Microrna Related Snps And Genetic Susceptibility To Hepatocellular Carcinoma

Hepatocellular Carcinoma (HCC) is the most common malignance worldwide. Environmental exposures and individual genetic susceptibility play important roles in the oncogenesis of HCC. Recently, researchers have discovered a new gene expression and regulation mechanism, which is called microRNA-mediated post-transcriptional regulation. Many tumor-related genes are subject to the regulation of microRNA (miRNA). The core regulatory mechanism of microRNA is the translational inhibition of microRNA induced by the Waston-Crick base-pairing of its seed zone and the target sequences of related mRNA. There are three kinds of SNPs in microRNA regulatory network:SNPs of genes that regulate the maturation of microRNA, SNPs of pre-miRNA, and SNPs of microRNA target sequences. SNPs in microRNA regulatory network can affect the structure of mature microRNA and its expression level, microRNA and its target gene identification, so that the microRNA regulatory network failure occurs, thus affect gene expression and function, and change individual cancer susceptibility. Based on the summary of relevant bioinformatics and according to the characteristics of the Chinese population, this study selected twelve SNPs in microRNA regulatory network. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and allele-specific PCR (AS-PCR) were performed to identify the twelve selected polymorphic loci. Then we compared the genotype frequency distribution in patients with HCC and control group, so as to explore whether certain genotypes, haplotypes, gene-gene and gene-environment interactions are related to the oncogenesis of HCC. This will play an important role in understanding the etiology of HCC carcinogenesis, and will lend strong evidence to personalized prevention and treatment of HCC. Objective1. To explore eight tag SNPs (tSNPs) from3genes that regulate the maturation of microRNA, they are DICER1gene loci rs3742330, RNA gene loci rs14035and rs3803012, GEMIN4gene loci rs7813, rs1045491, rs2291778, rs2740348, and rs3744741. Investigate the association of these loci and HCC susceptibility, and then speculate the possible mechanisms of how they function.2. To explore two SNPs of pre-miRNA, including pre-miR-146a rs2910164locus and pre-miR-196a2rs11614913locus. Investigate the association of these loci and HCC susceptibility, and then speculate the possible mechanisms of how they function.3. To explore two SNPs of microRNA target sequence, including IL16gene locus rs1131445and NOD2gene locus rs3135500. Investigate the association of these loci and HCC susceptibility, and then speculate the possible mechanisms of how they function.4. To conduct a comprehensive analysis of the selected SNPs, and investigate potential genotypes, haplotypes and gene-environment interactions, which might be related with the oncogenesis of HCC.MethodsTag SNPs (tSNPs) of genes that regulate the maturation of microRNA were selected by using bioinformatics. SNPs data of DICER1gene, RAN gene and GEMIN4gene in Chinese populations (CHB) were extracted from HapMap (http//www.hapmap.org) database, and then the data were imported to Haploview software (version4.2) running in accordance with the following criteria to select tSNPs:r2>0.8, the minor of allele frequency (MAF) was set at0.05. We define pairs to be in "strong LD'if the one-sided upper95%confidence bound is>0.98(that is, consistent with no historical recombination) and the lower bound is above0.7. One tSNPs rs3742330was selected from DICER1gene; two tSNPs (rs14035and rs3803012) were selected from RAN gene; five tSNPs (rs7813, rs1045491, rs2291778, rs2740348and rs3744741) were selected from GEMIN4gene. Two SNPs (pre-miR-146a rs2910164and pre-miR-196a2rs11614913) of pre-miRNA gene were selected by conducting literature review. As for SNPs of microRNA target sequences, we reviewed liver cancer related literatures and summarized ninety-six susceptible genes. Then we downloaded the SNPs of3'UTR of these genes, and predicated their target microRNA and free energy by using miRanda, PicTar, TargetScans and RNAfold webserver. Ten SNPs which strictly pair with the 'seed' sequences and were closely related with liver cancer were chosen as candidate microRNA target sequences, and ultimately, two out of ten SNPs, whose MAF>0.05and free energy(AAG) were relatively high, were selected to be verified. They are IL16gene loci rsl131445and NOD2gene loci rs3135500.560HCC patients and560controls were selected from Chinese Han Population. PCR-RFLP and AS-PCR were performed to identify the SNPs of the twelve selected loci. χ2test was used to compare the distribution differences between case-control groups, unconditional logistic regression method was used to extract the OR value and its95%confidence interval (95%CI) by adjusting for age, sex, smoking, alcohol consumption, and family history of cancer. Haploview software was used to predict haplotpyes. Trend χ2test was used to analyze the dose-effect relationship of the number of mutations and the risk of HCC. Multifactor dimensionality reduction (MDR) and multivariate logistic regression analysis were used to evaluate gene-environment interactions.ResultsResult of single locus analysis showed that TT genotype carriers of RAN gene loucs rs14035had2.40times (OR=2.40,95%CI:1.11-5.18) higher risk of suffering from HCC than CC genotype carriers. A allele carriers of locus rs1045491had1.66times (OR=1.66,95%CI:1.29-2.13) higher risk of suffering from HCC than G allele carriers; T allele carrier of locus rs2291778had0.71times (OR=0.71,95%CI:0.60-0.85) lower risk of suffering from HCC than G allele carriers. G allele carrier of locus pre-miR-146a rs2910164had1.33times (OR=1.33,95%CI:1.12-1.57) higher risk of suffering from HCC than C allele carriers. CC genotype carrier of IL16gene locus rs1131445had0.64times (OR=0.64,95%CI:0.52-0.93) lower risk of suffering from HCC than CC genotype carriers. The distribution of DICER1gene locus rs3742330, RAN gene locus rs3803012, GEMIN4gene loci rs7813, rs2740348, and rs3744741, pre-miR-196a2locus rs11614913, NOD2gene locus rs3135500showed no significant differences between case and control groups(P>0.05).Haploview softeware was used to conduct haplotype analysis of the eight tSNPs of pathway genes that regulate the maturation of microRNA. The results showed that the haplotype AATCAGGT and AGTCAGCC might increase HCC risk (OR=1.37,95%CI:1.08-1.74; OR=1.32,95%CI:1.01-1.72), while haplotype AATCGTCC and AACCGTGT might reduce HCC risk (OR=0.71,95%CI:0.55-0.93; OR=0.62,95%CI:0.41-0.82). MDR software was used to evaluate the gene-environment interactions. rs14035(allele T), rs1045491(allele A) and a history of alcohol consumption showed gene-envrionment interaction. Individuals who fit this3-order model had3.48times (OR=3.48,95%CI:2.38-5.56) higher risk of suffering from HCC than the ones who did not.Twenty haplotypes was predicted from these twelve loci by using Haploview softeware (version4.2). The results showed that haplotype AGTTAGGTCGGC might increase HCC risk (OR=2.29,95%CI:1.08-4.83), while haplotype AACTGTGCTGCC might reduce HCC risk (OR=0.62,95%CI:0.40-0.98). MDR software was used to evaluate gene-environment interactions. The results showed that3-order model was the optimal model. This model included two polymorphic loci and one environmental factor:rs14035(allele T) and rs2910164(allele G) and ahistory of alcohol consumption. Individuals who fit this3-order model had3.66times (OR=3.66,95%CI:2.19-4.40) higher risk of suffering from HCC than the ones who did not.ConclusionsRAN gene, GEMIN4gene, pre-miR-146a gene and L16gene might be involved in the process of HCC carcinogenesis. TT genotype in RAN gene locus rs14035, A allele in GEMIN4gene locus rs1045491, and G allele in pre-miR-146a rs2910164 locus might increase the risk of HCC in Henan Han population, while T allele in GEMIN4gene locus rs2291778, CC genotype in IL16gene locus rs1131445might reduce the risk of HCC in Henan Han population.Gene-gene interactions analysis of eight tSNPs of microRNA regulatory pathway genes showed that:haplotype AATCAGGT and haplotype AGTCAGCC might be the risk genetic risk factors in Henan Han population, and haplotype AATCGTCC and haplotype AACCGTGT might be the protective genetic factors in Henan Han population. Gene-environment interactions analysis showed that:T allele in rs14035, A allele in rs1045491and a history of alcohol consumption was risk gene-environment interaction of HCC.Gene-gene interactions analysis of twelve selected SNPs of microRNA regulatory network showed:haplotype AGTTAGGTCGGC might be the risk genetic factor of HCC, and haplotype AACTGTGCTGCC might be the protective genetic factor of HCC in Henan Han popualtion. Gene-environment interactions analysis showed that:T allele in rs14035, G allele in rs290164and a history of alcohol consumption might be risk gene-environment interaction of HCC. This research lends strong evidences to futher understanding the relaitionship of the genotype, haplotype and gene-environment interactions and genetic susceptibility of HCC in Henan Han population.