Anti-tumor effects of an ID antagonist with no observed acquired resistance
Bibliographic record
Abstract
ID proteins are helix-loop-helix (HLH) transcriptional regulators frequently overexpressed in cancer. ID proteins inhibit basic-HLH transcription factors often blocking differentiation and sustaining proliferation. A small-molecule, AGX51, targets ID proteins for degradation and impairs ocular neovascularization in mouse models. Here we show that AGX51 treatment of cancer cell lines impairs cell growth and viability that results from an increase in reactive oxygen species (ROS) production upon ID degradation. In mouse models, AGX51 treatment suppresses breast cancer colonization in the lung, regresses the growth of paclitaxel-resistant breast tumors when combined with paclitaxel and reduces tumor burden in sporadic colorectal neoplasia. Furthermore, in cells and mice, we fail to observe acquired resistance to AGX51 likely the result of the inability to mutate the binding pocket without loss of ID function and efficient degradation of the ID proteins. Thus, AGX51 is a first-in-class compound that antagonizes ID proteins, shows strong anti-tumor effects and may be further developed for the management of multiple cancers.
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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) | 0.003 | 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".