Effects of epidermal growth factor receptor kinase inhibition on radiation response in canine osteosarcoma cells
Bibliographic record
Abstract
BACKGROUND: Radiation therapy is a palliative treatment modality for canine osteosarcoma, with transient improvement in analgesia observed in many cases. However there is room for improvement in outcome for these patients. It is possible that the addition of sensitizing agents may increase tumor response to radiation therapy and prolong quality of life. Epidermal growth factor receptor (EGFR) expression has been documented in canine osteosarcoma and higher EGFR levels have been correlated to a worse prognosis. However, effects of EGFR inhibition on radiation responsiveness in canine osteosarcoma have not been previously characterized. This study examined the effects of the small molecule EGFR inhibitor erlotinib on canine osteosarcoma radiation responses, target and downstream protein expression in vitro. Additionally, to assess the potential impact of treatment on tumor angiogenesis, vascular endothelial growth factor (VEGF) levels in conditioned media were measured. RESULTS: Erlotinib as a single agent reduced clonogenic survival in two canine osteosarcoma cell lines and enhanced the impact of radiation in one out of three cell lines investigated. In cell viability assays, erlotinib enhanced radiation effects and demonstrated single agent effects. Erlotinib did not alter total levels of EGFR, nor inhibit downstream protein kinase B (PKB/Akt) activation. On the contrary, erlotinib treatment increased phosphorylated Akt in these osteosarcoma cell lines. VEGF levels in conditioned media increased after erlotinib treatment as a single agent and in combination with radiation in two out of three cell lines investigated. However, VEGF levels decreased with erlotinib treatment in the third cell line. CONCLUSIONS: Erlotinib treatment promoted modest enhancement of radiation effects in canine osteosarcoma cells, and possessed activity as a single agent in some cell lines, indicating a potential role for EGFR inhibition in the treatment of a subset of osteosarcoma patients. The relative radioresistance of osteosarcoma cells does not appear to be related to EGFR signalling exclusively. Angiogenic responses to radiation and kinase inhibitors are similarly likely to be multifactorial and require further investigation.
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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 | 0.000 |
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".