Differential expression of calcium-related genes in gastric cancer cells transfected with cellular prion protein
Bibliographic record
Abstract
The prion protein (PrPC) has a primary role in the pathogenesis of transmissible spongiform encephalopathies, which causes prion disorders partially due to Ca2+ dysregulation. In our previous work, we found that overexpressed PrPC in gastric cancer was involved in apoptosis, cell proliferation, and metastasis of gastric cancer. To better understand how PrPC acts in gastric cancer, a human microarray was performed to select differentially regulated genes that correlate with the biological function of PrPC. The microarray data were analyzed and revealed 3798 genes whose expression increased at least 2-fold in gastric cancer cells transfected with PrPC. These genes encode proteins involved in several aspects of cell biology, among which, we specially detected molecules related to calcium, especially the S100 calcium-binding proteins, and found that PrPC upregulates S100A1, S100A6, S100B, and S100P but downregulates CacyBP in gastric cancer cells. We also found that intracellular Ca2+ levels in cells transfected with PrPC increased, whereas these levels decreased in knockdowns of these cells. Taken together, PrPC might increase intracellular Ca2+, partially through calcium-binding proteins, or PrPC might upregulate the expression of S100 proteins, partially through stimulating the intracellular calcium level in gastric cancer. Though the underlying mechanisms need further exploration, this study provides a new insight into the role of PrPC in gastric cancer and enriches our knowledge of prion protein.
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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 | 0.001 | 0.001 |
| 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".