EBNA-1 - BIOMARKER FOR NASOPHARYNGEAL CARCINOMA: A META-ANALYSIS ‎‎

Thuan Duc Lao¹, Thuy Ai Huyen Le¹, Dung Huu Nguyen^2*

Department of Pharmaceutical and Medical Biotechnology, Faculty of Biotechnology, Ho Chi Minh City Open University, Ho Chi Minh City, Vietnam. University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam.

ABSTRACT

Background: Epstein-Bar virus (EBV) is reported to be intimately associated with the development of nasopharyngeal carcinoma (NPC), the most common and high incidence cancer of the head and neck in Asian countries. Among the EBV DNA genome, the EBNA-1 gene plays an important role in NPC. Objective: a meta-analysis was performed according to the PRISMA guideline to systematically evaluate the association between the EBNA-1 and NPC. Materials and methods: Relevant articles were identified by searching the MEDLINE database. The frequency and Odds ratio (OR) were applied to estimate the effect of EBNA-1 based on random-/fix-effects models. Results: eight studies included 1,372 samples: 588 samples from NPC cancer patients, and 784 samples from non-cancerous samples, were enrolled in the meta-analysis. The overall frequency of EBNA-1 in NPC patients and controls was 88.72% and 4.32%, respectively. The current meta-analysis suggested that individuals with the presence of EBNA-1 are associated with NPC risk under the fix-effects model (pooled OR = 331.09, 95%CI = 139.95-783.30). Our findings underscore the correlation among EBNA-1 and all subgroups, including region, method, and source of samples under the fix-effects model. Conclusion: Based on those findings, the presence of EBNA was suggested as a promising biomarker for the diagnosis and screening of NPC‎.

Keywords: EBNA-1, nasopharyngeal carcinoma, meta-analysis

Introduction

 

Nasopharyngeal carcinoma (NPC) is a malignant tumor of the nasopharynx, which has remarkably pronounced differences in distribution according to geography and ancestry, gravitating toward Southern Asia, especially in China and Vietnam. [1-7] A wide range of non-cancerous diseases, benign and malignant originated from the squamous and mesenchymal epithelium occur in the laryngopharynx and among these types , polyps, vocal cord nodules, papilloma, and squamous cell carcinoma are more common. [8] Cancer cells have higher levels of reactive oxygen species (ROS) than normal cells, resulting in increased oxidative stress. [9] Updated to 2018, a total of 129,079 new nasopharyngeal cases were recorded in the world, of which 72,987 nasopharyngeal death cases have occurred. In the Southeast Asian region, a total of 34,681 new cases, of which 22,231 nasopharyngeal death cases were recorded. [6] Notably, the symptoms of NPC were unclear, thus, NPC is commonly diagnosed at a late stage (stage 3 or 4). [10-12] Therefore, the major obstacle to early diagnosis and screening of NPC is the different access due to the deeply seated location of the nasopharynx, as well as the unclear presenting symptoms.

A well-established etiology factor of NPC is strongly associated with Epstein-Barr virus (EBV), also known as human gammaherpesvirus 4 (HHV4), has been postulated. [13-16] The infection of EBV has been reported to be the early step in nasopharyngeal tumorigenesis and act as an important role in the carcinogenesis of the disease. [16-18] Since then, based on the detection of genomic EBV has been received as much attention and represented a prospective biomarker for diagnosis and early screening of NPC. EBV has a double-strand DNA genome consisted of approximately 170-kilobases, encoded more than 85 genes. [19, 20] Among them, EBNA-1 (Epstein-Barr nuclear antigen-1) gene plays an important role in EBV infection. As a function, EBNA-1 is essential for the EBV immortalization of cells and responsible for EBV DNA episome replication, segregation, and persistence of the viral genome, which achieved through sequence-specific DNA binding. [19, 21] However, due to the different sensitivities and intra/interassay coefficients of variation of methods, the reported frequency of EBNA-1, and its prognostic value is highly variable, and also remain controversial. Therefore, we performed the present study to carry out a systematic review and a meta-analysis, notably, the first systematic review and a meta-analysis, to summarize the previously published studies and to evaluate EBNA-1 as prognostic markers for NPC risk.

Materials and Methods

Search strategy and inclusion/exclusion criteria

The current meta-analysis was performed according to the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). [22] The related published articles were searched and collected in MEDLINE database (updated on December 2019), by using separation or combination of following keywords: “Nasopharyngeal carcinoma”, “Epstein-Barr Virus”, “EBV”, “Epstein-Barr Antigen 1”, “EBNA-1”, “prognosis”, “diagnosis”. Additional studies were also identified via the references listed in the articles.

Studies were considered eligible only when they met all of the following inclusion criteria: i) The articles were limited to studies written in English; ii) case-control study designed; iii) provided that data about the frequency of EBNA-1 as well as the sample size in both case and control group. Exclusion criteria were as follows: i) The articles were written in other languages; ii) abstracts, case reports, letter to the editor or unpublished articles were eliminated; iii) studies were related to other tumors and not specific for NPC; iv) studies lacked vital information for analysis.

Data Extraction

The eligibility of each study, the relevant data from the eligible studies were independently retrieved by two authors. Disagreements were resolved through discussion within the third author or our research team. The relevant data were extracted from each study according to the data form, including the first Author’s last name, year of publication, the country where the study was performed, sample type, experimental methods to assess EBNA-1 detection, and some cases and controls subjects.

Statistical Analysis

All data were statistically analyzed using the MedCalc® software by MedCalc Software Ltd. (https://www.medcalc.org/). The frequency of EBNA-1 was calculated in both case and control groups. The strength of the association between EBNA-1 and NPC was evaluated by Odds ratio (OR) with 95% confidence intervals (95%CI). In the present study, the heterogeneity among the included studies was estimated by the Cochran Q test and I² statistics. [23] The cut-off point: p = 0.05 for the Q test and I² were used to test the heterogeneity between studies. [24, 25]. The scale of I² value is classified as following: I² < 25%: no heterogeneity, 25% ≤ I² ≤ 50%: moderate heterogeneity, and I² > 50%: strong heterogeneity. [24, 25] The random-effects model was applied if the heterogeneity among studies existed (p < 0.05 for Q test, I² > 50%). In the case of no between-study heterogeneity, a fixed-effects model was applied to compute the pooled ORs. To determine the presence of publication bias, the symmetry of the funnel plots in which ORs were plotted against their corresponding standard errors were assessed by the Begg’s funnel plot and Egger’s test (p < 0.05 indicates statistically significant). [26, 27]

Results

The characteristics of eligible studies

A total of 409 articles were retrieved from the database. After exclusion of studies that not met the inclusion criteria, finally, eight studies included 1,372 samples: 588 samples from NPC cancer patients, and 784 samples from non-cancerous samples, were enrolled in the meta-analysis. The characteristics of the included studies of EBNA-1 and NPC risk were summarized in Table 1.

The number of patients in the included studies ranged from 13 to 105 (mean: 98). These patients came from Asia (five countries: Taiwan, India, Malaysia, China, Vietnam), Europe (one country: Netherlands) and Africa (one country: Morocco). All the studies were published between 2004 and 2017. The source of NPC samples consisted of biopsy tissue, Biopsy of fine-needle aspiration of neck masses, nasopharyngeal swab, and blood samples. Of this, the biopsy tumor sample was preferentially used in the evaluation of EBNA-1 frequency in NPC. Among the included eight studies, six studies used PCR method, two studies used Realtime-PCR to explore the frequency of EBNA-1 in NPC and corresponding controls.

The frequency of EBNA-1, and the association between EBNA-1 and NPC

Considering the significant heterogeneity between studies (Case: Q = 159.28, p < 0,0001, I² = 94.35%; Control: Q = 63,35, p < 0,0001, I² = 85.79%, 95% CI for I² = 91.48-96.25), the random-effects model was used to explore the frequency of EBNA-1 in NPC and corresponding controls (Fig. 1, Fig. 2).

As shown in Fig. 1, Fig. 2, the frequency of EBNA-1 in NPC patients and controls was 88.72%, and 4.32%, respectively. The meta-analysis results suggested that the frequency of EBNA-1 in NPC patients was significantly higher than the corresponding controls. We also evaluated the association between the presence of EBNA-1 and NPC by analysis OR. The presence of EBNA-1 was associated with an increased NPC risk with a pooled OR of 277.07 (95% CI = 66.0-1,163.16), based on the random-effects model (Q = 39.70, p < 0.0001, I² = 77.33%, 95% CI for I² = 58.37-87.65) (Fig. 3). The funnel plot of pooled analysis, which was quite asymmetric, indicated that there was significant bias among the included studies, therefore there was a factor of influence on the current meta-analysis (Fig. 4). Aiming to remove the influent factor of the current meta-analysis, the sensitivity analysis was applied. The sensitivity analysis found that the study by Krishna et al. (2006) was a relatively poor-quality study. When the study by Krishna et al. (2006) was removed, the between heterogeneity decreased to I² = 8.39% (p = 0.37). Notably, the association between EBNA-1 and NPC increased, which was indicated by the increased OR of 331.09 in the fix-effects model (Fig. 5).

Subgroup analysis was performed according to the region, source of samples and methods for EBNA-1 detection. The association between EBNA-1 and NPC was confirmed in each subgroup (Table 2). Considering the source of samples, the significant association between presence of EBNA-1 and NPC was observed among the NPC biopsy tissue group and non-biopsy group in the fix-effect model (NPC biopsy tissue group: OR = 377.61, 95% CI = 144.36-987.74; non-biopsy group: OR = 295.35, 95% CI = 76.69-1,137.57). With the method for EBNA-1 detection, significant correlation between EBNA-1 and NPC was found among method of PCR group and Real-time PCR in fix-effects model (PCR: OR = 254.62, 95% CI = 99.62-50.78; Real-time PCR: OR = 789.83, 95% CI = 104.02-5,997.52). Regarding to the subgroup of region, there was the significant association between EBNA-1 and NPC among the group of Asia in random-effects model and non-Asia group in fix-effects model (Asia: OR = 361.19, 95% CI = 131.02-995.72; non-Asia: OR = 243.04, 95% CI = 47.28-1,249.42).

 

Sensitivity analysis and publication bias

Aiming to evaluate the stability and reliability of the conclusions, the sensitivity analysis was performed according to the leave-one-out method by excluding one study. As results, the pooled OR was ranged from 288.63 (95% CI = 107.26-776.71) to 502.46 (95%CI = 208.45-1,211.178) under the fix-effects model within the I2 ranged from 0.00 (95%CI = 0.00-59.55, p = 0.59) to 4.55 (95% CI = 0.00-69.38, p = 0.40) (Table 3). Additionally, the quite symmetric in the funnel plot, indicating that publication bias could not be completely excluded, was observed (Fig. 6). Therefore, the results, and conclusion of the present meta-analysis, which was to evaluate the association between EBNA-1 and NPC risk, were stable and reliable.

Discussion

In the current study, a large pool of clinical studies, based on the previously published studies, was used to evaluate the association between EBNA-1 and NPC risk. Eight studies, including 588 samples from NPC cancer patients, were combined to 784 samples from non-cancerous samples, to evaluate the potential of EBNA-1 as a biomarker for screening and diagnosis of NPC. The overall frequency of EBNA-1 in NPC patients and controls were 88.72% (95% CI = 75.87-97.09) and 4.32% (95% CI = 1.07-9.61), respectively. Additionally, the current meta-analysis suggested that individuals with the presence of EBNA-1 are associated with NPC risk (pooled OR = 331.09, 95%CI = 139.95-783.30) (Fig. 5, Table 2). Previous studies reported that EBNA-1 plays an important role in the nasopharyngeal tumorigenesis by the infection of EBV. In detail, EBNA-1 is essential for EBV immortalization of cell and responsible for EBV DNA episome replication, segregation and persistence of viral genome as well as the maintenance of EBV genome in circular episome with multi copies in the infected cell [15, 19, 21]. This indicated that the EBNA-1 gene might play a crucial role in the pathogenesis of NPC, and may be included in diagnosis and screening models of NPC.

After omitting the relatively poor-quality study by Krishna et al. (2006), the heterogeneity of current meta-analysis was decreased to 8.39% (< 25%), indicating no heterogeneity among the included studies. This indicated that the EBNA-1 might play a crucial role in the pathogenesis of NPC. Additionally, a significant association between EBNA-1 and NPC risk was found among in all subgroups, including region, method, and source of samples (Table 2): PCR method was applied to determine the presence of EBNA-1 of a favorable clinical sample of nasopharyngeal carcinoma biopsy samples, which are comprised of tumor cells. Additionally, a significant association between EBNA-1 and NPC was found among the Asian region and the Non-Asia region, which once again confirmed that nasopharyngeal cancer is native to the Asian region.

However, the current meta-analysis exhibited some limitations due to the data of non-English language studies that may contribute to some bias, as well as the evaluation of the correlation between EBNA-1 and clinicopathological features.

Conclusion

Our meta-analysis indicated the presence of EBNA-1 was significantly associated with NPC, which suggested that the EBNA-1 plays a crucial role in the nasopharyngeal tumorigenesis. Additionally, our findings underscore the correlation among EBNA-1 and all subgroups, including region, method, and source of samples. Based on those findings, the presence of EBNA was suggested as a promising biomarker for the diagnosis and screening of NPC.

 

 

Table 1. The characteristics of studies included in the meta-analysis of EBNA-1 and NPC risk

Author, Reference	Year	Region	Case		Control		Method	Source of
			P	N	P	N		Case	Control
Hao et al. [11]	2004	Taiwan	64	70	6	354	PCR	B	Sb
Krishna et al. [28]	2006	India	20	29	6	26	PCR	B	Se
Steven et al. [29]	2006	Netherlands	67	78	0	67	RT-PCR	Sb	Sb
Yap et al. [30]	2007	Malaysia	34	35	0	35	PCR	B	B
Yap et al. [30]	2007	Malaysia	30	34	1	34	PCR	Bf	Bf
Zhang et al. [31]	2012	China	49	49	0	20	PCR	B	B
Zhang et al. [31]	2012	China	48	49	0	20	PCR	Sb	Sb
Lourembam et al. [32]	2015	India	105	105	24	115	RT- PCR	Bl	Bl
Nawaz et al. [33]	2015	Morocco	36	44	1	18	PCR	B	B
Lao et al. [16]	2017	Vietnam	44	95	1	95	PCR	Sb	Sb

Note: B: Nasopharyngeal carcinoma biopsy tissue; Bf: Biopsy of fine-needle aspiration of neck masses; Sb: Nasopharyngeal swab; Bl: Blood sample.

Table 2. Summary of subgroup analysis in the meta-analysis of EBNA-1 and NPC risk

Group	Case		Control		Model, OR, 95% CI (Fix-effects model)	Heterogeneity
	P	N	P	N		I2 (%)	p
Total	477	559	33	758	331.09, 139.95-783.30	8.39	0.37
Region
Asia	374	437	32	673	361.19, 131.02-995.72	3.82	0.40
Non-Asia	103	122	1	85	243.04, 47.28-1,249.42	43.27	0.18
Method
PCR	305	376	9	576	254.62, 99.62-50.78	32.01	0.19
Real-time PCR	172	183	24	182	789.83, 104.02-5,997.52	0.00	1.00
Source of sample
Biopsy sample	213	232	8	461	377.61, 144.36-987.74	21.66	0.28
Non-biopsy	264	327	25	297	295.35, 76.69-1,137.57	10.12	0.34

 

Table 3. Sensitivity analysis of EBNA-1 and NPC risk by the fix-effects model

	OR, 95% CI	Heterogeneity
		I2, 95% CI	p
Omitting Hao et al., 2006	288.63, 107.26-776.71	8.43, 0.00-70.62	0.37
Omitting Steven et al., 2006	302.02, 122.97-741.82	8.64, 0.00-61.67	0.82
Omitting Yap et al., 2007	310.21, 128.62-748.17	11.99, 0.00-71.76	0.34
Omitting Yap et al., 2007	399.27, 135.33-850.54	18.47, 0.00-61.24	0.28
Omitting Zhang et al., 2012	311.09, 129.86-745.25	4.55, 0.00-69.38	0.40
Omitting Zhang et al., 2012	314.91, 130.77-758.32	14.13, 0.00-56.96	0.32
Omitting Lourembam et al., 2015	289.40, 118.01-709.67	20.42, 0.00-62.80	0.27
Omitting Nawaz et al., 2015	392.96, 150.13-1,028.57	0.00, 0.00-63.81	0.52
Omitting Lao et al., 2017	502.46, 208.45-1,211.178	0.00, 0.00-59.55	0.59

 

Figure 1. Forest plot of the EBNA-1 gene detected in NPC samples

Figure 2. Forest plot of the EBNA-1 gene detected in nasopharyngeal control

Figure 3. Forest plot of the association between the presence of EBNA-1 gene and NPC through OR based on the random-effects model.

Figure 4. Forest plot of the association between the presence of EBNA-1 gene and NPC through OR based on the random-effects model.

Figure 5. Forest plot of the association between the presence of EBNA-1 gene and NPC through OR based on the fix-effects model

Figure 6. Forest plot of the association between the presence of EBNA-1 gene and NPC through OR based on the fix-effects model

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