Transcript Level Modulates the Inherent Oncogenicity of RET/PTC Oncoproteins
Bibliographic record
Abstract
Mutations to the RET proto-oncogene occur in as many as one in three cases of thyroid cancer and have been detected in both the medullary (MTC) and the papillary (PTC) forms of the disease. Of the nearly 400 chromosomal rearrangements resulting in oncogenic fusion proteins that have been identified to date, the rearrangements that give rise to RET fusion oncogenes in PTC remain the paradigm for chimeric oncoprotein involvement in solid tumors. RET-associated PTC tumors are phenotypically indolent and relatively less aggressive than RET-related MTCs. The mechanism(s) contributing to the differences in oncogenicity of RET-related MTC and PTC remains unexplained. Here, through cellular and molecular characterization of the two most common RET/PTC rearrangements (PTC1 and PTC3), we show that RET/PTC oncoproteins are highly oncogenic when overexpressed, with the ability to increase cell proliferation and transformation. Further, RET/PTCs activate similar downstream signaling cascades to wild-type RET, although at different levels, and are relatively more stable as they avoid lysosomal degradation. Absolute quantitation of transcript levels of RET, CCDC6, and NCOA4 (the 5' fusion genes involved in PTC1 and PTC3, respectively) suggest that these rearrangements result in lower RET expression in PTCs relative to MTCs. Together, our findings suggest PTC1 and PTC3 are highly oncogenic proteins when overexpressed, but result in indolent disease compared with RET-related MTCs due to their relatively low expression from the NCOA4 and CCDC6 promoters in vivo.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".