ERCC2 rs13181 Polymorphism Association with Glioma Risk: an Update Meta-Analysis

Abstract

Glioma is the most common type of primary brain tumour which accounts for about 30% of all brain and central nervous system tumours, and approximately 70% of adult malignant brain tumours. Numerous studies have been performed to assess the relationship between ERCC2 rs13181 polymorphism and the risk of glioma development, yet these findings of these studies are often inconsistent and contradictory. Therefore, the aim of this study is to conduct a systematic review and meta-analysis to assess the role of ERCC2 rs13181 in glioma developing. In this work, we have conducted a systematic review and meta-analysis. In order to collect the results of relevant studies on the association of ERCC2 rs13181 gene polymorphism with glioma, we initially searched the Scopus, Embase, Web of Science (WoS), PubMed, and ScienceDirect databases, without a lower time limit, and until June 2020. In order to analyse the eligible studies, the random effects model was used and the heterogeneity of the studies was investigated with the I² index. Data analysis was performed within the Comprehensive Meta-Analysis software (version 2). The total number of studies that focused on patients with glioma was 10. The odds ratio of GG vs TT genotype in patients with glioma based on meta-analysis was 1.08 (0.85–1.37: 95% confidence interval), which indicates the increasing effect of GG vs TT genotype by 0.08. The odds ratio of GG + TG vs TT genotype in patients with glioma was 1.22 (1.38–1.7: 95% confidence interval) based on meta-analysis, which indicates the increasing effect of GG + TG vs TT genotype as 0.22. The odds ratio of TG vs TT genotype in patients with glioma was 1.2 (0.38–1.4: 95% confidence interval), which shows the increasing effect of TG vs TT genotype by 0.2. The odds ratio of G vs T genotype in patients with glioma based on the meta-analysis was 1.15 (1.26–1.4: 95% confidence interval), which indicates the increasing effect of G vs T genotype by 0.15. The odds ratio of GG vs TG + TT genotype in patients with glioma based on meta-analysis was 1.22 (1.33–1.45: 95% confidence interval), which indicates the increasing effect of GG vs TG + TT genotype by 0.22. The results of this systematic review and meta-analysis show that ERCC2 rs13181 polymorphism and its genotypes are an important risk factor for genetic susceptibility to glioma tumour.

Introduction

Glioma, which originates in the glial cells of the brain and spinal cord, is the most common type of primary brain tumour, accounting for about 30% of all brain and central nervous system tumours and approximately 70% of adult malignant brain tumours [1].

Gliomas are categorised according to cell type, degree of malignancy, and location [2, 3]. The main types of glioma include the following: (1) ependymoma, (2) astrocytoma, (3) oligodendroglioma, (4) brainstem glioma, (5) optical nerve glioma, and (6) and mixed types of glioma such as oligoastrocytoma. In recent decades, due to the high mortality rate of high-grade glioma, more attention has been paid to this type of tumour [4, 5].

Research has shown that some genetic polymorphisms are associated with an increased risk of glioma [6–9]. Moreover, many genetic factors can affect glioma, including CCDC26, CCND1, CHEK2, GSTP1, P53, and ERCC1 [10–13]. Ionizing radiation such as X-rays and gamma rays cause extensive damage to DNA. The human genome is also constantly affected by intracellular metabolites, drugs, and environmental mutagens. Therefore, DNA repair mechanisms play an important role in restoring and compensating for the damage caused by these factors, to maintain the stability of the human genome [14–16].

Defects in DNA repair process lead to higher sensitivity to DNA-damaging elements and also results in the accumulation of mutations in the genome; this ultimately leads to cancer and various metabolic diseases [17, 18]. Variants of the ERCC2 gene play a role in reducing helicase activity and reducing the ability of DNA repair in the NER pathway, which in turn increases the risk of cancer [19, 20]. On the other hand, different types of DNA repair genes may impair DNA repair capacity and be a factor in cancer incidence [21]. Recent studies have shown that NER has been one of the most important pathways during DNA repair [22]. In addition, ERCC1, ERCC2, and ERCC5 are the main factors participating in the NER path [23, 24].

Recently, various studies have been performed on the relationship between polymorphisms in the ERCC1 gene (rs3212986), rs11615), the ERCC2 gene (rs1799793), rs13181 and rs238406), and the ERCC5 polymorphism rs17655 and the risk of glioma [25–27]. Several previous studies have reported an association between ERCC2 rs13181 polymorphisms and the risk of glioma, yet the results of these studies have been inconsistent [24, 28–30].

As mentioned above, there are different types of gliomas, but not all studies have shown the results by type of glioma. Therefore, considering this general limitation, this study attempted to answer the following research question: Is the ERCC2 rs13181 gene polymorphism which is a general risk factor, also a risk factor for the development of glioma? By answering this question, the chances of people with polymorphisms for general glioma are determined and future clinical studies can be effective in determining the further association of this polymorphism with certain types of gliomas. Therefore, the aim of this systematic review and meta-analysis is to assess the effect of different genotypes of ERCC2 rs13181 gene polymorphism on glioma development.

Methods

In order to identify and selected relevant articles, the ScienceDirect, Embase, Scopus, PubMed, Web of Science, and Google Scholar databases were searched. The search process entailed using appropriate search keywords of brain tumour, polymorphism, DNA repair gene, variant, ERCC2 rs13181 glioma, and Excision repair cross-complementing group 2, and all possible combinations of these words. No lower time limit was considered in the search process. Once all related studies were identified, the general information of these research works were transferred into EndNote bibliography management software.

In order to maximize the comprehensiveness of the search, the lists of references used in all related articles that were selected following the above search process were manually reviewed.

Inclusion and Exclusion Criteria

Inclusion criteria for studies include (1) evaluation of the relationship between ERCC2 rs13181 polymorphism and glioma risk, (2) results related to the frequency of existing genotype, (3) case studies, (4) access to the full text of articles, (5) access to information of patients with glioma, and (6) odd ratio (OR) is reported with an interval of 95%. Exclusion criteria were (1) case reports, meta-analysis studies, and review papers; (2) non-cancerous glioma studies; (3) duplicate articles; (4) unrelated studies; (5) studies without sufficient data; and (6) unclear research methodology.

Study Selection

Initially, studies that were repeated in various searched databases were excluded from our work. Then, a list of titles of all the remaining articles was prepared, with a view to assess and evaluate the selection. In the first stage, screening, the title and abstract of the articles were carefully examined, and irrelevant articles were removed in accordance with the inclusion and exclusion criteria. In the second stage, eligibility evaluation, the full texts of the articles remaining from the screening stage were examined based on the inclusion and exclusion criteria, and in this stage, the unrelated studies were omitted.

To avoid bias, all steps of reviewing sources and extracting data were performed by two reviewers independently. If an article was not included, the reason for the exclusion them was mentioned. In cases where there was a disagreement between the two reviewers, the article was reviewed by a third reviewer. A total of 10 studies entered the third stage, i.e. quality evaluation.

Quality Evaluation

In order to evaluate the quality of articles (i.e. methodological validity and results), a checklist appropriate to the type of study was used. The STROBE checklist is commonly used to critically evaluate observational studies such as the present work. The STROBE checklist consists of six general scales/sections that include title, abstract, introduction, methods, results, and discussion. Some of these scales have subscales (items) resulting in a total of 32 fields.

In fact, these 32 fields describe different methodological aspects of the study, including title, problem statement, study objectives, type of study, statistical population of the study, sampling strategy, sample size, definition of variables and procedures, study data collection methods, statistical analysis methods, and findings. Accordingly, the maximum score that can be obtained from the quality evaluation using the STROBE 32 checklist is 32; considering the score of 16 as the cut-off point [31], articles with scores of 16 or above were considered as articles with medium or high-quality articles. Two articles with a score below 16 were considered as low-quality studies and were therefore excluded from our work.

Following the evaluation based on the STROBE checklist, 12 articles were entered into the systematic review and meta-analysis process, as they were assessed as medium or high-quality studies, and 2 articles were of poor methodological quality were excluded.

Data Extraction

Information of all final papers entered into the systematic review and meta-analysis process were extracted using a different pre-prepared checklist. This checklist has the following headings: article title, first author name, year of publication, place of study, sample size, country of origin, type of study and control source, genotyping method, total number of case and control groups (total number of cases and controls) genotype or frequency of control alleles.

Statistical Analysis

The I² test was used to evaluate the heterogeneity of the selected studies. In order to investigate the publication bias, due to the high volume of samples in the study, Egger’s test was used at a significance level of 0.05, and the corresponding funnel plots were drawn. Data analysis was performed using the Comprehensive Meta-Analysis software (version 2).

Results

In this work, we have conducted a systematic review and meta-analysis on studies that had examined the association between ERCC2 rs13181 polymorphism and glioma, without a lower time limit until June 2020. We have conducted the research in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Based on the initial search results, 172 possible related articles were identified and transferred into the EndNote bibliography management software. Out of a total of 172 studies identified, 52 studies were duplicates and were therefore excluded. In the screening phase, out of the remaining 120 studies, 63 articles were removed after assessing their titles and abstracts and based on the inclusion and exclusion criteria.

In the eligibility evaluation stage, out of 57 studies, the 45 irrelevant articles were omitted after examining their full text and by considering inclusion and exclusion criteria. In the quality evaluation stage, by assessing the full text of the remaining articles and based on the score obtained from the STROBE checklist, 2 articles that had a low methodological quality were excluded. Finally, 10 studies were selected and included for the final analysis (Fig. 1 and Table 1).

Fig. 1.

The PRISMA flow diagram for the systematic review and meta-analysis

Table 1.

Meta-analysis of the association of ERCC2 rs13181 with glioma risk

Study ID, year	City	Total patients	Total controls	OR (95% CI)
				GG vs TT	GG + TG vs TT	TG vs TT	G vs T	GG vs TG + TT
X. Gao Y.G, 2015	China	104	216	2.05[1.11,3.79]	-	-	-	1.87[1.03,3.37]
McKean-Cowdin R, 2009	USA	143	256	1.22[096,1.55]	1.19[1.02,1.39]	1.18[1.00,1.39]	1.12[1.01,1.26]	1.12[0.90,1.39]
Chen DQ, 2012	China	56	49	1.44[0.92,2.24]	1.36[1.02,1.81]	1.39[0.99,1.81]	1.23[1.00,1.51]	1.22[0.81,1.85]
Salnikova LE, 2013	Russia	33	71	1.47[0.88,2.46]	1.18[0.81,1.72]	1.08[0.72,1.62]	1.20[0.93,1.55]	1.41[0.89,2.23]
Luo KQ, 2013	China	297	415	1.34[0.54,3.35]	-	-	-	-
Rodriguez-Hernandez I, 2014	Spain	115	200	0.32[0.09,0.92]	-	-	-	-
Caggana M, 2001	Boston	148	148	1.27[0.64,2.52]	-	-	-	-
Wrensch M, 2005	USA	365	432	0.82[0.53,1.26]	-	-	-	-
Liu Y, 2009	Houston	367	362	0.69[0.44,1.09]	-	-	-	-
Rajaraman P, 2010	USA	351	481	0.81[0.53,1.24]	-	-	-	-

Investigation of Heterogeneity and Publication Bias (GG vs TT Genotype)

The heterogeneity of the studies was investigated using the I² test and based on this test, I² was obtained as 53.9% which presents a high heterogeneity in the final studies; thus, the random effects model was used to combine the results of the studies. Moreover, the results of publication bias among the studies were measured by Egger’s test, which was not statistically significant (P = 0.664).

The odds ratio of GG vs TT genotype in patients with glioma based on the meta-analysis was 1.08 (0.85–1.37: 95% confidence interval), which indicates the increasing effect of GG vs TT genotype by 0.08. This means that people with this genotype are 8% more likely than others to have glioma (Fig. 2). In Fig. 2, the odds ratio based on the random effects model is shown in which the black square is the odds ratio and the length of the line segment on which the square is placed represents the 95% confidence interval for each study.

Fig. 2.

The odds ratio of GG vs TT genotype in patients with glioma based on the random effects model

Investigation of Heterogeneity and Publication Bias (GG + TG vs TT Genotype)

Heterogeneity of studies was investigated using the I² test and based on this test, I² was obtained as 0 which indicates no heterogeneity in the studies. Therefore, the fixed effects model was used to combine the results of the studies. Moreover, publication bias in the studies was assessed using Egger’s test, and this was not statistically significant (P = 0.700).

The odds ratio of GG + TG vs TT genotype in patients with glioma was 1.22 (1.38–1.7: 95% confidence interval) based on meta-analysis, which indicates the increasing effect of GG + TG vs TT genotype as is 0.22. This means that people with this genotype are 22% more likely than others to have glioma (Fig. 3). In this figure, the squares’ width denotes the 95% confidence interval in each study, and the diamond shape shows the overall combined odds ratio.

Fig. 3.

Overall odds ratio of GG + TG vs TT genotype in patients with glioma based on the fixed effects model

Investigation of Heterogeneity and Publication Bias (TG vs TT Genotype)

Heterogeneity of studies was investigated using the I² test and based on this test, I² was obtained as 0 which indicates no heterogeneity in the studies. Therefore, the fixed effects model was used to amalgamate the results of the studies. Moreover, publication bias in the studies was examined using Egger’s test, and this was not statistically significant (P = 0.890).

The odds ratio of TG vs TT genotype in patients with glioma was 1.2 (0.38–1.4: 95% confidence interval), which indicates the increasing effect of TG vs TT genotype by 0.2. This means that people with this genotype are 20% more likely than others to have glioma (Fig. 4).

Fig. 4.

The odds ratio of TG vs TT genotype in patients with glioma based on the fixed effects model

Investigation of Heterogeneity and Publication Bias (G vs T Genotype)

Heterogeneity of studies was investigated using the I² test. According to this test, I² was obtained as 0 which indicates no heterogeneity in the studies. Therefore, the fixed effects model was used to combine the results of the studies. Also, the results of the publication bias study in the studies were measured with the Egger test, which was not statistically significant (P = 0.279).

The odds ratio of G vs T genotype in patients with glioma based on meta-analysis was 1.15 (1.26–1.4: 95% confidence interval). This shows the increasing effect of G vs T genotype by 0.15, which means that people with this genotype are 15% more likely than others to have glioma (Fig. 5). In Fig. 5, the odds ratio is represented by black squares and the length of the line segment on which the square is placed denotes the 95% confidence interval in each study.

Fig. 5.

Overall odds ratio of G vs T genotype in patients with glioma based on the fixed effects model

Investigation of Heterogeneity and Publication Bias (GG vs TG + TT Genotype)

Heterogeneity of studies was investigated using the I² test and based on this test, I² was obtained as 0. This indicates no heterogeneity in the studies. Therefore, the fixed effects model was used to combine the results of the studies. Besides, publication bias in the studies was examined using Egger’s test, and this was not statistically significant (P = 0.081).

The odds ratio of GG vs TG + TT genotype in patients with glioma was obtained as 1.22 (1.33–1.45: 95% confidence interval). This shows the increasing effect of GG vs TG + TT genotype by 0.22, meaning that people with this genotype are 22% more likely than others to have glioma (Fig. 6). In Fig. 6, the odds ratio is presented as black squares and the length of the line segment on which the square is located represents the 95% confidence interval in each study; the diamond shape represents the total combined odds ratio for the entire study.

Fig. 6.

Overall odds ratio of GG vs TG + TT genotype in patients with glioma based on the fixed effects model

Discussion

In this study, we have investigated the relationship between different genotypes of ERCC2 rs13181 gene polymorphism and glioma. The total number of studies that were systematically reviewed and meta-analysed was 10. Considering the results of meta-analysis, the odds ratio of GG vs TT genotype in patients with glioma was 1.08; the odds ratio of GG + TG vs TT genotype was 1.22; the odds ratio of TG vs TT genotype was 1.2; the odds ratio of G vs T genotype was 1.15, and the odds ratio of GG vs TG + TT genotype was 1.22 in patients with glioma.

The ERCC2 protein is a key element in the NER transcription pathway and plays an important role in altering DNA repair capacity. ERCC2 plays a key role in maintaining genetic stability, and a defect in the ERCC2 protein can influence cancer susceptibility [32]. ERCC2 rs13181 polymorphisms can cause defects in NER, and several pieces of research works have been conducted on the role of inadequate DNA repair in carcinogenesis. Previous studies have also shown that defects in DNA repair function are a risk factor for several types of cancer, including bladder cancer, acute leukaemia, and breast cancer [33, 34].

ERCC2 rs13181 polymorphism may also lead to defects in nucleotide excision repair. The role of adequate DNA repair in carcinogenesis has been extensively investigated. Xue et al. (2012) performed a meta-analysis with 12 case–control studies and found that ERCC2 rs13181 polymorphism was associated with an increased risk of gastric cancer [20]. Guo et al. (2015) performed a meta-analysis with 21 control case studies and reported that ERCC2 rs13181 polymorphism is associated with the susceptibility to oesophageal cancer [35].

Young et al. (2015) performed a meta-analysis on 11 control case studies in an Asian population, and reported that ERCC2 rs13181 could be a risk factor for liver cancer susceptibility [36]. Although a number of epidemiological studies have reported an association between ERCC2 rs13181 polymorphism and the risk of glioma, a number of studies have found no significant association between them.

Caggana et al. (2001) examined the association between ERCC2 rs13181 polymorphism and the risk of glioma in a gender- and age-matched control case study, yet found no association between them [37]. Another study in the USA showed that there was no significant association between ERCC2 rs13181 polymorphism and the risk of adult glioma, and a similar result was observed in the work of Lei Hui [38, 39].

Luo et al. (2013) also conducted a study in an American population and reported that the ERCC2 rs13181 polymorphism does not affect the growth of adult glioma, which is contrary to the results of our study [40]. Wrensch et al. (2005) conducted research in Americans and reported that the ERCC2 polymorphism rs13181 was associated with the risk of glioma [41].

A meta-analysis study in 2017 showed that ERCC2 rs13181 polymorphism contributed to glioma susceptibility [42]. Tavares et al. (2020) found that the main single nucleotide polymorphisms (XRCC1 Arg194Trp), ERCC2 rs13181 and EFEMP1 rs3791679 were associated with an increased risk of glioma [43]. However, several recent studies have reported that ERCC2 rs13181 polymorphism is associated with the risk of glioma, which our meta-analysis results are consistent with these studies [29, 30, 44].

A meta-analysis study conducted by Rodriguez-Hernandez et al. (2014) showed that ERCC2 rs13181 polymorphism increases the risk of glioma [29]. Qi et al. (2017) argued that ERCC2 rs13181 may be associated with an increased risk of glioma, although this association may vary between different ethnicities [45].

In the research conducted by Al-Khatib et al. (2020), no statistically significant relationship was observed between any of the polymorphisms of ERCC2 rs13181, ERCC2 rs1799793, and XRCC1 rs1799782 and glioma susceptibility [46]. The results of their work indicate that there is generally no association between ERCC2 rs13181 gene polymorphism and the risk of glioma. These results are not in line with the results of our work.

Limitations

Studies with larger sample sizes are needed to obtain more reliable results, in different countries and with different ethnic groups. Most of the works have limitations such as the use of one type of population that does not allow the generalisation of the findings to other ethnic groups. In most cases, the samples were collected from only one hospital, and this itself increases bias.

In addition, most studies have not considered the interactions between genes, environmental factors, and even the location of polymorphisms, which are aspects that may affect the risk of glioma. In all articles, the information was not specified by type of glioma, and therefore the authors could not perform an analysis based on the effect of ERCC2 rs13181 polymorphism on different types of glioma as a subgroup.

Conclusion

The results of our meta-analysis show that the ERCC2 polymorphism rs13181 is an important risk factor for the genetic susceptibility of glioma tumour. However, studies with larger sample sizes are needed to confirm these findings.

Abbreviations

STROBE

Strengthening the Reporting of Observational Studies in Epidemiology for Cross-sectional Study

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Author Contribution

NS, KM, RF, and NF contributed to the design. MM contributed to statistical analysis and participated in most of the study steps. SHR, SHSH, and MH prepared the manuscript. SHSH and SE assisted in designing the study and helped in the interpretation of the study. All authors have read and approved the content of the manuscript.

Data Availability

Datasets are available through the corresponding author upon reasonable request.

Declarations

Ethics Approval and Consent to Participate

Ethics approval was received from the ethics committee of deputy of research and technology, Kermanshah University of Medical Sciences. This work adhered to the Declaration of Helsinki.

Consent for Publication

Not applicable.

Competing Interests

The authors declare no competing interests.