Screening And Bioinformatics Analysis Of Genes In Triple Negative Breast Cancer

Triple negative breast cancer(TNBC)is a special subtype of breast carcinoma characterized by ER-negative,PR-negative and HER2-negative,and represents 15% of breast cancers.TNBC had the worst survival rate with its highly diffusivity and invasiveness and lacks validated therapeutic targets compared with other breast cancer subtypes.Therefore,most of the current studies have focused on identifying effective targets for the treatment of TNBC,and researching effective therapeutic targets and finding diagnostic and prognostic markers with high sensitivity and specificity are the key to improve the prognosis of patients with TNBC.Bioinformatics is an interdisciplinary subject involving life sciences,mathematics,and computer science.Many studies have shown that integrated bioinformatics analysis can help to explored the underlying molecular mechanisms of disease,and unearth targets with research value and potential effects.In this study,we downloaded two original microarray datasets,GSE38959 and GSE121657,from the Gene Expression Omnibus(GEO)database and reanalyzed potential hub genes and mi RNA master regulators related with TNBC progression using bioinformatics methods.The main results are as follows:1.Bioinformatics identification of DEGs in TNBC based on m RNA expression profiling1340 differentially expressed genes(DEGs)were screened from the data set GSE38959 by GEO2 R.These differential genes are mainly involved in cell cycle,systemic lupus erythematosus,alcoholism,small cell lung cancer,viral cancer,tumor pathway,ECM receptor interaction,DNA replication,as well as meiotic antibiotic biosynthesis,p53 signaling pathway,progesterone mediated oocyte maturation and bacterial infection.The results of string analysis showed that CDK1,CCNB1,PLK1,CCNA2,CCNB2,BUB1,BUB1 B,MAD2L1,NDC80,CDCA8 and other proteins interacted with more than 10 kinds of proteins and were the nodes of protein interaction network.After deleting these nodes,the network structure was relatively loose.These genes may be the key genes leading to TNBC.Combined with the analysis results of relevant signaling pathways and the key roles of core genes,it is found that the disorder of cell cycle regulation may lead to the occurrence and development of TNBC.2.Bioinformatics identification of micro RNAs in TNBC based on micro RNA expression profilingSixty-one differentially expressed micro RNAs were screened and 165 corresponding target genes were obtained.These target genes are mainly involved in cell localization,cell cycle,cell division,apoptosis and other biological processes.It is mainly involved in the regulation of PI3K-Akt signaling pathway,platelet activation,focal adhesion,and actin cytoskeleton signaling pathway.Three key target genes,YWHAG?ACTR2 and ACTR3 linked to one mi RNA,hsa-mir-141-3p,and suggested that mi RNA hsa-mir-141-3p may is a good classifier of TNBC and might play key roles in the progression of TNBC.In summary,this study analyzed the gene expression profile data and micro RNA expression profile data through bioinformatics method,and found key genes and key micro RNA regulatory molecules of TNBC,which provided a reference for further experimental studies and was beneficial to guide for the further research on TNBC.