Integrated Multi-Omics and Network-Based Identification of Prognostic Cell-Cycle Hub Genes in Lung cancer

Lung cancer (LC) remains the leading cause of cancer-related mortality global, dictating the identification of novel predictive biomarkers for improved diagnosis and therapeutic targeting. In this article, transcriptomic analysis was performed using RNA-seq data retrieved from three publicly available GEO datasets (GSE81089, GSE40419 and GSE141569). Differentially expressed genes (DEGs) were identified via comparing tumor and adjacent normal tissue samples using the DESeq2 package, with batch effects corrected by ComBat-seq preceding to analysis. There were 6,849 significant DEGs originate, including 2,003 downregulated and 4,846 upregulated genes. The topGO package (weight01 algorithm, Fisher's exact test) for Gene Ontology (GO) enrichment and the fgsea program for Gene Set Enrichment Analysis (GSEA) spanning MSigDB Hallmark, KEGG, and Reactome databases were used to comportment study of the DEGs pathways and functional enrichment. Cell cycle checkpoints, E2F targets, G2M checkpoints, and MYC targets were among the signaling pathways that were significantly activated, although immune-related pathways were frequently suppressed. Using the STRING database and Cytoscape software, the top 1000 important protein–protein interactions (PPIs) were collected into a network with 920 nodes and 10,559 edges. Four important hub genes were originated via hub gene analysis employing six topological methods in the CytoHubba plug-in tool: CDK1, CCNB1, CCNA2, and TOP2A. CCNA2 was hypermethylated in tumor tissues, although CDK1, CCNB1, and TOP2A were hypomethylated, according to promoter methylation study via UALCAN database. All four hub genes consist of missense mutations, amplification, and copy number variations, which contribute to chromosomal instability and abnormal cell cycle control, according to genetic alteration study via cBioPortal. Immune cell infiltration analysis via TIMER 2.0 revealed significant correlations between hub gene expression and infiltration levels of B cells, CD4 + T cells, CD8 + T cells, neutrophils, and dendritic cells in the tumor microenvironment. Survival analysis via GEPIA2 established that elevated expression of CDK1 and CCNA2 (HR = 1.9), CCNB1 (HR = 1.8), and TOP2A (HR = 1.5) was significantly associated with poor overall survival in lung cancer patients. The identified hub genes characterize auspicious prognostic biomarkers and potential therapeutic targets for lung cancer diagnosis and treatment.