A Multifocal Pediatric Papillary Thyroid Carcinoma (PTC) Harboring the AGK-BRAF and RET/PTC3 Fusion in a Mutually Exclusive Pattern Reveals Distinct Levels of Genomic Instability and Nuclear Organization
Bibliographic record
Abstract
The spectrum and incidence of gene fusions in papillary thyroid carcinoma (PTC) can differ significantly depending on the age of onset, histological subtype or radiation exposure history. In sporadic pediatric PTC, RET/PTC1-3 and AGK-BRAF fusions are common genetic alterations. The role of RET/PTC as a prognostic marker in pediatric PTC is still under investigation. We recently showed that AGK-BRAF fusion is prevalent in young patients (mean 10 years) and associated with specific and aggressive pathological features such as multifocality and lung metastasis. In this pilot study, we report a unique patient harboring three different foci: the first was positive for AGK-BRAF fusion, the second was positive for just RET/PTC3 fusion and the third was negative for both rearrangements. To investigate whether AGK-BRAF and RET/PTC3 are associated with genomic instability and chromatin modifications, we performed quantitative fluorescence in situ hybridization (Q-FISH) of telomere repeats followed by 3D imaging analysis and 3D super-resolution Structured Illumination Microscopy (3D-SIM) to analyze the DNA structure from the foci. We demonstrated in this preliminary study that AGK-BRAF is likely associated with higher levels of telomere-related genomic instability and chromatin remodeling in comparison with RET/PTC3 foci. Our results suggest a progressive disruption in chromatin structure in AGK-BRAF-positive cells, which might explain a more aggressive disease outcome in patients harboring this rearrangement.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".