Leukotriene B₄ Metabolism and p70S6 Kinase 1 Inhibitors: PF-4708671 but Not LY2584702 Inhibits CYP4F3A and the ω-Oxidation of Leukotriene B₄ In Vitro and In Cellulo
Bibliographic record
Abstract
LTB4 is an inflammatory lipid mediator mainly biosynthesized by leukocytes. Since its implication in inflammatory diseases is well recognized, many tools to regulate its biosynthesis have been developed and showed promising results in vitro and in vivo, but mixed results in clinical trials. Recently, the mTOR pathway component p70S6 kinase 1 (p70S6K1) has been linked to LTC4 synthase and the biosynthesis of cysteinyl-leukotrienes. In this respect, we investigated if p70S6K1 could also play a role in LTB4 biosynthesis. We thus evaluated the impact of the p70S6K1 inhibitors PF-4708671 and LY2584702 on LTB4 biosynthesis in human neutrophils. At a concentration of 10 μM, both compounds inhibited S6 phosphorylation, although neither one inhibited the thapsigargin-induced LTB4 biosynthesis, as assessed by the sum of LTB4, 20-OH-LTB4, and 20-COOH-LTB4. However, PF-4708671, but not LY2584702, inhibited the ω-oxidation of LTB4 into 20-OH-LTB4 by intact neutrophils and by recombinant CYP4F3A, leading to increased LTB4 levels. This was true for both endogenously biosynthesized and exogenously added LTB4. In contrast to that of 17-octadecynoic acid, the inhibitory effect of PF-4708671 was easily removed by washing the neutrophils, indicating that PF-4708671 was a reversible CYP4F3A inhibitor. At optimal concentration, PF-4708671 increased the half-life of LTB4 in our neutrophil suspensions by 7.5 fold, compared to 5 fold for 17-octadecynoic acid. Finally, Michaelis-Menten and Lineweaver-Burk plots indicate that PF-4708671 is a mixed inhibitor of CYP4F3A. In conclusion, we show that PF-4708671 inhibits CYP4F3A and prevents the ω-oxidation of LTB4 in cellulo, which might result in increased LTB4 levels in vivo.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".