Synchronous Ovarian Sertoli–Leydig Cell and Clear Cell Papillary Renal Cell Tumors: A Rare Case Without Mutations in Cancer-Associated Genes
Bibliographic record
Abstract
(1) Background: Sertoli-Leydig cell tumors (SLCTs) are rare ovarian neoplasms that account for less than 0.5% of all ovarian tumors. They usually affect young women and often present with androgenic symptoms. We report a unique case of a 40-year-old woman diagnosed with both SLCT and clear cell papillary renal cell carcinoma (CCP-RCC), a rare tumor association with unclear pathogenesis. (2) Methods: Both tumors were treated surgically. The diagnostic workup included hormonal testing, imaging studies, and extensive genetic testing, including DICER1 mutation analysis and multiplex ligation-dependent probe amplification (MLPA), as well as the examination of a next-generation sequencing (NGS) panel covering ~280 cancer-related genes. (3) Results: Histopathologic examination confirmed a well-differentiated SLCT and CCP-RCC. No pathogenic variants in DICER1 were identified by WES or MLPA. No clinically relevant changes were found in the extended NGS panel either, so a known hereditary predisposition could be ruled out. The synchronous occurrence of both tumors without genomic alterations could indicate a sporadic event or as yet unidentified mechanisms. (4) Conclusions: This case highlights the importance of a multidisciplinary approach in the management of rare tumor compounds. The exclusion of DICER1 mutations and the absence of genetic findings adds new evidence to the limited literature and underscores the importance of long-term surveillance and further research into potential shared oncogenic pathways.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".