Oncotarget

Meta-Analysis:

Association of three promoter polymorphisms in interleukin-10 gene with cancer susceptibility in the Chinese population: a meta-analysis

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Oncotarget. 2017; 8:62382-62399. https://doi.org/10.18632/oncotarget.18220

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Ping Wang, Junling An, Yanfeng Zhu, Xuedong Wan, Hongzhen Zhang, Shoumin Xi _ and Sanqiang Li

Abstract

Ping Wang1, Junling An1, Yanfeng Zhu1, Xuedong Wan1, Hongzhen Zhang1, Shoumin Xi1 and Sanqiang Li2

1The Key Laboratory of Pharmacology and Medical Molecular Biology, Medical College, Henan University of Science and Technology, Luoyang 471023, Henan, China

2The Molecular Medicine Key Laboratory of Liver Injury and Repair, Medical College, Henan University of Science and Technology, Luoyang 471023, Henan, China

Correspondence to:

Shoumin Xi, email: xishoumin@haust.edu.cn

Sanqiang Li, email: lsqhkd@163.com

Keywords: interleukin-10, polymorphism, cancer, susceptibility, meta-analysis

Received: March 15, 2017     Accepted: April 14, 2017     Published: May 26, 2017

ABSTRACT

Numerous studies have examined the associations of three promoter polymorphisms (-1082A/G, -819T/C and -592A/C) in IL-10 gene with cancer susceptibility in the Chinese population, but the results remain inconclusive. To gain a more precise estimation of this potential association, we conducted the current meta-analysis based on 53 articles, including 26 studies with 4,901 cases and 6,426 controls for the -1082A/G polymorphism, 33 studies with 6,717 cases and 8,550 controls for the -819T/C polymorphism, and 42 studies with 9,934 cases and 13,169 controls for the -592A/C polymorphism. Pooled results indicated that the three promoter polymorphisms in IL-10 gene were significantly associated with an increased overall cancer risk in the Chinese population. Stratification analysis showed that the association was more pronounced for hepatocellular carcinoma and low quality studies for the -1082A/G polymorphism, lung cancer and oral cancer for the -819T/C polymorphism. However, the -592A/C polymorphism was associated with a statistically significant increased risk for lung cancer, oral cancer, hospital-based studies and low quality studies, but a decreased risk for colorectal cancer. We further investigated the significant results using the false-positive report probability (FPRP) test. Interestingly, FPRP test results revealed that only IL-10 -1082A/G polymorphism was truly associated with an increased overall cancer risk. In the subgroup analysis, only the low quality studies, lung cancer and colorectal cancer remained significant at the prior level of 0.1. Although this association needs further confirmation by considering large studies, this meta-analysis suggested an association between IL-10 gene polymorphisms and cancer risk in the Chinese population.


INTRODUCTION

Cancer is still a global public health problem. According to the GLOBOCAN estimates, about 14.1 million new cancer cases and 8.2 million deaths occurred in 2012 worldwide [1]. In China, cancer has become the leading cause of death since 2010, with an estimate of 4292,000 new cancer cases and 2814,000 cancer deaths in 2015 [2]. As a multifactorial disease, it involves both genetic and environmental factors [3]. Accumulating evidence has indicated that inflammation plays a vital role in cancer development [46], and approximately 20% of all cancers are associated with chronic inflammation [7].

Interleukin-10 (IL-10) is an anti-inflammatory cytokine with both immunosuppressive and immunostimulatory activities [8]. Although the relationship between IL-10 and cancer has been extensively studied, the exact role of IL-10 in cancer is still elusive, since IL-10 have both cancer-promoting and -inhibiting properties [9, 10]. In view of these properties, we hypothesized that IL-10 gene polymorphisms could influence cancer susceptibility.

The IL-10 gene is located on chromosome 1q31-32, and is composed of five exons and four introns. IL-10 gene promoter region is highly polymorphic, and three promoter single nucleotide polymorphisms (SNPs) such as -1082A/G (rs1800896), -819T/C (rs1800871) and -592A/C (rs1800872) have been reported to regulate IL-10 expression [11, 12] and alter the susceptibility to various types of cancers [1316]. In the Chinese population, numerous case-control studies were performed to investigate the role of IL-10 -1082A/G, -819T/C and -592A/C polymorphisms in cancer risk. However, the results remain inconclusive. Hence, we performed the present meta-analysis to investigate the association between three polymorphisms in IL-10 gene and cancer susceptibility in the Chinese population.

RESULTS

Study characteristics

As shown in Figure 1, 1,596 published records were initially retrieved from PubMed, Embase, Chinese National Knowledge Infrastructure (CNKI) and Wanfang database, and 14 more articles were identified by checking the references in the retrieved publications. After reviewing of the titles and abstracts, 1,535 articles were excluded, leaving only 75 articles for further assessment. Among them, we excluded one study [17] that was covered by another included publication [18], five case-only studies [1923], five lacking detailed data for further analysis [2428], and eleven that were considering the deviation from the Hardy-Weinberg equilibrium (HWE) [2939]. Ultimately, 53 articles were included in the final meta-analysis. Of these 53 articles, 24 articles [4063] include 26 studies examining IL-10 -1082A/G polymorphism, 28 articles [18, 42, 43, 45, 47, 49, 52, 53, 57-61, 63-77] include 33 studies examining the -819T/C polymorphism, and 39 articles [18, 42, 43, 45, 47, 52, 53, 56-67, 69, 70, 73-76, 78-91] include 42 studies examining the -592A/C polymorphism (Table 1). Of the 53 articles, two publications [18, 45] with three cancer types were considered as three studies and one publication [65] with two cancer types were also considered as two studies.

Flow diagram of the study selection process.

Figure 1: Flow diagram of the study selection process.

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

Surname [ref]

Year

Cancer type

Control source

Genotype method

Case

Control

MAF

HWE

Score

11

12

22

All

11

12

22

All

-1082A/G polymorphism

Wu [40]

2002

Gastric

HB

Sequencing

135

14

1

150

208

11

1

220

0.03

0.057

6

Heneghan [41] a

2003

HCC

PB

Probe

86

12

0

98

90

7

0

97

0.04

0.712

10

Shih [42]a

2005

Lung

HB

PCR-RFLP

115

39

0

154

194

11

0

205

0.03

0.693

8

Wei [43]

2007

NPC

HB

PCR-RFLP

123

61

14

198

167

38

5

210

0.11

0.124

8

Bai [44]b

2008

Gastric

HB

PCR-RFLP

89

22 (AG+GG)

111

104

7 (AG+GG)

111

NA

NA

7

Hsing [45]

2008

Gallbladder

PB

Taqman

231

23

1

255

624

99

7

730

0.08

0.173

12

Hsing [45] a

2008

EHBD

PB

Taqman

107

18

0

125

664

108

7

779

0.08

0.270

12

Hsing [45]a

2008

AV

PB

Taqman

38

9

0

47

664

108

7

779

0.08

0.270

12

Hao [46] b

2009

Lung

PB

Taqman

36

7 (AG+GG)

43

46

6 (AG+GG)

52

NA

NA

7

Xiao [47] a

2009

Gastric

HB

PCR-RFLP

176

41

3

220

593

31

0

624

0.03

0.525

9

Kong [48]

2010

Breast

HB

PCR-RFLP

285

29

1

315

285

35

2

322

0.06

0.422

9

Liu [49]

2010

HCC

HB

Taqman

131

35

4

170

160

24

3

187

0.08

0.075

5

Niu [50] b

2011

Prostate

PB

Sequencing

24

74 (AG+GG)

98

42

46 (AG+GG)

88

NA

NA

9

Wang [51]

2011

Cervical

PB

PCR-SSP

77

85

24

186

103

76

21

200

0.30

0.222

8

He [52] a

2012

Gastric

HB

PCR-RFLP

154

42

0

196

194

54

0

248

0.11

0.055

9

Chang [53] a

2013

HN

HB

Taqman

289

23

1

313

268

27

0

295

0.05

0.410

10

Chen [54]

2013

Bladder

HB

AS-PCR

374

25

1

400

350

48

2

400

0.07

0.799

10

Du [55]

2013

Esophageal

HB

PCR

95

20

3

118

103

15

1

119

0.07

0.587

8

Pan [56]

2013

Gastric

HB

MassARRAY

263

41

4

308

264

41

3

308

0.08

0.329

9

Cheng [57] a

2015

NTCL

HB

PCR-LDR

101

24

0

125

237

60

3

300

0.11

0.710

10

Fei [58]

2015

AML

HB

PCR-RFLP

75

70

22

167

159

134

35

328

0.31

0.398

8

Hsu [59] a

2015

Oral

HB

PCR-SSP

130

14

1

145

96

16

0

112

0.07

0.416

7

Yang [60]

2015

Esophageal

HB

MassARRAY

41

106

99

246

46

204

242

492

0.30

0.751

9

Bai [61]

2016

Cervical

HB

PCR-RFLP

74

75

16

165

80

72

13

165

0.30

0.563

8

Cai [62] a

2016

Colorectal

HB

MassARRAY

323

50

2

375

343

39

0

382

0.05

0.293

9

Peng [63]

2016

HCC

PB

PCR-RFLP

83

74

16

173

96

74

12

182

0.27

0.653

10

-819T/C polymorphism

Wu [64]

2003

Gastric

HB

Sequencing

88

105

27

220

127

83

20

230

0.27

0.231

9

Savage [65]

2004

Gastric

PB

SBE

37

38

9

84

170

163

49

382

0.34

0.315

11

Savage [65]

2004

Esophageal

PB

SBE

53

46

17

116

170

163

49

382

0.34

0.315

12

Shih [42]

2005

Lung

HB

PCR-RFLP

66

58

30

154

104

86

15

205

0.28

0.627

8

Wei [43]

2007

NPC

HB

PCR-RFLP

82

81

35

198

94

92

24

210

0.33

0.836

8

Hsing [45]

2008

Gallbladder

PB

Taqman

122

92

23

237

311

335

82

728

0.34

0.564

12

Hsing [45]

2008

EHBD

PB

Taqman

55

52

17

124

334

353

90

777

0.34

0.823

12

Hsing [45]

2008

AV

PB

Taqman

20

6

21

47

334

353

90

777

0.34

0.823

12

Yao [66]

2008

Oral

HB

PCR-RFLP

113

120

47

280

129

134

37

300

0.35

0.809

10

Xiao [47]

2009

Gastric

HB

PCR-RFLP

100

100

20

220

272

283

69

624

0.34

0.719

9

Liu [67]

2010

Prostate

HB

PCR-RFLP

120

108

34

262

132

110

28

270

0.31

0.477

10

Liu [49]

2010

HCC

HB

Taqman

79

73

18

170

75

92

20

187

0.35

0.292

5

Oh [18]

2010

Esophageal

PB

Taqman

90

79

27

196

179

158

42

379

0.32

0.426

13

Oh [18]

2010

Gastric

PB

Taqman

81

87

20

188

179

158

42

379

0.32

0.426

13

Oh [18]

2010

HCC

PB

Taqman

91

70

25

186

179

158

42

379

0.32

0.426

13

Su [68]

2010

Gastric

HB

PCR-RFLP

18

21

4

43

51

43

6

100

0.28

0.433

6

Bei [69]

2011

HCC

HB

Taqman

44

247

298

589

51

240

306

597

0.29

0.686

12

Liu [70]

2011

Gastric

HB

PCR-RFLP

99

96

39

234

109

106

28

243

0.33

0.773

7

He [52]

2012

Gastric

HB

PCR-RFLP

82

96

18

196

92

128

28

248

0.37

0.095

9

He [71]

2012

Breast

HB

MALDI-TOF MS

177

141

29

347

229

223

44

496

0.31

0.322

10

Yuan [72]

2012

Gastric

HB

MassARRAY

108

129

42

279

142

120

34

296

0.32

0.266

9

Zeng [73]

2012

Gastric

PB

SBE

60

80

11

151

78

65

10

153

0.28

0.467

10

Chang [53]

2013

HN

HB

Taqman

132

153

28

313

136

130

29

295

0.32

0.798

10

Yao [74]

2013

AML

HB

PCR-RFLP

68

38

9

115

56

63

18

137

0.36

0.966

9

Cheng [57]

2015

NTCL

HB

PCR-LDR

57

59

9

125

136

125

39

300

0.34

0.230

10

Fei [58]

2015

AML

HB

PCR-RFLP

57

72

38

167

137

137

54

328

0.37

0.052

8

Hsu [59]

2015

Oral

HB

PCR-SSP

33

101

11

145

53

51

8

112

0.30

0.363

7

Yang [60]

2015

Esophageal

HB

MassARRAY

101

105

40

246

219

203

69

492

0.35

0.051

9

Zhang [75]

2015

Lung

HB

PCR-RFLP

108

135

87

330

145

144

47

336

0.35

0.247

8

Bai [61]

2016

Cervical

HB

PCR-RFLP

44

76

45

165

28

73

64

165

0.39

0.362

8

Cui [76]

2016

Osteosarcoma

HB

PCR-RFLP

34

120

106

260

43

118

99

260

0.39

0.438

10

Li [77]

2016

Gastric

HB

PCR-RFLP

36

83

38

157

36

127

85

248

0.40

0.300

6

Peng [63]

2016

HCC

PB

PCR-RFLP

74

77

22

173

86

78

17

181

0.31

0.910

10

-592A/C polymorphism

Wu [64]

2003

Gastric

HB

Sequencing

88

105

27

220

127

83

20

230

0.27

0.231

9

Savage [65]

2004

Gastric

PB

SBE

9

39

36

84

49

166

171

386

0.34

0.383

11

Savage [65]

2004

Esophageal

PB

SBE

17

51

51

119

49

166

171

386

0.34

0.383

12

Shih [42]

2005

Lung

HB

PCR-RFLP

66

70

18

154

116

76

13

205

0.25

0.907

8

Tseng [78]

2006

HCC

HB

MALDI-TOF MS

93

84

31

208

90

75

19

184

0.31

0.567

7

Wei [43]

2007

NPC

HB

PCR-RFLP

82

81

35

198

94

92

24

210

0.33

0.836

8

Hsing [45]

2008

Gallbladder

PB

Taqman

121

91

23

235

318

334

82

734

0.34

0.684

12

Yao [66]

2008

Oral

HB

PCR-RFLP

113

120

47

280

129

134

37

300

0.35

0.809

10

Xiao [47]

2009

Gastric

HB

PCR-RFLP

100

100

20

220

272

283

69

624

0.34

0.719

9

Liu [67]

2010

Prostate

HB

PCR-RFLP

120

108

34

262

132

110

28

270

0.31

0.477

10

Oh [18]

2010

Esophageal

PB

SNPlex

81

72

26

179

167

159

36

362

0.32

0.837

13

Oh [18]

2010

Gastric

PB

SNPlex

77

81

20

178

167

159

36

362

0.32

0.837

13

Oh [18]

2010

HCC

PB

SNPlex

82

68

19

169

167

159

36

362

0.32

0.837

13

Xiong [79]

2010

Cervical

HB

PCR-RFLP

35

23

12

70

51

44

13

108

0.32

0.467

7

Bei [69]

2011

HCC

HB

Taqman

42

248

299

589

49

244

304

597

0.29

0.997

12

Liang [80]

2011

Lung

HB

PCR-RFLP

69

36

11

116

69

44

7

120

0.24

0.997

9

Liu [70]

2011

Gastric

HB

PCR-RFLP

99

96

39

234

109

106

28

243

0.33

0.773

7

Yu [81]

2011

Cervical

PB

PCR-RFLP

59

37

7

103

52

44

19

115

0.36

0.075

10

He [52]

2012

Gastric

HB

PCR-RFLP

82

96

18

196

92

128

28

248

0.37

0.095

9

Zeng [73]

2012

Gastric

PB

SBE

59

77

15

151

80

66

7

153

0.26

0.148

10

Zhang [82]

2012

NHL

PB

Taqman

226

228

60

514

269

235

53

557

0.31

0.872

14

Chang [53]

2013

HN

HB

Taqman

134

152

27

313

137

129

29

295

0.32

0.864

10

Pan [56]

2013

Gastric

HB

MassARRAY

144

128

36

308

142

135

31

308

0.32

0.896

9

Sun [83]

2013

Esophageal

HB

SNPscan

162

163

31

356

191

141

33

365

0.28

0.347

10

Tsai [84]

2013

NPC

HB

PCR-RFLP

93

66

17

176

261

205

56

522

0.30

0.103

9

Yao [74]

2013

AML

HB

PCR-RFLP

68

38

9

115

56

63

18

137

0.36

0.966

9

Bei [85]

2014

HCC

HB

Taqman

356

312

52

720

392

313

79

784

0.30

0.160

11

Hsia [86]

2014

Lung

HB

PCR-RFLP

173

145

40

358

368

277

71

716

0.29

0.080

12

Kuo [87]

2014

Gastric

HB

PCR-RFLP

186

134

38

358

180

141

37

358

0.30

0.235

9

Yu [88]

2014

Colorectal

PB

PCR-RFLP

153

114

31

298

118

135

38

291

0.36

0.950

13

Cheng [57]

2015

NTCL

HB

PCR-LDR

57

59

9

125

138

124

38

300

0.33

0.225

10

Fei [58]

2015

AML

HB

PCR-RFLP

54

74

39

167

126

142

59

328

0.40

0.091

8

Hsu [59]

2015

Oral

HB

PCR-SSP

33

101

11

145

53

51

8

112

0.30

0.363

7

Yang [60]

2015

Esophageal

HB

MassARRAY

85

116

45

246

185

228

79

492

0.39

0.534

9

Yin [89]

2015

Gastric

HB

SNPscan

112

96

20

228

235

184

42

461

0.29

0.491

10

Zhang [75]

2015

Lung

HB

PCR-RFLP

64

156

110

330

85

176

75

336

0.49

0.374

8

Bai [61]

2016

Cervical

HB

PCR-RFLP

63

82

20

165

70

80

15

165

0.33

0.243

8

Cai [62]

2016

Colorectal

HB

MassARRAY

221

128

26

375

184

158

40

382

0.31

0.485

9

Chang [90]

2016

RCC

HB

PCR-RFLP

61

27

4

92

371

185

24

580

0.20

0.877

9

Cui [76]

2016

Osteosarcoma

HB

PCR-RFLP

108

125

27

260

100

128

32

260

0.37

0.359

10

Peng [63]

2016

HCC

PB

PCR-RFLP

57

81

35

173

79

81

22

182

0.34

0.860

10

Ma [91]

2016

Gastric

HB

PCR-RFLP

67

63

17

147

71

67

12

150

0.30

0.486

8

MAF: minor allele frequency; HWE: Hardy-Weinberg equilibrium; HB: hospital based; PB: population based; NA: not applicable; HCC: hepatocellular carcinoma; NPC: nasopharyngeal carcinoma; EHBD: extrahepatic bile duct; AV: ampulla of vater; HN: head and neck; NTCL: NK/T-cell lymphoma; AML: acute myeloid leukemia; NHL: non-Hodgkin’s lymphoma; RCC: renal cell carcinoma; PCR-RFLP: polymorphism chain reaction restriction fragment length polymorphism; PCR-SSP: polymerase chain reaction sequence-specific primer; AS-PCR: allele-specific polymorphism chain reaction; PCR-LDR: polymorphism chain reaction-ligase detection reaction; SBE: single base extension; MALDI-TOF MS: matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry.

a Heneghan [41], Shih [42], Hsing [44] (extrahepatic bile duct cancer and ampulla of vater cancer), Xiao [47], He [52], Chang [53], Cheng [57], Hsu [59] and Cai [62] were only calculated for the heterozygous model, dominant model and allele comparison for the IL-10 -1082A/G polymorphism, and the number of GG genotype was zero.

b Bai [44], Hao [46] and Niu [50] were only calculated for the dominant model.

For the studies assessing three polymorphisms (-1082A/G, -819T/C and -592A/C) [32, 37], two (-1082A/G and -592A/C) [31], only one such as -1082A/G [29, 30, 33-35, 38] or -819T/C [36, 39] polymorphism and cancer risk but no other IL-10 gene polymorphisms, the genotypes distribution in the controls were deviated from HWE, thus, these studies were excluded in the final analysis. Sixteen studies were also deviated from HWE, but the genotypes distribution in the controls of eight studies [18, 64-67, 70, 73, 76] were consistent with that expected from the HWE for both -819T/C and -592A/C polymorphisms, five [81, 84, 86, 87, 90] for the -592A/C polymorphism and three [41, 48, 54] for the -1082A/G polymorphism, thus, these studies were included in the final analysis. For those studies [18, 45, 65] with the same control subjects, the control numbers were calculated once in the total number. Overall, 26 studies with 4,901 cases and 6,426 controls for the -1082A/G polymorphism, 33 studies with 6,717 cases and 8,550 controls for the -819T/C polymorphism, and 42 studies with 9,934 cases and 13,169 controls for the -592A/C polymorphism were considered in this meta-analysis. Sample sizes for cases of the included studies ranged from 43 to 400 for the -1082A/G polymorphism, 43 to 589 for the -819T/C polymorphism, and 70 to 720 for the -592A/C polymorphism.

As regards the -1082A/G polymorphism, five studies focused on gastric cancer [40, 44, 47, 52, 56], three on hepatocellular carcinoma [41, 49, 63], two studies for each of the following cancer types, such as lung cancer [42, 46], cervical cancer [51, 61] and esophageal cancer [55, 60], and the other cancer types with one study per each cancer type. As regards the -819T/C polymorphism, 10 studies focused on gastric cancer [18, 47, 52, 64, 65, 68, 70, 72, 73, 77], four on hepatocellular carcinoma [18, 49, 63, 69], three on esophageal cancer [18, 60, 65], two studies for each of the following cancer types, such as lung cancer [42, 75], oral cancer [59, 66] and acute myeloid leukemia [58, 74], and the other cancer types with one study per each cancer type. As regards the -592A/C polymorphism, 11 studies focused on gastric cancer [18, 47, 52, 56, 64, 65, 70, 73, 87, 89, 91], five on hepatocellular carcinoma [18, 63, 69, 78, 85], four studies for each of the following cancer types, such as lung cancer [42, 75, 80, 86] and esophageal cancer [18, 60, 65, 83], three on cervical cancer [61, 79, 81], two studies for each of the following cancer types, such as nasopharyngeal carcinoma [43, 84], oral cancer [59, 66], acute myeloid leukemia [58, 74] and colorectal cancer [62, 88], and the other cancer types with one study per each cancer type. Among all studies, 18 were hospital-based and eight were population-based associated to the -1082A/G polymorphism, 23 were hospital-based and 10 were population-based associated to the -819T/C polymorphism, 31 were hospital-based and 11 were population-based associated to the -592A/C polymorphism. Furthermore, 18 studies were rated as low quality (quality score ≤ 9) and eight were considered as high quality (quality score > 9) for the -1082A/G polymorphism, 16 were low quality and 17 were high quality studies for the -819T/C polymorphism, 21 were low quality and 21 were high quality studies for the -592A/C polymorphism. Controls were matched for age and sex in most studies, and cases were mostly histologically confirmed.

Meta-analysis results

The main results regarding the association between IL-10 -1082A/G polymorphism and cancer risk are shown in Table 2 and Figure 2. A significant association was found between IL-10 -1082A/G polymorphism and overall cancer risk [dominant: odds ratio (OR) = 1.32, 95% confidence interval (CI) = 1.04-1.67, P < 0.001]. In the subgroup analysis, a statistically significant association was found for hepatocellular carcinoma (heterozygous: OR = 1.40, 95% CI = 1.01-1.94, P = 0.433; dominant: OR = 1.43, 95% CI = 1.04-1.95, P = 0.497 and allele comparison: OR = 1.35, 95% CI = 1.04-1.75, P = 0.480) and low quality studies (heterozygous: OR = 1.42, 95% CI = 1.05-1.91, P < 0.001; dominant: OR = 1.56, 95% CI = 1.17-2.08, P < 0.001 and allele comparison: OR = 1.43, 95% CI = 1.08-1.88, P < 0.001).

Table 2: Meta-analysis of the association between IL-10 polymorphisms and cancer risk

Variables

No. of studies

Sample size (case/controls)

Homozygous

Heterozygous

Recessive

Dominant

Allele comparison

OR (95% CI)

Phet

OR (95% CI)

Phet

OR (95% CI)

Phet

OR (95% CI)

Phet

OR (95% CI)

Phet

-1082A/G

GG vs. AA

AG vs. AA

GG vs.(AA+AG)

(AG+GG) vs. AA

G vs.A

All

26

4,901/6,426

1.21 (0.80-1.85)

0.025

1.22 (0.97-1.54)

<0.001

1.12 (0.84-1.48)

0.242

1.32 (1.04-1.67)

<0.001

1.22 (0.99-1.51)

<0.001

Cancer type

Gastric

5

985/1,511

1.38 (0.37-5.20)

0.930

1.70 (0.79-3.66)

<0.001

1.37 (0.36-5.13)

0.953

1.97 (0.97-3.99)

<0.001

1.72 (0.79-3.71)

<0.001

HCC

3

441/466

1.56 (0.77-3.18)

0.950

1.40 (1.01-1.94)

0.433

1.45 (0.73-2.90)

0.978

1.43 (1.04-1.95)

0.497

1.35 (1.04-1.75)

0.480

Lung a

2

197/257

NA

NA

NA

NA

NA

NA

3.24 (0.84-12.54)

0.047

NA

NA

Cervical

2

351/365

1.45 (0.87-2.40)

0.792

1.31 (0.96-1.79)

0.371

1.26 (0.78-2.04)

0.991

1.33 (0.99-1.79)

0.386

1.24 (0.99-1.55)

0.490

Esophageal

2

364/611

0.88 (0.14-5.40)

0.099

0.88 (0.36-2.14)

0.041

0.94 (0.29-3.01)

0.205

0.87 (0.29-2.56)

0.009

1.00 (0.44-2.26)

0.015

Others

12

2,563/3,216

1.30 (0.59-2.85)

0.168

0.96 (0.74-1.25)

0.002

1.30 (0.68-2.46)

0.280

1.05 (0.78-1.41)

<0.001

0.97 (0.74-1.27)

<0.001

Source of control

PB

8

1,025/1,398

1.42 (0.87-2.33)

0.454

1.13 (0.84-1.53)

0.114

1.25 (0.78-2.01)

0.538

1.29 (0.92-1.80)

0.013

1.07 (0.82-1.41)

0.078

HB

18

3,876/5,028

1.20 (0.69-2.09)

0.018

1.25 (0.93-1.68)

<0.001

1.13 (0.78-1.64)

0.183

1.33 (0.98-1.80)

<0.001

1.27 (0.97-1.68)

<0.001

Score

Low

18

3,365/4,373

1.29 (0.78-2.12)

0.012

1.42 (1.05-1.91)

<0.001

1.16 (0.83-1.63)

0.160

1.56 (1.17-2.08)

<0.001

1.43 (1.08-1.88)

<0.001

High

8

1,536/2,053

1.13 (0.52-2.48)

0.349

0.89 (0.68-1.17)

0.073

1.15 (0.57-2.31)

0.417

0.88 (0.67-1.67)

0.059

0.88 (0.68-1.14)

0.047

-819T/C

CC vs.TT

CT vs.TT

CC vs.(TT+CT)

(CT+CC) vs.TT

C vs.T

All

33

6,717/8,550

1.19 (1.00-1.41)

<0.001

1.04 (0.93-1.16)

<0.001

1.17 (1.00-1.36)

<0.001

1.08 (0.97-1.20)

<0.001

1.08 (1.00-1.18)

<0.001

Cancer type

Gastric

10

1,772/2,142

1.08 (0.79-1.47)

0.021

1.15 (0.95-1.38)

0.046

1.01 (0.81-1.27)

0.196

1.14 (0.93-1.40)

0.007

1.08 (0.92-1.27)

0.002

HCC

4

1,118/1,344

1.14 (0.86-1.51)

0.744

0.96 (0.78-1.19)

0.396

1.04 (0.86-1.26)

0.668

1.00 (0.82-1.22)

0.412

1.01 (0.90-1.15)

0.549

Esophageal

3

558/873

1.23 (0.90-1.67)

0.940

1.02 (0.82-1.27)

0.741

1.21 (0.91-1.61)

0.966

1.07 (0.87-1.31)

0.763

1.09 (0.94-1.27)

0.852

Lung

2

484/541

2.66 (1.84-3.84)

0.569

1.18 (0.90-1.56)

0.560

2.40 (1.71-3.37)

0.399

1.49 (1.16-1.92)

0.633

1.59 (1.33-1.91)

0.920

Oral

2

425/412

1.58 (1.01-2.46)

0.464

1.77 (0.58-5.37)

0.001

1.35 (0.89-2.06)

0.583

1.80 (0.67-4.82)

0.002

1.38 (0.94-2.02)

0.080

AML

2

282/465

0.87 (0.22-3.48)

0.006

0.80 (0.32-2.01)

0.007

0.98 (0.38-2.53)

0.046

0.82 (0.29-2.34)

0.001

0.88 (0.38-2.03)

<0.001

Others

10

2,078/2,773

1.08 (0.76-1.53)

<0.001

0.91 (0.76-1.09)

0.047

1.14 (0.79-1.65)

<0.001

0.95 (0.82-1.11)

0.117

1.10 (0.87-1.18)

0.001

Source of control

PB

10

1,502/1,872

1.24 (0.93-1.65)

0.035

0.96 (0.79-1.16)

0.035

1.31 (0.92-1.86)

<0.001

1.01 (0.88-1.16)

0.248

1.08 (0.95-1.24)

0.031

HB

23

5,215/6,678

1.17 (0.94-1.44)

<0.001

1.08 (0.95-1.22)

0.001

1.12 (0.95-1.33)

<0.001

1.10 (0.96-1.27)

<0.001

1.08 (0.97-1.20)

<0.001

Score

Low

16

3,039/4,160

1.21 (0.89-1.64)

<0.001

1.07 (0.89-1.29)

<0.001

1.18 (0.92-1.51)

<0.001

1.11 (0.91-1.36)

<0.001

1.10 (0.94-1.29)

<0.001

High

17

3,678/4,390

1.17 (0.98-1.39)

0.075

1.01 (0.89-1.13)

0.097

1.16 (0.95-1.42)

0.001

1.03 (0.94-1.12)

0.409

1.05 (0.97-1.14)

0.089

-592A/C

CC vs.AA

AC vs.AA

CC vs.(AA+AC)

(AC+CC) vs.AA

C vs.A

All

42

9,934/13,169

1.13 (1.00-1.28)

0.001

1.04 (0.96-1.13)

0.001

1.10 (0.99-1.21)

0.035

1.06 (0.97-1.15)

<0.001

1.05 (0.99-1.12)

<0.001

Cancer type

Gastric

11

2,324/2,775

1.18 (0.96-1.44)

0.289

1.08 (0.94-1.23)

0.200

1.11 (0.94-1.32)

0.562

1.10 (0.95-1.27)

0.093

1.08 (0.97-1.21)

0.080

HCC

5

1,859/2,109

1.20 (0.82-1.75)

0.032

1.09 (0.94-1.27)

0.650

1.10 (0.80-1.50)

0.039

1.09 (0.94-1.27)

0.373

1.08 (0.93-1.24)

0.094

Esophageal

4

900/1,243

1.18 (0.90-1.54)

0.637

1.13 (0.93-1.36)

0.399

1.11 (0.88-1.39)

0.498

1.15 (0.96-1.37)

0.582

1.10 (0.97-1.25)

0.702

Lung

4

958/1,377

1.64 (1.19-2.24)

0.301

1.17 (0.94-1.45)

0.285

1.52 (1.20-1.93)

0.402

1.27 (1.01-1.60)

0.198

1.27 (1.06-1.52)

0.149

Cervical

3

338/388

0.89 (0.35-2.24)

0.031

0.91 (0.67-1.25)

0.431

0.94 (0.41-2.19)

0.042

0.89 (0.60-1.32)

0.174

0.91 (0.60-1.38)

0.034

NPC

2

374/732

1.19 (0.62-2.31)

0.116

0.95 (0.72-1.25)

0.697

1.22 (0.66-2.25)

0.125

0.99 (0.77-1.29)

0.346

1.05 (0.78-1.42)

0.129

Oral

2

425/412

1.58 (1.01-2.46)

0.464

1.77 (0.58-5.37)

0.001

1.35 (0.89-2.06)

0.583

1.80 (0.67-4.82)

0.002

1.38 (0.94-2.02)

0.080

AML

2

282/465

0.84 (0.23-3.05)

0.011

0.79 (0.33-1.90)

0.010

0.95 (0.40-2.27)

0.064

0.80 (0.30-2.16)

0.002

0.86 (0.39-1.88)

0.001

Colorectal

2

673/673

0.58 (0.40-0.85)

0.694

0.66 (0.53-0.83)

0.882

0.70 (0.49-1.01)

0.599

0.65 (0.52-0.80)

0.994

0.72 (0.61-0.85)

0.750

Others

7

1,801/2,995

0.98 (0.77-1.24)

0.313

1.01 (0.86-1.17)

0.246

0.98 (0.80-1.21)

0.437

1.00 (0.86-1.16)

0.185

0.99 (0.88-1.11)

0.187

Source of control

PB

11

2,203/2,780

1.08 (0.82-1.43)

0.011

0.96 (0.82-1.13)

0.056

1.08 (0.89-1.33)

0.117

0.99 (0.82-1.18)

0.004

1.01 (0.87-1.16)

0.001

HB

31

7,731/10,389

1.14 (0.99-1.31)

0.009

1.07 (0.97-1.17)

0.004

1.10 (0.98-1.24)

0.054

1.09 (0.99-1.20)

<0.001

1.07 (1.00-1.15)

<0.001

Score

Low

21

4,240/6,041

1.23 (1.02-1.49)

0.012

1.03 (0.90-1.19)

<0.001

1.21 (1.05-1.40)

0.193

1.08 (0.93-1.25)

<0.001

1.09 (0.98-1.21)

<0.001

High

21

5,694/7,128

1.05 (0.89-1.23)

0.023

1.05 (0.96-1.15)

0.161

1.02 (0.89-1.16)

0.100

1.05 (0.95-1.15)

0.033

1.03 (0.95-1.11)

0.007

Het: heterogeneity; NA: not applicable; HCC: hepatocellular carcinoma; NPC: nasopharyngeal carcinoma; AML: acute myeloid leukemia; PB: population based; HB: hospital based.

a Lung cancer was only calculated for the dominant model.

Forest plot for overall cancer risk associated with the IL-10 -1082A/G polymorphism by a dominant model.

Figure 2: Forest plot for overall cancer risk associated with the IL-10 -1082A/G polymorphism by a dominant model. For each study, the estimated OR and its 95% CI are plotted with a box and a horizontal line. ◊, pooled ORs and its 95% CIs.

The overall results regarding the association between IL-10 -819T/C polymorphism and cancer risk are shown in Table 2. A significant association was found between IL-10 -819T/C polymorphism and overall cancer risk (homozygous: OR = 1.19, 95% CI = 1.00-1.41, P < 0.001; recessive: OR = 1.17, 95% CI = 1.00-1.36, P < 0.001 and allele comparison: OR = 1.08, 95% CI = 1.00-1.18, P < 0.001). In the subgroup analysis, a statistically significant association was found for lung cancer (homozygous: OR = 2.66, 95% CI = 1.84-3.84, P = 0.569; recessive: OR = 2.40, 95% CI = 1.71-3.37, P = 0.399; dominant: OR = 1.49, 95% CI = 1.16-1.92, P = 0.633 and allele comparison: OR = 1.59, 95% CI = 1.33-1.91, P = 0.920) and oral cancer (homozygous: OR = 1.58, 95% CI = 1.01-2.46, P = 0.464).

The detailed results regarding the association between IL-10 -592A/C polymorphism and cancer risk are shown in Table 2. A significant association was found between IL-10 -592A/C polymorphism and increased overall cancer risk (homozygous: OR = 1.13, 95% CI = 1.00-1.28, P = 0.001). In the subgroup analysis, a statistically significant increased risk was found for lung cancer (homozygous: OR = 1.64, 95% CI = 1.19-2.24, P = 0.301; recessive: OR = 1.52, 95% CI = 1.20-1.93, P = 0.402; dominant: OR = 1.27, 95% CI = 1.01-1.60, P = 0.198 and allele comparison: OR = 1.27, 95% CI = 1.06-1.52, P = 0.149), oral cancer (homozygous: OR = 1.58, 95% CI = 1.01-2.46, P = 0.464), hospital-based studies (allele comparison: OR = 1.07, 95% CI = 1.00-1.15, P < 0.001) and low quality studies (homozygous: OR = 1.23, 95% CI = 1.02-1.49, P = 0.012 and recessive: OR = 1.21, 95% CI = 1.05-1.40, P = 0.193). In contrast, a significantly decreased risk was observed for colorectal cancer (homozygous: OR = 0.58, 95% CI = 0.40-0.85, P = 0.694; heterozygous: OR = 0.66, 95% CI = 0.53-0.83, P = 0.882; dominant: OR = 0.65, 95% CI = 0.52-0.80, P = 0.994 and allele comparison: OR = 0.72, 95% CI = 0.61-0.85, P = 0.750).

Heterogeneity and sensitivity analysis

Substantial heterogeneities were found among all studies regarding IL-10 -1082A/G polymorphism and overall cancer risk (homozygous: P = 0.025; heterozygous: P < 0.001; dominant: P < 0.001 and allele comparison: P < 0.001), but not under the recessive model (P = 0.242) (Table 2). Considerable heterogeneities were also observed for the -819T/C (all P < 0.001) and -592A/C (homozygous: P = 0.001; heterozygous: P = 0.001; recessive: P = 0.035; dominant: P < 0.001 and allele comparison: P < 0.001) polymorphisms. Therefore, the random-effect model was used to generate wider CIs. Sensitivity analysis was conducted and the results indicated that each individual study did not influence the pooled ORs obviously (data not shown).

Publication bias

The funnel plot was symmetric for the -1082A/G (Figure 3), -819T/C and -592A/C polymorphisms, indicating no presence of publication bias, which was further supported by the Egger’s test for the -1082A/G polymorphism (homozygous: P = 0.428; heterozygous: P = 0.395; recessive: P = 0.168; dominant: P = 0.223 and allele comparison: P = 0.179), -819T/C polymorphism (homozygous: P = 0.589; heterozygous: P = 0.777; recessive: P = 0.616; dominant: P = 0.797 and allele comparison: P = 0.576), and -592A/C polymorphism (homozygous: P = 0.727; heterozygous: P = 0.763; recessive: P = 0.748; dominant: P = 0.474 and allele comparison: P = 0.677).

Begg&#x2019;s funnel plot for the IL-10 -1082A/G polymorphism and overall cancer risk by a dominant model.

Figure 3: Begg’s funnel plot for the IL-10 -1082A/G polymorphism and overall cancer risk by a dominant model.

False-positive report probability (FPRP) test analysis

The significant findings were assessed using the FPRP test and the results are shown in Table 3. With a prior probability of 0.1, assuming that the OR for a specific genotype was 0.67/1.50 (protection/risk), with statistical power of 0.857, the FPRP value was 0.179 for the -1082A/G polymorphism and cancer risk under the dominant model, and a positive association was also found for low quality studies (dominant: FPRP = 0.053 and allele comparison: FPRP = 0.129). As regards the -819T/C polymorphism, a positive association was found for lung cancer (homozygous: FPRP = 0.001; recessive: FPRP = 0.001; dominant: FPRP = 0.034 and allele comparison: FPRP < 0.001). As regards the -592A/C polymorphism, noteworthy findings were observed for lung cancer (homozygous: FPRP = 0.055; recessive: FPRP = 0.011 and allele comparison: FPRP = 0.078), colorectal cancer (homozygous: FPRP = 0.165; heterozygous: FPRP = 0.007; dominant: FPRP = 0.001 and allele comparison: FPRP = 0.001) and low quality studies (recessive: FPRP = 0.086). However, greater FPRP values were observed for other significant findings, which need validation in further studies.

Table 3: False-positive report probability values for associations between cancer risk and IL-10 polymorphisms

Genotype

Crude OR (95% CI)

P-valuea

Statistical powerb

Prior probability

0.25

0.1

0.01

0.001

0.0001

 -1082A/G

 All

Dominant

1.32 (1.04-1.67)

0.021

0.857

0.068

0.179

0.705

0.960

0.996

 Cancer type-HCC

Heterozygous

1.40 (1.01-1.94)

0.043

0.661

0.164

0.371

0.866

0.985

0.998

Dominant

1.43 (1.04-1.95)

0.024

0.619

0.103

0.257

0.792

0.975

0.997

Allele comparison

1.35 (1.04-1.75)

0.023

0.787

0.082

0.211

0.747

0.967

0.997

 Quality score-low

Heterozygous

1.42 (1.05-1.91)

0.020

0.641

0.087

0.223

0.759

0.970

0.997

Dominant

1.56 (1.17-2.08)

0.002

0.395

0.018

0.053

0.380

0.861

0.984

Allele comparison

1.43 (1.08-1.88)

0.010

0.634

0.047

0.129

0.619

0.942

0.994

 -819T/C

 All

Homozygous

1.19 (1.00-1.41)

0.044

0.996

0.118

0.286

0.815

0.978

0.998

Recessive

1.17 (1.00-1.36)

0.041

0.999

0.109

0.269

0.802

0.976

0.998

Allele comparison

1.08 (1.00-1.18)

0.088

1.000

0.210

0.443

0.898

0.989

0.999

 Cancer type-lung cancer

Homozygous

2.66 (1.84-3.84)

<0.001

0.001

<0.001

0.001

0.015

0.137

0.613

Recessive

2.40 (1.71-3.37)

<0.001

0.003

<0.001

0.001

0.013

0.114

0.564

Dominant

1.49 (1.16-1.92)

0.002

0.521

0.012

0.034

0.281

0.797

0.975

Allele comparison

1.59 (1.33-1.91)

<0.001

0.267

<0.001

<0.001

<0.001

0.003

0.026

 Cancer type-oral cancer

Homozygous

1.58 (1.01-2.46)

0.043

0.409

0.239

0.485

0.912

0.991

0.999

 -592A/C

 All

Homozygous

1.13 (1.00-1.28)

0.055

1.000

0.141

0.330

0.844

0.982

0.998

 Cancer type-lung cancer

Homozygous

1.64 (1.19-2.24)

0.002

0.287

0.019

0.055

0.392

0.867

0.985

Recessive

1.52 (1.20-1.93)

0.001

0.457

0.004

0.011

0.113

0.563

0.928

Dominant

1.27 (1.01-1.60)

0.043

0.921

0.122

0.294

0.821

0.979

0.998

Allele comparison

1.27 (1.06-1.52)

0.009

0.965

0.028

0.078

0.484

0.904

0.990

 Cancer type-oral cancer

Homozygous

1.58 (1.01-2.46)

0.043

0.409

0.239

0.485

0.912

0.991

0.999

 Cancer type-colorectal cancer

Homozygous

0.58 (0.40-0.85)

0.005

0.238

0.062

0.165

0.685

0.956

0.995

Heterozygous

0.66 (0.53-0.83)

<0.001

0.466

0.002

0.007

0.075

0.449

0.891

Dominant

0.65 (0.52-0.80)

<0.001

0.406

<0.001

0.001

0.012

0.105

0.541

Allele comparison

0.72 (0.61-0.85)

<0.001

0.818

<0.001

0.001

0.013

0.113

0.562

 Control source-HB

Allele comparison

1.07 (1.00-1.15)

0.066

1.000

0.165

0.372

0.867

0.985

0.998

 Quality score-low

Homozygous

1.23 (1.02-1.49)

0.034

0.979

0.095

0.240

0.777

0.972

0.997

Recessive

1.21 (1.05-1.40)

0.010

0.998

0.030

0.086

0.508

0.913

0.991

HCC: hepatocellular carcinoma; HB: hospital based.

aChi-square test was used to calculate the genotype frequency distributions.

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

DISCUSSION

In this meta-analysis, we comprehensively investigated the associations between three promoter variants (-1082A/G, -819T/C and -592A/C) in IL-10 gene and cancer risk in the Chinese population through 53 articles. The results revealed that all the three IL-10 gene polymorphisms we considered were associated with an increased overall cancer risk. Stratification analysis showed that the association between the -1082A/G polymorphism and cancer risk was more evident for hepatocellular carcinoma and low quality studies, the association between the -819T/C polymorphism and cancer risk was more obvious for lung cancer and oral cancer. However, the -592A/C polymorphism showed a statistically significant increased risk for lung cancer, oral cancer, hospital-based studies and low quality studies, but a decreased risk for colorectal cancer. To our knowledge, this is so far the first meta-analysis that has assessed multiple promoter polymorphisms in IL-10 gene with cancer risk in the Chinese population.

Three meta-analyses including international studies have investigated the association of IL-10 -1082A/G, -819T/C and -592A/C polymorphisms with overall cancer susceptibility. The study carried out by Wang et al. [92] analyzed IL-10 -1082A/G polymorphism, consisting 61 international studies with a total of 14,499 cases and 16,967 controls, in which no significant association was found between this polymorphism and overall cancer risk. Another meta-analysis [93] including 15,942 cases and 22,336 controls investigated IL-10 -819C/T polymorphism and cancer risk, without finding any significant association between this polymorphism and overall cancer risk. The study carried out by Ding et al. [94] considered IL-10 -592C/A polymorphism, in which a decreased risk of overall cancer was found with the AA genotype. Other meta-analyses with international studies have assessed the association between polymorphisms in IL-10 gene and susceptibility to some types of cancer. For example, two studies [95, 96] revealed no significant association between IL-10 -1082A/G, -819T/C and -592A/C polymorphisms with non-Hodgkin lymphoma susceptibility. Some of the significant associations found in the previous studies were not validated in our meta-analysis, for example, IL-10 -1082A/G polymorphism was associated with an increased lung cancer risk [92]. We also found some significant associations that were not observed in previous analyses. For instance, we found that IL-10 -592A/C polymorphism was associated with a decreased colorectal cancer risk. The discrepancy occurred because our analysis was carried out only in the Chinese population, suggesting that the polymorphisms on cancer risk might vary among different study subjects’ ethnicity or lifestyle factors.

To make our significant findings more noteworthy, FPRP analysis was performed. Interestingly, FPRP test results revealed that only the association between IL-10 -1082A/G polymorphism and overall cancer risk remained significant at the prior probability level of 0.1. In the subgroup analysis, only the low quality studies, lung cancer and colorectal cancer remained significant. Other findings were false-positive, which might be due to the limited sample size.

Our present meta-analysis has some highlights. First, it identified the significant association between IL-10 -1082A/G, -819T/C and -592A/C polymorphisms and an increased overall cancer risk in the Chinese population. Second, the quality of each included study was evaluated by the quality score criteria. Third, no publication bias was detected in the study, indicating the robustness of the results. Finally, the significant findings were further validated using the FPRP test, making the results more authentic. However, some possible limitations should be considered. First, the total sample size in each individual study was less than 1000 in all but four studies [69, 82, 85, 86], which might reflect a difficulty to evaluate the real association. Second, our results were based on unadjusted estimates, which might cause confounding bias. Third, in the subgroup analysis by cancer type, only two studies were included for some types of cancer, which might affect the detection of the real association. Finally, the potential gene-gene, and gene-environment interactions were not assessed due to the lack of information in the original studies.

In conclusion, this meta-analysis suggested an association between IL-10 gene polymorphisms and cancer risk in the Chinese population, especially for lung cancer, colorectal cancer and low quality studies. Well-designed studies with large sample size are required to verify our findings.

MATERIALS AND METHODS

Search strategy

A systematic literature search was conducted in PubMed, Embase, CNKI and Wanfang database using the following MeSH terms and their synonyms: (“interleukin-10” or “interleukin 10” or “IL-10” or “IL 10”) AND (“polymorphism, single nucleotide” [MeSH] or “SNP” or “single nucleotide polymorphism” or “polymorphism” or “variant” or “variation”) AND (“neoplasms” [MeSH] or “neoplasia” or “neoplasm” or “tumor” or “malignancy” or “cancer”), up to 19 January, 2017. In addition, review articles and references of the selected articles were manually searched to identify additional relevant articles. Only the most recent publications or the ones with most participants were included in the final meta-analysis in cases of overlapping data.

Inclusion and exclusion criteria

The inclusion criteria were as follows: (1) studies investigating the association between IL-10 -1082A/G, -819T/C and -592A/C polymorphisms with cancer risk in Chinese populations; (2) case-control studies; (3) studies providing sufficient data for calculation of ORs and 95% CIs. Studies were excluded if any of the following aspects existed: (1) not a case-control study; (2) duplicate publications; (3) studies without available genotype data; (4) review articles, meta-analyses, conference abstracts or editorial articles; and (5) genotype frequencies in the controls departure from HWE.

Data extraction

Two investigators independently extracted the relevant data from all included studies based on the inclusion criteria listed above. Disagreement was resolved by discussion with a third investigator. The following information was extracted from each included study: first author’s surname, publication year, cancer type, control source (hospital-based or population-based), genotyping methods, and number of cases and controls with different genotypes.

Quality assessment

Two independent investigators assessed the qualities of all included studies according to the criteria from a previous meta-analysis [97]. Quality scores of studies ranged from 0 (lowest) to 15 (highest), and the studies with scores > 9 were considered of high quality.

Statistical analysis

The strength of association between IL-10 -1082A/G, -819T/C and -592A/C polymorphisms and cancer risk was assessed by calculating the ORs and the corresponding 95% CIs. The pooled ORs were calculated for the homozygous model, heterozygous model, recessive model, dominant model and an allele comparison. The between-study heterogeneity was quantified by chi-square based Q test and the fixed-effects model (the Mantel-Haenszel method) [98] was used when no significant heterogeneity was observed (P > 0.1); otherwise, the random-effects model (the DerSimonian and Laird method) [99] was adopted. Subgroup analysis was performed by cancer type (if one cancer type contained less than two studies, it was merged into the “other cancers” group), control source (hospital-based studies and population-based studies), and quality scores (≤ 9 and > 9). Sensitivity analysis was performed to assess results stability. Publication bias was examined using Begg’s funnel plot and Egger’s linear regression test.

The FPRP was calculated to examine the significant associations found in the present meta-analysis. FPRP was calculated with 0.2 as a FPRP threshold and a prior probability of 0.1 was assigned to detect an OR of 0.67/1.50 (protective/risk effects) for an association with the genotypes under investigation [100]. FPRP values below threshold 0.2 were considered as noteworthy associations. All the statistical tests were performed using STATA version 12.0 (Stata Corporation, College Station, TX). All the P values were two-sided, and P < 0.05 were considered statistically significant.

Author contributions

Ping Wang, Junling An and Yanfeng Zhu performed the research study and collected the data; Ping Wang, Xuedong Wan and Hongzhen Zhang analyzed the data; Shoumin Xi and Sanqiang Li designed the research study; Ping Wang wrote the paper. All authors read and approve the final manucript.

ACKNOWLEDGMENTS

This work was supported by the Key Scientific and Technological Project of Henan province (Grant No. 162102310413).

CONFLICTS OF INTEREST

The authors declare no conflicts of interest.

REFERENCES

1. Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015; 65:87-108.

2. Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ, He J. Cancer statistics in China, 2015. CA Cancer J Clin. 2016; 66:115-132.

3. Pharoah PD, Dunning AM, Ponder BA, Easton DF. Association studies for finding cancer-susceptibility genetic variants. Nat Rev Cancer. 2004; 4:850-860.

4. O’Callaghan DS, O’Donnell D, O’Connell F, O’Byrne KJ. The role of inflammation in the pathogenesis of non-small cell lung cancer. J Thorac Oncol. 2010; 5:2024-2036.

5. Grivennikov SI, Greten FR, Karin M. Immunity, inflammation, and cancer. Cell. 2010; 140:883-899.

6. Terzić J, Grivennikov S, Karin E, Karin M. Inflammation and colon cancer. Gastroenterology. 2010; 138:2101-2114.

7. Grivennikov SI. Inflammatory cytokines in cancer: tumour necrosis factor and interleukin 6 take the stage. Ann Rheum Dis. 2011; 70:i104-i108.

8. Chen S, Kapturczak MH, Wasserfall C, Glushakova OY, Campbell-Thompson M, Deshane JS, Joseph R, Cruz PE, Hauswirth WW, Madsen KM. Interleukin 10 attenuates neointimal proliferation and inflammation in aortic allografts by a heme oxygenase-dependent pathway. Proc Natl Acad Sci U S A. 2005; 102:7251-7256.

9. Mocellin S, Marincola FM, Young HA. Interleukin-10 and the immune response against cancer: a counterpoint. J Leukocyte Biol. 2005; 78:1043-1051.

10. Howell WM, Rosezerilli MJ. Cytokine gene polymorphisms, cancer susceptibility, and prognosis. J Nutr. 2007; 137:194S-199S.

11. Turner DM, Williams DM, Sankaran D, Lazarus M, Sinnott PJ, Hutchinson IV. An investigation of polymorphism in the interleukin-10 gene promoter. Eur J Immunogenet. 1997; 24:1-8.

12. Kingo K, Rätsep R, Kõks S, Karelson M, Silm H, Vasar E. Influence of genetic polymorphisms on interleukin-10 mRNA expression and psoriasis susceptibility. J Dermatol Sci. 2005; 37:111-113.

13. Pooja S, Chaudhary P, Nayak LV, Rajender S, Saini KS, Deol D, Kumar S, Bid HK, Konwar R. Polymorphic variations in IL-1β, IL-6 and IL-10 genes, their circulating serum levels and breast cancer risk in Indian women. Cytokine. 2012; 60:122-128.

14. Lee JY, Kim HY, Kim KH, Kim SM, Jang MK, Park JY, Lee JH, Kim JH, Yoo JY. Association of polymorphism of IL-10 and TNF-A genes with gastric cancer in Korea. Cancer Lett. 2005; 225:207-214.

15. Jeong SW, Tae K, Lee SH, Kim KR, Park CW, Park BL, Shin HD. Cox-2 and IL-10 polymorphisms and association with squamous cell carcinoma of the head and neck in a Korean sample. J Korean Med Sci. 2010; 25:1024-1028.

16. Peddireddy V, Badabagni SP, Sulthana S, Kolla VK, Gundimeda SD, Mundluru H. Association of TNFα−308, IFNγ+874, and IL10-1082 gene polymorphisms and the risk of non-small cell lung cancer in the population of the South Indian state of Telangana. Int J Clin Oncol. 2016; 21:843-852.

17. Li Y, Chang SC, Goldstein BY, Scheider WL, Cai L, You NC, Tarleton HP, Ding B, Zhao J, Wu M, Jiang Q, Yu S, Rao J, et al. Green tea consumption, inflammation and the risk of primary hepatocellular carcinoma in a Chinese population. Cancer Epidemiol. 2011; 35:362-368.

18. Oh SS, Chang SC, Cai L, Cordon-Cardo C, Ding BG, Greenland S, He N, Jiang Q, Kheifets L, Le A, Lee YC, Liu S, Lu ML, et al. Single nucleotide polymorphisms of 8 inflammation-related genes and their associations with smoking-related cancers. Int J Cancer. 2010; 127:2169-2182.

19. Sun F, Sun Y, Zhang D, Zhang J, Song B, Zheng H. Association of interleukin-10 gene polymorphism with cachexia in Chinese patients with gastric cancer. Ann Clin Lab Sci. 2010; 40:149-155.

20. Liang X, Zhang J, Zhu Y, Lu Y, Zhou X, Wang Z, Yu J, Yan Y, Di L, Che L, Jiang H, Shao B, Wang X, et al. Specific genetic polymorphisms of IL10-592 AA and IL10-819 TT genotypes lead to the key role for inducing docetaxel-induced liver injury in breast cancer patients. Clin Transl Oncol. 2013; 15:331-334.

21. Lu XH, Mao GX, Zhang YY, Chu YS, Yuan HX, Zhu XQ. Association between variants of IL-8 and IL-10 genes, and efficacy of transcatheter arterial chemoembolization and subsequent prognosis in patients with liver cancer. Eur Rev Med Pharmacol Sci. 2015; 19:3218-3223.

22. Yuan C, Yip SP, Wu VW, Kwong DL, Cheuk IW, Ying M. Association between genetic polymorphisms and carotid atherosclerosis in patients treated with radiotherapy for nasopharyngeal carcinoma. Radiat Oncol. 2015; 10:39.

23. Wang YM, Li ZX, Tang FB, Zhang Y, Zhou T, Zhang L, Ma JL, You WC, Pan KF. Association of genetic polymorphisms of interleukins with gastric cancer and precancerous gastric lesions in a high-risk Chinese population. Tumor Biol. 2016; 37:2233-2242.

24. Nieters A, Yuan JM, Sun CL, Zhang ZQ, Stoehlmacher J, Govindarajan S, Yu MC. Effect of cytokine genotypes on the hepatitis B virus-hepatocellular carcinoma association. Cancer. 2005; 103:740-748.

25. Wang J, Ni H, Chen L, Song WQ. Interleukin-10 promoter polymorphisms in patients with hepatitis B virus infection or hepatocellular carcinoma in Chinese Han ethnic population. Hepatobiliary Pancreat Dis Int. 2006; 5:60-64.

26. Zhou SZ, Zhu WL, Li MY, Li HY, Zhang JR. [Association of single nucleotide polymorphism at interleukin-10 gene 1082 nt with the risk of gastric cancer in Chinese population]. [Article in Chinese]. Nan Fang Yi Ke Da Xue Xue Bao. 2008; 28:1335-1338.

27. Hosgood HD, Au WY, Kim HN, Liu J, Hu W, Tse J, Song B, Wong KF, Lee JJ, Chanock SJ, Siu LP, Purdue MP, Shin MH, et al. IL10 and TNF variants and risk of non-Hodgkin lymphoma among three Asian populations. Int J Hematol. 2013; 97:793-799.

28. Wang N, Wang L, Yang H, Zhang HQ, Lan B, He X, Jin TB, Kang LL, Chen C. Multiple genetic variants are associated with colorectal cancer risk in the Han Chinese population. Eur J Cancer Prev. 2015; 24:1-5.

29. Guo W, Wang N, Wang YM, Li Y, Wen DG, Chen ZF, He YT, Zhang JH. Interleukin-10 -1082 promoter polymorphism is not associated with susceptibility to esophageal squamous cell carcinoma and gastric cardiac adenocarcinoma in a population of high-incidence region of north China. World J Gastroenterol. 2005; 11:858-862.

30. Lu W, Pan K, Zhang L, Lin D, Miao X, You W. Genetic polymorphisms of interleukin (IL)-1B, IL-1RN, IL-8, IL-10 and tumor necrosis factor α and risk of gastric cancer in a Chinese population. Carcinogenesis. 2005; 26:631-636.

31. Deng WY, He LP, Peng XW. [The relationship among IL-10 gene polymorphisms, H elicobacter pylori and noncardia gastric cancer development in Fujian province]. [Article in Chinese]. Wei Chang Bing Xue He Gan Bing Xue Za Zhi. 2008; 17:212-214.

32. He XP, Wang LL, Zhao H, Wu D, Tang HD, Cao FL. [Association of interleukin-10 polymorphisms with susceptibility to ovarian cancer in Chinese Han population]. [Article in Chinese]. Zhongguo You Sheng Yu Yi Chuan Za Zhi. 2008; 16:37-38.

33. Zhou Y, Hu W, Zhuang W, Wu X. Interleukin-10 -1082 promoter polymorphism and gastric cancer risk in a Chinese Han population. Mol Cell Biochem. 2011; 347:89-93.

34. Bai DS, Ma D, Li O. [Study on IL-10 -1082G/A polymorphism in high risk-HPV 16, 18-associated cervical carcinoma in Tangshan]. [Article in Chinese]. Zhongguo Mei Tan Gong Ye Yi Xue Za Zhi. 2012; 15:1147-1149.

35. Yin YQ, Liu CJ, Zhang MM, Zhou Y. [Interleukin-10 -1082 promoter polymorphism and the risk of gastric cancer]. [Article in Chinese]. Sichuan Da Xue Xue Bao Yi Xue Ban. 2012; 43:378-381.

36. Jin T, Li X, Zhang J, Wang H, Geng T, Li G, Gao G, Chen C. Genetic association between selected cytokine genes and glioblastoma in the Han Chinese population. BMC Cancer. 2013; 13:236.

37. Tsai CW, Chang WS, Lin KC, Shih LC, Tsai MH, Hsiao CL, Yang MD, Lin CC, Bau DT. Significant association of Interleukin-10 genotypes and oral cancer susceptibility in Taiwan. Anticancer Res. 2014; 34:3731-3737.

38. Zeng YY, Chen XY, Tian KG, Ren HY, Li ZR, Zhao Q. [The correlation of interleukin-10 gene polymorphism and HPV infection and cervical lesions in Dongguan region]. [Article in Chinese]. Lin Chuang He Shi Yan Yi Xue Za Zhi. 2015; 14:636-639.

39. Ma B, Li L. [Interaction between H. pylori infection and IL-10-819C/T polymorphism in gastric cancer]. [Article in Chinese]. Zhonghua Pu Wai Ke Shou Shu Xue Za Zhi. 2016; 10:255-258.

40. Wu MS, Huang SP, Chang YT, Shun CT, Chang MC, Lin MT, Wang HP, Lin JT. Tumor necrosis factor-alpha and interleukin-10 promoter polymorphisms in Epstein-Barr virus-associated gastric carcinoma. J Infect Dis. 2002; 185:106-109.

41. Heneghan MA, Johnson PJ, Clare M, Ho S, Harrison PM, Donaldson PT. Frequency and nature of cytokine gene polymorphisms in hepatocellular carcinoma in Hong Kong Chinese. J Gastrointest Cancer. 2003; 34:19-26.

42. Shih CM, Lee YL, Chiou HL, Hsu WF, Chen WE, Chou MC, Lin LY. The involvement of genetic polymorphism of IL-10 promoter in non-small cell lung cancer. Lung Cancer. 2005; 50:291-297.

43. Wei YS, Kuang XH, Zhu YH, Liang WB, Yang ZH, Tai SH, Zhao Y, Zhang L. Interleukin-10 gene promoter polymorphisms and the risk of nasopharyngeal carcinoma. Tissue Antigens. 2007; 70:12-17.

44. Bai XL, Sun LP, Liu J, Chen W, Zhang Y, Yuan Y. [Correlation of interleukin-10-1082G/A single nucleotide polymorphism to the risk of gastric cancer in North China: a case-control study]. [Article in Chinese]. Ai Zheng. 2008; 27:35-40.

45. Hsing AW, Sakoda LC, Rashid A, Andreotti G, Chen J, Wang BS, Shen MC, Chen BE, Rosenberg PS, Zhang M. Variants in inflammation genes and the risk of biliary tract cancers and stones: a population-based study in China. Cancer Res. 2008; 68:6442-6452.

46. Hao MG, Wang WJ, Lu Y, Ying XP, Liu CZ, Hu XJ, Gao ZQ, Lu W. [Association of genetic polymorphism within promoter region of TNF-α, IL-1β and IL-10 with the susceptibility to lung cancer]. [Article in Chinese]. Huan Jing Yu Zhi Ye Yi Xue. 2009; 26:24-27.

47. Xiao H, Jiang Y, Li R, Xia B. [Association of IL-10 gen polymorphisms with gastroduodenal in Hubei Han population]. [Article in Chinese]. Zhonghua Yi Xue Yi Chuan Xue Za Zhi. 2009; 26:423-426.

48. Kong F, Liu J, Liu Y, Song B, Wang H, Liu W. Association of interleukin-10 gene polymorphisms with breast cancer in a Chinese population. J Exp Clin Cancer Res. 2010; 29:72.

49. Liu JJ, Gao YT, Du Z, Yang B, Jing X, Wang YJ, Wang FM, Liu T. [Relationship between IL-10 gene promoter polymorphisms and outcome of hepatitis B virus infection]. [Article in Chinese]. Shijie Huaren Xiao Hua Za Zhi. 2010; 18:1656-1663.

50. Niu WQ. [The study on the association between the IL-10 promoter genetic polymorphisms and prostate cancer in Hubei Hans population]. [Article in Chinese]. Guoji Jian Yan Yi Xue Za Zhi. 2011; 32:42-43.

51. Wang Q, Zhang C, Walayat S, Chen HW, Wang Y. Association between cytokine gene polymorphisms and cervical cancer in a Chinese population. Eur J Obstet Gyn R B. 2011; 158:330-333.

52. He B, Pan Y, Xu Y, Nie Z, Chen L, Gu L, Wang S. Increased risk for gastric cancer in carriers of the lymphotoxin-α+252G variant infected by Helicobacter pylori. Genet Test Mol Bioma. 2012; 16:9-14.

53. Chang JS, Lo HI, Wong TY, Huang CC, Lee WT, Tsai ST, Chen KC, Yen CJ, Wu YH, Hsueh WT, Yang MW, Wu SY, Chang KY, et al. Investigating the association between oral hygiene and head and neck cancer. Oral Oncol. 2013; 49:1010-1017.

54. Chen ZG, Zhou W, Dai GJ, Wu ZG, Jin R. [Association between the interaction polymorphisms of interleukin-10 and smoking on patients with bladder cancer risk from a case-control study]. [Article in Chinese]. Zhonghua Liu Xing Bing Xue Za Zhi. 2013; 34:183-186.

55. Du WP, Ye WJ, Chen MH, Li D, Jing XA. [Association research between polymorphism of IFN-γ and IL-10, environmental risk factors, and susceptibility to esophageal cancer]. [Article in Chinese]. Wei Sheng Yan Jiu. 2013; 42:770-776.

56. Pan XF, Yang SJ, Loh M, Xie Y, Wen YY, Tian Z, Huang H, Lan H, Chen F, Soong R, Yang CX. Interleukin-10 gene promoter polymorphisms and risk of gastric cancer in a Chinese population: single nucleotide and haplotype analyses. Asian Pac J Cancer P. 2013; 14:2577-2582.

57. Cheng S, Li J, Liu W, Liu C, Su L, Liu X, Guo L, Ma Y, Song B, Liu J. LTA + 252A > G polymorphism is associated with risk of nasal NK/T-cell lymphoma in a Chinese population: a case-control study. BMC Cancer. 2015; 15:480.

58. Fei C, Yao XM, Sun Y, Gu XZ, Yu LQ, Lai X. Interleukin-10 polymorphisms associated with susceptibility to acute myeloid leukemia. Genet Mol Res. 2015; 14:925-930.

59. Hsu HJ, Yang YH, Shieh TY, Chen CH, Kao YH, Yang CF, Ko EC. TGF-beta1 and IL-10 single nucleotide polymorphisms as risk factors for oral cancer in Taiwanese. Kaohsiung J Med Sci. 2015; 31:123-129.

60. Yang Y, Fa X. Role of IL-10 gene polymorphisms on the susceptibility for esophageal cancer and its association with environmental factors. Int J Clin Exp Pathol. 2015; 8:9580-9585.

61. Bai CY, Shi XY, He J, Xue J, Feng Y. Association between IL-10 genetic variations and cervical cancer susceptibility in a Chinese population. Genet Mol Res 2016; 15. doi: 10.4238/gmr.15038116.

62. Cai J, Zhang Z. An analysis of IL-10/IL-10R genetic factors related to risk of colon cancer and inflammatory bowel disease in a Han Chinese population. Clin Lab. 2016; 62:1147-1154.

63. Peng MW, Lu SQ, Liu J, Dong CY. Role of IL-10 polymorphisms in susceptibility to hepatitis B virus-related hepatocellular carcinoma. Genet Mol Res. 2016; 15. doi: 10.4238/gmr.15017984.

64. Wu MS, Wu CY, Chen CJ, Lin MT, Shun CT, Lin JT. Interleukin-10 genotypes associate with the risk of gastric carcinoma in Taiwanese Chinese. Int J Cancer. 2003; 104:617-623.

65. Savage SA, Abnet CC, Haque K, Mark SD, Qiao YL, Dong ZW, Dawsey SM, Taylor PR, Chanock SJ. Polymorphisms in interleukin -2, -6, and -10 are not associated with gastric cardia or esophageal cancer in a high-risk Chinese population. Cancer Epidem Biomar. 2004; 13:1547-1549.

66. Yao JG, Gao LB, Liu YG, Li J, Pang GF. Genetic variation in interleukin-10 gene and risk of oral cancer. Clin Chim Acta. 2008; 388:84-88.

67. Liu J, Song B, Bai X, Liu W, Li Z, Wang J, Zheng Y, Wang Z. Association of genetic polymorphisms in the interleukin-10 promoter with risk of prostate cancer in Chinese. BMC Cancer. 2010; 10:456.

68. Su SP, Yang ZB, Tian YL, Xiang Y, Wu M, Ma XJ. [Relationship between polymorphisms of IL-1β-31, IL-10-819 and TNF-α-1031 genes and susceptibilities to H. pylori infection-associated gastric ulcer and cancer]. [Article in Chinese]. Chin J Biologicals. 2010; 23:517-520.

69. Bei CH, Qiu XQ, Zeng XY, Yang Y, Huang JM, Fan XJ. [Association of interleukin-10 gene polymorphism with hepatocellular carcinoma]. [Article in Chinese]. Zhongguo Gong Gong Wei Sheng. 2011; 27:309-311.

70. Liu J, Song B, Wang JL, Li ZJ, Li WH, Wang ZH. Polymorphisms of interleukin-10 promoter are not associated with prognosis of advanced gastric cancer. World J Gastroenterol. 2011; 17:1362-1367.

71. He JR, Chen LJ, Su Y, Cen YL, Tang LY, Yu DD, Chen WQ, Wang SM, Song EW, Ren ZF. Joint effects of Epstein-Barr virus and polymorphisms in interleukin-10 and interferon-gamma on breast cancer risk. J Infect Dis. 2012; 205:64-71.

72. Yuan LJ, Jin TB, Yin JK, Du XL, Wang Q, Dong R, Wang SZ, Cui Y, Chen C, Lu JG. Polymorphisms of tumor-related genes IL-10, PSCA, MTRR and NOC3L are associated with the risk of gastric cancer in the Chinese Han population. Cancer Epidemiol. 2012; 36:e366-e372.

73. Zeng X, Li Y, Liu T, Zhang J. Diverse H. pylori strains, IL-10 promoter polymorphisms with high morbidity of gastric cancer in Hexi area of Gansu Province, China. Mol Cell Biochem. 2012; 362:241-248.

74. Yao CJ, Du W, Chen HB, Xiao S, Wang CH, Fan ZL. Associations of IL-10 gene polymorphisms with acute myeloid leukemia in Hunan, China. Asian Pac J Cancer P. 2013; 14:2439-2442.

75. Zhang YM, Mao YM, Sun YX. Genetic polymorphisms of IL-6 and IL-10 genes correlate with lung cancer in never-smoking Han population in China. Int J Clin Exp Med. 2015; 8:1051-1058.

76. Cui Y, Zhu JJ, Ma CB, Cui K, Wang F, Ni SH, Zhang ZY. Interleukin 10 gene -1082A/G polymorphism is associated with osteosarcoma risk and poor outcomes in the Chinese population. Tumor Biol. 2016; 37:4517-4522.

77. Li L, Ye LM, Li Y. Investigation on the association between IL-10 C819T gene polymorphisms and susceptibility to gastric cancer. J Digest Dis. 2016; 17:117-118.

78. Tseng LH, Lin MT, Shau WY, Lin WC, Chang FY, Chien KL, Hansen JA, Chen DS, Chen PJ. Correlation of interleukin-10 gene haplotype with hepatocellular carcinoma in Taiwan. Tissue Antigens. 2006; 67:127-133.

79. Xiong XD, Lu SX, Zeng LQ, Chen MJ, Yang ZH, Luo XP, Liu XG. [Relationship between IL-10-592A>C promoter polymorphism and the susceptibility to cervical cancer]. [Article in Chinese]. Zhongguo You Sheng Yu Yi Chuan Za Zhi. 2010; 18:46-48.

80. Liang HG, Zhao-Ran FU, Xi-Ming QI. [Relationship between the genetic polymorphism in Interleukin-10-592C/A and susceptibility to non-small cell lung cancer]. [Article in Chinese]. Zhongguo Xian Dai Yi Xue Za Zhi. 2011; 21:189-193.

81. Yu XM, Ma D, Wu SQ, Guan WJ, Feng FM, Gao HX, Li O. [Relationship between polymorphisms of IL-10 gene and cervical cancer]. [Article in Chinese]. Zhonghua Yi Yuan Gan Ran Xue Za Zhi. 2011; 21:239-241.

82. Zhang Y, Wang MY, He J, Wang JC, Yang YJ, Jin L, Chen ZY, Ma XJ, Sun MH, Xia KQ, Hong XN, Wei QY, Zhou XY. Tumor necrosis factor-alpha induced protein 8 polymorphism and risk of non-Hodgkin's lymphoma in a Chinese population: a case-control study. PLoS One. 2012; 7:e37846.

83. Sun JM, Li Q, Gu HY, Chen YJ, Wei JS, Zhu Q, Chen L. Interleukin 10 rs1800872 T>G polymorphism was associated with an increased risk of esophageal cancer in a Chinese population. Asian Pac J Cancer P. 2013; 14:3443-3447.

84. Tsai CW, Tsai MH, Shih LC, Chang WS, Lin CC, Bau DT. Association of interleukin-10 (IL10) promoter genotypes with nasopharyngeal carcinoma risk in Taiwan. Anticancer Res. 2013; 33:3391-3396.

85. Bei CH, Bai H, Yu HP, Yang Y, Liang QQ, Deng YY, Tan SK, Qiu XQ. Combined effects of six cytokine gene polymorphisms and SNP-SNP interactions on hepatocellular carcinoma risk in Southern Guangxi, China. Asian Pac J Cancer P. 2014; 15:6961-6967.

86. Hsia TC, Chang WS, Liang SJ, Chen WC, Tu CY, Chen HJ, Yang MD, Tsai CW, Hsu CM, Tsai CH, Bau DT. Interleukin-10 (IL-10) promoter genotypes are associated with lung cancer risk in Taiwan males and smokers. Anticancer Res. 2014; 34:7039-7044.

87. Kuo WH, Huang CY, Fu CK, Hsieh YH, Liao CH, Hsu CM, Huang YK, Tsai CW, Chang WS, Bau DT. Effects of interleukin-10 polymorphisms and smoking on the risk of gastric cancer in Taiwan. In Vivo. 2014; 28:967-971.

88. Yu Y, Zheng S, Zhang S, Jin W, Liu H, Jin M, Chen Z, Ding Z, Wang L, Chen K. Polymorphisms of inflammation-related genes and colorectal cancer risk: a population-based case-control study in China. Int J Immunogenet. 2014; 41:289-297.

89. Yin J, Wang X, Wei J, Wang L, Shi Y, Zheng L, Tang W, Ding G, Liu C, Liu R, Chen S, Xu Z, Gu H. Interleukin 12B rs3212227 T > G polymorphism was associated with an increased risk of gastric cardiac adenocarcinoma in a Chinese population. Dis Esophagus. 2015; 28:291-298.

90. Chang WS, Liao CH, Tsai CW, Hu PS, Wu HC, Hsu SW, Ji HX, Hsiao CL, Bau DT. The role of IL-10 promoter polymorphisms in renal cell carcinoma. Anticancer Res. 2016; 36:2205-2209.

91. Ma B, Zhang TY, Wan Y, Zhan FS. [A case-control study of interleukin-10 gene -592A/C polymorphism and the risk of gastric cancer]. [Article in Chinese]. Ningxia Yi Xue Za Zhi. 2016; 38:580-582.

92. Wang J, Ding Q, Shi Y, Cao Q, Qin C, Zhu J, Chen J, Yin C. The interleukin-10-1082 promoter polymorphism and cancer risk: a meta-analysis. Mutagenesis. 2012; 27:305-312.

93. Yu Z, Liu Q, Huang C, Wu M, Li G. The interleukin 10 -819C/T polymorphism and cancer risk: a HUGE review and meta-analysis of 73 studies including 15,942 cases and 22,336 controls. Omics. 2013; 17:200-214.

94. Ding Q, Shi Y, Fan B, Fan Z, Ding L, Li F, Tu W, Jin X, Wang J. The interleukin-10 promoter polymorphism rs1800872 (-592C>A), contributes to cancer susceptibility: meta-analysis of 16,785 cases and 19,713 controls. PLoS One. 2013; 8:e57246.

95. Zhang T, Xie S, Zhu JH, Li QW, He J, Zeng AP. Association of IL10 -819C>T and -592C>A polymorphisms with non-Hodgkin lymphoma susceptibility: evidence from published studies. J Cancer. 2015; 6:709-716.

96. Zhang Y, Xia ZG, Zhu JH, Chen MB, Wang TM, Shen WX, He J. Association of Interleukin-10 -3575T>A and -1082A>G polymorphisms with non-Hodgkin lymphoma susceptibility: a comprehensive review and meta-analysis. Mol Genet Genomics. 2015; 290:2063-2073.

97. He J, Liao XY, Zhu JH, Xue WQ, Shen GP, Huang SY, Chen W, Jia WH. Association of MTHFR C677T and A1298C polymorphisms with non-Hodgkin lymphoma susceptibility: evidence from a meta-analysis. Sci Rep. 2014; 4:6159.

98. Mantel N, Haenszel W. Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst. 1959; 22:719-748.

99. Dersimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986; 7:177-188.

100. He J, Wang MY, Qiu LX, Zhu ML, Shi TY, Zhou XY, Sun MH, Yang YJ, Wang JC, Jin L. Genetic variations of mTORC1 genes and risk of gastric cancer in an eastern Chinese population. Mol Carcinogen. 2013; 52:70-79.


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