Screening Of Potential Biomarkers For Breast Cancer Based On Bioinformatics

Objective:with the aging of population in China,the incidence of malignant tumor in China is increasing year by year.The incidence of lung cancer is the highest,followed by gastric cancer and colorectal cancer.The incidence of breast cancer is the highest in female cancer patients.Therefore,screening a molecular marker that can guide the early diagnosis of breast cancer plays a key role in preventing the occurrence and development of breast cancer.With the rapid development of bioinformatics,biological big data,such as gene chip data,RNA-seq data,has been rapidly increased.Using bioinformatics analysis methods and bioinformatics analysis software,we can analyze bioinformatics and find targets related to the occurrence and development of diseases.It provides a new way to study the formation and development of disease.Methods:1,download gene chip data from GEO database,screen differentially expressed genes related to breast cancer by using bioinformatics software in R language,and then use WGCNA method for differential expression genes.A gene coexpression module was constructed.According to the clinical information of each sample in the GEO database,gene modules related to breast cancer were screened.At the same time,the co-expression relationship of genes in the module was visualized by Cytoscape.The RNA-seq data of breast cancer patients were downloaded from GEO,and the.sra file was converted to.fastq file by sratoolkit software.Then the quality of RNA-seq data is evaluated by FastQC software,and the data of poor quality is eliminated.Then the data is compared to the human reference genome by HISAT software,and then the expression level of genes in transcriptional group is quantified by StringTiesoftware.At the same time,the data is converted into a format that Ballgown can read.In order to verify the results of bioinformatics and software analysis,it is best to use R language Ballgown to carry out gene differential expression analysis and screen out differentially expressed gene.3.The breast tissues of breast cancer patients and those of non-breast cancer patients were collected and the results of bioinformatics analysis were detected by fluorescence quantitative PCR.Results:by analyzing the microarray data of breast tissues,we screened out 2404 genes related to the occurrence and development of breast cancer,and constructed 11 gene coexpression modules,and analyzed the correlation with the clinical information of the samples.The yellow module was selected to be closely related to breast cancer,and then go enrichment analysis was carried out.The results showed that the major enriched biological processes included morphogenesis of embryonic epithelial cells and formation of embryonic epithelial tubules.Epithelial tubule formation and so on.Four genes,RAB25,KRT19,SPINT2 and AP1M2,were selected by visual analysis of their genes by Cytoscape software.They were significantly related to the occurrence and development of breast cancer.The gene differential expression of RNA-seq data in breast cancer tissue was analyzed by gene differential expression analysis.I screened out the AGR2,AGR3,AMP11,POSTN and KRT19 genes.Comparing the results of RNA-seq data analysis with the results of microarray data analysis,and combining with literature research,we found that KRT19 plays a key role in the occurrence and development of breast cancer.Its expression level was significantly related to the occurrence and development of breast cancer.By fluorescence quantitative PCR assay,we verified the results of bioinformatics analysis and found that KRT19 gene was significantly overexpressed in breast cancer tissues.It is suggested that KRT19 plays a key role in the development of breast cancer and can be used as a molecular marker for early diagnosis of breast cancer.