Inhibition of RET tyrosine kinase by SU5416
Bibliographic record
Abstract
Thyroid neoplasia is frequently associated with rearranged during transfection (RET) proto-oncogene mutations that cause hyperactivation of RET kinase activity. Selective inhibition of RET-mediated signaling should lead to an efficacious therapy. SU5416 is a potent inhibitor of vascular endothelial cell growth factor receptor, c-Kit, and FLT-3 receptor tyrosine kinases presently used in clinical trials. We found that SU5416 inhibits RET with similar potency, both in cell-free assays and in cells, thus causing proliferation arrest in oncogenic RET-transfected cells and in papillary thyroid carcinoma (PTC) cells expressing the RET/PTC1 oncogene, but not in RET-negative control cells. SU5416 inhibited RET-mediated signaling through the extracellular signal regulated kinase (ERK) and JNK pathways. In addition, we show that a naturally occurring MEN2 mutation at codon 804 confers resistance to SU5416, but not to the related compound SU4984. We provide a possible explanation to these results by using molecular docking. Finally, SU5416 was also assessed against an array of 52 tyrosine and serine/threonine kinases.
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 | 0.000 |
| 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".