Abstract #5446: Mechanisms of myocyte cytotoxicity induced by the anticancer serine/threonine multikinase inhibitor sorafenib
Bibliographic record
Abstract
The anticancer serine/threonine multikinase inhibitor sorafenib has recently been shown to be cardiotoxic. Using a neonatal rat myocyte model we investigated various mechanisms that might be responsible for its cardiotoxicity. It had been hypothesized that inhibition of RAF1 and BRAF kinases may be responsible for sorafenib-induced cardiotoxicity. As measured by lactate dehydrogenase release sorafenib treatment of myocytes caused dose-dependent damage at therapeutically relevant concentrations. Heart tissue with its high energy needs might be particularly sensitive to inhibition of critical kinases. At longer times (15 hr) sorafenib treatment of myocytes also reduced cellular ATP levels at pharmacological concentrations. Likewise, at longer times sorafenib treatment induced caspase 3/7 activity which was suggestive of induction of apoptosis. Dexrazoxane, which is a clinically approved doxorubicin cardioprotective agent did not protect myocytes from damage, which suggests that sorafenib did not damage myocytes through induction of oxidative damage. In a published profiling study of sorafenib binding to 317 kinases at therapeutic concentrations, sorafenib was found to strongly bind to 18% of the kinases tested. In conclusion, given the extreme lack of kinase selectivity that sorafenib exhibits it is likely that inhibition of other kinases or combinations of kinases also contribute to the cardiotoxic effects of sorafenib. Support: CIHR and a Canada Research Chair in Drug Development to BBH. Citation Information: In: Proc Am Assoc Cancer Res; 2009 Apr 18-22; Denver, CO. Philadelphia (PA): AACR; 2009. Abstract nr 5446.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".