DNA Repair Gene XRCC1 Polymorphisms and Head and Neck Cancer Risk: An Updated Meta-Analysis Including 16344 Subjects

Abstract

Background

DNA repair gene X-ray repair cross complementing group 1 (XRCC1) plays an important role in the maintenance of the genomic integrity and protection of cells from DNA damage. Sequence variation in XRCC1 gene may alter head and neck cancer (HNC) susceptibility. However, these results are inconclusive. To derive a more precise estimation of the relationship between XRCC1 polymorphism and HNC risk, we undertook a meta-analysis involving 16,344 subjects.

Methods

A search of the literature by PubMed, Embase, Web of Science and China National Knowledge Infrastructure was performed to identify studies based on the predetermined inclusion criteria. The odds ratio (OR) with 95% confidence interval (CI) was combined using a random-effects model or a fixed-effects model.

Results

Twenty-nine studies consisting of 6,719 cases and 9,627 controls were identified and analyzed. Overall, no evidence of significant association was observed between XRCC1 Arg194Trp, XRCC1 Arg280His, XRCC1 Arg399Gln genotypes and the risk of HNC in any genetic models. Subgroup analyses according to ethnicity, tumor site, publication year, genotyping method also detected no significant association in any subgroup, except that oral cancer was associated with Arg194Trp variant in recessive model. Furthermore, no significant effect of these polymorphisms interacted with smoking on HNC risk was detected but Arg194Trp homozygous variant.

Conclusion

In conclusion, this meta-analysis suggests that the XRCC1 Arg194Trp, Arg280His and Arg399Gln polymorphism may not involve in HNC susceptibility. Further studies about gene-gene and gene-environment interactions in different populations are required.

About the Authors:

Yin Lou

Affiliation: Department of Plastic Surgery, The second Hospital of Anhui Medical University, Hefei, China

Wen-jia Peng

Affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China

Dong-sheng Cao

* E-mail: [email protected]

Affiliation: Department of Plastic Surgery, The second Hospital of Anhui Medical University, Hefei, China

Juan Xie

Affiliation: Department of Plastic Surgery, The second Hospital of Anhui Medical University, Hefei, China

Hong-hong Li

Affiliation: Department of Plastic Surgery, The second Hospital of Anhui Medical University, Hefei, China

Zheng-xuan Jiang

Affiliation: Department of Ophthalmology, The second Hospital of Anhui Medical University, Hefei, China

Introduction

Head and neck cancer (HNC) is now the fifth most common type of cancer in the world [1], with approximately 434,000 new patients diagnosed annually worldwide [2]. Most of the cases involving new patients occur in economically developing countries, such as India, Brazil, and Thailand [3,4]. HNC is generally divided into three groups: oral cavity, pharynx, and larynx. Evolvement of HNC is a multifactorial process associated with various risk factors. Accumulative evidence indicates that tobacco smoking, drinking alcohol, and chewing betel quid are three major risk factors for HNC [5,6]. These environmental carcinogens may induce a defective DNA damage response, which may lead to apoptosis or may result in genomic instability and un-regulated (proliferative) cell growth [7–9].

The DNA repair system aims to maintain genomic integrity, and constantly challenge the environmental insults and replication errors. Therefore, the alteration of DNA repair genes could increase the risk of carcinoma in the head and neck [10]. Three important DNA repair pathways, including nucleotide excision repair (NER), base excision repair (BER), and double strand break (DSB), are involved in this process. The x-ray repair cross-complementing group 1 (XRCC1) involved in the BER pathway is thought to play a key role in protecting the genome from a variety of risk factors. Three common single nucleotide polymorphisms in the XRCC1 gene, including Arg194Trp (C to T substitution at exon 6 resulting in an Arg to Trp amino acid change), Arg280His (G to A substitution at exon 9 resulting in an Arg to His amino acid change), and Arg399Gln (G to A substitution at exon 10 resulting in an Arg to Gln amino acid change) are most commonly tested in many studies that have examined different populations.

Multiple studies have evaluated the association of HNC risk with polymorphism in the DNA repair genes XRCC1 Arg194Trp, XRCC1 Arg280His, and XRCC1 Arg399Gln. However, these results are inconsistent. While no association between XRCC1 polymorphisms and HNC risk was demonstrated in some studies [11,12], but Ramachandran et al. [13] and Olshan et al. [14] found a relationship between XRCC1 Arg194Trp and Arg399Gln polymorphisms and the risk of HNC. Olshan et al. [14] performed a stratified analysis to estimate the interaction between XRCC1 polymorphisms and smoking, suggesting that the Arg194Trp and Arg399Gln variants of XRCC1 were associated with the risk of HNC in those cases, but no association was found in Kumar’s research [15]. Although Flores-Obando et al. [16] performed a meta-analysis in 2010 on the relationship between XRCC1 polymorphisms and the risk of HNC, subgroup analyses of smoking and genotyping method were not performed. Considering these conflicting results, we conducted an updated meta-analysis to deduce a reasonable conclusion about the relationship between XRCC1 polymorphisms and HNC risk. Subgroup analyses concerning ethnicity, smoking, site of HNC, publication year, and genotyping method were performed. Therefore, the current meta-analysis has a greater ability power to derive a more accurate conclusions than previous meta-analyses.

Materials and Methods

Search strategy

A systematic and electronic search of the PubMed, EMBASE, Web of Science, and China National Knowledge Infrastructure (CNKI) databases was performed to identify studies using combinations of the following search terms: “head and neck”, “oral”, “pharynx”, “larynx”, “nasopharynx”, “cancer”, “tumor”, “carcinoma”, “x-ray repair cross complementing group 1”, “XRCC1”, “Arg194Trp”, “Arg280His”, “Arg399Gln”, “polymorphism”, and “variation”. All of the studies were published from their earliest entry points to March 2013.

Selection

All of the studies met the following inclusion criteria: (1) published in English; (2) examined case-control studies estimating the relationship between XRCC1 polymorphism and the risk of HNC; (3) described genotype frequencies; (4) genotype distribution in controls must be in Hardy-Weinberg equilibrium (HWE); and (5) when duplicated studies were published by the same author obtained from the same patient sample, only the most complete publication study was included in this meta-analysis. Unpublished reports and abstracts were not considered.

Data extraction

The data were collected according to a standard protocol. The following information was extracted from each study: name of the first author, year of publication, country, genotyping methods, ethnicity and source of the cases and controls, characteristics of the sample population, and the genotype numbers from the cases and the controls.

Statistical analysis

We first tested for deviations from the Hardy-Weinberg equilibrium (HWE) in the control groups using the goodness-of-fit test (Chi-square test or Fisher exact test). The odds ratio (OR) with a corresponding 95% confidence interval (CI) was used to examine the association between XRCC1 polymorphism and HNC risk. The current meta-analysis used the following statistical models, the allelic genetic model, the codominant genetic model (homozygote comparison), and the recessive genetic model. Heterogeneity among the studies was assessed using the chi-square-based Q statistic (P<0.1 for the Q test indicates significant heterogeneity) [17]. We also quantified the effect of heterogeneity using the I2 statistic [18]. Either the random-effects model (DerSimonian-Laird method [19]) or the fixed-effects model (Mantel-Haenszel method [20]) was used to calculate pooled effect estimates in the presence or absence of heterogeneity, respectively. Finally, potential publication bias was evaluated through Begg’s test and Egger’s test by visual analysis of the funnel plot [21,22]. P< 0.05 was considered statistically significant publication bias. Genotype frequencies in the control populations according to race were calculated and tests on the equality of proportions was performed for the Asian and Caucasian control populations in order to compare differences in genotype frequencies between the two groups. All statistical analyses were performed with the STATA version 10.0 software (Stata Corporation, College Station, TX).

Results

Studies characteristics

As shown in Figure 1, the computerized search using the search strategy mentioned above delivered 38 publications. Of these, two papers were excluded due to the fact that they did not evaluate the association between HNC risk and XRCC1 polymorphisms [23,24]. Subsequently, five studies were excluded because of the lack of useful genotype data [25–29]. In the remaining 31 studies, two papers were excluded because of overlapping data [30,31]. Ultimately, 29 studies were identified as eligible and they were analyzed [11–15,32–55].

[Figure omitted. See PDF.]

Figure 1. Flow diagram of articles selection process.

https://doi.org/10.1371/journal.pone.0074059.g001

In total, 29 reports, consisting of 6,719 cases and 9,627 controls, matching the inclusion criteria were included in the present meta-analysis. The characteristics are summarized in Table 1. Of those 29 reports, 15 studies were performed on Caucasians, 10 studies were performed on Asians, and four studies were performed on a mixed population. In the 29 studies, 23 focused on the relationship between XRCC1 Arg194Trp polymorphism and HNC risk, 11 focused on Arg280His polymorphism, and 28 investigated the association between Arg399Gln polymorphism and HNC risk. In 19 studies, the controls were from a healthy population and in eight studies the controls were from a hospital population.

First author (year) Country Ethnicity Control source Tumor Sites Genotyping Methods Sample size (case/control) Research of environmental factors

Sturgis et al.(1999) USA Caucasian Hospital Oral cavity, larynx, oro/hypo-pharynx PCR-RFLP 203/424 NR

Olshan et al.(2002) USA Caucasian Hospital Oral cavity, larynx, pharynx PCR-RFLP 98/161 Smoking

Varzim et al.(2003) Portugal Caucasian Healthy Larynx PCR-RFLP 88/178 NR

Cho et al.(2003) Taiwan Asian Healthy Nasopharynx PCR-RFLP 334/282 NR

Tae et al.(2004) Korea Asian Hospital Oral cavity, larynx, oro/hypo-pharynx Sequence 129/157 NR

Demokan et al.(2005) Turkey Other Healthy NR PCR-RFLP 95/98 Smoking, alcohol

Matullo et al.(2005) Europe Caucasian Healthy Oral cavity, larynx, pharynx Taqman 82/1094 Smoking

Rydzanicz et al.(2005) Poland Caucasian Healthy Oral cavity, tongue, larynx and pharynx PCR-RFLP 182/143 Smoking

Gajecka et al.(2005) Poland Caucasian Healthy Larynx PCR-RFLP 293/319 NR

Kietthubthew et al. (2006) Thailand Asian Healthy Oral cavity PCR-RFLP 106/164 Smoking

Ramachandran et al. (2006) India Asian Hospital Oral cavity PCR-RFLP 110/110 Smoking, alcohol, betel quid chewing

Cao et al.(2006) China Asian Healthy Nasopharynx PCR-RFLP 425/501 Smoking

Li et al.(2007) USA Caucasian Healthy Oral cavity, larynx, pharynx PCR-RFLP 830/854 Smoking, alcohol

Majumder et al.(2007) India Asian Hospital Oral cavity PCR-RFLP 309/385 NR

Yang et al.(2007) China Asian Healthy Nasopharynx PCR-RFLP 153/168 NR

Ho et al.(2007) USA Caucasian Hospital Oral cavity PCR-RFLP 138/503 NR

Harth et al.(2008) Germany Caucasian Hospital Oral cavity, larynx, pharynx PCR-RFLP 310/300 Smoking

Yen et al.(2008) Taiwan Asian Hospital Oral cavity PCR-RFLP 103/98 NR

Csejtei et al.(2009) Hungary Caucasian Healthy Oral cavity, larynx, pharynx PCR-RFLP 108/102 Smoking

Kowalski et al.(2009) Poland Caucasian Healthy Oral cavity, larynx, pharynx PCR-RFLP 92/124 Smoking

Applebaum et al. (2009) USA Caucasian Healthy Oral cavity, larynx, oro/hypo-pharynx PCR-RFLP 483/547 Smoking

Jelonek et al.(2010) Poland Caucasian Healthy NR PCR-RFLP 104/252 NR

Gugatschka et al.(2011) Austria Caucasian Healthy NR Taqman 168/463 NR

Laantri et al.(2011) Morocco African NR Nasopharynx Taqman 512/477 NR

Kumar et al.(2012) India Asian Healthy Oral cavity, tongue, larynx and pharynx PCR-RFLP 278/278 Smoking, alcohol, tobacco chewing

Yuan et al.(2012) China Asian Healthy Oral cavity, larynx, oropharynx Taqman 390/886 NR

Al-Hadyan et al. (2012) Saudi Arabia Other Healthy Nasopharynx Sequence 156/251 NR

Dos Reis et al.(2012) Brazil Other Healthy Oral cavity PCR-RFLP 150/150 NR

Kostrzewska-Poczekaj et al.(2012) Poland Caucasian NR Oral cavity, larynx PCR-RFLP 290/158 NR

Table 1. Main characteristics of studies included in the meta-analysis.

Abbreviations:NR= not reported; PCR-RFLP= PCR-based restriction fragment length polymorphism

CSV

Download CSV

The distribution of XRCC1 Arg194Trp, XRCC1 Arg280His, and XRCC1 Arg399Gln polymorphism genotype frequencies between the HNC cases and the controls in the 29 studies are shown in Table 2. Noticeably, genotype distribution in the controls of Arg194Trp polymorphism in the study by Demokan et al. [36] and Arg399Gln polymorphism in the study by Dos Reis et al. [46] deviate from HWE, which are excluded in the subgroup analyses.

Gene Polymorphism First author (year) Cases (n) Controls (n) P-value of HWE in controls

XRCC1-Arg194Trp Arg/Arg Arg/Trp Trp/Trp Arg/Arg Arg/Trp Trp/Trp

Sturgis et al. (1999) 180 22 1 363 61 0 0.279

Olshan et al. (2002) 82 16 0 135 26 0 0.537

Varzim et al. (2003) 80 8 0 160 18 0 0.777

Tae et al. (2004) 59 52 9 101 39 5 0.879

Matullo et al. (2005) 78 4 0 951 141 2 0.391

Rydzanicz et al. (2005) 165 16 1 129 14 0 0.827

Gajecka et al. (2005) 262 27 1 291 33 1 0.998

Kietthubthew et al. (2006) 40 50 16 77 67 20 0.664

Ramachandran et al. (2006) 66 37 7 90 19 1 0.999

Cao et al. (2006) 232 166 19 235 217 43 0.776

Majumder et al. (2007) 248 58 3 317 62 8 0.074

Yang et al. (2007) 62 79 12 99 65 4 0.204

Ho et al. (2007) 108 29 0 433 69 1 0.592

Harth et al. (2008) 217 40 1 259 39 2 0.924

Yen et al. (2008) 48 40 15 54 35 9 0.643

Csejtei et al. (2009) 96 11 1 85 15 2 0.425

Kowalski et al. (2009) 71 21 0 102 22 0 0.556

Applebaum et al. (2009) 427 55 2 485 61 3 0.776

Gugatschka et al. (2011) 148 20 0 397 63 3 0.959

Laantri et al. (2011) 492 55 4 470 41 1 0.994

Kumar et al. (2012) 144 111 23 121 131 26 0.535

Dos Reis et al. (2012) 127 23 0 123 24 3 0.396

XRCC1-Arg280His Arg/Arg Arg/His His/His Arg/Arg Arg/His His/His

Cho et al. (2003) 275 55 2 215 66 2 0.442

Tae et al. (2004) 113 21 1 139 29 0 0.473

Ramachandran et al. (2006) 77 31 2 83 26 1 0.798

Majumder et al. (2007) 225 79 3 297 87 3 0.461

Yang et al. (2007) 125 27 1 131 35 2 0.981

Ho et al. (2007) 125 13 0 453 50 0 0.503

Harth et al. (2008) 283 28 1 270 30 0 0.660

Applebaum et al. (2009) 437 46 1 492 52 4 0.150

Gugatschka et al. (2011) 159 9 0 430 32 1 0.885

Laantri et al. (2011) 431 114 10 405 92 9 0.382

Kumar et al. (2012) 129 123 26 142 116 20 0.855

XRCC1- Arg399Gln Arg/Arg Arg/Gln Gln/Gln Arg/Arg Arg/Gln Gln/Gln

Sturgis et al. (1999) 94 77 32 181 197 46 0.782

Olshan et al. (2002) 45 50 3 62 82 17 0.412

Varzim et al. (2003) 37 40 11 80 80 18 0.954

Cho et al. (2003) 174 128 32 152 109 21 0.972

Tae et al. (2004) 69 51 9 86 64 7 0.517

Demokan et al. (2005) 42 41 12 39 46 13 0.995

Matullo et al. (2005) 34 38 10 484 482 128 0.892

Rydzanicz et al. (2005) 63 98 21 59 63 21 0.825

Gajecka et al. (2005) 106 153 34 124 145 50 0.783

Kietthubthew et al. (2006) 55 45 6 67 74 23 0.940

Ramachandran et al. (2006) 46 48 16 73 33 4 0.996

Cao et al. (2006) 241 152 32 270 201 30 0.651

Li et al. (2007) 335 374 121 360 385 109 0.929

Majumder et al. (2007) 134 143 32 170 179 36 0.523

Yang et al. (2007) 93 54 6 95 67 6 0.370

Ho et al. (2007) 61 62 15 220 216 67 0.486

Harth et al. (2008) 114 166 30 143 121 36 0.423

Csejtei et al. (2009) 50 47 11 53 41 8 0.999

Kowalski et al. (2009) 37 44 11 49 53 22 0.521

Applebaum et al. (2009) 192 229 62 232 246 69 0.956

Jelonek et al.(2010) 47 50 7 103 124 25 0.374

Gugatschka et al. (2011) 70 74 24 204 198 61 0.503

Laantri et al. (2011) 274 193 45 279 163 35 0.268

Kumar et al. (2012) 128 124 26 98 144 36 0.323

Yuan et al. (2012) 221 146 23 481 339 66 0.842

Al-Hadyan et al. (2012) 96 50 10 135 99 17 0.980

Kostrzewska-Poczekaj et al. (2012) 110 154 26 50 81 27 0.837

Arg194Trp influenced by smoking Arg/Arg Arg/Trp Trp/Trp Arg/Arg Arg/Trp Trp/Trp

Olshan et al. (2002) 74 16 0 81 16 0 0.675

Rydzanicz et al. (2005) 165 16 1 129 14 0 0.827

Cao et al. (2006) 154 108 9 78 62 14 0.947

Csejtei et al. (2009) 96 11 1 85 15 2 0.425

Kowalski et al. (2009) 49 17 0 44 8 0 0.835

Arg399Gln influenced by smoking Arg/Arg Arg/Gln Gln/Gln Arg/Arg Arg/Gln Gln/Gln

Rydzanicz et al. (2005) 63 98 21 59 63 21 0.825

Cao et al. (2006) 156 102 21 85 60 12 0.953

Csejtei et al. (2009) 50 47 11 53 41 8 0.999

Kowalski et al. (2009) 19 36 11 36 16 0 0.423

Table 2. Distribution of XRCC1 genotypes among head and neck cancer cases and controls included in the meta-analysis.

Abbreviations: HWE= Hardy–Weinberg equilibrium.

CSV

Download CSV

Meta-analysis results

The overall results of the meta-analysis for XRCC1 polymorphism and the risk of HNC are shown in Table 3.

Comparison Number of studies Sample size (case/control) Test of association Test of heterogeneity Publication bias

OR 95%CI P value Model Q P value I2 P value (Begg’s) P value (Egger’s)

Arg194Trp

Arg194 allele vs. Trp194 allele

Total 22 4,478/6,873 0.91 0.77-1.08 0.279 R 66.78 0.000 68.6% 0.367 0.449

Caucasian 12 2,190/4,366 1.04 0.89-1.21 0.652 F 12.28 0.304 10.4% 0.086 0.108

Asian 8 1,596/1,845 0.76 0.55-1.05 0.095 R 50.48 0.000 86.1% 0.019 0.001

OC 6 915/1,412 0.74 0.55-1.01 0.054 R 13.99 0.016 64.3% 0.452 0.573

Smoking 5 717/548 1.19 0.94-1.52 0.155 F 4.83 0.305 17.2% 0.221 0.219

Publication year 4 1147/1403 1.11 0.93-1.34 0.251 F 5.95 0.114 49.6% 1.000 0.890

PCR-RFLP 18 3566/4659 0.92 0.77-1.09 0.332 R 49.24 0.000 65.5% 0.820 0.176

Taqman 3 801/2069 1.21 0.63-2.35 0.768 R 7.65 0.022 73.9% 0.296 0.221

Arg/Arg vs. Trp/Trp

Total 22 4,478/6,873 0.80 0.50-1.28 0.349 R 33.77 0.013 46.7% 0.944 0.245

Caucasian 12 2,190/4,366 1.04 0.45-2.40 0.920 F 2.95 0.937 0.0% 0.118 0.125

Asian 8 1,596/1,845 0.70 0.37-1.35 0.294 R 27.71 0.000 74.7% 0.035 0.046

OC 6 915/1,412 0.71 0.44-1.13 0.145 F 8.40 0.136 40.4% 1.000 0.715

Smoking 5 717/548 2.53 1.16-5.53 0.020 F 1.38 0.502 0.0% 0.296 0.346

Publication year 4 1147/1403 1.33 0.77-2.28 0.308 F 3.55 0.314 15.5% 0.308 0.908

PCR-RFLP 18 3566/4659 0.90 0.54-1.50 0.684 R 27.70 0.016 49.5% 0.621 0.334

Taqman 3 801/2069 0.59 0.16-2.22 0.439 F 1.55 0.461 0.0% 1.000 0.525

Arg/Arg vs.Arg/Trp+ Trp/Trp

Total 22 4,478/6,873 0.90 0.75-1.08 0.225 R 61.79 0.000 66.0% 0.693 0.450

Caucasian 12 2,190/4,366 1.03 0.88-1.21 0.711 F 13.22 0.279 16.8% 0.086 0.112

Asian 8 1,596/1,845 0.72 0.50-1.06 0.094 R 45.55 0.000 84.6% 0.019 0.003

OC 6 915/1,412 0.70 0.52-0.95 0.022 R 10.66 0.059 53.1% 1.000 0.483

Smoking 6 842/705 1.57 0.68-3.64 0.289 R 44.81 0.000 88.8% 0.452 0.948

Publication year 4 1147/1403 1.13 0.91-1.40 0.283 F 5.53 0.137 45.7% 0.734 0.852

PCR-RFLP 18 3566/4659 0.90 0.75-1.10 0.305 R 44.93 0.000 62.2% 0.940 0.156

Taqman 3 801/2069 1.22 0.63-2.33 0.704 R 6.88 0.032 70.9% 0.296 0.169

Arg280His

Arg280 allele vs. His280 allele

Total 11 2,972/3,714 0.98 0.87-1.10 0.757 F 9.87 0.452 0.0% 0.276 0.153

Caucasian 4 1,102/1,804 1.12 0.86-1.45 0.411 F 0.42 0.937 0.0% 0.734 0.508

Asian 6 1,315/1,394 0.97 0.83-1.13 0.696 F 8.00 0.156 37.5% 0.452 0.550

OC 3 555/1,000 0.86 0.67-1.10 0.241 F 0.59 0.746 0.0% 1.000 0.749

Publication year 3 1001/1247 0.89 0.75-1.07 0.220 F 1.48 0.477 0.0% 0.296 0.097

PCR-RFLP 8 2114/2577 0.99 0.87-1.14 0.922 F 8.48 0.292 17.4% 0.711 0.413

Taqman 2 723/969 0.94 0.73-1.20 0.617 F 1.21 0.272 17.2% 1.000

Arg/Arg vs.His/His

Total 11 2,972/3,714 0.84 0.55-1.29 0.427 F 3.73 0.928 0.0% 0.721 0.638

Caucasian 4 1,102/1,804 1.56 0.38-6.41 0.536 F 1.42 0.492 0.0% 1.000 0.276

Asian 6 1,315/1,394 0.74 0.44-1.24 0.250 F 1.44 0.920 0.0% 0.707 0.826

OC 3 555/1,000 0.65 0.17-2.44 0.521 F 0.11 0.741 0.0% 1.000

Publication year 3 1001/1247 0.78 0.47-1.30 0.342 F 0.36 0.836 0.0% 1.000 0.559

PCR-RFLP 8 2114/2577 0.83 0.50-1.37 0.463 F 3.13 0.792 0.0% 1.000 0.404

Taqman 2 723/969 0.97 0.40-2.32 0.943 F 0.01 0.930 0.0% 1.000

Arg/Arg vs. Arg/His + His/His

Total 11 2,972/3,714 0.99 0.87-1.13 0.872 F 9.95 0.445 0.0% 0.276 0.205

Caucasian 4 1,102/1,804 1.10 0.84-1.44 0.483 F 0.34 0.952 0.0% 0.308 0.258

Asian 6 1,315/1,394 0.99 0.83-1.18 0.913 F 8.26 0.142 39.5% 0.452 0.680

OC 3 555/1,000 0.85 0.65-1.12 0.247 F 0.61 0.736 0.0% 1.000 0.746

Publication year 3 1001/1247 0.88 0.72-1.09 0.252 F 1.38 0.502 0.0% 1.000 0.200

PCR-RFLP 8 2114/2577 1.01 0.86-1.17 0.938 F 8.41 0.298 16.8% 0.536 0.596

Taqman 2 723/969 0.92 0.70-1.21 0.565 F 1.16 0.282 13.7% 1.000

Arg399Gln

Arg399 allele vs. Gln399 allele

Total 27 6,466/9,379 1.01 0.94-1.09 0.850 R 50.97 0.002 49.0% 0.532 0.529

Caucasian 14 2,639/4,768 1.00 0.93-1.08 0.965 F 14.09 0.368 7.7% 0.511 0.324

Asian 9 2,234/2,931 1.01 0.84-1.21 0.931 R 30.42 0.000 73.7% 0.466 0.425

OC 4 663/1,162 0.91 0.59-1.40 0.674 R 22.41 0.000 86.6% 1.000 0.685

Smoking 4 635/454 0.70 0.43-1.15 0.158 R 18.19 0.000 83.5% 0.089 0.042

Publication year 7 1898/2765 1.12 0.96-1.29 0.149 R 14.08 0.029 57.4% 0.764 0.276

PCR-RFLP 21 5029/6051 1.02 0.93-1.11 0.737 R 44.77 0.001 55.3% 0.566 0.558

Taqman 4 1152/2920 0.96 0.85-1.08 0.478 F 3.73 0.292 19.6% 1.000 0.762

Sequence 2 285/408 1.08 0.85-1.39 0.519 F 1.56 0.212 35.8% 1.000

Arg/Arg vs.Gln/Gln

Total 27 6,466/9,379 1.03 0.88-1.20 0.714 R 43.00 0.019 39.5% 0.260 0.330

Caucasian 14 2,639/4,768 1.08 0.92-1.28 0.348 F 16.57 0.219 21.6% 0.324 0.157

Asian 9 2,234/2,931 0.97 0.65-1.44 0.874 R 22.86 0.004 65.0% 0.466 0.478

OC 4 663/1,162 0.91 0.38-2.20 0.838 R 15.87 0.001 81.1% 0.806 0.692

Smoking 4 635/454 0.73 0.33-1.63 0.445 R 7.49 0.058 60.0% 0.089 0.002

Publication year 7 1898/2765 1.28 0.93-1.75 0.129 R 11.32 0.079 47.0% 0.230 0.314

PCR-RFLP 21 5029/6051 1.06 0.87-1.30 0.534 R 39.18 0.006 49.0% 0.156 0.290

Taqman 4 1152/2920 0.95 0.73-1.24 0.709 F 2.58 0.460 0.0% 0.734 0.974

Sequence 2 285/408 0.94 0.50-1.77 0.843 F 0.96 0.328 0.0% 1.000

Arg/Arg vs. Arg/Gln +Gln/Gln

Total 27 6,466/9,379 0.99 0.90-1.09 0.869 R 46.67 0.008 44.3% 0.677 0.721

Caucasian 14 2,639/4,768 0.94 0.85-1.04 0.233 F 14.54 0.337 10.6% 0.381 0.380

Asian 9 2,234/2,931 1.04 0.85-1.28 0.687 R 23.77 0.003 66.3% 0.917 0.472

OC 4 663/1,162 0.88 0.55-1.42 0.612 R 15.80 0.001 81.0% 1.000 0.657

Smoking 7 1,039/746 0.73 0.45-1.19 0.206 R 35.56 0.000 83.1% 0.230 0.038

Publication year 7 1898/2765 1.13 0.94-1.36 0.199 R 12.65 0.049 52.6% 0.764 0.225

PCR-RFLP 21 5029/6051 0.99 0.89-1.12 0.928 R 40.73 0.004 50.9% 0.833 0.795

Taqman 4 1152/2920 0.94 0.81-1.09 0.412 F 2.95 0.400 0.0% 0.734 0.734

Sequence 2 285/408 1.17 0.86-1.59 0.308 F 1.37 0.242 27.1% 1.000

Table 3. Results of meta-analysis for XRCC1 polymorphism and the risk of HNC.

Abbreviations: CI, confidence interval; OR, odds ratio; OC, oral cancer; R: random-effects model; F: fixed-effects model.

CSV

Download CSV

XRCC1 Arg194Trp polymorphism on HNC risk in total population.

A total of 22 studies, including 4,487 cases and 6,873 controls, examining the association between XRCC1 Arg194Trp polymorphism and HNC risk were reviewed. There was significant difference in the frequency of the XRCC1 Arg194Trp polymorphism between Caucasians and Asians (34.42% vs. 12.27%, P<0.001). The pooled ORs for total population showed no evidence of a significant association between the variant genotypes of XRCC1 Arg194Trp and the risk of HNC in any genetic model. Significant heterogeneity was found in all genetic models. The forest plot is shown in Figure 2.

[Figure omitted. See PDF.]

Figure 2. Forest plot of HNC risk associated with XRCC1 Arg194Trp gene polymorphism under all genetic models in total population.

https://doi.org/10.1371/journal.pone.0074059.g002

XRCC1 Arg194Trp polymorphism on HNC risk in a specific population.

Stratified analysis by ethnicity was performed in order to determine the source of heterogeneity among the studies. No significant association of HNC risk with XRCC1 Arg194Trp polymorphism was detected in Asians and Caucasians under any genetic model (Figures S1-S2). Significant differences between-study heterogeneities were found in the Asians, but they were not found in the Caucasians.

Oral cancer (OC) is the most common form of HNC and it is responsible for more than 90% of head and neck cancers [56]. Consequently, we performed a stratified analysis to investigate the relationship between XRCC1 Arg194Trp polymorphism and OC susceptibility. Six studies, including 915 cases and 1,412 controls, evaluating the association between OC risk and XRCC1 variant genotypes were included (Table 1). No significant association between the XRCC1 Arg194Trp polymorphism and risk of OC was found in the allelic genetic model and the homozygote comparison, but a significant association was found for the recessive model (Figure S3). Between-study heterogeneities were detected in the allelic genetic model and the recessive model, but it was not found to be significant in the homozygote comparison.

Many studies have demonstrated that the interaction between XRCC1 polymorphism and environmental toxins could influence the risk of HNC. Considering that smoking is a major aspect of environmental toxins, we performed a subgroup analysis of six studies to investigate the influence that the interaction of tobacco smoke with XRCC1 polymorphism has on HNC risk. There was a significant association between the joint effect of smoking with XRCC1 Arg194Trp polymorphism and the risk of HNC under homozygote comparison (Figure 3). No significant association was observed in the allelic genetic model and the recessive model (Figure 3). Heterogeneity among the studies was not remarkable in any genetic model, except for the recessive model.

[Figure omitted. See PDF.]

Figure 3. Forest plot of HNC risk associated with interaction between XRCC1 Arg194Trp polymorphism and smoking under all genetic models.

https://doi.org/10.1371/journal.pone.0074059.g003

Flores-Obando et al. conducted a similar meta-analysis that included studies published before 2010. Considering the inconsistent results between the two studies, we decided to perform a stratified analysis by including studies published after 2010. The result showed no significant association was detected between Arg194Trp polymorphism and HNC risk in any genetic model (Figure S4). Between-study heterogeneity was not remarkable in this stratified analysis.

The different genotyping methods used in the literature could cause the different genotyping results. Therefore, we performed a subgroup analysis by genotyping methods to investigate the relationship between Arg194Trp and HNC susceptibility. Neither the PCR-RFLP subgroup nor the TaqMan subgroup detected any significant association in the analyses for all genetic models (Figures S5-S6). Moreover, heterogeneity among the studies was observed in the two stratified analyses under all genetic models, except for the homozygote comparison in the TaqMan subgroup.

XRCC1 Arg280His polymorphism on HNC risk in total population.

Eleven studies, including 2,972 cases and 3,714 controls, examining the relationship between XRCC1 Arg280His polymorphism and HNC risk were reviewed. There was significant difference in the frequency of the XRCC1 Arg280His polymorphism between Caucasians and Asians (25.75% vs. 9.04%, P<0.001). There was no significant association of HNC risk with variant genotypes of XRCC1 Arg280His in any genetic model. Significant between-study heterogeneity was absence in all genetic models. The forest plot is shown in Figure 4.

[Figure omitted. See PDF.]

Figure 4. Forest plot of HNC risk associated with XRCC1 Arg280His gene polymorphism under all genetic models in total population.

https://doi.org/10.1371/journal.pone.0074059.g004

XRCC1 Arg280His polymorphism on HNC risk in specific a population.

We conducted subgroup analyses by ethnicity, tumor site, publication year, and genotyping method to estimate the relationship between XRCC1 Arg280His variant genotypes and the risk of NHC. However, no significant association was observed in any subgroup under different genetic models, and there was no significant heterogeneity among the studies in any stratified analysis (Figures S7-S12). Only one study evaluated the influence of the interaction between smoking and Arg280His polymorphism on HNC risk; however, we are unable to conduct a further stratified analysis of that study.

XRCC1 Arg399Gln polymorphism on HNC risk in total population.

There were 27 studies, including 6,466 cases and 9,379 controls, that examined the association between HNC susceptibility and XRCC1 Arg399Gln polymorphism. There was significant difference in the frequency of the XRCC1 Arg399Gln polymorphism between Caucasians and Asians (41.28% vs. 44.65%, P=0.004). Overall, the association between variant genotypes of XRCC1 Arg399Gln polymorphism and HNC susceptibility was not significant under the allelic genetic model, homozygote comparison, and the recessive model. Between-study heterogeneity was detected in all genetic models. The forest plot is shown in Figure 5.

[Figure omitted. See PDF.]

Figure 5. Forest plot of HNC risk associated with XRCC1 Arg399Gln gene polymorphism under all genetic models in total population.

https://doi.org/10.1371/journal.pone.0074059.g005

XRCC1 Arg399Gln polymorphism on HNC risk in a specific population.

In the subgroup analysis by ethnicity, no significant association between XRCC1 Arg399Gln polymorphism and HNC risk was found in Asians (Figure S13) and Caucasians (Figure S14). Heterogeneity among the studies was not remarkable in Caucasians; however, significant heterogeneity was detected in Asians under all genetic models.

Four studies, including 663 cases and 1,162 controls, were performed on OC population, and there was no significant association between XRCC1 Arg399Gln polymorphism and HNC susceptibility (Figure S15). Between-study heterogeneity was found in all genetic models.

In the stratified analysis by smoking in the allelic genetic model and homozygote comparison, four studies were included and no significant association was found (Figure S16). Seven studies were combined in the recessive model. However, we failed to derive a significant association between HNC risk and Arg399Gln genotype (Figure S16). Heterogeneity among the studies was observed in all genetic models.

In stratified analysis by publication year of literature published from 2010–2012, significant heterogeneity was detected in all genetic models. Moreover, we found no association between Arg399Gln and HNC risk under any genetic model (Figure S17).

In subgroup analysis of genotyping method, PCR-RFLP, TaqMan, and sequence analysis were used in the literature for genotyping of XRCC1 Arg399Gln polymorphism. The results showed no significant association between Arg399Gln and HNC risk in any stratified analysis under different genetic models (Figures S18-S20).

Publication bias

Both Begg’s test and Egger’s test were performed to assess the publication bias of the literature. Visual analysis of the funnel plots did not present any evidence of obvious asymmetry for any genetic model in the overall meta-analyses of XRCC1 Arg194Trp, Arg280His, and Arg399Gln (Figures 6-8). However, obvious evidence of publication bias was revealed in the XRCC1 Arg194Trp Asian group under all genetic models. In XRCC1 Arg399Gln smoking stratified analysis, potential publication bias was not revealed in Begg’s test under any genetic model, but it was presented in the Egger’s test. Neither the Begg’s test nor the Egger’s test detected any obvious evidence of publication bias in other stratified analyses for all genetic models (Table 3).

[Figure omitted. See PDF.]

Figure 6. Funnel plot for studies of the association of HNC risk and XRCC1 Arg194Trp gene polymorphism under an allelic genetic model.

https://doi.org/10.1371/journal.pone.0074059.g006

[Figure omitted. See PDF.]

Figure 7. Funnel plot for studies of the association of HNC risk and XRCC1 Arg280His gene polymorphism under an allelic genetic model.

https://doi.org/10.1371/journal.pone.0074059.g007

[Figure omitted. See PDF.]

Figure 8. Funnel plot for studies of the association of HNC risk and XRCC1 Arg399Gln gene polymorphism under an allelic genetic model.

https://doi.org/10.1371/journal.pone.0074059.g008

Discussion

DNA repair mechanisms play a critical role in the protection of cells from DNA damage and in the maintenance of genomic integrity. The protein encoded by the XRCC1 gene is a scaffolding protein that associates with DNA ligase I, DNA ligase III, polynucleotide kinase (PNK), DNA polymerase β, and poly polymerase, which are parts of the DNA repair system. The interaction of XRCC1 with DNA ligase III could increase the endocellular stability of ligase. The joint effects of XRCC1 and PNK stimulate the 5’-kinase and 3’-phospatase activities. All of these conditions promote the repair of DNA. Therefore, sequence variation in the XRCC1 gene is suggested to alter cancer’s susceptibility. The most common variant genotypes of XRCC1, including the Arg194Trp, Arg399Gln, and Arg280His genes, are described and a number of studies have investigated the genetic effect of the XRCC1 Arg194Trp, Arg280His, and Arg399Gln polymorphisms on HNC susceptibility with inconsistent results. This diversity motivates the current updated meta-analysis that may help us to explore a more robust estimate of the effect of XRCC1 polymorphism on the risk of HNC. In the present meta-analysis of 6,719 cases and 9,627 controls, no evidence of a significant association between HNC susceptibility and any type of XRCC1 variant genotype was detected.

A previous meta-analysis, conducted in 2010 by Flores-Obando et al., evaluated the relationship between XRCC1 polymorphisms and the risk of HNC based on 15 publications including 2,330 cases and 3,834 controls for Arg194Trp, four publications including 879 cases and 926 controls for Arg280His, and 15 studies including 3,582 cases and 5,347 controls for Arg399Gln polymorphism. We updated this meta-analysis by adding the sample sizes. A total of 22 studies, including 4,487 cases and 6,873 controls, evaluated the association between the XRCC1 Arg194Trp gene and HNC risk; 11 studies, including 2,972 cases and 3,714 controls, evaluated the association between Arg280His and HNC risk; and 27 studies, including 6,466 cases and 9,379 controls, evaluated the association between Arg399Gln polymorphism and HNC risk. There are some discrepancies between the Flores-Obando et al. meta-analysis and ours. A marginal association between XRCC1 Arg399Gln polymorphism and HNC risk was detected under the recessive genetic model on Caucasians in the meta-analysis conducted by Flores-Obando et al., but it was not found in ours. These diverse results may, generally, be due to the differences in the studies included in the meta-analysis. Nasopharyngeal carcinoma (NPC) is one type of HNC, which has a striking geographic and ethnic distribution, with particularly high rates observed among Asians. The literature on NPC was not included in the Flores-Obando et al. study, but it was included in ours. In the above-mentioned stratified analysis result, seven articles were shared the Flores-Obando et al. study and our study, and our study included an additional seven articles, including newly published literature and NPC literature. The results of these seven studies account for 54.94% weight (Figure 9), which caused the discrepancy between these two meta-analyses. In the assessment of the effect of XRCC1 Arg194Trp variant genotypes on HNC susceptibility, the meta- OR conducted by Flores-Obando et al. found a significant association between the Arg194Trp variant and HNC risk for homozygote comparison in the overall population and in the Asian group, which was not detected in our meta-analysis. Similarly, in our study, an additional nine studies and four studies, comprised of recently published research and NPC studies, included in the overall population group and the Asian group, respectively. The results of these additional studies account for 53.46% and 53.79% weight (Figures 10-11), respectively. In the controls in a study conducted by Demokan et al., genotype distribution in Arg194Trp deviated from HWE, which was excluded in our analysis of Arg194Trp polymorphism; however, it was included in the Flores-Obando et al. article. Furthermore, both our study and the Flores-Obando et al. study included two studies by Majumder et al. Majumder et al.’s most recent publication was included in our study, but Majumder et al.’s research published in 2005 was included in the Flores-Obando et al. meta-analysis. These factors lead to the different conclusion. Many other relationships were not described in the Flores-Obando et al. article. Moreover, we carried out some independent and original subgroup analyses. Subgroup analysis of smoking was not performed in the Flores-Obando’s study, but it was included in this meta-analysis. We also conducted stratified analyses by genotyping methods and publication year, and all the results revealed no association between XRCC1 polymorphism and cancer risk. Therefore, our meta-analysis has stronger evidence to clarify the associations.

[Figure omitted. See PDF.]

Figure 9. Forest plot of HNC risk associated with XRCC1 Arg399Gln gene polymorphism under recessive genetic models on Caucasians.

https://doi.org/10.1371/journal.pone.0074059.g009

[Figure omitted. See PDF.]

Figure 10. Forest plot of HNC risk associated with XRCC1 Arg194Trp gene polymorphism under a homozygote comparison in total population.

https://doi.org/10.1371/journal.pone.0074059.g010

[Figure omitted. See PDF.]

Figure 11. Forest plot of HNC risk associated with XRCC1 Arg194Trp gene polymorphism under a homozygote comparison on Asians.

https://doi.org/10.1371/journal.pone.0074059.g011

The relationship between HNC susceptibility and variant genotypes of XRCC1 might be affected by the tumor sites. Accordingly, we also performed stratified analysis in the oral cancer group. The result of this subgroup analysis showed no evidence for a significant association between XRCC1 polymorphism and the risk of OC in any genetic model, except for the Arg194Trp variant in the recessive model. These results generally agreed with the meta-analysis conducted by Zhou et al. [57], but there were still several differences. Two studies by Sturgis et al. [45] and Matullo et al. [49], which included oral cavity, pharynx, and larynx cancer cases, were not excluded from the Zhou et al. study. The two studies [31,48] were conducted by the same first author and the patient population was obtained from the same hospital; as a result, there is a suspicion that the findings are a duplication of a previous publication. Therefore, only one study met the inclusion criteria to participate in our research.

Recent studies have reported on the associated risk of XRCC1 polymorphism cross lifestyle factors in the progression of head and neck cancer. Cigarette smoking is a major subject of investigation in various cancers. In 1997, the World Health Organization reported that there were 1.1 billion smokers worldwide and smoking-related cancers accounted for 22% of all cancers. Hence, subgroup analysis to estimate the interaction between the genotypes of XRCC1 Arg194Trp and Arg399Gln and smoking on HNC risk was performed. The results showed that the interaction of smoking and Arg399Gln variant genotypes displayed no statistical significance in all three genetic models. A significant association between the joint effect of smoking and XRCC1 Arg194Trp polymorphism and HNC susceptibility was detected under a homozygote comparison (OR= 2.53, 95% CI= 1.16-5.53, P= 0.020), but no statistical significance was revealed in the other genetic models. In the forest plot of HNC risk associated with the interaction between smoking and Arg194Trp, the result of a study by Cao et al. accounted for 71.15% weight (Figure 12), which may mean that XRCC1 Arg194Trp variants are nominally associated with HNC susceptibility in smokers even at a lenient threshold for statistical significance (P= 0.05). Hence, careful consideration is needed for the lack of signals with strong credibility that emerged from this subgroup analysis. The results suggest that XRCC1 Arg194Trp polymorphism may have a small involvement in the pathogenesis of HNC in smokers.

[Figure omitted. See PDF.]

Figure 12. Forest plot of HNC risk associated with interaction between XRCC1 Arg194Trp polymorphism and smoking under a homozygote comparison.

https://doi.org/10.1371/journal.pone.0074059.g012

Between-study heterogeneity is a well-known problem that is unavoidable. In our meta-analysis, heterogeneity was detected in the Arg194Trp and Arg399Gln polymorphism total population groups (Table 3). The source of heterogeneity may arise from many aspects, such as the region of study, the sample size of the case and the control group, and the genotyping method. In order to explain the main reasons for the heterogeneity across studies, stratified analyses by ethnicity and genotyping method were performed. The results showed that in both the Arg194Trp group and the Arg399Gln group, significant heterogeneity was observed in the Asian population subgroup and in the PCR-RFLP analysis subgroup under all different genetic models. This signifies that the source of total population group heterogeneity may come from different races and different genotyping methods.

Publication bias is a well-known problem that was not found by funnel plot for the overall meta-analyses of the XRCC1 polymorphisms (Figures 6-8). However, we found a potential publication bias in the Arg194Trp Asians stratified analysis and the Arg399Gln smoking stratified analysis. The reasons for this could arise from many aspects. For instance, our meta-analysis took into consideration only fully published studies. Positive results tend to be accepted by journals. In addition, language bias may also have existed.

Some limitations should be considered in our meta-analysis. First, some of the included studies in our meta-analysis contained a smaller sample size, which might result in a lack of ability to detect the possible risk for XRCC1 polymorphism. Second, due to the limited number of studies, subgroup analysis was not performed in Africans [12]. Third, this study was based on unadjusted estimates, while a more precise analysis could be performed if individual data were available.

Despite of the limitations mentioned above, the results of the current meta-analysis suggest that XRCC1 Arg194Trp, Arg280His, and Arg399Gln polymorphism is not involved in HNC susceptibility. In addition, further studies evaluating the effect of gene-gene and gene-environment interactions on these gene polymorphisms with HNC susceptibility are required, especially in an African population.

Supporting Information

[Figure omitted. See PDF.]

Figure S1.

Forest plot of HNC risk associated with XRCC1 Arg194Trp gene polymorphism under all genetic models on Asians.

https://doi.org/10.1371/journal.pone.0074059.s001

(DOC)

Figure S2.

Forest plot of HNC risk associated with XRCC1 Arg194Trp gene polymorphism under all genetic models on Caucasians.

https://doi.org/10.1371/journal.pone.0074059.s002

(DOC)

Figure S3.

Forest plot of HNC risk associated with XRCC1 Arg194Trp gene polymorphism under all genetic models in oral cancer population.

https://doi.org/10.1371/journal.pone.0074059.s003

(DOC)

Figure S4.

Forest plot of HNC risk associated with XRCC1 Arg194Trp gene polymorphism under all genetic models in the stratified analysis by studies published after 2010.

https://doi.org/10.1371/journal.pone.0074059.s004

(DOC)

Figure S5.

Forest plot of HNC risk associated with XRCC1 Arg194Trp gene polymorphism under all genetic models in using PCR-RFLP analysis.

https://doi.org/10.1371/journal.pone.0074059.s005

(DOC)

Figure S6.

Forest plot of HNC risk associated with XRCC1 Arg194Trp gene polymorphism under all genetic models in using TaqMan analysis.

https://doi.org/10.1371/journal.pone.0074059.s006

(DOC)

Figure S7.

Forest plot of HNC risk associated with XRCC1 Arg280His gene polymorphism under all genetic models on Asians.

https://doi.org/10.1371/journal.pone.0074059.s007

(DOC)

Figure S8.

Forest plot of HNC risk associated with XRCC1 Arg280His gene polymorphism under all genetic models on Caucasians.

https://doi.org/10.1371/journal.pone.0074059.s008

(DOC)

Figure S9.

Forest plot of HNC risk associated with XRCC1 Arg280His gene polymorphism under all genetic models in oral cancer population.

https://doi.org/10.1371/journal.pone.0074059.s009

(DOC)

Figure S10.

Forest plot of HNC risk associated with XRCC1 Arg280His gene polymorphism under all genetic models in the stratified analysis by studies published after 2010.

https://doi.org/10.1371/journal.pone.0074059.s010

(DOC)

Figure S11.

Forest plot of HNC risk associated with XRCC1 Arg280His gene polymorphism under all genetic models in using PCR-RFLP analysis.

https://doi.org/10.1371/journal.pone.0074059.s011

(DOC)

Figure S12.

Forest plot of HNC risk associated with XRCC1 Arg280His gene polymorphism under all genetic models in using TaqMan analysis.

https://doi.org/10.1371/journal.pone.0074059.s012

(DOC)

Figure S13.

Forest plot of HNC risk associated with XRCC1 Arg399Gln gene polymorphism under all genetic models on Asians.

https://doi.org/10.1371/journal.pone.0074059.s013

(DOC)

Figure S14.

Forest plot of HNC risk associated with XRCC1 Arg399Gln gene polymorphism under all genetic models on Caucasians.

https://doi.org/10.1371/journal.pone.0074059.s014

(DOC)

Figure S15.

Forest plot of HNC risk associated with XRCC1 Arg399Gln gene polymorphism under all genetic models in oral cancer population.

https://doi.org/10.1371/journal.pone.0074059.s015

(DOC)

Figure S16.

Forest plot of HNC risk associated with interaction between XRCC1 Arg399Gln polymorphism and smoking under all genetic models.

https://doi.org/10.1371/journal.pone.0074059.s016

(DOC)

Figure S17.

Forest plot of HNC risk associated with XRCC1 Arg399Gln gene polymorphism under all genetic models in the stratified analysis by studies published after 2010.

https://doi.org/10.1371/journal.pone.0074059.s017

(DOC)

Figure S18.

Forest plot of HNC risk associated with XRCC1 Arg399Gln gene polymorphism under all genetic models in using PCR-RFLP analysis.

https://doi.org/10.1371/journal.pone.0074059.s018

(DOC)

Figure S19.

Forest plot of HNC risk associated with XRCC1 Arg399Gln gene polymorphism under all genetic models in using TaqMan analysis.

https://doi.org/10.1371/journal.pone.0074059.s019

(DOC)

Figure S20.

Forest plot of HNC risk associated with XRCC1 Arg399Gln gene polymorphism under all genetic models in using sequence analysis.

https://doi.org/10.1371/journal.pone.0074059.s020

(DOC)

Supplement S1.

PRISMA Flowchart.

https://doi.org/10.1371/journal.pone.0074059.s021

(DOC)

Supplement S2.

PRISMA Checklist.

https://doi.org/10.1371/journal.pone.0074059.s022

(DOC)

Acknowledgments

Thanks to the Department of Otolaryngology, The second Hospital of Anhui Medical university. Thanks to Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University.

Author Contributions

Conceived and designed the experiments: D-sC YL. Performed the experiments: YL JX H-hL. Analyzed the data: W-jP YL. Wrote the manuscript: YL XJ H-hL W-jP Z-xJ.

Citation: Lou Y, Peng W-j, Cao D-s, Xie J, Li H-h, Jiang Z-x (2013) DNA Repair Gene XRCC1 Polymorphisms and Head and Neck Cancer Risk: An Updated Meta-Analysis Including 16344 Subjects. PLoS ONE 8(9): e74059. https://doi.org/10.1371/journal.pone.0074059

References

1. Marcu LG, Yeoh E (2009) A review of risk factors and genetic alterations in head and neck carcinogenesis and implications for current and future approaches to treatment. J Cancer Res Clin Oncol 135: 1303-1314. doi:https://doi.org/10.1007/s00432-009-0648-7. PubMed: 19641938.

2. Kamangar F, Dores GM, Anderson WF (2006) Patterns of cancer incidence, mortality, and prevalence across five continents: defining priorities to reduce cancer disparities in different geographic regions of the world. J Clin Oncol 24: 2137-2150. doi:https://doi.org/10.1200/JCO.2005.05.2308. PubMed: 16682732.

3. Parkin DM, Pisani P, Ferlay J (1999) Global cancer statistics. CA Cancer J Clin 49: 33-64. doi:https://doi.org/10.3322/canjclin.49.1.33. PubMed: 10200776.

4. Jemal A, Tiwari RC, Murray T, Ghafoor A, Samuels A et al. (2004) Cancer statistics, 2004. CA Cancer J Clin 54: 8-29. doi:https://doi.org/10.3322/canjclin.54.1.8. PubMed: 14974761.

5. Hiyama T, Sato T, Yoshino K, Tsukuma H, Hanai A et al. (1992) Second primary cancer following laryngeal cancer with special reference to smoking habits. Jpn J Cancer Res 83: 334-339. doi:https://doi.org/10.1111/j.1349-7006.1992.tb00111.x. PubMed: 1506266.

6. Geisler SA, Olshan AF (2001) GSTM1, GSTT1, and the risk of squamous cell carcinoma of the head and neck: a mini-HuGE review. Am J Epidemiol 154: 95-105. doi:https://doi.org/10.1093/aje/154.2.95. PubMed: 11447041.

7. Pfeifer GP, Denissenko MF, Olivier M, Tretyakova N, Hecht SS et al. (2002) Tobacco smoke carcinogens, DNA damage and p53 mutations in smoking-associated cancers. Oncogene 21: 7435-7451. doi:https://doi.org/10.1038/sj.onc.1205803. PubMed: 12379884.

8. Zhong Y, Carmella SG, Upadhyaya P, Hochalter JB, Rauch D et al. (2011) Immediate consequences of cigarette smoking: rapid formation of polycyclic aromatic hydrocarbon diol epoxides. Chem Res Toxicol 24: 246-252. doi:https://doi.org/10.1021/tx100345x. PubMed: 21184614.

9. Hoeijmakers JH (2001) Genome maintenance mechanisms for preventing cancer. Nature 411: 366-374. doi:https://doi.org/10.1038/35077232. PubMed: 11357144.

10. Yu HP, Zhang XY, Wang XL, Shi LY, Li YY et al. (2004) DNA repair gene XRCC1 polymorphisms, smoking, and esophageal cancer risk. Cancer Detect Prev 28: 194-199. PubMed: 15225899.

11. Csejtei A, Tibold A, Koltai K, Varga Z, Szanyi I et al. (2009) Association between XRCC1 polymorphisms and head and neck cancer in a Hungarian population. Anticancer Res 29: 4169-4173. PubMed: 19846968.

12. Laantri N, Jalbout M, Khyatti M, Ayoub WB, Dahmoul S et al. (2011) XRCC1 and hOGG1 genes and risk of nasopharyngeal carcinoma in North African countries. Mol Carcinog 50: 732-737. doi:https://doi.org/10.1002/mc.20754. PubMed: 21520294.

13. Ramachandran S, Ramadas K, Hariharan R, Rejnish Kumar R, Radhakrishna Pillai M (2006) Single nucleotide polymorphisms of DNA repair genes XRCC1 and XPD and its molecular mapping in Indian oral cancer. Oral Oncol 42: 350-362. PubMed: 16324877.

14. Olshan AF, Watson MA, Weissler MC, Bell DA (2002) XRCC1 polymorphisms and head and neck cancer. Cancer Lett 178: 181-186. PubMed: 11867203.

15. Kumar A, Pant MC, Singh HS, Khandelwal S (2012) Associated risk of XRCC1 and XPD cross talk and life style factors in progression of head and neck cancer in north Indian population. Mutat Res 729: 24-34. doi:https://doi.org/10.1016/j.mrfmmm.2011.09.001. PubMed: 21945240.

16. Flores-Obando RE, Gollin SM, Ragin CC (2010) Polymorphisms in DNA damage response genes and head and neck cancer risk. Biomarkers 15: 379-399. doi:https://doi.org/10.3109/13547501003797664. PubMed: 20429839.

17. Cochran WG (1954) The combination of estimates from different experiments. Biometrics 10: 101-102. doi:https://doi.org/10.2307/3001666.

18. Higgins JP, Thompson SE (2002) Quantifying heterogeneity in a meta-analysis. Stat Med 21: 1539-1558. doi:https://doi.org/10.1002/sim.1186. PubMed: 12111919.

19. DerSimonian R, Laird N (1986) Meta-analysis in clinical trials. Control Clin Trials 7: 177-188. doi:https://doi.org/10.1016/0197-2456(86)90046-2. PubMed: 3802833.

20. Mantel N, Haenszel W (1959) Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst 22: 719-748. PubMed: 13655060.

21. Begg CB, Mazumdar M (1994) Operating characteristics of a rank correlation test for publication bias. Biometrics 50: 1088-1101. doi:https://doi.org/10.2307/2533446. PubMed: 7786990.

22. Egger M, Davey SG, Schneider M, Minder C (1997) Bias in meta-analysis detected by a simple, graphical test. BMJ 315: 629-634. doi:https://doi.org/10.1136/bmj.315.7109.629. PubMed: 9310563.

23. Gal TJ, Huang WY, Chen C, Hayes RB, Schwartz SM (2005) DNA repair gene polymorphisms and risk of second primary neoplasms and mortality in oral cancer patients. Laryngoscope 115: 2221-2231. doi:https://doi.org/10.1097/01.mlg.0000183736.96004.f7. PubMed: 16369171.

24. Pratesi N, Mangoni M, Mancini I, Paiar F, Simi L et al. (2011) Association between single nucleotide polymorphisms in the XRCC1 and RAD51 genes and clinical radiosensitivity in head and neck cancer. Radiother Oncol 99: 356-361. doi:https://doi.org/10.1016/S0167-8140(11)71051-9. PubMed: 21704413.

25. Yang CH, Chuang LY, Cheng YH, Lin YD, Wang CL et al. (2012) Single nucleotide polymorphism barcoding to evaluate oral cancer risk using odds ratio-based genetic algorithms. Kaohsiung J Med Sci 28: 362-368. doi:https://doi.org/10.1016/j.kjms.2012.02.002. PubMed: 22726897.

26. Khlifi R, Rebai A, Hamza-Chaffai A (2012) Polymorphisms in human DNA repair genes and head and neck squamous cell carcinoma. J Genet 91: 375-384. doi:https://doi.org/10.1007/s12041-012-0193-z. PubMed: 23271025.

27. Mahjabeen I, Baig RM, Masood N, Sabir M, Inayat U et al. (2012) Genetic Variations in XRCC1 Gene in Sporadic Head and Neck Cancer (HNC) Patients. Pathol Oncol Res, 19: 183–8. PubMed: 23055018.

28. Vaezi A, Feldman CH, Niedernhofer LJ (2011) ERCC1 and XRCC1 as biomarkers for lung and head and neck cancer. Pharmgenomics Pers Med 4: 47-63.

29. Ruwali M, Khan AJ, Shah PP, Singh AP, Pant MC et al. (2009) Cytochrome P450 2E1 and head and neck cancer: interaction with genetic and environmental risk factors. Environ Mol Mutagen 50: 473-482. doi:https://doi.org/10.1002/em.20488. PubMed: 19334053.

30. Kumar A, Pant MC, Singh HS, Khandelwal S (2012) Reduced expression of DNA repair genes (XRCC1, XPD, and OGG1) in squamous cell carcinoma of head and neck in North India. Tumour Biol 33: 111-119. doi:https://doi.org/10.1007/s13277-011-0253-7. PubMed: 22081374.

31. Majumder M, Sikdar N, Paul RR, Roy B (2005) Increased risk of oral leukoplakia and cancer among mixed tobacco users carrying XRCC1 variant haplotypes and cancer among smokers carrying two risk genotypes: one on each of two loci, GSTM3 and XRCC1 (Codon 280). Cancer Epidemiol Biomarkers Prev 14: 2106-2112. doi:https://doi.org/10.1158/1055-9965.EPI-05-0108. PubMed: 16172217.

32. Gugatschka M, Dehchamani D, Wascher TC, Friedrich G, Renner W (2011) DNA repair gene ERCC2 polymorphisms and risk of squamous cell carcinoma of the head and neck. Exp Mol Pathol 91: 331-334. doi:https://doi.org/10.1016/j.yexmp.2011.03.004. PubMed: 21419115.

33. Kowalski M, Przybylowska K, Rusin P, Olszewski J, Morawiec-Sztandera A et al. (2009) Genetic polymorphisms in DNA base excision repair gene XRCC1 and the risk of squamous cell carcinoma of the head and neck. J Exp Clin Cancer Res 28: 37. doi:https://doi.org/10.1186/1756-9966-28-37. PubMed: 19284666.

34. Applebaum KM, McClean MD, Nelson HH, Marsit CJ, Christensen BC et al. (2009) Smoking modifies the relationship between XRCC1 haplotypes and HPV16-negative head and neck squamous cell carcinoma. Int J Cancer 124: 2690-2696. doi:https://doi.org/10.1002/ijc.24256. PubMed: 19230024.

35. Kietthubthew S, Sriplung H, Au WW, Ishida T (2006) Polymorphism in DNA repair genes and oral squamous cell carcinoma in Thailand. Int J Hyg Environ Health 209: 21-29. doi:https://doi.org/10.1016/j.ijheh.2005.06.002. PubMed: 16373199.

36. Demokan S, Demir D, Suoglu Y, Kiyak E, Akar U et al. (2005) Polymorphisms of the XRCC1 DNA repair gene in head and neck cancer. Pathol Oncol Res 11: 22-25. doi:https://doi.org/10.1007/BF03032401. PubMed: 15800678.

37. Tae K, Lee HS, Park BJ, Park CW, Kim KR et al. (2004) Association of DNA repair gene XRCC1 polymorphisms with head and neck cancer in Korean population. Int J Cancer 111: 805-808. doi:https://doi.org/10.1002/ijc.20338. PubMed: 15252855.

38. Varzim G, Monteiro E, Silva RA, Fernandes J, Lopes C (2003) CYP1A1 and XRCC1 gene polymorphisms in SCC of the larynx. Eur J Cancer Prev 12: 495-499. doi:https://doi.org/10.1097/00008469-200312000-00008. PubMed: 14639127.

39. Yuan H, Li H, Ma H, Niu Y, Wu Y et al. (2012) Genetic polymorphisms in key DNA repair genes and risk of head and neck cancer in a Chinese population. Exp Ther Med 3: 719-724. PubMed: 22969958.

40. Kostrzewska-Poczekaj M, Gawęcki W, Illmer J, Rydzanicz M, Gajecka M et al. (2013) Polymorphisms of DNA repair genes and risk of squamous cell carcinoma of the head and neck in young adults. Eur Arch Otorhinolaryngol 270: 271-276. doi:https://doi.org/10.1007/s00405-012-1993-8. PubMed: 22427030.

41. Al-Hadyan KS, Al-Harbi NM, Al-Qahtani SS, Alsbeih GA (2012) Involvement of single-nucleotide polymorphisms in predisposition to head and neck cancer in Saudi Arabia. Genet Tests Mol Biomarkers 16: 95-101. doi:https://doi.org/10.1089/gtmb.2011.0126. PubMed: 21877955.

42. Jelonek K, Gdowicz-Klosok A, Pietrowska M, Borkowska M, Korfanty J et al. (2010) Association between single-nucleotide polymorphisms of selected genes involved in the response to DNA damage and risk of colon, head and neck, and breast cancers in a Polish population. J Appl Genet 51: 343-352. doi:https://doi.org/10.1007/BF03208865. PubMed: 20720310.

43. Harth V, Schafer M, Abel J, Maintz L, Neuhaus T et al. (2008) Head and neck squamous-cell cancer and its association with polymorphic enzymes of xenobiotic metabolism and repair. J Toxicol Environ Health A 71: 887-897. doi:https://doi.org/10.1080/15287390801988160. PubMed: 18569591.

44. Li C, Hu Z, Lu J, Liu Z, Wang LE et al. (2007) Genetic polymorphisms in DNA base-excision repair genes ADPRT, XRCC1, and APE1 and the risk of squamous cell carcinoma of the head and neck. Cancer 110: 867-875. doi:https://doi.org/10.1002/cncr.22861. PubMed: 17614107.

45. Sturgis EM, Castillo EJ, Li L, Zheng R, Eicher SA et al. (1999) Polymorphisms of DNA repair gene XRCC1 in squamous cell carcinoma of the head and neck. Carcinogenesis 20: 2125-2129. doi:https://doi.org/10.1093/carcin/20.11.2125. PubMed: 10545415.

46. Dos Reis MB, Losi-Guembarovski R, de Souza Fonseca Ribeiro EM, Cavalli IJ, Morita MC et al. (2013) Allelic variants of XRCC1 and XRCC3 repair genes and susceptibility of oral cancer in Brazilian patients. J Oral Pathol Med 42: 180-185.

47. Yen CY, Liu SY, Chen CH, Tseng HF, Chuang LY et al. (2008) Combinational polymorphisms of four DNA repair genes XRCC1, XRCC2, XRCC3, and XRCC4 and their association with oral cancer in Taiwan. J Oral Pathol Med 37: 271-277. PubMed: 18410587.

48. Majumder M, Sikdar N, Ghosh S, Roy B (2007) Polymorphisms at XPD and XRCC1 DNA repair loci and increased risk of oral leukoplakia and cancer among NAT2 slow acetylators. Int J Cancer 120: 2148-2156. doi:https://doi.org/10.1002/ijc.22547. PubMed: 17290401.

49. Matullo G, Dunning AM, Guarrera S, Baynes C, Polidoro S et al. (2006) DNA repair polymorphisms and cancer risk in non-smokers in a cohort study. Carcinogenesis 27: 997-1007. doi:https://doi.org/10.1093/carcin/bgi280. PubMed: 16308313.

50. Rydzanicz M, Wierzbicka M, Gajecka M, Szyfter W, Szyfter K (2005) The impact of genetic factors on the incidence of multiple primary tumors (MPT) of the head and neck. Cancer Lett 224: 263-278. doi:https://doi.org/10.1016/j.canlet.2005.01.015. PubMed: 15914277.

51. Gajecka M, Rydzanicz M, Jaskula-Sztul R, Wierzbicka M, Szyfter W et al. (2005) Reduced DNA repair capacity in laryngeal cancer subjects. A comparison of phenotypic and genotypic results. Adv Otorhinolaryngol 62: 25-37. PubMed: 15608415.

52. Cao Y, Miao XP, Huang MY, Deng L, Hu LF et al. (2006) Polymorphisms of XRCC1 genes and risk of nasopharyngeal carcinoma in the Cantonese population. BMC Cancer 6: 167. doi:https://doi.org/10.1186/1471-2407-6-167. PubMed: 16796765.

53. Cho EY, Hildesheim A, Chen CJ, Hsu MM, Chen IH et al. (2003) Nasopharyngeal carcinoma and genetic polymorphisms of DNA repair enzymes XRCC1 and hOGG1. Cancer Epidemiol Biomarkers Prev 12: 1100-1104. PubMed: 14578150.

54. Yang ZH, Du B, Wei YS, Zhang JH, Zhou B et al. (2007) Genetic polymorphisms of the DNA repair gene and risk of nasopharyngeal carcinoma. DNA Cell Biol 26: 491-496. PubMed: 17630853.

55. Ho T, Li G, Lu J, Zhao C, Wei Q et al. (2007) X-ray repair cross-complementing group 1 (XRCC1) single-nucleotide polymorphisms and the risk of salivary gland carcinomas. Cancer 110: 318-325. doi:https://doi.org/10.1002/cncr.22794. PubMed: 17559126.

56. Silverman S Jr, Gorsky M (1990) Epidemiologic and demographic update in oral cancer: California and national data--1973 to 1985. J Am Dent Assoc 120: 495-499. PubMed: 2335670.

57. Zhou C, Zhou Y, Li J, Zhang Y, Jiang L et al. (2009) The Arg194Trp polymorphism in the X-ray repair cross-complementing group 1 gene as a potential risk factor of oral cancer: a meta-analysis. Tohoku J Exp Med 219(1):43-51. PubMed: 19713684.