Oxygen‐independent degradation of HIF‐α via bioengineered VHL tumour suppressor complex
Bibliographic record
Abstract
Tumour hypoxia promotes the accumulation of the otherwise oxygen-labile hypoxia-inducible factor (HIF)-alpha subunit whose expression is associated with cancer progression, poor prognosis and resistance to conventional radiation and chemotherapy. The oxygen-dependent degradation of HIF-alpha is carried out by the von Hippel-Lindau (VHL) protein-containing E3 that directly binds and ubiquitylates HIF-alpha for subsequent proteasomal destruction. Thus, the cellular proteins involved in the VHL-HIF pathway have been recognized as attractive molecular targets for cancer therapy. However, the various compounds designed to inhibit HIF-alpha or HIF-downstream targets, although promising, have shown limited success in the clinic. In the present study, we describe the bioengineering of VHL protein that removes the oxygen constraint in the recognition of HIF-alpha while preserving its E3 enzymatic activity. Using speckle variance-optical coherence tomography (sv-OCT), we demonstrate the dramatic inhibition of angiogenesis and growth regression of human renal cell carcinoma xenografts upon adenovirus-mediated delivery of the bioengineered VHL protein in a dorsal skin-fold window chamber model. These findings introduce the concept and feasibility of 'bio-tailored' enzymes in the treatment of HIF-overexpressing tumours.
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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) | 0.000 | 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 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".