Transforming Growth Factor β1 Induces Hypoxia-inducible Factor-1 Stabilization through Selective Inhibition of PHD2 Expression
Bibliographic record
Abstract
The hypoxia-inducible transcription factor-1 (HIF-1) is central to a number of pathological processes through the induction of specific genes such as vascular endothelial growth factor (VEGF). Even though HIF-1 is highly regulated by cellular oxygen levels, other elements of the inflammatory and tumor microenvironment were shown to influence its activity under normal oxygen concentration. Among others, recent studies indicated that transforming growth factor (TGF) beta increases the expression of the regulatory HIF-1alpha subunit, and induces HIF-1 DNA binding activity. Here, we demonstrate that TGFbeta acts on HIF-1alpha accumulation and activity by increasing HIF-1alpha protein stability. In particular, we demonstrate that TGFbeta markedly and specifically decreases both mRNA and protein levels of a HIF-1alpha-associated prolyl hydroxylase (PHD), PHD2, through the Smad signaling pathway. As a consequence, the degradation of HIF-1alpha was inhibited as determined by impaired degradation of a reporter protein containing the HIF-1alpha oxygen-dependent degradation domain encompassing the PHD-targeted prolines. Moreover, inhibition of the TGFbeta1 converting enzyme, furin, resulted in increased PHD2 expression, and decreased basal HIF-1alpha and VEGF levels, suggesting that endogenous production of bioactive TGFbeta1 efficiently regulates HIF-1-targeted genes. This was reinforced by results from HIF-1alpha knock-out or HIF-1alpha-inhibited cells that show impairment in VEGF production in response to TGFbeta. This study reveals a novel mechanism by which a growth factor controls HIF-1 stability, and thereby drives the expression of specific genes, through the regulation of PHD2 levels.
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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".