Bibliographic record
Abstract
Nasopharyngeal cancer (NPC) is a cancer of the head and neck and is unique in its intimate association with the Epstein Barr virus (EBV). Currently, patients with NPC are treated with radiation (RT) and chemotherapy, which is able to achieve a 5-year overall survival of approximately 65%, underscoring the need for novel treatments. Using a gene therapy approach, this thesis presents the development of viral-based strategies to improve tumour control. Chapter 2 evaluates the effect of introducing the tumour suppressor gene p53 using an adenoviral vector (adv. CMV.p53) in vivo in combination with radiation. Despite extensive cytotoxicity in vitro, there was no significant effect. Further analyses revealed that this lack of efficacy may have been due to its limited distribution throughout the tumour mass. Also presented in chapter 2 is the development of a transcriptional targeting system, denoted as oriP-FR. This strategy exploits the exclusive presence of EBV and it associated latent proteins within the tumour cells. This tumour-specific strategy was shown to drive EBV-dependent gene expression both in vitro and in vivo. With the advent of the oriP-FR platform, Chapter 3 addresses the issue of limited in vivo biodistribution through the development and characterization of a conditionally replicating adenovirus (CRA). The CRA was demonstrated to replicate in an EBV-dependent manner and result in selective cytotoxicity in vitro. When combined with RT, the CRA was able to delay tumour growth for at least 2 weeks in two independent NPC models with limited systemic toxicity. In order to further understand the potential therapeutic opportunities exploiting the relationship between EBV and NPC, Chapter 4 explores the effects of the EBV latent to lytic transition after RT and cisplatin treatment. This work characterized the induction of lytic gene expression after treatment with DNA damaging agents and identified a novel role for the transcription factor Nuclear Factor Y in mediating this process. Finally, Chapter 5 discusses the implications and future directions that this research may inspire. In sum, this thesis presents the development and identification of new therapeutic approaches that seek to provide opportunities for improved treatment regimens for patients with NPC.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".