Lung Cancer Biomarker Identification from Differential Expression Analysis Using RNA-Seq Data for Designing Multitargeted Drugs

Lung cancer presents a global health challenge, demanding exploration of its molecular intricacies for treatment targets. The goal is to delay progression and intervene early, reducing patient burden. Novel biomarkers are urgently needed for early diagnosis. We analysed RNA sequencing on lung cancer samples from NCBI's SRA database. Using Bioconductor in R, we identified key genes, including hub genes TOP2A and TMEM100, crucial for cellular processes. Additionally, FDA-approved drugs are repurposed as multitargeted inhibitors against upregulated genes, validated through simulations. This approach aims to inhibit the function of crucial genes, potentially offering effective treatment for lung cancer within a comprehensive strategy.