Proteomic identification of a role for the von Hippel Lindau tumour suppressor in changes in the expression of mitochondrial proteins and septin 2 in renal cell carcinoma
Bibliographic record
Abstract
The von Hippel Lindau (VHL) tumour suppressor gene, VHL, plays a central role in development of sporadic conventional renal cell carcinomas (RCCs). Studying VHL function may, therefore, increase understanding of the pathogenesis of RCC and identify markers/therapeutic targets. Comparison of 2-DE protein profiles of VHL-defective RCC cells (UMRC2) transfected with control vector or wild-type VHL showed differences in 30 proteins, including several novel changes. One of the findings confirmed by Western blotting was up-regulation of the mitochondrial protein ubiquinol cytochrome c reductase complex core protein 2 following VHL transfection, a change that was also observed in two other cell line backgrounds. A marked decrease in expression of this and several other mitochondrial proteins was demonstrated in RCC tissues and using VHL-transfectants, several were shown to exhibit VHL-dependent regulation. Thus, VHL may contribute to the decreased mitochondrial function seen in RCC. A form of septin 2 down-regulated following VHL transfection was also identified. Septin 2 was up-regulated in 12/16 RCCs, while alteration of the form present was also observed in 1/3 tumours analysed. Thus, increased expression of septin 2 is a common event in RCC and protein modification may also alter septin 2 function in a subset of 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) | 0.001 | 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".