Bioinformatics Analysis Of Differentially Expressed Genes In Ovarian Cancer And Meta Analysis For Differentially Expressed Gene CD24

Background:Ovarian cancer is a common malignant tumor of the reproductive system in women.Its the most common gynecological malignant tumors in women,as well as cervical cancer and endometrial cancer.The morbidity of ovarian cancer is the second,but the mortality is the first,and the five-year survival rate for advanced ovarian cancer is only 30 percent.According to the statistics,there were 52,100 new diagnosed ovarian cancer and about 22,500 women died of ovarian cance in 2015 in China.The mechanism of ovarian cancer is unknown,and the diagnosis and treatment is difficult,and the prognosis is extremely poor.So,ovarian cancer seriously threat females’ health.Therefore,the research on the development mechanism of ovarian cancer is of great significance for the early diagnosis and treatment of ovarian cancer.Nowadays,the development of bioinformatics has provided great convenience for the study of ovarian cancer.We can study the molecular mechanism,diagnosis,treatment and prognosis by using bioinformatics methods,so as to provide us directions and clues for our research.Objective:This study is based on bioinformatics methods and tools,the microarray data of the ovarian cancer were analyzed to screen the differentially expressed genes.And the functional annotation and pathway analysis of differentially expressed genes were analyzed so as to analyze and predict the biological functions of these differentially expressed genes.Select key differentially expressed genes and find the target genes of interest,then Meta analysis was used to analyze the significance of the target gene in ovarian cancer.Methods:Screening expression of ovarian cancer microarray data and downloa GSE52460 as the research object from the GEO database of NCBI.The limma package from R language and Bioconductor packages were used to analysis GSE52460 so as to identify differentially expression gene.The gene probe number is converted to a gene symbol using DAVID database.GO functional annotation and KEGG pathway analysis of differentially expressed genes were also performed by using DAVID database.NCBI database was used to query the first 10 differentially expressed gene to learn their biological functions,then the gene CD24 was screened for Meta analysis.CNKI,VIP,WanFang,PubMed,The Cochrane Library,Springer Link and OVID database were searched to collect studies investigating the correlation between CD24 expression and different clinical features of ovarian cancer.After independent screening of the literature and evaluation the risk of bias by two researchers,the meta-analysis was performed using RevMan 5.3 software.Results:1.Combining with GEO database,the ovarian cancer related gene chip GSE52460 were obtained.Through the analysis of GSE52460,totally 1505 gene were obtained,among them 206 genes were up-expressed and 1299 genes were down-expressed.2.The GO biological analysis and KEGG pathway analysis of the differentially expressed genes were analysed by using DAVID.The up-expressed differentially expressed genes were mainly involved in cell mitotic,cell proliferation,the separation and integration of sister chromosomes,and mainly particapate in the formation of midbody,condensed chromosome kinetochore,cytosol,and mainly involved in protein binding,he structure of extracellular matrix,protein enzyme binding,P53 signal pathway,cell cycle,PI3K-Akt pathway and so on.The down-expressed differentially genes mainly involved in positive regulation of cell migration,development of cartilage,regulation of cell morphology,and mainly participate in cytoplasm,Golgi apparatus,cytomembrane,endoplasmic reticulum,and mainly involved in protein binding,Ca binding,growth factor binding,Ras signal pathway,PI3K-Akt pathway and so on.3.After quering the first 10 differentially expressed gene function using NCBI database,we found that CD24 gene mainly involves in the migration of cell adhesion cells,the differentiation and regulation of epithelial cells.Mainly paticipate in cytomembrane,cytoplasm and GPI-linked proteins,and mainly involved in protein binding and protein enzyme binding.4.The results of meta-analysis showed that:1.The CD24 expression was increased as the sort order of normal ovarian tissue,benign ovarian tumors,borderline tumors and ovarian cancer.There was significant difference in CD24 expression among the groups,and the difference was statistically significant(P<0.05).Besides,CD24 overexpression was associated with lymph node metastasisand and higher FIGO(P<0.05).But there was no significant difference between the age of the patients(P>0.05).Conclusions:1.Using bioinformatics methods and tools,we successfully screened out the ovarian cancer differentially expressed genes,and the key genes.Gene function analysis was performed on the first 10 genes of differentially expressed genes to obtain the target gene CD24 for the follow Meta analysis.This method is convenient and time-saving,and contribute to reduce the blindness of the research process.2.Through meta analysis,we found that the expression of CD24 was related to the behavior of the tumor,lymphatic metastasis and the stage of ovarian tumor.