| Lung cancer is the leading cause of cancer mortality in China,and its escalating prevalence presents a major public health challenge. To unravel the genetic underpinnings of lung cancer, a proliferating range of single-locus investigations to genome-wide scans have been undertaken. however, neither a gene nor a variant hitherto has been confirmed uniformly across ethnic groups. One compelling reason might be attributable to the lack of consideration of gene-to-gene interaction, which is increasingly recognized as an ubiquitous component in the underlying etiology of most common diseases. To shed some light on this issue, we, in this study, focused on two candidate genes, advanced glycosylation end product-specific receptor (RAGE) and apurinic/apyrimidinic endonuclease1(APE1), to explore their interactive association of common genetic defects with lung cancer risk.A total of819lung cancer patients and803cancer-free controls were recruited from Heilongjiang province.Venous blood samples were collected in EDTA tubes for genomic DNA extraction and subsequent batch genotyping. Five examined polymorphisms were genotyped by the polymerase chain reaction-ligase detection reactions (PCR-LDR) method. Data were statistically analyzed with the use of the open-source R software and multifactor dimensionality reduction (MDR).A priori study power was estimated using PS software.Unpaired t-test and x2test were used to compare continuous and categorical variables between patients and controls, respectively. Hardy-Weinberg equilibrium was evaluated by using a goodness-of-fit test. Logistic regression analyses were adopted under the assumptions of additive, dominant and recessive models for each polymorphism examined. Odds ratio (OR) and its corresponding95%confidence interval (CI) were computed to quantify the association of genotypes with lung cancer risk. Statistical significance was set at P <0.05.Haplotype frequencies and their risk prediction were calculated by Haplo.stats software developed by R software. In detail,haplo.em program was used to estimate frequencies; haplo.cc and haplo.glm programs were used to estimate OR and95%CI according to a generalized linear model. The differences in the estimated haplotype frequencies between patients and controls were based on simulated P-values. Simulated statistics are based on randomly permuting the trait and covariates and then computing the haplotype score statistics. The haplo.em, haplo.cc and haplo.glm were implemented using Haplo.stats software. Gene-to-gene interactions were conducted by MDR software.Baseline characteristics of the study population are summarized. Distributions of age, gender and family history of cancers were comparable between patients with lung cancer and controls (P>0.05). Percentages of smokers (P<0.0005) and drinkers (P<0.0005), as well as history of COPD (P<0.0005),were remarkably higher in patients than in controls; Genotype distributions and allele frequencies of five examined polymorphisms, as well as their risk prediction under various genetic models are analysed. No deviations from Hardy-Weinberg equilibrium were seen in both patients and controls for all polymorphisms. Overall, there were significant differences in the genotype and allele distributions of rs1800625(Pgenotype<0.0005; Pallele<0.0005), rs2070600(Pgenotype=0.005; Pallele=0.004) polymorphisms in RAGE gene and rs1130409(Pgenotype=0.009; Pallele=0.004) polymorphism in APE1gene, and the estimated study power to detect these differences was94.2%,81.6%and81.3%, respectively. Across all genetic models, carriers of mutant allele or genotype of polymorphisms rs1800625and rs1130409polymorphisms were significantly associated with lung cancer risk, especially under the recessive model, even after adjusting for confounding factors. With regard to rs2070600polymorphism, significance was merely attained under additive and recessive models; Given that RAGE and APE1genes are mapped to different chromosomes, haplotype analyses were conducted separately for each gene. Haplotype frequencies and their risk prediction for lung cancer are analysed. Frequencies of the most common haplotype in both RAGE (T-T-G in order of rs1800625,rs1800624, and rs2070600, Psim=0.315) and APE1(G-G in order of rs1760944and rs1130409, Psim=0.084) genes were similar between patients and controls. Compared with controls, haplotype C-A-A in RAGE gene was overrepresented in patients (Study power:99.5%), and was associated with a2.1-fold increased risk of lung cancer (95%CI:1.52-2.91) before adjustment and a2.15-fold increased risk after adjustment (95%CI:1.55-2.97). There were no significant differences in the haplotype frequencies of APE1gene between two groups; An exhaustive MDR analysis on the possible interaction of five examined polymorphisms is summarized. Each best model was accompanied with its cross-validation consistency, testing accuracy and significant level determined by permutation testing. The overall best MDR model encompassed polymorphism rs2070600in RAGE gene and rs1130409in APE1gene. This model had a maximal testing accuracy of65.63%and a maximal cross-validation consistency of9out of10at the significant level of0.006.In this study, we sought to investigate the association of five common polymorphisms from two candidate genes with lung cancer risk in a large Han Chinese population involving1622individuals. The most noteworthy finding was that genetic interaction between RAGE and APE1genes might confer a potentially increased risk for lung cancer, which was reinforced by the results of single-locus and haplotype analyses. |
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