Analysis Of Liver Cancer Gene Mutations Based On Integrated Data

Liver cancer is the fifth most common cancer and the third leading cause of cancerrelated death worldwide.The occurrence of liver cancer is related to many risk factors.A number of case-control studies identified a number of susceptibility mutations in liver cancer,but there were significant differences between the results of specific polymorphic sites(SNP).Therefore,systematic integration analysis based on casecontrol study data of liver cancer is necessary for us to have a deeper understanding of the genetic risk of polymorphism in liver cancer.In addition,based on the large-scale human genome cohort data and the linkage disequilibrium rule of the genome,we can carry out linkage analysis on liver cancer associated SNPs and discover new potential liver cancer associated genetic loci.In this dissertation,we focused on evaluating the known susceptibility genes and mutations of liver cancer,discussed the regulatory methods and functions,and applied sequencing techniques to further explore and study unknown genes and mutations.The first part of this dissertation is a meta-analysis and systematic evaluation study of the existing genetic mutations associated with liver cancer.A total of 2,667 relevant literatures were screened by keyword searching.A total of 69 susceptibility sites to liver cancer were included.Three genetic models were used for meta-analysis.The results showed that 25 genes with 31 sites were significantly associated with the risk of liver cancer.Based on the cumulative epidemiological evidence grading criteria,we identified a site rated A(NQO1 rs1800566).In addition,we constructed a liver cancer susceptibility gene database-HCCdb based on these data for follow-up analysis.In the second part of this dissertation,functional annotations were performed on the susceptibility sites of hepatocellular carcinoma,and the mechanisms governing the expression of hepatoma cells were explored.Genome-wide association analysis(GWAS)has become an important tool in the identification of genetic risk sites for a variety of cancers.However,most of the identified risk sites are located in the noncoding regions and regulatory regions of the genome,and the mechanism and function of these mutations for cancer susceptibility are still unclear.In this work,we performed functional annotations based on genomic structure regions,apparent modification regions and transcription factor binding regions,and liver cancer expression data for 13 HCC GWAS tag-SNPs.It was found that the exons,promoters and adjacent enhancers of KIF1 B and PGD were all affected by HCC-associated SNPs.In addition,an annotation of the transcription factor binding regions revealed that the liver cancer susceptible mutation rs11121557 affected the binding of NFE2L2 to the PGD upstream enhancer,thereby affecting the expression of PGD.In the third part of this dissertation,we delineated the mutation landscape of hepatoblastoma.To identify mutations in hepatoblastoma,we performed a wholeexome sequencing of 20 pairs of hepatoblastoma tumor tissues and paracancerous tissues.We found that the mutation rate of hepatoblastoma was very low,similar to other childhood tumors.Furthermore,we further confirmed that CTNNB1 is the most frequently mutated gene in hepatoblastoma,and the Wnt signaling pathway is the primary signaling pathway.We also identified new mutations such as KMT2 D,FAM47C,and MUC16,and calcium signaling pathways,MAPK signaling pathways,and mTOR signaling pathways.The chromosomal rearrangement variants of CTNNB1 and MUC16 and seven germline mutant genes such as FANCL were also identified for the first time.In conclusion,this paper studied the genetic mechanism of liver cancer and found many key genes related to the development of liver cancer.Many genes were discovered for the first time.Our research results have important theoretical significance and potential application value for in-depth understanding of the occurrence,development,individualized prevention and prognosis of liver cancer.