TRANSCRIPTOMIC AND GENOMIC PROFILING OF MOLECULAR DRIVERS IN CANCER PROGRESSION

Abstract

This paper seeks to determine the major molecular drivers of cancer progression by performing thorough transcriptomic and genomic profiling and by trying to find out the genes, mutations, and signaling pathways that are being dysregulated leading to tumor development and progression. Approaches: TCGA and GEO public datasets of tumor and normal tissues were taken. RNA-seq data were subjected to transcriptomic analysis (DESeq2) to identify differentially expressed genes (DEGs), and genomic profiling (mutation, single nucleotide polymorphism (SNP) and copy number variation (CNV) screening) to RNA-seq data. Gene ontology (GO) and KEGG pathway analysis were performed to enrich the functions, whereas protein-protein interaction (PPI) network was constructed to obtain hub genes. Findings: The results indicated that the number of the DEGs was high and the oncogenes and tumor suppressor genes were up- and down-regulated respectively. The predominant changes in the genome were detected in the genes like TP53, KRAS, and EGFR, as well as in the SNP distributions and CNVs. The enrichment analysis demonstrated that the crucial pathways were PI3K-AKT, MAPK and p53 signaling and the network analysis showed hub genes such as MYC, AKT1 and CDK1 as the key players in cancer progression. Conclusion: The multi-omics integrated method offers in-depth information on the molecular processes governing cancer pathogenesis, which might help to develop the formulated biomarkers and treatment options as a basis of precise oncology interventions.