Growth Factor-Mediated Induction of HDM2 Positively Regulates Hypoxia-Inducible Factor 1α Expression
Bibliographic record
Abstract
The hypoxia-inducible factor 1 (HIF-1) transcriptional complex is regulated by cellular oxygen levels and growth factors. The phosphoinosotide 3-kinase (PI-3K)-Akt/protein kinase B (PKB) pathway has been shown to regulate HIF-1 activity in response to oncogenic signals and growth factors. We assessed whether the HDM2 oncoprotein, a direct target of Akt/PKB, could regulate HIF-1alpha expression and HIF-1 activity under normoxic conditions. We found that growth factor stimulation, overexpression of Akt/PKB, or loss of PTEN resulted in enhanced expression of both HIF-1alpha and HDM2. Growth factor-mediated induction of HIF-1alpha was ablated by transient expression of a dominant negative form of Akt/PKB or by treatment with LY294002. Transient expression of HDM2 led to increased expression of HIF-1alpha. Pulse-chase and cycloheximide experiments revealed that HDM2 did not significantly affect the half-life of HIF-1alpha. Growth factor-induced HIF-1alpha and HDM2 proteins were localized to the nucleus, and induction of both proteins was observed in both p53(+/+) and p53(-/-) HCT116 cells to comparable levels. Importantly, insulin-like growth factor 1-induced HIF-1alpha expression was observed in p53-null mouse embryo fibroblasts (MEFs) but was significantly impaired in p53 Mdm2 double-null MEFs, indicating a requirement for Mdm2 in this process. Finally, we showed that phosphorylation at Ser166 in HDM2 contributed in part to growth factor-mediated induction of HIF-1alpha. Our study has important implications for the role of the PI-3K-Akt/PKB-HDM2 pathway in tumor progression and angiogenesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".