Prostaglandin E2 Receptor 4 (EP4) as a Therapeutic Target to Impede Breast Cancer-Associated Angiogenesis and Lymphangiogenesis
Bibliographic record
Abstract
The formation of new blood (angiogenesis) and lymphatic (lymphangiogenesis) vessels are major events associated with most epithelial malignancies, including breast cancer. Angiogenesis is essential for cancer cell survival. Lymphangiogenesis is critical in maintaining tumoral interstitial fluid balance and importing tumor-facilitatory immune cells. Both vascular routes also serve as conduits for cancer metastasis. Intratumoral hypoxia promotes both events by stimulating multiple angiogenic/lymphangiogenic growth factors. Studies on tumor-associated lymphangiogenesis and its exploitation for therapy have received less attention from the research community than those on angiogenesis. Inflammation is a key mediator of both processes, hijacked by many cancers by the aberrant expression of the inflammation-associated enzyme cyclo-oxygenase (COX)-2. In this review, we focus on breast cancer and showed that COX-2 is a major promoter of both events, primarily resulting from the activation of prostaglandin (PG) E receptor EP4 on tumor cells, tumor-infiltrating immune cells, and endothelial cells; and the induction of oncogenic microRNAs. The COX-2/EP4 pathway also promotes additional events in breast cancer progression, such as cancer cell migration, invasion, and the stimulation of stem-like cells. Based on a combination of studies using multiple breast cancer models, we show that EP4 antagonists hold a major promise in breast cancer therapy in combination with other modalities including immune check-point inhibitors.
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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 | 0.001 | 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 | 0.001 |
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".