Targeting aberrant DNA methylation in mesenchymal stromal cells as a treatment for myeloma bone disease

Multiple myeloma (MM) progression and myeloma-associated bone disease (MBD) are highly dependent on bone marrow mesenchymal stromal cells (MSCs). MM-MSCs exhibit abnormal transcriptomes, suggesting the involvement of epigenetic mechanisms governing their tumor-promoting functions and prolonged osteoblast suppression. Here, we identify widespread DNA methylation alterations of bone marrow-isolated MSCs from distinct MM stages, particularly in Homeobox genes involved in osteogenic differentiation that associate with their aberrant expression. Moreover, these DNA methylation changes are recapitulated in vitro by exposing MSCs from healthy individuals to MM cells. Pharmacological targeting of DNMTs and G9a with dual inhibitor CM-272 reverts the expression of hypermethylated osteogenic regulators and promotes osteoblast differentiation of myeloma MSCs. Most importantly, CM-272 treatment prevents tumor-associated bone loss and reduces tumor burden in a murine myeloma model. Our results demonstrate that epigenetic aberrancies mediate the impairment of bone formation in MM, and its targeting by CM-272 is able to reverse MBD.

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Ballestar, Esteban 02/12/2020 Methylation and gene expression array data were processed in the statistical language R. DNA methylation and gene expression array data were obtained from Infinium® MethylationEPIC BeadChip array (Illumina, Inc.) and GeneChip Human Gene 1.0 ST (Affymetrix) respectively. Raw data was processed using R statistical software v4.0 ran in RStudio 1.3 (https://rstudio.com).

October 2018
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All studies must disclose on these points even when the disclosure is negative. No sample size calculation was performed. For in vitro experiments, MSCs from at least 3 independent donors were used, which allowed sufficient data to perform paired student t-tests to determine statistical significance. For mice models, six mice were decided for each experimental group. We believe that this number provided sufficient statistical power, with relatively low standard deviation, for group comparisons. For donor samples, a minimum of 8 donors were recruited in each group. Although this is a relatively small number, it allowed us to generate a linear weighted model for ANOVA analysis. Furthermore, we believe that this number of patients is representative of a larger population.
No data was excluded for the analysis.
Methylation data was validated in an independent cohort of primary MSCs from healthy donors and patients at different MM stages. All attempts at replication were successful.
Samples allocation was not random, as each sample comes from a known specific diagnosis. The effect of each known covariates were first calculated using either Pearson correlation or Wilcoxon signed-rank test depending on whether the covariate of interest was continuous or categorical. In the cases where samples were not matched, specific covariates were imputed in the interaction matrix when generating linear weighted models for group comparisons. Sample hybridization was randomized to minimize batch effects.
Blinding was performed during data collection of microCT samples. Blinding was not possible during data collection, as our experimental design involved the recruitment of age-and sex-matched patients from various dignostic stages of MM. Note that full information on the approval of the study protocol must also be provided in the manuscript.

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