The Role of Peroxisome Proliferator-activated Receptor γ during Breast Tumour Angiogenesis
Bibliographic record
Abstract
Breast cancer remains a global health challenge as the most common cancer type worldwide and the leading cause of new cancer cases among Canadian females. Despite recent advances in early screening and targeted therapies, mechanisms of breast cancer progression remain to be fully understood. Peroxisome proliferator-activated receptor (PPAR) γ, expressed in many mammary associated cell types, is traditionally known for its role in adipocyte differentiation and lipid metabolism, but also plays a role in suppressing tumour progression. While there is some discrepancy in the literature, most studies used indirect models to suggest an anti-angiogenic role of PPARγ activation both in vitro and in vivo. This dissertation examines the direct role of PPARγ expression and activation in endothelial cells (ECs), in particular during mammary tumour angiogenesis. Utilizing human and murine aortic ECs, I reveal PPARγ expression and activation with the PPARγ activating drug rosiglitazone (ROSI) in ECs inhibits early angiogenic events in vitro, including EC sprouting, proliferation, and migration/invasion, associated with downregulating vascular endothelial growth factor receptor 2 (VEGFR-2) and cyclin D1 protein expression. I also used female EC-targeted PPARγ knockout (PPARγE-KO) mice and their congenic wildtype controls to show that PPARγ expression in ECs is necessary for the protective effect conferred by ROSI treatment during 7, 12-dimethylbenz[a]anthracene (DMBA)-mediated mammary tumourigenesis in vivo. Finally, I provide the first direct evidence that PPARγ expression and activation with ROSI treatment in mammary ECs exerts inhibitory effects on early angiogenic events in mammary tumours in vivo, but such anti-angiogenic effects may become less critical in late-stage mammary tumours. Collectively, evidence presented in the current dissertation supports the anti-angiogenic benefits of PPARγ activating drugs in at least early-stage mammary tumours, and the use of PPARγ expression in ECs as a potential prognostic and predictive biomarker of therapeutic response in some breast cancer patients.
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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 | 0.000 | 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) | 0.000 | 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".