Background: Lung cancer is still a major public health problem in the world, and it is still one of the leading causes of cancer mortality. Non-small cell lung cancer (NSCLC), which mainly includes lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), constitutes the majority of diagnosed lung cancer cases. While significant advances have been made in treatment strategies, it is still crucial to identify potentially useful molecular markers and clinically relevant therapeutic targets to advance patient care and disease management. Methods: An integrated bioinformatics platform was used to analyze transcriptomic, clinical, and pharmacogenomic data from publicly available databases, such as The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), STRING, DrugBank, and DGIdb. Differential expression analysis was used to find genes related to NSCLC. Protein–protein interaction network construction, functional enrichment analysis, prognostic evaluation, and drug–gene interaction analysis were then conducted to identify the biological and clinical significance of the identified genes. Results: We identified several candidate genes that could be of diagnostic and therapeutic value in NSCLC. EGFR, KRAS, MET, TP53, and PIK3CA were identified as the major hub genes of the most crucial cancer-related pathways in LUAD. The genes identified as central regulatory genes associated with cell-cycle control and tumour progression in LUSC were TOP2A, CCNB1, CCNA2, and BUB1B. Survival analyses showed that strong relationships exist between expression levels of these genes and overall patient survival. Additionally, drug–gene interaction analysis revealed several approved and Phase II/III drugs that could exploit these molecular abnormalities. Conclusion: This study proves that the integration of transcriptomic and pharmacogenomic data, in conjunction with the system biology approach, offers valuable insights into the molecular features of NSCLC.
Muchokota Sushma*2 Firdos Khanam1 (Fri,) studied this question.