Niclosamide is a potential candidate for the treatment of chemo-resistant osteosarcoma
Bibliographic record
Abstract
Abstract Chemotherapy is the main treatment option for advanced osteosarcoma, which is the most common type of primary bone malignancy. However, patients develop resistance rapidly and many succumb to the disease. Niclosamide, an anthelmintic drug, has been recently identified to display potent and selective anti-cancer activity. In this work, we show that niclosamide at sub-micromolar concentrations inhibits proliferation and migration, and induces apoptosis in both parental and chemo-resistant osteosarcoma cells, with much less toxicity in normal osteoblastic cells. Interestingly, chemo-resistant osteosarcoma cells are more sensitive to niclosamide compared to parental cells. We further identify that inhibition of β-catenin is the underlying mechanism of niclosamide’s action in osteosarcoma cells. In addition, we reveal that chemo-resistant osteosarcoma cells display increased β-catenin activity compared to parental cells, which might explain the hypersensitivity of chemo-resistant cells to niclosamide. Our work provides pre-clinical evidence that niclosamide can be repurposed for treating osteosarcoma. Our findings also suggest the therapeutic value of β-catenin to overcome osteosarcoma chemo-resistance.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.042 | 0.016 |
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".