01 December 2015: Meta-Analysis
Association Between COX-2 Polymorphisms and Lung Cancer Risk
Weiwei Wang ABDG , Xinyun Fan BD , Yong Zhang DE , Yi Yang CE , Siyuan Yang BE , Gaofeng Li EFG
DOI: 10.12659/MSM.894839
Med Sci Monit 2015; 21:3740-3747
Abstract
BACKGROUND: Multiple relevant risk factors for lung cancer have been reported in different populations, but results of previous studies were not consistent. Therefore, a meta-analysis is necessary to summarize these outcomes and reach a relatively comprehensive conclusion.
MATERIAL AND METHODS: STATA 12.0 software was used for all statistical of the relationship between COX-2 polymorphisms and lung cancer risk. Inter-study heterogeneity was examined with the Q statistic (significance level at P<0.1). The publication bias among studies in the meta-analysis was analyzed with Begg’s funnel plot and Egger’s test. Hardy-Weinberg equilibrium was tested in all controls of the studies.
RESULTS: COX-2 rs20417 polymorphism had a significant association with reduced risk of lung cancer under homozygous and recessive models, and similar results were observed in white and population-based subgroups under 2 and 3 contrasts, respectively. Additionally, rs2066826 polymorphism manifested a strong correlation with increased risk of lung cancer under 5 genetic models.
CONCLUSIONS: In COX-2 gene, rs20417 may have a certain relationship with reduced risk of lung cancer, while rs2066826 may increase the risk of lung cancer.
Keywords: Cyclooxygenase 2 - genetics, Case-Control Studies, Genetic Association Studies, Genetic Predisposition to Disease, Lung Neoplasms - genetics, Polymorphism, Single Nucleotide, Software
Background
Lung cancer, also known as bronchogenic carcinoma, generally refers to malignant tumors from epidermal cells of the bronchus or bronchiole, which account for 90–95% of total lung cancer cases [1–3]. Currently, lung cancer is the leading cause of death among all cancers worldwide, and its mortality shows a rising tendency each year, especially in women [4–6]. The precise pathogenesis of lung cancer is not yet clearly understood, but numerous reports have confirmed some risk factors involved in lung cancer, including smoking, air pollution, occupational factors, chronic lung diseases, and human genetic factors [7–11].
An
Cyclooxygenase (COX), also called prostaglandin endoperoxide synthases (PTGs), is a rate-limiting enzyme catalyzing the synthesis of prostaglandins (PGs) and thromboxanesA2 (TXA2) through arachidonic acid (AA) [26]. So far, there are at least 2 types in the COX family – COX-1 and COX-2. As an induced enzyme, COX-2 rarely expresses in normal tissues, but starts its expression after being stimulated by multiple factors, such as cytokines, growth factors (including PD-GF, TNF, EGF, bFGF and IL-1), oncogenes (like ras and V-rsc), tumor promoters, and endotoxins, thus participating in physiological and pathological processes in inflammation and tumors [27,28].
Many studies have explored the relationship between polymorphisms in
Material and Methods
LITERATURE SEARCH:
A literature search was performed in the databases of PubMed, EMBASE, CNKI, and Chinese Wanfang Data for potentially relevant studies published in English or Chinese languages. The terms for search included “lung cancer” or “pulmonary cancer” or “lung carcinoma”, “
INCLUSION CRITERIA:
All studies included in this meta-analysis met the following criteria: (1) using case-control study method to assess the relationship of
DATA EXTRACTION:
The data for meta-analysis were extracted independently by 2 authors in accordance with the same standard. No disagreement occurred in this work. From each study included in this analysis, the following information was recorded: first author, year of publication, original country, ethnicity, source of control, genotyping methods, researched polymorphism, and genotype frequencies in cases and controls.
STATISTICAL ANALYSIS:
The overall pooled ORs and corresponding 95%CIs were calculated to evaluate the relationship between COX-2 polymorphisms and lung cancer under homozygous, dominant, recessive, allele, and heterozygous models. The chi-square-based Q statistic was used to assess the heterogeneity among included articles. The overall ORs were obtained under the random-effects model when there was significant heterogeneity (P<0.1), and under the fixed-effects model when the heterogeneity was not significant. The genotype distribution in controls of each study was measured with the chi-square test to examine the goodness-of-fit in controls to Hardy-Weinberg equilibrium, and P>0.05 indicates that the control samples were in good equilibrium. Publication bias was detected by Begg’s funnel plot and Egger’s linear regression test [33,34]. Sensitivity test was performed through deleting a single included study each time to observe the effect on the overall ORs in this meta-analysis. All data were processed with STATA 12.0 software (Stata Corporation, College Station, TX, USA).
Results
STUDY CHARACTERISTICS:
We retrieved 81 relevant articles following the above search strategy, and 12 qualified ones were included ultimately [35–46]. Figure 1 presents the particular process of literature screening. Table 1 displays the general characteristics of these 12 studies.
META-ANALYSIS RESULTS:
The association of each polymorphism in COX-2 gene with lung cancer is listed in Table 2 under 5 contrasts with corresponding effect models. Among 9 polymorphisms, 7 polymorphisms (rs5275, rs689466, rs2745557, rs3218625, rs20432, rs16825748, and rs5277) had no significant relationship with lung cancer risk, while the other 2 (rs20417 and rs2066826) expressed significant correlations with the cancer. COX-2 rs20417 polymorphism demonstrated a remarkable relevance to reduced lung cancer risk under AA versus GG (OR=0.41, 95%CI=0.22–0.77) and AA versus GG+GA contrast (OR=0.39, 95%CI=0.22–0.70), as well as in subgroup analysis of white and population-based groups (Figure 2, Figure 3). As for rs2066826, a positive relationship with lung cancer was found in all 5 models [AA versus GG (OR=4.36, 95%=1.48–12.87), AA+GA versus GG (OR=1.65, 95%CI=1.20–2.26), AA versus GG+GA (OR=4.00, 95%CI=1.36–11.79), A versus G (OR=1.76, 95%CI=1.31–2.35), and GA versus GG (OR=1.56, 95%CI=1.12–2.16)] (Figure 4).
SENSITIVITY ANALYSIS:
The pooled ORs showed no distinct discrepancy from those obtained after omitting a single study each time, indicating all these studies did not have substantial impact on the whole ORs.
PUBLICATION BIAS: Begg’s funnel plot seemed symmetrical for each polymorphism, which was further proven by Egger’s linear regression test (P=0.582), implying there was no significant publication bias among studies in our meta-analysis (Figure 5).
Discussion
In spite of the advances in the diagnostic technology, the 5-year overall survival rate of lung cancer is still low, at about 12–15%, because the patients were diagnosed at moderate and advanced stages when clinic symptoms are presented. Statistically, the 5-year survival rate of patients at stage I reaches more than 70%, so early discovery, diagnosis, and treatment appear to be important to reduce the mortality rate of lung cancer. Currently, only 10% of asymptomatic patients are identified and receive radical treatments. Because of the limited sensitivity and specificity of existing screening methods, the mortality rate of lung cancer is still not reduced. It is urgently important to discover effective means for detection of individuals with high risk of lung cancer.
Human
As shown in the present analysis, 9 polymorphisms were examined to ascertain their potential relationships with lung cancer risk, of which 7 were not found to have relevance to the risk of lung cancer, including rs5275, rs689466, rs2745557, rs3218625, rs20432, rs16825748, and rs5277. rs2066826 had a significant association with the increased risk of lung cancer under all 5 contrasts, while a distinct correlation was observed between rs20417 polymorphism and the reduced risk of lung cancer under both homozygous and dominant models. Furthermore, in subgroup analysis for rs20417 and lung cancer risk, the same relationship was revealed in the white group under homozygous and dominant contrasts, and in population-based group under homozygous, dominant, and allele models.
There is discrepancy between our meta-analysis and previous studies. The presence of this phenomenon might be attributed to the following aspects: the samples in previous studies and our meta-analysis were not balanced in terms of quantity, or based on different ethnicities in various genetic backgrounds; and the possible interactions among genes and environmental factors were not taken into consideration in this meta-analysis. Therefore, the exact correlations of
Multiple genetic variants in
Conclusions
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