AGRO100 inhibits activation of nuclear factor-κB (NF-κB) by forming a complex with NF-κB essential modulator (NEMO) and nucleolin
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Bibliographic record
Abstract
AGRO100, also known as AS1411, is an experimental anticancer drug that recently entered human clinical trials. It is a member of a novel class of antiproliferative agents known as G-rich oligonucleotides (GRO), which are non-antisense, guanosine-rich phosphodiester oligodeoxynucleotides that form stable G-quadruplex structures. The biological activity of GROs results from their binding to specific cellular proteins as aptamers. One important target protein of GROs has been previously identified as nucleolin, a multifunctional protein expressed at high levels by cancer cells. Here, we report that AGRO100 also associates with nuclear factor-kappaB (NF-kappaB) essential modulator (NEMO), which is a regulatory subunit of the inhibitor of kappaB (IkappaB) kinase (IKK) complex, and also called IKKgamma. In the classic NF-kappaB pathway, the IKK complex is required for phosphorylation of IkappaBalpha and subsequent activation of the transcription factor NF-kappaB. We found that treatment of cancer cells with AGRO100 inhibits IKK activity and reduces phosphorylation of IkappaBalpha in response to tumor necrosis factor-alpha stimulation. Using a reporter gene assay, we showed that AGRO100 blocks both tumor necrosis factor-alpha-induced and constitutive NF-kappaB activity in human cancer cell lines derived from cervical, prostate, breast, and lung carcinomas. In addition, we showed that, in AGRO100-treated cancer cells, NEMO is coprecipitated by nucleolin, indicating that both proteins are present in the same complex. Our studies suggest that abrogation of NF-kappaB activity may contribute to the anticancer effects of AGRO100 and that nucleolin may play a previously unknown role in regulating the NF-kappaB pathway.
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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 | 0.000 |
| 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) | 0.000 | 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