Meta-Analysis of Microarray Data IdentifiesKey Biomarkers in Breast Cancer

Background: Breast cancer is a very heterogeneous disease.Identification of new molecular markers could help diagnosisand treatment of the disease.Materials and Methods: Breast cancer datasets with theAffymetrix Human Genome U۱۳۳ plus ۲.۰ Array (HG-U۱۳۳_Plus_۲) platform containing ۱۸۷ tumor and healthy sampleswere extracted from Gene Expression Omnibus (GEO). BioconductorSVA package corrected the batch effect between thetwo datasets and normalize the data. Following the correctionof batch effects, differentially expressed breast cancer geneswere identified from the resulting matrix, by the Limma package.Then the cellular pathways in which genes play a rolewere identified using the Enricher database and the KEGG repository.The PPI network of DEGs was constructed with theSTRING database and by Cytoscape and CytoHubba plugin,we reached the hub genes of the PPI network.Results: Among the identified DEGs, the up-regulated geneswere mainly involved in pathways related to the cell cycle, p۵۳signaling pathway, and estrogen signaling pathway, and downregulatedgenes were involved in the PPAR signaling pathway.Interestingly all the related pathways play a role in the progressionand metastasis of breast cancer. Among the hub genes,NUSAP۱, CCNB۱, CEP۵۵, EZH۲, RRM۲, MELK, PRC۱, andCDC۲۰, which had the highest degree in the PPI network, wereintroduced as hub genes and candidates for breast cancer biomarkers.Conclusion: The meta-analysis resulted in the identification ofhub genes in breast cancer and their related molecular pathways.The identified hub genes could be suggested for further investigationas biomarkers or therapeutic targets in breast cancer

کلیدواژه ها:

Meta-analysis ، Breast cancer ، Microarray Analysis ، Biomarker