/10.1016/j.immuni.2007.07.009Google Scholar
- Muramatsu M, Kinoshita K, Fagarasan S. Class switch recombination and hypermutation require activation-induced cytidine deaminase (AID), a potential RNA editing enzyme. Cell. 2000; 102(5):553-563. PubMedhttps://doi.org/10.1016/S0092-8674(00)00078-7Google Scholar
- Jackson SM, Harp N, Patel D. Key developmental transitions in human germinal center B cells are revealed by differential CD45RB expression. Blood. 2009; 113(17):3999-4007. PubMedhttps://doi.org/10.1182/blood-2008-03-145979Google Scholar
- Tooze RM. A replicative self-renewal model for long-lived plasma cells: questioning irreversible cell cycle exit. Front Immunol. 2013; 4:460. PubMedGoogle Scholar
- González D, van der Burg M, García-Sanz R. Immunoglobulin gene rearrangements and the pathogenesis of multiple myeloma. Blood. 2007; 110(9):3112-3121. PubMedhttps://doi.org/10.1182/blood-2007-02-069625Google Scholar
- Rasmussen T, Lodahl M, Hancke S, Johnsen HE. In Multiple Myeloma Clonotypic CD38−/CD19+/CD27+ Memory B Cells Recirculate Through Bone Marrow, Peripheral Blood and Lymph Nodes. Leuk Lymphoma. 2004; 45(7):1413-1417. PubMedhttps://doi.org/10.1080/10428190410001655157Google Scholar
- Billadeau D, Ahmann G, Greipp P, Van NB. The bone marrow of multiple myeloma patients contains B cell populations at different stages of differentiation that are clonally related to the malignant plasma cell. J Exp Med. 1993; 178(3):1023-1031. PubMedhttps://doi.org/10.1084/jem.178.3.1023Google Scholar
- Corradini P, Boccadoro M, Voena C, Pileri A. Evidence for a bone marrow B cell transcribing malignant plasma cell VDJ joined to C mu sequence in immunoglobulin (IgG)- and IgA-secreting multiple myelomas. J Exp Med. 1993; 178(3):1091-1096. PubMedhttps://doi.org/10.1084/jem.178.3.1091Google Scholar
- Rasmussen T, Jensen L, Johnsen HE. The Clonal Hierachy in Multiple Myeloma. Acta Oncol. 2001; 39(7):765-770. Google Scholar
- Potten CS, Loeffler M. Stem cells: attributes, cycles, spirals, pitfalls and uncertainties. Lessons for and from the crypt. Development. 1990; 110(4):1001-1020. PubMedGoogle Scholar
- Pilarski LM, Giannakopoulos NV, Szczepek AJ, Masellis AM, Mant MJ, Belch AR. In multiple myeloma, circulating hyperdiploid B cells have clonotypic immunoglobulin heavy chain rearrangements and may mediate spread of disease. Clin Cancer Res. 2000; 6(2):585-596. PubMedGoogle Scholar
- Pilarski LM, Hipperson G, Seeberger K. Myeloma progenitors in the blood of patients with aggressive or minimal disease: engraftment and self-renewal of primary human myeloma in the bone marrow of NOD SCID mice. Blood. 2000; 95(3):1056-1065. PubMedGoogle Scholar
- Kuehl WM, Bergsagel PL. Multiple myeloma: Envolving genetic events and host interactions. Nat Rev Cancer. 2002; 2(3):175-187. PubMedhttps://doi.org/10.1038/nrc746Google Scholar
- Bergsagel PL, Kuehl WM, Zhan F. Cyclin D dysregulation: an early and unifying pathogenic event in multiple myeloma. Blood. 2005; 106(1):296-303. PubMedhttps://doi.org/10.1182/blood-2005-01-0034Google Scholar
- Bergsagel PL, Kuehl M. Chromosome translocation in multiple myeloma. Oncogene. 2001; 20(40):5611-5622. PubMedhttps://doi.org/10.1038/sj.onc.1204641Google Scholar
- Vescio RA, Cao J, Hong CH. Myeloma Ig heavy chain V region sequences reveal prior antigenic selection and marked somatic mutation but no intraclonal diversity. J Immunol. 1995; 155(5):2487-2497. PubMedGoogle Scholar
- Bakkus MH, Heirman C, Van RI, Van CB, Thielemans K. Evidence that multiple myeloma Ig heavy chain VDJ genes contain somatic mutations but show no intraclonal variation. Blood. 1992; 80(9):2326-2335. PubMedGoogle Scholar
- Rasmussen T, Jensen L, Honoré L, Johnsen HE. Frequency and kinetics of polyclonal and clonal B-cells in the peripheral blood of patients being treated for multiple myeloma. Blood. 2000; 96(13):4357-4359. PubMedGoogle Scholar
- Rasmussen T, Jensen L, Johnsen HE. The CD19 compartment in myeloma includes a population of clonal cells persistent after high-dose treatment. Leuk Lymphoma. 2002; 43(5):1075-1077. PubMedhttps://doi.org/10.1080/10428190290021524Google Scholar
- Pfeifer S, Perez-Andres M, Ludwig H, Sahota SS, Zojer N. Evaluating the clonal hierarchy in light-chain multiple myeloma: implications against the myeloma stem cell hypothesis. Leukemia. 2011; 25(7):1213-1216. PubMedhttps://doi.org/10.1038/leu.2011.70Google Scholar
- Thiago LS, Perez-Andres M, Balanzategui A. Circulating clonotypic B cells in multiple myeloma and monoclonal gammopathy of undetermined significance. Haematologica. 2014; 99(1):155-162. PubMedhttps://doi.org/10.3324/haematol.2013.092817Google Scholar
- Rasmussen T, Haaber J, Dahl IM. Identification of translocation products but not K-RAS mutations in memory B cells from patients with multiple myeloma. Haematologica. 2010; 95(10):1730-1737. PubMedhttps://doi.org/10.3324/haematol.2010.024778Google Scholar
- Paino T, Ocio EM, Paiva B. CD20 positive cells are undetectable in the majority of multiple myeloma cell lines and are not associated with a cancer stem cell phenotype. Haematologica. 2012; 97(7):1110-1114. PubMedhttps://doi.org/10.3324/haematol.2011.057372Google Scholar
- Paíno T, Sarasquete ME, Paiva B. Phenotypic, genomic and functional characterization reveals no differences between CD138++ and CD138low subpopulations in multiple myeloma cell lines. PLoS One. 2014; 9(3):e92378. PubMedhttps://doi.org/10.1371/journal.pone.0092378Google Scholar
- Van Valckenborgh E, Matsui W, Agarwal P. Tumor-initiating capacity of CD138− and CD138+ tumor cells in the 5T33 multiple myeloma model. Leukemia. 2012; 26(6):1436-1439. PubMedhttps://doi.org/10.1038/leu.2011.373Google Scholar
- Hosen N. Multiple myeloma-initiating cells. Int J Hematol. 2013; 97(3):306-312. PubMedhttps://doi.org/10.1007/s12185-013-1293-0Google Scholar
- Tanno T, Lim Y, Wang Q. Growth differentiating factor 15 enhances the tumor-initiating and self-renewal potential of multiple myeloma cells. Blood. 2014; 123(5):725-733. PubMedhttps://doi.org/10.1182/blood-2013-08-524025Google Scholar
- Christensen JH, Jensen PV, Kristensen IB. Characterization of potential CD138 negative myeloma “stem cells”. Haematologica. 2012; 97(6):e18-20. PubMedhttps://doi.org/10.3324/haematol.2011.043125Google Scholar
- Schmidt-Hieber M, Paivia B, Perez-Andres M. CD56+ Clonal Plasma Cells In Multiple Myeloma Are Associated With Unique Disease Characteristics and Have a Counterpart Of CD56+ Normal Plasma Cells With Increased Maturity. Blood. 2013; 122(21):751. Google Scholar
- Bøgsted M, Holst JM, Fogd K. Generation of a predictive melphalan resistance index by drug screen of B-cell cancer cell lines. PLoS One. 2011; 6(4):e19322. PubMedhttps://doi.org/10.1371/journal.pone.0019322Google Scholar
- Bøgsted M, Bilgrau AE, Wardell CP. Proof of the concept to use a malignant B cell line drug screen strategy for identification and weight of melphalan resistance genes in multiple myeloma. PLoS One. 2013; 8(12):e83252. PubMedhttps://doi.org/10.1371/journal.pone.0083252Google Scholar
- Falgreen S, Laursen MB, Bødker JS. Exposure time independent summary statistics for assessment of drug dependent cell line growth inhibition. BMC Bioinformatics. 2014; 15:168. PubMedhttps://doi.org/10.1186/1471-2105-15-168Google Scholar
- Laursen MB, Falgreen S, Bødker JS. Human B-cell cancer cell lines as a preclinical model for studies of drug effect in diffuse large B-cell lymphoma and multiple myeloma. Exp Hematol. 2014; 42(11):927-938. PubMedhttps://doi.org/10.1016/j.exphem.2014.07.263Google Scholar
- Kjeldsen MK, Perez-Andres M, Schmitz A. Multiparametric flow cytometry for identification and fluorescence activated cell sorting of five distinct B-cell subpopulations in normal tonsil tissue. Am J Clin Pathol. 2011; 136(6):960-969. PubMedhttps://doi.org/10.1309/AJCPDQNP2U5DZHVVGoogle Scholar
- Bergkvist KS, Nyegaard M, Bøgsted M. Validation and implementation of a method for microarray gene expression profiling of minor B-cell subpopulations in man. BMC Immunol. 2014; 15:3. Google Scholar
- Johnsen HE, Bergkvist KS, Schmitz A. Cell of origin associated classification of B-cell malignancies by gene signatures of the normal B-cell hierarchy. Leuk Lymphoma. 2014; 55(6):1251-1260. Google Scholar
- Johnsen HE, Bødker JS, Schmitz A. A Multiple Myeloma Classification System That Associates Normal Bone Marrow B-Cell Subset Phenotypes with Disease Stage and Prognosis. Blood. 2014; 124(21):3352. Google Scholar
- Paiva B, Pérez-Andrés M, Vídriales MB. Competition between clonal plasma cells and normal cells for potentially overlapping bone marrow niches is associated with a progressively altered cellular distribution in MGUS vs myeloma. Leukemia. 2011; 25(4):697-706. PubMedhttps://doi.org/10.1038/leu.2010.320Google Scholar
- Perez-Andres M, Paiva B, Nieto WG, Caraux A. Human peripheral blood B-cell compartments: a crossroad in B-cell traffic. Cytometry B Clin Cytom. 2010; 78(Suppl 1):S47-60. PubMedGoogle Scholar
- Ross FM, Avet-Loiseau H, Ameye G. Report from the European Myeloma Network on interphase FISH in multiple myeloma and related disorders. Haematologica. 2012; 97(8):1272-1277. PubMedhttps://doi.org/10.3324/haematol.2011.056176Google Scholar
- Caraux A, Klein B, Paiva B. Circulating human B and plasma cells. Age-associated changes in counts and detailed characterization of circulating normal CD138− and CD138+ plasma cells. Haematologica. 2010; 95(6):1016-1020. PubMedhttps://doi.org/10.3324/haematol.2009.018689Google Scholar
- Johnsen HE, Kjeldsen MK, Urup T. Cancer stem cells and the cellular hierarchy in haematological malignancies. Eur J Cancer. 2009; 45(Suppl 1):194-201. Google Scholar
- Rawstron AC, Orfao A, Beksac M. Report of the European Myeloma Network on multiparametric flow cytometry in multiple myeloma and related disorders. Haematologica. 2008; 93(3):431-438. PubMedhttps://doi.org/10.3324/haematol.11080Google Scholar
- Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011; 144(5):646-674. PubMedhttps://doi.org/10.1016/j.cell.2011.02.013Google Scholar
- O’Brien CA, Kreso A, Jamieson CH. Cancer stem cells and self-renewal. Clin Cancer Res. 2010; 16(12):3113-3120. PubMedhttps://doi.org/10.1158/1078-0432.CCR-09-2824Google Scholar
- Cenci S, van Anken E, Sitia R. Proteostenosis and plasma cell pathophysiology. Curr Opin Cell Biol. 2011; 23(2):216-222. PubMedhttps://doi.org/10.1016/j.ceb.2010.11.004Google Scholar
- Morrison SJ, Kimble J. Asymmetric and symmetric stem-cell divisions in development and cancer. Nature. 2006; 441(7097):1068-1074. PubMedhttps://doi.org/10.1038/nature04956Google Scholar
- Keats JJ, Chesi M, Egan JB. Clonal competition with alternating dominance in multiple myeloma. Blood. 2012; 120(5):1067-1076. PubMedhttps://doi.org/10.1182/blood-2012-01-405985Google Scholar
- Egan JB, Shi CX, Tembe W. Whole-genome sequencing of multiple myeloma from diagnosis to plasma cell leukemia reveals genomic initiating events, evolution, and clonal tides. Blood. 2012; 120(5):1060-1066. PubMedhttps://doi.org/10.1182/blood-2012-01-405977Google Scholar
- Walker BA, Wardell CP, Melchor L. Intraclonal heterogeneity and distinct molecular mechanisms characterize the development of t(4;14) and t(11;14) myeloma. Blood. 2012; 120(5):1077-1086. PubMedhttps://doi.org/10.1182/blood-2012-03-412981Google Scholar
- Walker BA, Wardell CP, Melchor L. Intraclonal heterogeneity is a critical early event in the development of myeloma and precedes the development of clinical symptoms. Leukemia. 2014; 28(2):384-390. PubMedhttps://doi.org/10.1038/leu.2013.199Google Scholar
- Moignard V, Macaulay IC, Swiers G. Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis. Nat Cell Biol. 2013; 15(4):363-372. PubMedhttps://doi.org/10.1038/ncb2709Google Scholar
- Melchor L, Brioli A, Wardell CP. Single-cell genetic analysis reveals the composition of initiating clones and phylogenetic patterns of branching and parallel evolution in myeloma. Leukemia. 2014; 28(8):1705-1715. PubMedhttps://doi.org/10.1038/leu.2014.13Google Scholar
- Vicente-Dueñas C, Romero-Camarero I, González-Herrero I. A novel molecular mechanism involved in multiple myeloma development revealed by targeting MafB to haematopoietic progenitors. EMBO J. 2012; 31(18):3704-3717. PubMedhttps://doi.org/10.1038/emboj.2012.227Google Scholar
- Asai T, Hatlen MA, Lossos C. Generation of a novel, multi-stage, progressive, and transplantable model of plasma cell neoplasms. Sci Rep. 2016; 6:22760. Google Scholar
- Mitsiades CS, Anderson KC, Carrasco DR. Mouse models of human myeloma. Hematol Oncol Clin North Am. 2007; 21(6):viii-1069. PubMedhttps://doi.org/10.1016/j.hoc.2007.08.003Google Scholar
- McMillin DW, Negri JM, Mitsiades CS. The role of tumour-stromal interactions in modifying drug response: challenges and opportunities. Nat Rev Drug Discov. 2013; 12(3):217-228. PubMedhttps://doi.org/10.1038/nrd3870Google Scholar
- Li X, Nadauld L, Ootani A. Oncogenic transformation of diverse gastrointestinal tissues in primary organoid culture. Nat Med. 2014; 20(7):769-777. PubMedhttps://doi.org/10.1038/nm.3585Google Scholar
- Cantrell MA, Kuo CJ. Organoid modeling for cancer precision medicine. Genome Med. 2015; 7(1):32. Google Scholar
- Gracz AD, Williamson IA, Roche KC. A high-throughput platform for stem cell niche co-cultures and downstream gene expression analysis. Nat Cell Biol. 2015; 17(3):340-349. PubMedhttps://doi.org/10.1038/ncb3104Google Scholar
- Reya T, Morrison S, Clarke M, Weissman I. Stem cells, cancer, and cancer stem cells. Nature. 2001; 414(6859):105-111. PubMedhttps://doi.org/10.1038/35102167Google Scholar
- Takebe N, Harris PJ, Warren RQ, Ivy SP. Targeting cancer stem cells by inhibiting Wnt, Notch, and Hedgehog pathways. Nat Rev Clin Oncol. 2011; 8(2):97-106. PubMedhttps://doi.org/10.1038/nrclinonc.2010.196Google Scholar
- Takebe N, Miele L, Harris PJ. Targeting Notch, Hedgehog, and Wnt pathways in cancer stem cells: clinical update. Nat Rev Clin Oncol. 2015; 12(8):445-464. PubMedhttps://doi.org/10.1038/nrclinonc.2015.61Google Scholar
- Bonnet D, Dick JE. Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat Med. 1997; 3(7):730-7. PubMedhttps://doi.org/10.1038/nm0797-730Google Scholar
- Shlush LI, Zandi S, Mitchell A. Identification of pre-leukaemic haematopoietic stem cells in acute leukaemia. Nature. 2014; 506(7488):328-333. PubMedhttps://doi.org/10.1038/nature13038Google Scholar
- Eppert K, Takenaka K, Lechman ER. Stem cell gene expression programs influence clinical outcome in human leukemia. Nat Med. 2011; 17(9):1086-1093. PubMedhttps://doi.org/10.1038/nm.2415Google Scholar
- Potter NE, Ermini L, Papaemmanuil E. Single-cell mutational profiling and clonal phylogeny in cancer. Genome Res. 2013; 23(12):2115-2125. PubMedhttps://doi.org/10.1101/gr.159913.113Google Scholar
- Leung-Hagesteijn C, Erdmann N, Cheung G. Xbp1s-negative tumor B cells and pre-plasmablasts mediate therapeutic proteasome inhibitor resistance in multiple myeloma. Cancer Cell. 2013; 24(3):289-304. PubMedhttps://doi.org/10.1016/j.ccr.2013.08.009Google Scholar
- Lawson MA, McDonald MM, Kovacic N. Osteoclasts control reactivation of dormant myeloma cells by remodelling the endosteal niche. Nat Commun. 2015; 6:8983. Google Scholar
- Rasmussen T, Kuehl M, Lodahl M, Johnsen HE, Dahl IM. Possible roles for activating RAS mutations in the MGUS to MM transition and in the intramedullary to extramedullary transition in some plasma cell tumors. Blood. 2005; 105(1):317-323. PubMedhttps://doi.org/10.1182/blood-2004-03-0833Google Scholar
- Rasmussen T, Theilgaard-Mönch K, Hudlebusch HR, Lodahl M, Johnsen HE, Dahl IM. Occurrence of dysregulated oncogenes in primary plasma cells representing consecutive stages of myeloma pathogenesis: indications for different disease entities. Br J Haematol. 2003; 123(2):253-262. PubMedhttps://doi.org/10.1046/j.1365-2141.2003.04577.xGoogle Scholar
- Walker BA, Boyle EM, Wardell CP. Mutational Spectrum, Copy Number Changes, and Outcome: Results of a Sequencing Study of Patients With Newly Diagnosed Myeloma. J Clin Oncol. 2015; 33(33):3911-3920. PubMedhttps://doi.org/10.1200/JCO.2014.59.1503Google Scholar
- Paíno T, Paiva B, Sayagués JM. Phenotypic identification of subclones in multiple myeloma with different chemoresistant, cytogenetic and clonogenic potential. Leukemia. 2015; 29(5):1186-1194. PubMedhttps://doi.org/10.1038/leu.2014.321Google Scholar