Reclassification of two germline DICER1 splicing variants leads to DICER1 syndrome diagnosis
Bibliographic record
Abstract
DICER1 syndrome is an inherited condition associated with an increased risk of developing hamartomatous and neoplastic lesions in diverse organs, mainly at early ages. Germline pathogenic variants in DICER1 cause this condition. Detecting a variant of uncertain significance in DICER1 or finding uncommon phenotypes complicate the diagnosis and can negatively impact patient care. We present two unrelated patients suspected to have DICER1 syndrome. Both females (aged 13 and 15 years) presented with multinodular goiter (thyroid follicular nodular disease) and ovarian tumours. One was diagnosed with an ovarian Sertoli-Leydig cell tumour (SLCT) and the other, with an ovarian juvenile granulosa cell tumour, later reclassified as a retiform variant of SLCT. Genetic screening showed no germline pathogenic variants in DICER1. However, two potentially splicing variants were found, DICER1 c.5365-4A>G and c.5527+3A>G. Also, typical somatic DICER1 RNase IIIb hotspot mutations were detected in the thyroid and ovarian tissues. In silico splicing algorithms predicted altered splicing for both germline variants and skipping of exon 25 was confirmed by RNA assays for both variants. The reclassification of the ovarian tumour, leading to recognition of the association with DICER1 syndrome and the characterization of the germline intronic variants were all applied to recently described DICER1 variant classification rules. This ultimately resulted in confirmation of DICER1 syndrome in the two teenage girls.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".