Diverse Expression Patterns of EBV Oncogenes (LMP2A, EBV-Encoded microRNA, and EBV-encoded dUTPase) in EBV Associated Gastric Carcinoma and their Association with Viral Loads

1. Introduction

Epstein-Barr virus (EBV), with a significant role of 1.5%-2%, has been documented in all types of cancer worldwide, and EBV viral genes are expressed at different periods in cancerous growths ( 1 , 2 ). EBV-associated gastric carcinoma (EBVGC) is considered one of the four subtypes of GC based on molecular features ( 3 ). EBVGC often shows a latency pattern that has been observed with Epstein-Barr nuclear antigen 1 (EBNA1), Epstein-Barr virus-encoded small RNAs (EBER), and BamHI fragment A rightward transcript (BART) microRNA expressions. Various studies consider the latent form of EBV in GC varies between latency types l and 2 ( 4 , 5 ). Although the critical role of EBV in different types of cancer is well documented, the exact mechanism of carcinogenicity of this virus in the EBVGC subtype is not yet clear.

The Bllf3 open reading frame of EBV encodes the EBV-encoded dUTPase enzyme ( 6 ). Although a large number of patients with primary infection or activated EBV infection have EBV-encoded dUTPase antibodies, no antibodies against EBV-encoded dUTPase have been detected in healthy individuals carrying EBV ( 7 ). It has been shown that EBV-infected cells at the lytic stage express high amounts of EBV-encoded dUTPase protein ( 7 ). Several studies have demonstrated the importance of the tumor’s microenvironment in the growth and progression of the disease. Indeed, EBV-encoded dUTPase affects the tumor’s microenvironment by inducing IL-6 and IL-10 expression and increasing the expression of BIC/microRNA-155 (pri-miR-155) and CCL20 ( 8 ).

It has been shown that EBV-encoded LMP2A plays an important role and exerts its biological actions through different mechanisms, including activating the signaling phosphatidylinositol kinase PI3CK and serine-threonine kinase AKT, activating the Notch pathway in epithelial cells in breast and GCs ( 9 ), enhancing survival ( 10 ), and maintaining viral latency through inhibiting the normal activation of the B cell receptor ( 11 ).

Recent studies have shown that EBV can encode viral microRNAs, which, like cellular microRNAs, play an essential role in various physiological processes, such as differentiation, immune signaling, apoptosis, proliferation, and tumorigenesis. EBV encodes at least 40 microRNAs from two regions of the viral genome. While the BART microRNA clusters are located between the intronic regions of the BARTs, the BHRF1 microRNA cluster is located immediately upstream and downstream of the BHRF1 open reading frame ( 12 ). Although many studies have shown that EBV-encoded microRNAs are involved in EBV malignancy, limited data are available regarding the role of EBV-encoded microRNAs in GC ( 12 ).

2. Materials and Methods

2.1. Specimen’s Characteristics and Ethic Statements

Fifty-three fresh frozen tissues matching formalin-fixed paraffin-embedded (FFPE) specimens were collected from surgical resections in the tumor bank at the Cancer Institute of Imam Khomeini Hospital, Tehran, Iran. Nine EBVGC subtype patients confirmed by RT-PCR and CISH test results were selected as the case group. In addition, 44 patients with positive RT-PCR but negative CISH test results were considered the control group. The patient and control groups were selected by the standard CISH test. The mean age of the control group was 53 years (range: 33 to 80), and the female-male ratio was 1/4. On the other hand, the nine EBVGC phenotype patients had a median age of 61 years. The mean age was 58.6 (range: 40 to 74), and the female-male ratio was 1/9.

This study was approved by the clinical research Ethics Committee of the Tehran University of Medical Sciences (IR.TUMS.SPH.REC.1397.324), and all specimens were named numerically before being included in the study.

2.2. EBV DNA Detection by Quantitative Real-Time PCR and EBER1 Detection by CISH

Briefly, DNA was extracted from fresh frozen tissues using DNeasy Blood and Tissue Kits (QIAGEN, Germany), according to the protocol. The extracted DNA was analyzed to identify and quantify the EBV genome (the DNA sequence of the single-copy gene encoding EBNA1) by Gene Proof Epstein-Barr Virus PCR Kit (Gene Proof, Czech), as instructed by the manufacturer.

Epstein-Barr virus-encoded small RNA1 (EBER1) CISH Detection Kit (Master Diagnostica, Spain) was also used to identify specific EBV EBER1 RNA sequences in FFPE of surgical resections to confirm EBVGC phenotype.

2.3. RNA Extraction and cDNA Synthesis

Briefly, the viral RNA was extracted from 30-50 mg of tissue pieces, and the master digestion reagents were used from the extraction kit of Dneasy Blood & Tissue Kits (QIAGEN, Germany). Next, 500 μl of RNX solution (TRIzol) was added to ensure tissue homogenization. After the formation of the pellet, 30 μl of elution buffer was added. The extracted RNA concentration was immediately measured by the NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, USA). A total of 1000 ng RNA of the samples was treated with DNase I to remove the residual DNA, and then cDNA synthesis was performed using Transcriptor First Strand cDNA Synthesis Kit (Roche, Switzerland). The cDNA master mix contents included 1000 ng RNA in 4 μl of 5× RT reaction buffer, 1 μl of dNTP mix (40 μM), 1 μl of random hexamer (300 μM), 0.5 μl of RNase inhibitor (40 U/μl), 0.5 μl of reverse transcriptase (20 U/μl), and nuclease-free water to adjust 20 μl of the final volume. The cDNA synthesis was performed for 10 min at 25°C, followed by 30 min at 55°C, with a final enzyme denaturation for 5 min at 85°C.

2.4. Primer Design

To design primers for LMP2A, EBV-encoded dUTPase, and beta-actin (ACTB as a reference gene) genes, the reference gene was first taken from the NCBI-Gene website and then imputed as a template in the online Primer-BLAST software. Default parameters were considered for the primer design, and only the product size was changed between 100 and 150. The designed primers are listed in table 1.

2.5. EBV-encoded microRNA (BART1, BART2, BHRF1) Detection by TaqMan Real-Time PCR

To detect the EBV-encoded microRNA (BHRF1 and BART clusters), TaqMan RT-PCR was used, as described by Amoroso et al. (doi:10.1128/JVI.01528-10). Quantitative PCRs were performed using the Rotor-Gene^TM 6000 (QIAGEN, Germany). Briefly, the 20 μl reaction consisted of 5 μl of cDNA and 15 μl of the master mix, which was prepared using 1 μl of the 10 μM of the forward and reverse primers, 5 μM of prob, 10 μl of TaqMan master mix (Roche, Switzerland), and 4 μl of nuclease-free water. The cycling conditions consisted of 5 min at 95°C to activate the hot-start polymerase, followed by 40 cycles of 10 sec at 95°C, 20 sec at 60°C, and detection for 20 sec at 72°C. At each stage, positive and negative control were used. The results of BART1, BART2, and BHRF1 expressions (CT value) were determined automatically using the device software.

2.6. EBV-encoded dUTPase and LMP2A mRNA Detection by SYBR Green Real-Time PCR

To detect the expression of EBV-encoded dUTPase and LMP2A, SYBR Green PCR was performed on the first-strand cDNA using Rotor-Gene^TM 6000-6 Plex Instrument (QIAGEN, Germany) with Fast Start Universal SYBR Green Master (Roche, Switzerland). Briefly, 2.5 μl of 1:10 diluted cDNA were added to 22.5 μl of a master mix consisting of 12.5 SYBR Green Master and 1 μl (10 pmol) of forward and reverse primers. The cycling conditions consisted of 10 min denaturation at 95°C to activate the hot-start polymerase, followed by 40 cycles of 15 sec at 95°C, 20 sec at 59°C, and 20 sec at 72°C (data collection was conducted in this step). The melting curve analysis was performed from 65-98°C in 0.5°C/s increments to assess the specificity of RT-PCR products.

2.7. Primer Efficiency and Validation by SYBR Green Real-Time PCR

To construct relative calibration curves, three duplicates of cDNA as 1:10 serial dilutions were prepared for SYBR Green RT-PCR. Primers with more than 85% efficiency in calibration curves had acceptable performance.

2.8. Statistical Analysis

The SPSS Software (version 24) was employed to process the data with Spearman’s rank correlation coefficient and the Kruskal-wills test for clinical data analysis.

3. Results

3.1. Patients’ Data

Fifty-three fresh frozen GC tissues were included in this study, which had positive TaqMan RT-PCR test results with identified viral loads. Nine out of 53, who had been confirmed to have EBVGC subtype by positive CISH EBER1 results on formalin-fixed paraffin-embedded, were considered the case group. In addition, 44 patients with positive RT-PCR and negative CISH test results were also included as the control group.

The mean age of the control group was 53 years (range: 33 to 80), and the female-male ratio was 1/4. The nine EBVGC phenotype patients had a median age of 61 years. The mean age was 58.6 years (range: 40 to 74), and the female-male ratio was 1/9.

3.2. Expression of EBV-Encoded microRNAs (BART1, BART2, BHRF1) and LMP2A in Gastric Carcinoma Tissues

The expression of LMP2A and EBV-encoded microRNAs (BART1, BART2, and BHRF1) was investigated in 53 GC tissues, including EBVGC subtypes that previously had been confirmed by the CISH EBER1 and RT-PCR results, as well as the control group. EBV-encoded microRNAs and LMP2A were identified in 2 out of 9 EBVGC subtypes (22%) simultaneously, and both of them showed a high viral load (513,656 and 8,818,367, respectively). Viral loads of other samples were much less than these two. None of the patients in the control group had LMP2A and EBV-encoded microRNAs (BART1, BART2, and BHRF1) expression.

3.3. Expression of EBV-Encoded dUTPase Gene in Gastric Carcinoma Tissues

EBV-encoded dUTPase expression assay was developed in 53 GC tissues, including nine EBVGC subtypes as the case group that had been confirmed by RT-PCR and the CISH positive results and also 44 GC patients with RT-PCR results. EBV-encoded dUTPase was detected in 4 out of 9 (44.5%) patients, and also 1 gastric carcinoma sample of the control group expressed EBV-encoded dUTPase. Overall, 5 out of 53 (9.4%) GC patients with positive RT-PCR results expressed EBV-encoded dUTPase, most of which had a high EBV viral load.

4. Discussion

The treatment of tumors can improve through concentration on the understanding of their biology ( 13 ). The identification of the genomic features of GC subgroups creates an appropriate roadmap for classifying patients, performing clinical trials, and providing therapeutic goals ( 3 ). The recognition of virus virulence markers also makes it possible to detect high-risk groups in cancer progression ( 14 ).

This study highlights the role of EBV-encoded dUTPase in EBVGC patients. A previous study suggested that some lytic EBV genes can be expressed in EBVGC tumor tissues ( 4 ), but no study assayed the bllf3 (EBV-encoded dUTPase) gene. As such, EBV-encoded dUTPase was investigated and detected in 4 out of 9 (44.5%) EBVGC phenotypes. One sample of the control group from GC that had positive RT-PCR but negative CISH test results also expressed EBV-encoded dUTPase. This may be due to the fact that although the CISH assay is the gold standard to detect EBV EBER with high specificity, it has a lower sensitivity than RT-PCR. Therefore, it is possible that this sample of the control group actually belongs to the case group, which was not detected in the CISH test.

The dUTPase family is the new target of antimicrobial and anti-cancer therapies, which arises in human tumor cells. It has been shown that in human cells, dUTPase silencing siRNA can increase sensitivity to the anti-cancer drug 5-fluorodeoxyuridine ( 15 ). Studies on human dUTPase have shown that the dUTPase enzyme could be a prognostic marker in prognosis and metastasis in colorectal carcinoma ( 16 , 17 ). Many factors are associated with the development of chemoresistance to 5-fluorouracil (5-FU) drugs. Some studies have reported that dUTPase expression is an important mediator of resistance to chemotherapeutic agents in the class of thymidylate synthase inhibitors, such as 5-FU in vivo and in vitro (these agents are used to treat gastrointestinal, breast, and neck cancers) ( 18 ). In this study, clinical data showed that 4 out of 5 EBV-encoded dUTPase patients did not respond to the treatment, and there was no record of the fifth patient. Our study showed that the expression of dUTPase may be correlated with EBVGC patients’ non-response to treatment. Since the sample size of the present study was small, we recommend that future studies investigate the role of EBV-encoded dUTPase in larger sample sizes. In addition, we recommend they assay the level of EBV-encoded dUTPase protein (the product of the bllf3 gene) in the EBVGC subtype.

The present study showed that 2 out of 9 (22%) patients with EBVGC subtypes express LMP2A and EBV-encoded microRNAs. However, none of the patients in the control group had LMP2A expression. The LMP2A protein has been detected in EBV-related malignant tumor biopsies, which induces transformation, anchorage independence, increased motility, and differentiation inhibition, all of which are functions that can cause malignant cell growth ( 9 ). A previous study reported that LMP2A was expressed in 40% of patients with EBVGC subtypes ( 19 ). This data suggest that LMP2A-targeted treatment is suitable for some patients. In this study, 2 out of 9 fresh frozen GC specimens from the EBVGC subtype (22%) expressed LMP2A, both of which had the highest viral load. We recommend that more studies should be performed on the correlation of high viral loads with the expression of LMP2A in fresh frozen samples.

EBV encodes numerous microRNAs that have been recognized to stimulate EBV-associated diseases by targeting the host genes and self-viral mRNA ( 20 ). Two cluster regions of the EBV genome, including BHRF1 encoding three microRNA precursors (BHRF1 to 3) that generate four mature microRNAs and the BART region containing 22 microRNA precursors (BART1 to 22) that produce 44 mature microRNAs ( 21 ).

Some studies have also shown the increased level of some EBV-encoded microRNAs in tumor biopsy specimens of 10 to 100-fold ( 22 ). A study reported that microRNA BARTs expressed more than 10% of the total pool of microRNAs in EBVGC tumor cells ( 23 ). A study on surgically resected tissues from 10 EBVGC subtypes reported that from 44 known viral microRNAs, 40 were expressed at different levels; however, no BHRF cluster microRNA was detected ( 24 ).

Some studies showed that microRNA BARTs were expressed highly in EBV-associated Hodgkin lymphoma and GC, but microRNA BARTs were barely detectable ( 21 ). A study suggested that 18 out of 52 EBVGC cases identified microRNA BART (34%), but none of them expressed the BHRF1 cluster ( 25 ).

In this study, 2 out of 9 (22%) patients that had been confirmed as EBVGC patients were reported to have EBV-encoded microRNAs (BART1, BART2, and BHRF1). None of the patients in the control group expressed EBV-encoded microRNA. Given that the detection of BHRF1 is rare, in this study, two samples expressed BHRF1 with the highest viral loads; therefore, high EBV viral load may be associated with BHRF1 expression. In this study, the details of the microRNA members were not studied.

Our results showed the expression of oncogenes, such as EBV-encoded micro RNAs, LMP2A, and EBV-encoded dUTPase, in EBVGC in the case (EBVGC phenotype confirmed by the gold standard test) and the control group (the presence of EBV reported only by RT-PCR test results), as well as their correlation with response to treatment and viral load. The samples with the highest viral load expressed EBV-encoded micro RNAs and LMP2A. EBV-encoded dUTPase in EBVGC was expressed in patients with progressive disease who also did not respond to treatment. Although the sample size was small, the results of this study pave the way for further research in this area.

Authors' Contribution

Study concept and design: M. S, A. N., T. M. A. and F. N.

Analysis and interpretation of data: M. S. and A. N.

Drafting of the manuscript and wrote final manuscript: M. S., A. N. and S. M. M.

Statistical analysis: M. S. and M. Y.

Ethics

This study was approved by the clinical research ethics committee of the Tehran University of Medical Science. (IR.TUMS.SPH.REC.1397.324) and all specimens were named by numeral before study inclusion.

Conflict of Interest

The authors declare that they have no conflict of interest.

Acknowledgment

We thank the staff of the Virology Department, School of Public Health, Tehran University of Medical Sciences (TUMS). This study was part of a Ph.D. thesis supported by the Tehran University of Medical Sciences (Grant No.: 98-01-27-41043).

References

1. Farrell PJ. Epstein–Barr virus and cancer. Annu Rev Pathol: Mech Dis. 2019; 14:29-53.
2. Zur Hausen H. The search for infectious causes of human cancers: where and why. Virology. 2009; 392(1):1-10.
3. Network CGAR. Comprehensive molecular characterization of gastric adenocarcinoma. Nature. 2014; 513(7517):202.
4. Luo B, Wang Y, Wang X-F, Liang H, Yan L-P, Huang B-H, et al. Expression of Epstein-Barr virus genes in EBV-associated gastric carcinomas. World J Gastroenterol. 2005; 11(5):629.
5. Murphy G, Pfeiffer R, Camargo MC, Rabkin CS. Meta-analysis shows that prevalence of Epstein–Barr virus-positive gastric cancer differs based on sex and anatomic location. Gastroenterology. 2009; 137(3):824-33.
6. Glaser R, Litsky ML, Padgett DA, Baiocchi RA, Yang EV, Chen M, et al. EBV-encoded dUTPase induces immune dysregulation: Implications for the pathophysiology of EBV-associated disease. Virology. 2006; 346(1):205-18.
7. Sommer P, Kremmer E, Bier S, König S, Zalud P, Zeppezauer M, et al. Cloning and expression of the Epstein—Barr virus-encoded dUTPase: patients with acute, reactivated or chronic virus infection develop antibodies against the enzyme. J Gen Virol. 1996; 77(11):2795-805.
8. Williams MV, Cox B, Ariza ME. Herpesviruses dUTPases: a new family of pathogen-associated molecular pattern (PAMP) proteins with implications for human disease. Pathogens. 2017; 6(1):2.
9. Pal AD, Basak NP, Banerjee AS, Banerjee S. Epstein–Barr virus latent membrane protein-2A alters mitochondrial dynamics promoting cellular migration mediated by Notch signaling pathway. Carcinogenesis. 2014; 35(7):1592-601.
10. Hino R, Uozaki H, Inoue Y, Shintani Y, Ushiku T, Sakatani T, et al. Survival advantage of EBV-associated gastric carcinoma: survivin up-regulation by viral latent membrane protein 2A. Cancer Res. 2008; 68(5):1427-35.
11. Portis T, Longnecker R. Epstein–Barr virus (EBV) LMP2A mediates B-lymphocyte survival through constitutive activation of the Ras/PI3K/Akt pathway. Oncogene. 2004; 23(53):8619-28.
12. Navari M, Etebari M, Ibrahimi M, Leoncini L, Piccaluga PP. Pathobiologic roles of epstein–barr virus-encoded microRNAs in human lymphomas. Int J Mol Sci. 2018; 19(4):1168.
13. Allum W, Meyer H, Garofalo A, Schuhmacher J, Demanzoni G, Degiuli M, et al. Gastric cancer in Europe: European union network of excellence (EUNE) for gastric cancer steering group. 2008.
14. Chen X-Z, Chen H, Castro FA, Hu J-K, Brenner H. Epstein–Barr virus infection and gastric cancer: a systematic review. Medicine. 2015; 94(20)
15. Vértessy BG, Tóth J. Keeping uracil out of DNA: physiological role, structure and catalytic mechanism of dUTPases. Acc Chem Res. 2009; 42(1):97-106.
16. Fleischmann J, Kremmer E, Müller S, Sommer P, Kirchner T, Niedobitek G, et al. Expression of deoxyuridine triphosphatase (dUTPase) in colorectal tumours. Int J Cancer. 1999; 84(6):614-7.
17. Kawahara A, Akagi Y, Hattori S, Mizobe T, Shirouzu K, Ono M, et al. Higher expression of deoxyuridine triphosphatase (dUTPase) may predict the metastasis potential of colorectal cancer. J Clin Pathol. 2009; 62(4):364-9.
18. Wilson PM, Fazzone W, LaBonte MJ, Lenz H-J, Ladner RD. Regulation of human dUTPase gene expression and p53-mediated transcriptional repression in response to oxaliplatin-induced DNA damage. Nucleic Acids Res. 2009; 37(1):78-95.
19. Yang J, Liu Z, Zeng B, Hu G, Gan R. Epstein–Barr virus-associated gastric cancer: A distinct subtype. Cancer Lett. 2020; 495:191-9.
20. Zheng X, Wang J, Wei L, Peng Q, Gao Y, Fu Y, et al. Epstein-Barr virus microRNA miR-BART5-3p inhibits p53 expression. J Virol. 2018; 92(23)
21. De Re V, Caggiari L, De Zorzi M, Fanotto V, Miolo G, Puglisi F, et al. Epstein-Barr virus BART microRNAs in EBV-associated Hodgkin lymphoma and gastric cancer. Infect Agents Cancer. 2020; 15(1):1-9.
22. Yang Y-C, Liem A, Lambert PF, Sugden B. Dissecting the regulation of EBV's BART miRNAs in carcinomas. Virology. 2017; 505:148-54.
23. Hooykaas MJ, Kruse E, Wiertz EJ, Lebbink RJ. Comprehensive profiling of functional Epstein-Barr virus miRNA expression in human cell lines. BMC Genom. 2016; 17(1):1-13.
24. Shinozaki-Ushiku A, Kunita A, Isogai M, Hibiya T, Ushiku T, Takada K, et al. Profiling of virus-encoded microRNAs in Epstein-Barr virus-associated gastric carcinoma and their roles in gastric carcinogenesis. J Virol. 2015; 89(10):5581-91.
25. Tsai CY, Liu YY, Liu KH, Hsu JT, Chen TC, Chiu CT, et al. Comprehensive profiling of virus microRNAs of Epstein–Barr virus‐associated gastric carcinoma: highlighting the interactions of ebv‐Bart9 and host tumor cells. J Gastroenterol Hepatol. 2017; 32(1):82-91.