Lysophosphatidic acid represses autophagy in prostate carcinoma cells
Bibliographic record
Abstract
Lysophosphatidic acid (LPA) is a small signaling phospholipid that mediates diverse functions including cell proliferation, migration, and survival by engaging LPA-agonized G-protein coupled receptors. Autophagy is a survival mechanism in response to nutrient depletion or organellar damage that encloses idle or damaged organelles within autophagosomes that are then delivered to lysosomes for degradation. However, the relationship between LPA and autophagy is largely unknown. The purpose of this study is to elucidate whether LPA affects autophagy through the ERK1/2 and (or) the Akt-mTOR signaling pathways. In this study, we investigated the effect of LPA on autophagy-regulating pathways in various prostate-derived cancer cells including PC3, LNCaP, and Du145 cells grown in complete medium and exposed to serum-free medium. Using Western blotting and ELISA, we determined that LPA stimulates the ERK and mTOR pathways in complete and serum-free medium. The mTOR pathway led to phosphorylation of S6K and ULK, which respectively stimulates protein synthesis and arrests autophagy. Consistent with this, LPA exposure suppressed autophagy as measured by LC3 maturation and formation of GFP-LC3 puncta. Altogether, these results suggest that LPA suffices to activate mTORC1 and suppress autophagy in prostate cancer cells.
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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 | 0.000 | 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) | 0.001 | 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".