Intersecting Mechanisms of Hypoxia and Prostaglandin E2-Mediated Inflammation in the Comparative Biology of Oral Squamous Cell Carcinoma
Bibliographic record
Abstract
The importance of inflammation in the pathogenesis of cancer was first proposed by Rudolph Virchow over 150 years ago, and our understanding of its significance has grown over decades of biomedical research. The arachidonic acid pathway of inflammation, including cyclooxygenase (COX) enzymes, PGE2 synthase enzymes, prostaglandin E2 (PGE2) and PGE2 receptors has been extensively studied and has been associated with different diseases and different types of cancers, including oral squamous cell carcinoma (OSCC). In addition to inflammation in the tumour microenvironment, low oxygen levels (hypoxia) within tumours have also been shown to contribute to tumour progression. Understandably, most of our OSCC knowledge comes from study of this aggressive cancer in human patients and in experimental rodent models. However, domestic animals develop OSCC spontaneously and this is an important, and difficult to treat, form of cancer in veterinary medicine. The primary goal of this review article is to explore the available evidence regarding interaction between hypoxia and the arachidonic acid pathway of inflammation during malignant behaviour of OSCC. Overlapping mechanisms in hypoxia and inflammation can contribute to tumour growth, angiogenesis, and, importantly, resistance to therapy. The benefits and controversies of anti-inflammatory and anti-angiogenic therapies for human and animal OSCC patients will be discussed, including conventional pharmaceutical agents as well as natural products.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".