Synergistic inhibition of breast cancer cell lines with a dual inhibitor of EGFR-HER-2/neu and a Bcl-2 inhibitor
Why this work is in the frame
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Bibliographic record
Abstract
The epidermal growth factor receptor (EGFR) (ErbB1) and HER-2/neu (ErbB2) are members of the ErbB family of receptor tyrosine kinases. These receptors are overexpressed in a variety of human tumors and overexpression generally correlates with poor prognosis and decreased survival. Lapatinib, a reversible inhibitor of both EGFR and HER-2/neu, has shown some success in achieving clinical responses in heavily pretreated advanced cancer patients. GW2974 is a reversible dual inhibitor similar to lapatinib, but GW2974 was not progressed to clinical trials due to pharmacokinetic issues. Bcl-2, an anti-apoptotic protein, is also overexpressed in a number of human tumors. Bcl-2 inhibitors induce apoptosis and sensitize cancer cells to other therapies. The purpose of this study was to assess the effects of combining ErbB and Bcl-2 inhibitors on the growth of human breast cancer cell lines. EGFR/HER-2/neu tyrosine kinase inhibitors (lapatinib and GW2974) were combined with Bcl-2 inhibitors (HA14-1 or GX15-070) and the anti-proliferative effects were determined by the MTT tetrazolium dye assay. Combinations were tested in MCF-7 human breast cancer cells, a HER-2/neu transfected MCF-7 cell line (MCF/18), and a tamoxifen-resistant MCF-7 cell line (MTR-3). A synergistic inhibitory effect was observed with the combination of inhibitors of EGFR-HER-2/neu (lapatinib or GW2974) and Bcl-2 (GX15-070 or HA14-1) on the growth of the MCF-7, MCF/18, and MTR-3 human breast cancer cell lines. This study suggests that simultaneously blocking the ErbB family of receptor tyrosine kinases and Bcl-2 family of proteins may be a benefit to breast cancer patients.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it