IRE1 Signaling Is Essential for Ischemia-Induced Vascular Endothelial Growth Factor-A Expression and Contributes to Angiogenesis and Tumor Growth <i>In vivo</i>
Bibliographic record
Abstract
In solid tumors, cancer cells subjected to ischemic conditions trigger distinct signaling pathways contributing to angiogenic stimulation and tumor development. Characteristic features of tumor ischemia include hypoxia and glucose deprivation, leading to the activation of hypoxia-inducible factor-1-dependent signaling pathways and to complex signaling events known as the unfolded protein response. Here, we show that the activation of the endoplasmic reticulum stress sensor IRE1 is a common determinant linking hypoxia- and hypoglycemia-dependent responses to the up-regulation of vascular endothelial growth factor-A (VEGF-A). Tumor cells expressing a dominant-negative IRE1 transgene as well as Ire1alpha-null mouse embryonic fibroblasts were unable to trigger VEGF-A up-regulation upon either oxygen or glucose deprivation. These data correlated with a reduction of tumor angiogenesis and growth in vivo. Our results therefore suggest an essential role for IRE1-dependent signaling pathways in response to ischemia and identify this protein as a potential therapeutic target to control both the angiogenic switch and tumor development.
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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) | 0.000 | 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 | 0.001 |
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".