Dominant-Negative HIF-3α4 Suppresses VHL-Null Renal Cell Carcinoma Progression
Bibliographic record
Abstract
The most prevalent mutations associated with the development of clear-cell renal cell carcinoma (CC-RCC) are the loss-of-function mutations of von Hippel-Lindau (VHL) tumor suppressor gene. These mutations invariably result in an inappropriate accumulation of HIF-alpha due to a failure of VHL as a substrate-recognition component of an E3 ubiquitin ligase complex to target HIFalpha for oxygen-dependent ubiquitin-mediated destruction. Stabilization of HIF-2alpha, but not HIF-1alpha, is the critical oncogenic event upon the functional loss of VHL in the development of CC-RCC. Here, we show that HIF-3alpha4, an alternatively spliced variant of human HIF-3alpha with similar domain structure as the murine inhibitory PAS protein (IPAS), forms an abortive transcriptional complex with HIF-2alpha and prevents the engagement of HIF-2 to the hypoxia-responsive elements (HREs) located in the promoter/ enhancer regions of hypoxia-inducible genes. In addition, the re-expression of HIF-3alpha4 in VHL-null 786-O CC-RCC cells via adenovirus decreases the endogenous expression of HIF-2-driven gene expression and suppresses the growth of 786-O tumor xenografts in SCID mice. These results suggest that HIF-3alpha4 is a naturally occurring dominant-negative HIF-3alpha splice isoform with tumor suppressive activity and support the targeted delivery of HIF-3alpha4 as a potential therapeutic option to curtail HIF-dependent tumor progression.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".