Wild-Type p53 Attenuates Cancer Cell Motility by Inducing Growth Differentiation Factor-15 Expression
Bibliographic record
Abstract
A major function of the p53 tumor suppressor is the regulation of the cell cycle and apoptosis. In addition to its well-documented functions in malignant cancer cells, p53 can also regulate cell migration and invasion, which contribute to metastasis. Growth differentiation factor-15 (GDF-15), a member of the TGF-β superfamily, has been shown to be a downstream target of p53 and is associated with diverse human diseases and cancer progression. In this study, we examined the potential role of GDF-15 in p53-regulated cancer cell motility. We show that overexpression of wild-type p53 in two highly invasive p53-null human cancer cell lines, SKOV3 and PC3, attenuated cell migration and the movement through Matrigel. Using wild-type p53 and DNA-binding-deficient p53 mutants, we found that the transcriptional activity of p53 is required in the induction of GDF-15 expression. Cell movement through uncoated and Matrigel-coated transwell decreased in response to treatment with recombinant GDF-15, whereas the cell proliferation was not affected by GDF-15 treatment. Moreover, the induction of GDF-15 expression and secretion by p53 and the reduction in cell movement through Matrigel were diminished by treatment with GDF-15 small interfering RNA. This study demonstrates a mechanism by which p53 attenuates cancer cell motility through GDF-15 expression. In addition, our results indicate that GDF-15 mediates the functions of p53 by autocrine/paracrine action.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".