Differential Dependence of Hypoxia-inducible Factors 1α and 2α on mTORC1 and mTORC2
Bibliographic record
Abstract
Constitutive expression of hypoxia-inducible factor (HIF) has been implicated in several proliferative disorders. Constitutive expression of HIF1 alpha and HIF2 alpha has been linked to a number of human cancers, especially renal cell carcinoma (RCC), in which HIF2 alpha expression is the more important contributor. Expression of HIF1 alpha is dependent on the mammalian target of rapamycin (mTOR) and is sensitive to rapamycin. In contrast, there have been no reports linking HIF2 alpha expression with mTOR. mTOR exists in two complexes, mTORC1 and mTORC2, which are differentially sensitive to rapamycin. We report here that although there are clear differences in the sensitivity of HIF1 alpha and HIF2 alpha to rapamycin, both HIF1 alpha and HIF2 alpha expression is dependent on mTOR. HIF1 alpha expression was dependent on both Raptor (a constituent of mTORC1) and Rictor (a constitutive of mTORC2). In contrast, HIF2 alpha was dependent only on the mTORC2 constituent Rictor. These data indicate that although HIF1 alpha is dependent on both mTORC1 and mTORC2, HIF2 alpha is dependent only on mTORC2. We also examined the dependence of HIF alpha expression on the mTORC2 substrate Akt, which exists as three different isoforms, Akt1, Akt2, and Akt3. Interestingly, the expression of HIF2 alpha was dependent on Akt2, whereas that of HIF1 alpha was dependent on Akt3. Because HIF2 alpha is apparently more critical in RCC, this study underscores the importance of targeting mTORC2 and perhaps Akt2 signaling in RCC and other proliferative disorders in which HIF2 alpha has been implicated.
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 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".