Epidermal Growth Factor–Independent Transformation of Ba/F3 Cells with Cancer-Derived Epidermal Growth Factor Receptor Mutants Induces Gefitinib-Sensitive Cell Cycle Progression
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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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".