Comparative proteomic analysis reveals differentially expressed proteins regulated by a potential tumor promoter, BRE, in human esophageal carcinoma cells
Bibliographic record
Abstract
Esophageal tumorigenesis is a complex and cascading process, involving the interaction of many genes and proteins. In this study, we have used the comparative proteomic approach to identify tumor-associated proteins and explore the carcinogenic mechanisms. Two-dimensional electrophoresis (2-DE) and MALDI-TOF MS analysis of esophageal carcinoma and control cells revealed 10 proteins that were upregulated. A further 10 proteins were downregulated. Among these 20 differentially expressed proteins, brain and reproductive organ-expressed (BRE) protein was identified as a potential tumor promoter. It was high expressed by the esophageal carcinoma cells, as confirmed by RT-PCR and immunoblotting. BRE has been reported to be a stress-responsive protein. To gain further insight into its function, BRE expression was silenced in esophageal carcinoma cells using BRE-specific small interference RNA. It was discovered that silencing BRE expression downregulated prohibitin expression, but upregulated tumor-suppressor p53 expression. Furthermore, cyclin A and CDK2 expressions were suppressed suggesting that BRE inhibited cell proliferation. These results implied that BRE plays a significant role in mediating antiapoptotic and proliferative responses in esophageal carcinoma 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".