Targeting Prostate Cancer Subtype 1 by Forkhead Box M1 Pathway Inhibition
Bibliographic record
Abstract
Abstract Purpose: Prostate cancer was recently classified to three clinically relevant subtypes (PCS) demarcated by unique pathway activation and clinical aggressiveness. In this preclinical study, we investigated molecular targets and therapeutics for PCS1, the most aggressive and lethal subtype, with no treatment options available in the clinic. Experimental Design: We utilized the PCS1 gene set and our model of enzalutamide (ENZR) castration-resistant prostate cancer (CRPC) to identify targetable pathways and inhibitors for PCS1. The findings were evaluated in vitro and in the ENZR CRPC xenograft model in vivo. Results: The results revealed that ENZR CRPC cells are enriched with PCS1 signature and that Forkhead box M1 (FOXM1) pathway is the central driver of this subtype. Notably, we identified Monensin as a novel FOXM1-binding agent that selectively targets FOXM1 to reverse the PCS1 signature and its associated stem-like features and reduces the growth of ENZR CRPC cells and xenograft tumors. Conclusions: Our preclinical data indicate FOXM1 pathway as a master regulator of PCS1 tumors, namely in ENZR CRPC, and targeting FOXM1 reduces cell growth and stemness in ENZR CRPC in vitro and in vivo. These preclinical results may guide clinical evaluation of targeting FOXM1 to eradicate highly aggressive and lethal PCS1 prostate cancer tumors. Clin Cancer Res; 23(22); 6923–33. ©2017 AACR.
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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) | 0.002 | 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".