Identification of EGFR-related pathwaysinvolved in erlotinib drug sensitivity and resistance in nonsmallcell lung cancer using bioinformatics analysis

Background: Lung cancer is the second most common canceramong people, and the main type is non-small cell lung cancer(NSCLC), which accounts for approximately ۸۵% of all lungcancers. Targeting EGFR by erlotinib is one of its key treatments,but drug sensitivity and resistance to treatment are challengesthat make the treatment process difficult for patients.we aimed to identify the pathways related to EGFR signalinginvolved in erlotinib drug sensitivity through bioinformaticsanalysis.Materials and Methods: The GSE۶۹۷۴۷ dataset from GeneExpression Omnibus (GEO) was used for bioinformatics analysis.In this dataset, ۲۰ genes related to EGFR signaling and drugsensitivity to erlotinib were knocked down in EGFR mutantH۱۶۵۰ cell line. In the present study, the differentially expressedgenes (DEGs) were identified using the LIMMA package of R,and the common DEGs were screened by Venn diagram. UsingEnrichr, DEGs were grouped based on common molecularpathways. Then, the enrichment was obtained by KEGG (KyotoEncyclopedia of Genes and Genomes) human database andthe significant pathways (P.value <۰.۰۵) were selected.Results: Our analysis revealed cell lines with PRKAA۱, LEPR,TCS۱, TCS۲ and PRKAB۱ genes knocked down had the mostexpression changes (۱۳۰۴, ۹۸۴, ۱۳۷۱, ۱۱۶۰, and ۱۱۵۰ genes, respectively).Also, the expression change of ۲۱ genes was commonin these five gene profiles and in general, ۱۴% of EGFRrelatedpathways were common in these gene profiles.Conclusion: In this study, it was found that in cells with mutatedEGFR, other pathways such as AKT/mTOR signaling canplay a significant role in sensitivity and resistance to erlotinibtreatment in patients with non-small cell lung cancer and thereis a need for special attention to research on these signalingpathways.