Progranulin modulates cholangiocarcinoma cell proliferation, apoptosis, and motility via the PI3K/pAkt pathway
Bibliographic record
Abstract
Progranulin (PGRN) is a growth factor normally expressed in rapidly cycling epithelial cells for growth, differentiation, and motility. Several studies have shown the association of PGRN overexpression with the progression of numerous malignancies, including cholangiocarcinoma (CCA). However, the underlying mechanisms on how PGRN modulates CCA cell proliferation and motility is not clear. In this study, we investigated the prognostic significance of PGRN expression in human CCA tissue and the mechanisms of PGRN modulation of CCA cell proliferation and motility. We found that CCA tissues with high PGRN expression were correlated with poor prognosis and likelihood of metastasis. PGRN knockdown KKU-100 and KKU-213 cells demonstrated a reduced rate of proliferation and colony formation and decreased levels of phosphatidyl inositol-3-kinase (PI3K) and phosphorylated Akt (pAkt) proteins. Accumulation of cells at the G1 phase was observed and was accompanied by a reduction of cyclin D1 and CDK4 protein levels. Knockdown cells also induced apoptosis by increasing the Bax-to-Bcl-2 ratio. Increased cell apoptosis was confirmed by annexin V-FITC/PI staining. Moreover, suppression of PGRN reduced CCA cell migration and invasion in vitro. Investigating the biomarkers in epithelial-mesenchymal transition (EMT) revealed a decrease in the expression of vimentin, snail, and metalloproteinase-9. In conclusion, our findings imply that PGRN modulates cell proliferation by dysregulating the G1 phase, inhibiting apoptosis, and that it plays a role in the EMT affecting CCA cell motility, possibly via the PI3K/pAkt pathway.
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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".