Identification of a Novel Genetic Mechanism Involved in Repeated Lipopolysaccharide (LPS) Enabled Carcinogenesis of Lung Cancer
Aim: To identify the gene expression of Lipopolysaccharide (LPS) in lung cancer by analysing and comparing the data retrieved from the GEO database. Materials and methods: The Microarray dataset was retrieved from NCBI gene expression omnibus (GEO) with ID GSE132661 to find significant genes and upregulated and downregulated genes. STRING analysis is used to find the relations between upregulated and downregulated genes to find possible interactions in lung cancer. Enrichr analyses were used to compare input gene sets with annotated gene sets to find pathways and ontologies. ‘CytoHubba’ plugin of ‘Cytoscape’ used to analyze the data from STRING to identify HUB genes. Results: We observed 11753 genes were significantly overexpressed and upregulated genes (UG) (log FC ≥ 1) 73 genes and downregulated genes (DG) (log FC ≤ −1) 56 genes co-expressed in lung cancer. STRING analysis is used to find 33 possible interactions in lung cancer. Enrichr analysis were used to find cellular biological pathways involved in inflammatory responses. ‘CytoHubba’ is used to identify RELN, NTRK2, MYCN, DMD, WT1, PIK3C2A, PLCZ1, PIP5K11 as HUB genes. ‘ClueGO’ identified pathways like PIP kinase activity and IP metabolism involved in inflammatory responses. Conclusion: We identified the gene expression of eight hub genes that are involved in different pathways. Furthermore, our results suggest that these novel gene expressions could be targeted for the further drug discovery process.