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. 2017 May 25;8(34):56780–56790. doi: 10.18632/oncotarget.18187

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

Jiarong Cai 1,#, Qingjian Ye 2,#, Suling Luo 3,#, Ze Zhuang 4, Kui He 5, Zhen-Jian Zhuo 6, Xiaochun Wan 7,8, Juan Cheng 2
PMCID: PMC5593601  PMID: 28915630

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.

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

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 [3–6].

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 [14–21], three were case only studies [22–24], 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, 26–57].

Figure 1. Flow diagram of the study selection process.

Figure 1

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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
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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
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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.

Figure 2. Forest plot of the association between the CASP8 -652 6N ins/del polymorphism and cancer risk via the homozygous model.

Figure 2

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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.

Figure 3. Funnel plot analysis to detect publication bias for the CASP8 -652 6N ins/del polymorphism via the homozygous model.

Figure 3

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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.

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

Figure 4

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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) [62–65]. 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 [66–69]. 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.

SUPPLEMENTARY MATERIALS TABLES

Footnotes

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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