Exploring the Association Between<i>DICER1</i>Mutations and Differentiated Thyroid Carcinoma
Bibliographic record
Abstract
CONTEXT: Carriers of germline DICER1 mutations are predisposed to a rare cancer syndrome, the DICER1 syndrome. Thyroid abnormalities are a common finding in DICER1 syndrome with multinodular goiter frequently present in many families in which a germline DICER1 mutation is segregating. Differentiated thyroid carcinoma (DTC) is infrequently seen in such pedigrees. In addition to germline DICER1 mutations, specific somatic mutations have been identified in the DICER1 ribonuclease IIIb catalytic domain in several tumor types. OBJECTIVE: We aimed to determine whether such characteristic somatic DICER1 mutations are present in DTCs that arise within germline DICER1 mutation carriers. DESIGN AND SETTING: The study involved an opportunistic collection of 3 cases of DTC arising in individuals suspected to have DICER1 syndrome and hospital-based ascertainment and testing was implemented. RESULTS: We identified somatic DICER1 mutations in 3 DTCs arising in unrelated germline DICER1 mutation carriers, all of whom had been diagnosed in infancy with pleuropulmonary blastoma (PPB), were treated with chemotherapy, exposed frequently to diagnostic radiation, and subsequently developed DTC. The somatic mutations occurred within the DICER1 ribonuclease IIIb domain, affecting highly conserved amino acid residues central to the catalytic activity of the domain. CONCLUSION: This report of somatic DICER1 mutations in DTC strengthens the association between DTC and the DICER1 syndrome. The possible association between germline DICER1 mutations, PPB treatment, and the risk of subsequent DTC must be considered by clinicians when treating PPB.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".