Screening The Core Gene Of Breast Cancer Prognosis Based On The Principle Of Chip Analysis And Evaluating Its Predictive Effect

Objective:By mining the gene chip data provided by the Euro pean Molecular Biology Laboratory(EMBL),meanwhile,combined with bioinformatics related statistical methods,so we can screen an d evaluate the core genes that determine the prognosis of breast ca ncer.Methods:①First,we obtained the gene chip data provided by European Molecular Biology Laboratory,and classified them accor ding to different prognosis classifying into better prognosis group a nd poor prognosis group.②The differentially expressed genes betw een the better prognosis group and the poor prognosis group were s creened by SAM algorithm,and the gene function was described b y NCBI’s gene information database.③Based on KEGG and Gene Ontology database,the differential signal pathways between the bett er prognosis group and the poor prognosis group were screened by KoBAS software.④MCODE algorithm was used to construct a gen e co-expression network for prognosis of breast cancer.⑤The accur acy of core genotyping was verified by discriminant analysis modul e in SPSS16.0.Results:① In this study,342 samples of gene chip were colle cted from European Molecular Biology laboratory.342 cases of bre ast cancer gene chip samples classified as a better prognosis of gen e chip sample of 167 cases(48.83%),including 93 cases of ductal carcinoma in situ(27.19%),74 cases of lobular carcinoma in situ(21.64%);classified as poor prognostic gene chip samples in 175 c ases(51.17%),including 155 invasive ductal carcinoma(45.32%cas es),20 cases of invasive lobular carcinoma(5.85%).② According to the differentially expressed gene screening conditions(Fold chan ge>2 and P<0.05),743 differentially expressed genes were obtained,in which the IGF1 gene had the largest expression difference amo ng the different prognostic groups.Besides,4 of top 5 differential expression genes(IGF1,PIK3CA,OGN and PPAP2B)gene encodin g protein had greater similarity in function,they are involved in an giogenesis and carbohydrate metabolism.③ The 743 differentially e xpressed gene signal pathway enrichment results showed that adhesi on kinase signal pathway got the highest score(P<0.05).④ Based on the 743 differential expression genes in different prognosis group s,the network construction of a total of 81 differentially expressed genes co-expression were obtained,which determine the prognosis o f breast cancer control were the highest gene is PIK3CA,which ca n be considered as the core of the gene is to determine the progno sis of breast cancer the genes.Besides ACTB,RAC1,ITGB1 and IT GB5 gene are also the core gene in co-expression network.The exp ression of the core gene in the poor prognosis group has been impr oved.⑤ PIK3CA gene’s expression affected by GNG2,LYN,GNB1],GNB5,CRK,RAC1,IRS2,IGF1,PDGFRA and IGF1R gene’s expr ession,GNG2,LYN,GNB1,GNB5,CRK,RAC1 and IRS2 gene ma y directly affect the expression of PIK3CA gene,and IGF1,PDGF RA and IGF1R directly affect the expression of PIK3CA gene.⑥Here we did a meta-analysis about the relationship between PIK3C A gene and the prognosis of breast cancer.The results showed that the heterogeneity of breast cancer prognosis prediction sensitivity a nd specificity were relatively high(both SEN I2 and SPE I2 are hig her than 50%);Then we explored the sources of heterogeneity thro ugh subgroup analysis,the results showed that heterogeneity was no t significantly reduced and the difference was not statistically signifi cant because of the high heterogeneity caused by different methods of analysis or different types of prognosis.The SEN value was 0.85(95%CI:0.82-0.88),and the SPE value was 0.79(95%CI:0.75-0.83)after the combination of the random effect model.It is found t hat the change of heterogeneity is not significant after eliminating t he literature in turn,so it is considered that the research results are stable.⑦ Simple cross validation results show that the 5 core gen es in this study were obtained to determine the results with the ori ginal type of inconsistency of a total of 27 cases,the error rate is 7.89%(P<0.05);the K fold cross validation results show that the 5 core genes in this study were obtained to determine the results with the original type of inconsistency of a total of 37 cases,the error rate is 10.82%(P<0.05);leave one out cross validation results sho w that the 5 core genes in this study were obtained to determine t he results with the original type of inconsistency of a total of 27 c ases,the error rate is 7.89%(P<0.05);therefore the core gene can p redict the type of breast cancer prognosis accurately.Conclusion:①PIK3CA,ACTB,RAC1,ITGB1 and ITGB5 are t he core genes from the co-expression network,and the expression o f the core gene in the poor prognosis group has been improved.So these genes are thought to play the most important role in determi ning the prognosis of breast cancer.②The expression of the core g enes in the coexpression network is of high accuracy in predicting the prognosis of breast cancer,therefore PIK3CA,ACTB,RAC1,IT GB1 and ITGB5 genes may be used as molecular markers for predi cting the prognosis of breast cancer.