A novel epidermal growth factor receptor-signaling platform and its targeted translation in pancreatic cancer
Why this work is in the frame
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Bibliographic record
Abstract
Epidermal growth factor (EGF)-induced EGFR tyrosine kinase receptor activation in cancer cell survival responses has become a strategic molecular-targeting clinical therapeutic intent, but the failures of these targeted approaches in the clinical setting demand alternate strategies. Here, we uncover a novel neuraminidase-1 (Neu1) and matrix metalloproteinase-9 (MMP-9) cross-talk in alliance with GPCR neuromedin B, which is essential for EGF-induced receptor activation and cellular signaling. Neu1 and MMP-9 form a complex with EGFR on the cell surface. Tamiflu (oseltamivir phosphate), anti-Neu1 antibodies, broad range MMP inhibitor galardin (GM6001), neuromedin B GPCR specific antagonist BIM-23127, the selective inhibitor of whole heterotrimeric G-protein complex BIM-46174 and MMP-9 specific inhibitor dose-dependently inhibited Neu1 activity associated with EGF stimulated 3T3-hEGFR cells. Tamiflu, anti-Neu1 antibodies and MMP9i attenuated EGFR phosphorylation associated with EGF-stimulated cells. Preclinical data provide the proof-of-evidence for a therapeutic targeting of Neu1 with Tamiflu in impeding human pancreatic cancer growth and metastatic spread in heterotopic xenografts of eGFP-MiaPaCa-2 tumors growing in RAGxCγ double mutant mice. Tamiflu-treated cohort exhibited a reduction of phosphorylation of EGFR-Tyr1173, Stat1-Tyr701, Akt-Thr308, PDGFRα-Tyr754 and NFκBp65-Ser311 but an increase in phospho-Smad2-Ser465/467 and -VEGFR2-Tyr1175 in the tumor lysates from the xenografts of human eGFP-MiaPaCa-2 tumor-bearing mice. The findings identify a novel promising alternate therapeutic treatment of human pancreatic cancer.
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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 | 0.000 | 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) | 0.002 | 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