In silico analysis of some potential molecular alterations in breast tumors compared to the adjacent normal tissues

The incidence of breast cancer among women worldwide is on the rise. In recent decades, advancements in microarray technology have made it possible to collect and analyze extensive relevant data, allowing for a more precise identification of genes involved in the development and progression of cancers. In this study, we extracted and merged three datasets (GSE109169, GSE80754, and GSE72644) containing breast cancer tumor samples and adjacent healthy tissues from the NCBI database. Utilizing appropriate software, we identified key genes with altered expression and evaluated their co-expression. We also determined the gene ontology (GO) for these key genes and examined the associated microRNAs and transcription factors. Our findings revealed that the genes PPARG, LEP, ADIPOQ, LPL, LIPE, FABP4, PLIN1, and CIDEC exhibited significantly decreased expression. Conversely, ten genes—AURKA, DLGAP5, NCAPG, CCNB1, KIF23, KIF11, BUB1B, RRM2, UBE2C, and NUSAP1—showed increased expression. Additionally, two microRNAs, has-miR-6782-5p and has-miR-6836-5p, had the strongest associations with the down-regulated genes, while has-miR-7110-5p and has-miR-7106-5p were most closely linked to the up-regulated genes. Furthermore, PPARG was identified as the most important transcription factor regulating the key down-regulated genes, whereas E2F4, FOXM1, E2F1, and MYC were significant in controlling the up-regulated genes. The results of this study can inform the design of beneficial therapeutic methods to help prevent breast cancer.