The X-ray repair cross-complementing group 1 (XRCC1) gene is a major DNA repair gene involved in base excision repair (BER) and single-strand break (SSB) repair. XRCC1 interacts strongly with poly[ADP-ribose] polymerase 1 (PARP1), which recognizes SSBs, and LIGIII that seals SSBs and BER intermediates [1]. Several single nucleotide polymorphisms (SNPs) have been identified in the XRCC1 gene [2], and the potential associations with lung cancer risk have been proposed [3–6]. Among them, a polymorphism of rs25487 (Arg399Gln, G > A) is one the most extensively studied SNPs, which leads to amino acid substitutions (exon 10). This mutation could alter XRCC1 function, diminish repair kinetics, and influence susceptibility to cancers. To date, a considerable number of studies have investigated the association between XRCC1 Arg399Gln polymorphism and lung cancer risk [7–54]. However, the results remained conflicting rather than conclusive.

Recently, we have read with great interest the paper titled “X-ray repair cross-complementing group 1 codon 399 polymorphism and lung cancer risk: an updated meta-analysis” published online in Tumor Biology, 2014, 35:411–418 [3]. The authors performed a meta-analysis of 46 studies on the association between XRCC1 codon 399 polymorphism and lung cancer risk published before June 2013. In general population, the authors found that the M (Gln) allele and MM (Gln/Gln) genotype were associated with an increased risk of lung cancer compared with C (Arg) allele and CC (Arg/Arg) genotype, and the odds ratios (ORs) were 1.06 [95 % confidence interval (95 %CI) 1.01–1.12] and 1.19 (95 % CI 1.05–1.34), respectively. When it was stratified according to Asian population, the association between XRCC1 codon 399 polymorphism and lung cancer risk was further strengthened. It is an extremely interesting study.

However, after carefully examining the data provided by Wang et al. (Table 1 in the original text) [3], we found that there are several overlapping data that were not properly excluded from Wang et al.’s study [3]. Firstly, the data from Zhang et al.’s study [55] overlapped with the data reported by Hao et al. [17]. Secondly, the data from Liu et al.’s study [56] overlapped with Zhou et al.’s data [47]. Thirdly, the data reported by Yin et al. in 2009 [57] overlapped with the data reported by Yin et al. in 2007 [44]. Fourthly, Hung et al.’s paper published in 2008 [58] was a pooled analysis study, which included the data from Hung et al.’s paper published in 2005 [20], Zhou et al.’s paper published in 2003 [47], Popanda et al.’s paper published in 2004 [35], and Shen et al.’s paper published in 2005 [39]. Fifthly, the data from two papers reported by Li et al. in 2005 [59, 60] overlapped with Li et al.’s paper published in 2008 [26]. Sixthly, the data from Li et al.’s published in 2005 [61] overlapped with the data reported by Su et al. [41]. As a consequence, 5986 cases and 6495 controls were calculated two times in Wang et al.’s paper [3]. In addition, two eligible papers [7, 23] published before 2013 was not included in Wang et al.’s paper [3]. Therefore, it is required to verify the conclusions by Wang et al. [3]. In order to clarify the association between XRCC1 Arg399Gln polymorphism and lung cancer risk, a meta-analysis including the updated data was reconducted, which may provide comprehensive evidence for this association. We also presented the stratified results by mainly confounding factors such as source of control, ethnicity, smoking status, histological subtypes, and Hardy-Weinberg equilibrium (HWE) in control besides giving overall estimates.

Table 1 Characteristics of selected studies in this meta-analysis
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A comprehensive search was performed through the database of Medline/PubMed, Science Direct, Elsevier, China National Knowledge Infrastructure (CNKI), and Wanfang Medical Online with a combination of the following terms: “lung cancer,” “lung neoplasm” or “lung carcinoma” and “XRCC1” or “rs25487” and “polymorphism” or “variant.” Last search was updated on March 20, 2015. The references cited in the publications and review articles were also manually searched.

Data inclusion criteria were as follows: (a) the papers reporting lung cancer risk and XRCC1 codon 399 polymorphism; (b) case-control studies or cohort studies; and (c) sufficient data to estimate the OR and 95 % CI. For overlapping or repeated studies, the results including more information were included. Accordingly, papers lacking essential information were excluded; review papers were also excluded. In total, 69 published papers were identified with the association between XRCC1 Arg399Gln polymorphism and lung cancer risk. We reviewed all papers in the light of the criteria defined above and excluded 12 reviews and 9 overlapping articles. Therefore, 48 studies were determined to enter our study.

The Cochrane Q statistics test was used to assess the heterogeneity among studies. A fixed-effects model or a random-effects model was applied to estimate the combined effects according to the results of heterogeneity test [62]. A fixed-effects model is used while the effects are assumed to be homogenous; otherwise, a random-effects model is used. The funnel plot was drawn to evaluate publication bias visually. In addition, Begg’s test and Egger’s test were used to assess the publication bias [63, 64]. The χ 2 test was used to check whether the genotype frequencies of the controls were in agreement with HWE.

All of the statistical analyses were conducted by using Review Manager (version 4.2.10, the Cochrane Collaboration) and STATA10.0 software package (Stata Corporation, College Station, TX). Statistical significance was determined as a two-sided P value less than 0.05 for any test or model.

Table 1 lists the characteristics of included studies. Table 2 lists the summary effects of the association between XRCC1 codon 399 polymorphism and lung cancer risk on the basis of 48 published studies including 15,751 cases and 18,688 controls. Overall, we observed a significant association between XRCC1 codon 399 MM genotype variant and lung cancer risk, and the summary OR was 1.19 (95 %CI 1.04–1.37) (Fig. 1); we did not observe any association between XRCC1 codon 399 CM and CM + MM genotype variants and lung cancer risk, and the summary ORs were 0.98 (95 % CI 0.92–1.05) for CM vs. CC (Fig. 2) and 1.02 (95 % CI 0.95–1.10) for CM + MM vs. CC (Fig. 3), respectively. Our results are consistent with Wang et al.’s study [3]. They also found that the MM genotype was associated with increased risk of lung cancer compared with CC genotype in total population. Limiting the analysis to studies of control in agreement with HWE, we did not observe the association between XRCC1 codon 399 polymorphism and lung cancer risk, the summary ORs were 0.99 (95 % CI 0.92–1.07) for CM vs. CC, 1.12 (95 % CI 0.98–1.29) for MM vs. CC, and 1.02 (95 % CI 0.94–1.10) for CM + MM vs. CC, respectively (Table 2). In subgroup analysis by ethnicity, we observed an increased lung cancer risk among subjects carrying XRCC1 codon 399 MM genotype compared with CC genotype carriers (OR = 1.43, 95 % CI 1.16–1.76) among Asians, which is consistent with Wang et al.’s results [3]. We did not observe the association of XRCC1 codon 399 polymorphism with lung cancer risk among Caucasians (Table 2), which is consistent with Wang et al.’s results [3]. When stratified by source of control, we observed an increased lung cancer risk among subjects carrying MM genotype compared with those carrying CC genotype on the basis of hospital-based control (OR = 1.37, 95 % CI 1.11–1.70); we did not observe the association of XRCC1 codon 399 polymorphism with lung cancer risk on the basis of population-based control (Table 2). We did not observe the association between XRCC1 codon 399 polymorphism and lung cancer risk in additional subgroup analyses by smoking status and histological subtypes (Table 2).

Table 2 Summery odds ratios of the relation of XRCC1 codon 399 polymorphism to lung cancer risk
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Fig. 1
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Forest plots for the association between XRCC1 codon 399 MM genotype variant and lung cancer risk

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Fig. 2
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Forest plots for the association between XRCC1 codon 399 CM genotype variant and lung cancer risk

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Fig. 3
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Forest plots for the association between XRCC1 codon 399 CM + MM genotype variant and lung cancer risk

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The shape of funnel plots did not reveal any evidence of obvious asymmetry (Figs. 4, 5, and 6) among total studies, which suggested that there was not any potential publication bias. Begg’s test and Egger’s test suggested that there was no obvious publication bias in this study, except for the analysis under the genetic model of CM vs. MM among Caucasians, since the P value was less than 0.05 in Egger’s test (Table 2).

Fig. 4
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Funnel plots for the association between XRCC1 codon 399 MM genotype variant and lung cancer risk

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Fig. 5
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Funnel plots for the association between XRCC1 codon 399 CM genotype variant and lung cancer risk

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Fig. 6
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Funnel plots for the association between XRCC1 codon 399 CM + MM genotype variant and lung cancer risk

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In summary, our results suggest that XRCC1 codon 399 MM genotype variant was associated with an increased lung cancer risk, especially among Asians. To reach a definitive conclusion, further well-designed studies with large sample size are needed to verify the association of XRCC1 codon 399 polymorphism and lung cancer risk. We hope that this remark will contribute to a more accurate elaboration and substantiation of the results presented by Wang et al. [3].