Novel <i>PRKD</i> gene rearrangements and variant fusions in cribriform adenocarcinoma of salivary gland origin
Bibliographic record
Abstract
Polymorphous low-grade adenocarcinoma (PLGA) and cribriform adenocarcinoma of minor salivary gland (CAMSG) are low-grade carcinomas arising most often in oral cavity and oropharynx, respectively. Controversy exists as to whether these tumors represent separate entities or variants of one spectrum, as they appear to have significant overlap, but also clinicopathologic differences. As many salivary carcinomas harbor recurrent translocations, paired-end RNA sequencing and FusionSeq data analysis was applied for novel fusion discovery on two CAMSGs and two PLGAs. Validated rearrangements were then screened by fluorescence in situ hybridization (FISH) in 60 cases. Histologic classification was performed without knowledge of fusion status and included: 21 CAMSG, 18 classic PLGA, and 21 with "mixed/indeterminate" features. The RNAseq of 2 CAMSGs showed ARID1A-PRKD1 and DDX3X-PRKD1 fusions, respectively, while no fusion candidates were identified in two PLGAs. FISH for PRKD1 rearrangements identified 11 additional cases (22%), two more showing ARID1A-PRKD1 fusions. As PRKD2 and PRKD3 share similar functions with PRKD1 in the diacylglycerol and protein kinase C signal transduction pathway, we expanded the investigation for these genes by FISH. Six additional cases each showed PRKD2 and PRKD3 rearrangements. Of the 26 (43%) fusion-positive tumors, there were 16 (80%) CAMSGs and 9 (45%) indeterminate cases. A PRKD2 rearrangement was detected in one PLGA (6%). We describe novel and recurrent gene rearrangements in PRKD1-3 primarily in CAMSG, suggesting a possible pathogenetic dichotomy from "classic" PLGA. However, the presence of similar genetic findings in half of the indeterminate cases and a single PLGA suggests a possible shared pathogenesis for these tumor types.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".