Lestaurtinib is a potent inhibitor of anaplastic thyroid cancer cell line models
Bibliographic record
Abstract
Anaplastic thyroid cancer (ATC) is a rare and lethal human malignancy with no known effective therapies in the majority of cases. Despite the use of conventional treatments such as chemotherapy, radiation and surgical resection, this disease remains almost universally fatal. In the present study, we identified the JAK2 inhibitor Lestaurtinib as a potent compound when testing against 13 ATC cell lines. Lestaurtinib demonstrated a potent antiproliferative effect in vitro at nanomolar concentrations. Furthermore, Lestaurtinib impeded cell migration and the ability to form colonies from single cells using scratch-wound and colony formation assays, respectively. Flow cytometry was used for cell cycle analysis following drug treatment and demonstrated arrest at the G2/M phase of the cell cycle, indicative of a cytostatic effect. In vivo studies using the chick chorioallantoic membrane xenograft models demonstrated that treatment with Lestaurtinib resulted in a significant decrease in endpoint tumor volume and vascularity using power Doppler ultrasound imaging. Overall, this study provides evidence that Lestaurtinib is a potent antiproliferative agent with potential antiangiogenic activity that warrants further investigation as a targeted therapy for ATC.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".