Skip to main content
NCBI home page
Medicine logoLink to Medicine
. 2018 Aug 10;97(32):e11852. doi: 10.1097/MD.0000000000011852

Association between XRCC1 single-nucleotide polymorphisms and susceptibility to nasopharyngeal carcinoma

An update meta-analysis

Juan Lin a, Qing Ye a,∗, Yihong Wang a, Ying Wang b, Yanfen Zeng b
Editor: Kou Yi
PMCID: PMC6133630  PMID: 30095663

Supplemental Digital Content is available in the text

Keywords: meta-analysis, nasopharyngeal carcinoma, polymorphism, XRCC1

Abstract

Background:

Many studies have investigated polymorphisms of X-ray repair cross-complementing protein 1 (XRCC1) and risk of nasopharyngeal carcinoma (NPC), but the results are somewhat contradictory in different studies. There is an urgent need to keep in step with the relevant observational studies to more comprehend the effects of XRCC1 variants on the NPC risk.

Methods:

A systematic literature search accompanied with meta-analysis was carried out to obtain a detailed evaluation on the association between XRCC1 polymorphisms and NPC risk.

Results:

Meta-analyses showed that there was no statistically significant association observed between Arg194Trp/Arg280His variants in the XRCC1 gene and NPC risk with all genetic models, when relatively larger samples were pooled into the update meta-analysis. The reassessment suggested NPC risk was significantly increased with Arg399Gln polymorphism. The significant association was identified in homozygous, recessive, and allelic models, more than previously reported.

Conclusion:

We confirmed that Arg399Gln polymorphism of XRCC1 gene is a potential predictor for susceptibility to NPC, especially for Asians. More studies are required to evaluate the association in different populations.

1. Introduction

Nasopharyngeal carcinoma (NPC) is a malignant tumor of the nasopharynx with an unusual geographical distribution, especially occurs within economically developing countries.[1,2] The high incidence are mainly found in North Africa, Southeast Asia, and the arctic region. It has been reported that about 86,700 new cases of NPC and 50,800 deaths occurred in 2012.[1] NPC is an epithelial cancer whose etiology is associated with several factors, including Epstein–Barr virus (EBV) infection, genetics, and environmental exposures to chemical carcinogens.[3] The difference of clinical response and outcome on NPC suggests the inter-individual variation might play a more important role in NPC susceptibility,[4] especially the ability of DNA damage repair.[5,6]

Damage to cellular DNA relates to the development of cancer.[7] Cells have evolved several systems to detect DNA damage and repair damaged DNA, since mutations arise each time DNA is replicated. Genetic polymorphisms in DNA repair genes may account for some of the observed differences in development of different cancers,[8] including NPC. Therefore, polymorphisms in DNA repair genes may be an explanation for susceptibility of some cancer.[9] The X-ray repair cross-complementing group 1 (XRCC1) gene plays an important role in DNA-damage processing.[10] XRCC1 functions as a scaffold to be recruited to sites of damaged DNA and facilitated in various DNA repair pathways.[11] Three functional polymorphisms in XRCC1, including Arg194Trp, Arg280His, and Arg399Gln, are most commonly studied.[4] Many studies have investigated the association between XRCC1 polymorphisms and clinical outcomes in cancer patients. They revealed that individual susceptibility of cancer treatment and survival of patients was different due to genetic polymorphisms in XRCC1, including head and neck cancer,[12] cervical carcinoma,[13] and non-small-cell lung cancer[14]. Meta-analyses have also revealed significant associations between various polymorphisms in XRCC1 and cancer risk, such as the lung,[15] breast,[16] stomach,[17] esophageal cancer,[18] and NPC.[19]

Several polymorphisms in XRCC1 have been reported to undertake crucial functions in NPC risk. Cho et al first reported high-risk genotypes of XRCC1 for developing NPC.[20] Subsequent studies had shown inconsistent conclusions.[21–27] Most of published studies were conducted with the high NPC incidence regions in Asia, except for North Africa.[25] Although previous 2 studies performed pooling analyses regarding the association of XRCC1 Arg194Trp, Arg280His, and Arg399Gln with NPC risk.[19,28] However, several published studies with additional origin were not included in these meta-analyses.[29–32] Importantly, the previous meta-analyses on XRCC1 from case–control studies conducted different conclusions. Hence, the association of XRCC1 polymorphisms remains unknown before reevaluating the susceptibility effects. Herein, we summarize the data from more reliable studies to perform a meta-analysis to reevaluate the effect of XRCC1 variants (Arg194Trp, Arg280His, and Arg399Gln) on NPC risk.

2. Methods

2.1. Identification of eligible studies

A comprehensive literature search was performed by 2 independent investigators. The database of reference included PubMed, Web of Science, Chinese National Knowledge Infrastructure (CNKI), Wanfang, and Weipu. The published references in English or Chinese were both considered, and last search was updated on January 1, 2018. The key terms were used during searching: “XRCC1,” “Polymorphism,” and “Nasopharyngeal carcinoma.” After filtering duplicate publications, we retrieved all eligible studies and checked for the case–control studies of NPC with at least one of the 3 SNPs, Arg194Trp, Arg280His, and Arg399Gln.

2.2. Inclusion and exclusion criteria

The inclusion criteria were made to select eligible studies. The following factors were mainly considered: case–control studies, focus on XRCC1 polymorphisms and NPC, odds ratio (OR) and 95% confidence interval (CI) with clear genotype, and studies focusing on human beings.

In contrast, the exclusion criteria were used to filter out ineligible studies. A few criteria were included as follows: duplicate publication of an article, only case population reported, studies on family pedigrees, not cancer research, not experiment, and no genotype data.

2.3. Data extraction

According to the inclusion and exclusion criteria, we carried out the data extraction carefully and independently by 2 investigators. These contents were collected from each study: author name, publication year, country and ethnicity of origin, study design, the criteria of NPC, control source, genotyping methods, sample sizes of cases, and controls. Ethnicity was categorized as “African” and “Asian.” The extracted data from 2 authors were compared to reach to consensus on all the data.

2.4. Quality assessment

We established a set of predetermined criteria to score the included studies (Table S1), with a few modification from the previous studies.[33–35] Two reviewers (YQ and ZY) independently evaluated the qualities of these studies. The main parts of these criteria for quality score of studies comprised the following aspects: diagnosed criteria of cases, collected criteria of healthy controls, population size, quality methods of controls, and Hardy–Weinberg equilibrium (HWE). Finally, an overall quality score was generated within a certain range from 0 to 10. Higher score means better quality for quality assessment. Studies gained more than 5 points were regards as eligible studies. Disagreements on the inclusion or exclusion were resolved by corresponding author.

2.5. Statistical analysis

The deviation of genotypes among controls was evaluated by HWE. P < .05 in a Chi-squared test was considered a departure from HWE. The extent of association with XRCC1 polymorphisms was assessed by ORs and 95% CIs. The significance of association was performed by Z-test with P < .05. The genetic models used for meta-analysis were dominant model: BB + BA versus AA; recessive model: BB versus BA + AA; homozygous model: BB versus AA; heterozygous model: BA versus AA; and allelic model: B versus A, respectively (where BB = variant homozygote, BA = heterozygote, AA = wild homozygote, B = variant type, A = wild type).

The heterogeneity analysis used a Q statistic and I2 statistic, respectively.[36,37] Significant inconsistency was satisfied with either P > .10 or I2 > 50%. A fixed-effect model was selected if there was not heterogeneous, otherwise a random-effect model was used.

Sensitivity analysis was used to investigate the stability of outcomes. We deleted any study one by one with all genetic models and recalculated the association. No significant change of the meta-analysis was thought to be stable and reliable results. Finally, publication bias was used to examine the stability of the meta-analysis by Begg funnel plot[38] and Egger regression test[39] with all genetic models. These statistical analyses were all conducted by using Stata SE 12.0.

2.6. Ethical approval

As this article is a meta-analysis of the previous works of literature, in which informed consent has already been obtained by the previous clinical researcher, hence approval of the ethics committee was not required.

3. Results

3.1. Literature search and characteristics of studies

The selection of eligible studies is summarized in Figure 1. A total of 78 publications were relevant to the search term. Among these publications, 16 duplicates and 45 articles were firstly excluded according to improper title and abstract. After reviewing the full text of the remaining literature, we excluded 6 studies, including meeting report, meta-analysis, and not about NPC. Finally, a total of 11 eligible studies were included in meta-analysis of XRCC1 polymorphisms and NPC risk.

Figure 1.

Figure 1

Open in a new tab

Flow chart summarized the selection process of the 11 eligible studies in the meta-analysis. CNKI = Chinese National Knowledge Infrastructure, HWE = Hardy–Weinberg equilibrium.

The characteristics of each study are summarized in Table 1. Among them, 5 studies on XRCC1 Arg194Trp contained 1428 patients and 1519 controls, and 5 studies on XRCC1 Arg280His contained 1416 patients and 1343 controls, and 10 studies on XRCC1 Arg399Gln contained 2143 patients and 2269 controls. The distribution of genotype within controls conformed with HWE, except for 1 study[29] on XRCC1 Arg194Trp and XRCC1 Arg399Gln.

Table 1.

Characteristics of studies included in the meta-analysis.

3.1.

Open in a new tab

3.2. Significant association between XRCC1 Arg399Gln polymorphism and NPC susceptibility

The meta-analysis displayed that no significant association was found between XRCC1 Arg194Trp and NPC risk. In heterogeneity analysis with all genetic models, heterogeneity of studies was to a significant extent. Therefore, a random-effect model should be used in the subsequent meta-analysis. The results are summarized in Table 2. There was no significant association in any genetic model, such as dominant model (OR = 1.24, 95% CI 0.78–1.98, P = .369), recessive model (OR = 1.21, 95% CI 0.49–2.96, P = .682), homozygous model (OR = 1.33, 95% CI 0.45–3.94, P = .602), and heterozygous model (OR = 1.23, 95% CI 0.82–1.86, P = .312). Forest-plot-illustrated meta-analysis of XRCC1 Arg280His and NPC under allelic model (OR = 1.19, 95% CI 0.79–1.79, P = .408) is given in Figure 2.

Table 2.

Summary of meta-analysis for three X-ray repair cross-complementing protein 1 polymorphisms and nasopharyngeal carcinoma risk in both overall and Asian subgroup with five genetic models.

3.2.

Open in a new tab

Figure 2.

Figure 2

Open in a new tab

Forest plots showed no significant association between X-ray repair cross-complementing protein 1 Arg194Trp and nasopharyngeal carcinoma risk under the allelic genetic model. CI = confidence interval, OR = odds ratio.

The meta-analysis also indicated that no significant association was found between XRCC1 Arg280His and NPC risk in any genetic model. Heterogeneity analysis suggested that there was significant heterogeneity in both overall and Asian subgroup with all genetic models. The detailed meta-analysis results under the random-effect model are summarized in Table 2. No significance was detected under the genetic models, including dominant model (OR = 0.97, 95% CI 0.74–1.28, P = .837), recessive model (OR = 0.86, 95% CI 0.45–1.63, P = .645), homozygous model (OR = 0.84, 95% CI 0.46–1.66, P = .682), heterozygous model (OR = 0.99, 95% CI 0.75–1.31, P = .933), and allelic model (OR = 0.98, 95% CI 0.83–1.16, P = .812). Forest-plot-illustrated meta-analysis of XRCC1 Arg280His and NPC under allelic model is given in Figure 3.

Figure 3.

Figure 3

Open in a new tab

Forest plots showed no significant association between X-ray repair cross-complementing protein 1 Arg280His and nasopharyngeal carcinoma risk under the allelic genetic model. CI = confidence interval, OR = odds ratio.

The meta-analysis revealed that significant association was found between XRCC1 Arg399Gln and NPC risk in 3 genetic models. Significant heterogeneity was only observed in the dominant model and heterozygote model, so that the random-effect model was used in those models. No significant association between XRCC1 Arg399Gln and NPC was detected in overall and Asian subgroup under both dominant and heterozygote model (Table 2). In contrast, the fixed-effect model of meta-analysis was selected to be used in the other 3 genetic models. The results of significant association are presented in Table 2, including recessive model (OR = 1.27, 95% CI 1.02–1.60, P = .035), homozygote model (OR = 1.34, 95% CI 1.07–1.70, P = .013), and allele model (OR = 1.13, 95% CI 1.03–1.24, P = .012). Forest-plot-illustrated meta-analysis of XRCC1 Arg399Gln and NPC under allelic model is given in Figure 4. Subgroup analysis was considered in Asian population due to 1 study in other subgroup. The significant association was repetitively identified in homozygous model (OR = 1.36, 95% CI 1.04–1.77, P = .025) and allelic model (OR = 1.11, 95% CI 1.00–1.24, P = .048), while under the recessive model, the P-value showed a slightly significance (OR = 1.29, 95% CI 1.00–1.67, P = .052) (Table 2).

Figure 4.

Figure 4

Open in a new tab

Forest plots showed significant association between X-ray repair cross-complementing protein 1 Arg399Gln and nasopharyngeal carcinoma risk under the allelic genetic model. CI = confidence interval, OR = odds ratio.

3.3. Sensitivity analysis indicating stable and reliable results

To further assess the stability of meta-analysis outcomes, sensitivity analysis was conducted through the sequential omitting of each study and recalculating of the association. The studies with various sample sizes did not show significant changes when deleting any study one by one in every genetic model among three XRCC1 polymorphisms. Moreover, as for XRCC1 Arg194Trp, one study deviated from HWE[29] was also excluded during sensitivity analysis, but the association was not substantially altered. The results of sensitivity analysis suggested that the meta-analysis was stable and reliable.

3.4. Publication bias without remarkably influence

To assess the potential unstable due to publication bias, the funnel plot and Egger test was conducted under all genetic models. We did not observe significant effect on the meta-analysis results with publication bias. The funnel plots in Figure 5 illustrate publication bias of XRCC1 Arg399Gln and NPC, in which the shapes do not show obvious asymmetry. Similarly, Egger test also provided statistical evidence. The statistical P-value for XRCC1 Arg399Gln was .479 in recessive model, .580 in homozygous model, and .799 in allelic model. Both funnel plots and Egger test suggested no publication bias in credibility of outcomes in our meta-analysis.

Figure 5.

Figure 5

Open in a new tab

Begg funnel plot did not show obvious asymmetry for publication bias of X-ray repair cross-complementing protein 1 Arg399Gln under allelic model. SE = standard error.

4. Discussion

Since 2003, several large case–control studies have identified the specific association between XRCC1 polymorphisms and increased risk of NPC.[11] However, NPC risk varies with not only environmental factors but also genetic background,[37] so that the results remain inconclusive. In the present study, we used an update meta-analysis with 11 eligible case–control studies and confirmed the association between XRCC1 polymorphisms and NPC risk. The most important finding in our study was that significant association between XRCC1 Arg399Gln polymorphism and NPC risk was identified in homozygous, recessive, and allelic models. Additionally, our reassessment suggested no evidence for the association between XRCC1 Arg194Trp and Arg280His polymorphisms and NPC risk when relatively larger samples were pooled into the update meta-analysis.

Certainly, the previous several meta-analyses have investigated polymorphisms of XRCC1 gene and risk of NPC.[19,28,40,41] A latest study on meta-analysis suggested the association between XRCC1 Arg399Gln with NPC, which was only detected in homozygous model, but not in the other 4 genetic models.[41] Another meta-analysis study indicated the association between XRCC1 Arg399Gln with NPC in homozygous model, as well as marginally significant association in recessive model.[19] The result contradicts ours due in part to less number of study, 5 studies in previous meta-analyses. However, we reported the association in 3 genetic models by using 10 studies. Therefore, more studies used in meta-analysis showed stronger ability to detect the association. We noticed that the study with significant departure from HWE in the control groups had an impact on the strength of conclusion in the previous meta-analyses. Likewise, Yang et al[28] also detected a significant deleterious effect under homozygous model through the meta-analysis. However, studies conducted in Chinese,[21,22,29] Taiwanese,[20] Malaysian,[32] and North African[25] population did not reported such association. These outcomes indicated the complexity of susceptibility gene for NPC and the related complications. Thus it is beneficial to make the meta-analysis to be updated along with latest study to provide more stable and reliable conclusions.

In conclusion, we demonstrated that Arg194Trp and Arg280His polymorphisms of XRCC1 gene are not significantly associated with NPC risk. The association between XRCC1 Arg399Gln and NPC risk was significant in homozygous, recessive, and allelic genetic models. However, the significant association should be further reevaluate by the meta-analysis with more study and larger population to validate our findings.

Author contributions

J.L. and Q.Y. conceived the study and designed the experiments. Q.Y. and Y.Z. collected Identified the eligible studies. YH.W. and Y.W. performed the meta-analysis. J.L. and Q.Y. were mainly involved in preparation of manuscript. All authors provided input during the writing of the manuscript. All authors reviewed and approved the final manuscript.

Conceptualization: Juan Lin, and Qing Ye.

Data curation: Qing Ye.

Formal analysis: Yihong Wang, Ying Wang.

Funding acquisition: Juan Lin.

Investigation: Yanfen Zeng.

Project administration: Juan Lin.

Resources: Qing Ye.

Software: Yihong Wang, Ying Wang.

Supervision: Juan Lin, Qing Ye.

Validation: Qing Ye, Yanfen Zeng.

Writing – original draft: Qing Ye.

Writing – review & editing: Juan Lin.

Supplementary Material

Supplemental Digital Content
medi-97-e11852-s001.xlsx (8.9KB, xlsx)

Footnotes

Abbreviations: A = wild type, AA = wild homozygote, B = variant type, BA = heterozygote, BB = variant homozygote, CI = confidence interval, CNKI = Chinese National Knowledge Infrastructure, EBV = Epstein–Barr virus, HWE = Hardy–Weinberg equilibrium, NPC = nasopharyngeal carcinoma, OR = odds ratio, XRCC1 = X-ray repair cross-complementing protein 1.

This work was supported by grants from National Natural Science Foundation of China (61475036), Natural Science Foundation of Fujian Province (2014J01286) and Key Clinical Specialist Program of Fujian Province, High level joint research and construction program of Fujian provincial Hospital.

The authors have no conflicts of interest to disclose.

Supplemental Digital Content is available for this article.

References

  • [1].Torre LA, Bray F, Siegel RL, et al. Global cancer statistics, 2012. CA Cancer J Clin 2015;65:87–108. [DOI] [PubMed] [Google Scholar]
  • [2].Chang ET, Adami HO. The enigmatic epidemiology of nasopharyngeal carcinoma. Cancer Epidemiol Biomarkers Prev 2006;15:1765–77. [DOI] [PubMed] [Google Scholar]
  • [3].Cao SM, Simons MJ, Qian CN. The prevalence and prevention of nasopharyngeal carcinoma in China. Chin J Cancer 2011;30:114–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [4].Chen H, Wu M, Li G, et al. Association between XRCC1 single-nucleotide polymorphism and acute radiation reaction in patients with nasopharyngeal carcinoma: a cohort study. Medicine (Baltimore) 2017;96:e8202. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [5].Wang J, Guo C, Gong X, et al. The impacts of genetic polymorphisms in genes of base excision repair pathway on the efficacy and acute toxicities of (chemo)radiotherapy in patients with nasopharyngeal carcinoma. Oncotarget 2017;8:78633–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [6].Bernig T, Chanock SJ. Challenges of SNP genotyping and genetic variation: its future role in diagnosis and treatment of cancer. Expert Rev Mol Diagn 2006;6:319–31. [DOI] [PubMed] [Google Scholar]
  • [7].Broustas CG, Lieberman HB. DNA damage response genes and the development of cancer metastasis. Radiat Res 2014;181:111–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [8].Meyer LA, Westin SN, Lu KH, et al. Genetic polymorphisms and endometrial cancer risk. Expert Rev Anticancer Ther 2008;8:1159–67. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [9].Chaudhuri J, Alt FW. Class-switch recombination: interplay of transcription, DNA deamination and DNA repair. Nat Rev Immunol 2004;4:541–52. [DOI] [PubMed] [Google Scholar]
  • [10].Thompson LH, West MG. XRCC1 keeps DNA from getting stranded. Mutat Res 2000;16:1–8. [DOI] [PubMed] [Google Scholar]
  • [11].Horton JK, Watson M, Stefanick DF, et al. XRCC1 and DNA polymerase beta in cellular protection against cytotoxic DNA single-strand breaks. Cell Res 2008;18:48–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [12].Sturgis EM, Castillo EJ, Li L, et al. Polymorphisms of DNA repair gene XRCC1 in squamous cell carcinoma of the head and neck. Carcinogenesis 1999;20:2125–9. [DOI] [PubMed] [Google Scholar]
  • [13].Cheng XD, Lu WG, Ye F, et al. The association of XRCC1 gene single nucleotide polymorphisms with response to neoadjuvant chemotherapy in locally advanced cervical carcinoma. J Exp Clin Cancer Res 2009;28:91. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [14].Yoon SM, Hong YC, Park HJ, et al. The polymorphism and haplotypes of XRCC1 and survival of non-small-cell lung cancer after radiotherapy. Int J Radiat Oncol Biol Phys 2005;63:885–91. [DOI] [PubMed] [Google Scholar]
  • [15].Zhang X, Miao X, Liang G, et al. Polymorphisms in DNA base excision repair genes ADPRT and XRCC1 and risk of lung cancer. Cancer Res 2005;65:722–6. [PubMed] [Google Scholar]
  • [16].Deligezer U, Dalay N. Association of the XRCC1 gene polymorphisms with cancer risk in Turkish breast cancer patients. Exp Mol Med 2004;36:572–5. [DOI] [PubMed] [Google Scholar]
  • [17].Putthanachote N, Promthet S, Hurst C, et al. The XRCC1 DNA repair gene modifies the environmental risk of stomach cancer: a hospital-based matched case-control study. BMC Cancer 2017;17:680. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [18].Li S, Deng Y, You JP, et al. XRCC1 Arg399Gln, Arg194Trp, and Arg280His polymorphisms in esophageal cancer risk: a meta-analysis. Dig Dis Sci 2013;58:1880–90. [DOI] [PubMed] [Google Scholar]
  • [19].Huang GL, Guo HQ, Yu CY, et al. XRCC1 polymorphisms and risk of nasopharyngeal carcinoma: a meta-analysis. Asian Pac J Cancer Prev 2011;12:2329–33. [PubMed] [Google Scholar]
  • [20].Cho EY, Hildesheim A, Chen CJ, et al. Nasopharyngeal carcinoma and genetic polymorphisms of DNA repair enzymes XRCC1 and hOGG1. Cancer Epidemiol Biomarkers Prev 2003;12:1100–4. [PubMed] [Google Scholar]
  • [21].Cao Y, Miao XP, Huang MY, et al. Polymorphisms of XRCC1 genes and risk of nasopharyngeal carcinoma in the Cantonese population. BMC Cancer 2006;6:167. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [22].Yang ZH, Du B, Wei YS, et al. Genetic polymorphisms of the DNA repair gene and risk of nasopharyngeal carcinoma. DNA Cell Biol 2007;26:491–6. [DOI] [PubMed] [Google Scholar]
  • [23].Dai Q, Yang ZH, Ye YL. Association of the DNA repair gene genetic polymorphisms and risk of nasopharyngeal carcinoma in Sichuan Luzhou population. Guangdong Med J 2007;28:513–5. [Google Scholar]
  • [24].Dai Q, Yang ZH, Ye YL. Association between genetic polymorphisms in the DNA repair gene X-ray repair cross-complementing 1-Arg399Gln and the risk of nasopharyngeal carcinoma in Chinese population from Sichuan province. J Clin Rehabil Tissue Eng Res 2007;11:5861–4. [Google Scholar]
  • [25].Laantri N, Jalbout M, Khyatti M, et al. XRCC1 and hOGG1 genes and risk of nasopharyngeal carcinoma in North African countries. Mol Carcinog 2011;50:732–7. [DOI] [PubMed] [Google Scholar]
  • [26].Ayiheng Q, Bogela a. Study on laryngeal cancer related on polymorphism of the Arg399Gln of XRCC1 DNA repair gene in different nationalities in Xinjiang. J Clin Otorhinolaryngol Head Neck Surg 2013;27:948–51. [PubMed] [Google Scholar]
  • [27].Li Q, Wang JM, Peng Y, et al. Association of DNA base-excision repair XRCC1, OGG1 and APE1 gene polymorphisms with nasopharyngeal carcinoma susceptibility in a Chinese population. Asian Pac J Cancer Prev 2013;14:5145–51. [DOI] [PubMed] [Google Scholar]
  • [28].Yang J, Li L, Yin X, et al. The association between the gene polymorphisms and nasopharyngeal carcinoma risk: evidence from comprehensive meta-analyses (Scientific Paper Competition - China) (Report). J Asian Med Stud Assoc 2014;3:14–21. [Google Scholar]
  • [29].Zhu QB, Fan JP, Wu J, et al. Ploymorphism of XRCC1 gene and its relation with genetic susceptibility of nasopharyngeal carcinoma in Chinese living in Jiangsu, Zhejiang Province and Shanghai. Acad J Sec Mil Med Univ 2014;35:452–5. [Google Scholar]
  • [30].Guo JY, Zheng YH, Cui ZL, et al. Associations and interactions between EB virus infection and XRCC1 Arg399Gln polymorphism in nasopharyngeal carcinoma. Exp Lab Med 2016;34:539–44. [Google Scholar]
  • [31].Singh SA, Ghosh SK. Polymorphisms of XRCC1 and XRCC2 DNA repair genes and interaction with environmental factors influence the risk of nasopharyngeal carcinoma in Northeast India. Asian Pac J Cancer Prev 2016;17:2811–9. [PubMed] [Google Scholar]
  • [32].Visuvanathan S, Chong PP, Yap YY, et al. Distribution and haplotype associations of XPD Lys751Gln, XRCC1 Arg280His and XRCC1 Arg399Gln polymorphisms with nasopharyngeal carcinoma in the Malaysian population. Asian Pac J Cancer Prev 2014;15:2747–51. [DOI] [PubMed] [Google Scholar]
  • [33].Guo J, Jin M, Zhang M, et al. A genetic variant in miR-196a2 increased digestive system cancer risks: a meta-analysis of 15 case-control studies. PLoS One 2012;7:e30585. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [34].Gao LB, Pan XM, Li LJ, et al. RAD51135G/C polymorphism and breast cancer risk: a meta-analysis from 21 studies. Breast Cancer Res Treat 2011;125:827–35. [DOI] [PubMed] [Google Scholar]
  • [35].Li K, Tie H, Hu N, et al. Association of two polymorphisms rs2910164 in miRNA-146a and rs3746444 in miRNA-499 with rheumatoid arthritis: a meta-analysis. Hum Immunol 2013;75:602–8. [DOI] [PubMed] [Google Scholar]
  • [36].Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med 2002;21:1539–58. [DOI] [PubMed] [Google Scholar]
  • [37].DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials 1986;7:177–88. [DOI] [PubMed] [Google Scholar]
  • [38].Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics 1994;50:1088–101. [PubMed] [Google Scholar]
  • [39].Egger M, Davey Smith G, Schneider M, et al. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997;315:629–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [40].Feng YZ, Liu YL, He XF, et al. Association between the XRCC1 Arg194Trp polymorphism and risk of cancer: evidence from 201 case-control studies. Tumour Biol 2014;35:10677–97. [DOI] [PubMed] [Google Scholar]
  • [41].Yang J, Li L, Yin X, et al. The association between gene polymorphisms and risk of nasopharyngeal carcinoma. Med Oncol 2015;32:398. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Digital Content
medi-97-e11852-s001.xlsx (8.9KB, xlsx)

Articles from Medicine are provided here courtesy of Wolters Kluwer Health

RESOURCES