Gastroenterology

Gastroenterology

Volume 148, Issue 1, January 2015, Pages 137-147.e9
Gastroenterology

Original Research
Full Report: Basic and Translational—Alimentary Tract
Deregulation of Immune Response Genes in Patients With Epstein-Barr Virus-Associated Gastric Cancer and Outcomes

https://doi.org/10.1053/j.gastro.2014.09.020Get rights and content

Background & Aims

Patients with Epstein-Barr virus–associated gastric carcinoma (EBVaGC) have a better prognosis than those with gastric cancer not associated with EBV infection (EBVnGC). This is partly because EBV infection recruits lymphocytes, which infiltrate the tumor. A high degree of tumor heterogeneity is likely to be associated with poor response. We investigated differences in gene expression patterns between EBVaGC and EBVnGC.

Methods

We used gene expression profile analysis to compare tumor and nontumor gastric tissues from 12 patients with EBVaGC and 14 patients with EBVnGC. Findings were validated by whole transcriptome RNAseq and real-time quantitative polymerase chain reaction analyses. CD3+ primary T cells were isolated from human blood samples; migration of these cells and of Jurkat cells were measured in culture with EBV-infected and uninfected gastric cancer cells.

Results

Based on Pearson correlation matrix analysis, EBVaGCs had a higher degree of homogeneity than EBVnGCs. Although 4550 genes were differentially expressed between tumor and nontumor gastric tissues of patients with EBVnGC, only 186 genes were differentially expressed between tumor and nontumor gastric tissues of patients with EBVaGC (P < .001). This finding supports the concept that EBVaGCs have fewer genetic and epigenetic alterations than EBVnGCs. Expression of major histocompatibility complex class II genes and genes that regulate chemokine activity were more often deregulated in EBVaGCs compared with nontumor tissues. In culture, more T cells migrated to EBV-infected gastric cancer cells than to uninfected cells; migration was blocked with a neutralizing antibody against CXCR3 (a receptor for many chemokines).

Conclusions

Fewer genes are deregulated in EBVaGC than in EBVnGC. Most changes in EBVaGCs occur in immune response genes. These changes might allow EBVaGC to recruit reactive immune cells; this might contribute to the better outcomes of these patients compared with those with EBVnGC.

Section snippets

Materials and Methods

The messenger RNA microarray data of normal (N) and tumor (T) pairs from 14 EBVnGC and 12 EBVaGC patients (see Supplementary Table 1 for sample information) were analyzed (Table 1) to list differentially expressed gene (DEG) between EBVnGC and EBVaGC. The results were validated by RNA sequencing of paired ends of whole transcriptome (Hi RNAseq) using Illumina HiSeq 2000 instrument and by real-time quantitative polymerase chain reaction (RTqPCR). All materials and methods are described in the

Unsupervised Clustering Analyses Separate Epstein-Barr Virus–Associated Gastric Carcinoma From Epstein-Barr Virus–Nonassociated Gastric Carcinoma

The messenger RNA microarray raw data were corrected by Robust Multi-Array Average and normalized by the quantile method. The box plots before and after plot normalization showed that all data were normalized to present almost equal median and quantile fraction (deposited as GSE51575 in GEO) (Supplementary Figure 1A). Hierarchical clustering distinguished tumors from normal tissues and also EBVaGC from EBVnGC with a few outliers (Supplementary Figure 1B). An unsupervised fuzzy clustering and

Discussion

Both EBVnGC and EBVaGC are subclassified into 3 subtypes, LELC, carcinoma with Crohn's disease-like lymphoid reaction, and conventional-type adenocarcinoma, based on the degree of infiltration of immune cells and the extent of desmoplasia regardless of EBV infection. Among EBVaGC patients, those with the LELC subtype presented the best prognosis, followed by those with Crohn's disease-like lymphoid reaction, which in turn presented better survival than those with conventional-type

Acknowledgments

The messenger RNA microarray and RNAseq data were deposited as GSE51575 and GSE60873, respectively, in GEO.

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    Conflicts of interest The authors disclose no conflicts.

    Funding This study was supported by Samsung Biomedical Research Institute (SMX1132731, SMX1132461, OB00013). This research was supported by a grant of the Korea Healthcare Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry for Health & Welfare, Republic of Korea. (HI09C1552).

    Author names in bold designate shared co-first authorship.

    Authors share co-first authorship.

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