Decoding Critical Targets and Signaling Pathways in EBV-Mediated Diseases Using Large Language Models

Abstract

Epstein–Barr virus (EBV), a member of the gamma herpesvirus, is the first identified human oncovirus and is associated with various malignancies. Understanding the intricate interactions between EBV antigens and cellular pathways is crucial to unraveling the molecular mechanisms in EBV-mediated diseases. However, fully elucidating EBV–host interactions and the associated pathogenesis remains a significant challenge. In this study, we employed large language models (LLMs) to screen 36,105 EBV-relevant scientific publications and summarize the current literature landscape on various EBV-associated diseases like Burkitt lymphoma (BL), diffuse large B-cell lymphoma (DLBCL), nasopharyngeal carcinoma (NPC), and so on. LLM-generated data indicate that the most-studied EBV-associated pathways are enriched in immune response, apoptosis, cell growth, and replication. The analyses of protein–protein interactions (PPIs) reveal three principal EBV-related protein clusters: TP53-centered apoptotic factors, EBV-associated transcription factors, and immune response elements. Utilizing our dataset and public databases, we demonstrated that BLLF3-targeted TLR2-associated factors are effective diagnostic markers for DLBCL. Next, we confirmed the co-expression of LMP1-targeted calcium pathway factors in BL. Finally, we demonstrated the correlation and co-expression of LMP1-induced PARP1, HIF1A, HK2, and key glycolysis-related factors, further suggesting that LMP1 actively regulates the glycolysis pathway. Therefore, our study presents a comprehensive functional encyclopedia of the interactions between EBV antigens and host signaling pathways across various EBV-associated diseases, providing valuable insights for the development of therapeutic strategies.

Keywords

• EBV
• signaling pathways
• EBV-mediated diseases
• LLM