Tyrosine kinase receptor EGFR regulates the switch in cancer cells between cell survival and cell death induced by autophagy in hypoxia
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
Autophagy is an intracellular lysosomal degradation pathway where its primary function is to allow cells to survive under stressful conditions. Autophagy is, however, a double-edge sword that can either promote cell survival or cell death. In cancer, hypoxic regions contribute to poor prognosis due to the ability of cancer cells to adapt to hypoxia in part through autophagy. In contrast, autophagy could contribute to hypoxia induced cell death in cancer cells. In this study, we showed that autophagy increased during hypoxia. At 4 h of hypoxia, autophagy promoted cell survival whereas, after 48 h of hypoxia, autophagy increased cell death. Furthermore, we found that the tyrosine phosphorylation of EGFR (epidermal growth factor receptor) decreased after 16 h in hypoxia. Furthermore, EGFR binding to BECN1 in hypoxia was significantly higher at 4 h compared to 72 h. Knocking down or inhibiting EGFR resulted in an increase in autophagy contributing to increased cell death under hypoxia. In contrast, when EGFR was reactivated by the addition of EGF, the level of autophagy was reduced which led to decreased cell death. Hypoxia led to autophagic degradation of the lipid raft protein CAV1 (caveolin 1) that is known to bind and activate EGFR in a ligand-independent manner during hypoxia. By knocking down CAV1, the amount of EGFR phosphorylation was decreased in hypoxia and amount of autophagy and cell death increased. This indicates that the activation of EGFR plays a critical role in the switch between cell survival and cell death induced by autophagy in hypoxia.
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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) | 0.001 | 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 it