A Transgenic Model Of Multiple Myeloma Bone Disease Shows Profound Mesenchymal Stem Cell Impairment
Bibliographic record
Abstract
Abstract Bone disease affects 70% of Multiple Myeloma (MM) patients during the course of their illness. While new treatments for the MM itself have prolonged their survival, patients are living longer with their bone disease. Bisphophonates have been shown to reduce skeletal related events in MM, but they neither eliminate these events nor reverse skeletal damage. The transgenic mouse model of MM (vk*myc) is the only mouse model that has been shown to faithfully recapitulate the clinical disease, including its bony abnormalities. The original publication of the model showed principally a decrease in bone mineral density of affected animals but scant lytic lesions. We have cross bred this model with a substrain of C56/BL6 mice, KaLwRiJ, that is the basis of a competing model of MM and its bone disease the 5T33 model. This new transgenic substrain shows significant number bony lesions on x-ray and microCT analyses. Immunohistochemistry of the femurs and spines of these animals show an increased number of osteoclast and a decreased number of osteoblasts as compared to non-transgenic wild type mice of the same substrain. Dynamic labeling of bone shows a decreased mineral apposition rate (1.21mm/day ±0.03 vs 2.05mm/day ±0.04) in mice with MM vs wild type mice. In addition to the demineralization associated with MM bone disease and unique to this model, we show a dramatic decrease in the formation of osteoblasts from cultured mesenchymal stem cells (MSCs). These are grown ex-vivo from affected transgenic mice and induced to differentiate into osteoblasts in culture. We demonstrate a close to 90% reduction in observed and quantified mineralized colonies indicating a dramatic impairment in MSC differentiation in these mice, similar to what is seen in human MM. Gene expression profiling analyses using mRNA from ex-vivo mesenchymal stem cells derived from transgenic and wild type mice reveal a number of pathways and genes that can potentially play a role in the inhibition of MSC differentiation in this model. These include the wnt signaling pathway as well as genes involved in histone acetyltransferase activity. The latter suggests that MSCs are ‘permanently’ affected by the presence of MM cells in vivo and that this inhibition does not improve even when they are separated from MM cells for a prolonged period of time. Bortezomib has been shown in MM patients to improve the appearance of MM lytic lesions radiographically as well as to improve serum markers of osteoblastic activity. This improvement is thought to be due to a reversal of MSC differentiation impairment. Wild type and transgenic mice with MM and bone disease were treated with bortezomib (0.5mg/Kg twice per week) for two weeks. CT analyses of mice pre and post bortezomib treatment showed a 28% improvement in the treated transgenic mice. We also show a concomitant improvement in the ex-vivo ability of MSCs to differentiate into osteoblasts. In summary, we present a unique animal model to study MM bone disease that shows profound MSC impairment. This model responds to a treatment strategy that has been shown to work in the human disease and opens itself to further study and use for future developments targeting MM bone disease. Disclosures: No relevant conflicts of interest to declare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".