Inhibition of copper chaperones sensitizes human and canine osteosarcoma cells to carboplatin chemotherapy
Bibliographic record
Abstract
Osteosarcoma (OSA) is the most common primary bone cancer in children, adolescents and dogs. Current combination surgical and chemotherapeutic treatments have increased survival. However, in recurrent or metastatic disease settings, the prognosis significantly decreases, representing an urgent need for better second-line and novel chemotherapeutics. The current gold standard for combination chemotherapy in OSA often includes a platinum agent, for example, cisplatin or carboplatin. These platinum agents are shuttled within the cell via copper transporters. Recent interest in targeting copper transport has been directed towards antioxidant protein 1 (Atox1) and copper chaperone for superoxide dismutase 1 (CCS), with Atox1 demonstrating the ability to aggregate platinum agents, preventing them from forming DNA adducts. DC_AC50 is a small molecule inhibitor of both Atox1 and CCS. To assess the impact of targeting these pathways on chemotherapy response, two human and two canine OSA cell lines were utilized. After treatment with single agent or combination drugs, cell viability was evaluated and pharmacological synergism calculated using the combination index method. Apoptosis, cell cycle distribution, clonogenic survival and migration were also evaluated. DC_AC50 synergised with carboplatin in combination treatment of human and canine OSA cells to reduce cancer cell viability. DC_AC50-treated cells were significantly less mitotically active, as demonstrated by decreased expression of phospho-histone H3 and cell cycle analysis. DC_AC50 also potentiated carboplatin-induced apoptosis in OSA cells and decreased clonogenic survival. Finally, DC_AC50 reduced the migratory ability of OSA cells. These results justify further investigation into inhibiting intracellular copper chaperones as a means of reducing/preventing acquired chemotherapy 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 | 0.000 |
| 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".