Exploring Hub Genes In Lung Cancer Using Integrated Bioinformatics Analysis

Malaysian has suffered from lung cancer, accounting for around 10% of all cancers reported in 2021. Prioritization of early diagnosis and natural treatments of lung cancer patients is crucial to improve their survival rate.The aim of this study is to identify the miRNA-mRNA and potential hub gene corresponding to lung carcinoma and natural drugs candidates to inhibit progression of lung cancer via insilico approaches.GSE176348,GSE85841 and GSE164750 gene expression profiles were retrieved from NCBI and GEO2R analysis was carried out accordingly to principal standard p<0.05 and logFC>1 to identify up-regulated and down-regulated genes from the datasets. Protein-protein interaction analysis of up-regulated and down-regulated genes was performed in Cytoscape software and top 10 hub genes were observed by cytohubba tools plugin in Cytoscape.Next, Biological Process (BP), cellular component (CC), molecular function (MF) of top 10 up regulated and down regulated hub genes were observed via DAVID server. The survival curves of top 10 up and down regulated hub genes were constructed by the Kaplan-Meier plotter and the expression level of hub genes in lung cancer tissues and normal tissues analyzed via GEPIA2 online database. IMPPAT: Indian Medicinal Plants, Phytochemistry And Therapeutics database was utilized for selection of potential natural drug candidates for lung cancer and ADME test was carried out on the selected drug compounds.To identify the most promising drug candidates,the hub genes were docked with respective natural drugs candidates via Swiss Dock online tool.Finally, The Encyclopedia of RNA Interactomes (ENCORI) database was used to study the MIRNA-MRNA network of targeted hub genes.In summary,this study is helpful in discovery of miRNAs-mRNA and analysis of natural drug candidates to inhibit lung carcinoma.