Inhibition of IRAK1/4 enhances the antitumor effect of lenvatinib in anaplastic thyroid cancer cells
Bibliographic record
Abstract
Anaplastic thyroid cancer (ATC) is an extremely aggressive tumor associated with poor prognosis due to a lack of efficient therapies. In Japan, lenvatinib is the only drug approved for patients with ATC; however, its efficacy is limited. Therefore, novel therapeutic strategies are urgently required for patients with ATC. The present study aimed to identify compounds that enhance the antiproliferative effects of lenvatinib in ATC cells using a compound library. IRAK1/4 Inhibitor I was identified as a candidate compound. Combined treatment with lenvatinib and IRAK1/4 Inhibitor I showed synergistic antiproliferative effects via the induction of cell cycle arrest at G2/M phase in the ATC cell lines 8305C, HTC/C3, ACT-1, and 8505C. Furthermore, IRAK1/4 Inhibitor I enhanced the inhibition of ERK phosphorylation by lenvatinib in 8305C, HTC/C3, and 8505C cells. In an HTC/C3 xenograft mouse model, tumor volume was lower in the combined IRAK1/4 Inhibitor I and lenvatinib group compared with that in the vehicle control, IRAK1/4 Inhibitor I, and lenvatinib groups. IRAK1/4 Inhibitor I was identified as a promising compound that enhances the antiproliferative and antitumor effects of lenvatinib in 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) | 0.000 | 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 | 0.001 |
| 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".