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Arquivos de Gastroenterologia

Print version ISSN 0004-2803On-line version ISSN 1678-4219

Arq. Gastroenterol. vol.55 no.3 São Paulo July/Sept. 2018

http://dx.doi.org/10.1590/s0004-2803.201800000-66 

REVIEW

ASSOCIATION OF PROMOTER REGION POLYMORPHISMS OF INTERLEUKIN-10 GENE WITH SUSCEPTIBILITY TO COLORECTAL CANCER: A SYSTEMATIC REVIEW AND META-ANALYSIS

Associação de polimorfismos da região do promotor do gene interleucina-10 com susceptibilidade ao câncer colorretal: uma revisão sistemática e meta-análise

Seyed Alireza MIRJALILI1 

Mansour MOGHIMI2 
http://orcid.org/0000-0002-4000-9953

Kazem AGHILI3 

Mohammadali JAFARI4 

Seyed Mojtaba ABOLBAGHAEI5 

Hossein NEAMATZADEH1 

Mahta MAZAHERI1 

Masoud ZARE-SHEHNEH1 

1Shahid Sadoughi University of Medical Sciences, Department of Medical Genetics, Yazd, Iran.

2Shahid Sadoughi University of Medical Sciences, Department of Pathology, Yazd, Iran.

3Shahid Sadoughi University of Medical Sciences, Department of Radiology, Yazd, Iran.

4Shahid Sadoughi University of Medical Sciences, Department of Emergency Medicine, Yazd, Iran.

5Shahid Beheshti University of Medical Sciences, Department of Forensic Medicine, Tehran, Iran.

ABSTRACT

BACKGROUND:

Several epidemiological studies have investigated the association of promoter region polymorphisms of Interleukin-10 (IL-10) gene with colorectal cancer (CRC), while the conclusion is still conflicting and inconclusive.

OBJECTIVE:

We conducted this meta-analysis to evaluate the association of promoter region polymorphisms of IL-10 with CRC.

METHODS:

Eligible articles were identified by a search of several bibliographic databases for the period up to March 15, 2018. The strength of the association was measured by odd ratios with 95% confidence intervals.

RESULTS:

A total of 28 case-control studies with 5,647 CRC cases and 6,908 controls were selected, including 14 studies for IL-10 -1082A>G (rs1800896) polymorphism (2,702 cases and 3,649 controls), eleven studies for -592C>A (rs1800872) polymorphism (3,259 cases and 4,992 controls), and three studies for -819T>C (rs1800871) polymorphism (477 cases and 544 controls). By pooling all eligible studies, we found that the IL-10 -1082A>G and -592C>A polymorphisms were not associated with increased CRC risk in overall population. However, there was significant associations between the IL-10 -819T>C polymorphism and CRC susceptibility under the allele model (A vs G: OR=1.278, 95% CI 1.043-1.566, P=0.018) and the recessive model (AA vs AG+GG: OR=1.709, 95% CI 1.026-2.845, P=0.039).

CONCLUSION:

In this meta-analysis we found that IL-10 -819T>C polymorphism was associated with significantly increased risk of CRC; while the IL-10 -1082A>G and -592C>A polymorphisms were not associated with CRC risk. The IL-10 -819T>C polymorphism may be important as suspected predictive factor of CRC occurrence.

HEADINGS: Interleukin-10; Colorectal neoplasms; Genetic polymorphism; Meta-analysis

RESUMO

CONTEXTO:

Vários estudos epidemiológicos têm investigado a associação de polimorfismo da região promotora do gene interleucina-10 (IL-10) com câncer colorretal (CRC), mas por enquanto a conclusão ainda é conflitante e inconclusiva.

OBJETIVO:

Foi realizada esta meta-análise para avaliar a associação de polimorfismo da região promotora do Il-10 com o câncer colorretal.

MÉTODOS:

Os artigos elegíveis foram identificados por uma pesquisa de várias bases de dados bibliográficas para o período até 15 de março de 2018. A força da associação foi medida por odds ratio (OR) com intervalos de 95% de confiança (IC).

RESULTADOS:

Um total de 28 estudos de casos-controles com 5.647 casos de câncer colorretal e 6.908 controles foram selecionados, incluindo 14 estudos para o polimorfismo de IL-10-1082A>G (rs1800896) (2.702 casos e 3.649 controles), 11 estudos para-592C>A (rs1800872) polimorfismo (3.259 casos e 4.992 controles), e três estudos para-819T>C (rs1800871) polimorfismo (477 casos e 544 controles). Ao reunir todos os estudos elegíveis, verificou-se que o Il-10-1082A>G e-592C>A polimorfismo não foram associados com o aumento do risco de câncer colorretal na população global. No entanto, houve associações significativas entre o polimorfismo IL-10-819T>C e a susceptibilidade de câncer colorretal o modelo alelo (A vs G: OR=1,278; 95% CI 1,043-1,566; P=0,018) e o modelo recessivo (AA vs AG + GG: ou =1,709; 95% CI 1,026-2,845; P=0,039).

CONCLUSÃO:

Nesta meta-análise revelou-se que o polimorfismo IL-10-819T>C foi associado a um risco significativamente maior de câncer colorretal; enquanto o Il-10-1082A>G e-592C>A polimorfismos não foram associados com o risco de câncer colorretal. O polimorfismo IL-10-819T>C pode ser importante como fator preditivo suspeito da ocorrência de câncer colorretal.

DESCRITORES: Interleucina-10; Neoplasias colorretais; Polimorfismo genético; Metanálise

INTRODUCTION

Colorectal cancer (CRC) ranks among the three most common cancers in terms of both cancer incidence and cancer-related deaths worldwide1-4. CRC is the cancer of the colon and the rectum and approximately two thirds are located in the colon. Differences in the CRC death rates relate to differences in socioeconomic factors, diet, population life span, genetic factors, and to the quality of medical care available5,6. The most common risk factors for to CRC include age, the presence of polyps, inflammatory bowel disease, lifestyle, genetic background and family medical history7. Life style relating factors such as obesity, physical inactivity, poor diet, cigarette smoking and heavy alcohol consumption account for approximately 80% of all colorectal cancer cases8. The sequence of genetic alterations in CRC development is well documented9. Genetic conditions such as familial adenomatous polyposis (FAP), Lynch syndrome (HNPCC; hereditary nonpolyposis colorectal cancer) and Gardner’s syndrome (considered a subtype of FAP) are genetic risk factors10, which accounts for 10% of all colorectal cancer cases11.

Several cytokines that modulate the immunologic response have been implicated in the development of cancer12. Interleukin-10 (IL-10) is a multifunctional cytokine involved in both innate and adaptive immune response, and a wealth of evidence supports its regulatory role in carcinogenesis and tumor growth13,14. In addition, increased circulating IL10 has been shown in patients diagnosed with different malignancies, such as hepatocellular carcinoma, autoimmune cancers, and leukemia. The IL10 gene (Gene ID: 3586) has been mapped to human chromosome 1q31-q32, spans 5.2 kb and contains five exons14. Many SNPs in the promoter and coding region of IL-10 gene were shown to be associated with cancer risk, and also, studies have showed that the genetic variants played important roles in the transcription and protein expression15.

It is well known that IL-10 gene production can be influenced by the SNPs located within the promoter regions of the gene15,16. The IL-10 promoter is highly polymorphic and three single nucleotide polymorphisms (SNPs) have been confirmed in the promoter region of IL-10 including IL-10 -1082A>G (rs1800896), -592C>A (rs1800872) and -819T>C (rs1800871). In recent decade, accumulating evidence has supported the hypothesis that the promoter region of IL-10 polymorphisms correlates with genetic susceptibility of CRC16,17. However, the results from the studies were often inconsistent and inconclusive. This inconsistency may derive from a number of issues, including limited sample size of single study, different characteristics among studies (such as ethnicity, pathological types, and sources of controls), false-positive errors, lack of power, and minor impacts of IL-10 gene polymorphisms on CRC susceptibility. Therefore, we performed a meta-analysis to comprehensively assess the association of promoter region polymorphisms of IL-10 with CRC risk.

METHODS

Identification of eligible studies

The present meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. We carried out a search in the internet covering well-known biomedical databases such as PubMed, Excerpta Medica Database (EMBASE), Elsevier Science Direct, Cochrane Library, and Chinese Biomedical Literature Database (CBM) regarding the association of IL-10 polymorphisms with CRC risk up to March 15, 2018. The following keywords were used for searching: (‘‘Interleukin- 10’’ OR ‘‘IL-10’’) AND (‘’colorectal cancer’’ OR ‘’CRC’’ OR ‘colon cancer’’) AND (‘’promoter region’’ OR ‘’promoter’’) AND (‘‘polymorphism’’ OR ‘‘mutation’’ OR ‘‘genotype’’ OR ‘‘allele’’ OR ‘‘variation’’ OR ‘‘variant’’). All searched studies were retrieved and the bibliographies were checked for other relevant publications. Review articles and bibliographies of other relevant studies identified were hand searched to find additional eligible studies. We also conducted a manual search of references of original or reviewed articles on this subject to identify additional studies. No language restrictions were applied. Abstracts, case reports and editorials were excluded.

Inclusion criteria

The following criteria were used for the literature selection: (1) evaluating the association between promoter region polymorphisms of IL-10 and CRC risk; (2) case-control or cohort studies comparing CRC cases with healthy or non-cancer controls; (3) the numbers of CRC case and healthy subjects for each genotype were reported or the relevant data was available, and adequate data was provided for calculating the pooled odds ratios (OR) with 95% confidence intervals (CI). Studies was excluded if they were the following: (1) case-only studies; (2) animal studies, abstracts, seminar posters, case reports, letters, or reviews; (3) incomplete data or no usable data were reported; (4) duplicated or studies containing overlapping data; (5) family-based design studies. After deliberate searching, we reviewed all papers in accordance with the criteria defined above for further analysis.

Data extraction

Information was carefully extracted from all eligible papers by two of the authors independently according to the inclusion criteria mentioned above. Data included the following: first author, publication year, country, cancer type, source of control, each genotype frequency of the case and control groups, genotype methods, and the Hardy-Weinberg equilibrium (HWE) value in the control group. Disagreement was resolved by discussion until consensus was reached. If these two authors could not reach a consensus, then a third author was consulted to resolve the dispute.

Statistical analysis

The strength of the association between the IL-10 polymorphisms and the risk of CRC was measured by odd ratios (ORs) with 95% confidence intervals (CI). Z-test was carried out to evaluate the statistical significance of pooled ORs. The pooled ORs were performed for the allele model (B vs A), homozygote model (BB vs AA), heterozygote model (BA vs AA), dominant model (BB + BA vs AA) and recessive model (BB vs BA + AA), respectively. The heterogeneity between studies was assessed with the chi-squared based Q-test. A significant P value (<0.10) was used to indicate heterogeneity among studies. Moreover, the I2 statistic to quantify the proportion of the total variation due to heterogeneity were used, according to the criteria from the Cochrane Handbook, which categorized it into unimportant (0%-40%), moderate (30%-60%), substantial (50%-90%) and considerable (75%-100%). When the effects were assumed to be homogenous, the fixed-effects model was used (Mantel-Haenszel method)18. If obvious heterogeneity was present, the random effects model was used (DerSimonian-Laird method)19. Stratification and meta-regression analyses were used to detect the potential heterogeneity among studies. In case-control studies, Hardy-Weinberg equilibrium (HWE) was tested using an online program (http://ihg2.helmholtz-muenchen.de/cgi-bin/hw/hwa1.pl) to evaluate the study quality of genotype data, and P<0.05 was considered statistically significant. A high-quality study was said that its control group was in HWE. Sensitivity analysis by sequentially omitting the single studies and recounting the pooled ORs and 95% confidence intervals (CIs) was performed to estimate the effect of individual studies on overall risk of CRC. The funnel plot was utilized to test the publication bias and Egger’s test (linear regression analysis) was used to check the symmetry of funnel plots20,21. The statistical analysis for the current meta-analysis study was performed by using the comprehensive meta-analysis (CMA) version 2.0 software (Biostat, USA). All P-values in the meta-analysis were two-sided, and statistical significance was considered when the P-value was less than 0.05.

RESULTS

The initial search of online databases yielded 253 relevant articles, and an additional 4 articles were identified through manually search. A total of 157 articles were excluded after reading the title or abstract because of obvious irrelevance to our criteria, lack of data for calculation and duplication. Finally, a total of 28 case-control studies in 17 publications22-38 with 5,647 CRC cases and 6,908 controls were selected for the current meta-analysis, including 14 studies22-35 for IL-10 -1082A>G (rs1800896) polymorphism (2,702 cases and 3,649 controls), eleven case-control studies22,23,25,26,28,29,32,34,36-38 for -592C>A (rs1800872) polymorphism (3,259 cases and 4,992 controls), and three case-control studies24,25,28 for -819T>C (rs1800871) polymorphism (477 cases and 544 controls). All of these 28 case-control studies provided sufficient data to calculate the possible relationship between the three polymorphisms of the IL-10 gene and CRC risk. The baseline characteristics of the case-control studies are shown in Table 1. Two ethnicities were addressed: 24 studies focused on Caucasian populations and four on Asian populations. The countries of these studies included Scotland, Italy, USA, Spain, Romania, Brazil, Canada, China, India, Korea, Egypt, and Turkey. Three genotyping methods were applied in the present case-control studies such as TaqMan, ARMS-PCR, Sequencing, AS-PCR, MassARRAY, PCR-RFLP, and KASP assay. The distribution of genotypes in the controls was consistent with the HWE for all selected studies, except for three case-control studies for IL-10 -1082A>G24,28,33.

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

First Country SOC Genotyping Case/Control Cases Controls MAFs HWE
Author/Year (Ethnicity) Technique Genotypes Allele Genotypes Allele
IL10 -1082A>G (rs1800896) AA AG GG A G AA AG GG A G
Macarthur 200522 Scotland (Caucasian) PB TaqMan 257/403 61 125 71 247 267 86 202 115 374 432 0.536 0.877
Crivello 200623 Italy (Caucasian) PB ARMS-PCR 62/124 16 34 12 66 58 38 60 26 136 112 0.451 0.796
Guntar 200624 USA (Caucasian) HB TaqMan 222/207 61 114 47 236 208 55 123 29 233 181 0.437 0.002
Cozar 2007 25 Spain (Caucasian) PB TaqMan 126/175 42 62 22 146 106 58 87 30 203 147 0.420 0.787
Talseth 200726 Mixed (Caucasian)* HB Sequencing 118/100 36 61 21 133 103 33 50 17 116 84 0.420 0.792
Wilkening 200827 Sweden (Caucasian) PB TaqMan 304/579 83 146 75 312 296 164 283 132 611 547 0.472 0.639
Cacev 200828 Croatia (Caucasian) PB TaqMan 160/160 54 86 20 194 126 43 92 25 178 142 0.443 0.037
Tsilidis 2009 29 USA (Caucasian) PB TaqMan 205/372 69 101 35 239 171 98 187 87 383 361 0.485 0.903
Miteva 201430 Bulgaria (Caucasian) PB ARMS-PCR 119/154 40 57 22 137 101 54 79 21 187 121 0.392 0.349
Burada 201331 Romania (Caucasian) HB TaqMan 144/233 65 60 19 190 98 80 118 35 278 188 0.403 0.426
Basavaraju 201532 Scotland (Caucasian) PB TaqMan 388/496 58 210 92 351 394 103 261 130 471 521 0.527 0.183
Li 201533 China (Asian) HB AS-PCR 102/105 26 66 10 118 86 20 77 8 117 93 0.442 ≤0.001
Cai 201634 China (Asian) HB MassARRAY 375/382 323 50 2 696 54 343 39 0 725 39 0.051 0.293
Gulubova 201835 Bulgaria (Caucasian) NS ARMS-PCR 120/159 47 57 16 151 89 59 78 22 196 122 0.383 0.638
IL-10 -592C>A (rs1800872) CC AC AA C A CC AC AA C A
Macarthur 200522 Scotland (Caucasian) PB TaqMan 258/403 151 99 8 401 115 248 133 22 629 177 0.219 0.455
Crivello 200623 Italy (Caucasian) PB ARMS-PCR 62/124 31 28 3 90 34 69 48 7 186 62 0.250 0.719
Talseth 200726 Mixed (Caucasian) HB Sequencing 117/99 62 51 4 175 59 50 45 4 145 53 0.267 0.112
Vogel 200736 Danish (Caucasian) PB TaqMan 355/753 224 109 22 557 153 455 256 42 1166 340 0.225 0.450
Cozar 200725 Spain (Caucasian) PB TaqMan 95/175 52 41 2 145 45 98 63 14 259 91 0.260 0.393
Cacev 200828 Croatia (Caucasian) PB PCR-RFLP 160/160 83 64 13 230 90 104 52 4 260 60 0.187 0.399
Tsilidis 200929 USA (Caucasian) PB TaqMan 203/361 123 71 9 317 89 213 131 17 557 165 0.228 0.579
Andersen 201236 Danish (Caucasian) PB KASP assay 949/1748 596 297 56 1489 409 1072 580 96 2724 772 0.226 0.134
Yu 201438 China (Asian) PB PCR-RFLP 298/291 153 114 31 420 176 118 135 38 371 211 0.362 0.949
Basavaraju 201532 Scotland (Caucasian) HB TaqMan 387/496 241 134 12 616 158 311 168 17 790 202 0.203 0.323
Cai 201634 China (Asian) HB MassARRAY 375/382 221 128 26 570 180 184 158 40 526 238 0.311 0.484
IL-10 -819T>C (rs1800871) TT TC CC T C TT TC CC T C
Guntar 200624 USA (Caucasian) HB TaqMan 222/209 125 76 21 326 118 117 79 13 313 105 0.251 0.944
Cozar 2007 25 Spain (Caucasian) PB TaqMan 95/175 81 37 9 199 55 98 63 14 259 91 0.260 0.393
Cacev 2008 28 Croatia (Caucasian) PB PCR-RFLP 160/160 83 64 13 230 90 106 51 3 263 57 0.178 0.262

SOC: source of control, PB: Population based; HB: hospital based; NA: not available; PCR: Polymerase chain reaction; ASPCR: Allele-specific PCR; RFLP: restriction fragment length polymorphism; MAF: minor allele frequency; HWE: Hardy-Weinberg equilibrium. * Australia and Poland.

Quantitative synthesis

The evaluation of the associations of IL-10 -1082A>G, -592C>A and -819T>C polymorphisms with CRC risk are presented in Table 2. The results showed that no association of IL-10 polymorphism was observed with the risk of CRC in five genetic models, i.e., allele (A vs G: OR=0.9623, 95% CI 0.893-1.038, P=0.318, Figure 1.A), homozygote (AA vs GG: OR=0.983, 95% CI 0.836-1.155, P=0.835), heterozygote (AC vs GG: OR=0.953, 95% CI 0.843-1.078, P=0.444), dominant (AA+AG vs GG: OR=0.921, 95% CI 0.821-1.034, P=0.165) and recessive model (AA vs AG+GG: OR=0.986, 95% CI 0.861-1.129, P=0.839).

Table 2 listed the main results of the meta-analysis of IL-10 polymorphism and CRC risk. When all the eligible studies were pooled into the meta-analysis of IL-10 polymorphism, significantly increased risk of CRC was observed in all the five genetic comparison models, i.e., allele (A vs G: OR=1.497, 95% CI 0.838-1.064, P=0.349), homozygote (AA vs GG: OR=2.153, 95% CI 0.705-1.047, P=0.132), heterozygote (AC vs GG: OR=1.494, 95% CI 0.826-1.094, P=0.481), dominant (AA+AG vs GG: OR=1.584, 95% CI 0.693-1.145, P=0.368, Figure 1.B) and recessive (AA vs AG+GG: OR=1.753, 95% CI 0.747-1.099, P=0.319).

FIGURE 1.A Forest plots for association of IL-10 -1082A>G and -592C>A polymorphisms with CRC risk. (A) -1082A>G under allele model (G vs. A). 

FIGURE 1.B 592C>A under dominant model (AA+AC vs. CC). 

Table 2 listed the main results of the meta-analysis of IL-10 -819T>C (rs1800871) polymorphism and CRC risk. When all the eligible studies were pooled into the meta-analysis of IL-10 -819T>C (rs1800871) polymorphism, significantly increased risk of CRC was observed in the two genetic models, i.e., allele (A vs G: OR=1.278, 95% CI 1.043-1.566, P=0.018) and recessive (AA vs AG+GG: OR=1.709, 95% CI 1.026-2.845, P=0.039).

TABLE 2 Results of the association of IL-10 promoter region polymorphisms with CRC risk. 

Subgroup Genetic Model Type of Model Heterogeneity Odds Ratio Publication Bias
I2 (%) P H OR 95% CI Ztest P OR P Beggs P Eggers
IL-10 -1082A>G (rs1800896)
G vs A Fixed 10.58 0.337 0.962 0.893-1.038 -0.999 0.318 0.228 0.422
GG vs AA Fixed 3.88 0.408 0.983 0.836-1.155 -0.208 0.835 0.826 0.664
GA vs AA Fixed 16.60 0.272 0.953 0.843-1.078 -0.766 0.444 0.826 0.688
GG+GA vs AA Fixed 0.00 0.458 0.921 0.821-1.034 -1.387 0.165 0.324 0.826
GG vs GA+AA Fixed 0.00 0.561 0.986 0.861-1.129 -0.203 0.839 0.228 0.260
IL-10 -592C>A (rs1800872)
A vs C Random 53.69 0.017 0.945 0.838-1.064 -0.937 0.349 0.533 0.544
AA vs CC Fixed 37.90 0.097 0.859 0.705-1.047 -1.507 0.132 1.000 0.863
AC vs CC Random 45.87 0.047 0.951 0.826-1.094 -0.704 0.481 0.275 0.328
AA+AC vs CC Random 84.90 ≤0.001 0.891 0.693-1.145 -0.900 0.368 0.350 0.005
AA vs AC+CC Fixed 24.83 0.207 0.906 0.747-1.099 -0.997 0.319 0.436 0.625
IL-10 -819T>C (rs1800871)
C vs T Fixed 57.07 0.097 1.278 1.043-1.566 2.368 0.018 1.000 0.636
CC vs TT Random 66.94 0.049 1.682 0.651-4.348 1.074 0.283 1.000 0.533
CT vs TT Fixed 66.43 0.051 1.011 0.779-1.312 0.083 0.934 1.000 0.988
CC+CT vs TT Fixed 52.19 0.123 1.253 0.974-1.611 1.757 0.079 1.000 0.653
CC vs CT+TT Fixed 33.49 0.222 1.709 1.026-2.845 2.060 0.039 1.000 0.411

The studies were further stratified on the basis of ethnicity, source of control, genotyping technique and HWE status. Subgroup analysis did not showed the IL-10 -1082A>G and -592C>A polymorphisms significantly increased risk of CRC (data not showed).

Heterogeneity and sensitivity analyses

Table 2 summarizes the results of this meta-analysis for heterogeneity test. For IL-10 -1082A>G polymorphism, there was no a significant heterogeneity in all five genetic models. Our meta-analysis showed little evidence of genetic heterogeneity in the homozygote model of IL-10 -819T>C. We detected significant between-study heterogeneity in the three genetic models, i.e., allele, heterozygote and dominant for -592C>A. One-way sensitivity analyses were performed by iteratively removing one study at a time to assess the stability of the meta-analysis results. The result showed that there was still no significant association of IL-10 -1082A>G and -819T>C polymorphisms with CRC. Significant between-study heterogeneity was still significant after removing one study under the genetic models (data not shown).

Publication bias

We performed Begg’s test and Egger’s test to assess the publication bias. As shown in the Table 2, no obvious publication bias was found according to the obtained P values for all the genetic models for IL-10 -1082A>G and -819T>C polymorphisms. However, the results of Egger’s regression test and relative asymmetry of funnel plot showed evidence of publication bias for IL-10 -592C>A under the dominant model (P Begg’s=0.350, P Eggers=0.005, Figure 2), suggesting that there was obvious publication bias in the genetic model. Therefore, we have performed the Duval and Tweedie nonparametric “trim and fill” method to adjust for publication bias. The “trim and fill” method did not change conclusion, indicating that our results were statistically robust.

FIGURE 2 Begg’s funnel plot of publication bias test before (blue) and after (red) trim-and-fill method for IL10 -592C>A polymorphism with CRC risk under dominant model (AA+AC vs. CC). 

Minor Allele Frequencies (MAFs)

The minor allele frequencies (MAFs) of the IL-10 polymorphisms are presented in Table 1. The IL10 -1082G, -592A and -819C allele frequencies in the overall populations were 29.35% (5.10%-53.60%), 27.45% (18.70%-36.20%), and 21.9% (17.80%-26.0%), respectively.

DISCUSSION

To date, numerous molecular epidemiological studies have been conducted to evaluate the association between polymorphisms of IL-10 promoter polymorphisms and the risk of CRC, but results have remained conflicting. In this meta-analysis, we identified 28 eligible studies, including 5,647 CRC cases and 6,908 controls, and analyzed the association of IL-10 -1082A>G, -592C>A and -819T>C polymorphisms with susceptibility to CRC. We found that the IL-10 -1082A>G and -592C>A polymorphisms were not associated with CRC risk in overall population. We suggested that the IL-10 -1082A>G and -592C>A polymorphisms could play a protective role in the development of CRC due to a higher incidence found in controls than in cases from the included studies in the meta-analysis.

Previously, association of the IL-10 polymorphisms with CRC risk has been investigated by two meta-analyses. In 2013, Yu et al. performed a comprehensive meta-analysis about IL-10 -819C>T polymorphism and cancer susceptibility. They have found that the IL-10 -819C>T polymorphism was not significantly associated with CRC, breast cancer, lung cancer, hepatocellular carcinoma, prostate cancer, lymphoma, or melanoma16. Compared with Yu et al., we only focused on the association of IL-10 polymorphisms with CRC cancer, while Yu et al. analyzed a variety of human malignancies. In 2012, Zhang et al. performed a meta-analysis about IL-10 -1082 A>G and -592 C>A polymorphisms and CRC risk17. Compared with Yu et al. and Zhang et al. studies, we have focused on the association of three promoter region polymorphisms with CRC. On the other hand, we also analyzed the association of IL-10 -819T>C polymorphism with CRC risk. Additionally, we identified more eligible studies undertaken to assess the association IL-10 gene promoter polymorphisms and CRC risk.

To the best knowledge, this is the first comprehensive meta-analysis to assess the association of IL-10 -819T>C polymorphism with CRC risk. The current meta-analysis, which included a total of three case-control studies with 477 cases and 544 controls, investigated the association of IL-10 -819T>C polymorphism with CRC risk. We found that the IL-10 -819T>C polymorphism significantly increased risk of CRC in the two genetic models, i.e., allele (A vs G: OR=1.278, 95% CI 1.043-1.566, P=0.018) and recessive (AA vs AG+GG: OR=1.709, 95% CI 1.026-2.845, P=0.039). However, a small number of eligible studies were enrolled for IL-10 -819T>C polymorphism, which may fail to provide enough statistical power to detect a possible or effect of IL-10 -819T>C polymorphism on CRC. Therefore, to achieve more precise correlation, future studies should take ethnic difference in to consideration. However, we suggests that the IL-10 -819T>C polymorphism may be important as suspected predictive factor for CRC occurrence.

Between-study heterogeneity is a potential problem that might affect the interpretation of the results. thus, one of the most important goals of the meta-analysis is to identify the source of heterogeneity39-42. Through conducting meta-regression, we found that the heterogeneity could not be explained by ethnicity, source of control, genotyping methods and HWE status in the current meta-analysis. Therefore, we suggested that the heterogeneity may have resulted due to something more than these factors. It is known that the existence of publication bias can influence the conclusions of a meta-analysis. Therefore, the “trim and fill” methods have been developed to deal with publication bias. In the current meta-analysis, we have found possible publication bias between IL-10 -592C>A polymorphism and CRC risk under the dominant model (P Begg’s=0.350, P Eggers=0.005), adjusting for possible publication bias using the Duval and Tweedie nonparametric “trim and fill” method showed that the results did not adjust, indicating that the overall pooled results should be unbiased.

In interpreting the results, some cautions should be applied. First, there was limited number of eligible studies in the meta-analysis of the association between IL-10 -819T>C polymorphism and risk of CRC. The limited sample size in the meta-analysis may fail to provide enough statistical power to detect a possible or weak effect of IL-10 -819T>C polymorphism on CRC. Therefore, more studies with large sample are needed to give a more precise estimation of the association between IL-10 -819T>C polymorphism and risk of CRC. Second, the included studies involved in the meta-analysis were mainly Caucasian, so it is uncertain whether these results are generalizable to other populations. Moreover, the stratification by ethnicity had little or no information for other ethnicities, which may limited the strength of our results. Thus, strengthening the statistical power will require more data from different ethnicities. Third, although no significant publication bias was detected, we have included only published studies in this meta-analysis, and it is possible that some relevant published and unpublished studies in other languages might be missed, which also publication bias may occur. Fourth, our results were based on unadjusted estimates without adjustment for other risk factors such as age, gender, drinking consumption, environmental factors and other variables, while a more precise analysis should be conducted according to potentially confounding factors. Finally, lack of the original data of the included studies, the interaction of different susceptibility genes, gene-to-environment, and even different polymorphic loci of the same gene interactions due to the limited information of included studies.

In conclusion, this meta-analysis indicated that IL-10 -1082A>G and -592C>A polymorphisms could play a protective role in the development of CRC. However, we found that there was a significant association between IL-10 -819T>C polymorphism and CRC risk. The IL-10 -819T>C polymorphism may be important as suspected predictive factor of CRC occurrence. More extensive studies with large sample sizes, gene-gene and gene-environment interactions are necessary to provide a more reliable estimation of these associations in overall and by ethnicity.

REFERENCES

1. Wang N, Wang L, Yang H, Zhang HQ, Lan B, He X, et al. Multiple genetic variants are associated with colorectal cancer risk in the Han Chinese population. Eur J Cancer Prev. 2014;1-5. [ Links ]

2. Forat-Yazdi M, Gholi-Nataj M, Neamatzadeh H, Nourbakhsh P, Shaker-Ardakani H. Association of XRCC1 Arg399Gln polymorphism with colorectal cancer risk: A huge meta-analysis of 35 studies. Asian Pacific J Cancer Prev. 2015;16:3285-91. [ Links ]

3. Khoram-Abadi KM, Forat-Yazdi M, Kheirandish S, Saeidi N, Zarezade Z, Mehrabi N, et al. DNMT3B -149 C>T and -579 G>T Polymorphisms and Risk of Gastric and Colorectal Cancer: a Meta-analysis. Asian Pac J Cancer Prev. 2016;17:3015-20. [ Links ]

4. Namazi A, Abedinzadeh M, Nourbaksh P, Neamatzadeh H. Association between the XRCC3 Thr241Met polymorphism and risk of colorectal cancer: A meta-analysis of 5,193 cases and 6,645 controls. Asian Pacific J Cancer Prev . 2015;16:2263-8. [ Links ]

5. Møller H, Sandin F, Robinson D, Bray F, Klint Å, Linklater KM, et al. Colorectal cancer survival in socioeconomic groups in England: Variation is mainly in the short term after diagnosis. Eur J Cancer. 2012;48:46-53. [ Links ]

6. Breen N, Lewis DR, Gibson JT, Yu M, Harper S. Assessing disparities in colorectal cancer mortality by socioeconomic status using new tools: health disparities calculator and socioeconomic quintiles. Cancer Causes Control. 2017;28:117-25. [ Links ]

7. Amersi F, Agustin M, Ko CY. Colorectal cancer: epidemiology, risk factors, and health services. Clin Colon Rectal Surg. 2005;18:133-40. [ Links ]

8. Haggar FA, Boushey RP. Colorectal cancer epidemiology: incidence, mortality, survival, and risk factors. Clin Colon Rectal Surg . 2009;22:191-7. [ Links ]

9. Pancione M, Remo A, Colantuoni V. Genetic and Epigenetic Events Generate Multiple Pathways in Colorectal Cancer Progression. Patholog Res Int. 2012;2012:1-11. [ Links ]

10. Souglakos J. Genetic alterations in sporadic and hereditary colorectal cancer: implementations for screening and follow-up. Dig Dis. 2007;25:9-19. [ Links ]

11. Al-Sukhni W, Aronson M, Gallinger S. Hereditary Colorectal Cancer Syndromes: Familial Adenomatous Polyposis and Lynch Syndrome. Surg Clin North Am. 2008;88:819-44. [ Links ]

12. Seruga B, Zhang H, Bernstein LJ, Tannock IF. Cytokines and their relationship to the symptoms and outcome of cancer. Nat Rev Cancer. 2008;8:887-99. [ Links ]

13. Sheikhpour E, Noorbakhsh P, Foroughi E, Farahnak S, Nasiri R, Neamatzadeh H. A survey on the role of interleukin-10 in breast cancer: a narrative. Reports Biochem Mol Biol. 2018;7:30-7. [ Links ]

14. Namazi A, Forat-Yazdi M, Jafari M, Farahnak S, Nasiri R, Foroughi E, et al. Association of Interleukin-10 -1082 a/G (Rs1800896) Polymorphism With Susceptibility To Gastric Cancer: Meta-Analysis of 6,101 Cases and 8,557 Controls. Arq Gastroenterol. 2018;55:33-40. [ Links ]

15. Howell WM, Rose-Zerilli MJ. Cytokine Gene Polymorphisms, Cancer Susceptibility, and Prognosis. J Nutr. 2007;137:194S-199S. [ Links ]

16. Yu Z, Liu Q, Huang C, Wu M, Li G. The Interleukin 10 −819C/T Polymorphism and Cancer Risk: A HuGE Review and Meta-Analysis of 73 Studies Including 15,942 Cases and 22,336 Controls. Omi A J Integr Biol. 2013;17:200-14. [ Links ]

17. Zhang YM, Zhou XC, Xu Z, Tang CJ. Meta-analysis of epidemiological studies of association of two polymorphisms in the interleukin-10 gene promoter and colorectal cancer risk. Genet Mol Res. 2012 S;11:3389-97. [ Links ]

18. Mantel N, Haenszel W. Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst. 1959;22:719-48. [ Links ]

19. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7:177-88. [ Links ]

20. Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994;50:1088-101. [ Links ]

21. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315:629-34. [ Links ]

22. Macarthur M, Sharp L, Hold GL, Little J, El-Omar EM. The Role of Cytokine Gene Polymorphisms in Colorectal Cancer and Their Interaction with Aspirin Use in the Northeast of Scotland. Cancer Epidemiol Biomarkers Prev. 2005;14:1613-8. [ Links ]

23. Crivello A, Giacalone A, Vaglica M, Scola L, Forte GI, Macaluso MC, et al. Regulatory cytokine gene polymorphisms and risk of colorectal carcinoma. Ann N Y Acad Sci. 2006;1089:98-103. [ Links ]

24. Gunter MJ, Canzian F, Landi S, Chanock SJ, Sinha R, Rothman N. Inflammation-Related Gene Polymorphisms and Colorectal Adenoma. Cancer Epidemiol Biomarkers Prev . 2006;15:1126-31. [ Links ]

25. Cozar JM, Romero JM, Aptsiauri N, Vazquez F, Vilchez JR, Tallada M, et al. High incidence of CTLA-4 AA (CT60) polymorphism in renal cell cancer. Hum Immunol. 2007;68:698-704. [ Links ]

26. Talseth BA, Meldrum C, Suchy J, Kurzawski G, Lubinski J, Scott RJ. Lack of association between genetic polymorphisms in cytokine genes and disease expression in patients with hereditary non-polyposis colorectal cancer. Scand J Gastroenterol. 2007;42:628-32. [ Links ]

27. Wilkening S, Tavelin B, Canzian F, Enquist K, Palmqvist R, Altieri A, et al. Interleukin promoter polymorphisms and prognosis in colorectal cancer. Carcinogenesis. 2008;29:1202-6. [ Links ]

28. Cacev T, Radosević S, Krizanac S, Kapitanović S. Influence of interleukin-8 and interleukin-10 on sporadic colon cancer development and progression. Carcinogenesis. 2008;29:1572-80. [ Links ]

29. Tsilidis KK, Helzlsouer KJ, Smith MW, Grinberg V, Hoffman-Bolton J, Clipp SL, et al. Association of common polymorphisms in IL10, and in other genes related to inflammatory response and obesity with colorectal cancer. Cancer Causes Control . 2009;20:1739-51. [ Links ]

30. Miteva LD, Stanilov NS, Deliysky TS, Stanilova SA. Significance of -1082A/G polymorphism of IL10 gene for progression of colorectal cancer and IL-10 expression. Tumour Biol. 2014;35:12655-64. [ Links ]

31. Burada F, Dumitrescu T, Nicoli R, Ciurea ME, Rogoveanu I, Ioana M. Cytokine promoter polymorphisms and risk of colorectal cancer. Clin Lab. 2013;59:773-9. [ Links ]

32. Basavaraju U, Shebl FM, Palmer AJ, Berry S, Hold GL, El-Omar EM, et al. Cytokine gene polymorphisms, cytokine levels and the risk of colorectal neoplasia in a screened population of Northeast Scotland. Eur J Cancer Prev . 2015;24:296-304. [ Links ]

33. Li HX, Li YY, Song ZJ, He SX, Guo QY. Association between IL-8-251A/T and il-10-1082A/G genetic polymorphisms and susceptibility to colorectal cancer: A case-control study in a population in Shaanxi. World Chinese J Dig. 2015;23:1184-90. [ Links ]

34. Cai J, Zhang Z. An Analysis of IL-10/IL-10R Genetic Factors Related to Risk of Colon Cancer and Inflammatory Bowel Disease in a Han Chinese Population. Clin Lab. 2016;62:1147-54. [ Links ]

35. Gulubova M, Aleksandrova E, Vlaykova T. Promoter polymorphisms in TGFB1 and IL10 genes influence tumor dendritic cells infiltration, development and prognosis of colorectal cancer. J Gene Med. 2018;e3005. [ Links ]

36. Vogel U, Christensen J, Dybdahl M, Friis S, Hansen RD, Wallin H, et al. Prospective study of interaction between alcohol, NSAID use and polymorphisms in genes involved in the inflammatory response in relation to risk of colorectal cancer. Mutat Res. 2007;624:88-100. [ Links ]

37. Andersen V, Egeberg R, Tjønneland A, Vogel U. Interaction between interleukin-10 (IL-10) polymorphisms and dietary fibre in relation to risk of colorectal cancer in a Danish case-cohort study. BMC Cancer. BioMed Central. 2012;12:183. [ Links ]

38. Yu Y, Zheng S, Zhang S, Jin W, Liu H, Jin M, et al. Polymorphisms of inflammation-related genes and colorectal cancer risk: a population-based case-control study in China. Int J Immunogenet. 2014;41:289-97. [ Links ]

39. Jafari Nedooshan J, Kargar S, Neamatzadeh H, Haghighi F, Dehghani Mohammad Abadi R, Seddighi N. Lack of Association of the Fat Mass and Obesity Associated (FTO) Gene rs9939609 Polymorphism with Breast Cancer Risk: a Systematic Review and Meta-Analysis Based on Case - Control Studies. Asian Pac J Cancer Prev . 2017;18:1031-7. [ Links ]

40. Jafari Nedooshan J, Forat Yazdi M, Neamatzadeh H, Zare Shehneh M, Kargar S, Seddighi N. Genetic Association of XRCC1 Gene rs1799782, rs25487 and rs25489 Polymorphisms with Risk of Thyroid Cancer: a Systematic Review and Meta-Analysis. Asian Pac J Cancer Prev . 2017;18:263-70. [ Links ]

41. Sadeghiyeh T, Hosseini Biouki F, Mazaheri M, Zare-Shehneh M, Neamatzadeh H, Poursharif Z. Association between Catechol-O-Methyltransferase Val158Met (158G/A) Polymorphism and Suicide Susceptibility: A Meta-analysis. J Res Health Sci. 2017;17:e00383. [ Links ]

42. Mehdinejad M, Sobhan MR, Mazaheri M, Zare Shehneh M, Neamatzadeh H, Kalantar SM. Genetic Association between ERCC2, NBN, RAD51 Gene Variants and Osteosarcoma Risk: a Systematic Review and Meta-Analysis. Asian Pac J Cancer Prev . 2017;18:1315-21. [ Links ]

Disclosure of funding: no funding received

Received: March 16, 2018; Accepted: May 08, 2018

Corresponding author: Mansour Moghimi. Orcid: 0000-0002-4000-9953. E-mail: moghimim1350@gmail.com

Declared conflict of interest of all authors: none

Authors’ contributions: Mirjalili SA, Moghimi M and Neamatzadeh H conceived and research design. Abolbaghaei SM and Mazaheri M selected the articles and extracted the data. Aghili K, Jafari M and Zare-Shehneh M performed data analysis. The manuscript was drafted by Mirjalili SA and Neamatzadeh H. Moghimi M and Abolbaghaei SM critically reviewed the manuscript and discussed with the other co-authors. All the authors read and approved the final manuscript.

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