Molecular profile of atypical Leydig cell tumours
Bibliographic record
Abstract
AIMS: To investigate histological and copy number variations (CNVs) in Leydig cell tumours (LCTs) of the testis. Although usually benign, a small minority of cases can be associated with a poor prognosis and metastasis. METHODS: We performed whole copy number analysis to compare the genomic profile of atypical (defined by the presence of any atypical features) versus benign LCTs. Our sample consisted of one malignant (with biopsy-proven metastasis), five atypical and five benign cases. RESULTS: We found increased genomic instability in the malignant tumour and within two out of five (40%) atypical cases. One benign case revealed a likely pathogenic mutation in the neurofibromatosis type 2 gene, but all benign cases lacked genomic instability. Apart from the malignant case (which had metastatic spread to the scrotal skin), all remaining atypical cases did not reveal evidence of recurrence or metastatic spread. CONCLUSION: CNVs by themselves are not sufficient to discriminate between cases that are benign versus those with malignant potential, without the use of histomorphological parameters. Genomic instability was only detected in the malignant and atypical cases, and not in any of the benign tumours. Thus, genomic instability may represent an early step in malignant progression. The presence of metastasis remains the only malignant criterion for LCTs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".