Interpretation of EBV infection in pan-cancer genome considering viral life cycle: LiEB (Life cycle of Epstein-Barr virus)

Sci Rep. 2019 Mar 5;9(1):3465. doi: 10.1038/s41598-019-39706-0.

Abstract

We report a novel transcriptomic analysis workflow called LiEB (Life cycle of Epstein-Barr virus) to characterize distributions of oncogenic virus, Epstein-Barr virus (EBV) infection in human tumors. We analyzed 851 The Cancer Genome Atlas whole-transcriptome sequencing (WTS) data to investigate EBV infection by life cycle information using three-step LiEB workflow: 1) characterize virus infection generally; 2) align transcriptome sequences against a hybrid human-EBV genome, and 3) quantify EBV gene expression. Our results agreed with EBV infection status of public cell line data. Analysis in stomach adenocarcinoma identified EBV-positive cases involving PIK3CA mutations and/or CDKN2A silencing with biologically more determination, compared to previous reports. In this study, we found that a small number of colorectal adenocarcinoma cases involved with EBV lytic gene expression. Expression of EBV lytic genes was also observed in 3% of external colon cancer cohort upon WTS analysis. Gene set enrichment analysis showed elevated expression of genes related to E2F targeting and interferon-gamma responses in EBV-associated tumors. Finally, we suggest that interpretation of EBV life cycle is essential when analyzing its infection in tumors, and LiEB provides high capability of detecting EBV-positive tumors. Observation of EBV lytic gene expression in a subset of colon cancers warrants further research.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell Transformation, Viral
  • Epstein-Barr Virus Infections / complications*
  • Epstein-Barr Virus Infections / diagnosis
  • Epstein-Barr Virus Infections / virology*
  • Gene Expression Profiling
  • Genome, Human*
  • Herpesvirus 4, Human / physiology*
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Life Cycle Stages
  • Molecular Diagnostic Techniques
  • Mutation
  • Neoplasms / diagnosis
  • Neoplasms / etiology*
  • Reproducibility of Results
  • Transcriptome