Determination of the EGFR Gene Role in Lung Cancer Pathway using STRING and Cytoscape Software
Year: 2024
Type: article
Abstract: The leading cause of cancer-related fatalities worldwide is lung cancer. Both non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), the two main types of lung cancer, have successfully responded to chemotherapy, radiation therapy, and adjuvant therapies. Surgery to remove the tumor also seemed to be a successful treatment plan. However, these treatments showed undesirable side effects; therefore, new lung cancer-targeting medications have become crucial. Activation of EGFR-tyrosine kinases is the main reason for lung cancer development. In this study, the EGFR gene involved in the lung cancer pathway was mapped using bioinformatics applications such as STRING version 11.5 and Cytoscape version 3.8.2 to provide a clear visualization of all the related and involved proteins and genes that interact with the EGFR gene in the pathway. Using EGFR as a seed, a protein-protein interaction network was generated with 2343 interactions obtained from the STRING version 11.5 database. The protein network interaction was further clustered into 6 groups using the MCODE application. The molecular function and biological processes of the genes involved in the EGFR protein network were determined using Biological Networks Gene Ontology (BiNGO). The protein-protein network interaction map results show that the EGFR mechanism and co-expressed genes are interconnected with protein or enzyme binding, signaling receptor binding, MAPK cascade, and regulation of cell death. Understanding these protein-protein interactions can give us insight into biological processes and, in turn, help us understand how oncogenic diseases develop.
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W4406288084