Silencing of <i>Astrocyte elevated gene-1</i> (<i>AEG-1</i>) inhibits proliferation, migration, and invasiveness, and promotes apoptosis in pancreatic cancer cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To investigate the role of Astrocyte elevated gene-1 (AEG-1) in the development and progress of pancreatic cancer, short hairpin RNA (shRNA) was inserted into the RNA interference vector to knock-down the endogenous AEG-1 in two pancreatic cancer cell lines: AsPC-1 and PANC-1. Our results showed that silencing of AEG-1 suppressed the proliferation, colony formation ability, and cell stemness of AsPC-1 and PANC-1 cells, and inhibited their G1-to-S phase transition. Results from apoptosis assay showed that knock-down of AEG-1 led to cell apoptosis. The expression of anti-apoptotic Bcl-2 was downregulated and that of the pro-apoptotic Bax and cleaved caspase-3 was upregulated in AEG-1-silenced pancreatic cancer cells. Further, the capability of AEG-1-silenced cells to migrate and to invade through the Matrigel-coated membrane was weaker, and the expression of matrix metallopeptidase 2 (MMP-2) and MMP-9 were decreased. Moreover, the AKT-β-catenin signaling pathway was inhibited in the cells with knock-down of AEG-1. In addition, the growth of xenograft tumors formed by AsPC-1 and PANC-1 cells was suppressed by AEG-1 shRNA. In conclusion, our study demonstrates that pancreatic cancer cells require AEG-1 to maintain their survival and metastasis, suggesting AEG-1 as a potential target for the treatment of pancreatic cancers.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it