Upregulation of matrix metalloproteinase‐9 in murine 5T33 multiple myeloma cells by interaction with bone marrow endothelial cells
Bibliographic record
Abstract
MM is a B-cell malignancy mainly characterized by monoclonal expansion of plasma cells in the BM, presence of paraprotein in serum and occurrence of osteolytic bone lesions. MMPs are a family of proteolytic enzymes that can contribute to cancer growth, invasion, angiogenesis, bone degradation and other processes important in the pathogenesis of MM. We investigated MMP-9 production in the 5T33MM murine model. Expression of MMP-9 protein in supernatant and cell extracts was analyzed by gelatin zymography. The in vitro, stroma-independent variant 5T33MMvt showed no protein expression of MMP-9 in contrast to in vivo growing MM cells, 5T33MMvv. However, when 5T33MMvt cells were injected into naive mice and isolated after tumor take (5T33MMvt-vv), they secreted a significant amount of MMP-9. These results were confirmed by specific staining of cytospins with an anti-MMP-9 antibody. The MMP-9 production by 5T33MMvt-vv cells disappeared when the cells were recultured in vitro. These data demonstrated that upregulation of MMP-9 occurs in vivo and that this process is dependent on the microenvironment. Cocultures of 5T33MMvt cells with STR10 BMECs induced MMP-9 in MM cells, as determined by both gelatin zymography and flow-cytometric analysis. In conclusion, our results demonstrate that MMP-9 production by MM cells is upregulated in vivo by the interaction of MM cells with BMECs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".