BMS-754807 is cytotoxic to non-small cell lung cancer cells and enhances the effects of platinum chemotherapeutics in the human lung cancer cell line A549
Bibliographic record
Abstract
BACKGROUND: Despite advances in targeted therapy for lung cancer, survival for patients remains poor and lung cancer remains the leading cause of cancer-related deaths worldwide. The type I insulin-like growth factor receptor (IGF-IR) has emerged as a potential target for lung cancer treatment, however, clinical trials to date have provided disappointing results. Further research is needed to identify if certain patients would benefit from IGF-IR targeted therapies and the ideal approach to incorporate IGF-IR targeted agents with current therapies. METHODS: The dual IGF-IR/insulin receptor inhibitor, BMS-754807, was evaluated alone and in combination with platinum-based chemotherapeutics in two human non-small cell lung cancer (NSCLC) cell lines. Cell survival was determined using WST-1 assays and drug interaction was evaluated using Calcusyn software. Proliferation and apoptosis were determined using immunofluorescence for phospho-histone H3 and cleaved caspase 3, respectively. RESULTS: Treatment with BMS-754807 alone reduced cell survival and wound closure while enhancing apoptosis in both human lung cancer cell lines. These effects appear to be mediated through IGF-IR/IR signaling and, at least in part, through the PI3K/AKT pathway as administration of BMS-754807 to A549 or NCI-H358 cells significantly suppressed IGF-IR/IR and AKT phosphorylation. In addition of BMS-754807 enhanced the cytotoxic effects of carboplatin or cisplatin in a synergistic manner when given simultaneously to A549 cells. CONCLUSIONS: BMS-754807 may be an effective therapeutic agent for the treatment of NSCLC, particularly in lung cancer cells expressing high levels of IGF-IR.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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".