Open Access

RAD 51 Gene 135G/C polymorphism and the risk of four types of common cancers: a meta-analysis

Diagnostic Pathology20149:18

DOI: 10.1186/1746-1596-9-18

Received: 30 August 2013

Accepted: 27 December 2013

Published: 23 January 2014

Abstract

Objectives

RAD 51 gene plays an important role in the pathogenesis of squamous cell carcinoma of the head and neck (SCCHN), colorectal cancer, ovarian cancer and acute leukaemia. A number of studies assessed the association between RAD51 135G/C polymorphism and the risk of these cancers in different population. However, the results have been inconclusive. We performed a systematic meta-analysis to evaluate the association between RAD51 135G/C polymorphism and the risk of these four types of cancer.

Methods

Pubmed, Cochrane library and Chinese Biomedical Literature Database (CBM) were searched for case-control studies on RAD 51 135G/C polymorphism and the risk of SCCHN, colorectal cancer, ovarian cancer and acute leukaemia published up to Oct 31, 2013. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of association.

Results

A total of twenty-two published studies, with 6836 cases and 8507 controls were included. Overall, no significant association was found between RAD51 135G/C polymorphism and the risk of the four types of cancers (G/G vs. C/C: OR = 0.83, 95% CI: 0.43-1.59, P = 0.57). However, there was a significant association between this polymorphism and SCCHN risk in the subgroup analysis by cancer type (G/G vs. C/C: OR = 2.46, 95% CI: 1.08-5.61, P = 0.03).

Conclusion

The RAD 51 135G/C polymorphism was associated with the risk of SCCHN.

Virtual slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1383180234106945.

Keywords

RAD 51 Single nucleotide polymorphism Cancer risk Meta-analysis

Introduction

Cancer is one of the most common fatal diseases, which results from complex interactions between environmental and genetic factors [1]. More and more studies have focused on the role of gene polymorphism in the aetiology of cancers. Recently, there is growing evidence that single nucleotide polymorphism (SNP) plays an important role in carcinogenesis [2, 3]. DNA repair systems have been considered to maintain genomic integrity by counting threats posed by DNA lesions. Deficiency in the DNA repair pathways might make these lesions unrepaired or repaired incorrectly, eventually leading to genome instability or mutations which may contribute directly to cancer.

RAD51 gene is located on chromosome 15q15.1 in humans [4]. The RAD51 protein encoding by RAD51 gene is essential for the repair of DNA damage. Growing evidences show that RAD51 has an irreplaceable role in the maintenance of genomic stability and the repair of DNA double-strand breaks [5]. The RAD51 genetic variations may contribute to the development of cancers [6]. A functional single nucleotide polymorphism, 135G/C (rs1801320), has been identified in the 5′ untranslated region of the RAD51 gene [7] and has been reported to affect gene transcription activity [8].

Up to now, a variety of molecular epidemiological studies have been conducted to estimate the association between the RAD51 135G/C polymorphism and risk of various cancers [917], including squamous cell carcinoma of the head and neck [1821], colorectal cancer [2225], ovarian cancer [2628] and acute leukaemia [2937]. However, the results of previous studies on the association between RAD51 135G/C polymorphism and cancer risk have been inconclusive, partially because of the relatively small sample size of most studies. Therefore, we carried out this meta-analysis to evaluate the association between RAD51 135G/C polymorphism and risk of the four common types of cancers.

Methods

Selection of eligible studies

We conducted a comprehensive search in Pubmed, Cochrane library and Chinese Biomedical Literature Database (CBM), covering all articles published up to Oct 31, 2013, using the following terms: “RAD51” AND “polymorphism” AND “(squamous cell carcinoma of the head and neck) OR (colorectal cancer) OR (ovarian cancer) OR (acute leukaemia)”. References of all identified studies and reviews were examined for additional articles.

Study assessment

Included studies in this meta-analysis met the following criteria: (a) a human case-control study on the association between RAD51 135G/C polymorphism and any of the four common cancers; (b) containing available genotype data in cases and controls for estimating an odds ratio (OR) and 95% confidence interval (CI); (c) genotype distributions of control population were consistent with Hardy-Weinberg equilibrium (HWE). The exclusion criteria were: (a) reviews, letters, editorial articles and case reports; (b) studies involving only a case population; (c) research not providing cancer information.

Data extraction

Two investigators (Cheng and Shi) extracted the data from all of the eligible publications according to the inclusion and exclusion criteria mentioned above. Primary extraction data were reviewed by Zhen, and any disagreement was resolved by discussion among the three authors. From each study, the following information was collected: first author’s name, year of publication, study location, cancer type, sample size, source of control, the genotyping method, the number of genotype frequencies in cases and controls.

Statistical analysis

For each case-control study, we first examined whether the genotype frequencies in controls were consistent with HWE. ORs and 95% CIs were calculated as a measure of the association between the RAD51 135G/C gene polymorphism and risk of the four cancers. The pooled ORs were performed for the homozygote comparison (G/G vs. C/C), heterozygote comparison (G/C vs. C/C), dominant (G/G + G/C vs. C/C) and recessive (G/G vs. G/C + C/C) genetic model comparison, and the significances of the summary ORs were determined by Z test, P < 0.05 was considered as statistically significant. The chi-square-based Q-test was used to assess the statistical heterogeneity among studies, and it was considered significant if P < 0.10 [38]. If the P value greater than 0.10, indicating the absence of heterogeneity, then a fixed-effects model (the Mantel-Haenszel method) was applied to calculate the summary ORs [39]. Otherwise, the random-effects model (the DerSimonian and Laird method) was used [40]. I2 was also calculated to test heterogeneity among included studies, with I2 < 25%, 25-75%, and >75% considered to represent low, moderate and high degree of heterogeneity, respectively [41]. Sensitivity analysis was performed to estimate the stability of the results, each study involved in this meta-analysis was deleted each time to reflect the influence of the individual data set to pooled ORs. Publication bias within the literature was assessed using Begg’s test [42], an asymmetric funnel plot showed a potential publication bias. Egger’s linear regression test (P < 0.05 was considered significant publication bias) was also used to evaluate the symmetry of the funnel plot [43]. All of the analyses were carried out with RevMan 5.0.23 (Cochrane Library Software, Oxford, UK) and STATA11.0 (STATA Corporation, College Station, TX, USA).

Results

Study characteristics

A total of 133 related publications were identified, of which 19 studies were not accepted since they were not full articles (6 reviews, 7 meta-analysis, 4 comments, 2 case-reports). Fifty-nine articles were not about the above four cancers, 33 publications were excluded because they did not meet the inclusion criteria (11 not case-control studies, 6 not human studies, 7 not present the usable data, 7 not the gene loci, 2 not about polymorphism research). Finally, 22 studies including 6836 cases and 8507 controls were included in this meta-analysis (Figure 1).
https://static-content.springer.com/image/art%3A10.1186%2F1746-1596-9-18/MediaObjects/13000_2013_Article_923_Fig1_HTML.jpg
Figure 1

Flow diagram of study selection.

The main characteristics of these 22 included studies are summarized in Table 1. There were 14 studies from European countries, 3 studies from Asian countries, 3 studies from American countries, 1 study from Australia and 1 study from Africa. In addition, 9 articles were population-based and 13 articles were hospital-based. The number of publications on SCCHN, colorectal, ovarian cancer and acute leukaemia were 4, 4, 5, and 9, respectively. The diagnosis of most of the cases was based on pathology. Healthy subjects matched for age and sex were used as controls. Polymerase chain reaction (PCR) or restriction fragment length polymorphism(RFLP) were performed as genotyping methods. The genotype distributions and HWE examination results were shown in Table 2.
Table 1

Characteristics of 22 published studies included in this meta-analysis

First author

Year

Study location

Cancer type

Sample size

Source of controls

Genotyping methods

1. Lu JC

2006

USA

SCCHN

716/719

HCC

PCR-RFLP

2. Gil J

2011

Poland

CC

133/100

HCC

PCR-RFLP

3. Webb PM

2005

Australia

OC

548/335

PCC

PCR

4. Gresner P

2012

Poland

SCCHN

81/111

PCC

PCR

5. Seedhouse C

2004

UK

AL

267/186

PCC

PCR

6. Jawad M

2006

UK

AL

267/186

PCC

PCR

7. Krupa R

2011

Poland

CC

100/100

HCC

PCR

8. Sliwinski T

2010

Poland

SCCHN

288/353

HCC

PCR-RFLP

9. Hamdy MS

2011

Egypt

AL

50/30

HCC

PCR-RFLP

10. Liu L

2011

China

AL

625/704

HCC

PCR

11. Romanowicz-MakowskaH

2012

Poland

CC

320/320

HCC

PCR

12. WerbouckJ

2008

Belgium

SCCHN

152/157

HCC

PCR

13. Romanowicz-MakowskaH

2011

Poland

OC

120/120

HCC

PCR

14. Bhatla D

2008

USA

AL

452/646

PCC

PCR

15. Voso MT

2007

Italy

AL

160/161

HCC

PCR-RFLP

16. Mucha B

2012

Poland

CC

200/200

HCC

PCR-RFLP

17. Zhang ZQ

2009

China

AL

166/458

HCC

PCR-RFLP

18. Auranen A (UK)

2005

UK

OC

729/847

PCC

PCR

18. Auranen A (USA)

2005

USA

OC

326/419

PCC

PCR

18. Auranen A (Danish)

2005

Denmark

OC

278/699

PCC

PCR

21. Yang L

2011

China

AL

379/704

HCC

PCR

22. Rollinson S

2006

UK

AL

479/952

PCC

PCR

SCCHN: squamous cell carcinoma of the head and neck; CC: colorectal cancer; OC: ovarian cancer; AL: acute leukaemia; HCC: hospital-based case-control; PCC: population-based case-control; PCR: polymerase chain reaction; RFLP: restriction fragment length polymorphism.

Table 2

Distribution of RAD51 genotype and allele among cancer patients and controls

First author

Year

Case

GC

CC

Control

GC

CC

Case

C

Control

C

HWE

  

GG

  

GG

  

G

 

G

  

1. Lu JC

2006

624

91

1

622

96

1

1339

93

1340

98

0.17

2. Gil J

2011

100

29

4

73

27

0

229

37

173

27

0.19

3. Webb PM

2005

457

85

4

971

145

10

999

93

2087

165

0.08

4. Gresner P

2012

67

13

1

71

14

2

147

15

156

18

0.22

5. Seedhouse C

2004

210

44

3

166

18

2

464

50

350

22

0.08

6. Jawad M

2006

210

44

3

166

18

2

464

50

350

22

0.08

7. Krupa R

2011

61

36

3

36

35

29

158

42

107

93

0.003

8. Sliwinski T

2010

138

145

5

258

64

32

421

155

580

128

0.28

9. Hamdy MS

2011

39

9

2

26

3

1

87

13

55

5

0.06

10. Liu L

2011

72

25

8

511

175

18

169

25

1197

211

0.52

11. Romanowicz- MakowskaH

2012

51

56

213

91

164

65

158

482

346

294

0.57

12. Werbouck J

2008

136

15

1

134

23

0

287

17

291

23

0.32

13. Romanowicz-MakowskaH

2011

13

15

92

33

69

18

41

199

135

105

0.07

14. Bhatla D

2008

374

73

5

555

85

6

821

83

1195

97

0.18

15. Voso MT

2007

125

33

2

142

18

1

283

37

302

20

0.61

16. Mucha B

2012

161

34

5

157

37

6

356

44

351

49

0.05

17. Zhang ZQ

2009

117

47

2

315

123

20

281

51

753

163

0.08

18. Auranen A (Danish)

2005

241

36

1

616

78

5

518

38

1310

88

0.15

18. Auranen A (UK)

2005

642

84

3

745

100

2

1368

90

1590

104

0.48

18. Auranen A (USA)

2005

270

52

4

357

61

1

592

60

775

63

0.34

21. Yang L

2011

268

101

10

511

175

18

637

121

1197

211

0.52

22. Rollinson S

2006

431

34

1

817

115

4

896

36

1749

123

0.98

HWE: P value for Hardy-Weinberg equilibrium for RAD51 135G/C polymorphism among controls.

Quantitative synthesis

The evaluation of association between RAD 51 135G/C gene polymorphism and the risk of the four types of cancers was summarized in Table 3. Overall, no significant association was found between RAD 51 135G/C gene polymorphism and the risk of the four cancers (G/G vs. C/C: OR = 0.83, 95%CI = 0.43-1.59, P = 0.57; G/C vs. C/C: OR = 0.90, 95%CI = 0.39-2.08, P = 0.81; G/G + G/C vs. C/C: OR = 0.82, 95%CI = 0.39-1.73, P = 0.60; G/G vs. G/C + C/C: OR = 0.84, 95%CI = 0.69-1.02, P = 0.08). However, in the subgroup analysis by cancer type, there was a significant association between this polymorphism and SCCHN under homozygote comparison (G/G vs. C/C: OR = 2.46, 95%CI = 1.08-5.61; P = 0.03) (Figure 2). There was no significant association between this polymorphism and the risk of other three cancers under all comparisons. In the subgroup analyses by ethnicity or source of controls, no significant association was found in different genetic models.
Table 3

Total and stratified analysis of the RAD51 135G/C polymorphism on risk of the four cancers

Variables

No.a

Case/Control

GG vs. CC

GC vs. CC

GG+GC vs. CC

GG vs. GC+CC

   

OR(95% CI)

Pb

P

OR(95% CI)

Pb

P

OR(95% CI)

Pb

P

OR(95% CI)

Pb

P

Total cancer types

22

6836/8507

0.83(0.43–1.59)

0.00c

0.57

0.90(0.39–2.08)

0.00c

0.81

0.82(0.39–1.73)

0.00c

0.60

0.84(0.69–1.02)

0.00c

0.08

SCCHN

4

1237/1340

2.46(1.08–5.61)

0.50

0.03

2.20(0.30–16.22)

0.02

0.44

2.50(0.76–8.28)

0.25

0.13

0.84(0.40–1.75)

0.00c

0.64

CC

4

753/720

0.92(0.08–10.55)

0.00c

0.95

0.65(0.05–8.08)

0.00c

0.74

0.79(0.06–10.16)

0.00c

0.85

1.12(0.53–2.35)

0.00c

0.77

OC

5

2001/2420

0.42(0.10–1.78)

0.0007

0.24

0.41(0.06–2.67)

0.00c

0.35

0.40(0.07–2.18)

0.00c

0.29

0.80(0.62–1.03)

0.07

0.09

AL

9

2845/4027

0.82(0.49–1.39)

0.26

0.47

1.00(0.59–2.08)

0.29

0.99

0.85(0.50–1.44)

0.25

0.60

0.82(0.63–1.07)

0.002

0.14

Source of controls

HCC

13

3409/4126

0.77(0.30–1.98)

0.00c

0.58

0.79(0.24–2.60)

0.00c

0.70

0.74(0.26–2.13)

0.00c

0.58

0.82(0.60–1.12)

0.00c

0.20

PCC

9

3427/4381

0.93(0.53–1.62)

0.87

0.79

1.14(0.64–2.02)

0.87

0.66

0.95(0.54–1.67)

0.88

0.87

0.88(0.71–1.09)

0.01

0.25

Ethnicity

Asian

3

1170/1866

0.92(0.27–3.19)

0.01

0.90

0.98(0.28–3.40)

0.01

0.97

0.94(0.27–3.26)

0.009

0.92

0.94(0.77–1.14)

0.64

0.52

Caucasian

18

5616/6611

0.80(0.36–1.79)

0.00c

0.59

0.86(0.31–2.38)

0.00c

0.77

0.79(0.32–1.95)

0.00c

0.61

0.83(0.65–1.05)

0.00c

0.13

African

1

50/30

0.75(0.06–8.70)

 

0.82

1.50(0.10–23.07)

 

0.77

0.83(0.07–9.54)

 

0.88

0.55(0.16–1.90)

 

0.34

aNumber of studies.

bP value of Q-test for heterogeneity test.

cFixed-effects model was used when P value for heterogeneity test <0.10, otherwise, random-effects model was used.

SCCHN: squamous cell carcinoma of the head and neck; CC: colorectal cancer; OC: ovarian cancer; AL: acute leukaemia.

https://static-content.springer.com/image/art%3A10.1186%2F1746-1596-9-18/MediaObjects/13000_2013_Article_923_Fig2_HTML.jpg
Figure 2

The association between RAD51 135G/C polymorphism and the four common cancers risk in the subgroup analysis by cancer type (GG vs. CC).

Test of heterogeneity

For the comprehensive analysis, the I2 showed a stable variation under all comparisons (G/G vs. C/C: P < 0.00001, I2 = 81%; G/C vs. C/C: P < 0.00001, I2 = 89%; G/G + G/C vs. C/C: P < 0.00001, I2 = 88%; G/G vs. G/C + C/C: P < 0.00001, I2 = 78%). In the subgroup analyses of SCHNN and acute leukaemia, the I2 showed a low or moderate variation under all comparisons. In the subgroup analyses of colorectal cancer and ovarian cancer, under most comparisons, the moderate heterogeneity was detected. For source of controls, there was no significant heterogeneity under all comparisons of population-based case-control (PCC), except for heterozygous and dominant model comparisons (G/C vs. C/C: P < 0.00001, I2 = 93%; G/G + G/C vs. C/C: P < 0.00001, I2 = 92%) in hospital-based case-control (HCC). P value for heterogeneity was not significant under all comparisons in the subgroup analyses of Asian population, but in Caucasian group, there were high degree heterogeneity under heterozygous and dominant model comparisons (G/C vs. C/C: P < 0.00001, I2 = 90%; G/G + G/C vs. C/C: P < 0.00001, I2 = 89%).

Sensitivity analysis

Sensitivity analyses were performed to assess the stability of the results in this meta-analysis. Statistically similar data were obtained after sequentially excluding each study, indicating that our results were statistically reliable.

Publication bias

Begg’s funnel plot and Egger’s test were used to assess the publication bias of included studies. Publication bias was not observed in Begg’s funnel plot. The shape of the funnel plots showed to be symmetrical (G/G vs. C/C) and the Egger’s test did not show any evidence of publication bias (P = 0.248 for G/G vs. C/C) (Figure 3). These data indicate that there is no significant publication bias in this meta-analysis.
https://static-content.springer.com/image/art%3A10.1186%2F1746-1596-9-18/MediaObjects/13000_2013_Article_923_Fig3_HTML.jpg
Figure 3

Begg’s funnel plot for publication bias in selection of studies on RAD51 135G/C polymorphism (GG vs. CC; P for bias = 0.248).

Discussion

The RAD51 protein encoding by RAD51 gene is essential for the repair of DNA damage. A number of original studies have reported the association between RAD51 135G/C polymorphism and the risk of cancer with inconclusive results, These inconsistent results are possibly because of a small effect of the polymorphism on cancers risk or the relatively low statistical power of the published studies. To better understanding of this association,a meta-analysis, which potentially investigates a large number of individuals and could estimate the effect of a genetic factor on the risk of cancers, was needed to provid a quantitative approach for combining the results of various studies with the same topic, and for estimating and explaining their diversity [44, 45]. We performed a meta-analysis including 6836 cases and 8507 controls from 22 case-control studies to evaluate the association between RAD51 135G/C polymorphism and risk of SCCHN, colorectal cancer, ovarian cancer and acute leukaemia.

The overall population analysis showed no significant association between RAD51 135G/C polymorphism and risk of SCCHN, colorectal cancer, ovarian cancer and acute leukaemia in any genetic model. However, in the subgroup analysis by cancer type, we found that the 135G/C polymorphism of the RAD51 gene was associated with a significantly increased SCCHN risk. There was an aggregated OR of 2.46 (95% CI = 1.08-5.61) for increased SCCHN susceptibility under homozygote comparison. This indicates that the RAD51 135G/C polymorphism may contribute to pathogenesis of SCCHN. GG genotype has been reported to enhance RAD51 gene transcription activity [8], individuals with GG genotype may be more likely to develop SCCHN than those with CC or GC genotype. No associations were found between this polymorphism and the risk of colorectal cancer, ovarian cancer and acute leukaemia, which was consistent with previous reports [22, 23, 2729, 32, 36].

Heterogeneity is one of the important issues in performing a meta-analysis. In the present meta-analysis, heterogeneity was found in almost all comparisons. Using random-effect models and the stratified analyses by cancer type, sources of control and ethnicity, the heterogeneity was significantly decreased in most of the comparisons. The sensitivity analysis did not alter the results of our meta-analysis, indicating the results are stable. Meanwhile, the publication bias for the association between RAD51 135G/C polymorphism and the risk of the four types of cancers were not detected.

The present meta-analysis has some limitations. First, the control subjects were not uniformly defined. Selection bias and classification bias were possible because the included controls may have other different risks of developing cancers. Second, in the subgroup analyses, the sample sizes of Asian and African population were relatively small, not having enough statistical power to explore the real association. Third, cancer is a multi-factorial disease, our meta-analysis was based on unadjusted estimates.

In conclusion, the GG genotype of RAD51 135G/C was associated with a significantly increased risk of SCCHN. However, there was no significant association between this polymorphism and colorectal cancer, ovarian cancer or acute leukaemia susceptibility.

Declarations

Funding

This study was supported by National Natural Science Foundation of China Grant 81170022, and National Key Technology R&D Program of the 12th Five-year Development Plan 2012BAI05B01.

Authors’ Affiliations

(1)
Department of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
(2)
Key Laboratory of Respiratory Diseases, Ministry of Health

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