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Research Papers:

CASP8 -652 6N insertion/deletion polymorphism and overall cancer risk: evidence from 49 studies

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Oncotarget. 2017; 8:56780-56790. https://doi.org/10.18632/oncotarget.18187

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Jiarong Cai, Qingjian Ye, Suling Luo, Ze Zhuang, Kui He, Zhen-Jian Zhuo, Xiaochun Wan and Juan Cheng _

Abstract

Jiarong Cai1,*, Qingjian Ye2,*, Suling Luo3,*, Ze Zhuang4, Kui He5, Zhen-Jian Zhuo6, Xiaochun Wan7,8 and Juan Cheng2

1Department of Urology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China

2Department of Gynecology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China

3Department of Otolaryngology, The First People’s Hospital of Foshan (Affiliated Foshan Hospital of Sun Yat-Sen University), Foshan 528000, China

4Department of Joint Surgery and Orthopaedic Trauma, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China

5The Second People’s Hospital of FuTian District, Shenzhen 518000, China

6School of Chinese Medicine, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong 999077, China

7Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai 200032, China

8Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China

*These authors have contributed equally to this work

Correspondence to:

Juan Cheng, email: [email protected]

Xiaochun Wan, email: [email protected]

Keywords: CASP8, -652 6N insertion/deletion, polymorphism, cancer risk, meta-analysis

Received: March 13, 2017     Accepted: April 24, 2017     Published: May 25, 2017

ABSTRACT

The CASP8 -652 6N insertion/deletion (I/D) polymorphism reduces expression of caspase 8. We conducted a meta-analysis to clarify the relationship between this polymorphism and cancer risk. Eligible articles were retrieved from PubMed, EMBASE, CNKI, and WANFANG databases through February 2017. A total of 33 articles with 49 studies, including 33,494 cases and 36,397 controls, were analyzed. We found that the CASP8 -652 6N ins/del polymorphism was associated with decreased overall cancer risk in five genetic models [DD vs. II: odds ratio (OR)=0.76, 95% confidence interval (CI)=0.69–0.84, ID vs. II: OR=0.87, 95% CI=0.83–0.92, DD vs. ID/II: OR=0.82, 95% CI=0.75–0.89, ID/DD vs. II: OR=0.85, 95% CI=0.80–0.90, and D vs. I: OR=0.87, 95% CI=0.83–0.91]. Stratified analyses showed that the polymorphism was associated with decreased risk of colorectal, breast, esophageal, renal cell, lung, cervical, bladder, gastric, and other cancers. Overall cancer risk was reduced in Asian and Caucasian patients, both hospital- and population-based studies, and both high and low quality studies. Our results highlight the role of the CASP8 -652 6N ins/del polymorphism in decreasing cancer risk. Further studies with large-cohort populations, especially for specific cancer types and ethnic groups, are needed to confirm our findings.


INTRODUCTION

Cancer is a substantial public health burden worldwide and is the second leading cause of death in the United States. An estimated 1,688,780 new cancer cases and 600,920 cancer deaths will occur in the United States this year [1]. Approximately 14 million new cancer cases occurred worldwide in 2012, and by 2025, global cancer incidence is predicted to rise to 20 million new cases annually [2]. Although there are many cancer risk factors, genetic abnormalities play crucial roles in carcinogenesis [36].

Apoptosis is a control mechanism to prevent over-proliferation in normal cells [7], and apoptosis pathway aberrations are implicated in cancer development [8]. Caspases are the main regulatory enzymes in the apoptosis pathway [9]. Caspase 8 mediates the extrinsic apoptosis pathway [10, 11]. Human CASP8 is located on chromosome 2q33~q34, has 11 exons [12], and is highly polymorphic with more than 474 single nucleotide polymorphisms (SNPs) according to the dbSNP database (http://www.ncbi.nlm.nih.gov/SNP). The CASP8 -652 6N ins/del polymorphism (rs3834129) is a six-nucleotide insertion/deletion variant located in the CASP8 promoter region [13], and leads to decreased CASP8 expression. Impaired caspase 8 function reduces T lymphocyte “activation-induced cell death” (AICD) activity, which is important in immune surveillance of cancer cells [13].

Extensive epidemiological studies have assessed the association between the CASP8 -652 6N ins/del polymorphism and cancer risk. However, these studies have not produced conclusive results. The most recent previous meta-analysis of this association, conducted in 2014, assessed a relatively small number of studies. We performed this meta-analysis with a larger sample size to more precisely describe the association of interest.

RESULTS

Study characteristics

Our study selection workflow is shown in Figure 1. Our systematic computer-based search initially identified 108 potentially relevant articles. After scanning titles and abstracts, 67 articles about unrelated topics were excluded. We further excluded 12 articles: eight were meta-analyses [1421], three were case only studies [2224], and one deviated from HWE [25]. Articles incorporating several ethnic groups or cancer types were separated into corresponding independent studies. In total, our analysis included datasets from 33 articles with 49 studies [13, 2657].

Flow diagram of the study selection process.

Figure 1: Flow diagram of the study selection process.

Characteristics for 33,494 cases and 36,397 controls are summarized in Table 1. Of the included studies, 12 were conducted on colorectal cancer, nine on other cancers, eight on breast cancer, three on esophageal cancer, three on renal cell carcinoma, and two on lung cancer, cervical cancer, prostate cancer, bladder cancer, lymphoma cancer, and gastric cancer, respectively. Twenty-seven studies were conducted in Asians, 20 in Caucasians, one in Africans, and one in mixed populations. Twenty-four studies were of population-based design, 22 studies were of hospital-based design, and three did not mention study design in the original data. We also classified the studies as either low quality (25 studies) or high quality (24 studies) by quality score.

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

Author last name

Year

Cancer type

Country

Ethnicity

Design

Genotype method

Case

Control

MAF

HWE

Score

II

ID

DD

All

II

ID

DD

All

Sun

2007

Lung

China

Asian

PB

PCR-RFLP

756

348

45

1149

640

407

64

1111

0.24

0.947

11

Sun

2007

Esophagus

China

Asian

PB

PCR-RFLP

652

328

38

1018

543

338

56

937

0.24

0.724

11

Sun

2007

Gastric

China

Asian

PB

PCR-RFLP

262

142

16

420

233

152

25

410

0.25

0.975

11

Sun

2007

Colorectal

China

Asian

PB

PCR-RFLP

605

280

33

918

528

304

58

890

0.24

0.116

11

Sun

2007

Breast

China

Asian

PB

PCR-RFLP

699

371

49

1119

513

419

72

1004

0.28

0.279

11

Sun

2007

Cervical

China

Asian

PB

PCR-RFLP

199

102

13

314

314

211

42

567

0.26

0.428

10

Yang

2008

Pancreatic

China

Asian

PB

PCR-RFLP

268

111

18

397

521

323

63

907

0.25

0.185

13

Pittman

2008

Colorectal

England

Caucasian

PB

AS-PCR

995

1897

987

3879

892

1872

897

3661

0.50

0.170

9

Frank

2008

Breast

Germany

Caucasian

HB

Fluorescent

298

535

221

1054

270

506

263

1039

0.50

0.403

7

Frank

2008

Breast

England

Caucasian

PB

Fluorescent

235

541

251

1027

245

608

321

1174

0.53

0.169

10

Frank

2008

Breast

Germany

Caucasian

PB

Fluorescent

280

509

222

1011

285

492

229

1006

0.47

0.550

9

Frank

2008

Breast

England

Caucasian

PB

Fluorescent

1133

2115

1050

4298

1149

2263

1062

4474

0.49

0.422

8

Cybulski

2008

Breast

Poland

Caucasian

PB

AS-PCR

178

314

126

618

274

499

192

965

0.46

0.195

6

Cybulski

2008

Prostate

Poland

Caucasian

PB

AS-PCR

139

236

110

485

274

499

192

965

0.46

0.195

6

Li

2008

Melanoma

USA

Caucasian

HB

PCR

243

385

177

805

207

440

188

835

0.49

0.116

11

Wang

2009

Bladder

China

Asian

HB

PCR-RFLP

238

115

12

365

205

138

25

368

0.26

0.786

10

Gangwar

2009

Bladder

India

Asian

HB

PCR-RFLP

121

84

7

212

133

101

16

250

0.27

0.584

9

De Vecchi

2009

Breast

Italy

Caucasian

PB

PCR-RFLP

162

301

117

580

106

206

94

406

0.49

0.752

7

Zhu

2010

RCC

China

Asian

HB

PCR-RFLP

226

119

8

353

205

139

21

365

0.25

0.686

11

Srivastava

2010

Gallbladder

India

Asian

PB

PCR-RFLP

147

69

12

228

122

84

24

230

0.29

0.103

11

Liu

2010

Colorectal

China

Asian

PB

PCR-RFLP

233

116

21

370

528

278

32

838

0.20

0.538

13

Li

2010

HNSCC

USA

Caucasian

HB

PCR–RFLP

311

456

256

1023

257

542

253

1052

0.50

0.324

10

Xiao

2011

Lymphoma

China

Asian

NM

PCR-PAGE

43

17

4

64

89

38

6

133

0.19

0.460

3

Xiao

2011

Lymphoma

China

Asian

NM

PCR-PAGE

49

23

3

75

63

40

4

107

0.22

0.442

3

Umar

2011

Esophageal

India

Asian

PB

PCR

139

103

17

259

138

93

28

259

0.29

0.046

11

Theodoropoulos

2011

Colorectal

Greece

Caucasian

HB

RFLP-PCR

103

201

98

402

120

254

106

480

0.49

0.194

9

Malik

2011

Esophageal

India

Asian

HB

RFLP-PCR

68

59

8

135

96

75

24

195

0.32

0.127

8

Malik

2011

Gastric

India

Asian

HB

RFLP-PCR

59

44

5

108

96

75

24

195

0.32

0.127

8

Ma

2011

Ovarian

China

Asian

HB

MassARRAY

128

87

3

218

138

122

25

285

0.30

0.789

8

Liamarkopoulos

2011

Gastric

Greece

Caucasian

HB

PCR-RFLP

35

42

11

88

120

254

106

480

0.49

0.194

7

Hart

2011

Lung

Norway

Caucasian

PB

TaqMan

125

210

101

436

106

209

118

433

0.51

0.481

10

Chatterjee

2011

Cervical

South Africa

African

HB

PCR-RFLP

18

63

25

106

43

129

85

257

0.58

0.614

6

Fu

2011

Prostate

China

Asian

HB

PCR-RFLP

257

132

17

406

211

159

38

408

0.29

0.315

10

Wang

2012

RCC

China

Asian

HB

PCR-RFLP

192

101

7

300

168

114

18

300

0.25

0.817

10

Wang

2012

PTC

China

Asian

HB

PCR–RFLP

65

45

8

118

106

92

15

213

0.29

0.408

7

Tong

2012

ALL

China

Asian

HB

PCR-RFLP

217

113

31

361

338

153

28

519

0.20

0.057

10

Hashemi

2012

Breast

Iran

Asian

HB

AS-PCR

113

107

16

236

79

91

33

203

0.39

0.434

6

George

2012

Prostate

India

Asian

HB

PCR-RFLP

84

69

12

165

116

83

6

205

0.23

0.050

9

Xiao

2013

Colorectal

China

Asian

HB

PCR-PAGE

187

107

11

305

212

115

15

342

0.21

0.905

7

Wu

2013

Colorectal

China

Asian

HB

PCR-SSCP

284

152

15

451

358

244

29

631

0.24

0.119

11

De Martino

2013

RCC

Austria

Caucasian

HB

PCR-RFLP

72

138

40

250

53

129

68

250

0.53

0.572

9

Pardini

2014

Colorectal

Spain

Caucasian

PB

Taqman

500

996

482

1978

425

802

420

1647

0.50

0.290

11

Pardini

2014

Colorectal

Italy

Caucasian

PB

Taqman

195

285

137

617

783

1230

538

2551

0.45

0.178

9

Pardini

2014

Colorectal

USA

Caucasian

PB

Taqman

237

514

259

1010

383

794

403

1580

0.51

0.835

9

Pardini

2014

Colorectal

England

Caucasian

PB

Taqman

410

825

341

1576

165

393

209

767

0.53

0.436

11

Pardini

2014

Colorectal

Czech

Caucasian

PB

Taqman

239

479

249

967

169

326

177

672

0.51

0.443

10

Pardini

2014

Colorectal

Netherlands

Caucasian

PB

Taqman

169

282

134

585

106

177

76

359

0.46

0.895

8

Tang

2015

OSCC

China

Asian

HB

PCR-RFLP

328

159

18

505

276

197

34

507

0.26

0.885

10

Carvalho

2015

ALL

Brazil

Mixed

NM

PCR

23

81

26

130

47

53

25

125

0.41

0.163

4

MAF: minor allele frequency; HWE: Hardy-Weinberg equilibrium; OSCC: oral squamous cell carcinoma; PTC: papillary thyroid carcinoma; RCC: renal cell carcinoma; HNSCC: head and neck squamous cell carcinoma; ALL: acute lymphocytic leukemia; PB: population based; HB: hospital based; NM: not mentioned; PCR-PAGE: polymerase chain reaction-polyacrylamide gel electrophoresis; PCR-RFLP: polymerase chain reaction-restriction fragment length polymorphism; AS-PCR: allele-specific polymerase chain reaction.

Quantitative analysis

Overall meta-analysis information is shown in Table 2 and Figure 2. In the pooled analysis, the CASP8 -652 6N ins/del polymorphism was associated with reduced overall cancer risk in all five genetic models (homozygous: DD vs. II: odds ratio (OR)=0.76, 95% confidence interval (CI)=0.69–0.84; heterozygous: ID vs. II: OR=0.87, 95% CI=0.83–0.92; recessive: DD vs. ID/II: OR=0.82, 95% CI=0.75–0.89; dominant: ID/DD vs. II: OR=0.85, 95% CI=0.80–0.90; and allele: D vs. I: OR=0.87, 95% CI=0.83–0.91.

Table 2: Meta-analysis of the association between the CASP8 -652 6N ins/del polymorphism and overall cancer risk

Variables

No. of studies

Sample size

Homozygous

Heterozygous

Recessive

Dominant

Allele

DD vs. II

ID vs. II

DD vs. ID/II

ID/DD vs. II

D vs. I

OR (95% CI)

P het

OR (95% CI)

P het

OR (95% CI)

P het

OR (95% CI)

P het

OR (95% CI)

P het

All

49

33494/36397

0.76 (0.69-0.84)

<0.001

0.87 (0.83-0.92)

<0.001

0.82 (0.75-0.89)

<0.001

0.85 (0.80-0.90)

<0.001

0.87 (0.83-0.91)

<0.001

Cancer type

 Colorectal

12

13058/14418

0.93 (0.82-1.05)

0.018

0.94 (0.88-0.99)

0.529

0.96 (0.87-1.06)

0.019

0.93 (0.87-1.00)

0.190

0.96 (0.90-1.01)

0.012

 Breast

8

9943/10271

0.80 (0.67-0.96)

0.001

0.90 (0.81-1.01)

0.018

0.85 (0.74-0.99)

0.002

0.87 (0.77-0.99)

0.002

0.89 (0.80-0.98)

<0.001

 Esophageal

3

1412/1196

0.56 (0.40-0.78)

0.901

0.93 (0.74-1.17)

0.206

0.58 (0.42-0.79)

0.812

0.83 (0.71-0.97)

0.385

0.81 (0.72-0.92)

0.712

 RCC

3

903/915

0.39 (0.26-0.59)

0.852

0.78 (0.64-0.95)

0.998

0.46 (0.32-0.66)

0.732

0.71 (0.58-0.86)

0.949

0.70 (0.61-0.82)

0.966

 Lung

2

1585/1544

0.66 (0.51-0.87)

0.473

0.75 (0.64-0.88)

0.385

0.75 (0.59-0.95)

0.458

0.73 (0.63-0.85)

0.453

0.78 (0.69-0.87)

0.273

 Cervical

2

420/824

0.58 (0.36-0.93)

0.456

0.86 (0.59-1.25)

0.230

0.59 (0.39-0.88)

0.728

0.76 (0.59-0.98)

0.355

0.76 (0.63-0.92)

0.556

 Prostate

2

650/205

1.54 (0.67-3.55)

0.100

0.99 (0.79-1.23)

0.411

1.50 (0.74-3.07)

0.135

1.05 (0.85-1.29)

0.321

1.11 (0.93-1.33)

0.255

 Bladder

2

577/618

0.44 (0.25-0.77)

0.799

0.79 (0.62-1.01)

0.334

0.48 (0.27-0.84)

0.907

0.74 (0.59-0.93)

0.317

0.74 (0.61-0.90)

0.338

 Lymphoma

2

139/240

1.19 (0.44-3.23)

0.729

0.82 (0.52-1.31)

0.635

1.26 (0.47-3.39)

0.789

0.86 (0.56-1.34)

0.559

0.93 (0.64-1.35)

0.535

 Gastric

2

196/675

0.35 (0.19-0.63)

0.939

0.74 (0.44-1.23)

0.145

0.45 (0.26-0.78)

0.538

0.64 (0.40-1.01)

0.171

0.66 (0.51-0.84)

0.487

 ALL

2

491/644

1.85 (1.20-2.87)

0.655

1.83 (0.69-4.85)

0.004

1.32 (0.81-2.14)

0.228

1.79 (0.81-3.97)

0.014

1.33 (1.10-1.61)

0.443

 Others

9

4120/4847

0.57 (0.43-0.75)

0.009

0.72 (0.65-0.79)

0.976

0.65 (0.49-0.88)

0.001

0.70 (0.64-0.77)

0.855

0.75 (0.68-0.84)

0.013

Ethnicity

 Asian

27

10569/11219

0.58 (0.48-0.70)

<0.001

0.80 (0.75-0.85)

0.231

0.62 (0.52-0.74)

0.002

0.77 (0.72-0.83)

0.016

0.79 (0.73-0.84)

<0.001

 Caucasian

20

22689/24796

0.90 (0.83-0.98)

0.006

0.92 (0.88-0.97)

0.225

0.95 (0.89-1.02)

0.007

0.92 (0.87-0.97)

0.079

0.95 (0.91-0.99)

0.008

 African

1

106/257

0.70 (0.35-1.43)

/

1.17 (0.62-2.19)

/

0.63 (0.37-1.05)

/

0.98 (0.54-1.80)

/

0.82 (0.60-1.13)

/

 Mixed

1

130/125

2.13 (1.01-4.46)

/

3.12 (1.70-5.73)

/

1.00 (0.54-1.85)

/

2.80 (1.57-5.00)

/

1.50 (1.05-2.12)

/

Source of control

 PB

24

25259/26848

0.83 (0.75-0.92)

<0.001

0.89 (0.84-0.94)

0.008

0.89 (0.82-0.96)

<0.001

0.87 (0.81-0.93)

<0.001

0.89 (0.85-0.95)

<0.001

 HB

22

7966/9184

0.61 (0.49-0.75)

<0.001

0.83 (0.77-0.89)

0.213

0.67 (0.55-0.82)

<0.001

0.79 (0.73-0.87)

0.024

0.81 (0.75-0.88)

<0.001

 NM

3

269/365

1.73 (0.95-3.14)

0.619

1.30 (0.53-3.20)

0.003

1.07 (0.63-1.80)

0.896

1.29 (0.58-2.88)

0.005

1.14 (0.79-1.64)

0.156

Quality score

 >9

24

16745/16831

0.67 (0.58-0.77)

<0.001

0.81 (0.76-0.87)

0.008

0.75 (0.66-0.85)

<0.001

0.78 (0.73-0.84)

<0.001

0.81 (0.76-0.87)

<0.001

 ≤9

25

16749/19566

0.87 (0.77-0.99)

<0.001

0.95 (0.90-1.01)

0.289

0.90 (0.81-1.00)

<0.001

0.94 (0.88-1.00)

0.048

0.94 (0.90-0.99)

<0.001

Values were in bold, if the 95% CI excluded 1 or P<0.05.

Het: heterogeneity; RCC: renal cell carcinoma; ALL: acute lymphocytic leukemia; HB: hospital based; PB: population based; NM: not mentioned.

Forest plot of the association between the CASP8 -652 6N ins/del polymorphism and cancer risk via the homozygous model.

Figure 2: Forest plot of the association between the CASP8 -652 6N ins/del polymorphism and cancer risk via the homozygous model. The OR and 95% CI for each study are plotted as a box and horizontal line. ◊, pooled ORs and the corresponding 95% CIs.

In cancer type stratification analysis, the CASP8 -652 6N ins/del polymorphism decreased risk for colorectal cancer, breast cancer, esophageal cancer, renal cell carcinoma, lung cancer, cervical cancer, bladder cancer, gastric cancer, and other cancers. However, acute lymphocytic leukemia risk was increased (DD vs. II: OR=1.85, 95% CI=1.20–2.87; and D vs. I: OR=1.33, 95% CI=1.10–1.61). We observed no correlations between the CASP8 -652 6N ins/del polymorphism and prostate cancer or lymphoma.

Stratification analysis by ethnicity revealed a decreased cancer risk for Asians (DD vs. II: OR=0.58, 95% CI=0.48–0.70) and Caucasians (DD vs. II: OR=0.90, 95% CI=0.83–0.98), and an increased risk in mixed populations (DD vs. II: OR=2.13, 95% CI=1.01–4.46). We also found that the CASP8 -652 6N ins/del polymorphism decreased cancer risk in population-based (DD vs. II: OR=0.83, 95% CI=0.75–0.92) and hospital-based groups (DD vs. II: OR=0.61, 95% CI=0.49–0.75). Similarly, the CASP8 -652 6N ins/del polymorphism was associated with decreased cancer risk in both the high quality (DD vs. II: OR=0.67, 95% CI=0.58–0.77) and low quality study groups (DD vs. II: OR=0.87, 95% CI=0.77–0.99).

Heterogeneity and sensitivity analysis

Heterogeneity was observed in all five genetic models (P<0.001, Q test). Therefore, the random-effect model was adopted to generate ORs and 95% CIs. We also conducted a sequential leave-one-out sensitivity analysis to evaluate the impact of a single study on the pooled estimates. Omission of no single study influenced the pooled ORs, indicating the statistical robustness of this meta-analysis (data not shown).

Publication bias

Begg’s funnel plot shapes did not suggest any obvious asymmetry (Figure 3). Egger’s test results (DD vs. II: t=-4.17, P<0.001; ID vs. II: t=-0.12, P=0.905; DD vs. ID/II: t=-1.15, P=0.257; ID/DD vs. II: t=-1.09, P=0.281; and D vs. I: t=-3.33, P=0.002) suggested that publication bias existed in the homozygote and allele models.

Funnel plot analysis to detect publication bias for the CASP8 -652 6N ins/del polymorphism via the homozygous model.

Figure 3: Funnel plot analysis to detect publication bias for the CASP8 -652 6N ins/del polymorphism via the homozygous model. Each point represents a separate study for the indicated association.

Trial sequential analysis

To minimize random errors and strengthen the robustness of our conclusions, we performed trial sequential analysis (TSA) (Figure 4). The cumulative Z-curve crossed the trial sequential monitoring boundary before the required information size was reached, suggesting that our study conclusion was convincing and no additional evidence was needed to verify said conclusion.

Trial sequential analysis for the CASP8 -652 6N ins/del polymorphism via the allele contrast model.

Figure 4: Trial sequential analysis for the CASP8 -652 6N ins/del polymorphism via the allele contrast model.

DISCUSSION

The present meta-analysis comprehensively evaluated the relationship between the CASP8 -652 6N ins/del polymorphism and cancer risk across 49 studies (33,494 cases and 36,397 controls). The CASP8 -652 6N ins/del polymorphism was associated with decreased cancer risk in all five genetic models, and in the following subgroups: colorectal cancer, breast cancer, esophageal cancer, renal cell carcinoma, lung cancer, cervical cancer, bladder cancer, gastric cancer, other cancers, Asian, Caucasian, mixed population, population-based controls, hospital-based controls, high quality score, and low quality score.

Human immune cells play critical roles in eliminating potentially malignant cells [58]. Caspase 8 protein (encoded by CASP8) maintains immune cells by mediating the activation-apoptosis balance [59]. Low caspase 8 expression or functional aberrations may decrease T lymphocyte apoptotic reactivity [13]. The CASP8 -652 6N del variant inactivates the transcription factor stimulatory protein 1 binding site, decreasing CASP8 transcription [13]. Thus, this variant may affect cancer susceptibility by influencing immune surveillance.

The first case-control study of the CASP8 -652 6N del variant-cancer association, with 4,995 cases and 4,972 controls, was conducted by Sun, et al. in 2007 [13]. The authors found that the CASP8 -652 6N deletion allele decreased susceptibility to lung, colorectal, esophageal, breast, cervical, and gastric cancers. Biochemical assays illustrated that this variant might decrease apoptotic reactivity in cancer cell-stimulated T lymphocytes. However, Umar, et al. did not detect any association between the CASP8 -652 6N polymorphism and esophageal squamous cell carcinoma (ESCC) risk in 259 patients and 259 healthy controls in an Indian population [45]. Several meta-analyses have attempted to address these contradictory conclusions. A 2012 meta-analysis by Chen, et al., including 19 case-control studies with 23,172 cases and 26,532 controls, associated the del allele, ins/del genotype, and del allele carriers with reduced overall cancer risk [16]. Similarly, in a meta-analysis incorporating 11 reports with 27,459 cases and 31,614 controls, Yin, et al. associated the CASP8 -652 5N del polymorphism with reduced overall cancer risk via homozygous, dominant, and recessive models [15]. In 2014, breast cancer- and colorectal cancer-specific meta-analyses [19, 20] concluded that the CASP8 -652 6N del polymorphism reduced cancer risk. However, no association was observed between this polymorphism and prostate cancer susceptibility in a meta-analysis by Zhang, et al. [21].

To provide a more robust clarification, our meta-analysis included all eligible studies published in either the English or Chinese language. In agreement with the four previously published meta-analyses, we found that the CASP8 -652 6N ins/del polymorphism was associated with reduced overall cancer risk. In subgroup analyses, the polymorphism was associated with reduced risk of colorectal cancer, breast cancer, esophageal cancer, renal cell carcinoma, lung cancer, cervical cancer, bladder cancer, gastric cancer, and other cancers, but not prostate cancer or lymphoma. A prostate cancer-specific meta-analysis also failed to detect a significant association. This may be attributed to cancer-specific inherent heterogeneity [60, 61]. Additionally, we observed an association with decreased cancer risk among Asians and Caucasians, but not Africans or mixed ethnicity populations. However, the limited number of studies in Africans and mixed ethnicity population may account for this finding, and CASP8 -652 6N ins/del polymorphism allelic distributions might vary geographically and ethnically.

Our meta-analysis of the association between the CASP8 -652 6N ins/del polymorphism and cancer risk is by far the largest such meta-analysis with the greatest statistical power published thus far. We conducted subgroup analyses to provide a more precise, cancer type-specific conclusion, and we assessed studies in both Chinese and English to minimize selection bias. However, our study had certain limitations. First, for some types of cancers, the calculated association was not robust enough due to limited numbers of original studies. Second, only one CASP8 genetic variant was considered, and confounding factors, such as other genetic mutations and environmental exposures, also influence cancer susceptibility. Third, the observed between-study heterogeneity may reduce the validity of our conclusions. Finally, publication bias, language bias, or selection bias might lead to false positive or negative findings.

The present work robustly concludes that the CASP8 -652 6N ins/del polymorphism is associated with reduced overall cancer risk. Refined studies with larger sample sizes, especially for certain cancer types and ethnic groups, are needed to fully validate this relationship.

MATERIALS AND METHODS

Search strategy

We conducted a literature search in PubMed and EMBASE using the following combined terms: ‘Caspase 8’ or ‘CASP8’ and ‘polymorphism’ or ‘polymorphisms’ or ‘single nucleotide polymorphism’ or ‘SNP’ or ‘variant’ and ‘cancer’ or ‘tumor’ or ‘carcinoma’ or ‘carcinogenesis’ or ‘neoplasm’. We also searched studies written in Chinese from two databases, WANFANG and CNKI. We searched for articles published through February 2017 without imposing language limitations. Relevant references were also collected from retrieved articles. Only the largest or the most recent study was retained if studies contained overlapping data.

Inclusion/exclusion criteria

Studies included in our analysis met the following criteria: (1) evaluated CASP8 -652 6N ins/del polymorphism with respect to cancer risk; (2) case-control design; (3) sufficient information to extract genotype frequencies for all subjects; (4) genotype frequency of controls consistent with Hardy-Weinberg equilibrium (HWE); (5) publication language was English or Chinese. Criteria for exclusion included: (1) abstract only, review, or meta-analysis; (2) case only studies; (3) no detailed genotyping data provided; (4) repeated publication.

Data extraction

Two authors (Jiarong Cai and Qingjian Ye) independently identified all eligible studies, and extracted data was included in the meta-analysis following consensus. The following items were recorded from each study: first author’s name, year of publication, country, patient ethnicity, cancer type, source of controls, genotyping method, and genotype distributions of cases and controls. If reports contained more than one ethnic group or cancer type, we separated them into different studies.

Trial sequential analysis

After adopting a risk of 5% for type I errors and 30% for type II errors, the required information size (sample sizes from all included trials) was calculated. TSA monitoring boundaries were built based on required information size and risk for type I and type II errors. If the cumulative Z-curve crossed the TSA monitoring boundary before the required information size was reached (i.e. if a sufficiently small P-value was achieved), further trials were unnecessary.

Statistical analyses

We used the Chi-square test to ensure that all control genotype frequencies were in agreement with HWE. Odds ratios (ORs) with corresponding 95% confidence intervals (CIs) obtained from case and control genotype frequencies were used to assess the strength of association between the CASP8 -652 6N ins/del polymorphism and cancer risk. Pooled ORs were calculated for the following five genetic models: homozygote model (DD vs. II), heterozygote model (ID vs. II), recessive model (DD vs. ID/II), dominant model (ID/DD vs. II), and allele model (D vs. I). The Cochran’s Chi-square-based Q-test and the inconsistency index (I2 statistics) were adopted to assess heterogeneity between study results. I2<50% or P>0.10 indicates heterogeneity. The fixed-effects model (Mantel-Haenszel method) was used to estimate the pooled OR if no heterogeneity existed (I2<50% or P>0.10). Otherwise, the random-effects model (DerSimonian and Laird method) was applied. Quality assessment for each study was performed using the quality assessment criteria described previously (Supplementary Table 1) [6265]. To decrease heterogeneity among studies, we conducted stratification analyses by ethnicity, cancer type, control source, and quality score. By adopting one-way sensitivity analysis, we recalculated the pooled ORs to assess the robustness of the results. We also conducted Begg’s funnel plot and Egger’s regression asymmetry test to examine potential publication bias [6669]. STATA software v. 11.0 (Stata Corporation, College Station, TX) was used for statistical analyses [70]. P<0.05 (two-sided) was considered statistically significant.

CONFLICTS OF INTEREST

The authors declare no conflicts of interest.

GRANT SUPPORT

This study was supported by grants from the National Natural Science Foundation of China (Grant No. 31172044).

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