Whole-Exome Sequencing Identifies the VHL Mutation (c.262T > C, p.Try88Arg) in Non-Obstructive Azoospermia-Associated Cystic Renal Cell Carcinoma
Bibliographic record
Abstract
Von Hippel-Lindau (VHL) genes are intimately involved in renal cell carcinoma (RCC), including clear cell RCC (ccRCC) pathogenesis. However, the contribution of pathogenic VHL mutations to ccRCC remains poorly understood. We report a xanthoderm with non-obstructive azoospermia (NOA)-associated cystic ccRCC, and the missense VHL mutation (c.262T > C, p.Try88Arg). In a 34-year-old patient, a urologic physical examination identified hard epididymis, and imaging tests revealed deferens-associated NOA, as well as multi-organ hydatid cysts, including bilateral epididymal cysts, bilateral testicular cysts, bilateral renal cysts, and pancreatic cysts. Five years later, ccRCC was developed based on clinical and radiologic evidence. Two different prediction models of protein structure and multiple sequence alignment across species were applied to assess the pathological effects of the VHL mutation. The reliability of the assessment in silico was determined by both the cellular location and protein levels of the mutant products, using IF and Western blot, respectively. Our study shows that the missense VHL mutation (c.262T > C, p.Try88Arg) plays a deleterious role in pVHL functions, as predicted by multiple sequence alignment across species. While a structural analysis identified no significant structural alterations in pVHL, the detrimental effects of this mutation were determined by exogenous expression, evidenced by a markedly different spatial distribution and reduced expression of mutant pVHL. This is the first report of the VHL gene mutation (c.475T > C, p.Try88Arg) in a xanthoderm.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".