Literature DB >> 24853559

PARP-1 Val762Ala polymorphism and risk of cancer: a meta-analysis based on 39 case-control studies.

Qin Qin1, Jing Lu1, Hongcheng Zhu1, Liping Xu1, Hongyan Cheng1, Liangliang Zhan1, Xi Yang1, Chi Zhang1, Xinchen Sun1.   

Abstract

BACKGROUND: Poly(ADP-ribose) polymerase-1 (PARP-1) is a nuclear chromatin-associated enzyme involved in several important cellular processes, particularly in the DNA repair system. PARP-1 rs1136410: C>T is among the most studied polymorphisms and likely involved in human carcinogenesis. However, results from previous studies are inconclusive. Thus, a meta-analysis was conducted to derive a more precise estimation of the effects of this enzyme. METHODOLOGY AND PRINCIPAL
FINDINGS: A comprehensive search was conducted in the PubMed and EMBASE databases until December 9, 2013. A total of 39 studies with 16,783 cancer cases and 23,063 control subjects were included in the meta-analysis on the basis of the inclusion and exclusion criteria. No significant association between the PARP-1 Val762Ala polymorphism and cancer risk was found when all of the studies were pooled into the analysis (VA + AA vs. VV: OR = 1.03, 95% CI = 0.95-1.11). The subgroup analysis of cancer types revealed that the -762Ala allele was associated with increased risk of gastric, cervical, and lung cancers and a decreased risk of glioma. In addition, a significantly increased risk of cancer associated with the polymorphism was observed in Asian descendents (VA + AA vs. VV: OR = 1.17, 95% CI = 1.09-1.25; AA vs. VV: OR = 1.28, 95% CI = 1.08-1.51; VA vs. VV: OR = 1.12, 95% CI = 1.04-1.20; AA vs. VA + VV: OR = 1.09, 95% CI = 1.03-1.39). These results also indicated that a joint effect between PARP-1 Val762Ala and XRCC1 Arg399Gln could be involved in the risk of cancer development (OR = 3.53, 95% CI = 1.30-9.59).
CONCLUSION: The present meta-analysis provides evidence that the PARP-1 Val762Ala may be involved in cancer development at least in some ethnic groups (Asian) or some specific cancer types (gastric, cervical, and lung cancers, and glioma).

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Year:  2014        PMID: 24853559      PMCID: PMC4031170          DOI: 10.1371/journal.pone.0098022

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

The etiology and development of cancer are a result of complex interactions between genetic and environmental factors. Physical and chemical agents originated from either endogenous processes, such as cellular metabolism, or exogenous exposure, including ionizing radiation, tobacco smoke, and genotoxic chemicals, are responsible for oxidative cell DNA damage; when left unrepaired or incorrectly repaired, cell DNA damage may lead to mutations and genomic instability [1]. Base excision repair (BER) system repairs base damage and single-strand breaks caused by X-rays, oxygen radicals, and alkylating reagents. However, inherited defects in DNA repair pathways result in the accumulation of DNA damage, cell apoptosis, or unregulated cell growth and development of malignancy [2]–[4]. Poly(ADP-ribose) polymerase-1 (PARP-1), also called adenosine diphosphate ribosyl transferase, is one of the most important components of the BER system. PARP1 is a nuclear nick sensor enzyme that becomes activated in response to DNA breakage [5]. In general, PARP1 binds to the sites of DNA damage via the N-terminal DNA-binding domain and catalyzes the addition of poly(ADP-ribose) polymers from NAD+ to nuclear acceptor proteins, including histones, P53, and PARP-1 itself, thereby causing chrome relaxation and recruitment of other repair proteins (e.g., XRCC1, DNA-PK) into the damaged site [6], [7]. Therefore, PARP-1 is essential for the surveillance and maintenance of genome integrity and interaction with various proteins involved in multiple DNA repair pathways, including BER, SSBR (Single-strand break repair), and DSBR (DNA double-strand break repair). Moreover, PARP-1 is implicated in other molecular and cellular processes, such as gene transcription modulation, apoptosis decision, telomere maintenance, and chromatin remodeling [8], [9]. Evidence has suggested that the deficiency of PARP-1 results in DNA repair defects, genomic instability, failure of induction of cell death, and modulation of gene transcription, thereby contributing to carcinogenesis [10]–[12]. The human PARP1 gene, located on chromosome 1q41–42, is approximately 47.3 kb in length and consists of 23 exons. Numerous single nucleotide polymorphisms (SNPs), including 17 non-synonymous SNPs, have been identified in PARP-1; among these SNPs, rs1136410 at codon 762 in exon 17, a non-synonymous T→C polymorphism changing valine to alanine, is the most extensively investigated. This polymorphism is located in the sixth helix of the COOH-terminal NAD-binding region with all of the catalytic activities of the full-length enzyme. This amino acid change contributes to low poly(ADP-ribosyl)ation activities in a dosage-dependent manner, thereby impairing DNA repair and enhancing the susceptibility of variant allele carriers to damage caused by environmental carcinogens and cancer risk [5], [13]. Thus far, molecular epidemiological studies have indicated the genetic association of Val762Ala with the risk of many cancer types, including cancers of the breast, stomach, lung, cervix, brain, and colorectum, as well as other types of malignancies [14]–[19]. However, these studies have not yet produced consistent results. The discrepancies of the findings are partially attributed to the limited power of individual studies with small sample sizes and differences in the baseline characteristics of included patients. Although the PARP-1 Val762Ala polymorphism and susceptibility to cancers have been discussed [20], [21], all of the eligible studies have not been included, particularly case-control studies published in the past two years. Therefore, these meta-studies are disputed because of the limited number of included studies and relatively small sample size. The present meta-analysis aimed to update previous meta-analyses and derive a reliable conclusion regarding the effect of the V762A polymorphism on the function of PARP-1 in cancer. This meta-analysis also aimed to quantify the potential of heterogeneity between studies.

Materials and Methods

Literature search

Relevant publications were identified by conducting a literature search in PubMed and EMBASE databases using the following search terms: PARP-1 or ADPR, variant or polymorphism or SNP, and cancer or carcinoma or tumor. The last search was updated on December 9, 2013. The references of the identified studies and reviews were also screened to find additional eligible studies. If studies with overlapped subjects were reported, only the one with the most complete data was included in the meta-analysis. Search results were limited to studies published in English.

Inclusion and exclusion criteria

Studies were included in our meta-analysis if the following criteria were satisfied: (1) studies were designed as cohort or case-control; (2) studies investigated the association between PARP-1 Val762Ala polymorphism and cancer susceptibility; and (3) sufficient genotype data were provided to estimate the odds ratio (OR) and a corresponding 95% confidence interval (CI). Studies were excluded if the following criteria were satisfied: (1) case-only, case reports, or reviews; (2) duplicate of previous publications; (3) family-based studies; and (4) based on insufficient data for calculation.

Data extraction

Two investigators dependently reviewed the publications and obtained information according to a standard data form. The following data were extracted from each study: name of first author; year of publication; country or region of origin; ethnicity of the study population; cancer type; number of cases and controls; allele and genotype frequency; evidence of Hardy-Weinberg equilibrium (HWE) in controls; source of controls; and genotyping method. Disagreements between the two investigators were resolved by discussing the results with a third investigator.

Statistical analysis

The strength of the association between the PARP-1 Val762Ala polymorphism and the risk of cancer was measured by OR with 95% CI in five genetic models, including dominant model (VA + AA vs. VV), recessive model (AA vs. VA + VV), homozygous model (AA vs. VV), heterozygous model (VA vs. VV), and allele model (A vs. V). The significance of the pooled OR was determined by a Z-test, and P<0.05 was considered statistically significant. A statistical test to determine heterogeneity between studies was performed using Q-test and I test. In the Q-test, P>0.10 indicates the absence of heterogeneity. The pooled OR estimates of each study were calculated using the fixed-effect model, the Mantel-Haenszel method. Otherwise, a random-effect model, the Dersimonain and Laird method, was applied. The I test was used to quantify the effect of heterogeneity (ranges from 0% to 100%); The test represents the proportion of inter-study variability that can be attributed to heterogeneity rather than by chance. Subgroup analyses were also performed to evaluate the potential effects of ethnicity, cancer types, source of controls, and genotyping method. Sensitivity analysis was conducted by omitting each study to identify the effect of an individual study on the pooled OR. Publication bias was qualitatively detected using Begger's funnel plots, and Egger's linear regression test was performed to determine funnel plot asymmetry (P<0.05 was considered as statistically significant publication bias). All of the P values were two-tailed. Statistical analyses were performed using STATA version 11.0 (Stata Corporation, College Station, TX, USA).

Results

Characteristics of eligible studies

A total of 84 articles relevant to search keywords were identified after our literature search from PubMed and EMBASE was completed. According to the inclusion criteria, 45 studies were excluded. Among these studies, two were excluded because of a lack of genotyping data [22], [23]. The flow chart of the detailed steps of study selection is shown in Figure 1. A total of 39 case-control studies with 16,783 cancer cases and 23,063 control subjects were included in our meta-analysis. The main characteristics of the eligible studies are listed in Table 1. A total of 21 studies involved Caucasian populations and 18 focused on Asian populations. Among these studies, three focused on colorectal, lung, cervical, and bladder cancer, individually; and four described gastric, glioma, and breast cancer, individually. The distribution of the genotypes in the control subjects was in agreement with HWE except three studies [15], [24], [25].
Figure 1

Flow chart of literature search and study selection.

Table 1

Characteristics of eligible studies included in the meta-analysis.

NameYearCountryEthnicityCancer typeSample sizeSourceControls in HWEGenotyping method
cases/controls
Hosono [33] 2013JapanAsianEndometrial91261HBYesTaqMan
Li [18] 2013ChinaAsianColorectal451626MixedYesPCR-RFLP
Roszak [17] 2013PolandCaucasianCervical446491PBYesPCR-HRM
Xue [34] 2013ChinaAsianLung410410HBYesPCR-RFLP
Nakao [24] 2012JapanAsianPancreas1851465HBNoTaqMan
Pan [25] 2012ChinaAsianGastric176308MixedNoMassARRAY
Santonocito [19] 2012ItalyCaucasianMelanoma16799NMYesPCR-HRM
Santos [35] 2012PotugalCaucasianThyroid108216HBYesTaqMan
Wen [32] 2012ChinaAsianGastric307307MixedYesMassARRAY
Ye [36] 2012ChinaAsianCervical539800HBYesMA-PCR
Yuan [37] 2012ChinaAsianHead and neck395883PBYesTaqMan
Zhang [38] 2012ChinaAsianCervical80176HBYesSNPware 12plex assay
Yosunkaya [39] 2010TurkeyCaucasianGlioma119180PBYesPCR-RFLP
Gao [40] 2010USCaucasianProstate453119HBYesSequence
Jin [41] 2010KoreaAsianNHL573721PBYesPCR-HRM
Rajaraman [42] 2010USCaucasianGlioma340463HBYesTaqMan
Rajaraman2010USCaucasianMeningioma121463HBYesTaqMan
Rajaraman2010USCaucasianAcoustic neuroma65463HBYesTaqMan
Wang [43] 2010ChinaAsianBladder234253HBYesPCR-RFLP
Liu [44] 2009USCaucasianGlioma372365PBYesMassARRAY
McKean [45] 2009USCaucasianGlioblastoma9871935MixedYesMassARRAY
Zhang [46] 2009ChinaAsianGastric236320HBYesPCR-RFLP
Chiang[47] 2008ChinaAsianThyroid283469HBYesTaqMan
Smith[14] 2008USCaucasianBreast314397HBYesMassARRAY
Berndt[48] 2007USCaucasianColorectal649659NMYesTaqMan
Cao[49] 2007FranceCaucasianBreast83100HBYesSequence
Figueroa[50] 2007SpainCaucasianBladder11381131HBYesTaqMan
Li[51] 2007USCaucasianHead and neck830854HBYesPCR-RFLP
Stern[52] 2007SingaporeAsianColorectal3071173PBYesTaqMan
Landi[53] 2006Multiple regionsCaucasianLung292307HBYesAPEX
Li[54] 2006USCaucasianMelanoma602603HBYesPCR-RFLP
Miao[15] 2006ChinaAsianGastric5001000PBNoPCR-RFLP
Shen[55] 2006USCaucasianNHL455535PBYesTaqMan
Wu[56] 2006USCaucasianBladder606595HBYesTaqMan
Zhai[57] 2006ChinaAsianBreast302639HBYesPCR-RFLP
Zhang[58] 2006USCaucasianBreast17151371PBYesTaqMan
Zhang[16] 2005ChinaAsianLung10001000HBYesPCR-RFLP
Hao[59] 2004ChinaAsianEsophageal414479HBYesPCR-RFLP
Lockett[5] 2004USCaucasianProstate438427HBYesMassARRAY

PB: population-based; HB: hospital-based; HWE: Hardy-Winberg equilibrium. Genotyping method: PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; MassARRAY: genotyping was performed using the Sequenom MassARRAY iPLEXTM platform2. MassARRAY Workstation version 3.3 software was used to process and analyze iPLEX SpectroCHIP bioarrays; PCR-HRM, PCR cycling and high resolution melting analysis was performed on the Rotor-Gene 6000TM. APEX: polymorphism was analyzed together for a given sample by a microarray technique based on the arrayed primer extension principle.

PB: population-based; HB: hospital-based; HWE: Hardy-Winberg equilibrium. Genotyping method: PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; MassARRAY: genotyping was performed using the Sequenom MassARRAY iPLEXTM platform2. MassARRAY Workstation version 3.3 software was used to process and analyze iPLEX SpectroCHIP bioarrays; PCR-HRM, PCR cycling and high resolution melting analysis was performed on the Rotor-Gene 6000TM. APEX: polymorphism was analyzed together for a given sample by a microarray technique based on the arrayed primer extension principle.

Quantitative synthesis

The meta-analysis findings of the correlation between PARP-1 V762A and cancer risk are summarized in Table 2. After the 39 studies were pooled into meta-analysis, no evidence of a significant association between V762A polymorphism and cancer risk was observed (dominant model: OR = 1.03, 95% CI = 0.95–1.11; recessive model: OR = 1.10, 95% CI = 0.97–1.26; homozygous model: OR = 1.13, 95% CI = 0.98–1.31; heterozygous model: OR = 1.02, 95% CI = 0.95–1.10; allele model: OR = 1.04, 95% CI = 0.97–1.11; Table 2; Figure 2). We excluded three studies with genotypic distribution in control subjects that deviated from HWE and found that the results did not significantly alter from the corresponding pooled OR (Table 2).
Table 2

Meta-analysis of the association between PARP-1 Val762Ala polymorphism and cancer risk.

No. of subjects cases/controlsnVA+AA vs. VVAA vs. VA+VVAA vs. VVVA vs. VVA vs. V
OR (95% CI) Phet OR (95% CI) Phet OR (95% CI) Phet OR (95% CI) Phet OR (95% CI) Phet
Total 16783/23063391.03 (0.95–1.11)0.0001.10 (0.97–1.26)0.0001.13 (0.98–1.31)0.0001.02 (0.95–1.10)0.0011.04 (0.97–1.11)0.000
Controls in HWE 15922/20290361.01 (0.94–1.09)0.0001.09 (0.95–1.29)0.0001.11 (0.96–1.28)0.0001.00 (0.94–1.08)0.0011.03 (0.96–1.10)0.000
Ethnicities
Caucasian10300/11773210.93 (0.83–1.03)0.0000.95 (0.76–1.18)0.0790.92 (0.78–1.08)0.1110.94 (0.84–1.04)0.0000.96 (0.87–1.05)0.000
Asian6483/11290181.17 (1.09–1.25)* 0.2491.09 (1.03–1.39)* 0.0001.28 (1.08–1.51)* 0.0001.12 (1.04–1.20)* 0.8051.12 (1.05–1.21)* 0.001
Cancer type
Colorectal1407/245831.08 (0.93–1.25)0.1221.14 (0.79–1.67)0.0641.18 (0.76–1.85)0.0391.05 (0.90–1.23)0.4191.08 (0.88–1.31)0.032
Cervical1065/146731.26 (1.06–1.50)* 0.4441.59 (0.82–3.07)0.0111.68 (0.91–3.10)0.0361.14 (0.95–1.36)0.2521.31 (1.16–1.48)* 0.201
Lung1702/171731.16 (1.00–1.33)* 0.2341.32 (1.09–1.61)* 0.4871.42 (1.14–1.76)* 0.3261.10 (0.95–1.28)0.4471.16 (1.05–1.28)* 0.182
Gastric1219/193541.33 (1.14–1.55)* 0.2221.22 (0.77–1.94)0.0011.38 (0.84–2.26)0.0021.28 (1.09–1.51)* 0.7421.19 (0.95–1.48)0.006
Glioma1818/294340.78 (0.69–0.89)* 0.9071.06 (0.46–2.42)0.0130.92 (0.48–1.78)0.0710.79 (0.68–0.91)* 0.3020.84 (0.75–0.95)* 0.414
Bladder1978/197931.09 (0.86–1.39)0.0830.96 (0.69–1.33)0.8180.99 (0.70–1.40)0.8501.10 (0.84–1.44)0.0571.08 (0.96–1.22)0.159
Breast2414/250740.94 (0.83–1.07)0.2030.92 (0.71–1.19)0.8520.89 (0.68–1.17)0.8380.95 (0.84–1.08)0.1760.95 (0.86–1.05)0.317
Other4489/6391111.02 (0.88–1.19)0.0050.98 (0.78–1.22)0.0750.99 (0.76–1.30)0.0241.01 (0.89–1.15)0.0481.02 (0.90–1.16)0.001
Source of controls
PB4882/671991.02 (0.87–1.19)0.0011.17 (0.90–1.51)0.0031.18 (0.88–1.59)0.0011.03 (0.89–1.20)0.0131.07 (0.94–1.22)0.000
HB9164/12410241.03 (0.93–1.13)0.0021.12 (0.94–1.33)0.0011.15 (0.95–1.39)0.0011.01 (0.93–1.10)0.041.03 (0.95–1.12)0.000
Mixed1921/317641.03 (0.79–1.34)0.010.98 (0.67–1.42)0.0191.03 (0.69–1.55)0.021.03 (0.80–1.33)0.0280.99 (0.80–1.23)0.002
Genotyping method
PCR-RFLP5098/6364111.09 (0.93–1.27)0.0001.29 (1.07–1.55)* 0.0081.34 (1.07–1.67)* 0.0021.03 (0.90–1.19)0.0041.10 (0.98–1.24)0.000
TaqMan6458/10147141.02 (0.92–1.12)0.0550.97 (0.85–1.12)0.8661.0 (0.86–1.16)0.6281.04 (0.96–1.12)0.1181.00 (0.93–1.09)0.061
MassARRAY2594/373960.89 (0.75–1.07)0.0510.90 (0.71–1.13)0.1340.93 (0.73–1.20)0.1330.94 (0.76–1.15)0.0630.93 (0.79–1.10)0.039
Other2261/233061.16 (0.89–1.50)0.0051.42 (0.73–2.74)0.0001.44 (0.73–2.85)0.0001.10 (0.87–1.40)0.0311.18 (0.92–1.52)0.000

Phet: P-value of Q-test for heterogeneity test. The fixed-effects model was used when P-value for heterogeneity test >0.10; otherwise, the random-effects model was used.

*indicate significant difference.

Figure 2

Forest plot for pooled OR of association between the PARP-1 Val762Ala polymorphism and overall cancer risk under dominant model (VA+AA vs. VV).

Phet: P-value of Q-test for heterogeneity test. The fixed-effects model was used when P-value for heterogeneity test >0.10; otherwise, the random-effects model was used. *indicate significant difference. Significant heterogeneity was observed among the overall 39 studies of the PARP-1 V762A polymorphism (e.g., dominant model: Q = 98.58 on 38 d.f., P = 0.000, I = 61.5%). To explore the source of heterogeneity, we performed stratified analyses on ethnicity, cancer type, source of controls, and genotyping method. In the subgroup analysis of ethnicity, PARP-1 V762A was significantly associated with an increased risk of cancer in Asian populations in all of the genetic models (e.g., dominant model: OR = 1.17, 95% CI = 1.09–1.25; Table 2; Figure 3). However, no significant association was found in Caucasian populations in any models (e.g., dominant model: OR = 0.93, 95% CI = 0.83–1.03; Table 2; Figure 3). The studies were further stratified on the basis of cancer type and the results showed that PARP-1 V762A polymorphism may be a risk factor of lung cancer in all of the genetic models except the heterozygous model (dominant model: OR = 1.16, 95% CI = 1.00–1.33; recessive model: OR = 1.32, 95% CI = 1.09–1.61; homozygous model  =  OR = 1.42, 95% CI: 1.14–1.76; heterozygous model  =  OR = 1.10, 95% CI = 0.95–1.28; allele model: dominant model: OR = 1.16, 95% CI = 1.05–1.28; Table 2; Figure 4). We also found significant correlation between the Ala carrier of PARP-1 V762A polymorphism and increased risk of cervical cancer (dominant model: OR = 1.26, 95% CI = 1.06–1.50; allele model: OR = 1.31, 95% CI = 1.16–1.48) and gastric cancer (dominant model: OR = 1.33, 95% CI = 1.14–1.55; heterozygous model: OR = 1.28, 95% CI = 1.09–1.51). By contrast, the PARP-1 V762A polymorphism was significantly associated with a decreased risk of glioma in three genetic models (Table 2; Figure 4). However, studies on colorectal, bladder, breast, and other cancer types have suggested null association (OR = 0.92–1.18; Table 2; Figure 4). Furthermore, V762A polymorphism was significantly associated with increased cancer risk in the subgroup of PCR-RFLP genotyping method (recessive model: OR = 1.29, 95% CI = 1.07–1.55; homozygous model: OR = 1.34, 95% CI = 1.07–1.67; Table 2). No significant associations were detected when the studies were stratified on the basis of the source of control subjects (Table 2).
Figure 3

Subgroup analysis by ethnicity of ORs for cancer risk associated with the PARP-1 Val762Ala polymorphism under dominant model (VA+AA vs. VV).

Figure 4

Subgroup analysis by cancer type of ORs for cancer risk associated with the PARP-1 Val762Ala polymorphism under dominant model (VA+AA vs. VV).

Considering that PARP-1 functionally interacts with XRCC1 in BER processes, we performed a gene-gene interaction analysis of the five studies that reported joint effects between PARP1 Val762Ala and XRCC1 Arg399Gln on cancer risks. In Table 3, a significant interaction between the pairwise-coding SNPs in XRCC1-PARP1 was found because subjects with the PARP1 Ala/Ala and XRCC1 Gln/Gln genotypes exhibited a higher risk of cancer compared with subjects carrying the PARP1 Val/Val and XRCC1 Arg/Arg genotypes (pooled OR = 3.53, 95% CI = 1.30–9.59).
Table 3

Pooled analysis of the interaction effects between PARP1 Val762Ala and XRCC1 Arg399Gln on overall cancer risk.

XRCC1 Arg399GlnPARP1 Val762AlaNo. of subjects cases/controlsOR (95% CI)PPhet
Arg/Arg Val/Val 282/5361
Either variant genotype 1142/16681.32 (0.94–1.87)0.1110.016
Both heterozygous genotype 875/10971.62 (0.96–2.71)0.0680.000
Gln/Gln Ala/Ala 67/523.53 (1.30–9.59)* 0.0140.067

Either variant genotype: an individual with any variant homozygote or heterozygote at one site and wild-type homozygote at the other site.

Both heterozygous genotype: an individual with heterozygote at both sites.

*indicate significant difference.

Either variant genotype: an individual with any variant homozygote or heterozygote at one site and wild-type homozygote at the other site. Both heterozygous genotype: an individual with heterozygote at both sites. *indicate significant difference.

Sensitivity analysis

Sensitivity analysis was conducted to verify the effect of each study on the overall OR by repeating the meta-analysis, but any single study was omitted at each time. In Figure 5, no individual study affected the pooled OR qualitatively, indicating that the pooled results were statistically robust.
Figure 5

Sensitivity analysis of overall OR coefficients for dominant model (VA+AA vs. VV).

The analysis was conducted by omitting each study in turn. Meta-analysis random-effects estimates were used. The two ends of the dotted lines represent the 95%CI.

Sensitivity analysis of overall OR coefficients for dominant model (VA+AA vs. VV).

The analysis was conducted by omitting each study in turn. Meta-analysis random-effects estimates were used. The two ends of the dotted lines represent the 95%CI.

Publication bias

Begger's funnel plot and Egger's test were performed to evaluate the publication bias of the studies. The shape of the funnel plots showed that the dots were nearly symmetrically distributed predominantly in pseudo 95% confidence limits (dominant model, Figure 6). The results of Egger's test statistically confirmed the absence of publication bias in the dominant model (t = −0.11, P = 0.916).
Figure 6

Begger's funnel plot of publication bias for PARP-1 Val762Ala polymorphism with cancer risk under dominant model (VA+AA vs. VV).

Each dot represents a separate study for the indicated association. Funnel plot of all 39 eligible studies P = 0.753, Egger's test P = 0.916.

Begger's funnel plot of publication bias for PARP-1 Val762Ala polymorphism with cancer risk under dominant model (VA+AA vs. VV).

Each dot represents a separate study for the indicated association. Funnel plot of all 39 eligible studies P = 0.753, Egger's test P = 0.916.

Discussion

PARP-1, the first discovered member of the PARP family, is involved in various important molecular and cellular processes, including cellular stress response, cell cycle control, telomere maintenance, chromatin remodeling, and mitotic apparatus functions. This nuclear DNA binding protein also functions in DNA single-strand break repair. This protein specifically detects DNA strand breaks generated by different genotoxic agents, facilitates the formation of DNA repair complexes, such as BRCA1 or BRCA2, and activates regulatory enzymes, namely, ATM and ATR, involved in the cell cycle [26]. Gene polymorphisms may also influence the rate of gene transcription, the stability of mRNA, or the quantity and activity of the resulting protein [27]. Thus, variations in PARP-1 gene may affect DNA repair in normal populations and facilitate cancer development in normal or exposed individuals. Thus far, approximately 1,066 single-nucleotide polymorphisms in the PARP-1 gene have been reported; among these polymorphisms, a T to C nucleotide transition results in Val762Ala substitution located in the C-terminal catalytic site and characterizes a commonly occurring PARP-1 polymorphism; this alteration is frequently investigated because of its association with cancer risk [28]. Several in vitro experiments have characterized the functional effect of this polymorphism on PARP1. For instance, Wang et al. [29] found that PARP-Ala762 displays approximately half of the activity of PARP-Val762 for both auto-poly(ADP-ribosyl)ation and trans-poly(ADP-ribosyl)ation of histone H1. Lockett et al. [5] also suggested that the PARP-1 Val762Ala polymorphism reduces the enzymatic activity of PARP1 in response to oxidative damage. Molecular epidemic studies have also been conducted to investigate the functional relevance of this variant with susceptibility to cancer. However, results remain inconsistent. A total of 39 studies with 16,783 cancer cases and 23,063 controls were considered in the present meta-analysis. The results indicated no significant association of PARP-1 Val762Ala polymorphism with overall cancer risk. In the stratified analysis by ethnicity, the variant –762Ala allele was significantly associated with an increased cancer risk among Asian populations. By contrast, no significant correlation was detected among Caucasians. The discrepancy in ethnicity could be attributed to the evident difference in the minor allele frequency (MAF) of Val762Ala polymorphism in Asians and Caucasians in our meta-analysis (41.6% and 16.2%, respectively). This genetic polymorphism variance with ethnicity was consistent with those described in a previous study [30]. Significant risks were also found in subgroup analysis based on cancer types. Subjects with the variant Ala allele were more susceptible to cancers of the cervix, lung, and stomach, whereas the polymorphism was a potential protective factor against glioma in dominant, heterozygous, and allele models. PARP-1 variant genotypes may possibly be tissue specific because of high or low PARP-1 expression levels in different tumor tissues [12], [31]. Moreover, this result could be interpreted partially on the basis of the different functions of PARP-1 in different tumor types as a result of distinct mechanisms in terms of cancer susceptibility. In addition, stratified analysis by genotyping techniques indicated that studies involving PCR-RFLP assay likely acquired significant results in the overall comparison. This trend is possible because studies involving Asians mainly utilized PCR-RFLP. In studies involving Caucasians, Taqman and MassArray were the main genotyping techniques. Considering gene-gene interaction analysis, we found a significant joint effect of ERCC1 –399Gln and PARP-1–762Ala on increased cancer risk in a homozygous genetic model. However, this result should be carefully interpreted because of a relatively small sample size; moreover, this result should be confirmed by conducting further analysis of additional published studies. Compared with two previous meta-analyses, our meta-analysis involved a remarkably larger number of studies (39 vs. 21 and 28) and provided a more comprehensive and reliable conclusion. Pooling the data from 39 studies, we reconfirmed the function of PARP-1 Val762Ala in increased cancer risk among Asian populations. Furthermore, cancer types in the study were more multifarious (seven types) and a significant association was found in cervical, lung, and gastric cancers, as well as glioma. In addition, the potential interaction effect of XRCC1 Arg399Gln on PARP-1 Val762Ala was also evaluated in the present analysis. Some potential limitations of this study should also be considered. First, the pooled results were based on unadjusted estimates because not all of the studies provided adjusted ORs; when these studies revealed adjusted ORs, these ORs were not adjusted by the same confounders. Hence, a precise analysis should be performed if individual data, such as age, sex, BMI, and smoking and drinking status, were available. Second, several factors, such as gene-gene or gene-environment interaction, may influence gene-disease factor. The joint effect between PARP-1 Val762Ala and XRCC1 Arg399Gln genotypes on the risk of cancer was addressed in the present study. However, the lack of individual data from the included studies limited the further evaluation of other potential interactions, as in other genes and environment factors. For instance, only two studies have reported the combined effect of XRCC1 Arg194Trp and PARP-1 Val762Ala genotypes on the risk of cancer [25], [32]. Third, only articles written in English were included; as such, bias may be observed in our meta-analysis. In conclusion, the present meta-analysis provided strong evidence of the association of PARP-1 Val762Ala with increased cancer risk among Asian populations. The same results were observed in the subgroups of gastric, cervical, and lung cancers, as well as in studies using PCR-RFLP genotyping method. Our findings suggested that the PARP-1 Val762Ala polymorphism may function in cancer development in an ethnicity- or cancer-specific manner. Well-designed epidemiological studies should be conducted by carefully matching cases and control subjects to verify our observations. Further studies may focus on the influence of gene-gene and gene-environment interactions on the association of cancer and PARP-1 Val762Ala polymorphism. PRISMA checklist. (DOC) Click here for additional data file.
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Review 1.  Polymorphisms in DNA repair genes and associations with cancer risk.

Authors:  Ellen L Goode; Cornelia M Ulrich; John D Potter
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2002-12       Impact factor: 4.254

2.  Identification of genetic variants in base excision repair pathway and their associations with risk of esophageal squamous cell carcinoma.

Authors:  Bingtao Hao; Haijian Wang; Kaixin Zhou; Yi Li; Xiaoping Chen; Gangqiao Zhou; Yunping Zhu; Xiaoping Miao; Wen Tan; Qingyi Wei; Dongxin Lin; Fuchu He
Journal:  Cancer Res       Date:  2004-06-15       Impact factor: 12.701

3.  Association between PARP-1 V762A polymorphism and cancer susceptibility: a meta-analysis.

Authors:  Hongping Yu; Hongxia Ma; Ming Yin; Qingyi Wei
Journal:  Genet Epidemiol       Date:  2011-11-29       Impact factor: 2.135

4.  Polymorphisms in DNA repair genes and risk of non-Hodgkin lymphoma among women in Connecticut.

Authors:  Min Shen; Tongzhang Zheng; Qing Lan; Yawei Zhang; Shelia H Zahm; Sophia S Wang; Theodore R Holford; Brian Leaderer; Meredith Yeager; Robert Welch; Daehee Kang; Peter Boyle; Bing Zhang; Kaiyong Zou; Yong Zhu; Stephen Chanock; Nathaniel Rothman
Journal:  Hum Genet       Date:  2006-04-26       Impact factor: 4.132

5.  Comprehensive association testing of common genetic variation in DNA repair pathway genes in relationship with breast cancer risk in multiple populations.

Authors:  Christopher A Haiman; Chris Hsu; Paul I W de Bakker; Melissa Frasco; Xin Sheng; David Van Den Berg; John T Casagrande; Laurence N Kolonel; Loic Le Marchand; Susan E Hankinson; Jiali Han; Alison M Dunning; Karen A Pooley; Matthew L Freedman; David J Hunter; Anna H Wu; Daniel O Stram; Brian E Henderson
Journal:  Hum Mol Genet       Date:  2007-12-03       Impact factor: 6.150

6.  Polymorphisms in base excision repair genes are associated with endometrial cancer risk among postmenopausal Japanese women.

Authors:  Satoyo Hosono; Keitaro Matsuo; Hidemi Ito; Isao Oze; Kaoru Hirose; Miki Watanabe; Toru Nakanishi; Kazuo Tajima; Hideo Tanaka
Journal:  Int J Gynecol Cancer       Date:  2013-11       Impact factor: 3.437

Review 7.  Poly(ADP-ribosyl)ation in relation to cancer and autoimmune disease.

Authors:  M Masutani; H Nakagama; T Sugimura
Journal:  Cell Mol Life Sci       Date:  2005-04       Impact factor: 9.261

8.  PARP-1 Val762Ala polymorphism is associated with reduced risk of non-Hodgkin lymphoma in Korean males.

Authors:  Xue Mei Jin; Hee Nam Kim; Il-Kwon Lee; Kyeong-Soo Park; Hyeoung-Joon Kim; Jin-Su Choi; Sang Woo Juhng; Chan Choi
Journal:  BMC Med Genet       Date:  2010-03-03       Impact factor: 2.103

9.  Genetic variation in base excision repair genes and the prevalence of advanced colorectal adenoma.

Authors:  Sonja I Berndt; Wen-Yi Huang; M Daniele Fallin; Kathy J Helzlsouer; Elizabeth A Platz; Joel L Weissfeld; Timothy R Church; Robert Welch; Stephen J Chanock; Richard B Hayes
Journal:  Cancer Res       Date:  2007-02-01       Impact factor: 12.701

10.  Polymorphisms in base excision repair genes and thyroid cancer risk.

Authors:  Luís S Santos; Sandra C Branco; Susana N Silva; Ana Paula Azevedo; Octávia M Gil; Isabel Manita; Teresa C Ferreira; Edward Limbert; José Rueff; Jorge F Gaspar
Journal:  Oncol Rep       Date:  2012-08-22       Impact factor: 3.906

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  9 in total

Review 1.  Trial watch - inhibiting PARP enzymes for anticancer therapy.

Authors:  Antonella Sistigu; Gwenola Manic; Florine Obrist; Ilio Vitale
Journal:  Mol Cell Oncol       Date:  2015-06-10

2.  Analyzing structure-function relationships of artificial and cancer-associated PARP1 variants by reconstituting TALEN-generated HeLa PARP1 knock-out cells.

Authors:  Lisa Rank; Sebastian Veith; Eva C Gwosch; Janine Demgenski; Magdalena Ganz; Marjolijn C Jongmans; Christopher Vogel; Arthur Fischbach; Stefanie Buerger; Jan M F Fischer; Tabea Zubel; Anna Stier; Christina Renner; Michael Schmalz; Sascha Beneke; Marcus Groettrup; Roland P Kuiper; Alexander Bürkle; Elisa Ferrando-May; Aswin Mangerich
Journal:  Nucleic Acids Res       Date:  2016-09-29       Impact factor: 16.971

3.  PARP1 rs1136410 Val762Ala contributes to an increased risk of overall cancer in the East Asian population: a meta-analysis.

Authors:  Yijuan Xin; Liu Yang; Mingquan Su; Xiaoli Cheng; Lin Zhu; Jiayun Liu
Journal:  J Int Med Res       Date:  2021-03       Impact factor: 1.671

4.  DNA repair genes polymorphisms and genetic susceptibility to Philadelphia-negative myeloproliferative neoplasms in a Portuguese population: The role of base excision repair genes polymorphisms.

Authors:  Ana P Azevedo; Susana N Silva; João P De Lima; Alice Reichert; Fernando Lima; Esmeraldina Júnior; José Rueff
Journal:  Oncol Lett       Date:  2017-04-21       Impact factor: 2.967

5.  Polymorphisms in PARP1 predict disease-free survival of triple-negative breast cancer patients treated with anthracycline/taxane based adjuvant chemotherapy.

Authors:  Yuqian Liao; Yulu Liao; Jun Li; Jianping Xiong; Ying Fan
Journal:  Sci Rep       Date:  2020-04-30       Impact factor: 4.379

6.  Modulation of brain tumor risk by genetic SNPs in PARP1gene: Hospital based case control study.

Authors:  Asad Ullah Khan; Ishrat Mahjabeen; Muhammad Arif Malik; Muhammad Zahid Hussain; Sarfraz Khan; Mahmood Akhtar Kayani
Journal:  PLoS One       Date:  2019-10-14       Impact factor: 3.240

Review 7.  DNA Damage Response in Multiple Myeloma: The Role of the Tumor Microenvironment.

Authors:  Takayuki Saitoh; Tsukasa Oda
Journal:  Cancers (Basel)       Date:  2021-01-28       Impact factor: 6.639

8.  Interaction among susceptibility genotypes of PARP1 SNPs in thyroid carcinoma.

Authors:  Kashif Bashir; Romana Sarwar; Soma Saeed; Ishrat Mahjabeen; Mahmood Akhtar Kayani
Journal:  PLoS One       Date:  2018-09-05       Impact factor: 3.240

9.  Contributions of PARP-1 rs1136410 C>T polymorphism to the development of cancer.

Authors:  Hunian Li; Yongjiu Zha; Fang Du; Jie Liu; Xiaoquan Li; Xu Zhao
Journal:  J Cell Mol Med       Date:  2020-10-27       Impact factor: 5.295

  9 in total

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