Cancer is a complex and multifaceted disease that continues to pose significant challenges to the medical community worldwide. To improve early detection and personalized treatment strategies, researchers have turned to computational analysis of gene expression patterns as a powerful tool for unraveling the intricate molecular mechanisms underlying cancer development and progression. This research paper presents a comprehensive review of the state-of-the-art computational methods and approaches utilized in the analysis of gene expression data for cancer diagnosis and treatment.