# Interleukin-17 Gene Polymorphisms Contribute to Cancer Risk

Authors: Yu-Ming Niu; Hua Yuan; Yu Zhou
Journal: Mediators of Inflammation
 (2014)

---

## Abstract

Epidemiological studies have suggested that interleukin-17 (IL-17) polymorphisms are associated with cancer risk. However, the results of these studies are inconsistent. Therefore, we performed a meta-analysis to obtain a precise conclusion. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the association of the IL-17A rs2275913G>A and IL-17F rs763780T>C polymorphisms with cancer risk. Publication bias and sensitivity analyses were performed to ensure the statistical power. Overall, 10 relevant case-control studies involving 4,516 cases and 5,645 controls were included. The pooled ORs with 95% CIs indicated that the IL-17A rs2275913G>A polymorphism was significantly associated with increased cancer risk (for A versus G: OR = 1.28, 95% CI: 1.16–1.41, P
<
0.001, I
2
=
61.1%; for GA versus GG: OR = 1.12, 95% CI: 1.02–1.23, P = 0.015, I
2
=
27.8%; for AA versus GG: OR = 1.71, 95% CI: 1.38–2.41, P
<
0.001, I
2
=
69.6%; for GA + AA versus GG: OR = 1.23, 95% CI: 1.13–1.34, P
<
0.001, I
2
=
6.4%; for AA versus GG + GA: OR = 1.62, 95% CI: 1.27–2.07, P
<
0.001, I
2
=
81.4%). Succeeding analysis of HWE and stratified analysis of gastric cancer and the Asian (and Chinese) population revealed similar results. The IL-17F rs763780T>C polymorphism was also significantly associated with gastric cancer development. Overall, the present meta-analysis suggests that IL-17 polymorphisms increase the risk of developing cancer, particularly gastric cancer, in the Asian (and Chinese) population.


---

## Body

## 1. Introduction

Cancer is one of the most common malignancies worldwide; it is the leading cause of death in economically developed countries and the second leading cause of death in developing countries [1]. Approximately 12.7 million new cases of cancer and 7.6 million cancer-related deaths were reported in 2008 [2]. Despite the efforts exerted by many researchers to elucidate the mechanism of carcinogenesis, this process remains unclear to date. Environmental factors, diet, lifestyle, and smoking and drinking habits have been implicated in the development of cancer [3, 4]. Various epidemiological studies have revealed that inflammation-associated factors, such as interleukin- (IL-) 1, IL-6, IL-10, and tumor necrosis factor-α, are associated with cancer tumorigenesis [5].Interleukin-17 (IL-17) is a proinflammatory cytokine that serves important functions in inflammation, autoimmune disorders, and cancer [6]. The IL-17 cytokine family consists of six members (IL-17A to IL-17F) and five receptors (IL-17RA to IL-17RD and SEF) [7, 8]. These cytokines are primarily produced from a subset of CD4+ effector cells known as Th17 cells [9, 10]. Clinical studies have shown increased IL-17 expression in malignant tumors [11–14].Single nucleotide polymorphisms (SNPs) can alter gene functions and protein expression, which influence cell proliferation and increase cancer risk. TheIL-17A rs2275913G>A andIL-17F rs763780T>C polymorphisms are the most common loci associated withIL-17activity and cancer risk. In 2009, Shibata et al. [15] conducted the first study and reported a positive relationship between gastric cancer and theIL-17A rs2275913G>A polymorphism in a Japanese population. But no significant association was found between gastric cancer and polymorphisms ofIL-17F rs763780 T>C. Many epidemiological studies have focused on the association of theIL-17A rs2275913G>A andIL-17F rs763780T>C polymorphisms with cancer risk. However, the results of these studies are inconsistent. Therefore, we performed a meta-analysis to clarify the possible association of theIL-17A rs2275913G>A andIL-17F rs763780T>C polymorphisms with cancer risk.


## 2. Materials and Methods

### 2.1. Search Strategy

The PubMed, Embase, and Chinese National Knowledge Infrastructure databases were searched using the terms “cancer,” “tumor,” “interleukin-17,” “IL-17,” and “polymorphism,” (last search was updated on January 20, 2014). The “Related Articles” option was also used in each research article to find potential relevant studies on the same topic. Only studies published in English or Chinese were included. The inclusion criteria in this meta-analysis were as follows: (a) researches that focused on population, (b) studies that evaluated the association of theIL-17A rs2275913G>A andIL-17F rs763780T>C polymorphisms with cancer risk, (c) case-controls studies, and (d) studies that contain available genotype frequency to estimate the odds ratio (OR) and 95% confidence intervals (CIs). The largest or the most recent publication was selected when some data were the same or overlapped.


### 2.2. Data Extraction

Two investigators (Yu-Ming Niu and Hua Yuan) independently extracted the following information from each eligible publication: first author’s name, publication year, country of origin, ethnicity of the individuals involved (categorized as Asian or Caucasian), source of controls, number of cases and controls, number of genotypes cases and controls, Hardy-Weinberg equilibrium (HWE) and minor allele frequency (MAF), and cancer category. Discrepancies were adjudicated by another author until consensus was achieved.


### 2.3. Statistical Analysis

The strength of the association of theIL-17A rs2275913G>A andIL-17F rs763780T>C polymorphisms with cancer risk was assessed by calculating crude ORs with 95% CIs. Pooled ORs were conducted for minor allele versus major allele with five models. Stratified analyses were performed by ethnicity, study design, and cancer category. Heterogeneity was calculated based on the I
2 statistic with low, moderate, and high I
2 values of 25%, 50%, and 75%, respectively [16, 17]. When I
2
≤
50% (which indicated a lack of heterogeneity), the OR estimation of each model was calculated by using the fixed-effects model (Mantel-Haenszel method); otherwise, the random-effects model (DerSimonian and Laird method) was used. We generated forest plots sorted by publication year. Potential publication bias was estimated using Egger’s linear regression test with funnel plot [18]. Sensitivity analyses were assessed by deleting each study to reflect the influence of individual datasets on the pooled ORs [19]. Statistical analysis was performed using STATA version 11.0 (Stata Corporation, College Station, TX, USA) with two-sided P values. P
<
0.05 was considered significant.


## 2.1. Search Strategy

The PubMed, Embase, and Chinese National Knowledge Infrastructure databases were searched using the terms “cancer,” “tumor,” “interleukin-17,” “IL-17,” and “polymorphism,” (last search was updated on January 20, 2014). The “Related Articles” option was also used in each research article to find potential relevant studies on the same topic. Only studies published in English or Chinese were included. The inclusion criteria in this meta-analysis were as follows: (a) researches that focused on population, (b) studies that evaluated the association of theIL-17A rs2275913G>A andIL-17F rs763780T>C polymorphisms with cancer risk, (c) case-controls studies, and (d) studies that contain available genotype frequency to estimate the odds ratio (OR) and 95% confidence intervals (CIs). The largest or the most recent publication was selected when some data were the same or overlapped.


## 2.2. Data Extraction

Two investigators (Yu-Ming Niu and Hua Yuan) independently extracted the following information from each eligible publication: first author’s name, publication year, country of origin, ethnicity of the individuals involved (categorized as Asian or Caucasian), source of controls, number of cases and controls, number of genotypes cases and controls, Hardy-Weinberg equilibrium (HWE) and minor allele frequency (MAF), and cancer category. Discrepancies were adjudicated by another author until consensus was achieved.


## 2.3. Statistical Analysis

The strength of the association of theIL-17A rs2275913G>A andIL-17F rs763780T>C polymorphisms with cancer risk was assessed by calculating crude ORs with 95% CIs. Pooled ORs were conducted for minor allele versus major allele with five models. Stratified analyses were performed by ethnicity, study design, and cancer category. Heterogeneity was calculated based on the I
2 statistic with low, moderate, and high I
2 values of 25%, 50%, and 75%, respectively [16, 17]. When I
2
≤
50% (which indicated a lack of heterogeneity), the OR estimation of each model was calculated by using the fixed-effects model (Mantel-Haenszel method); otherwise, the random-effects model (DerSimonian and Laird method) was used. We generated forest plots sorted by publication year. Potential publication bias was estimated using Egger’s linear regression test with funnel plot [18]. Sensitivity analyses were assessed by deleting each study to reflect the influence of individual datasets on the pooled ORs [19]. Statistical analysis was performed using STATA version 11.0 (Stata Corporation, College Station, TX, USA) with two-sided P values. P
<
0.05 was considered significant.


## 3. Results

### 3.1. Study Characteristics

A flow chart showing the study selection is presented in Figure1. A total of 185 relevant studies were found with the research words and manual research. After careful review, 10 published case-control studies involving 4,516 cases and 5,645 controls met our inclusion criteria [15, 20–28]. We found 10 and 7 eligible studies with adequate genotype and research subjects according toIL-17A rs2275913G>A andIL-17Frs763780T>C polymorphism. All characteristics of the selected studies are summarized in Table 1. Nine studies involved Asian populations (seven involved the Chinese population), and one study involved a Caucasian population. Diverse genotyping methods were used, including polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) [23, 27], TaqMan [21, 24, 28], polymerase chain reaction-sequence specific primers (PCR-SSCP) [15, 25], MassARRAY [20, 22], and SNaPshot SNP assay [26] methods in eligible publications. The genotypic distribution of controls in only two and three studies deviated from HWE in theIL-17A rs2275913G>A andIL-17F rs763780T>C polymorphisms, respectively.Table 1
Characteristics of case-control studies on IL-17A rs2275913G>A and IL-17F rs763780 T>C polymorphisms and cancer risk included in the meta-analysis.
First author
Year
Country
Ethnicity
Source of controls
Case
Control
Genotype distribution
Pfor HWEa
MAF
Genotyping method
Cancer category
Case
Control
G/G
G/A
A/A
G/G
G/A
A/A
Zhang [20]
2014
China
Asian
Population controls
260
512
110
102
48
258
187
67
<0.01
0.31
MassARRAY
Gastric cancer
Zhou [21]
2013
China
Asian
Hospital controls
301
446
79
154
68
164
204
78
0.29
0.40
TaqMan
Bladder cancer
Zhu [22]
2014
China
Asian
Hospital controls
293
550
126
122
45
273
216
61
0.07
0.31
MassARRAY
Gastric cancer
Rafiei [23]
2013
Iran
Caucasian
Healthy controls
161
171
56
61
44
78
72
21
0.49
0.33
PCR-RFLP
Gastric cancer
Quan [24]
2012
China
Asian
Hospital controls
311
463
93
142
76
168
215
80
0.43
0.40
TaqMan
Cervical cancer
Arisawa [25]
2012
Japan
Asian
Hospital controls
333
583
112
137
84
218
293
72
0.08
0.37
PCR-SSCP
Gastric cancer
Wang [26]
2012
China
Asian
Population controls
491
501
165
234
92
198
245
58
0.17
0.36
SNaPshot SNP assay
Breast cancer
Wu [27]
2010
China
Asian
Population controls
945
768
210
485
250
193
371
204
0.35
0.51
PCR-RFLP
Gastric cancer
Chen [28]
2010
China
Asian
Population controls
1042
1090
300
522
220
325
541
224
0.97
0.45
TaqMan
Gastric cancer
Shibata [15]
2009
Japan
Asian
Hospital controls
287
523
94
124
69
175
299
49
<0.01
0.38
PCR-SSCP
Gastric cancer
T/T
T/C
C/C
T/T
T/C
C/C
Zhang [20]
2014
China
Asian
Population controls
260
512
209
30
21
429
53
30
<0.01
0.11
MassARRAY
Gastric cancer
Zhou [21]
2013
China
Asian
Hospital controls
301
446
240
57
4
317
124
5
0.06
0.15
TaqMan
Bladder cancer
Zhu [22]
2014
China
Asian
Hospital controls
293
550
241
35
17
463
58
29
<0.01
0.11
MassARRAY
Gastric cancer
Quan [24]
2012
China
Asian
Hospital controls
311
462
222
85
4
332
126
5
0.06
0.15
TaqMan
Cervical cancer
Wang [26]
2012
China
Asian
Population controls
491
502
382
103
6
396
99
7
0.77
0.11
SNaPshot SNP assay
Breast cancer
Wu [27]
2010
China
Asian
Population controls
927
777
540
332
55
527
214
36
0.02
0.18
PCR-RFLP
Gastric cancer
Shibata [15]
2009
Japan
Asian
Hospital controls
280
523
221
55
4
419
100
4
0.46
0.10
PCR-SSCP
Gastric cancer
aHWE in control.
MAF: minor allele frequency in control group.Figure 1
Flow chart of study selection.


### 3.2. Quantitative Synthesis

Table2 shows the results of this meta-analysis and the heterogeneity test. TheIL-17A rs2275913G>A polymorphism showed significant associations with cancer risk in all populations (for A versus G: OR = 1.28, 95% CI: 1.16–1.41, P
<
0
.
001, I
2
=
61.1%; for GA versus GG: OR = 1.12, 95% CI: 1.02–1.23, P
=
0
.
0
15, I
2
=
27.8%; for AA versus GG: OR = 1.71, 95% CI: 1.38–2.41, P
<
0
.
001, I
2
=
69.6%; for GA + AA versus GG: OR = 1.23, 95% CI: 1.13–1.34, P
<
0
.
001, I
2
=
6.4% (Figure 2); and for AA versus GG + GA: OR = 1.62, 95% CI: 1.27–2.07, P
<
0
.
001, I
2
=
81.4%). The succeeding stratified analysis according to HWE, ethnicity, and study design subgroup also presented that theIL-17A rs2275913G>A polymorphism may be a strong risk factor in the development of cancer, especially gastric cancer, in the Chinese population.Table 2
Summary of ORs and 95% CI of IL-17A rs2275913G>A and IL-17F rs763780T>C polymorphisms and cancer risk.
N
*
A versus G
GA versus GG
AA versus GG
GA + AA versus GG
AA versus GG + GA
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)a
Total
10
1.28
1.16–1.41
<0.001
61.1
1.12
1.02–1.23
0.015
27.8
1.71
1.38–2.14
<0.001
69.6
1.23
1.13–1.34
<0.001
6.4
1.62
1.27–2.07
<0.001
81.4
HWE
8
1.26
1.13–1.41
<0.001
66.4
1.15
1.04–1.27
0.008
0
1.63
1.29–2.08
<0.001
70
1.23
1.12–1.36
<0.001
9.7
1.51
1.18–1.93
0.001
78.4
Ethnicity
Asian
9
1.25
1.14–1.37
<0.001
56.5
1.12
1.02–1.23
0.019
35.6
1.65
1.32–2.05
<0.001
68.6
1.22
1.12–1.33
<0.001
4.4
1.55
1.21–1.99
0.001
81.6
China
7
1.21
1.10–1.34
<0.001
56.2
1.19
1.07–1.32
0.001
0
1.46
1.20–1.79
<0.001
54.3
1.24
1.13–1.37
<0.001
14.9
1.30
1.09–1.56
0.004
56.6
Design
PB
4
1.16
1.01–1.32
0.031
63.3
1.14
1.01–1.29
0.041
0
1.34
1.02–1.76
0.033
65
1.18
1.05–1.32
0.006
1.1
1.23
0.96–1.59
0.108
69.7
HB
5
1.35
1.23–1.48
<0.001
0
1.10
0.87–1.39
0.447
63.1
1.97
1.64–2.37
<0.001
0
1.28
1.12–1.46
<0.001
11.8
1.87
1.38–2.52
<0.001
69.2
Location
Gastric
7
1.26
1.11–1.44
<0.001
70
1.07
0.96–1.19
0.202
24.2
1.70
1.26–2.30
0.001
77.8
1.18
1.06–1.30
0.001
0
1.67
1.18–2.36
0.004
87
Others
3
1.33
1.19–1.49
<0.001
0
1.27
1.05–1.53
0.013
6.6
1.81
1.43–2.29
<0.001
0
1.39
1.18–1.65
<0.001
0
1.56
1.27–1.91
<0.001
0
C versus T
TC versus TT
CC versus TT
TC + CC versus TT
CC versus TT + TC
Total
7
1.09
0.91–1.30
0.347
64.6
1.06
0.84–1.34
0.629
70
1.33
1.02–1.75
0.038
0
1.08
0.87–1.35
0.486
70.3
1.26
0.96–1.65
0.098
0
HWE
4
0.95
0.81–1.10
0.516
46.4
0.92
0.71–1.19
0.650
57.2
1.15
0.61–2.17
0.660
0
0.93
0.72–1.19
0.557
55.5
1.18
0.62–2.21
0.616
0
Ethnicity
China
6
1.08
0.88–1.33
0.439
70.4
1.06
0.81–1.39
0.676
74.7
1.32
1.00–1.74
0.053
0
1.08
0.84–1.39
0.555
75.1
1.24
0.94–1.63
0.130
0
Design
PB
3
1.29
1.13–1.41
<0.001
32.4
1.34
1.14–1.57
<0.001
43.4
1.40
1.01–1.96
0.045
0
1.34
1.05–1.57
<0.001
45.8
1.29
0.92–1.79
0.136
0
HB
4
0.97
0.77–1.21
0.550
52.2
0.92
0.69–1.22
0.554
57.3
1.20
0.74–1.94
0.466
0
0.84
0.72–1.23
0.643
58.1
1.20
0.74–1.94
0.456
0
Location
Gastric
4
1.29
1.14–1.46
<0.001
0
1.33
1.13–1.55
<0.001
21.6
1.40
1.04–1.88
0.026
0
1.34
1.16–1.55
<0.001
16
1.30
0.97–1.74
0.082
0
Others
3
0.91
0.70–1.18
0.472
57.4
0.88
0.62–1.24
0.460
69.2
1.02
0.50–2.08
0.962
0
0.89
0.64–1.22
0.461
66.7
1.04
0.51–2.13
0.905
0
*Numbers of comparisons.
aTest for heterogeneity.Figure 2
OR and 95% CIs for the association betweenIL-17A rs2275913G>A polymorphism with cancer risk for the GA + AA versus GG model.Statistical analysis also indicated that theIL-17F rs763780T>C polymorphisms were significantly associated with cancer risk, particularly gastric cancer (for C versus T: OR = 1.29, 95% CI: 1.14–1.46, P
<
0
.
001, I
2
=
0%; for TC versus TT: OR = 1.33, 95% CI: 1.13–1.55, P
<
0
.
001, I
2
=
21.6%; for CC versus TT: OR = 1.40, 95% CI: 1.04–1.88, P
=
0
.
026, I
2
=
0%; for TC + CC versus TT: OR = 1.34, 95% CI: 1.16–1.55, P
<
0
.
001, I
2
=
16% (Figure 3)).Figure 3
OR and 95% CIs for the association betweenIL-17F rs763780T>C polymorphisms and cancer risk in TC + CC versus TT model.


### 3.3. Sensitivity Analysis

A single study involved in the meta-analysis was deleted each time to reflect the influence of the individual data set on the pooled ORs, and the corresponding pooled ORs were not qualitatively altered. This indicated that the results about the association betweenIL-17 gene polymorphisms and cancer risk were statistically robust (Figures 4 and 5).Figure 4
Sensitivity analysis through deleting each study to reflect the influence of the individual dataset on the pooled ORs in GA + AA versus GG model ofIL-17A rs2275913G>A polymorphism.Figure 5
Sensitivity analysis through deleting each study to reflect the influence of the individual dataset on the pooled ORs in TC + CC versus TT model ofIL-17F rs763780T>C polymorphism.


### 3.4. Publication Bias

Funnel plot and Egger’s test were performed to estimate the publication bias of literature. Publication bias was detected in the meta-analyses on the allele contrast, homozygote (AA versus GG), dominant, and recessive models of theIL-17A rs2275913G>A polymorphism (Figure 6 for GA + AA versus GG model), except for the GA versus GG model (P
=
0.652). Stratified analyses were conducted only with the HWE and Chinese population, but the results were not substantially different. For theIL-17F rs763780T>C polymorphism, the funnel plots did not show any asymmetrical evidence in all genetic models (Figure 7). The result was further supported by analysis using Egger’s tests (P
=
0
.
102 for C versus T; P
=
0
.
185 for TC versus TT; P
=
0
.
382 for CC versus TT; P
=
0
.
114 for TC + CC versus TT (Figure 7); P
=
0
.
792 for CC versus TT + TC).Figure 6
Funnel plot analysis to detect publication bias for GA + AA versus GG model ofIL-17A rs2275913G>A polymorphism. Each point represents a separate study.Figure 7
Funnel plot analysis to detect publication bias for TC + CC versus TT model ofIL-17F rs763780T>C polymorphism. Each point represents a separate study.


## 3.1. Study Characteristics

A flow chart showing the study selection is presented in Figure1. A total of 185 relevant studies were found with the research words and manual research. After careful review, 10 published case-control studies involving 4,516 cases and 5,645 controls met our inclusion criteria [15, 20–28]. We found 10 and 7 eligible studies with adequate genotype and research subjects according toIL-17A rs2275913G>A andIL-17Frs763780T>C polymorphism. All characteristics of the selected studies are summarized in Table 1. Nine studies involved Asian populations (seven involved the Chinese population), and one study involved a Caucasian population. Diverse genotyping methods were used, including polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) [23, 27], TaqMan [21, 24, 28], polymerase chain reaction-sequence specific primers (PCR-SSCP) [15, 25], MassARRAY [20, 22], and SNaPshot SNP assay [26] methods in eligible publications. The genotypic distribution of controls in only two and three studies deviated from HWE in theIL-17A rs2275913G>A andIL-17F rs763780T>C polymorphisms, respectively.Table 1
Characteristics of case-control studies on IL-17A rs2275913G>A and IL-17F rs763780 T>C polymorphisms and cancer risk included in the meta-analysis.
First author
Year
Country
Ethnicity
Source of controls
Case
Control
Genotype distribution
Pfor HWEa
MAF
Genotyping method
Cancer category
Case
Control
G/G
G/A
A/A
G/G
G/A
A/A
Zhang [20]
2014
China
Asian
Population controls
260
512
110
102
48
258
187
67
<0.01
0.31
MassARRAY
Gastric cancer
Zhou [21]
2013
China
Asian
Hospital controls
301
446
79
154
68
164
204
78
0.29
0.40
TaqMan
Bladder cancer
Zhu [22]
2014
China
Asian
Hospital controls
293
550
126
122
45
273
216
61
0.07
0.31
MassARRAY
Gastric cancer
Rafiei [23]
2013
Iran
Caucasian
Healthy controls
161
171
56
61
44
78
72
21
0.49
0.33
PCR-RFLP
Gastric cancer
Quan [24]
2012
China
Asian
Hospital controls
311
463
93
142
76
168
215
80
0.43
0.40
TaqMan
Cervical cancer
Arisawa [25]
2012
Japan
Asian
Hospital controls
333
583
112
137
84
218
293
72
0.08
0.37
PCR-SSCP
Gastric cancer
Wang [26]
2012
China
Asian
Population controls
491
501
165
234
92
198
245
58
0.17
0.36
SNaPshot SNP assay
Breast cancer
Wu [27]
2010
China
Asian
Population controls
945
768
210
485
250
193
371
204
0.35
0.51
PCR-RFLP
Gastric cancer
Chen [28]
2010
China
Asian
Population controls
1042
1090
300
522
220
325
541
224
0.97
0.45
TaqMan
Gastric cancer
Shibata [15]
2009
Japan
Asian
Hospital controls
287
523
94
124
69
175
299
49
<0.01
0.38
PCR-SSCP
Gastric cancer
T/T
T/C
C/C
T/T
T/C
C/C
Zhang [20]
2014
China
Asian
Population controls
260
512
209
30
21
429
53
30
<0.01
0.11
MassARRAY
Gastric cancer
Zhou [21]
2013
China
Asian
Hospital controls
301
446
240
57
4
317
124
5
0.06
0.15
TaqMan
Bladder cancer
Zhu [22]
2014
China
Asian
Hospital controls
293
550
241
35
17
463
58
29
<0.01
0.11
MassARRAY
Gastric cancer
Quan [24]
2012
China
Asian
Hospital controls
311
462
222
85
4
332
126
5
0.06
0.15
TaqMan
Cervical cancer
Wang [26]
2012
China
Asian
Population controls
491
502
382
103
6
396
99
7
0.77
0.11
SNaPshot SNP assay
Breast cancer
Wu [27]
2010
China
Asian
Population controls
927
777
540
332
55
527
214
36
0.02
0.18
PCR-RFLP
Gastric cancer
Shibata [15]
2009
Japan
Asian
Hospital controls
280
523
221
55
4
419
100
4
0.46
0.10
PCR-SSCP
Gastric cancer
aHWE in control.
MAF: minor allele frequency in control group.Figure 1
Flow chart of study selection.


## 3.2. Quantitative Synthesis

Table2 shows the results of this meta-analysis and the heterogeneity test. TheIL-17A rs2275913G>A polymorphism showed significant associations with cancer risk in all populations (for A versus G: OR = 1.28, 95% CI: 1.16–1.41, P
<
0
.
001, I
2
=
61.1%; for GA versus GG: OR = 1.12, 95% CI: 1.02–1.23, P
=
0
.
0
15, I
2
=
27.8%; for AA versus GG: OR = 1.71, 95% CI: 1.38–2.41, P
<
0
.
001, I
2
=
69.6%; for GA + AA versus GG: OR = 1.23, 95% CI: 1.13–1.34, P
<
0
.
001, I
2
=
6.4% (Figure 2); and for AA versus GG + GA: OR = 1.62, 95% CI: 1.27–2.07, P
<
0
.
001, I
2
=
81.4%). The succeeding stratified analysis according to HWE, ethnicity, and study design subgroup also presented that theIL-17A rs2275913G>A polymorphism may be a strong risk factor in the development of cancer, especially gastric cancer, in the Chinese population.Table 2
Summary of ORs and 95% CI of IL-17A rs2275913G>A and IL-17F rs763780T>C polymorphisms and cancer risk.
N
*
A versus G
GA versus GG
AA versus GG
GA + AA versus GG
AA versus GG + GA
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)a
Total
10
1.28
1.16–1.41
<0.001
61.1
1.12
1.02–1.23
0.015
27.8
1.71
1.38–2.14
<0.001
69.6
1.23
1.13–1.34
<0.001
6.4
1.62
1.27–2.07
<0.001
81.4
HWE
8
1.26
1.13–1.41
<0.001
66.4
1.15
1.04–1.27
0.008
0
1.63
1.29–2.08
<0.001
70
1.23
1.12–1.36
<0.001
9.7
1.51
1.18–1.93
0.001
78.4
Ethnicity
Asian
9
1.25
1.14–1.37
<0.001
56.5
1.12
1.02–1.23
0.019
35.6
1.65
1.32–2.05
<0.001
68.6
1.22
1.12–1.33
<0.001
4.4
1.55
1.21–1.99
0.001
81.6
China
7
1.21
1.10–1.34
<0.001
56.2
1.19
1.07–1.32
0.001
0
1.46
1.20–1.79
<0.001
54.3
1.24
1.13–1.37
<0.001
14.9
1.30
1.09–1.56
0.004
56.6
Design
PB
4
1.16
1.01–1.32
0.031
63.3
1.14
1.01–1.29
0.041
0
1.34
1.02–1.76
0.033
65
1.18
1.05–1.32
0.006
1.1
1.23
0.96–1.59
0.108
69.7
HB
5
1.35
1.23–1.48
<0.001
0
1.10
0.87–1.39
0.447
63.1
1.97
1.64–2.37
<0.001
0
1.28
1.12–1.46
<0.001
11.8
1.87
1.38–2.52
<0.001
69.2
Location
Gastric
7
1.26
1.11–1.44
<0.001
70
1.07
0.96–1.19
0.202
24.2
1.70
1.26–2.30
0.001
77.8
1.18
1.06–1.30
0.001
0
1.67
1.18–2.36
0.004
87
Others
3
1.33
1.19–1.49
<0.001
0
1.27
1.05–1.53
0.013
6.6
1.81
1.43–2.29
<0.001
0
1.39
1.18–1.65
<0.001
0
1.56
1.27–1.91
<0.001
0
C versus T
TC versus TT
CC versus TT
TC + CC versus TT
CC versus TT + TC
Total
7
1.09
0.91–1.30
0.347
64.6
1.06
0.84–1.34
0.629
70
1.33
1.02–1.75
0.038
0
1.08
0.87–1.35
0.486
70.3
1.26
0.96–1.65
0.098
0
HWE
4
0.95
0.81–1.10
0.516
46.4
0.92
0.71–1.19
0.650
57.2
1.15
0.61–2.17
0.660
0
0.93
0.72–1.19
0.557
55.5
1.18
0.62–2.21
0.616
0
Ethnicity
China
6
1.08
0.88–1.33
0.439
70.4
1.06
0.81–1.39
0.676
74.7
1.32
1.00–1.74
0.053
0
1.08
0.84–1.39
0.555
75.1
1.24
0.94–1.63
0.130
0
Design
PB
3
1.29
1.13–1.41
<0.001
32.4
1.34
1.14–1.57
<0.001
43.4
1.40
1.01–1.96
0.045
0
1.34
1.05–1.57
<0.001
45.8
1.29
0.92–1.79
0.136
0
HB
4
0.97
0.77–1.21
0.550
52.2
0.92
0.69–1.22
0.554
57.3
1.20
0.74–1.94
0.466
0
0.84
0.72–1.23
0.643
58.1
1.20
0.74–1.94
0.456
0
Location
Gastric
4
1.29
1.14–1.46
<0.001
0
1.33
1.13–1.55
<0.001
21.6
1.40
1.04–1.88
0.026
0
1.34
1.16–1.55
<0.001
16
1.30
0.97–1.74
0.082
0
Others
3
0.91
0.70–1.18
0.472
57.4
0.88
0.62–1.24
0.460
69.2
1.02
0.50–2.08
0.962
0
0.89
0.64–1.22
0.461
66.7
1.04
0.51–2.13
0.905
0
*Numbers of comparisons.
aTest for heterogeneity.Figure 2
OR and 95% CIs for the association betweenIL-17A rs2275913G>A polymorphism with cancer risk for the GA + AA versus GG model.Statistical analysis also indicated that theIL-17F rs763780T>C polymorphisms were significantly associated with cancer risk, particularly gastric cancer (for C versus T: OR = 1.29, 95% CI: 1.14–1.46, P
<
0
.
001, I
2
=
0%; for TC versus TT: OR = 1.33, 95% CI: 1.13–1.55, P
<
0
.
001, I
2
=
21.6%; for CC versus TT: OR = 1.40, 95% CI: 1.04–1.88, P
=
0
.
026, I
2
=
0%; for TC + CC versus TT: OR = 1.34, 95% CI: 1.16–1.55, P
<
0
.
001, I
2
=
16% (Figure 3)).Figure 3
OR and 95% CIs for the association betweenIL-17F rs763780T>C polymorphisms and cancer risk in TC + CC versus TT model.


## 3.3. Sensitivity Analysis

A single study involved in the meta-analysis was deleted each time to reflect the influence of the individual data set on the pooled ORs, and the corresponding pooled ORs were not qualitatively altered. This indicated that the results about the association betweenIL-17 gene polymorphisms and cancer risk were statistically robust (Figures 4 and 5).Figure 4
Sensitivity analysis through deleting each study to reflect the influence of the individual dataset on the pooled ORs in GA + AA versus GG model ofIL-17A rs2275913G>A polymorphism.Figure 5
Sensitivity analysis through deleting each study to reflect the influence of the individual dataset on the pooled ORs in TC + CC versus TT model ofIL-17F rs763780T>C polymorphism.


## 3.4. Publication Bias

Funnel plot and Egger’s test were performed to estimate the publication bias of literature. Publication bias was detected in the meta-analyses on the allele contrast, homozygote (AA versus GG), dominant, and recessive models of theIL-17A rs2275913G>A polymorphism (Figure 6 for GA + AA versus GG model), except for the GA versus GG model (P
=
0.652). Stratified analyses were conducted only with the HWE and Chinese population, but the results were not substantially different. For theIL-17F rs763780T>C polymorphism, the funnel plots did not show any asymmetrical evidence in all genetic models (Figure 7). The result was further supported by analysis using Egger’s tests (P
=
0
.
102 for C versus T; P
=
0
.
185 for TC versus TT; P
=
0
.
382 for CC versus TT; P
=
0
.
114 for TC + CC versus TT (Figure 7); P
=
0
.
792 for CC versus TT + TC).Figure 6
Funnel plot analysis to detect publication bias for GA + AA versus GG model ofIL-17A rs2275913G>A polymorphism. Each point represents a separate study.Figure 7
Funnel plot analysis to detect publication bias for TC + CC versus TT model ofIL-17F rs763780T>C polymorphism. Each point represents a separate study.


## 4. Discussion

Carcinogenesis is a multistep process that involves numerous factors, such as smoking, drinking, xenobiotics infections, nutrition deficiency, and host genetic factor. Cancer-related inflammation factors have been recently confirmed to increase the risk of developing malignant tumors. IL-17 is a relatively novel cytokine family that is connected with adaptive and innate immune systems. IL-17A and IL-17F are members of the IL-17 cytokine family that are responsible for the pathogenic activity of IL-17 cells, the lineage of CD4+ effector cells, and multiple proinflammatory mediators [29].Genetic polymorphisms of the IL-17A and IL-17F cytokines could change the function and expression of cytokines, which influence the activity of ILs [12, 30, 31]. Several studies have revealed thatIL-17A andIL-17F polymorphisms are associated with gastric cancer, breast cancer, and so on. However, the results of these studies are inconsistent.In 2009, Shibata et al. [15] were the first to report that the AA homozygote was significantly correlated with the development of gastric cancer compared with the common homozygous genotype (GG) in a Japanese population (OR = 3.02, 95% CI: 1.86–4.91). One year later, Chen et al. [28] also found a positive relationship between gastric cancer and theIL-17A rs2275913G>A polymorphism in a Chinese Han population with a drinking habit (for A versus G: OR = 1.37, 95% CI: 1.07–1.76). Similar results were reported by Arisawa et al. [25], Rafiei et al. [23], Zhang et al. [20], and Zhuet al. [22] in gastric cancer. Furthermore, the mutation ofIL-17A rs2275913G>A locus was also demonstrated as tumorigenic for bladder cancer [21], breast cancer [26], and cervical cancer [24]. However, another article detected no significant association between theIL-17Ars2275913G>A polymorphism and gastric cancer risk [27].Regarding theIL-17F rs763780T>C polymorphism, Wu et al. [27] found that the CT and CC genotypes are associated with an increased risk of gastric cancer compared with the TT genotype (OR = 1.51, 95% CI: 1.22–1.87 for CT; OR = 1.61, 95% CI: 1.03–2.51 for CC). By contrast, Zhou et al. [21] showed that bladder cancer patients have significantly higher frequencies of T allele than controls. This result indicates that this T allele is significantly associated with bladder cancer (OR = 1.46, 95% CI: 1.07–2.00). Furthermore, other researches did not find any significant association between theIL-17F rs763780T>C polymorphism and cancer risk [15, 20, 22, 24, 26].To the best of our knowledge, this meta-analysis is the first to determine the association ofIL-17 polymorphisms with cancer risk. This study focused on two commonIL-17 polymorphisms, namely,IL-17A rs2275913G>A (10 studies with 4,516 cases and 5,645 controls) andIL-17F rs763780T>C (7 studies with 2,863 cases and 3,773 controls). Significant associations were found between theIL-17A rs2275913G>A polymorphism and cancer risk in all five genotype models of total populations. Besides, we also detected some association between theIL-17F rs763780T>C polymorphism and the risk of Asians (Chinese), population-based and hospital-based controls, and gastric cancer or other cancers in the subgroup analysis by HWE publications, ethnicity, control design, and cancer category. Interestingly, nine researches focused on Asian population; the results of our meta-analysis demonstrated that theIL-17A rs2275913G>A polymorphism may be a stranger canner risk for Asian ethnicity (including Chinese). Moreover, the category of control design did not influence the results; not only the population-based but also the hospital-based controls all showed that significant association existed betweenIL-17A rs2275913G>A polymorphism and cancer risk. In all selected publications, seven studies focused on gastric cancer and the results also indicated thatIL-17A rs2275913G>A polymorphism plays an important role during the development of gastric cancer. ForIL-17F rs763780T>C polymorphism, all selected studies were conducted in Asian population and significant association only was found in codominant model (CC versus TT) in total population. Furthermore, subgroup analyses revealed a significantly increased risk of gastric cancer withIL-17F rs763780T>C polymorphism in four models. Another stratified analysis of population-based control also drew a consistent conclusion.This meta-analysis has several limitations in result interpretation. First, each gene only has a moderate effect on cancer development. A combination of relative genotypes may be a higher risk factor than a single locus genotype. Linkage disequilibrium and haplotype analyses of the two polymorphisms were not conducted because of the lack of original data on the individual genotypes from the included studies. Second, certain publication biases existed until subgroup analyses were conducted. These deviations would influence the correctness and reliability of the results. Third, these results were based on unadjusted estimates, and the evaluations were limited without the effects of gene-gene and gene-environment interactions. Finally, most of the included studies had been conducted on Asians but not on Caucasians and Africans, and the association between ethnicity variation and cancer risk could not be explored deeply.In conclusion, despite these limitations, the present meta-analysis demonstrates that theIL-17A rs2275913G>A polymorphism is associated with cancer development. Furthermore, theIL-17F rs763780T>C polymorphism may be a potential risk factor in the development of gastric cancer. In the future, large-scale, case-control, and well-designed studies must be conducted to validate the findings of our meta-analysis and to comprehensively understand the potential gene-gene and gene-environment interactions betweenIL-17 polymorphisms and cancer risk.



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*Source: 128490-2014-07-24.xml*