Golgi phosphoprotein-3 promotes invasiveness of gastric cancer cells through the mTOR signalling pathway
Bibliographic record
Abstract
PURPOSE: Golgi phosphoprotein-3 (GOLPH3) is an oncogene that is overexpressed in multiple cancers and is associated with poor prognosis. The aim of this study was to examine the impact of GOLPH3 on the migration and metastasis of gastric cancer cells. METHODS: Following the shRNA-mediated knockdown of GOLPH3, we analyzed cytoskeletal reorganization and cell invasion, migration and adhesion, and determined the impact of components of the mammalian target of the rapamycin (mTOR) signalling pathway. RESULTS: The GOLPH3 mRNA and protein expression were significantly lower in both SGC-7901 and MKN-28 cells as compared with poorly-differentiated BGC-823 cells. The GOLPH3 knockdown also significantly reduced cell invasion in all three cell lines through reduced migration as compared with the non-targeting control sequence group. The GOLPH3 knockdown also reduced F-actin in all three cell lines, and decreased cell adhesion in BGC-823 and SGC-7901 cells. Finally, p-mTOR, p70S6K, p-4EBP1 and RhoA protein levels were significantly downregulated in shGOLPH3-1-treated cells. CONCLUSIONS: In conclusion, GOLPH3 increased in poorly-differentiated gastric cancer cells, activating the mTOR-70S6K/4EBP1-RhoA signalling pathway to promote the migration and metastasis of gastric 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 | 0.000 |
| 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".