Association Between SNPs In P53Binding Sites And Risk Of Esophageal Squamous Cell Carcinoma

BackgroundEsophageal cancer is one of the most common malignancy worldwide. China lies in thefamous “Esophageal Cancer Belt”, and esophageal squamous cell carcinoma (ESCC)accounts for more than ninety percent of esophageal cancer. Moreover, the incidence of ESCCis higher than other counties. Patients with ESCC have no obvious clinical features and arealways diagnosed at moderate or late stage, as a result,5-year survival rate is much lower thanthat of other tumors. Therefore, we must look for new markers for early diagnosis of ESCC.Esophageal cancer is a complex disease involving genetic and environmental factors,while genetic factors play an important role in ESCC. Single nucleotide polymorphism (SNP)is the most common variation across human genome, which is the ideal genetic marker inassociation studies of complex diseases. Candidate gene study and genome-wide associationstudy (GWAS) are the main strategies applied in SNP-based association studies, with theirown strengths and weaknesses. Candidate gene study must assume the causative gene, andscreening is confined; However, GWAS requires a lot of manpower and resources, andpositive SNPs are quite difficult to explain their biological function. Therefore, how to choosedisease-related SNPs for association analysis has become the key issue of complex diseasestudies.According to their location in the genome, SNPs are divided into intergenec SNPs,coding SNPs, and non-coding SNPs (also called regulatory SNPs or rSNPs). rSNPs intranscription factor binding sites may influence the binding of transcription factors and targetgenes, then may regulate gene expression, thus become a hotspot of resarch.P53is the most important tumor suppressor, which can prevent cancer by maintaininggenomic stability, inducing apoptosis, inhibiting angiogenesis and other ways throughregulation of many downstream target genes. Therefore, we speculate that SNPs lying in thebinding sites of P53may impact its regulation of target genes, then cause the carriers withdifferent alleles with varying degrees of susceptibility for the tumor. Hence, these rSNPs in P53binding sites is expected to become the novel risk marker for the early diagnosis ofESCC.ObjectivesOur study began with a genome-wide screening of SNPs in P53binding sites throughdata mining. Then, we chose the SNPs existing in Chinese Han population and tumor-relatedgenes as target SNPs. Case-control study was applied to evaluate the relevance between theseSNPs and susceptibility to ESCC based on the population of Chongqing. At last, we intendedto explore the function of positive SNPs and provide an experimental evidence for the earlydiagnosis of ESCC.Methods and Results1. Patients involved in our study are from Department of Cardiothoracic Surgery,Southwest Hospital, while health controls are from Physical Examination Center in the samehospital. Cases and controls are Han population with long-term living in Chongqing,matching in age, gender and without kinship. At last,400cases and400controls weregenotyped.2. Through screening by bioinfomatics approaches,12301SNPs lies in P53binding sites,2688of which exist in Chinese population and were regarded as SNP pool. Studies haveconfirmed that Bax, CDKN1A, GADD45A gene is regulated by P53and played a key role incarcinogenesis. Then, we focused on SNPs in the three loci and chose SNPs with Minor AlleleFrequency (MAF)≥5%in Chinese population. The following six SNPs were selected:rs1009316, rs3783468, rs681673, rs532446, rs762624, and rs2395655.3. Multiplex SNaPshot was adopted to genotype these six SNPs in400ESCC cases and400health controls. Three SNPs (rs3783468, rs681673, rs532446) can not fit Hardy-Weinbergequilibrium (HWE) test, while the other three SNPs (rs1009316, rs762624, rs2395655) passedHWE, with p values of0.240,0.258, and0.297, respectively.4. Codominant, dominant, recessive, multiple, and overdominant genetic model wereused to evaluate the relationship between SNPs and susceptibility to ESCC. We found that CCgenotype and C allele of rs1009316and rs762624can decrease the risk of ESCC in all themodels except dominant genetic model. While, rs2395655is related with risk of ESCC incodominant, dominant, recessive, and multiple genetic model. In the multiple genetic model,p value is the least (0.004) and compared with A allele, G allele increase susceptibility to ESCC (Odds Ratio:1.364;95%Confidence Interval:1.104-1.685）5. We carried out a stratification analysis between allele and risk of ESCC according tosmoking history. C allele of rs1009316is an independent protective factor from ESCC, with pvalue of0.005and0.008, Odds Ratio (95%CI) of0.516(0.324-0.819) and0.484(0.282-0.833) in the non-smoking and smoking group, respectively. While C allele ofrs762624reduce the risk of ESCC only in non-smokers (Odds Ratio:0.696,95%CI:0.503-0.962). Rs2395655is a risky locus of ESCC in smokers, and G allele significantlyraises the susceptibility to ESCC over A allele (Odds Ratio:2.341,95%CI:1.728-3.172).ConclusionsBy the comprehensive analysis of codominant, dominant, recessive, multiple, andoverdominant genetic model, we conclude that CC genotype of rs1009316was a protectivefactor from ESCC. Compared to T allele, C allele reduces the risk of ESCC in smokers andnon-smokers. While C allele of rs762624decreases the risk of ESCC only in non-smokinggroup. Rs2395655is a novel susceptible locus to ESCC, and G allele carriers with smokinghabits have higher risk of ESCC.