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. 2016 Feb 4;6:20439. doi: 10.1038/srep20439

Role of IL-17A rs2275913 and IL-17F rs763780 polymorphisms in risk of cancer development: an updated meta-analysis

Zhi-Ming Dai 1,2,*, Tian-Song Zhang 3,*, Shuai Lin 4, Wang-Gang Zhang 2, Jie Liu 2, Xing-Mei Cao 2, Hong-Bao Li 5, Meng Wang 4, Xing-Han Liu 4, Kang Liu 4, Shan-Li Li 4, Zhi-Jun Dai 4,a
PMCID: PMC4740815  PMID: 26843459

Abstract

Single nucleotide polymorphisms (SNPs) in the interleukin-17 (IL-17) gene have been shown to be correlated with susceptibility to cancer. However, various studies report different results of this association. The aim of the present work was to clarify the effects of IL-17A G197A (rs2275913) and IL-17F T7488C (rs763780) polymorphisms on cancer risk. We performed systematic searches of the PubMed and CNKI databases to obtain relevant publications. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to evaluate the association of rs2275913 and rs763780 polymorphisms with cancer risk. Data were extracted from the selected studies, and statistical analysis was conducted using the STATA software. Our results indicated that rs2275913 and rs763780 polymorphisms significantly increase cancer risk, especially in gastric cancers. Subgroup analysis suggested the existence of a significant correlation between rs763780 polymorphism and cancer susceptibility in Caucasian populations. This updated meta-analysis confirms that rs2275913 and rs763780 polymorphisms are highly associated with increased risk for multiple forms of cancer.

According to the latest global statistics on cancer, approximately 14.1 million new cancer cases and 8.2 million cancer-related deaths occurred worldwide in 20121. Cancer is currently the leading cause of death worldwide, and it represents a major global health concern. Although the pathogenic factors of cancer remain unknown, complex interactions between an individual’s genetic background and environmental factors have been suggested to be highly associated with cancer development2.

Inherited factors leading to the development of cancer are not clearly understood, but the roles of cytokines in tumour immunity and carcinogenesis have been well established3. Th17 cells, which were identified as a new subset of T helper cells4, play pivotal roles in both adaptive and innate immunity, by secreting the pro-inflammatory cytokine interleukin (IL)-175. IL-17 has six family members (IL17A-F) that bind to five receptors (IL-17RA-RD and SEF)6. Among all IL-17 family members, IL-17A is one of the most important cytokines, and it may play a role in autoimmune diseases, chronic inflammatory diseases, and malignancies7,8,9; IL-17A has been shown to induce the production of inflammatory chemokines and cytokines by macrophages and neutrophils. More recent studies have reported that IL-17F can also induce the expression of various chemokines, cytokines, and adhesion molecules involved in inflammation-related cancer10. The rs763780 variant in the IL-17F gene can lead to a His-to-Arg substitution at amino acid position 161, and thus, inhibit the function of wild-type IL-17F. This may contribute to increased risk of several malignant tumors including gastric cancer, colorectal cancer, and breast cancer11,12,13,14.

Meta-analysis is a statistical technique that combines results from different individual studies to produce a comprehensive assessment of the major findings with enhanced accuracy15. IL-17 polymorphism has been hypothesized to play a role in carcinogenesis, and numerous studies investigating the same have been published in the past few years11,12,13,14,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31. However, these published studies have reported mixed findings. Therefore, to clarify the role of IL-17A rs2275913 and IL-17F rs763780 polymorphisms in cancer risk, we conducted a comprehensive meta-analysis of all eligible case-control studies.

Results

Study characteristics

Through primary literature retrieval from Pubmed and CNKI databases, we identified 95 studies that investigated the effect of IL-17 polymorphisms on cancer risk. After screening the titles and abstracts according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA, Fig. 1), 55 studies were excluded from our meta-analysis. Then remaining 40 articles were assessed for eligibility by reading the full-text; 14 articles were excluded owing to either lack of complete data or presence of irrelevant data that focused on other IL-17 polymorphisms. Finally, 26 studies with 7,872 cases and 9,646 cancer-free controls met the inclusion criteria for our meta-analysis for assessing the influence of rs2275913 and rs763780 polymorphisms on cancer risk. Among these, 20 studies were based on the Asian population, and 6 were based on Caucasian populations. The selected studies presented data on several different cancer types: gastric, colorectal, prostate, thyroid, cervical, breast, ovary, bladder, hepatocellular, lung, and oesophageal cancer, and acute myeloid leukaemia. The main characteristics of the included studies are presented in Table 1. The distributions of IL-17A rs2275913 and rs763780 polymorphisms among patients and controls are shown in Table 2.

Figure 1. Preferred reporting items for systematic reviews and meta-analyses flow diagram of the literature review process for IL-17 polymorphisms and cancer.

Figure 1

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

First author Year Ethnicity Tumor type case control Genotyping medthod Source of control No. of SNP cancer risk
Hou 2015 Asian GC 326 326 MassARRAY Population 1, 2 No.1 yes
Nemati 2015 Caucasian CRC 202 203 PCR-RFLP Hospital 1*, 2 yes
Gao 2015 Asian GC 572 572 PCR–RFLP Hospital 1, 2* No.2 yes
Lv 2015 Asian CC 264 264 PCR–RFLP Population 1, 2* No.1 yes
Lee 2015 Asian PTC 94 260 TaqMan Population 1 no risk
Xi 2015 Asian HCC 155 171 PCR–RFLP Hospital 1, 2 no risk
Wang 2014 Asian GC 462 462 PCR–RFLP Population 1, 2 No.1 yes
Wróbel 2014 Caucasian AML 62 125 PCR–RFLP Population 1, 2 No.2 yes
Omrane 2014 Caucasian CRC 102 139 TaqMan Population 1 yes
Omrane 2014 Caucasian CRC 102 139 TaqMan Population 2 yes
Yin 2014 Asian EC 380 380 SNPscan Hospital 1 yes
Li 2014 Asian HCC 395 174 PCR–RFLP Hospital 1 yes
Kaabachi 2014 Caucasian LC 239 258 PCR–RFLP Population 1, 2 No.2 yes
Zhu 2014 Asian GC 311 611 MassARRAY Hospital 1, 2* No.1 yes
Zhang 2014 Asian GC 260 512 MassARRAY Hospital 1*, 2* yes
Bi 2014 Asian GC 99 150 PCR-RFLP Hospital 1, 2 no risk
Rafiei 2013 Caucasian GC 161 171 PCR–RFLP Hospital 1 yes
Zhou 2013 Asian BLC 301 446 TaqMan Hospital 1, 2 yes
Arisawa 2012 Asian GC 337 587 PCR-SSCP Hospital 1 yes
Quan 2012 Asian CC 311 463 TaqMan Hospital 1, 2 No.1 yes
Wang 2012 Asian BC 491 502 SNaPshot Population 1, 2 No.1 yes
Ruan 2012 Asian OC 92 38 PCR-RFLP Hospital 1*, 2* no risk
Chen 2010 Asian GC 1042 1090 TaqMan Population 1 no risk
Wu 2010 Asian GC 1010 800 PCR–RFLP Population 1, 2 No.2 yes
Luo 2010 Asian GC 24 50 PCR-RFLP Hospital 1*, 2 No.1 yes
Shibata 2009 Asian GC 287 524 PCR–SSCP Hospital 1*, 2 No.1 yes
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*The P-values of the Hardy-Weinberg equilibrium test of control group less than 0.05.

CRC: colorectal cancer; GC: gastric cancer; CC: cervical cancer; PTC: papillary thyroid cancer; HCC: hepatocellular carcinoma; LC: lung cancer; AML: acute myeloid leukemia; EC: esophageal cancer; BLC: bladder cancer; BC: breast cancer; OC: ovarian cancer; NA: not available; PCR-RFLP: polymerase chain reaction restriction fragment length polymorphism; SSCP: single strand conformation polymorphism; SNP: single-nucleotide polymorphisms; No. of SNP: No.1: rs2275913, No.2: rs763780.

Table 2. IL-17 polymorphisms Genotype Distribution and Allele Frequency in Cases and Controls.

First author Genotype (N,%)
 Allele frequency (N, %)
 MAF
Case
 Control
 Case
 Control
total AA AB BB total AA AB BB A B A B
rs2275913
 Hou 2015 326 121 149 56 326 161 136 29 391 261 458 194 0.40
 Nemati 2015 202 100 82 20 199 110 50 39 282 122 270 128 0.30
 Gao 2015 572 239 250 83 573 260 241 72 728 416 761 385 0.36
 Lv 2015 264 110 117 37 264 139 105 20 337 191 383 145 0.36
 Lee 2015 94 28 42 24 260 76 137 47 98 90 289 231 0.48
 Xi 2015 155 38 71 46 171 35 90 46 147 163 160 182 0.53
 Wang 2014 462 160 211 91 462 214 190 58 531 393 618 306 0.43
 Wróbel 2014 62 23 25 14 125 38 67 20 71 53 143 107 0.43
 Omrane 2014 102 48 51 3 139 95 38 6 147 57 228 50 0.28
 Yin 2014 364 104 180 80 370 117 174 79 388 340 408 332 0.47
 Li 2014 391 110 197 84 174 50 85 39 417 365 185 163 0.47
 Kaabachi 2014 239 147 80 12 258 166 79 13 374 104 411 105 0.22
 Zhu 2014 293 126 122 45 550 273 216 61 374 212 762 338 0.36
 Zhang 2014 260 110 102 48 512 258 187 67 322 198 703 321 0.38
 Bi 2014 99 32 39 28 150 41 69 40 103 95 151 149 0.48
 Rafiei 2013 161 56 61 44 171 78 72 21 173 149 228 114 0.46
 Zhou 2013 301 79 154 68 446 164 204 78 312 290 532 360 0.48
 Arisawa 2012 333 112 137 84 583 218 293 72 361 305 729 437 0.46
 Quan 2012 311 93 142 76 463 168 215 80 328 294 551 375 0.47
 Wang 2012 491 165 234 92 501 198 245 58 564 418 641 361 0.43
 Ruan 2012 92 20 60 12 38 12 24 2 100 84 48 28 0.46
 Chen 2010 1,042 300 522 220 1,090 325 541 224 1,122 962 1,191 989 0.46
 Wu 2010 945 210 485 250 768 193 371 204 905 985 757 779 0.52
 Luo 2010 24 11 12 1 530 58 426 46 34 14 542 518 0.29
 Shibata 2009 287 94 124 69 523 175 299 49 312 262 649 397 0.46
rs763780
 Hou 2015 326 266 38 22 326 278 33 15 570 82 589 63 0.13
 Nemati 2015 200 177 23 0 201 190 11 0 377 23 391 11 0.06
 Gao 2015 572 420 67 85 572 472 58 42 907 237 1002 142 0.21
 Lv 2015 264 209 35 20 264 223 30 11 453 75 476 52 0.14
 Xi 2015 155 100 46 9 171 105 63 3 246 64 273 69 0.21
 Wang 2014 462 349 98 15 462 362 90 10 796 128 814 110 0.14
 Wróbel 2014 62 42 15 5 125 114 11 0 99 25 239 11 0.20
 Omrane 2014 100 72 27 1 137 98 38 1 171 29 234 40 0.15
 Kaabachi 2014 239 204 34 1 258 236 22 0 442 36 494 22 0.08
 Zhu 2014 293 241 35 17 550 463 58 29 517 69 984 116 0.12
 Zhang 2014 260 209 30 21 512 429 53 30 448 72 911 113 0.14
 Bi 2014 100 69 22 9 150 108 35 7 160 40 251 49 0.20
 Zhou 2013 301 240 57 4 446 317 124 5 537 65 758 134 0.11
 Quan 2012 311 222 85 4 463 332 126 5 529 93 790 136 0.15
 Wang 2012 491 382 103 6 502 396 99 7 867 115 891 113 0.12
 Ruan 2012 92 13 69 10 38 2 34 2 95 89 38 38 0.48
 Wu 2010 927 540 332 55 777 527 214 36 1412 442 1268 286 0.24
 Luo 2010 24 14 10 0 230 176 51 3 38 10 403 57 0.21
 Shibata 2009 280 221 55 4 523 419 100 4 497 63 938 108 0.11
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A represents the major allele, B represents the minor allele. MAF: minor allele frequencies.

Quantitative synthesis results

IL-17A G197A polymorphism (rs2275913).

Overall, our meta-analysis found a borderline association between rs2275913 polymorphism and increased cancer risk in all genetic models (AA vs. GG: OR = 1.48, 95% CI = 1.25–1.74; AA vs. GG + GA: OR = 1.40, 95% CI = 1.19–1.65; AA + AG vs. GG: OR = 1. 22, 95% CI = 1.09–1.36, Fig. 2; GA vs. GG: OR = 1.13, 95% CI = 1.01–1.28; A vs. G: OR = 1.22, 95% CI = 1.13–1.32) for all cancer types. When only studies following the Hardy–Weinberg equilibrium (HWE) were included in the analysis, a significant association was also observed under all genetic models, and these results are shown in Table 3.

Figure 2. Forest plots of IL-17A rs2275913 polymorphism and cancer risk using a recessive genetic model (AA+AG vs. GG).

Figure 2

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Table 3. Summary of ORs and 95% CI of IL-17A rs2275913 and IL-17F rs763780 polymorphisms with cancer risk.

Comparisons B vs A
 BB vs AA
 BB vs AB + AA
 BB + AB vs AA
 AB vs AA
OR (95%CI) P OR (95%CI) P OR (95%CI) P OR (95%CI) P OR (95%CI) P
rs2275913
 Overall 1.22 (1.13–1.32) <0.001 1.48 (1.25–1.74) <0.001 1.40 (1.19–1.65) <0.001 1.22 (1.09–1.36) 0.001 1.13 (1.01–1.28) 0.04
HWE
  Yes 1.23 (1.14–1.33) <0.001 1.49 (1.27–1.75) <0.001 1.39 (1.20–1.61) <0.001 1.26 (1.14–1.38) <0.001 1.17 (1.06–1.30) 0.002
Ethnicity
  Asian 1.22 (1.12–1.32) <0.001 1.53 (1.29–1.81) <0.001 1.45 (1.24–1.70) <0.001 1.20 (1.06–1.35) 0.003 1.10 (0.97–1.24) 0.13
  Caucasian 1.24 (0.94–1.63) 0.13 1.16 (0.59–2.27) 0.66 1.08 (0.51–2.28) 0.84 1.34 (0.97–1.84) 0.07 1.35 (0.90–2.03) 0.14
Cancer type
  GC 1.24 (1.10–1.40) <0.001 1.62 (1.26–2.07) <0.001 1.56 (1.23–1.99) <0.001 1.17 (0.99–1.38) 0.07 1.05 (0.89–1.25) 0.56
  CRC 1.25 (0.65–2.38) 0.51 0.61 (0.35–1.07) 0.09 0.48 (0.28–0.82) 0.007 1.71 (0.90–3.24) 0.10 2.10 (1.49–2.96) <0.001
  CC 1.38 (1.18–1.62) <0.001 1.89 (1.35–2.64) <0.001 1.66 (1.23–2.24) 0.001 1.43 (1.14–1.80) 0.002 1.29 (1.01–1.64) 0.04
  HCC 0.99 (0.818–1.20) 0.89 0.96 (0.65–1.41) 0.82 1.03 (0.75–1.42) 0.85 0.94 (0.68–1.28) 0.68 0.92 (0.66–1.29) 0.63
rs763780
 Overall 1.28 (1.11–1.47) 0.001 1.69 (1.40–2.04) <0.001 1.64 (1.36–1.97) <0.001 1.25 (1.07–1.47) 0.001 1.17 (1.00–1.37) 0.06
HWE
  Yes 1.25 (1.02–1.52) 0.03 1.70 (1.21–2.39) 0.002 1.69 (1.20–2.38) 0.002 1.21 (0.98–1.50) 0.08 1.15 (0.93–1.41) 0.20
Ethnicity
  Asian 1.06 (0.95–1.19) 0.28 1.54 (1.08–2.20) 0.02 1.55 (1.09–2.20) 0.02 1.04 (0.87–1.24) 0.66 0.99 (0.83–1.19) 0.95
 Caucasian 2.08 (0.94–1.63) 0.03 6.17 (1.50–30.0) 0.01 6.19 (1.36–28.1) 0.02 2.02 (1.08–3.76) 0.03 1.83 (1.08–3.11) 0.02
Cancer type
  GC 1.37 (1.25–1.51) <0.001 1.67 (1.35–2.06) <0.001 1.59 (1.29–1.95) <0.001 1.37 (1.22–1.53) <0.001 1.28 (1.13–1.45) <0.001
  CRC 1.40 (0.65–3.00) 0.38 – – – – 1.43 (0.63–3.22) 0.39 1.42 (0.63–3.24) 0.40
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A: the major allele; B: the minor allele; CI: confidence interval; OR: odds ratio; GC: Gastric cancer; CRC: colorectal cancer; CC: cervical cancer; HCC: hepatocellular carcinoma.

When subgroup analysis was performed based on ethnicity, no significant correlation was observed between rs2275913 polymorphism and cancer risk in Caucasians. However, statistically significant associations were found in the following genetic models in Asians: (AA vs. GG: OR = 1.53, 95% CI = 1.29–1.81 Fig. 3; AA vs. GG + GA: OR = 1.45, 95% CI = 1.24–1.70; AA + AG vs. GG: OR = 1. 20, 95% CI = 1.06–1.35; A vs. G: OR = 1.22, 95% CI = 1.12–1.32). When results were stratified by cancer type, we found a significant association between rs2275913 polymorphism and increased gastric cancer risk in three genetic models (AA vs. GG: OR = 1.62, 95% CI = 1.26–2.07; AA + AG vs. GG: OR = 1.56, 95% CI = 1.23–1.99; A vs. G: OR = 1.24, 95% CI = 1.10–1.40, Fig. 4). Moreover, significant associations were observed between rs2275913 polymorphism and cervical cancer in all 5 comparison models. All comparisons are listed in Table 3.

Figure 3. Stratified analysis based on ethnicity for the association between IL-17A rs2275913 polymorphism and cancer risk using a homozygote genetic model (AA vs. GG).

Figure 3

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Figure 4. Stratified analysis based on the different cancer sites for the association between IL-17A rs2275913 polymorphism and cancer risk using an allele comparison model (A vs. G).

Figure 4

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IL-17F T7488C polymorphism (rs763780).

A significant association was found between rs763780 and cancer susceptibility in 3 different comparison models (CC vs. TT: OR = 1.69, 95% CI = 1.40–2.04; CC vs. TT + TC: OR = 1.64, 95% CI = 1.36–1.97; C vs. T: OR = 1.28, 95% CI = 1.11–1.47, Fig. 5). The same results were observed when studies with HW disequilibrium in controls were excluded.

Figure 5. Forest plots of IL-17F rs763780 polymorphism and cancer risk using an allele comparison model (C vs. T).

Figure 5

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As shown in Table 3, when subgroup analyses was performed based on ethnicity, significant correlation was observed between rs763780 polymorphism and increased risk of cancer in both Caucasians and Asians. When results were stratified by cancer type, rs763780 polymorphism was found to be significantly associated with an increased risk for gastric cancer in all genetic models (CC vs. TT: OR = 1.67, 95% CI = 1.35–2.06; CC vs. TT + TC: OR = 1.59, 95% CI = 1.29–1.95; CC + TC vs. TT: OR = 1.37, 95% CI = 1.22–1.53; TC vs. TT: OR = 1.28, 95% CI = 1.13–1.45; C vs. T: OR = 1.37, 95% CI = 1.25–1.51).

Publication bias

Publication bias of the selected articles was assessed using Begg’s funnel plot and Egger’s test. As shown in Fig. 6, the funnel plot was symmetrical in shape, and the P-value of Egger’s test indicated a lack of publication bias for rs2275913 and rs763780 polymorphisms.

Figure 6. Funnel plot assessing evidence of publication bias from the eligible studies.

Figure 6

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A. rs2275913; B. rs763780.

Heterogeneity and sensitivity analyses

Significant heterogeneities in the data of IL-17A rs2275913 and IL-17F rs763780 polymorphisms were observed in the overall meta-analysis as well as subgroup analysis (Table 4). Due to significant heterogeneity across studies, individual studies used in the meta-analysis were sequentially omitted to to identify the source by sensitivity analysis. The results showed that no individual study skewed the pooled OR values for rs2275913 and rs763780 polymorphisms (Fig. 7).

Table 4. Heterogeneity-analysis results.

Comparisons B vs A
 BB vs AA
 BB vs AA+AB
 BB+AB vs AA
 AB vs AA
I2 P EM I2 P EM I2 P EM I2 P EM I2 P EM
rs2275913
 Overall 61% <0.001 R 64% <0.001 R 70% <0.001 R 60% <0.001 R 62% <0.001 R
HWE
  Yes 58% 0.001 R 57% 0.001 R 60% <0.001 R 43% 0.02 R 39% 0.04 R
Ethnicity
  Asian 62% <0.001 R 63% <0.001 R 68% <0.001 R 62% <0.001 R 60% <0.001 R
  Caucasian 68% 0.01 R 72% 0.007 R 80% 0.001 R 58% 0.05 R 70% 0.009 R
Cancer type
  GC 74% <0.001 R 75% <0.001 R 79% <0.001 R 73% <0.001 R 71% <0.001 R
  CRC 84% 0.01 R 0% 0.48 F 0% 0.61 F 74% 0.05 R 14% 0.28 F
  CC 0% 0.45 F 0% 0.40 F 0% 0.47 F 0% 0.51 F 0% 0.51 F
  HCC 0% 0.93 F 0% 0.88 F 0% 0.56 F 0% 0.43 F 8% 0.30 F
rs763780
 Overall 68% <0.001 R 0% 0.79 F 0% 0.79 F 64% <0.001 R 57% 0.001 R
HWE
  Yes 68% <0.001 R 0% 0.79 F 0% 0.82 F 66% <0.001 R 61% 0.002 R
Ethnicity
  Asian 37% 0.12 F 0% 0.94 F 0% 0.93 F 43% 0.08 R 44% 0.08 R
  Caucasian 78% 0.003 R 17% 0.30 F 5% 0.35 F 72% 0.02 R 59% 0.06 R
Cancer type
  GC 31% 0.17 F 6% 0.79 F 0% 0.72 F 10% 0.36 F 0% 0.48 F
  CRC 66% 0.09 R – – – – – – 67% 0.08 R 67% 0.08 R
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A: the major allele; B: the minor allele; EM: Effects model; F: fixed effects model; R: random effects model; GC: Gastric cancer; CRC: colorectal cancer; CC: cervical cancer; HCC: hepatocellular carcinoma.

Figure 7. Sensitivity analysis of association between the polymorphisms and cancer risk.

Figure 7

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A. rs2275913; B. rs763780.

Re-sampling statistics

To obtain robust and replicable results, we performed the correlation analysis 10000 times using non-parametric bootstrap re-sampling method. As showed in Supplementary Table S1 & S2, the results indicated that rs2275913 and rs763780 polymorphism in IL-17 gene were consistently associated with cancer risk in different genetic models (P < 0.05).

Discussion

Recently, inflammatory factors have been shown to increase the risk of developing malignant tumors. IL-17 is a key pro-inflammatory cytokine originally produced by CD4+ memory T cells, and it is involved in both innate and acquired immune responses32,33. Studies indicate that IL-17 is activated by microbial products, and may promote tumor growth and progression via angiogenic functions34,35. Aberrant levels of IL-17 have been observed in gastric, colorectal, hepatocellular, ovarian, and breast cancers36,37,38,39,40.

The IL-17A rs22759133 polymorphism is located in close proximity to 2 nuclear factors activated T cell binding motifs, and it promotes production of high levels of IL-17, which in turn upregulates IL-17-mediated immune responses41. IL-17F, another important member of the IL-17 family, plays a key role in neutrophil recruitment and activation by inducing the secretion of cytokines and chemokines. IL-17F rs763780 polymorphism may inhibit the biological activity of IL-17F, and thus contribute to variations in host’s susceptibility to tumors. Data indicate that IL-17A and IL-17F gene polymorphism may play important roles in the pathogenesis of cancer11,13,16,18,24.

Our study indicated that the two variants of human IL-17 gene significantly increased the risk of cancer in the overall population. When we eliminated studies that deviated from the HWE, similar results were observed. Furthermore, subgroup analyses indicated that associations between these two polymorphisms and cancer risk were also ethnicity- and site-specific. According to the results, rs2275913 polymorphism was significantly associated with elevated cancer risk in Asians (mainly Chinese), but not Caucasians. When subgroup analysis was performed based on cancer types, a significant association was found between rs2275913 polymorphism and risk of gastric/cervical cancer. Interestingly, individuals with the rs2275913 AA genotype showed decreased risk of colorectal cancer as compared to individuals with the GG or GA genotypes. However, only two eligible studies examined IL-17 polymorphisms in colorectal cancer, and therefore, the results may need to be further confirmed. Interestingly, a significant association was found between the rs763780 variant and cancer risk in both the Asian and Caucasian populations. This meta-analysis is, to our knowledge, the first study showing that rs763780 polymorphism increases cancer risk in the Caucasian population.

A meta-analysis by Niu et al.42 suggested that IL-17 polymorphisms increase the risk of cancer, particularly gastric cancer, in Asian (especially Chinese) populations; our findings were partially in line with results from this meta-analysis. Another meta-analysis by Zhao et al.43 concluded that not rs763780, but rs2275913, polymorphism may contribute to cancer susceptibility in Asian populations. Long et al.44 found a positive association between the two polymorphisms and the occurrence of gastric cancer in a meta-analysis, which included 7 independent, case-control studies. Other meta-analyses focused on the association between IL-17F rs763780 polymorphism and cancer risk, and the results indicated that the CC allele might increase the risk of cancer, particularly gastric cancer, in Asian populations45,46. All of these previous meta-analyses included fewer than 10 eligible case-control studies, with few studies examining Caucasian populations. The present meta-analysis includes 25 independent case-control studies with 7,872 cancer cases and 9,646 cancer-free controls. In addition, 6 of the included studies were based on Caucasians, to more comprehensively evaluate the relationship between IL-17 polymorphisms and cancer risk in Caucasian populations14,16,24,27,31,47.

We conducted sensitivity analysis to confirm the validity of the results presented in our meta-analysis, and studies in which the genotype frequencies in the control group deviated from the HWE were excluded. Results showed that no individual study skewed the overall OR value.

Some limitations of the present meta-analysis should be addressed. First, although significant associations were found between the two polymorphisms and the risk of cancer in multiple genetic models, some potential sources of heterogeneity, such as source of controls, lifestyle, and environmental exposures, were not explored. In addition, some cancer types included in this meta-analysis were investigated only in 1 or 2 studies (Supplementary Table S3), which led to heterogeneity in quantitative analysis. Second, the study results included in this meta-analysis were based on unadjusted analyses, and therefore, we could not estimate the risk of cancer with respect to environmental factors, age, family history, lifestyle, and other risk factors that might have influenced the pooled results. Third, we did not include any studies on the African population, and therefore, the results should be interpreted with caution when extrapolating them to the overall population. Lastly, the study with relative smaller sample size is more likely to be lack of sufficient statistical power to influence the overall results.

Our study represents a comprehensive meta-analysis of the role of IL-17A rs2275913 and IL-17F rs763780 polymorphisms in cancer risk. The results demonstrated that these two polymorphisms significantly increase the risk of development of cancer, particularly gastric cancer. Further large-scale, multicentre studies are required to confirm the pre-diagnostic effect of IL-17 gene polymorphisms on the risk of cancer.

Material and Methods

Identification of eligible studies

Systematic article search and quantitative analysis were performed, and written reports were generated according to the Meta-analysis of Observational Studies in Epidemiology guidelines48. Eligible studies with publication dates up to March 2015 were obtained through the Pubmed and Chinese National Knowledge Infrastructure (CNKI) databases. No language or geographical restriction was placed for study selection. The keywords search was performed with or without the Medical Subject Headings (MeSH) terms for: ‘interleukin-17/IL-17’, ‘polymorphism’, and ‘cancer’. Additionally, the references in the retrieved articles were manually screened for potential eligible studies.

Inclusion and exclusion criteria

Studies included in our meta-analysis were required to meet the following criteria: (1) a case-control design; (2) the study goal was to evaluate the association of IL17A rs2275913 and IL-17F rs763780 polymorphisms with cancer risk; (3) the study offered available information on genotype frequency, (4) the controls used had no malignant disease. The following were used as our exclusion criteria: (1) the study was a repeat studies, reviews, or abstracts; (2) the study design was based on family cancers; (3) the study did not include a control group; (4) the study did not investigate the effect of polymorphism; (5) duplicate data.

Data extraction

Two authors independently selected the potentially relevant studies for data extraction. We screened the titles and abstracts of the studies that met our inclusion criteria. If the content of the abstract was relevant, full articles were read to extract related information. For each eligible study included in our meta-analysis, we obtained information pertaining to first author, years of publication, country of origin, racial ancestry, cancer types, source of control, genotyping method, total number of cases and controls, and P value of Hardy–Weinberg equilibrium (HWE). All cancers were confirmed by histology or pathology. All the case and control groups were well controlled.

Resampling

We applied re-sampling statistic to examine the robustness of the associations, and 10000 re-sampling analyses were conducted using the bootstrap re-sampling procedure49. All the re-sampling analyses were performed by R 3.2.2 software using non-parametric bootstrapping method. The 95% confidence intervals (95% CIs) were estimated by bias-corrected and accelerated (BCa) and overall odds ratios (ORs) were calculated containing all samples under the five different genetic models.

Statistical analysis

The strength of association between IL-17A rs2275913 and IL-17F rs763780 polymorphisms and cancer risk was assessed as ORs with corresponding 95% CIs based on the allele frequencies in cases and controls of each study selected. The summary OR was calculated according to Woolf’s method. Five different ORs were calculated: dominant model (BB+AB vs. AA), recessive model (BB vs. AA+AB), homozygote comparison (BB vs. AA), heterozygote comparison (AB vs. AA) and allele comparison (B vs. A), the A represents the major allele, and the B represents the minor allele. The Chi-square-based Q statistic was implemented to assess heterogeneity among the studies50. The controls that departures of the HWE were evaluated for each study using chi-square test.

The effect of heterogeneity using I2 test statistical and significance was considered at P < 0.10. In case of a significant heterogeneity, the pooled ORs were analyzed using a random-effects model, otherwise a fixed-effects model should be used. To evaluate the ethnicity-specific and control-specific effects, subgroup analyses were conducted by source of controls, cancer types, controls whether satisfied HWE or not, and features of the population such as ethnicity. Additionally, to estimate the possible sources of bias, we considered the Egger’s test and Begg’s funnel plot. All statistical analyses were calculated with the software STATA (Version 11.0; Stata Corp, College Station, TX). P-values less than 0.05 were considered statistically significant.

Additional Information

How to cite this article: Dai, Z.-M. et al. Role of IL-17A rs2275913 and IL-17F rs763780 polymorphisms in risk of cancer development: an updated meta-analysis. Sci. Rep. 6, 20439; doi: 10.1038/srep20439 (2016).

Supplementary Material

Supplementary Information
srep20439-s1.pdf (13.5KB, pdf)

Acknowledgments

This study was supported by the National Natural Science Foundation of China (No. 81471670); China Postdoctoral Science Foundation (No. 2014M560791); the Fundamental Research Funds for the Central Universities, China (No. 2014qngz-04) and the Science and Technology Foundation of Shaanxi Province, China (No. 2014K11020107).

Footnotes

Author Contributions Z.-M.D. and T.-S.Z. contributed equally to the work. Z.-J.D. designed the study. Z.-M.D., S.L. and W.-G.Z. wrote the main manuscript text, J.L., X.-M.C. and M.W. prepared figures and tables, H.-B.L., Z.-J.D., X.-H.L., K.L. and S.-L.L. reviewed the manuscript.

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Supplementary Materials

Supplementary Information
srep20439-s1.pdf (13.5KB, pdf)

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