Identification of Genes and Pathways Involved in Breast Cancer Subtypes through Expression Meta-analysis

Early diagnosis of breast cancer (BC), that whether it is invasive or non-invasive, is crucial in the field of breast surgery. The objective of this study was to discover the crucial genes, miRNAs, and TFs linked to the development and prognosis of BC. A meta-analysis was conducted on several gene expression profiles. A total of 14 datasets were analyzed to identify genes that were expressed differently between subtypes of BC and normal breast tissue samples. An analysis was conducted on the Gene Ontology (GO) concepts and pathways. The miRNAs, TFs, and drugs were predicted based on the DEGs. Furthermore, The DEGs identified from the meta-analysis were confirmed using an independent and comprehensive BC RNA-sequencing dataset collected from TCGA.A total of six DEGs were found to be common across all subtypes of BC. The primary enriched KEGG pathway was the "PPAR signaling pathway. "The hub genes identified in the PPAR pathway were LPL, FABP4, and ADIPOQ. The current investigation of the first meta-analysis of gene expression in five histological subgroups of breast cancer has linked three genes to all subtypes of BC. By employing gene expression profiling in conjunction with a meta-analysis technique, it is possible to identify new and diagnostic biomarkers as well as potential treatment targets for BC.