Multiple Myeloma Exemplifies a Model of Cancer Based on Tissue Disruption as the Initiator Event

Abstract

The standard model of multiple myeloma (MM) oncogenesis is based on the genetic instability of MM cells and presents its evolution as the emergence of clones with more and more aggressive genotypes, giving them surviving and proliferating advantage. The micro-environment has a passive role. In contrast, many works have shown that the progression of MM is also characterized by the selection of clones with extended phenotypes able to destroy bone trabeculae, suggesting a major role for early micro-environmental disruption. We present a model of MM oncogenesis in which genetic instability is the consequence of the disruption of normal interactions between plasma cells and their environment, the bone remodeling compartment. These interactions, which normally ensure the stability of the genotypes and phenotypes of normal plasma cells could be disrupted by many factors as soon as the early steps of the disease (MGUS, pre-MGUS states). Therapeutical implications of the model are presented.

Multiple Myeloma as a Bone Disease? The Tissue Disruption-Induced Cell Stochasticity (TiDiS) Theory

“…This process could only initiate with a loss of the environmental constraints present in the healthy tissue, whatever genetic alterations are present or not in the cells, because they are known to control the level of cellular stochasticity. This TiDiS theory is supported by much experimental evidence that has been reviewed elsewhere [63][64][65]71], especially in the context of MM [60].…”

“…During the malignant transition from MGUS to overt MM, both mechanisms interact to accentuate the disruption, and facilitate the occurrence of the MM bone disease, not only LBL, but also generalized bone loss, the second component of the MM bone disease (Table 3). We and others have previously emphasized that the natural history of MM includes a pre-MGUS phase, characterized by a hyper-gammaglobulinemia, reactive plasmacytosis (excess of circulating plasmablasts) or even transient MGUS in a context of immune deficiency [60,61]. Genetically altered memory B cells and plasmablasts could expand during such a pre-MGUS stage, because they remain sensitive to both polyclonal B cell activation and specific antigenic activation.…”

“…Much experimental evidence indicates that the normal microenvironment is able to control genetically altered cells and reduce phenotypic plasticity [21,[63][64][65]71]. Thus, mimicking this normal micro-environment with molecules that would mimic healthy cellular interactions, together with molecules stimulating the re-expression of the proteins necessary to interact with these partners, would be efficient in stopping cell proliferation and cancer evolution [60,74].…”

“…In the future, epigenetic-based treatments are clearly adequate for the first step that is to re-establish the initial interactions of MM cells with the BME. In MM, knowing the role of decorins and other interaction proteins in the inhibitory effects of osteoblasts over MM cells [79], providing decorins or "pseudo-decorins" as soluble proteins, and/or promoting osteoblast activity [80][81][82] would be good candidates for the second step [60], which is to mimic their inhibitory effects. Providing such peptides that mimic interactions domains of key environmental proteins could substitute for normal osteoblasts.…”

The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability

“…The perturbation in PMDs occurs at the epigenetic, transcriptomic and 3D organization levels and is responsible for interpatient variability. This disturbance in PMDs could explain, in part, some aberrant and heterogeneous phenotypes across MM samples [57,58]. In addition, the lack of accurate global DNA methylation maintenance also drives intrapatient DNA methylation heterogeneity, which can contribute to intrapatient variability, allowing cell-to-cell diversity in transcriptional programs and opening multiple trajectories in response to therapy (Additional file 3: Figure S25).…”