Overexpression of Smad7 Blocks Primary Tumor Growth and Lung Metastasis Development in Osteosarcoma
Bibliographic record
Abstract
PURPOSE: Osteosarcoma is the main malignant primary bone tumor in children and adolescents for whom the prognosis remains poor, especially when metastasis is present at diagnosis. Because transforming growth factor-β (TGFβ) has been shown to promote metastasis in many solid tumors, we investigated the effect of the natural TGFβ/Smad signaling inhibitor Smad7 and the TβRI inhibitor SD-208 on osteosarcoma behavior. EXPERIMENTAL DESIGN: By using a mouse model of osteosarcoma induced by paratibial injection of cells, we assessed the impact of Smad7 overexpression or SD-208 on tumor growth, tumor microenvironment, bone remodeling, and metastasis development. RESULTS: First, we demonstrated that TGFβ levels are higher in serum samples from patients with osteosarcoma compared with healthy volunteers and that TGFβ/Smad3 signaling pathway is activated in clinical samples. Second, we showed that Smad7 slows the growth of the primary tumor and increases mice survival. We furthermore demonstrated that Smad7 expression does not affect in vitro osteosarcoma cell proliferation but affects the microarchitectural parameters of bone. In addition, Smad7-osteosarcoma bone tumors expressed lower levels of osteolytic factors such as RANKL, suggesting that Smad7 overexpression affects the "vicious cycle" established between tumor cells and bone cells by its ability to decrease osteoclast activity. Finally, we showed that Smad7 overexpression in osteosarcoma cells and the treatment of mice with SD208 inhibit the development of lung metastasis. CONCLUSION: Taken together, these results demonstrate that the inhibition of the TGFβ/Smad signaling pathway may be a promising therapeutic strategy against tumor progression of osteosarcoma, specifically against the development of lung metastasis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".