A Meta-Analysis of TLR Polymorphisms and Prostate Cancer Risk

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Association between TLR1 rs5743551 and TLR6 rs5743795 polymorphisms and prostate cancer risk in American men: a meta-analysis

Abstract

Objective: There is growing evidence that inflammation may play a significant role in prostate cancer. Single nucleotide polymorphisms (SNPs) in inflammation-related genes such as Toll-like receptor-6-1-10 gene clusters (TLR6-1-10) have been implicated in prostate cancer risk. However, results from the published studies remain inconclusive. To clarify the role of this polymorphism in prostate cancer, we performed a meta-analysis of all available and relevant published studies.

Methods: A computerized search of PubMed, Web of Science, and Chinese National Knowledge Infrastructure for publications on the TLR1 rs5743551 polymorphism, TLR6 rs5743795 polymorphism, and prostate cancer risk was performed and the genotype data were analyzed in a meta-analysis. Odds Ratios (ORs) with 95% confidence intervals (CIs) were estimated to assess the association. Sensitivity analysis, test of heterogeneity, cumulative meta-analysis and assessment of bias were performed in our meta-analysis by STATA software 11.0.

Results: A significant association between the TLR1 rs5743551 polymorphism and cancer susceptibility was revealed by the results of the meta-analysis (homozygous model-GG versus AA: OR = 0.66, 95% CI = 0.54-0.83; heterozygous model-AG versus AA: OR = 0.89, 95% CI = 0.79-1.00; dominant model-AG/GG versus AA: OR = 0.85, 95% CI = 0.76-0.95; recessive model-GG versus AA/AG: OR = 0.69, 95% CI = 0.56-0.84). Moreover, a decreased risk of prostate cancer was found in the genetic model of TLR6 rs5743795 AG (OR = 0.82, 95% CI = 0.69–0.99) and AA/AG (OR = 0.81, 95% CI: 0.68–0.97) versus GG.

Conclusions: This meta-analysis suggests that the TLR1 rs5743551 and TLR6 rs5743795 polymorphisms may be protective factors for prostate cancer in American populations. Further functional studies about TLR6-1-10 polymorphisms and prostate cancer risk are warranted.

Key words: TLR1, TLR6, polymorphism, prostate cancer, meta-ananlysis

  1. Introduction

Toll-like receptors (TLRs) belong to type I Transmembrane glycoprotein (1), which is an essential component of the innate immune system, and mediates immune responses to foreign pathogens, including bacteria, fungi and viruses. Ten human TLRs have been identified that share significant homology in their cytoplasmic domains and differentially recognize various microbes (2). Members of the TLRs family can be classified according to their localization in the cell: TLR1, TLR2, TLR4, TLR5, TLR6, and TLR10 are usually located on the cell surface, whereas TLR3, TLR7, TLR8, and TLR9 function on the endoplasmic reticulum membrane or the endosomal-lysosomal membrane (3).

The association between the development of inflammation and cancer has long been appreciated(4). The first study that noticed the cancer often developed at sites of chronic inflammation was conducted by Rudolf Virchow in 1858(5). Under normal conditions, inflammation is controlled in order to restrict cell proliferation until infections are resolved and tissue repair is completed. However, these inflammatory responses can also promote tumorigenesis through multiple means, including promoting the anti-apoptotic effects. Over the past years, various cancers have been reported to be associated with local chronic inflammation. Thus, TLRs appear to provide signals that are necessary for the resolution of inflammation and play essential roles in cancer. However, the exact mechanisms by which TLRs interact with tumor cells and how these cells are able to escape immunological eradication have only recently started to unravel.

TLR1, TLR6 and TLR10 genes are located on the same chromosome locus and constitute one gene cluster. Compelling evidence supports a role for TLR1–TLR6–TLR10 gene cluster involved in the innate immunity and inflammation pathway in prostate cancer risk (6-12). These studies have shown that the TLR1 rs5743551 and TLR6 rs5743795 single nucleotide polymorphisms (SNPs) occurs in prostate cancer, but the results are generally controversial and inconclusive. To solve the problem of inadequate statistical power and controversial results, we conducted a meta-analysis on all eligible case-control studies to clarify the effects of these two SNPs on prostate cancer risk in American population.

2. Materials and methods

2.1 Identification and eligibility of relevant studies

Relevant publications were identified with a literature search using the following search terms TLR1”,TLR6”, “polymorphism”, and “prostate cancer” in PubMed, Web of Science (WOS), and Chinese National Knowledge Infrastructure (CNKI) (the last search update was 20 June 2014). The search was restricted to English-language journals. Additional relevant articles were identified by a manual search of citations from the original studies. In our study, The following criteria were used for inclusion of the identified articles: (1) In a case-control design, (2) the genotype distribution of control population must be conformed to Hardy-Weinberg equilibrium (HWE), (3) sufficient published data for estimating odds ratio (OR) with its 95% confidence interval (95% CIs), (4) evaluation of the association between the TLR1 and TLR6 polymorphisms and prostate cancer risks. The study exclusion procedures were shown in Fig.1.

2.2 Data extraction

Two investigators independently extracted data from all of the eligible publications. The following information was sought from each article included the first author’s name, publication time, cancer type, country of origin, ethnicity, total number of cases and controls, genotype frequencies for cases and controls, and Hardy–Weinberg equilibrium (HWE) of controls. The two investigators checked the data extraction results and reached an agreement on all of the data. Different ethnicity descents were categorized.

2.3 Statistical analysis

The association between the TLR1 rs5743551 and TLR6 rs5743795 polymorphisms and risk of prostate cancer was measured by ORs with their 95% CIs. The pooled ORs were made comparisons with homozygotes, heterozygotes, the dominant genetic model and the recessive genetic model. The significance of pooled ORs was determined by Z-test, and P<0.05 was considered as statistically significant. Statistical heterogeneity among the studies was evaluated with a Chi square-based Q test. If the P-value > 0.05 of the Q-test, thus indicating a lack of heterogeneity among studies, then the effects model was used (the Mantel–Haenszel method)(13). Otherwise, the random-effects model (the DerSimonian and Laird method) was performed(14). The potential publication bias was assessed with funnel plots and Egger’s linear regression test. All of the statistical analyses were performed with STATA software 11.0 (StataCorp. LP, College Station, TX, USA), and using two-sided P-values.

3. Results

3.1 Characteristics of eligible studies

A total of 17 studies were retrieved by literature search from the Pubmed and WOS. According to the criteria for inclusion and exclusion, 4 case-control studies involving 2554 cases and 2594 controls fulfilled the inclusion criteria. The characteristics of included studies were summarized in Tables 1 and 2. All studies were case-control studies. The cases were patients with prostate cancer, and the controls were matched to the cases. The genotype frequencies of the three polymorphisms were extracted from the studies. Three genotype distributions in the controls from the selection studies were conformed to Hardy–Weinberg equilibrium.

3.2 Evidence synthesis

The results of meta-analysis are shown in Tables 3 and 4. The Q-test of heterogeneity was not significant in all of the genetic models. Therefore, the pooled ORs were calculated using fixed effect models. In all of the genetic models, there were significant association between TLR1 rs5743551 polymorphism and the risk of prostate cancer was observed. (GG versus AA: OR = 0.66, 95% CI = 0.54-0.83; AG versus AA: OR = 0.89, 95% CI = 0.79-0.999; AG/GG versus AA: OR = 0.85, 95% CI = 0.76-0.95; GG versus AA/AG: OR = 0.69, 95% CI = 0.56-0.84 (Fig.2). Moreover, a decreased risk of prostate cancer was found in the genetic model of TLR6 rs5743795 AG versus GG (OR = 0.82, 95% CI = 0.69–0.99) and AA/AG versus GG (OR = 0.81, 95% CI: 0.68–0.97) (Fig.3).

3.3 Sensitivity analysis and Publication bias.

To examine the influence of the individual study on the pooled OR, sensitivity analysis was carried out by deleting any single study involved in this meta-analysis. The results suggested that the significance of the pooled ORs in overall analysis was influenced in TLR1 rs5743551 heterozygote model by two studies conducted by Stevens et al and Kazma et al. (10, 12). The pooled OR and CI values were weakly changed by exclusion of these two studies: OR =0.85 (95% CI: 0.71-1.02) and 0.92 (95% CI: 0.81-1.05) after removal, respectively. Therefore,the positive result about TLR1 rs5743551 heterozygote model and prostate cancer risk in Fig.2 and Table.3 was needed to be treated with caution. To assess the publication bias of the literature, Begg’s funnel plot and Egger’s test were performed. As shown in Figure 4, the shapes of the funnel plots and Begg’s test did not indicate any evidence of obvious asymmetry in all comparison models (P>0.05).

4. Discussion

Prostate cancer is the most frequent and second most lethal cancer in men in the United States (15). There is growing evidence that innate immunity and inflammation may play a role in prostate and other cancers(16-18). Chronic inflammation could contribute to prostate cancer through several biological processes: the mutagenesis caused by oxidative stress; the remodeling of the extracellular matrix; the recruitment of immune cells, fibroblasts, and endothelial cells; or the induction of cytokines and growth factors contributing to a proliferative and angiogenic environment

(12, 16, 17, 19).

The family of Toll-like receptors is an essential component of the innate immune system, which are members of the interleukin-1 receptor super-family and mediate immune responses to foreign pathogens, including bacteria, fungi and viruses. Recent years, interest in the role of these receptors in cancer has been increasing, which recognized a wide spectrum of exogenous and endogenous ligands playing the key role in realization of innate and adaptive immune response, and participating in the processes of cell proliferation, survival, apoptosis, angiogenesis, tissue remodeling and repair(7, 8, 20-22). Polymorphisms in TLR genes may shift balance between pro- and anti-inflammatory cytokines, modulating the risk of infection, chronic inflammation and cancer(23). Of these polymorphisms, the TLR1 rs5743551 and TLR6 rs5743795 SNPs were mostly studied (7, 10, 24, 25). However, there are significant discrepancies among these studies. In this meta-analysis, a significant association between the TLR1 rs5743551 polymorphism and the risk of prostate cancer was revealed in American population. Moreover, a decreased risk of prostate cancer was found in the genetic model of TLR6 rs5743795 AG versus GG (OR = 0.82, 95% CI = 0.69–0.99) and AA/AG versus GG (OR = 0.81, 95% CI: 0.68–0.97). The results suggest that the TLR1 rs5743551 and TLR6 rs5743795 polymorphisms may be protective factors for prostate cancer in American population.

Some limitations of our meta-analysis should be addressed. First, the numbers of published studies collected in our analysis were not large enough for the comprehensive analysis. Second, only papers written in English were included; studies published in other languages were not included, which thus may bias the results. Third, our lack of access to the original data from the included studies limited further evaluation of the potential interactions such as gene–environment and gene–gene interactions, and even different polymorphic loci of the same gene, may also modulate cancer risk. Fourth, our results were based on unadjusted estimates, while a more precise analysis needs to be conducted if individual data such as age and profession are available. Thus, lack of the information for the data analysis may lead to serious confounding bias. Based on the limitations of the present study listed above, detailed studies are warranted to confirm our findings. Nevertheless, our meta-analysis has some advantages. First, the well-designed search and selection method significantly increased the statistical power of this meta-analysis. Second, the distribution of genotypes in the controls was consistent with Hardy-Weinberg equilibrium in all studies. In conclusion, the overall results of this meta-analysis have shown that the TLR1 rs5743551 and TLR6 rs5743795 polymorphisms may be protective factors for prostate cancer in American population. Further functional studies between this gene and prostate cancer risk are warranted.

Figure legends

Fig.1 Studies identified with criteria of inclusion and exclusion

Fig.2 Forest plot showing the association between TLR1 rs5743551 A>G Polymorphism and prostate cancer risk in American population. (A) GG/AA (B) AG/AA (C) AGGG/AA (D) GG/AAAG.

Fig.3 Forest plot showing the association between TLR6 rs5743795 G>A Polymorphism and prostate cancer risk in American population. (A) AA/GG (B) AG/GG (C) AAAG/GG (D) AA/GGGA.

Fig.4 Begg’s funnel plot for publication bias test. (A) TLR1 rs5743551 A>G Polymorphism and prostate cancer risk (B) TLR6 rs5743795 G>A Polymorphism and prostate cancer risk. Each point represents a separate study for the indicated association. Log (OR): nature logarithm of OR. Horizontal line represents size of effect.

Table1. Characteristics of studies about TLR1 polymorphism included in our meta-analysis

Case Control

First author

Years

Country

Ethnicity

Cancer type

Cases

Controls

AA

AG

GG

AA

AG

GG

PHWE

Yen-Ching Chen

2007

USA

Caucasian

Prostate Cancer

638

644

366

233

39

352

237

55

0.098

Victoria L. Stevens

2008

USA

Mixed

Prostate Cancer

1422

1414

829

505

88

779

519

116

0.026*

Remi Kazma

2012

USA

Caucasian

Prostate Cancer

404

432

223

152

29

119

185

58

0.939

Remi Kazma

2012

USA

African

Prostate Cancer

90

104

2

35

52

2

29

73

0.945

Abbreviations : HWE, Hard--Weinberg Equilibrium

* PHWE<0.05 due to mixed population

Table2. Characteristics of studies about TLR6 polymorphism included in our meta-analysis

Case Control

First author

Years

Country

Ethnicity

Cancer type

Cases

Controls

AA

AG

GG

AA

AG

GG

PHWE

Ye-ching Chen

2007

USA

Caucasian

Prostate Cancer

635

638

28

189

418

31

23

0

204

403

0.62

Remi Kazma

2012

USA

Caucasian

Prostate Cancer

404

432

13

125

266

164

245

0.72

Remi Kazma

2012

USA

African

Prostate Cancer

90

104

0

8

82

7

97

0.51

Abbreviations : HWE, Hard--Weinberg Equilibrium

Table3. Meta-analysis of the TLR1 rs5743551 A>G polymorphism on prostate cancer risk

Test of association Test of heterogeneity

Polymorphism

OR(95%CI)

Z

P-value

Modelb

X2

Pc

I2(%)

GG/AA

0.66(0.54—0.83)

3.69

<0.001

F

1.04

0.792

0.0

AG/AA

0.89(0.79—1.00)

1.97

0.049

F

2.13

0.546

0.0

AGGG/AA

0.85(0.76—0.95)

2.92

0.003

F

2.73

0.435

0.0

GG/AAAG

0.69(0.56—0.84)

3.65

<0.001

F

0.73

0.866

0.0

aNumber of comparisons

bFix-effects model(F) was used when P-value for heterogeneity ≥ 0.05; otherwise, random-effects

model(R) was used.

cP-value of Q-test for heterogeneity test

Table4. Meta-analysis of the TLR6 rs5743795 G>A polymorphism on prostate cancer risk

Test of association Test of heterogeneity

Polymorphism

OR(95%CI)

Z

P-value

Modelb

X2

Pc

I2(%)

AA/GG

0.72(0.47—1.10)

1.54

0.12

F

1.32

0.25

24.0

AG/GG

0.82(0.69—0.99)

2.11

0.04

F

2.45

0.29

18.2

AAAG/GG

0.81(0.68—0.97)

2.36

0.02

F

3.06

0.22

34.6

AA/AGGG

0.77(0.51—1.17)

1.22

0.22

F

0.91

0.34

0.0

aNumber of comparisons

bFix-effects model(F) was used when P-value for heterogeneity ≥ 0.05; otherwise, random-effects model(R) was used.

cP-value of Q-test for heterogeneity test

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