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


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.

SUBMITTER: Song H 

PROVIDER: S-EPMC6401378 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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

Song Hyojin H   Lim Yoojoo Y   Im Hogune H   Bae Jeong Mo JM   Kang Gyeong Hoon GH   Ahn Junhak J   Baek Daehyun D   Kim Tae-You TY   Yoon Sung-Soo SS   Koh Youngil Y  

Scientific reports 20190305 1


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  ...[more]

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