The combination of pan-ErbB tyrosine kinase inhibitor CI-1033 and lovastatin: A potential novel therapeutic approach in squamous cell carcinoma of the head and neck
Bibliographic record
Abstract
The ErbB family of receptors are key regulators of growth, differentiation, migration and survival of epithelial cells. CI-1033 is an irreversible pan-ErbB tyrosine kinase inhibitor that has the ability to inhibit EGFR function but has shown limited therapeutic efficacy. Lovastatin targets the activity of HMG-CoA reductase, the rate-limiting step in the mevalonate pathway. In this study, the ability of lovastatin to potentiate the cytotoxic effects of CI-1033 was evaluated. The combination of lovastatin and CI-1033 exhibited some cooperative cytotoxic activity in a squamous cell carcinoma–derived cell line. This combination resulted in enhanced cell death by induction of a potent apoptotic response. Furthermore, this drug combination inhibited EGF-induced EGFR autophosphorylation and activation of the downstream signaling effectors, ERK and AKT. These findings suggest that combining lovastatin and tyrosine kinase inhibitors may represent a novel combinational therapeutic approach in squamous cell carcinoma of the head and neck.
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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) | 0.002 | 0.001 |
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".