Investigating the role of the von Hippel Lindau protein in tumor suppression through regulation of extracellular matrix assembly
Bibliographic record
Abstract
The VHL disease is a multisystem tumor disorder resulting from inactivation of the von Hippel-Lindau (VHL) tumor suppressor gene. VHL tumors are highly vascularized and can metastasize in the case of renal cell carcinoma (RCC). VHL was shown to operate along at least two evolutionarily conserved pathways with the first involving binding and degradation of hypoxia inducible factor alpha (HIF-alpha) and downregulation of its target genes including transforming growth factor alpha (TGF-alpha) and vascular endothelial growth factor (VEGF). This results in suppression of tumor growth and angiogenesis. The second less extensively studied pathway involves regulation of the extracellular matrix (ECM), which is the main focus of this thesis. We investigate the dependence of the VHL-ECM pathway on HIF and show, using in vitro and in vivo models that VHL leads to ECM assembly in a HIF-independent manner. We find that loss of the VHL-ECM pathway correlates with increased angiogenesis, tumorigenesis and tissue invasion. Our results lead to the identification of a novel VHL binding partner, collagen IV alpha 2 (COL4A2). We find this interaction to be direct and mediated by ER hydroxylation. We observe the VHL-COL4A2 interaction to occur at the ER prior to collagen IV secretion, leading to collagen IV network formation. Loss of this interaction is associated with matrix metalloproteinase (MMP-2) activation, collagen IV remodeling and correlates with increased invasiveness and angiogenic tumor formation. We conclude that COL4A2 is the mediator of the VHL-ECM pathway. Collectively, these results provide an exciting venue linking the VHL tumor suppressor protein to ECM regulation and emphasize the importance of the VHL-COL4A2 interaction in suppression of tumorigenesis and angiogenesis in the VHL disease.
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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".