Dataset Information

Multiple pathways for Epstein-Barr virus episome loss from nasopharyngeal carcinoma.

ABSTRACT: Epstein-Barr virus (EBV) is the prototypical example for episomal persistence of genetic information. Yet, little is known about how this viral episome is lost. Episome loss occurs naturally in nasopharyngeal carcinoma (NPC) upon explantation into culture. Using whole-genome profiling, we found evidence for 2 different pathways of episome loss: (i) rapid loss of the entire episome or (ii) successive mutation/deletion of the episome until at least 1 essential cis-element is destroyed. This second phenotype was seen in a clone of HONE-1 NPC cells that maintains the EBV episome for prolonged time in culture. The conceptual insights provided by our quantitative analysis should aid our understanding of mammalian episomes, as well as lead to designs to cure latent viral infection.

SUBMITTER: Dittmer DP

PROVIDER: S-EPMC2866115 | biostudies-literature | 2008 Nov

REPOSITORIES: biostudies-literature

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Multiple pathways for Epstein-Barr virus episome loss from nasopharyngeal carcinoma.

Dittmer Dirk P DP Hilscher Chelsey J CJ Gulley Margaret L ML Yang Eric V EV Chen Min M Glaser Ronald R

International journal of cancer 20081101 9

Epstein-Barr virus (EBV) is the prototypical example for episomal persistence of genetic information. Yet, little is known about how this viral episome is lost. Episome loss occurs naturally in nasopharyngeal carcinoma (NPC) upon explantation into culture. Using whole-genome profiling, we found evidence for 2 different pathways of episome loss: (i) rapid loss of the entire episome or (ii) successive mutation/deletion of the episome until at least 1 essential cis-element is destroyed. This second ...[more]

PMID: 18688856

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Project description:Nasopharyngeal carcinoma (NPC) is consistently associated with Epstein-Barr virus (EBV) infection in regions in which it is endemic, including Southern China and Southeast Asia. The high mortality rates of NPC patients with advanced and recurrent disease highlight the urgent need for effective treatments. While recent genomic studies have revealed few druggable targets, the unique interaction between the EBV infection and host cells in NPC strongly implies that targeting EBV may be an efficient approach to cure this virus-associated cancer. Key features of EBV-associated NPC are the persistence of an episomal EBV genome and the requirement for multiple viral latent gene products to enable malignant transformation. Many translational studies have been conducted to exploit these unique features to develop pharmaceutical agents and therapeutic strategies that target EBV latent proteins and induce lytic reactivation in NPC. In particular, inhibitors of the EBV latent protein EBNA1 have been intensively explored, because of this protein's essential roles in maintaining EBV latency and viral genome replication in NPC cells. In addition, recent advances in chemical bioengineering are driving the development of therapeutic agents targeting the critical functional regions of EBNA1. Promising therapeutic effects of the resulting EBNA1-specific inhibitors have been shown in EBV-positive NPC tumors. The efficacy of multiple classes of EBV lytic inducers for NPC cytolytic therapy has also been long investigated. However, the lytic-induction efficiency of these compounds varies among different EBV-positive NPC models in a cell-context-dependent manner. In each tumor, NPC cells can evolve and acquire somatic changes to maintain EBV latency during cancer progression. Unfortunately, the poor understanding of the cellular mechanisms regulating EBV latency-to-lytic switching in NPC cells limits the clinical application of EBV cytolytic treatment. In this review, we discuss the potential approaches for improvement of the above-mentioned EBV-targeting strategies.

Dataset Information

Multiple pathways for Epstein-Barr virus episome loss from nasopharyngeal carcinoma.

Publications

Multiple pathways for Epstein-Barr virus episome loss from nasopharyngeal carcinoma.

Similar Datasets

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