Recurrent RET Gene Rearrangements in Intraductal Carcinomas of Salivary Gland
Bibliographic record
Abstract
Intraductal carcinoma (IC) is the World Health Organization designation for lesions previously called low-grade cribriform cystadenocarcinoma. The relationship of IC to salivary duct carcinoma (SDC) is controversial, but currently these are considered distinct entities. It is hypothesized that IC and SDC should have different genomic signatures that may be identifiable by next-generation sequencing. A total of 23 ICs were identified: 14 pure IC and 9 invasive carcinomas with an intraductal component. Five invasive carcinomas were subjected to next-generation paired-end RNA sequencing. Data analysis was performed using FusionSeq and Mutation detection algorithms (MuTect and VarScan) for variant callers. Gene fusion candidates were validated by fluorescence in situ hybridization and reverse transcription polymerase chain reaction, and mutations by Sanger sequencing. Among the 9 invasive carcinomas, all except 1 were apocrine SDCs with an intraductal component. The remaining case showed typical intercalated duct type IC with invasive adenocarcinoma. The 14 pure ICs had typical intercalated duct features (2 showed hybrid intercalated/apocrine features). RNA sequencing predicted a NCOA4-RET fusion, confirmed by reverse transcription polymerase chain reaction, in the intercalated duct type IC invasive component. Six additional cases of pure IC showed RET rearrangement by fluorescence in situ hybridization (7/15=47%). No apocrine carcinomas showed RET rearrangement. RNA sequencing and Sanger sequencing identified PIK3CA (p.E545K/p.H1047R) and/or HRAS (p.Q61R) hotspot mutations in 6 of 8 (75%) apocrine carcinomas. In conclusion, 2 distinctive types of intraductal lesions are emerging based on molecular analysis. Classic intercalated type ICs commonly harbor fusions involving RET and rarely show widespread invasion. Apocrine intraductal lesions are typically associated with widespread invasion with no pure examples and show similar PIK3CA and HRAS mutations to SDC.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".