Lack of <i><scp>PRKD</scp>2</i> and <i><scp>PRKD</scp>3</i> kinase domain somatic mutations in <i><scp>PRKD</scp>1</i> wild‐type classic polymorphous low‐grade adenocarcinomas of the salivary gland
Bibliographic record
Abstract
AIMS: Polymorphous low-grade adenocarcinoma (PLGA) is the second most common intra-oral salivary gland malignancy. The vast majority of PLGAs harbour a PRKD1 E710D hot-spot somatic mutation or somatic rearrangements of PRKD1, PRKD2 or PRKD3. Given the kinase domain homology among PRKD1, PRKD2 and PRKD3, we sought to define whether PLGAs lacking PRKD1 somatic mutations or PRKD gene family rearrangements would be driven by somatic mutations affecting the kinase domains of PRKD2 or PRKD3. METHODS AND RESULTS: DNA was extracted from eight microdissected PLGAs lacking PRKD1 somatic mutations or PRKD gene family rearrangements. Samples were thoroughly centrally reviewed, microdissected and subjected to Sanger sequencing of the kinase domains of the PRKD2 and PRKD3 genes. None of the PLGAs lacking PRKD1 somatic mutations or PRKD gene family rearrangements harboured somatic mutations in the kinase domains of the PRKD2 or PRKD3 genes. CONCLUSION: PLGAs lacking PRKD1 somatic mutations or PRKD gene family rearrangements are unlikely to harbour somatic mutations in the kinase domains of PRKD2 or PRKD3. Further studies are warranted to define the driver genetic events in this subgroup of PLGAs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".