Identification of a Chemical Inhibitor of the Oncogenic Transcription Factor Forkhead Box M1
Bibliographic record
Abstract
The oncogenic transcription factor forkhead box M1 (FoxM1) is overexpressed in a number of different carcinomas, whereas its expression is turned off in terminally differentiated cells. For this reason, FoxM1 is an attractive target for therapeutic intervention in cancer treatment. As a first step toward realizing this goal, in this study, using a high-throughput, cell-based assay system, we screened for and isolated the antibiotic thiazole compound Siomycin A as an inhibitor of FoxM1. Interestingly, we observed that Siomycin A was able to down-regulate the transcriptional activity as well as the protein and mRNA abundance of FoxM1. Consequently, we found that the downstream target genes of FoxM1, such as Cdc25B, Survivin, and CENPB, were repressed. Also, we observed that consistent with earlier reports of FoxM1 inhibition, Siomycin A was able to reduce anchorage-independent growth of cells in soft agar. Furthermore, we found that Siomycin A was able to induce apoptosis selectively in transformed but not normal cells of the same origin. Taken together, our data suggest that FoxM1 inhibitor Siomycin A could represent a useful starting point for the development of anticancer therapeutics.
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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".