Lysophosphatidic Acid Decreases the Nuclear Localization and Cellular Abundance of the p53 Tumor Suppressor in A549 Lung Carcinoma Cells
Bibliographic record
Abstract
Lysophosphatidic acid (LPA) is a bioactive lipid that promotes cancer cell proliferation and motility through activation of cell surface G protein-coupled receptors. Here, we provide the first evidence that LPA reduces the cellular abundance of the tumor suppressor p53 in A549 lung carcinoma cells, which express endogenous LPA receptors. The LPA effect depends on increased proteasomal degradation of p53 and it results in a corresponding decrease in p53-mediated transcription. Inhibition of phosphatidylinositol 3-kinase protected cells from the LPA-induced reduction of p53, which implicates this signaling pathway in the mechanism of LPA-induced loss of p53. LPA partially protected A549 cells from actinomycin D induction of both apoptosis and increased p53 abundance. Expression of LPA(1), LPA(2), and LPA(3) receptors in HepG2 hepatoma cells, which normally do not respond to LPA, also decreased p53 expression and p53-dependent transcription. In contrast, neither inactive LPA(1) (R124A) nor another G(i)-coupled receptor, the M(2) muscarinic acetylcholine receptor, reduced p53-dependent transcription in HepG2 cells. These results identify p53 as a target of LPA action and provide a new dimension for understanding how LPA stimulates cancer cell division, protects against apoptosis, and thereby promotes tumor progression.
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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) | 0.002 | 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".