Identification Of Disease Markers Based On Genetic Data

Liver cancer is one of the most common malignant tumors in the world,and its incidence and mortality are ranked 6th and 3rd in the world in malignant tumors,respectively.The occurrence and development of liver cancer are a process involving multi-gene and multi-factor synergy.It takes several pathological stages and multiple molecular event changes to realize the complex process of normal liver cells to liver cancer cells.Due to the high incidence,high invasiveness,high metastasis and poor prognosis of liver cancer,most patients with liver cancer are diagnosed at an advanced stage with limited treatment and poor efficacy.Therefore,the discovery of new targets and the development of new drugs have become the research hotspots of the world medical community.High-throughput gene chip technology can explore the occurrence and development of diseases at the whole genome or transcriptome level,which has been widely used in gene expression profiling,gene cloning and searching for disease-specific molecular markers.By screening the differentially expressed genes in the gene expression profile of liver cancer and adjacent tissues,bioinformatics analysis of the differentially expressed genes is carried out.The aim of this study is to provide a theoretical basis for exploring molecular markers in early diagnosis and potential drug targets in the immunotherapy of liver cancer.The work completed is as follows:1.The two groups of liver cancer-related microarray data are downloaded from GEO database.A total of 807 differential expressed genes are screened from liver cancer tissues and adjacent tissues by using Limma package,of which 496 are up-regulated and 311 are down-regulated.GO and KEGG pathway enrichment analysis of differential expressed genes are performed by DAVID,and 128 common genes are obtained.Then,STRING database is used to construct a protein interaction network,which is visualized by using Cytoscape software and further screened for 10 hub genes.Finally,KM-plotter database and Oncolnc survival analysis website are used to analyze their survival curves,respectively.The results show that CYP3A4,CYP2C9,CYP2E1 and CYP2C8 are suitable as potential markers and drug targets of liver cancer.2.The gene expression profiles of liver cancer are downloaded from TCGA database and analyzed by R package.A total of 1564 differential expressed genes are obtained,of which 1400 are up-regulated and 164 are down-regulated.The GO and KEGG enrichment analysis of differential expressed genes are performed by DAVID.The STRING database is used to construct a protein interaction network,which is visualized using Cytoscape software and further screened for 15 hub genes.In addition,Oncomine database and survival analysis method are used to verify the hub genes.These results shown that PLK1,CDC20,CCNB2,BUU1,MAD2L1 and CCNA2 genes are closely related to the occurrence,development and prognosis of liver cancer.These genes could be used as potential markers and drug targets of liver cancer,which are provided to assist deeper understanding the mechanism of liver cancer,and find tumor markers and drug targets.3.The gene expression data and clinical information data are download from TCGAdatabase.A total of 1564 differential expressed genes are obtained from 371 liver cancer sample tissues and 50 normal tissues.CTSE,ESR1 and OR2T2 genes are screened by univariate,Lasso,and multivariate Cox regression analysis.The prediction model is established,and further analysis revealed the independent prognostic ability of the prognosis model compared with other clinical features.The good performance of the prediction model is confirmed by curve analysis.Finally,the clinical data in the TCGA database are used to analyze the survival of the three key genes selected by the model.The prognostic value of these key genes on the overall survival of patients with liver cancer is studied,and the high expression of CTSE and ESR1 are related to that of liver cancer.The occurrence and development and prognosis are closely related,which is of great significance for the study of liver cancer.