In silico approach for the detection of key genes and their interaction involved in breast cancer cell line Online publication date: Tue, 25-Jan-2022
by Desam Neeharika; Swetha Sunkar
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 17, No. 6, 2021
Abstract: Genes are known to play a pivotal role in Breast cancer. Any factor that that leads to a change in the expression level of the genes influences the mechanism and disturbs the functionality. Hence, our study aims to identify the key genes in the MCF-7 breast cancer cell line and their interaction with other genes using in silico approach. The microarray dataset GSE1400 was selected from gene expression omnibus (GEO) database and GEO2R tool was used and identified a total of 1932 differentially expressed genes (DEGs), of which 1809 and 123 genes were up-regulated and down-regulated respectively. database for annotation, visualisation and integrated discovery (DAVID) tool was used for functional annotations. Cytoscape was used for the screening of clusters and identification of hub genes. Among them, EGFR and HNRNPR were identified to have highest degree nodes from up-regulated and down-regulated gene networks respectively and hence can be used as possible molecular target.
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