Fer Protein-Tyrosine Kinase Promotes Lung Adenocarcinoma Cell Invasion and Tumor Metastasis
Bibliographic record
Abstract
UNLABELLED: Epidermal growth factor receptor (EGFR) is frequently amplified or mutated in non-small cell lung cancer (NSCLC). Although Fer protein-tyrosine kinase signals downstream of EGFR, its role in NSCLC tumor progression has not been reported. Here, Fer kinase was elevated in NSCLC tumors compared to normal lung epithelium. EGFR signaling in NSCLC cells fosters rapid Fer activation and increased localization to lamellipodia. Stable silencing of Fer in H1299 lung adenocarcinoma cells (Fer KD) caused impaired EGFR-induced lamellipodia formation compared to control cells. Fer KD NSCLC cells showed reduced Vav2 tyrosine phosphorylation that was correlated with direct Fer-mediated phosphorylation of Vav2 on tyrosine-172, which was previously reported to increase the guanine nucleotide exchange factor activity of Vav2. Indeed, Fer KD cells displayed defects in Rac-GTP localization to lamellipodia, cell migration, and cell invasion in vitro. To test the role of Fer in NSCLC progression and metastasis, control and Fer KD cells were grown as subcutaneous tumors in mice. Although Fer was not required for tumor growth, Fer KD tumor-bearing mice had significantly fewer numbers of spontaneous metastases. Combined, these data demonstrate that Fer kinase is elevated in NSCLC tumors and is important for cellular invasion and metastasis. IMPLICATIONS: Fer protein-tyrosine kinase is a potential therapeutic target in metastatic lung cancer. Mol Cancer Res; 11(8); 952-63. ©2013 AACR.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".