AEG33783, a potent JNK pathway inhibitor with neuroprotective properties, selectively induces apoptosis in tumor cell lines
Bibliographic record
Abstract
Proc Amer Assoc Cancer Res, Volume 46, 2005 2265 AEG33783 is a pre-clinical neuroprotective agent, under development to rescue peripheral neurons from chemotherapy-induced toxicity. [AEG33783][1] antagonizes JNK signaling through modulation of heat-shock protein levels in primary sympathetic neuronal culture, leading to potent neuronal protection against oxaliplatin, vinblastine and in-vivo protection against cisplatin and paclitaxel-induced nerve conduction velocity changes. Because JNK signaling is implicated in the survival of tumor cells, and [AEG33783][1] is projected to be used to treat chemotherapy-induced peripheral neuropathies, we examined the effect of [AEG33783][1] on cancer cells alone and in combination with chemotherapy agents. In combination with various chemotherapy agents (paclitaxel, vinblastine, and cisplatin) in 72 hour, MTS-based 96 well cell viability assays, [AEG33783][1] did not protect MDA MB231 (breast), HCT116 (colorectal), H460 (lung), or DU145 (prostate) from dose-proportional killing. At all doses there was increased chemotherapy efficacy. In fact, significant stand-alone cytotoxicity of [AEG33783][1] on certain neuroblastoma cell lines was noted, with IC50’s in the high nanomolar range. Of particular interest, [AEG33783][1] potentiated the efficacy of melphalan five- fold against neuroblastoma cells and importantly was not toxic to the diploid human fibroblast line WI38, nor did it affect melphalan toxicity on fibroblasts . Further examination of [AEG33783][1] in clonogenic assays revealed IC50 values in the high nanomolar range against cell lines of breast, prostate, and colorectal origin. [AEG33783][1] is revealed as a novel compound that has pronounced anticancer effects in addition to potent neuroprotective ability. [1]: /lookup/external-ref?link_type=GENPEPT&access_num=AEG33783&atom=%2Fcanres%2F65%2F9_Supplement%2F532.1.atom
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) | 0.001 | 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 | 0.001 |
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".