Inverse Relationship between 15-Lipoxygenase-2 and PPAR-γ Gene Expression in Normal Epithelia Compared with Tumor Epithelia
Bibliographic record
Abstract
15-Lipoxygenase-2 (15-LOX-2) synthesizes 15-S-hydroxyeicosatetraenoic acid (15-S-HETE), an endogenous ligand for the nuclear receptor, peroxisome proliferator-activated receptor-gamma (PPAR-gamma). Several studies have described an inverse relationship between 15-LOX-2 and PPAR-gamma expression in normal versus tumor samples. To systematically determine if this is a ubiquitous phenomenon, we used a variety of epithelial and nonepithelial cells and some tissues to further evaluate the extent of this inverse relationship. The levels of mRNA or protein were measured by reverse transcriptase polymerase chain reaction or Western gray level intensity, whereas distribution was determined by in situ hybridization or immunofluorescence. 15-S-HETE was measured by liquid chromatography/tandem mass spectrometry. Normal epithelial cells/samples generally expressed high levels of 15-LOX-2 along with the enzyme product 15-S-HETE, but both levels were reduced in cancer cells/samples. In contrast, most cancer cells expressed high levels of PPAR-gamma mRNA and protein, which were absent from normal epithelial cells. Overall, the inverse relationship between these two genes was primarily restricted to epithelial samples. Forced expression of PPAR-gamma reduced 15-LOX-2 protein levels in normal cells, whereas forced expression of 15-LOX-2 in tumor cells suppressed PPAR-gamma protein levels. These results suggest that feedback mechanisms may contribute to the loss of 15-LOX-2 pathway components, which coincide with an increase in PPAR-gamma in many epithelial cancers.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".