Association between TNF-α -308G>A Polymorphism and Lung Cancer Susceptibility

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Associationbetween TNF-α -308G>A Polymorphism and Lung Cancer Susceptibility: An Updated Meta-analysis

Running title: Meta-analysis of TNF-α polymorphism and lung cancer susceptibility

Highlights:

  1. This study indicates that TNF-α -308G>A polymorphism is associated with susceptibility to lung cancer.
  2. The mutations may not increase the risk of lung cancer, which means A-allele of TNF-α -308G>A polymorphism is not the risk allele of lung cancer.
  3. The subgroup analysis also suggests that TNF-α -308G>A polymorphism is not be associated with lung cancer susceptibility in European or Asian population.

Abstract

Objective: Our study aims to evaluate the association between TNF-α -308G>A polymorphism and risk for lung cancer by meta-analysis.

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Methods: We established corresponding searching strategies, using PubMed, Embase, China National Knowledge Infrastructure (CNKI) and Wanfang database (Chinese) and VIP database (Chinese) for relevant trials. Hardy-Weinberg Equilibrium (HWE) was tested using chi-square test and P value less than 0.05 was considered as significant disequilib­rium. Pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) for TNF-α -308G>A polymorphism and lung cancer susceptibility were calculated. We evaluated publication bias by means of the funnel plot. Analyses were conducted using the Rev.Man 5.2 for the study.

Results: There were 11 eligible studies, which included 4908 (Case group 2331; Control group 2577) participants were considered in this meta-analysis. There were no significant associations under the overall ORs for A-allele comparison (A vs. G, pooled OR 1.23, 95% CI 0.87-1.76, P=0.24), dominant model (AA+GA vs. GG, pooled OR 1.52, 95% CI 0.85-1.84, P=0.25) between TNF-α -308G>A polymorphism and risk for lung cancer.

Conclusions: This meta-analysis suggests that TNF-α -308G>A polymorphism is not associated with susceptibility to lung cancer. A larger sample size of studies or meta-analysis is necessary to verify this conclusion in the future research.

Key words: TNF; Case-control study; Lung cancer; Polymorphism; Meta-analysis

Introduction

Lung cancer is the most commonly diagnosed cancer and leading cause of cancer-related death worldwide 1-3, survival after diagnosis of lung cancer is poor 4. Studies show that several molecule mechanisms which involved in many stages of carcinogenesis, and respiratory epithelial cells become precancerous invasive cancer 5. Individuals at risk will be heterozygous allele in the germ line, carrying a copy of the normal function of a gene, a mutation, a recessive allele 6. Tumor necrosis factor-alpha (TNF-α) is a multifunctional cytokine which is involved with the pathogenesis of multiple inflammatory and malignant diseases 7. Functional promoter polymorphism of TNF-α, at the position -308, on behalf of an attractive potential marker of lung cancer susceptibility 8.

Nowadays, more and more studies in different countries assessed the association of TNF-α gene polymorphism and susceptibility to lung cancer. Current evidence indicates that heredity contributes to the progression of lung cancer 3. However, the conclusions of these studies are different. Most of the studies focus on the single nucleotide polymorphism (SNP) with TNF-α -308G>A (rs1800629), because this SNP locates in the promoter regions. The association between TNF-α -308G>A polymorphism and risk for lung cancer is uncertain, previous published two studies 9, 10 were explored this association, but the conclusion were unreliable because of the less number of included studies (6 studies). Our study aims to evaluate the association between TNF-α -308G>A polymorphism and susceptibility to lung cancer by making a comprehensive assessment of updated meta-analysis.

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Material and methods

Source of material

Public databases were retrieved mainly including PubMed (http://www.ncbi.nlm.nih.gov/pubmed), Embase (http://www.embase.com), China National Knowledge Infrastructure (CNKI, http://www.cnki.net/) and Wanfang database (Chinese, http://g.wanfangdata.com.cn/) and VIP database (Chinese, http://www.cqvip.com/) with the last report up to March 2014. The key words of “tumor necrosis factor”, “TNF”, “lung cancer”, “lung carcinoma”, “variant”, “polymorphism”, “genetic”, “study” or “trial” were used for searching. Meanwhile, references from retrieved papers were checked for any additional studies.

Included and excluded Standards of studies

Included standards of studies

Studies meeting the following criteria were included: (1) the investigation is case-control study, case group were the lung cancer patients, control group were health examination population or hospital-based population which were not lung cancer patients; (2) Detecting the association between TNF-α polymorphism and risk for lung cancer; (3) The objects were among human beings and the age of participants were not limited; (4) The included study was provided available genotype and allele data of TNF-α polymorphism in both case and control studies.

Excluded criteria of studies

Studies were deleted in the following situations: (1) the study was review, report, comment or letter; (2) it did not detect the association of TNF-α polymorphism with susceptibility to lung cancer; (3) the genotype distribution of control group in the study was not accorded with Hardy-Weinberg Equilibrium (HWE).

Extraction of data and Evaluation of quality

Two investigators (Author A and author B) extracted data mainly included the first author name, publication year, country, region, the number of genotype distribution in case group or control group, general demography characteristics of the included studies (eg. Gender and age). If there were discrepancies occurred during the course of data extraction, we made a discussion with the third investigator (Author C) in order to reach an agreement.

To assess the quality of included studies, we used the diagnostic criteria of Clark 11, which contains ten items (1 score for each item). If the quality of the study graded 8-10 scores, then this study is regarded as excellent; 5-7 scores is regarded as moderate; less than 5 scores is regarded as poor 12.

Statistical analysis

HWE test in the control group was performed using Chi-square goodness of fit tests, and a P value < 0.05 was considered as significant disequilib­rium. Pooled odds ratios (ORs) and its 95% confidence intervals (CIs) were calculated for A-allele comparison (A vs. G) and dominant model (AA+GA vs. GG), respectively. Analyses were performed using the Rev.Man 5.2 for the meta-analysis. We evaluated the heterogeneity by chi-square’s Q-statistic 13 and I2 statistics. A significant Q-statistic (P<0.10) or I2 >50% indicated heterogeneity across studies, and then the random effect model (Dersimonian-Laird method) was used for meta-analysis. Otherwise, the fixed effect model (Mantel-Haenszel method) was used 14. The sensitivity analysis was performed that when we deleted any one of the included study to estimate whether the overall combined OR were changed or not 15. We used funnel plot in order to evaluate publication bias.

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Results

Characteristics of eligible studies

We retrieved 118 papers, then excluding 95 articles after reading the title or abstract, and we deleted duplicate publications (10 papers) or unavailable data (2 papers). The flow diagram of the study selection process is shown in Figure 1. There were 11 eligible studies 7, 8, 16-24 included in this meta-analysis, including 9 studies in English and 2 studies in Chinese. A total of 4908 (Case group 2331; Control group 2577) participants were considered in this meta-analysis. The characteristics of included studies in the meta-analysis were presented in Table 1. The included studies were published between 2005 and 2013. The studies’ mean age of participants were between 46.2 and 66, studies had been carried out in European, American or Asian. All included studies were accorded with HWE (P>0.05). Furthermore, not all included studies adjusted the covariates (such as gender, age, etc.). All studies were between 5 and 7 scores by the literature quality evaluation, which means the literature quality was moderate.

Meta-analysis of quantitative data

We made a comprehensive assessment for the association of TNF-α -308G>A polymorphism and susceptibility to lung cancer by means of A-allele comparison (A vs. G) and dominant model (AA+GA vs. GG). There were significant heterogeneities (Figure 2-3) under both models for A-allele comparison and dominant model (P-value by χ2 -based Q testing < 0.1 and I2 > 50%), so we used the random effect model to compare the association between TNF-α -308G>A polymorphism and risk for lung cancer. No significant associations were found under the overall ORs for A-allele comparison (A vs. G, pooled OR 1.23, 95% CI 0.87-1.76, P=0.24, Figure 2), dominant model (AA+GA vs. GG, pooled OR 1.52, 95% CI 0.85-1.84, P=0.25, Figure 3) between TNF-α -308G>A polymorphism and risk for lung cancer.

In order to reduce the influence of heterogeneities with ethnicity on the results of the study, we conducted subgroup analysis for Asian population and European population in order to discuss the association between TNF-α -308G>A polymorphism and risk for lung cancer in these population, respectively. The subgroup analysis showed that the heterogeneities of A-allele comparison (A vs. G) and dominant model (AA+GA vs. GG) with TNF-α -308G>A polymorphism reduced (P=0.12, I2=45% and P=0.23,I2=29%, respectively) in European population, but there were significant heterogeneities (P<0.05,I2>50%) under A-allele comparison (A vs. G) and dominant model (AA+GA vs. GG) with TNF-α -308G>A polymorphism in Asian population. The results of subgroup analysis suggested that no significant associations were found under the overall ORs for A-allele comparison (A vs. G, pooled OR 1.34, 95% CI 0.65-2.76), dominant model (AA+GA vs. GG, pooled OR 1.35, 95% CI 0.61-3.02) between TNF-α -308G>A polymorphism and risk for lung cancer in Asian population. The results of subgroup analysis also showed that there were no significant associations were found under the overall ORs for A-allele comparison (A vs. G, pooled OR 0.96, 95% CI 0.83-1.12), dominant model (AA+GA vs. GG, pooled OR 0.96, 95% CI 0.81-1.15) between TNF-α -308G>A polymorphism and risk for lung cancer in European population.

Sensitivity analysis

The results of the sensitivity analysis showed that the overall combined OR were unchanged when we removed any one of the included study, which indicates the conclusion of our research is reliable and stable.

Evaluation of publication bias

We assessed publication bias by the funnel plot. The results of the nearly symmetrical funnel plots (Figure 4-5) showed that no obvious publication bias was found for the included studies.

Discussion

The result of this meta-analysis was showed that there were no significant associations between TNF-α -308G>A polymorphism and susceptibility to lung cancer under the overall ORs for A-allele comparison (A vs. G, pooled OR 1.23, 95% CI 0.87-1.76, P=0.24), dominant model (AA+GA vs. GG, pooled OR 1.52, 95% CI 0.85-1.84, P=0.25). Subgroup analysis (in European or Asian population) are basically identical with the overall model results.

Relevant apoptosis of TNF -inducing ligand and its receptors are the TNF superfamily members 25. Exposure to carcinogens, especially cigarette smoke, can produce somatic genetic alterations, such as chromosome deletions or mutations functional allele of the gene, in order to expose the non-functional allele 6. To test the reliability of the conclusions with the previous published studies, we conducted an updated meta-analysis to assess the association between TNF-α -308G>A polymorphism and risk for lung cancer, and we recruited more studies to let our study more reliable.

Due to the genotype distribution of A-allele in TNF-α -308G>A SNP was zero in some studies, and the results of association under the additive model or the recessive model is much the same with dominant model, so we did not display the results of the association between TNF-α -308G>A polymorphism and susceptibility to lung cancer under the additive model or the recessive model.

There were lager genetic heterogeneities with several included studies in our research, and the main causes are as follows: the differences of different countries or regions; different customs and habits of regional culture, life and diets habit; the differences of dwelling environment; the differences of gender, age and sample size. To reduce the heterogeneities, we performed the subgroup analysis, but we found large heterogeneities were already existed.

The limitations of this study are as follows. First of all, because of several studies’ data was incomplete, our study left out of consideration covariates to the meta-analysis (such as confounding factor of gender and age), which may affect the results of our meta-analysis. Secondly, due to lack of environmental factors’ data, we did not explore the interaction between TNF-α polymorphism and environmental factors. In addition, we only chose one SNP loci for analyzed and we did not clear other genetic mutation of functional sites, this may lead to underestimate the whole genetic effect of lung cancer risk. Therefore, it is necessary to construct a genetic map in order to make a comprehensive assessment of its role in lung cancer susceptibility. Finally, the data of the included studies involves pathological types and clinical staging of lung cancer is not complete, our study did not analyze this data.

Conclusions

This meta-analysis suggests that TNF-α-308G>A polymorphism is not associated with susceptibility to lung cancer. A larger sample size of studies or meta-analysis is necessary to verify this conclusion in the future research.

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