Epidermal Growth Factor–Independent Transformation of Ba/F3 Cells with Cancer-Derived Epidermal Growth Factor Receptor Mutants Induces Gefitinib-Sensitive Cell Cycle Progression
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Epidermal growth factor receptor (EGFR) plays critical roles in many biological processes and in tumorigenesis. Here, we show that two mutated EGFRs found in lung and other malignancies, EGFR-G719S and EGFR-L858R, could transform Ba/F3 cells to interleukin-3 (IL-3)-independent growth, in a ligand-independent manner, an activity associated with the transforming function of other mutated tyrosine kinases. The mutated receptors are autophosphorylated in the absence of IL-3 without EGF stimulation, and their expression led to the constitutive activation of signal transducers and activators of transcription 5, extracellular signal-regulated kinase 1/2 (ERK1/2), ERK5, and AKT. In wild-type EGFR-expressing Ba/F3 cells, the major EGF-mediated signaling pathways were still intact. Gefitinib inhibited the growth of mutant EGFR-transformed Ba/F3 cells. Strikingly, the gefitinib sensitivity of cells expressing the L858R mutant was significantly greater than that of cells expressing the G719S mutant form, suggesting that distinct EGFR mutations may be differentially sensitive to small-molecule inhibitors. Furthermore, our data showed an antiproliferative effect of gefitinib on the EGFR-transformed Ba/F3 cells. Our results provide a model system to study the function of mutated EGFR and the differential effects of pharmacologic EGFR inhibition on the distinct mutant forms of this tyrosine kinase.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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