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Article

Clinicopathological Significance of EBV-Infected Gastric Carcinomas: A Meta-Analysis

by
Jung-Soo Pyo
1,†,
Nae-Yu Kim
2,† and
Dong-Wook Kang
3,4,*
1
Department of Pathology, Daejeon Eulji University Hospital, Eulji University School of Medicine, Daejeon 35233, Korea
2
Department of Internal Medicine, Daejeon Eulji University Hospital, Eulji University School of Medicine, Daejeon 35233, Korea
3
Department of Pathology, Chungnam National University Sejong Hospital, 20 Bodeum 7-ro, Sejong 30099, Korea
4
Department of Pathology, Chungnam National University School of Medicine, 266 Munhwa Street, Daejeon 35015, Korea
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this study.
Medicina 2020, 56(7), 345; https://doi.org/10.3390/medicina56070345
Submission received: 5 June 2020 / Revised: 2 July 2020 / Accepted: 9 July 2020 / Published: 13 July 2020
(This article belongs to the Special Issue Meta-Research in the Medico-Scientific Field)
Browse Figure
Review Reports Versions Notes

Abstract

:
Background and objectives: The present study aims to elucidate the clinicopathologic significance of Epstein–Barr virus (EBV) infection in gastric carcinomas (GCs) through a meta-analysis. Materials and Methods: Sixty-one eligible studies were included in the present meta-analysis. The included patients, with and without EBV infection, were 2063 and 17,684, respectively. We investigated the clinicopathologic characteristics and various biomarkers, including programmed death-ligand 1 (PD-L1) expression and tumor-infiltrating lymphocytes (TILs). Results: The estimated EBV-infected rate of GCs was 0.113 (95% confidence interval (CI): 0.088–0.143). The EBV infection rates in GC cells were 0.138 (95% CI: 0.096–0.194), 0.103 (95% CI: 0.077–0.137), 0.080 (95% CI: 0.061–0.106), and 0.042 (95% CI: 0.016–0.106) in the population of Asia, America, Europe, and Africa, respectively. There was a significant difference between EBV-infected and noninfected GCs in the male: female ratio, but not other clinicopathological characteristics. EBV infection rates were higher in GC with lymphoid stroma (0.573, 95% CI: 0.428–0.706) than other histologic types of GCs. There were significant differences in high AT-rich interactive domain-containing protein 1A (ARID1A) and PD-L1 expressions, and high CD8+ TILs between EBV-infected and noninfected GCs. Conclusions: Our results showed that EBV infection of GCs was frequently found in male patients and GCs with lymphoid stroma. EBV infection was significantly correlated with ARID1A and PD-L1 expressions and CD8+ TILs in GCs.

1. Introduction

The Epstein–Barr virus (EBV) is a ubiquitous human herpesvirus associated with several lymphoid and epithelial malignancies, including Burkitt’s lymphoma, Hodgkin’s lymphoma, nasal NK/T cell lymphoma, and a subset of gastric carcinomas (GCs) [1,2,3,4,5,6]. In 1990, Burke et al. first detected the EBV genomes in a small group of GCs using a polymerase chain reaction [1]. Shibata et al. demonstrated that EBV genomes were uniformly present in GC cells, resembling lymphoepithelioma cells [4]. After that, EBV involvement was detected not only in lymphoepithelioma-like GCs but also in a subset of ordinary GCs [4,7].
EBV-associated gastric cancers (EBVaGCs) have a unique molecular signature, which has defined this group of tumors as a distinctive molecular subtype of gastric cancer that accounts for approximately 10% of all GCs [2,3,4]. Thus, EBVaGC is the most common cancer among EBV-related malignancies. However, the prevalence of EBV infection in GCs has differed by reports and histologic subtypes [7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67]. Furthermore, cumulative information cannot be obtained from individual studies. As part of The Cancer Genome Atlas (TCGA) project, EBVaGCs are associated with distinct molecular changes, as follows: DNA hypermethylation, high frequency of PIK3CA mutation, JAK2 gene amplification, programmed death-ligand 1/programmed cell death 1 ligand 2 (PD-L1/PD-L2) overexpression, and cyclin-dependent kinase inhibitor 2A (CDKN2A) silencing [2]. Recently, the loss of AT-rich interactive domain-containing protein 1A (ARID1A) was found in 20% of GCs and significantly correlated with EBVaGCs, PD-L1 status, as well as microsatellite instability (MSI) [64]. As the incidences and clinical features of GCs differ between regions, the clinicopathological characteristics of EBVaGCs may vary according to the various factors. In the present study, we investigate the clinicopathologic significance of EBVaGCs from eligible studies and perform the subgroup analysis to elucidate the EBV infection rate. We also evaluate the differences in the expression of various markers between EBVaGCs and non-EBVaGCs.

2. Materials and Methods

2.1. Published Study Search and Selection Criteria

Relevant articles were obtained by searching the PubMed database on 31 January 2020. For the search, the following keywords were used: “gastric carcinoma or gastric cancer or stomach cancer” and “Epstein–Barr virus or EBV”. The titles and abstracts of all searched articles were screened for the inclusion and exclusion of each article. Included articles contained information on the correlation between EBV positivity and clinicopathological characteristics in GCs. However, case reports, nonoriginal articles, or those not written in English were excluded from the present study. The PRISMA checklist is shown in Table S1.

2.2. Data Extraction

Data associated with clinicopathological characteristics based on EBV positivity in GCs were extracted from each of the eligible studies [7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67]. Two independent authors obtained all the data. The data extracted were the author’s information, study location, number of patients analyzed, EBV-positive rates, and clinicopathological characteristics by EBV infection. Additional information on immunohistochemical stains is shown in Table S2.

2.3. Statistical Analyses

The meta-analysis was performed using the Comprehensive Meta-Analysis software package 2.0 (Biostat, Englewood, NJ, USA). The EBV positivity rate was investigated in GCs. In addition, a subgroup analysis based on study location and histologic subtypes of GCs was performed. The correlations between EBV infection and clinicopathological characteristics were evaluated in GCs. In the present study, the following were included in the evaluated clinicopathological characteristics: age, sex, tumor size, tumor differentiation, histologic type, lymphatic, vascular, and perineural invasions, lymph node metastasis, and pTNM stages. Furthermore, the correlations between EBV positivity and p53, ARID1A, human epidermal growth factor receptor (HER2), and PD-L1 expressions, tumor-infiltrating lymphocytes (TILs), and microsatellite instability (MSI) in GCs were analyzed. We checked the heterogeneity between the studies by Q and I2 statistics, expressed as p-values. Additionally, we conducted a sensitivity analysis to assess the heterogeneity of the eligible studies and the impact of each study on the combined effects. In the meta-analysis, as the eligible studies used various populations, a random-effect model (rather than a fixed-effect model) was determined to be more suitable. The statistical difference between subgroups was evaluated by a metaregression test. We used Begg’s funnel plot and Egger’s test to assess the publication bias; if significant publication bias was found, the fail-safe N and trim-fill tests were additionally used to confirm the degree of publication bias. The results were considered statistically significant at p < 0.05.

3. Results

3.1. Selection and Characteristics of the Studies

In this study, 1301 relevant articles were found from the PubMed database and reviewed for a meta-analysis. Of these, 405 articles had no or a lack of sufficient information for the meta-analysis. A further 346 were excluded due to nonoriginal articles. Among the remaining articles, 489 reports were excluded for the following reasons: nonhuman studies (n = 238), articles on other diseases (n = 185), in a language other than English (n = 40), and duplication (n = 26); see Figure 1. Finally, 61 eligible articles were selected and included for the meta-analysis (Table 1). These studies included 19,747 GC patients with and without EBV infection (2063 and 17,684, respectively).

3.2. Epstein–Barr virus (EBV) Infected Rates of Gastric Carcinomas (GCs)

First, we investigated and analyzed the EBV-positive rates of GCs. The estimated EBV-positive rate was 0.113 (95% CI: 0.088–0.143) in overall GC cases. In the subgroup analysis based on study location, the EBV infected rate was the highest in Asia, compared to that in other regions. The EBV infected rate in the Asia region was 0.138 (95% CI: 0.096–0.194). In other areas, the EBV infected rates were 0.103, 0.080, and 0.042 in America, Europe, and Africa, respectively (Table 2).

3.3. Correlations Between Epstein–Barr virus (EBV) Infection and Clinicopathological Characteristics in Gastric Carcinomas (GCs)

The clinicopathological characteristics, according to EBV positivity, were investigated in GCs. The male patients showed a significantly higher estimation rate in the EBV-positive group than in the EBV-negative group (0.824 vs. 0.639; p < 0.001 in a metaregression test). Other clinicopathological characteristics, including age, tumor size, tumor differentiation, lymphatic, vascular, and perineural invasions, pT stage, lymph node metastasis, and pTNM stage, had no significant differences between EBV-infected and noninfected GCs (Table 3). Next, the EBV-positive rates by histologic type of GC were investigated (Table 4). The EBV-positive rate of GC with lymphoid stroma was 0.573 (95% CI: 0.428–0.706). This GC with lymphoid stroma showed higher EBV-positive rates compared to other tumor subtypes such as tubular adenocarcinoma (0.174), poorly cohesive carcinoma (0.078), papillary carcinoma (0.022), mucinous carcinoma (0.053), and undifferentiated carcinoma (0.111).
PD-L1 expressions in tumor and immune cells were significantly higher in EBVaGCs than in non-EBVaGCs (Table 5). In detail, PD-L1 expression rates of tumor cells were 0.573 (95% CI: 0.449–0.688) and 0.183 (95% CI: 0.118–0.272) in EBVaGCs and non-EBVaGCs, respectively. In addition, the PD-L1 expression rates of immune cells were 0.832 (95% CI: 0.630–0.935) and 0.487 (95% CI: 0.357–0.619) in EBVaGCs and non-EBVaGCs, respectively. ARID1A was highly expressed in EBVaGCs compared to non-EBVaGCs (0.29 vs. 0.170; p = 0.021 in a metaregression test). HER2 expression was higher in non-EBVaGCs than in EBVaGCs (0.104 vs. 0.048), but with no significant difference in a metaregression test (p = 0.051). There was no significant difference in MSI between EBVaGCs and non-EBVaGCs. CD8+ TILs were significantly higher in EBVaGCs than in non-EBVaGCs. In addition, there was no significant correlation between EBV positivity and loss of E-cadherin (Table S3).

4. Discussion

In other epithelial malignancies, the prevalence of EBV positivity was found to be 26.37%, 33.44%, and 45.37% in breast, cervical, and oral squamous cell carcinomas, respectively [68,69,70]. The range of EBV positivity reported was variable in GC tissues [7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67]. However, Chen et al. reported that non-neoplastic gastric tissue did not detect EBV positivity [71]. A TCGA study stated that the incidence of EBVaGCs was 9% [2]. Previous meta-analyses have reported the range as 2–20% and 6–33% [72,73]. In addition, the clinicopathological features of EBV positivity in GCs were variable, according to reports [72,73]. Therefore, the impact of variable EBV positivity on the controversy of clinicopathological implications of EBV in GCs needs to be elucidated. The present study includes a detailed meta-analysis of the clinicopathological implications of EBV positivity in GCs.
In the present study, the estimated EBV positive rate was 11.3%. EBV positive rates ranged from 1.2% to 89.2% in the individual eligible studies [7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67]. In previous meta-analyses, EBV positive rates have been reported as 7.5% and 12.6% in 2010 and 2019, respectively [74,75]. Various factors, including the eligible studies, may have affected the differences of EBV positivity between meta-analyses. In Murphy’s report, a subgroup analysis based on study location was performed, and the estimated EBV positive rates in America, Asia, and Europe were 9.88%, 8.28%, and 8.70%, respectively [72]. In the current study, the positive rate was highest in Asia at 13.8%. However, there were no significant differences between study locations in the metaregression test. Lee et al. reported that locations with a high prevalence of GCs had low EBV positivity [76]. They showed only odds ratios according to study locations, but not the estimated rates. As the criteria of the odds ratio were not described, interpretation of the odds ratio was not possible. They described that the EBV-positive rate of Asians was 8.4% through simple estimation using the raw data of each study. A meta-analysis did not obtain this result. Moreover, the estimated EBV-positive rates of Caucasian and Hispanic patients did not differ from Asians. In another meta-analysis, there was no significant difference in EBV-positive rates between study locations [75].
In addition, EBV positivity rates can differ according to the histologic type of GC. The highest EBV-positive rate was found in GC with lymphoid stroma at 57.3%. The implications of study location and ethnicity on EBV positivity may be less important when compared to the subtype of GC. Furthermore, the impact of studied years can contribute to varying EBV-positive rates. Additionally, we investigated EBV positivity in tubular adenocarcinoma according to study years. Based on 2017 data, EBV-positive rates were 0.113 (95% CI: 0.063–0.195) and 0.375 (95% CI: 0.132–0.703) after 2017 and before 2017, respectively, with a significant difference between subgroups (p = 0.012 in a metaregression test; data not shown). The possible causes are different methodologies and different histologic subtypes of the included cases. The cellular component can affect EBV positivity. In GCs, TILs can show EBV positivity [71]. Of course, the use of a PCR method with microdissection is possible for a more detailed examination; however, this limitation cannot be solved by microdissection due to intratumoral and peritumoral lymphocytes. Although PCR methods are more sensitive than in situ hybridization (ISH) methods, EBV positivity should be elucidated by evaluating cellular fractions, such as in ISH [71]. However, a definitive cause for the difference of EBV positivity by study years could not be found.
In previous studies, EBV positivity has been significantly correlated with some clinicopathological characteristics, sex, and tumor location [22,26,53]. In the present study, there was a significant correlation between EBV positivity and the patient’s sex; however, EBV positivity was not correlated with lymphovascular invasion or pTNM stage. The clinicopathological significance of EBV infection is different by reports [24,25,74,75,76]. Huang et al. reported that EBV infection in GCs was correlated with high pTNM stages and lymphatic tumor invasion, as opposed to our results [24,25]. Lee et al. reported that EBV positivity was higher in younger patients than in older patients [76]. Li et al. reported a correlation between EBV positivity and lymph node metastasis [74]. However, other meta-analyses showed no correlation between EBV positivity and lymph node metastasis, in agreement with our result [75,76]. For the evaluation of correlation with lymph node metastasis, Li’s meta-analysis and our meta-analysis included 5 and 40 datasets, respectively. Moreover, they analyzed their data using odds ratios, unlike our analysis. These discrepancies could be involved in the difference of results between the meta-analyses.
Although the molecular characteristics of GCs have been studied [2], previous meta-analyses have not dealt with their correlation with various molecular markers [75]. In our results, CD8+ TILs and PD-L1 expressions of the tumor and immune cells were more frequently found in EBVaGCs than in non-EBVaGCs. Abundant TILs are one of the histologic features in GCs with EBV infection [77,78,79]. In the TCGA report, PD-L1 gene amplification was elevated in EBVaGCs [2]. Furthermore, PD-L1 immunohistochemical expression in tumor cells was more frequently found in EBVaGCs than in non-EBVaGCs [28]. However, the impact of TILs in GCs is not yet fully understood. In addition, further evaluation of the tumor-infiltrating and peritumoral lymphocytes will be needed in GC with lymphoid stroma, which was significantly associated with high EBV positivity. In GCLS, EBV-positive tumors had more PI3K/AKT pathway mutations than EBV-negative tumors [80]. In addition, because EBVaGCs are significantly correlated with high TILs, new immunotherapeutic strategies associated with T-cells are challenging for the treatment of advanced EBVaGCs [81,82]. ARID1A expression was higher in EBVaGCs than in non-EBVaGCs. In the previous meta-analysis, correlations between EBV positivity and molecular markers, such as p53 and CpG island methylator phenotype, were found [76].
This study has some limitations. First, a subgroup analysis based on EBV detection methods could not be performed due to the methods used in the eligible studies. Second, the impact of study years on EBV positivity could not be fully investigated based on subtypes of GCs. We evaluated only tubular adenocarcinomas among the various GC subtypes. Third, the eligible studies used different antibodies and evaluation criteria for immunohistochemistry. However, subgroup analysis based on antibody and evaluation criteria could not be performed due to insufficient information.

5. Conclusions

Taken together, our results show that the EBV positivity of GCs is frequently found in male patients and GC with lymphoid stroma. Although EBV positivity was highest in Asians, there was no significant difference between study locations. EBV positivity is significantly correlated with ARID1A and PD-L1 expressions, as well as CD8+ TILs in GCs.

Supplementary Materials

The following are available online at https://www.mdpi.com/1648-9144/56/7/345/s1, Table S1 PRISMA Checklist, Table S2 Antibody information and evaluation criteria of immunohistochemical stains in eligible studies, and Table S3 The estimated rates of various markers in gastric carcinoma according to the Epstein-Barr virus positivity.

Author Contributions

Conceptualization, J.-S.P. and N.-Y.K.; methodology, J.-S.P.; software, J.-S.P.; data curation, N.-Y.K.; writing—original draft preparation, J.-S.P. and N.-Y.K.; writing—review and editing, D.-W.K.; funding acquisition, D.-W.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by Chungnam National University Sejong Hospital Research Fund, 2020.

Conflicts of Interest

The authors declare no conflict of interest.

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Medicina 56 00345 g001 550
Figure 1. Flow chart of the searching strategy.
Figure 1. Flow chart of the searching strategy.
Medicina 56 00345 g001
Table
Table 1. Main characteristics of the eligible studies.
Table 1. Main characteristics of the eligible studies.
StudyLocationNumber of PatientsEBVStudyLocationNumber of PatientsEBV
PositiveNegativePositiveNegative
Ahn 2017Korea34926323Ma 2017China57131540
Castaneda 2019Peru37572303Martinez-
Ciarpaglini 2019		Spain20913196
Birkman 2018Finland23817221Min 2016Korea14512421
Böger 2017Germany48422462Nogueira 2017Portugal82973
Bösch 2019Germany18911178Noh 2018Korea44936413
Baek 2018Korea27659217Osumi 2019Japan89871827
Chapel 2000France56749Pereira 2018Brazil28630256
Cho 2004Korea24195Ramos 2019Brazil17818160
de Lima 2012Brazil16011149Ribeiro 2017Portugal17915164
De Rosa 2018Italy16933136Roh 2019Korea58241541
de Souza 2014Brazil12512113Saito 2017Japan23296136
de Souza 2018Brazil30262240Setia 2019USA/Korea48633453
Dong 2016China85559796Shen 2017China20242160
Gasenko 2019Latvia30226276Shibata 1993USA18719168
Grogg 2003USA1107103Shinozaki 2009Japan1114368
Guo 2019China27018252Sun 2019China1652163
Han 2016Korea41030380Trimeche 2009Tunisia96492
Huang 2014Taiwan102052968Truong 2009USA23512223
Huang 2019Taiwan1248651183Valentini 2019Italy70268
Irkkan 2017Turkey105897van Beek 2004Netherlands56641525
Kawazoe 2017Japan48725462Vo 2002USA1081197
Kawazoe 2019Japan22514211Wang 2005China581345
Kijima 2003Japan42028392Wu 2017China34017323
Kim 2019 (a)Korea27325248Xing 2017China96734933
Kim 2019 (b)USA43637Yanagi 2019Japan106769998
Koriyama 2007Japan14949100Zhang 2017China21864154
Kwon 2017Korea39426368Yoon 2019USA1073104
Leung 1999China
(Hong Kong)		791861Yen 2014Brunei
Darussalam		812556
Li 2016China13730107Zhang 2019China101358955
Lim 2017Korea24121526Zhou 2019China30028272
Ma 2016USA44737
EBV, Epstein–Barr virus.
Table
Table 2. The estimated rates of Epstein–Barr virus positivity in gastric carcinoma.
Table 2. The estimated rates of Epstein–Barr virus positivity in gastric carcinoma.
Number
of Subsets		Fixed Effect
(95% CI)		Heterogeneity Test
(p-Value)		Random Effect
(95% CI)		Egger’s Test
(p-Value)
EBV positive rate610.116 (0.111, 0.121)<0.0010.113 (0.088, 0.143)0.912
Asia340.121 (0.115, 0.128)<0.0010.138 (0.096, 0.194)0.238
America130.132 (0.118, 0.148)<0.0010.103 (0.077, 0.137)0.002
Europe120.083 (0.073, 0.095)<0.0010.080 (0.061, 0.106)0.558
Africa10.042 (0.016, 0.106)1.0000.042 (0.016, 0.106)-
CI, confidence interval; EBV, Epstein–Barr virus.
Table
Table 3. Clinicopathological significance of Epstein–Barr virus positivity in gastric carcinomas.
Table 3. Clinicopathological significance of Epstein–Barr virus positivity in gastric carcinomas.
Number
of Subsets		Fixed Effect
(95% CI)		Heterogeneity Test
(p-Value)		Random Effect
(95% CI)		Egger’s Test (p-Value)MRT (p-Value)
Age
EBV-positive 2061.848 (61.115, 62.581)<0.00162.161 (60.126, 64.197)0.6930.568
EBV-negative1663.532 (63.219, 63.846)<0.00163.519 (60.349, 66.690)0.788
Male ratio
EBV-positive 440.823 (0.802, 0.843)0.0630.824 (0.796, 0.849)0.189<0.001
EBV-negative400.638 (0.629, 0.647)<0.0010.639 (0.620, 0.658)0.945
Size (cm)
EBV-positive 123.840 (3.666, 4.015)<0.0014.890 (4.223, 5.556)<0.0010.918
EBV-negative74.595 (4.507, 4.683)<0.0014.588 (4.354, 4.823)0.957
Tumor differentiation, poorly
EBV-positive 200.674 (0.630, 0.716)0.0040.682 (0.611, 0.745)0.5140.112
EBV-negative200.608 (0.595, 0.622)<0.0010.597 (0.525, 0.665)0.761
Lymphatic invasion
EBV-positive 70.487 (0.429, 0.546)<0.0010.476 (0.299, 0.659)0.8430.523
EBV-negative70.498 (0.483, 0.513)<0.0010.522 (0.454, 0.588)0.583
Vascular invasion
EBV-positive 70.297 (0.249, 0.350)<0.0010.286 (0.189, 0.408)0.6360.890
EBV-negative70.276 (0.263, 0.290)<0.0010.297 (0.202, 0.413)0.875
Perineural invasion
EBV-positive 80.415 (0.350, 0.482)<0.0010.399 (0.213, 0.619)0.8070.094
EBV-negative80.517 (0.498, 0.535)<0.0010.521 (0.458, 0.584)0.875
Low pT stage (pT1/T2)
EBV-positive 330.435 (0.401, 0.471)<0.0010.366 (0.274, 0.469)0.0660.670
EBV-negative310.413 (0.402, 0.424)<0.0010.350 (0.283, 0.422)0.141
Lymph node metastasis
EBV-positive 400.493 (0.461, 0.526)<0.0010.595 (0.496, 0.686)0.0140.127
EBV-negative370.593 (0.583, 0.604)<0.0010.655 (0.595, 0.711)0.064
pTNM stage
EBV-positive 250.507 (0.469, 0.544)<0.0010.500 (0.419, 0.580)0.7380.236
EBV-negative250.451 (0.439, 0.463)<0.0010.460 (0.425, 0.496)0.411
CI, confidence interval; MRT, metaregression test; EBV, Epstein–Barr virus.
Table
Table 4. The estimated rates of Epstein–Barr virus positivity in gastric carcinomas according to the histologic types.
Table 4. The estimated rates of Epstein–Barr virus positivity in gastric carcinomas according to the histologic types.
Histologic TypeNumber
of Subsets		Fixed Effect
(95% CI)		Heterogeneity Test
(p-Value)		Random Effect
(95% CI)		Egger’s Test
(p-Value)
Tubular adenocarcinoma60.152 (0.132, 0.174)<0.0010.174 (0.086, 0.320)0.531
Poorly cohesive carcinoma80.102 (0.063, 0.160)0.0380.078 (0.033, 0.173)0.263
Mixed carcinoma40.043 (0.016, 0.109)0.3060.039 (0.013, 0.113)0.054
Papillary carcinoma20.022 (0.004, 0.101)0.5300.022 (0.004, 0.101)-
Mucinous carcinoma40.053 (0.013, 0.190)0.6880.053 (0.013, 0.190)0.042
GCLS50.576 (0.468, 0.676)0.2030.573 (0.428, 0.706)0.748
Solid carcinoma20.130 (0.046, 0.316)0.8280.130 (0.046, 0.316)-
Undifferentiated carcinoma10.111 (0.015, 0.500)1.0000.111 (0.015, 0.500)-
CI, confidence interval; GCLS, gastric carcinoma with lymphoid stroma.
Table
Table 5. The estimated rates of various markers in gastric carcinomas according to the Epstein–Barr virus positivity.
Table 5. The estimated rates of various markers in gastric carcinomas according to the Epstein–Barr virus positivity.
MarkersNumber of SubsetsFixed Effect
(95% CI)		Heterogeneity Test
(p-Value)		Random Effect
(95% CI)		Egger’s Test
(p-Value)		MRT
(p-Value)
PD-L1 in tumor cells
EBV-positive 140.500 (0.447, 0.554)<0.0010.573 (0.449, 0.688)0.047<0.001
EBV-negative140.337 (0.323, 0.352)<0.0010.183 (0.118, 0.272)0.008
PD-L1 in immune cells
EBV-positive 80.610 (0.531, 0.683)<0.0010.832 (0.630, 0.935)0.0070.002
EBV-negative80.572 (0.552, 0.592)<0.001 0.487 (0.357, 0.619)0.081
p53 overexpression
EBV-positive 50.359 (0.256, 0.477)0.2230.194 (0.067, 0.446)0.0230.090
EBV-negative40.464 (0.418, 0.511)<0.0010.439 (0.314, 0.572)0.502
ARID1A
EBV-positive 40.295 (0.206, 0.403)0.3090.295 (0.196, 0.418)0.5190.021
EBV-negative40.176 (0.153, 0.201)0.0550.170 (0.134, 0.214)0.530
HER2
EBV-positive 80.048 (0.024, 0.093)0.7230.048 (0.024, 0.093)0.1670.051
EBV-negative80.101 (0.088, 0.115)<0.0010.104 (0.070, 0.152)0.739
Microsatellite instability
EBV-positive 50.087 (0.040, 0.179)0.2400.077 (0.028, 0.190)0.2300.536
EBV-negative50.104 (0.089, 0.121)<0.0010.108 (0.069, 0.166)0.637
CD8+ TILs
EBV-positive 40.705 (0.584, 0.802)0.1000.761 (0.547, 0.894)0.1630.001
EBV-negative40.307 (0.275, 0.341)<0.0010.269 (0.141, 0.450)0.851
CI, confidence interval; MRT, metaregression test; PD-L1, programmed death-ligand 1; EBV, Epstein–Barr virus; ARID1A, AT-rich interactive domain-containing protein 1A; HER2, human epidermal growth factor receptor 2; TIL, tumor-infiltrating lymphocyte.

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Pyo, J.-S.; Kim, N.-Y.; Kang, D.-W. Clinicopathological Significance of EBV-Infected Gastric Carcinomas: A Meta-Analysis. Medicina 2020, 56, 345. https://doi.org/10.3390/medicina56070345

AMA Style

Pyo J-S, Kim N-Y, Kang D-W. Clinicopathological Significance of EBV-Infected Gastric Carcinomas: A Meta-Analysis. Medicina. 2020; 56(7):345. https://doi.org/10.3390/medicina56070345

Chicago/Turabian Style

Pyo, Jung-Soo, Nae-Yu Kim, and Dong-Wook Kang. 2020. "Clinicopathological Significance of EBV-Infected Gastric Carcinomas: A Meta-Analysis" Medicina 56, no. 7: 345. https://doi.org/10.3390/medicina56070345

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