Inhibition of IRAK1/4 enhances the antitumor effect of lenvatinib in anaplastic thyroid cancer cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it