Research Paper Volume 10, Issue 5 pp 1073—1088

XPG rs17655 G>C polymorphism associated with cancer risk: evidence from 60 studies

Jie Zhao 1, *, , Shanshan Chen 1, *, , Haixia Zhou 1, *, , Ting Zhang 2, , Yang Liu 3, , Jing He 1, 4, , Jinhong Zhu 3, , Jichen Ruan 1, ,

  • 1 Department of Hematology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
  • 2 Department of Clinical Medicine Center, The First People’s Hospital of Wenling, The Affiliated Wenling Hospital of Wenzhou Medical University, Wenling, Zhejiang 317500, China
  • 3 Department of Clinical Laboratory, Molecular Epidemiology Laboratory, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150040, China
  • 4 Department of Pediatric Surgery, Guangzhou Institute of Pediatrics, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, Guangdong 510623, China
* Equal contribution

received: April 2, 2018 ; accepted: May 8, 2018 ; published: May 20, 2018 ;

https://doi.org/10.18632/aging.101448
How to Cite

Copyright: Zhao et al. This is an open‐access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Xeroderma pigmentosum group G (XPG), a key component in nucleotide excision repair pathway, functions to cut DNA lesions during DNA repair. Genetic variations that alter DNA repair gene expression or function may decrease DNA repair ability and impair genome integrity, thereby predisposing to cancer. The association between XPG rs17655 G>C polymorphism and cancer risk has been investigated extensively, but the results remain contradictory. To get a more accurate conclusion, we performed a comprehensive meta-analysis of 60 case-control studies, involving 27,098 cancer cases and 30,535 healthy controls. Crude odds ratios (ORs) and 95% confidence interval (CIs) were calculated to determine the association of interest. Pooled analysis indicated that the XPG rs17655 G>C polymorphism increased the risk of overall cancer (CC vs. GG: OR=1.10, 95% CI=1.00-1.20; CG vs. GG: OR=1.06, 95% CI=1.02-1.11; CG+CC vs. GG: OR=1.07, 95% CI=1.02-1.12; C vs. G: OR=1.05, 95% CI=1.01-1.09). Stratification analysis by cancer type further showed that this polymorphism was associated with increased risk of gastric cancer and colorectal cancer. This meta-analysis indicated that the XPG gene rs17655 G>C polymorphism was associated with increased overall cancer risk, especially the risk of gastric cancer and colorectal cancer. Further validation experiments are needed to strength our conclusion.

Introduction

Cancer-related deaths continue to rise in both developed and developing countries. In 2012, there were about 14.1 million new cancer cases and 8.2 million cancer-related deaths all over the world. Lung and breast cancer are the most common forms of cancer in human beings. Moreover, the incidences of liver, stomach and colorectal cancer are also very high in men and stomach, while cervix uteri and colorectal cancer prevail in women. Cancer is a complex disease. A variety of cancer risk factors have been recognized, such as smoking, drinking, lack of exercise, poor diet, reproductive changes, and genetic lesions [1]. Inherited genetic causations of cancer risk are mainly unidentified. Thus far, great effects have been made to discover genetic variant alleles implicated in the crucial signaling pathways, which may influence individual cancer predisposition.

Genetic DNAs of living organisms are constantly subjected to various types of damages caused by environmental agents and byproducts (e.g., reactive oxygen species) of cellular metabolic processes. To maintain genome integrity, human beings possess a number of systems for the prevention and restoration of DNA damage. Reduced DNA repair ability is a predisposing factor to cancer [2]. Five common DNA repair pathways have been identified, including nucleotide excision repair (NER), base excision repair, double-strand DNA break repair, mismatch repair, and transcription coupled repair [3,4]. Among these pathways, NER is responsible for removing damaged DNA fragments (e.g., bulky adducts) resulting from radiation or chemical agents [5,6]. In the NER pathway, at least eight vital genes [excision repair cross-complementation group 1 (ERCC1), ERCC2/ Xeroderma pigmentosum group D (XPD), ERCC3/XPB, ERCC4/XPF, ERCC5/XPG, XPA, XPC and XPE/damaged DNA-binding protein 1 (DDB1)] have been well studied, which participate in DNA repair, capable of preserving genetic integrity to prevent cells from malignant transformation [7].

ERCC5/XPG is located on chromosome 13q22-33, consisting of 15 exons and 14 introns . Its protein product is a 1,186 amino acid structure-specific endonuclease, and plays an essential role in the two incision steps of NER [4,8]. XPG is highly polymorphic. Among known single nucleotide polymorphisms (SNPs) in this gene, a nonsynonymous Asp1104His (rs17655, G>C) polymorphism is most frequently studied for its association with cancer risk [2,938]. However the results are inconsistent from study to study. Therefore, we performed this meta-analysis with all eligible publications to investigate the association between the XPG gene rs17655 G>C polymorphism and cancer risk.

Results

Study characteristics

As shown in Figure 1, we found 362 potentially relevant studies from PubMed, EMBASE, CNKI, WANFANG, and Vip databases. After reviewing titles and abstracts, we excluded 281 publications not investigating the association between XPG gene rs17655 polymorphism and cancer risk. And then, full texts of remaining articles were evaluated. Two publications [39,40] were removed for containing overlap data. We also excluded 11 publications [4151] because no sufficient data were reported to calculate ORs and 95% CIs. Furthermore, we eliminated five publications [5256] presenting survival data only. At last, we excluded five publications [5761] due to deviation from HWE. In the end, 58 publications with a total of 27,098 cancer cases and 30,535 healthy controls were included in the meta-analysis. It was noteworthy that, 58 publications actually consisted of 60 case-control studies, because 2 of them included two individual studies. The characteristics of these studies were showed in Table 1. Among these publications, five focused on gastric cancer [15,22,31,37,38], 10 on breast cancer [18,29,33,34,59,6266], four on colorectal cancer [16,20,25,67], four on lymphoma [11,21,68,69], six on bladder cancer [24,7074], five on lung cancer [17,30,7577], eight on skin cancer [14,23,26,32,35,7880], three on HNC [10,81,82], two on endometrial cancer [19,83], laryngeal carcinoma [9,84], and prostate cancer [12,28]. Moreover, there was only one study for each of the following cancers: osteosarcoma [13], hepatocellular carcinoma [36], esophageal carcinoma [85], oral squamous cell carcinoma [86], sarcoma [2], cervical carcinoma [27] and brain cancer [87]. Among these case-control studies, 25 of them had quality scores higher than 9, while 35 had quality scores no more than 9. Finally, this meta-analysis contained 26 hospital-based, 31 population-based, and three mixed control studies.

Flowchart of included publications.

Figure 1. Flowchart of included publications.

Table 1. Characteristics of included studies in the final meta-analysis.

NameYearCancer typeRegionEthnicityDesignGenotypeCaseControlMAFHWEScore
methodGGCGCCAllGGCGCCAll
Feng2016GastricChinaAsianHBPCR-RFLP47854517784107462370.420.2606
Ma2016BreastChinaAsianHBPCR-RFLP1161455932084107462370.420.2607
Du2016ColorectalChinaAsianHBTaqMan2864591338783554051248840.370.6239
Wang2015BreastChinaAsianHBPCR-RFLP9560101100101010.000.9609
Bahceci2014B-NHLTurkeyOthersPBAS-PCR593319343449960.320.6374
Li2014GastricChinaAsianHBPCR-RFLP99833621811282242180.300.1357
Zhu2014BladderChinaAsianHBMassARRAY621606528776139672820.480.8256
Lu2014LarynxChinaAsianHBMassARRAY5369541767863361770.380.0018
Liu2014GastricChinaAsianHBPCR-RFLP991003923812095232380.300.5108
Ruiz-Cosano2013BCLSpainCaucasianPBTaqMan125711721311981142140.250.9657
Zeng2013LungChinaAsianHBPCR-RFLP1577471393561371330.510.3418
Yuan2012HNCChinaAsianPBTaqMan108191953932344332178840.490.55212
Biason2012OsteosarcomaItalyCaucasianHBPCR-RFLP75391613014194152500.250.8998
Gil2012ColorectalPolandCaucasianHBPCR-RFLP863511132643151000.210.6256
Berhane2012ProstateIndiaAsianPBPCR-RFLP587220150667591500.310.0398
Ma2012HNCAmericaCaucasianPBSNPlex6483595210596543506210660.220.09910
Rouissi2011BladderTunisiaAfricanPBPCR4856211254661181250.390.7586
Ibarrola-Villava2011MelanomaSpainCaucasianHBTaqMan32622250598215140243790.250.855
Canbay2011ColorectalTurkeyOthersPBPCR-RFLP433427914883162470.230.35210
Goncalves2011MelanomaBrazilCaucasianHBPCR-RFLP105771019210974252080.300.0319
Doherty2011EndometrialAmericaOthersPBUnknown41825442714408248477030.240.26810
Hsu2010BreastChinaAsianHBTaqMan761911344011292431595310.530.0598
Figl2010MelanomaGerman, SpainCaucasianPBTaqMan7034097411867254658412740.250.4208
Canbay2010GastricTurkeyOthersPBPCR-RFLP251234014883162470.230.3528
Li2010HCCChinaAsianHBTaqMan17423393500151265915070.440.17511
Narter2009BladderTurkeyOthersPBPCR-RFLP252835618193400.310.5055
Abbasi2009LarynxGermanyCaucasianPBReal-time PCR1371038248380230376470.230.77811
Hussain2009GastricChinaAsianPBSNPlex381053818190180903600.501.00012
El-Zein2009HDAmericaCaucasianPBTaqMan104781619812780122190.240.89710
McKean-Cowdin2009BrainAmericaCaucasianMixedTaqMan and MassARRAY499348157100498965731119570.330.00013
Pan2009EsophagealAmericaCaucasianHBTaqMan20113112344287155154570.200.2817
Rajaraman2008BreastAmericaOthersPBTaqMan482288498196743525310790.210.42313
Chang2008LungAmericaAfrica AmericanPBIllumina681196825593138492800.420.8588
Chang2008LungAmericaLatinoPBIllumina60449113138127342990.330.5617
Pardini2008ColorectalCzechCaucasianHBPCR-RFLP33417721532356153235320.190.21111
Smith2008BreastAmericaAfrican AmericanPBMassARRAY1332752183720750.510.9139
Hung2008LungWorldWorldMixedUnknown1852115520932162485151028642810.240.00610
He2008CervicalChinaAsianHBmismatch amplification PCR7194352006780532000.470.0068
Hooker2008ProstateAmericaAfricanHBPCR741196125499142603010.440.4848
Wang2007NMSCTexasCaucasianHBPCR1468911246200119103290.210.1218
Povey2007MelanomaScotlandCaucasianPBPCR-RFLP31416924507252162274410.240.88713
Crew2007BreastAmericaOthersPBSequenom562371669995714097110510.260.84611
An2007HNCAmericaCaucasianHBPCR50728636829519289468540.220.48911
Jorgensen2007BreastAmericaOthersPBTaqMan159931226416595152750.230.78510
Mechanic2006BreastAmericaAfrican AmericanPBTaqMan2313871397572313201236740.420.5099
Mechanic2006BreastAmericaCaucasianPBTaqMan7714096912496614126011330.230.6859
Shen2006BreastAmericaOthersPBTaqMan83638154826271510.250.26811
Sugimura2006OSCCJapanAsianHBPCR-RFLP43592012277112522410.450.3485
Garcia-Closas2006BladderSpainCaucasianHBSequencing6294347811416074458411360.270.84411
Li2006MelanomaAmericaCaucasianHBPCR37320623602370206276030.220.80512
Wu2006BladderAmericaOthersPBTaqMan36422526615371211186000.210.06413
Thirumaran2006BCCHungry, Romania, SlovakiaCaucasianHBTaqMan32517232529330173305330.220.25011
Shen2006NHLAmericaOthersPBTaqMan26017034464352169295500.210.14613
Le Morvan2006SarcomaFranceCaucasianHBPCR-RFLP1821071930831211530.220.2276
Sakiyama2005LungJapanAsianMixedPyrosequencing30050020210022283331246850.420.9007
Shen2005LungChinaAsianPBTaqMan3852261163846251090.440.13310
Weiss2005EndometrialAmericaCaucasianPBPCR-RFLP21513422371250148224200.230.98711
Blankenburg2005MelanomaGermanCaucasianPBPCR-RFLP9100184293181242323740.790.7858
Sanyal2004BladderSwedenCaucasianPBPCR-RFLP182109829917391202840.230.1028
Kumar2003BreastFinlandCaucasianPBPCR-RFLP1089616220182107193080.240.54010
MAF, minor allele frequency; HWE, Hardy-Weinberg equilibrium; B-NHL, B cell non-Hodgkin's lymphoma; BCL, B cell lymphoma; HNC, head and neck cancer; HCC, hepatocellular carcinoma; HD, Hodgkin’s disease; NMSC, non-melanoma skin cancer; OSCC, oral squamous cell carcinoma; BCC, basal cell carcinoma; HB, hospital based; PB, population based; PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; AS-PCR, allele-specific PCR.

Meta-analysis results

As we can see in Table 2 and Figure 2, significant between-study heterogeneity was detected under all the genetic models in the overall analysis. Thus, we used random-effect model. After calculating crude odds ratios (ORs) and 95% confidence interval (CIs), we found that XPG gene rs17655 G>C polymorphism was associated with increased overall cancer susceptibility (CC vs. GG: OR=1.10, 95% CI=1.00-1.20, P=0.032; CG vs. GG: OR=1.06, 95% CI=1.02-1.11, P=0.013; CG+CC vs. GG: OR=1.07, 95% CI=1.02-1.12, P=0.004; C vs. G: OR=1.05, 95% CI=1.01-1.09, P=0.011). Stratification analysis further indicated that the XPG gene rs17655 G>C polymorphism was associated with increased risk of gastric cancer (CC vs. GG: OR=1.53, 95% CI=1.16-2.01, P=0.002; CG vs. GG: OR=1.25, 95% CI=1.02-1.53, P=0.030; CG+CC vs. GG: OR=1.32, 95% CI=1.09-1.60, P=0.005; C vs. G: OR=1.23, 95% CI=1.06-1.42, P=0.005) and colorectal cancer (CG vs. GG: OR=1.30, 95% CI=1.12-1.51, P=0.001; CG+CC vs. GG: OR=1.28, 95% CI=1.11-1.48, P=0.001; C vs. G: OR=1.16, 95% CI=1.05-1.30, P=0.011) (Supplemental Figure 1). We also checked the association in Asian (18 studies) and Caucasian (24 studies), among which ethnic groups studies were enriched. Interestingly, we only observed significant association in Asian (CC vs. GG: OR=1.25, 95% CI=1.05-1.49, P=0.013; CG vs. GG: OR=1.20, 95% CI=1.06-1.35, P=0.002; CG+CC vs. GG: OR=1.21, 95% CI=1.07-1.38, P=0.005; C vs. G: OR=1.13, 95% CI=1.03-1.23, P=0.005). Moreover, the association remained significant in the subgroups with quality score ≤ 9 (CC vs. GG: OR=1.20, 95% CI=1.04-1.39, P=0.015; CG vs. GG: OR=1.09, 95% CI=1.00-1.18, P=0.033; CG+CC vs. GG: OR=1.11, 95% CI=1.02-1.21, P=0.018; C vs. G: OR=1.07, 95% CI=1.01-1.15, P=0.065) and hospital-based studies (CC vs. GG: OR=1.19, 95% CI=1.02-1.39, P=0.028; CG vs. GG: OR=1.10, 95% CI=1.01-1.20, P=0.032; CG+CC vs. GG: OR=1.12, 95% CI=1.02-1.22, P=0.009; C vs. G: OR=1.09, 95% CI=1.02-1.16, P=0.007).

Table 2. Meta-analysis of the association between XPG gene rs17655 G>C polymorphism and overall cancer risk.

VariablesNo. ofHomozygousHeterozygousRecessiveDominantAllele
studiesCC vs. GGCG vs. GGCC vs. CG+GGCG+CC vs. GGC vs. G
OR (95% CI)PhetOR (95% CI)PhetOR (95% CI)PhetOR (95% CI)PhetOR (95% CI)Phet
All601.10(1.00-1.20)0.0011.06(1.02-1.11)0.0401.04(0.97-1.12)0.0281.07(1.02-1.12)0.0021.05(1.01-1.09)0.000
Cancer type
Gastric51.53(1.16-2.01)0.4071.25(1.02-1.53)0.7931.30(0.93-1.82)0.1311.32(1.09-1.60)0.7551.23(1.06-1.42)0.288
Breast111.10(0.95-1.27)0.6131.08(0.95-1.22)0.0471.04(0.92-1.19)0.7681.08(0.95-1.22)0.0361.04(0.96-1.14)0.073
Colorectal41.24(0.96-1.59)0.3951.30(1.12-1.51)0.3951.06(0.84-1.34)0.4011.28(1.11-1.48)0.5541.16(1.05-1.30)0.875
Lymphoma41.13(0.57-2.24)0.0490.98(0.69-1.41)0.0221.17(0.66-2.08)0.1100.97(0.65-1.46)0.0040.98(0.69-1.39)0.001
Bladder60.97(0.71-1.33)0.1771.03(0.92-1.16)0.5200.93(0.70-1.24)0.1931.02(0.91-1.14)0.5881.00(0.91-1.09)0.636
Lung61.26(0.92-1.73)0.0071.13(0.93-1.37)0.0511.12(0.92-1.37)0.1361.16(0.94-1.43)0.0111.11(0.96-1.28)0.012
HNC30.88(0.71-1.09)0.8191.01(0.90-1.14)0.8980.90(0.74-1.10)0.6840.99(0.88-1.11)0.9440.97(0.89-1.06)0.984
Others131.09(0.88-1.36)0.0141.04(0.95-1.14)0.4111.07(0.87-1.31)0.0141.05(0.95-1.15)0.2261.05(0.96-1.15)0.051
Skin80.96(0.75-1.23)0.1750.97(0.88-1.06)0.7930.96(0.79-1.17)0.2540.96(0.88-1.05)0.6570.97(0.90-1.04)0.427
Ethnicity
Asian181.25(1.05-1.49)0.0031.20(1.06-1.35)0.0311.10(0.97-1.25)0.0441.21(1.07-1.38)0.0051.13(1.03-1.23)0.002
Caucasian240.98(0.87-1.10)0.2541.01(0.95-1.06)0.4370.97(0.86-1.09)0.2301.00(0.95-1.05)0.5750.99(0.95-1.04)0.590
Quality score
>9250.98(0.90-1.07)0.8721.04(0.99-1.09)0.3410.97(0.90-1.05)0.9321.03(0.98-1.08)0.2671.01(0.98-1.05)0.447
≤9351.20(1.04-1.39)0.0001.09(1.00-1.18)0.0231.10(0.98-1.24)0.0021.11(1.02-1.21)0.0011.07(1.01-1.15)0.000
Design
HB261.19(1.02-1.39)0.0021.10(1.01-1.20)0.0311.09(0.97-1.24)0.0341.12(1.02-1.22)0.0041.09(1.02-1.16)0.003
PB311.03(0.91-1.17)0.0791.04(0.97-1.10)0.1851.00(0.90-1.12)0.1181.03(0.97-1.10)0.0691.02(0.97-1.07)0.022
Mixed31.04(0.91-1.18)0.3761.05(0.97-1.13)0.6901.01(0.90-1.14)0.5501.04(0.97-1.12)0.5041.03(0.97-1.09)0.431
HNC, Head and Neck cancer; OR, odds ratio; CI, confidence interval; Het, heterogeneity.
Forest plot for the association between the XPG rs17655 G>C polymorphism and overall cancer risk under the dominant model (CG/CC vs. GG). For each publication, the estimation of OR and its 95% CI was plotted with a box and a horizontal line. The diamonds represented the pooled ORs and 95% CIs.

Figure 2. Forest plot for the association between the XPG rs17655 G>C polymorphism and overall cancer risk under the dominant model (CG/CC vs. GG). For each publication, the estimation of OR and its 95% CI was plotted with a box and a horizontal line. The diamonds represented the pooled ORs and 95% CIs.

Publication Bias

Symmetry in the funnel plot (Figure 3) suggested that there was no significant publication bias in this meta-analysis (CC vs. GG: P=0.808; CG vs. GG: P=0.050; CC vs. CG+GG: P=0.806; CG+CC vs. GG: P=0.047; C vs. G: P=0.240).

Funnel plot for the association between XPG gene rs17655 G>C polymorphism and overall cancer risk under the dominant model (CG/CC vs. GG).

Figure 3. Funnel plot for the association between XPG gene rs17655 G>C polymorphism and overall cancer risk under the dominant model (CG/CC vs. GG).

Discussion

In the current meta-analysis, we estimated the association between the XPG gene rs17655 G>C polymorphism and cancer risk based on 60 eligible case-control studies with a total of 27,098 cancer cases and 30,535 healthy controls. Pooled risk estimates revealed that this polymorphism was significantly associated with an increased risk of overall cancer, especially with the risk of gastric cancer and colorectal cancer.

The etiology of cancer is multifactorial [1]. Abnormal accumulation of DNA mutations caused by a variety of factors might eventually trigger carcinogenic process [68]. Thus, properly repairing DNA damages in time to ensure genome stability and integrity is essential to prevent cancer. NER system includes two pathways: global genome repair and transcription-coupled repair, in both of which XPG plays a crucial role [68]. XPG gene, one of the eight vital genes in the NER pathway, is responsible for recognizing and excising DNA lesions on the 3’ side [3,4]. Loads of SNPs have been identified in the XPG gene over the past decades, among which the rs17655 polymorphism has revoked great attention for its association with cancer risk. The rs17655 polymorphism, leading to the replacement of aspartate with histidine at codon 1104 in ERCC5 protein, may cause an alteration in the protein function, thereby likely affecting DNA repair ability, genome integrity, and cancer predisposition.

Numerous studies were performed to explore the association between the rs17655 polymorphism and the risk of various types of cancer. Feng et al. [22] carried out a study in 2016 to investigate the roles of three SNPs (rs2094258, rs751402 and ra17655) in the XPG gene, consisting of 177 patients and 237 controls. They found that the rs17655 polymorphism was associated with an increased risk of gastric cancer. This association was reconfirmed in different types of cancer, including breast cancer by Hsu et al. [29] with 401 cases and 531controls, colorectal carcinoma by Du et al. [20] with 878 cases and 884 controls, lung cancer by Chang et al. [17] with 255 cases and 280 controls, as well as cancer of other types. However, opposite results were also frequently reported. A population-based case-control study containing 196 gastric cases and 397 controls subjects conducted by Hussain et al. [31] revealed that the XPG rs17655 polymorphism might be associated with reduced gastric cancer risk. Additionally, Ruiz-Cosano et al. [68] reported that this polymorphism did not seem to play a major role in lymphoma susceptibility after studying 213 cases and 214 controls. Ma et al. [62] selected 320 cases and 294 controls and found that the rs17655 polymorphism might not confer susceptibility to breast cancer after adjusting for potential confounding factors. Several meta-analyses were also conducted, and unfortunately the results were still inconsistent [8891]. As contradictory results were produced, we performed this meta-analysis to draw a more precise conclusion by including larger sample size and different cancer types from 60 studies. Our result indicated that this polymorphism may increase the risk of overall cancer, especially the risk of gastric cancer and colorectal cancer. The biological function of the rs17655 remains obscure. This polymorphism has been intensively studied for its association with cancer risk as a tagger. It was predicated to be a harmful variant by a sequence homology-based tool [92]. Moreover, its functional potential was further confirmed by SIFT algorithms (scale invariant feature transform) and SNPs3D tools (http://compbio.cs.queensu.ca/F-SNP/) [93]; however, solid in vitro and in vivo data are needed to elucidate biological function of this variant.

There are advantages that strengthened the robustness of our findings. First, we searched five databases to include most of the publications written in English or Chinese. The large sample size provided adequate statistical power. Second, stratified analyses were performed by cancer type, quality score, and source of control. Third, we used the Begg’s funnel plot and Egger’s linear regression test to assess the possible publication bias.

However, several limitations still existed in this meta-analysis. Firstly, selection bias might occur because only publications written in English or Chinese were included. Researches in other languages were missed. Secondly, the number of individual studies for some cancer types, like HNC and prostate cancer (<5 studies), may be inadequate. Third, more than half of included studies had relative low quality scores (≤ 9). Our results should be interpreted cautiously. Further studies with high quality scores are needed to verify the real association.

Additionally, age, sex, living habits, virus infections or some environmental factors may also influence cancer risk. Our findings based on unadjusted estimates for lack of access to original data might suffer from potential confounding bias. Therefore, the results should be interpreted with caution. Finally, lack of biological evidence of the implication of the rs17655 polymorphism in cancer is also a drawback of the study. Mechanistic studies of the rs17655 polymorphism with cancer should be performed in the future.

In conclusion, this meta-analysis suggests that the XPG rs17655 G>C polymorphism is significantly associated with an increased overall cancer risk, especially with the risk of gastric cancer and colorectal cancer. Moreover, large-scale, well-designed studies in different cancers should be conducted to corroborate our findings.

Materials and Methods

Publication search

We searched for relevant articles using the following terms: “ERCC5 or XPG”, “polymorphism or variant”, and “cancer or carcinoma or neoplasm or malignance” in PubMed, EMBASE, CNKI, WANFANG, and Vip databases (the last search was performed on June 17, 2016). We also manually searched the references of the retrieved publications for additional relevant eligible studies.

Inclusion and Exclusion criteria

The publications contained in the meta-analysis had to meet the following criteria: (1) the study was only written in English or Chinese; (2) the study investigated the association between the XPG gene rs17655 polymorphism and the risk of one or more types of cancer; (3) case-control study. If studies had overlapping subjects, the publication including the largest number of individuals were selected.

Exclusion criteria were as follows (1) the study did not report sufficient genotype data to calculate odds ratio (OR) and 95% confidence interval (CI); (2) the study included survival data only. (3) the genotype frequencies of the rs17655 G>C and other polymorphisms were deviated from Hardy-Weinberg equilibrium (HWE) in the controls.

Data Extraction and quality assessment

Two investigators (Chen SS and Zhao J) extracted the following information from each publication independently: first author, publication year, cancer type, country of origin, race, genotyping method, source of controls (hospital-based, population-based and mixed), the genotype counts of cases and controls for the rs17655 G>C polymorphism. We also calculated the score of each publication based on the quality score assessment as described before [94]. All contradictory information was discussed when necessary.

Statistical analysis

We evaluated crude ORs and 95% CIs to assess the association between XPG rs17655 G>C polymorphism and overall cancer risk under the homozygous (CC vs. GG), heterozygous (CG vs. GG), recessive (CC vs. CG+GG), dominant (CG+CC vs. GG), and allele contrast (C vs. G) models. We carried out stratification analyses by cancer type (if one cancer type were investigated in less than three studies, we termed this type as “others”), score (>9 and ≤9), and study design (if a study contained both hospital-based controls and population-based subjects, we termed the study design as “mixed”). We also calculated between-study heterogeneity using the Chi square-based Q-test. When P>0.1 indicating lack of heterogeneity, a fixed-effect model was adopted. Otherwise, a random-effect model would be applied [94]. The potential publication bias was evaluated by Begg’s funnel plot [95] and Egger’s linear regression test [96]. All of the P values were two-tailed. P<0.05 was considered statistically significant. All data analyses were performed by the STATA software (Version 12.0; Stata Corporation, College Station, TX).

Supplementary Materials

Supplemental File

Acknowledgements

This study was supported by grants from the Scientific Research Foundation of Wenzhou (2015Y0492), Zhejiang Provincial Medical and Health Science and Technology plan (2009A148), Zhejiang Provincial Science and Technology Animal Experimental Platform Project (016C37113), Scientific Research Fund of Wenling Science and Technology Bureau (2015C31BA0049), and Natural Science Foundation of Heilongjiang Province (H2015049).

Conflicts of Interest

We had no conflicts of interest to declare.

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