Research On Integrating Multi-omics Data Mining Driver Genes Of Gastric Adenocarcinoma

The latest data show that gastric cancer has become the fourth leading cause of cancer deaths.Conventional gastric cancer treatment methods such as surgical resection,radiotherapy,and chemotherapy have low cure rates,low five-year survival rates,and lack of targeted treatment.Therefore,it is particularly important to find genes related to the occurrence and development of gastric cancer at the molecular level,that is,the driver genes mentioned in this article,to provide biomarkers for the early diagnosis of gastric cancer and to provide effective targets for the targeted therapy of advanced gastric cancer.This paper uses bioinformatics methods to integrate and analyze gene expression data,DNA copy number variation data and miRNA data from gastric adenocarcinoma samples from different regions,in order to dig out the driver genes that are closely related to the occurrence and development of gastric cancer.In the past,most of the studies either analyzed the single genomic data in groups,or integrated the multi types of genomic data without grouping,resulting in more differential genes and lack of pertinence,which is difficult to provide accurate targets for the targeted treatment of gastric cancer.In this paper,on the premise of grouping and integrating multiple types of genomic data,we accurately mine genes that may be related to the occurrence and development of gastric cancer.First of all,this paper conducts an integrated analysis of the gene expression data and DNA copy number variation data of Asians and Caucasians obtained from the official website of TCGA.The differentially expressed genes shared by the two sets of data samples were screened out,and gene function enrichment analysis and pathway analysis were performed on them.Then import it into the String database to establish a protein interaction network,and filter out two important sub-networks from this network.Finally,49 driver genes that may be related to the occurrence and development of gastric adenocarcinoma were screened from the sub-network,and the expression of these genes was positively correlated with the number of gene copies.Secondly,this paper uses the miRDB database to predict the differentially expressed miRNA target genes shared by the two sets of gastric adenocarcinoma miRNA data samples,and integrates with those genes whose gene expression and gene copy number are positively correlated to establish a miRNA-target gene regulatory network.Perform gene function enrichment analysis and pathway analysis of target genes in the regulatory network,and screen out 36 genes that may be related to the occurrence and development of gastric adenocarcinoma.Excluding the repetitive occurrences of the 49 genes previously obtained,a total of 77 driver genes that may be related to the occurrence and development of gastric adenocarcinoma were unearthed in this paper.Studies have shown that 24 of these genes are indeed related to the occurrence and development of gastric cancer.The remaining 53 genes may be specific driver genes that play an important role in the occurrence and development of gastric cancer in Asians and Caucasians.Driver genes can provide a new reference basis for early diagnosis of Asians and Caucasians and targeted therapy in the middle and late stages.The research methods in this article provide new ideas for finding biomarkers for early diagnosis of gastric cancer and targeted therapy genes.