RET‐mediated gene expression pattern is affected by isoform but not oncogenic mutation
Bibliographic record
Abstract
The inherited cancer syndrome multiple endocrine neoplasia type 2 (MEN 2) is caused by mutations of the RET receptor tyrosine kinase and is characterized by medullary thyroid carcinoma. MEN 2 subtypes have distinct mutational spectrums and vary in severity. The most severe disease subtype, MEN 2B, is associated with a specific RET mutation (M918T) that has been predicted to alter downstream signaling and target gene expression patterns. We used gene expression microarray analysis to identify target genes modulated by RET. We compared two oncogenic RET mutants, associated with MEN 2A (2ARET) or MEN 2B (2BRET) disease subtypes, that are predicted to have distinct downstream target genes. We showed that overall, 2ARET and 2BRET modulated genes with similar functional ontologies. Further, when we validated our microarray data by quantitative real time PCR, we did not detect major differences in gene expression associated with these mutants when differences in receptor activity levels were considered. We did, however, detect differences in gene expression induced by two RET COOH-terminal isoforms, RET9 and RET51, irrespective of the RET form present (wildtype, 2ARET, or 2BRET). Our data suggest that similar transcriptional programs contribute to all forms of MEN 2 but that differences in target gene expression may contribute to developmental pattern differences observed between RET isoforms.
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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) | 0.001 | 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".