The Prostaglandin E2 Pathway and Breast Cancer Stem Cells: Evidence of Increased Signaling and Potential Targeting
Bibliographic record
Abstract
Culprits of cancer development, metastasis, and drug resistance, cancer stem cells (CSCs) are characterized by specific markers, active developmental signaling pathways, metabolic plasticity, increased motility, invasiveness, and epithelial-mesenchymal transition. In breast cancer, these cells are often more prominent in aggressive disease, are amplified in drug-resistant tumors, and contribute to recurrence. For breast cancer, two distinct CSC populations exist and are typically defined by CD44+/CD24- cell surface marker expression or increased aldehyde dehydrogenase (ALDH) activity. These CSC populations share many of the same properties but also exhibit signaling pathways that are more active in CD44+/CD24- or ALDH+ populations. Understanding these CSC populations and their shared or specific signaling pathways may lead to the development of novel therapeutic strategies that will improve breast cancer patient outcomes. Herein, we review the current evidence and assess published patient tumor datasets of sorted breast CSC populations for evidence of heightened prostaglandin E2 (PGE2) signaling and activity in these breast CSC populations. PGE2is a biologically active lipid mediator and in cancer PGE2promotes tumor progression and poor patient prognosis. Overall, the data suggests that PGE2signaling is important in propagating breast CSCs by enhancing inherent tumor-initiating capacities. Development of anti-PGE2signaling therapeutics may be beneficial in inhibiting tumor growth and limiting breast CSC populations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".