JOURNAL ARTICLE

Revisiting the Role of Epstein-Barr Virus (EBV) in Gastric Cancer: A Case Study of EBV in Normal, Dysplastic, and Malignant Gastric Epithelium.

  • Published In: International Journal of Surgical Pathology, 2025, v. 33, n. 8. P. 1824 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Mahadik, Juhi Devendra; Middleton, Charles E.; Saulino, David; Feely, Michael; Chua, Tiffany; Hong, Ansley; Nassour, Ibrahim; Assarzadegan, Naziheh 3 of 3

Abstract

This article focuses on the role of Epstein-Barr virus (EBV) in gastric carcinoma, particularly highlighting a case of a 78-year-old female patient with chronic atrophic gastritis, intestinal metaplasia, and multifocal intramucosal adenocarcinoma arising in hyperplastic gastric polyps. Uniquely, EBV expression, detected by Epstein-Barr encoding region in-situ hybridization (EBER-ISH) and polymerase chain reaction (PCR), was found not only in malignant and dysplastic gastric epithelium but also in adjacent nonneoplastic gastric mucosa. This finding suggests that latent EBV infection may precede and contribute to gastric carcinogenesis, especially in the inflammatory environment of chronic gastritis and intestinal metaplasia. The report underscores the need for further research into EBV’s mechanisms in gastric cancer development, including its potential role in genome-wide hypermethylation and disruption of normal cellular processes.

Additional Information

  • Source:International Journal of Surgical Pathology. 2025/12, Vol. 33, Issue 8, p1824
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2025
  • ISSN:1066-8969
  • DOI:10.1177/10668969251343218
  • Accession Number:188095598
  • Copyright Statement:Copyright of International Journal of Surgical Pathology is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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