RET Oncogene Activation in Papillary Thyroid Carcinoma
Bibliographic record
Abstract
The RET proto-oncogene encodes a cell membrane tyrosine-kinase receptor protein whose ligands belong to the glial cell line-derived neurotrophic factor. RET functions as a multicompetent receptor complex that includes alphaGFRs and RET. Somatic rearrangements of RET designated as RET/PTC (from papillary thyroid carcinoma) were identified in papillary thyroid carcinoma before RET was recognized as the susceptibility gene for MEN2. There are now at least at least 15 types of RET/PTC rearrangements involving RET and 10 different genes. RET/PTC1 and RET/PTC3 are by far the most common rearrangements. All of the rearrangements are due to DNA damage and result in the fusion of the RET tyrosine-kinase (RET-TK) domain to the 5'-terminal region of heterologous genes. RET/PTC rearrangements are very common in radiation-induced tumors but have been detected in variable proportions of sporadic (i.e., non-radiation associated) papillary carcinomas. It is estimated that up to approximately half the papillary thyroid carcinomas in the United States and Canada harbor RET/PTC rearrangements, most commonly RET/PTC-1, followed by RET/PTC-3 and occasionally RET/PTC-2. The cause of these rearrangements in sporadic papillary carcinomas is not known, but the close association between their presence and the papillary carcinoma phenotype indicates that they play a causative role in tumor development. The proposed mechanisms of RET/PTC-induced tumorigenesis and the clinical and pathologic implications of RET/PTC activation are discussed.
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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".