Sequencing of DICER1 in sarcomas identifies biallelic somatic DICER1 mutations in an adult-onset embryonal rhabdomyosarcoma
Bibliographic record
Abstract
BACKGROUND: Sarcomas are rare and heterogeneous cancers. We assessed the contribution of DICER1 mutations to sarcoma development. METHODS: The coding region of DICER1 was sequenced in 67 sarcomas using a custom Fluidigm Access Array. The RNase III domains were Sanger sequenced in six additional sarcomas to identify hotspot DICER1 variants. RESULTS: The median age of sarcoma diagnosis was 45.7 years (range: 3 months to 87.4 years). A recurrent embryonal rhabdomyosarcoma (ERMS) of the broad ligament, first diagnosed at age 23 years, harboured biallelic pathogenic somatic DICER1 variants (1 truncating and 1 RNase IIIb missense). We identified nine other DICER1 variants. One somatic variant (p.L1070V) identified in a pleomorphic sarcoma and one germline variant (c.2257-7A>G) may be pathogenic, but the others are considered to be benign. CONCLUSIONS: We show that deleterious DICER1 mutations underlie the genetic basis of only a small fraction of sarcomas, in particular ERMS of the urogenital tract.
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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 | 0.001 |
| 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 | 0.000 | 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".