Identification of an Imidazopyridine-based Compound as an Oral Selective Estrogen Receptor Degrader for Breast Cancer Therapy
Bibliographic record
Abstract
The pro-oncogenic activities of estrogen receptor alpha (ERα) drive breast cancer pathogenesis. Endocrine therapies that impair the production of estrogen or the action of the ERα are therefore used to prevent primary disease metastasis. Although recent successes with ERα degraders have been reported, there is still the need to develop further ERα antagonists with additional properties for breast cancer therapy. We have previously described a benzothiazole compound A4B17 that inhibits the proliferation of androgen receptor–positive prostate cancer cells by disrupting the interaction of the cochaperone BAG1 with the AR. A4B17 was also found to inhibit the proliferation of estrogen receptor—positive (ER+) breast cancer cells. Using a scaffold hopping approach, we report here a group of small molecules with imidazopyridine scaffolds that are more potent and efficacious than A4B17. The prototype molecule X15695 efficiently degraded ERα and attenuated estrogen-mediated target gene expression as well as transactivation by the AR. X15695 also disrupted key cellular protein–protein interactions such as BAG1–mortalin (GRP75) interaction as well as wild-type p53–mortalin or mutant p53–BAG2 interactions. These activities together reactivated p53 and resulted in cell-cycle block and the induction of apoptosis. When administered orally to in vivo tumor xenograft models, X15695 potently inhibited the growth of breast tumor cells but less efficiently the growth of prostate tumor cells. We therefore identify X15695 as an oral selective ER degrader and propose further development of this compound for therapy of ER+ breast cancers. Significance: An imidazopyridine that selectively degrades ERα and is orally bioavailable has been identified for the development of ER+ breast cancer therapeutics. This compound also activates wild-type p53 and disrupts the gain-of-function tumorigenic activity of mutant p53, resulting in cell-cycle arrest and the induction of apoptosis.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".