PERK/eIF2α signaling protects therapy resistant hypoxic cells through induction of glutathione synthesis and protection against ROS
Bibliographic record
Abstract
Hypoxia is a common feature of tumors and an important contributor to malignancy and treatment resistance. The ability of tumor cells to survive hypoxic stress is mediated in part by hypoxia-inducible factor (HIF)-dependent transcriptional responses. More severe hypoxia activates endoplasmatic reticulum stress responses, including the double-stranded RNA-activated protein kinase (PKR)-like endoplasmic reticulum kinase (PERK)/eukaryotic initiation factor 2α (eIF2α)-dependent arm of the unfolded protein response (UPR). Although several studies implicate important roles for HIF and UPR in adaption to hypoxia, their importance for hypoxic cells responsible for therapy resistance in tumors is unknown. By using isogenic models, we find that HIF and eIF2α signaling contribute to the survival of hypoxic cells in vitro and in vivo. However, the eIF2α-dependent arm of the UPR is uniquely required for the survival of a subset of hypoxic cells that determine tumor radioresistance. We demonstrate that eIF2α signaling induces uptake of cysteine, glutathione synthesis, and protection against reactive oxygen species produced during periods of cycling hypoxia. Together these data imply that eIF2α signaling is a critical contributor to the tolerance of therapy-resistant cells that arise as a consequence of transient changes in oxygenation in solid tumors and thus a therapeutic target in curative treatments for solid cancers.
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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) | 0.000 | 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".