Nuclear Factor-Y and Epstein Barr Virus in Nasopharyngeal Cancer
Bibliographic record
Abstract
PURPOSE: The Epstein Barr virus (EBV) is intimately associated with nasopharyngeal cancer (NPC) in a latent state expressing a limited number of genes. The process of switching from latency to replication is not well understood, particularly in response to DNA stress; hence, the focus of this study is on an EBV-positive NPC model. EXPERIMENTAL DESIGN: C666-1 cells were exposed to radiation (2-15 Gy) or cisplatin (0.1-50 microg/mL) assayed subsequently for relative EBV copy number (BamHI) and lytic gene expression (BRLF1 and BZLF1) using quantitative real-time PCR. Chromatin immunoprecipitation was conducted to assess the interaction of the transcription factor nuclear factor-Y (NF-Y) with promoter sequences. RESULTS: Radiation-induced and cisplatin-induced BamHI expression, along with increased levels of BRLF1 and BZLF1 in a dose-dependent and time-dependent manner, associated with the immediate nuclear transactivation of the transcription factor NF-Y and its own increased transcription of NF-Y subunits 8 h posttreatment. In silico analysis revealed three putative NF-Y consensus-binding sequences in the promoter region of BRLF1, which all interacted with NF-Y in response to radiation and cisplatin, confirmed using chromatin immunoprecipitation. Introduction of dominant-negative NF-YA reduced BRLF1 expression after radiation and cisplatin by 2.8-fold; in turn, overexpression of NF-YA resulted in a 2-fold increase in both BRLF1 and BZLF1 expression. CONCLUSIONS: These results show that NF-Y is an important mediator of EBV stress response in switching from a latent to lytic state. This novel insight could provide a potential therapeutic strategy to enhance NPC response to radiation and cisplatin.
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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) | 0.002 | 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".