Screening Of Differentially Expressed Genes For Trastuzumab-resistant Her2-positive Breast Cancer Based On Bioinformatics

Objective:Breast cancer is one of the most common malignancies among women worldwide.In recent years,the incidence of breast cancer has been increasing.Domestic and international studies have reported that Her2 overexpression is closely associated with the occurrence,progression,invasion and metastasis of breast cancer,and trastuzumab,a landmark targeted drug for the treatment of Her2-positive breast cancer,has effectively improved the overall survival(OS),disease-free survival(DFS)and ot Her prognostic conditions.However,70% of trastuzumab users develop drug resistance within 1 year,which affects the clinical efficacy.Bioinformatics is mainly based on genomics and proteomics to obtain genomic information and related data,and use them systematically to solve major biological and medical problems.In this study,we propose to analyze the gene expression profile microarray data of trastuzumab-resistant Her2-positive breast cancer based on bioinformatics analysis,screen the differentially expressed genes(DEGs)of both,and perform functional annotation,signaling pathway analysis and survival analysis on the differentially expressed genes to investigate the role of related genes in tumor development and find the genes that affect trastuzumab-resistant Her2-positive breast cancer.The study will provide a partial theoretical basis and a new direction for better study of Her2-positive breast cancer and trastuzumab resistance mechanism.Method:Firstly,the gene expression profile datasets were selected by setting up a search from the GEO(Gene Expression Omnibus)database,group the samples in the selected data set according to the research direction,analyze with GEO2 R online analysis tool and get DEGs.Using Venny2.1 to process the preliminary screening DEGs by taking the intersection to obtain common DEGs.The cell composition,molecular function,biological process and signal pathway of DEGs were enrichment analyzed by R language program.Setting up screening conditions to screen the common DEGs,and analyse each gene of eligible genes.The analysis content including:(1)Compared in the TIMER2 database,among multiple cancers,the difference in the expression level of target genes in cancer tissues and corresponding normal tissues;(2)to observe the difference of gene expression between cancer tissues and normal tissues and the location of gene expression in cells by HPA(Human Protein Atlas);(3)the analysis of tumor genome map(TCGA)database can be used to determine the clinical characteristics of genes.(4)enrich the gene signal pathway by using gene set enrichment analysis software(GSEA).(5)using the interactive online server GEPIA2(Gene Expression Profiling Interactive Analysis 2)to find the relationship between the selected genes and the known trastuzumab resistance-related genes in Her2-positive breast cancer.Result:Two gene expression profile datasets,GSE44272 and GSE50948,were obtained through data set screening.After GEO2 R analysis and setting of cut-off value of differential gene screening,2614 and 1248 differentially expressed genes were obtained respectively.The intersection of the up-regulated and down-regulated differentially expressed genes in the two datasets was obtained,and 47 genes with common differentially expressed up-regulated genes and 63 genes with common differentially expressed down-regulated genes were obtained.Functional enrichment analysis of differentially expressed genes and common differentially expressed genes in the two datasets showed that the biological processes were mainly reflected in neutrophil-mediated immune response,translation initiation,regulation of erb B signaling pathway,cell adhesion and so on.Cellular components are mainly in the nucleus,spindle,cell cortex,adhesion nodes and ot Her parts.Molecular functions are mainly reflected in the activity of transcription co-regulatory factors,protein heterodimerization activity,cell adhesion,etc.In terms of signaling pathways,it mainly affects autophagy and apoptosis,tight juncture,focus adhesion,proteoglycan in cancer,platinum resistance,AMPK signaling pathway,PI3K-Akt signaling pathway,m TOR signaling pathway,Hippo signaling pathway,JAK-STAT signaling pathway,signaling pathway regulating stem cell pluripotency,hypoxia-inducible factor 1 signaling pathway and so on.After setting screening conditions,110 common differentially expressed genes were screened one by one,and two genes,MTRF1 L and RBM5,were obtained.Single gene analysis was performed on the two genes of MTRF1 L and RBM5.Through the TIMER2 database,it is found that MTRF1 L and RBM5 are lowly expressed in Her2-positive breast cancer,and the expression of the two genes in various cancer types and corresponding normal tissues can be seen.In HPA,you can see the different expression of MTRF1 L and RBM5 between breast cancer and normal breast tissues.Among them,the expression position of MTRF1 L protein is on the cytoplasm/cell membrane;the expression position of RBM5 protein is on the nucleus and nuclear membrane.MTRF1L and RBM5 are both expressed although t Here is no strong correlation between the clinical characteristics,such as tumor stages and grades.Through GSEA analysis,MTRF1 L and RBM5 were enriched in the signaling pathways related to trastuzumab resistance,such as TGF? signaling pathway,JAK-STAT signaling pathway,Wnt signaling pathway,erb B signaling pathway,insulin signaling pathway,m TOR signaling pathway,and MAPK signaling pathway.Through statistical analysis,this study found that MTRF1 L was correlated with Akt1,EGFR,FASN,Her4,MAPK1,m TOR,Notch1,PIK3 CA,PTEN and STAT3.RBM5 is correlated with FASN,Her4,m TOR,Notch1,PIK3 Ca,STAT3 and TGF?1.Conclusion:1.Using bioinformatics methods to study trastuzumab resistance in Her2-positive breast cancer.2.MTRF1 L and RBM5 are enriched in the signaling pathways related to trastuzumab resistance.3.MTRF1 L and RBM5 are associated with some known genes related to trastuzumab resistance in Her2-positive breast cancer.