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Effect of Epstein–Barr virus infection on global gene expression in nasopharyngeal carcinoma

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Abstract

It was proposed that Epstein–Barr virus (EBV) is closely associated with nasopharyngeal carcinoma (NPC); however, the molecular mechanisms involved in the effect of EBV on NPC host genes have not yet been well defined. For this study, two sets of microarray experiments, NPC (EBV-free) vs normal epithelial cells and EBV+ vs EBV− NPC arrays, were analyzed and the datasets were cross-compared to identify any correlation between gene clusters involved in EBV targeting and the NPC host gene expression profiles. Statistical analysis revealed that EBV seems to have a preference for targeting more genes from the differentially expressed group in NPC cells than those from the ubiquitously expressed group. Furthermore, this trend is also reflected in log ratios where the EBV target genes of the differentially expressed group origin showed greater log ratios than genes with an origin from the ubiquitously expressed NPC group. Taken together, the genome-wide comparative scanning of EBV and NPC transcriptomes has successfully demonstrated that EBV infection has an intensifying effect on the signals involved in NPC gene expression both in breadth (the majority of the genes) and in depth (greater log ratios).

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Acknowledgements

The authors wish to thank Dr. S. K. Liao of Chang-Gung University for providing the NPC-CGBM1 cell lines and Dr. C. M. Liu of National Taiwan University Hospital for the surgical specimens of nasal polyps. They would also like to thank Dr. Shih-Lan Hsu, Dr. Fen-Hwa Wong, Dr. Hsiao-Sheng Liu, Dr. Jenn-Han Chen, Dr. Cheng-Yang Chou, Dr. Li-Wha Wu, Dr. A-Min Huang, Dr. Wey-Jinq Lin, Dr. King-Song Jeng, and Dr. Nan-Haw for their contributions to common reference RNA mixtures, and Dr. Fátima Al-Shahrour for allowing them to use the FatiGO algorithm. A special thank goes to Dr. Andrew Su (Genomics Institute of Novartis Research Foundation), Dr. Su-Fang Lin (National Health Research Institutes), Dr. Hung-Wen Chiu (Taipei Medical University), and Yang C. Fann (National Institute of Neurological Disorders and Stroke, National Institutes of Health) for the critical reading and inspiring comments on the manuscript. This research was supported, in part, by grants from the National Science Council (NSC93-3112-B-002-038 and NSC93-2320-B-002-112), the National Health Research Institutes (NHRI-EX92-9014BL), and the National Taiwan University Hospital (NTUH-92-S057, 93-S080, and 93A10-2) to C.-T. Lin; National Health Research Institutes and National Science Council (NRPGM: NSC93-3112-B-400-001) to C.-F. Huang; and National Science Council (NSC93-2320-B-038-043) and Topnotch Stroke Research Center Grant (Ministry of Education) to Y.-C. G. Lee. Yuan-Chii Gladys Lee and Yu-Chyi Hwang contributed equally to this work.

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Authors and Affiliations

  1. Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan, Republic of China

    Yuan-Chii Gladys Lee

  2. Bioinformatics Computing Center, Taipei Medical University, Taipei, Taiwan, Republic of China

    Yuan-Chii Gladys Lee

  3. National Institute of Cancer Research, National Health Research Institutes, Miaoli, Taiwan, Republic of China

    Yong-Shiang Lin

  4. Department of Chemical Engineering, National Chung Cheng University, Chiayi, Taiwan, Republic of China

    Kuang-Chi Chen

  5. Department of Pathology, National Taiwan University Hospital, Taipei, 100, Taiwan, Republic of China

    Chin-Tarng Lin

  6. Institute of Pathology, College of Medicine, National Taiwan University, Taipei, Taiwan, Republic of China

    Yu-Chyi Hwang, Dah-Yeou Huang & Han-Chung Wu

  7. Institute and Department of Pathology, College of Medicine, National Taiwan University, Taipei, 100, Taiwan, Republic of China

    Chin-Tarng Lin

  8. Institute of Oral Biology, College of Medicine, National Taiwan University, Taipei, Taiwan, Republic of China

    Han-Chung Wu

  9. Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan, Republic of China

    Tao-Wei Huang & Cheng-Yan Kao

  10. National Institute of Cancer Research, National Health Research Institutes, Taipei, 114, Taiwan, Republic of China

    Chi-Ying F. Huang

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  1. Yuan-Chii Gladys Lee
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Correspondence to Chin-Tarng Lin.

Additional information

Accession numbers of the genes used in the study are GEO: GSE2370, GEO: GSE2371, and GEO: GPL1885.

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10142_2006_35_MOESM1_ESM.doc

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Fig. S1

Boxplots analysis of the distribution of gene classification among groups in both NPC/Normal and EBV+/− arrays. The box presents the 75th and 25th percentiles (upper and lower quartiles) with the median value in between. The median values for up, down regulated and ubiquitously expressed groups are 076, −0.91 and 0.01 for NPC/Normal arrays (A) and are 0.38, −0.41 and 0.01 for EBV+/− arrays (B). The whiskers give the lowest and highest values. Outliers and extreme values are marked as circle and cross, respectively. The N means number of genes. The statistical significance between groups is also indicated. (JPEG 45 kb)

10142_2006_35_Fig1_ESM.tif

Fig. S2

Expression-data matrix for EBV and non-EBV target genes in the EBV+/− array (A) and their corresponding gene expression in NPC/Normal arrays (B). The 164 EBV target genes could be dived into two groups when traced back to the gene expression profiles in the NPC/Normal arrays: differentially expressed (n=98) and ubiquitously expressed genes (n=66). Again, the 136 non-EBV target genes in the EBV+/− arrays were also divided into differentially (n=52) and ubiquitously expressed genes (n=84) in the NPC/Normal arrays. In this two-dimensional presentation, each row represents a gene. The dendrogram at left of the matrix shows the relationship of gene expression for each sample. The expression level of each gene (relative to its median expression level across all samples) is represented by a unique color (red, blue and yellow indicating expression above, below and, equal to the mean, respectively), with the intensity of the color reflecting the magnitude of the deviation from the mean. As indicated, the fluorescence ratio-scale ranges from 0 to 6 (in log-base-2 units). (JPEG 150 kb)

10142_2006_35_Fig2_ESM.tif

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Lee, YC.G., Hwang, YC., Chen, KC. et al. Effect of Epstein–Barr virus infection on global gene expression in nasopharyngeal carcinoma. Funct Integr Genomics 7, 79–93 (2007). https://doi.org/10.1007/s10142-006-0035-2

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