Novel agent DMAMCL suppresses osteosarcoma growth and decreases the stemness of osteosarcoma stem cell
Bibliographic record
Abstract
Osteosarcoma (OS) is the most common primary malignancy of bone that mostly affects children, adolescents, and young people. Despite advances have been made in multimodal therapy of OS, the long-term survival rate has reached a plateau, and the main obstacles are bad response to chemotherapy and gained chemoresistance. In this study, we tested the therapeutic effect of a newly reported drug, DMAMCL, on OS. Five human OS cell lines (143B, MNNG, MG63, Saos-2, U-2OS), and the mouse fibroblast cell line (NIH3T3) and human retinal epithelial cell (ARPE19) were used. The anti-tumor effect of DMAMCL was studied by MTS assay or IncuCyte-Zoom (in vitro), and Xenograft-mice-model (in vivo). Changes of cell cycle, apoptotic cells, caspase3/7 activities, and stemness after DMAMCL treatment were investigated. BAX siRNAs were used to knockdown the expression of BAX. Expressions of CyclinB1, CDC2, BCL-2 family, PARP, CD133, and Nanog were measured by Western Blotting. DMAMCL-induced dose-dependent OS cell death in vitro, and suppressed tumor growth and extended the survival of xenograft-bearing mice. DMAMCL-induced G2/M phase arrest in vitro, and apoptosis both in vitro and in vivo. Down-regulation of BAX expression attenuated the DMAMCL-induced OS cell death in vitro. We also found that DMAMCL inhibited the stemness in OS cells. These results indicated that DMAMCL possess therapeutic value in OS and may be a promising candidate for the new drug discovery for OS therapy.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".