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XPG gene rs751402 C>T polymorphism and cancer risk: Evidence from 22 publications

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Oncotarget. 2017; 8:53613-53622. https://doi.org/10.18632/oncotarget.19421

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Haixia Zhou, Ting-Yan Shi, Wenwen Zhang, Qiwen Li, Jinhong Zhu, Jing He and Jichen Ruan _

Abstract

Haixia Zhou1,*, Ting-Yan Shi2,*, Wenwen Zhang3,*, Qiwen Li3, Jinhong Zhu4, Jing He1,5 and Jichen Ruan1

1Department of Hematology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325027, Zhejiang, China

2Department of Obstetrics and Gynecology, Zhongshan Hospital, Fudan University, Shanghai 200032, China

3State Key Laboratory of Oncology in South China, Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, Guangdong, China

4Molecular Epidemiology Laboratory and Department of Laboratory Medicine, Harbin Medical University Cancer Hospital, Harbin 150040, Heilongjiang, China

5Department of Pediatric Surgery, Guangzhou Institute of Pediatrics, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510623, Guangdong, China

*These authors have contributed equally to this work

Correspondence to:

Jichen Ruan, email: ruanjichen@163.com

Jing He, email: hejing198374@gmail.com

Keywords: DNA repair, XPG, polymorphism, cancer susceptibility, meta-analysis

Received: May 12, 2017     Accepted: June 12, 2017     Published: July 18, 2017

ABSTRACT

The Xeroderma pigmentosum group G (XPG) gene promotes recognition and excision of damaged DNA during the DNA repair process. We conducted a comprehensive search of the MEDLINE, EMBASE, and Chinese Biomedical databases for publications evaluating the association XPG gene rs751402 C>T polymorphism and overall cancer risk. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were adopted to assess the strength of the association. A total of 22 publications encompassing 10538 cases and 10511 control subjects were included in the final meta-analysis. We found the polymorphism to be associated with increased cancer risk (TT vs. CC: OR = 1.18, 95% CI = 1.01–1.38, P = 0.040; CT vs. CC: OR = 1.12, 95% CI = 1.01–1.24, P = 0.040; and CT/TT vs. CC: OR = 1.12, 95% CI = 1.002–1.26, P = 0.045). Stratification by cancer type indicated that this polymorphism may increase the risk of gastric cancer and hepatocellular carcinoma, which was further confirmed by a false-positive report probability analysis. Genotype-based mRNA expression provides further evidence that this polymorphism is associated with altered XPG mRNA expression. This meta-analysis suggests XPG gene rs751402 C>T polymorphism correlates with overall cancer risk, especially for gastric cancer and hepatocellular carcinoma.


INTRODUCTION

According to an estimation by GLOBOCAN, approximately 14.1 million new cancer cases, including 8.2 million deaths, occurred worldwide in 2012 [1]. Approximately 4,292,000 new cancer cases and 2,814,000 cancer deaths occurred in China in 2015, with lung, gastric, esophageal, and liver cancer being the most commonly diagnosed and the leading causes of death [2]. Risk factors for the leading causes of cancer-related deaths are tobacco consumption, overweight/obesity, physical inactivity, and infection [1]. Genetic factors should also be considered [38].

Human DNA repair genes maintain the integrity and stability of genomic DNA, consequently preventing carcinogenesis and influencing clinical outcomes [9, 10]. Many genes promote the diverse DNA repair pathways, including the nucleotide excision repair (NER) pathway [11]. The NER pathway consists of damage recognition, demarcation, dual incision, and gap filling and can repair a variety of damaged DNA [12]. The NER pathway is the main mechanism for the removal of DNA adducts and lesions caused by chemical adducts [13]. Polymorphisms of the genes from the NER pathway might activate cancer risk alteration [14]. As one of the eight core genes in the NER pathway, Xeroderma pigmentosum group G (XPG), which is also known as excision repair cross-complementing group 5 (ERCC5), can recognize and excise DNA lesions on the 3′ side to repair damaged DNA [15].

XPG gene polymorphisms were reported to be associated with the susceptibility of various types of cancers [1618]. Thus, most of the investigations were focused on rs17655 G>C (Asp1104His). The association between XPG gene rs751402 C>T polymorphism (located at the 5′ untranslational region) and cancer risk has been investigated in several studies [1940], but the findings were contradictory and inconclusive. Therefore, we performed this meta-analysis with all eligible publications to comprehensively evaluate the association of XPG gene rs751402 C>T polymorphism with overall cancer risk.

RESULTS

Characteristics of eligible publications

As shown in Figure 1, 227 publications were identified from MEDLINE and EMBASE and 26 additional publications in Chinese were identified from the Chinese Biomedical (CBM) database. After reviewing the abstracts and the full texts, we excluded 222 publications and selected 31 publications with studies of the rs751402 C>T polymorphism for further full-text review. Among these publications, nine were excluded because two studies were repetitive, five studies were clinical outcome studies, and two studies were not on cancers. In the final meta-analysis, 22 publications with studies of 10588 cases and 10511 control subjects were identified, with the duplicated samples counted only once. The characteristics of the included publications are showed in Table 1. In these publications, sample sizes ranged from 96 to 1900 cases and from 101 to 1977 control subjects. Among the studies, 10 focused on gastric cancer [21, 23, 27, 29, 30, 32-34, 38, 39], three focused on breast cancer [25, 35, 36], two focused on hepatocellular carcinoma [20, 37], and one each focused on lung cancer [19], oral squamous cell carcinoma [22], salivary gland tumor [24], nasopharyngeal carcinoma [26], neuroblastoma [28], colorectal cancer [31], and prostate cancer [40]. Of the publications, 12 had quality scores higher than nine, and 10 had quality scores of no more than nine.

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

Name

Year

Cancer type

Region

Ethnicity

Design

Genotype method

Case

Control

MAF

HWE

Score

CC

CT

TT

All

CC

CT

TT

All

Shao

2007

Lung

China

Asian

HB

Taqman

433

429

105

967

448

425

110

983

0.33

0.544

11

Yoon

2011

HCC

Taiwan

Asian

HB

Taqman

33

52

11

96

167

137

32

336

0.30

0.614

6

Duan

2012

Gastric

China

Asian

HB

MassARRAY

172

181

47

400

206

165

29

400

0.28

0.605

11

Zavras

2012

OSCC

Taiwan

Asian

HB

Taqman

98

110

31

239

167

137

32

336

0.30

0.614

9

He

2013

Gastric

China

Asian

HB

Taqman

486

491

148

1125

560

499

137

1196

0.32

0.110

13

Meng

2013

Salivary gland

China

Asian

HB

PCR-RFLP

59

63

11

133

64

55

23

142

0.36

0.065

8

Na

2015

Breast

China

Asian

HB

PCR-RFLP

128

152

45

325

137

147

41

325

0.35

0.872

10

Sun

2015

NPC

China

Asian

HB

PCR-LDR

17

118

237

372

19

117

235

371

0.79

0.377

11

Chen

2016

Gastric

China

Asian

HB

Taqman

286

313

93

692

351

331

89

771

0.33

0.416

11

He

2016

Neuroblastoma

China

Asian

HB

Taqman

96

114

38

248

208

241

82

531

0.38

0.380

10

Feng

2016

Gastric

China

Asian

HB

PCR-RFLP

70

83

24

177

101

107

28

236

0.35

0.967

6

Guo

2016

Gastric

China

Asian

HB

PCR-RFLP

47

73

22

142

117

136

21

274

0.32

0.029

5

Hua

2016

Colorectal

China

Asian

HB

Taqman

792

860

248

1900

724

952

301

1977

0.39

0.680

10

Hua

2016

Gastric

China

Asian

HB

Taqman

426

555

161

1142

433

551

189

1173

0.40

0.537

11

Li

2016

Gastric

China

Asian

HB

PCR-RFLP

88

106

22

216

95

103

18

216

0.32

0.174

8

Lu

2016

Gastric

China

Asian

HB

PCR-RFLP

69

91

24

184

87

97

22

206

0.34

0.510

6

Ma

2016

Breast

China

Asian

HB

PCR-RFLP

127

150

43

320

107

101

28

236

0.33

0.580

7

Wang

2016

Breast

China

Asian

HB

PCR-RFLP

90

10

1

101

51

39

11

101

0.30

0.398

9

Wang

2016

HCC

China

Asian

PB

MassARRAY

70

81

18

169

232

185

60

477

0.32

0.018

12

Yang

2016

Gastric

China

Asian

HB

PCR-RFLP

49

73

33

155

103

111

32

246

0.36

0.807

6

Zhou

2016

Gastric

China

Asian

HB

PCR-LDR

174

196

61

431

193

193

46

432

0.33

0.827

12

Wang

2017

Prostate

China

Asian

HB

Taqman

442

458

104

1004

477

467

111

1055

0.33

0.834

10

MAF, minor allele frequency; HWE, Hardy-Weinberg equilibrium; HCC, hepatocellular carcinoma; OSCC, oral squamous cell carcinoma; NPC, nasopharyngeal carcinoma; HB, hospital based; PB, population based; PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; PCR-LDR, polymerase chain reaction- ligase detection reaction.

Flowchart of the included publications.

Figure 1: Flowchart of the included publications.

Meta-analysis results

As shown in Table 2, significant heterogeneity was presented in all genetic models. As a result, we adopted a random-effect model for all the analyses. We found the XPG gene rs751402 C>T polymorphism associated with increased overall cancer risk (TT vs. CC: odds ratio [OR] = 1.18, 95% confidence interval [CI] =1.01–1.38; CT vs. CC: OR = 1.12, 95% CI = 1.01–1.24; and CT/TT vs. CC: OR = 1.12, 95% CI = 1.002–1.26). As shown in Figure 2, stratification analysis indicated that this polymorphism was associated with increased risk of gastric cancer (TT vs. CC: OR = 1.38, 95% CI = 1.12-1.70; CT vs. CC: OR = 1.14, 95% CI = 1.05–1.24; TT vs. CC/CT: OR = 1.27, 95% CI = 1.06-1.51; CT/TT vs. CC: OR = 1.17, 95% CI = 1.08–1.26; and T vs. C: OR = 1.17, 95% CI = 1.07–1.27) and hepatocellular carcinoma (CT vs. CC: OR = 1.61, 95% CI = 1.19–2.17; and CT/TT vs. CC: OR=1.53, 95% CI=1.10-2.13). The stratification analysis did not reveal a significant difference between the two strata in any genetic model by quality score.

Table 2: Meta-analysis of the association between XPG gene rs751402 C>T polymorphism and overall cancer risk

Variables

No. of studies

Sample size

Homozygous

Heterozygous

Recessive

Dominant

Allele

TT vs. CC

CT vs. CC

TT vs. CT+CC

CT+TT vs. CC

T vs. C

OR (95% CI)

Phet

OR (95% CI)

Phet

OR (95% CI)

Phet

OR (95% CI)

Phet

OR (95% CI)

Phet

All

22

10538/10511

1.18 (1.01–1.38)

<0.001

1.12 (1.01–1.24)

<0.001

1.09 (0.97–1.23)

0.009

1.12 (1.002–1.26)

<0.001

1.09 (1.00–1.18)

<0.001

Cancer type

Gastric

10

4664/5150

1.38 (1.12–1.70)

0.020

1.14 (1.05–1.24)

0.936

1.27 (1.06–1.51)

0.053

1.17 (1.08–1.26)

0.437

1.17 (1.07–1.27)

0.043

Breast

3

746/662

0.79 (0.31–1.98)

0.010

0.64 (0.26–1.58)

<0.001

0.87 (0.43–1.79)

0.044

0.60 (0.23–1.60)

<0.001

0.63 (0.29–1.35)

<0.001

HCC

2

265/813

1.24 (0.73–2.12)

0.262

1.61 (1.19–2.17)

0.373

0.96 (0.62–1.49)

0.398

1.53 (1.10–2.13)

0.256

1.26 (0.97–1.63)

0.220

Others

7

4863/5395

0.95 (0.78–1.16)

0.082

1.03 (0.89–1.18)

0.071

0.94 (0.82–1.07)

0.270

1.02 (0.88–1.18)

0.028

0.99 (0.90–1.10)

0.025

Quality score

>9

12

8775/9691

1.08 (0.93–1.25)

0.011

1.06 (0.98–1.17)

0.063

1.02 (0.92–1.14)

0.137

1.08 (0.98–1.19)

0.007

1.05 (0.98–1.14)

0.002

≤9

10

1763/2329

1.34 (0.95–1.89)

0.009

1.13 (0.86–1.48)

<0.001

1.21 (0.90–1.62)

0.029

1.12 (0.84–1.51)

<0.001

1.07 (0.85–1.35)

<0.001

OR, odds ratio; CI, confidence interval; Het, heterogeneity; HCC, hepatocellular carcinoma.

Stratification analysis for the association between XPG gene rs751402 C&#x003E;T polymorphism and overall cancer risk by cancer type under the dominant model (CT/TT vs. CC).

Figure 2: Stratification analysis for the association between XPG gene rs751402 C>T polymorphism and overall cancer risk by cancer type under the dominant model (CT/TT vs. CC). For each publication, the estimation of OR and its 95% CI are plotted with a box and a horizontal line. The diamonds represent the pooled ORs and 95% CIs.

False-positive report probability analysis for significant findings

We performed false-positive report probability (FPRP) analysis for all significant findings and confirmed that the findings were significant at the priority of 0.1 for gastric cancer and hepatocellular carcinoma (Table 3).

Table 3: False-positive report probability analysis values for the noteworthy findings

Genotype

Crude OR (95% CI)

Pa

Statistical powerb

Prior probability

0.25

0.1

0.01

0.001

0.0001

Overall cancer risk

 TT vs. CC

1.18 (1.01–1.38)

0.040

1.000

0.107

0.264

0.798

0.976

0.998

 CT vs. CC

1.12 (1.01–1.24)

0.040

1.000

0.106

0.263

0.797

0.975

0.997

 CT/TT vs. CC

1.12 (1.002–1.26)

0.047

1.000

0.123

0.296

0.822

0.979

0.998

Hepatocellular carcinoma

 CT vs. CC

1.61 (1.19–2.17)

0.002

0.394

0.013

0.038

0.305

0.816

0.978

 CT/TT vs. CC

1.53 (1.10–2.13)

0.011

0.608

0.050

0.137

0.636

0.946

0.994

Gastric cancer

 TT vs. CC

1.38 (1.12–1.70)

0.002

1.000

0.007

0.019

0.179

0.687

0.956

 CT vs. CC

1.14 (1.05–1.24)

0.003

1.000

0.008

0.024

0.213

0.732

0.965

 TT vs. CT/CC

1.27 (1.06–1.51)

0.010

1.000

0.030

0.085

0.506

0.912

0.990

 CT/TT vs. CC

1.17 (1.08–1.26)

<0.001

1.000

0.001

0.002

0.019

0.161

0.658

 T vs. C

1.17 (1.07–1.27)

0.001

1.000

0.002

0.006

0.063

0.404

0.871

OR, odds ratio; CI, confidence interval.

aA χ2 test was used to evaluate the distributions of genotype frequency.

bStatistical power was calculated by use of the number of observations in the subgroup and P values in this table.

The genotype-based mRNA expression for XPG gene rs751402 C>T polymorphism

As shown in Table 4, the rs751402T allele carriers were associated with decreased XPG mRNA expression among Asians (not significant), Africans (TT vs. CC: P = 0.029), and Caucasians (TT vs. CC: P = 0.013; and TT vs. CC/CT: P = 0.011), as well as all subjects (TT vs. CC: P = 0.010; and TT vs. CC/CT: P = 0.008).

Table 4: XPG gene mRNA expression by the genotypes of rs751402 C>Ta

Population

Genotypes

No.

Mean ± SD

Pb

Ptrend c

Asian

CC

30

9.79 ± 0.21

0.409

CT

47

9.76 ± 0.22

0.537

TT

13

9.69 ± 0.23

0.188

Dominant

60

9.75 ± 0.22

0.352

Recessive

77

9.77 ± 0.22

0.233

CEU

CC

54

9.72±0.23

0.039

CT

29

9.70±0.22

0.823

TT

7

9.48±0.15

0.013

Dominant

36

9.66±0.22

0.271

Recessive

83

9.71±0.23

0.011

YRI

CC

35

9.86±0.16

0.100

CT

43

9.82±0.17

0.245

TT

12

9.75±0.14

0.029

Dominant

55

9.80±0.17

0.094

Recessive

78

9.84±0.17

0.074

All

CC

119

9.78 ± 0.22

0.030

CT

119

9.77 ± 0.21

0.693

TT

32

9.67 ± 0.21

0.010

Dominant

151

9.75 ± 0.21

0.220

Recessive

238

9.77 ± 0.21

0.008

aThe rs751402 C>T genotypes data were obtained from the HapMap Phase II Release 23 data, and XPG mRNA expression levels were from EBV-transformed lymphoblastoid cell lines from 270 individuals.

bTwo-side Student’s t-test within the stratum.

cP values for the trend test of the XPG gene mRNA expression among three genotypes for rs751402 C>T from a general linear model.

Sensitivity analysis and publication bias

By omitting each publication once in every genetic model in the sensitivity analysis, we did not find any individual publication that could significantly alter the pooled ORs, which indicated that our data were stable and trustworthy. As shown in Figure 3, no obvious publication bias was observed for rs751402 C>T polymorphism (TT vs. CC: P = 0.111; CT vs. CC: P = 0.251; TT vs. CT/CC: P = 0.236; CT/TT vs. CC: P = 0.249; and T vs. C: P = 0.298).

Funnel plot for the association between XPG gene rs751402 C&#x003E;Tpolymorphism and overall cancer risk under the dominant model (CT/TT vs. CC).

Figure 3: Funnel plot for the association between XPG gene rs751402 C>Tpolymorphism and overall cancer risk under the dominant model (CT/TT vs. CC).

Trial sequential analysis

As shown in Figure 4, we observed that the cumulative z-curve crossed the monitoring boundary before reaching the required sample size, indicating the sample size was sufficient and no further investigation was needed to verify the results.

Trial sequential analysis for XPG gene rs751402 C&#x003E;T polymorphism under the dominant model.

Figure 4: Trial sequential analysis for XPG gene rs751402 C>T polymorphism under the dominant model.

DISCUSSION

In the current meta-analysis, we investigated all available publications that contained studies of the association between XPG gene rs751402 C>T polymorphism and cancer risk. The pooled results suggest that this polymorphism is associated with increased cancer risk, especially for gastric cancer and hepatocellular carcinoma.

The XPG gene, which is located at 13q33 and consists of 15 exons, promotes the removal of damaged DNA in the NER process [41]. When DNA repair capability is decreased, cells might fail to repair the damage. As DNA mutations accumulate, carcinoma might occur [9, 21]. The XPG gene is an essential component of the NER pathway, and it activates the cleavage of DNA on the 3′ side of the lesion [42]. Studies reported that the XPG gene promotes cellular processes such as RNA polymerase II transcription and transcription-coupled DNA repair [43]. XPG gene polymorphisms might affect the expression or function of the XPG protein. Studies in several publications investigated the function of XPG gene rs751402 C>T polymorphism in cancer susceptibility. However, inconsistent results have been reported. Duan et al. [21] found that this polymorphism might increase the risk of gastric cancer in a study of 403 gastric cancer cases and 403 healthy control subjects. This association was also confirmed in gastric cancer by Yang et al. [38] in a study of 155 gastric cancer cases and 246 healthy control subjects, in hepatocellular carcinoma by Yoon et al. [20], and in oral squamous cell carcinoma by Zavras et al. [22]. Hua et al. [31] found that this polymorphism might be associated with decreased colorectal cancer susceptibility by studying 1901 colorectal cases and 1976 control subjects, and might have no effect in gastric cancer, as determined by 1142 cases and 1173 control subjects. Others found that this polymorphism might have weak effects on cancer susceptibility. The controversy can possibly be ascribed to the small sample size as well as cancer differences. To overcome the limitations of a single study and to reduce the likelihood of random errors being responsible for false-positive or false-negative associations, we performed the current meta-analysis to assess the association between XPG gene rs751402 C>T polymorphism and overall cancer susceptibility. We included 22 available publications, encompassing 10588 cases and 10511 control subjects, and found that this polymorphism was associated with increased overall cancer risk, especially for gastric cancer and hepatocellular carcinoma. We also performed FPRP analysis to confirm that the significant associations were trustworthy and robust. In addition, the genotype-based mRNA expression analysis as performed also indicated that this polymorphism might be associated with XPG gene mRNA expression alteration.

The current meta-analysis has five advantages. First, we searched the latest publications and we also included the publications written in Chinese. Second, we assessed the quality of each investigation and conducted stratification analysis by the quality score to search for publication bias. Third, we performed genotype-based mRNA expression analysis to provide further evidence that the rs751402 C>T polymorphism can influence the expression of the XPG gene. Fourth, we performed FPRP analysis, which can confirm whether the significant associations are trustworthy and robust. Fifth, we performed TSA to strengthen the robustness and minimize random errors of our conclusions.

Although in the present study we performed the latest and largest meta-analysis for assessing the association between XPG gene rs751402 C>T polymorphism and overall cancer susceptibility, four limitations must be considered. First, because of the heterogeneity in the current meta-analysis, the conclusions on the overall cancer risk should be interpreted cautiously. Second, the results of this study were based on the unadjusted ORs, which might suppress the final results. Third, all the study subjects were Asians. Other ethnicities are needed as subjects in future studies. Fourth, despite the adequacy of the total number of publications, the number of publications that contain studies for some cancers were inadequate. Investigations into other cancers are needed.

Our meta-analysis found that XPG gene rs751402 C>T polymorphism is associated with increased overall cancer risk, especially with respect to gastric cancer and hepatocellular carcinoma. Investigations of different cancers and ethnicities are needed to validate our findings.

MATERIALS AND METHODS

Publication search

We systematically searched publications from the MEDLINE, EMBASE, and CBM databases (the last search was updated April 28, 2017) using the following search terms: “cancer or carcinoma or tumor or neoplasm,” “excision repair cross-complementing group 5 or ERCC5 or xeroderma pigmentosum group G or XPG or rs751402,” and “polymorphism or variant or single nucleotide polymorphism (SNP) or variation.” We also manually searched the reference lists of the articles in the included publications.

Inclusion and exclusion criteria

The studies in the included publications met the following criteria: (1) the study evaluated the association between XPG gene rs751402 C>T polymorphism and cancer risk, (2) the study was on human beings, (3) the study was a case-control or cohort design, (4) sufficient data were provided to calculate the ORs and 95% CIs, and (5) the study was published in English or Chinese.

Exclusion criteria were (1) the study was not a case-control design, (2) the study was duplicated from previous studies, (3) articles were case reports or review articles, and (4) the studies were without detailed genotype data.

Data extraction and quality assessment

Two authors (Haixia Zhou and Ting-Yan Shi) performed the publication search and data extraction independently. The extracted information includes surname of the first author, publication year, cancer type, country of origin, ethnicity, genotyping methods, and numbers of cases and control subjects with rs751402 CC, CT and TT genotypes. We assessed the quality of each publication based on the quality score assessment [44]. All contradictory information was discussed and resolved through consensus when necessary.

Genotype-based mRNA expression analysis

To determine whether the XPG gene rs751402 C>T polymorphism can influence expression of the XPG gene, we conducted genotype-based mRNA expression analysis as previously described [3, 45, 46]. Genotype data of XPG gene rs751402 C>T polymorphism for 270 individuals were obtained from HapMap Phase II Release 23. The mRNA expression data for the corresponding individuals were from SNPexp [47].

Statistical analysis

Pooled ORs and 95% CIs were used to investigate the strength of the association between XPG gene rs751402 C>T polymorphism and overall cancer risk under the homozygous (TT vs. CC), heterozygous (CT vs. CC), recessive (TT vs. CT+CC), dominant (CT+TT vs. CC), and allele contrast (T vs. C) models. A goodness-of-fit χ2 test was adopted to assess the Hardy-Weinberg equilibrium for the control subjects. Stratification analysis was carried out by cancer type (publications with no more than two were merged as the Others Group) and quality score (>9 and ≤9). Heterogeneities were assessed by χ2-based Q test, and a fixed-effect model was adopted when P > 0.1. Otherwise, the random-effect model was applied [48]. Sensitivity analysis was then conducted by omitting each publication in turn to evaluate the stability of the overall results. Potential publication bias was assessed by Begg’s funnel plot [49] and Egger’s linear regression test [50]. FPRP and TSA were as previously described [8]. All the statistics were two-sided, and P < 0.05 was statistically significant. All statistical analyses were performed by the STATA software (Version 11.0; Stata Corporation, College Station, TX).

CONFLICTS OF INTEREST

The authors declare that there are no conflicts of interest.

FUNDING

This study was supported by a grant awarded by the Scientific Research Foundation of Wenzhou (2015Y0492), Zhejiang Provincial Medical and Health Science and Technology plan (2009A148), Zhejiang Provincial Science and Technology Animal Experimental Platform Project (016C37113) and the Special Financial Grant with the China Postdoctoral Science Foundation (2014T70836).

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