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In this study, we took a comprehensive approach using bioinformatics to uncover potential therapeutic targets for colorectal cancer (CRC). We started by analyzing gene expression data from GEO2R to identify genes that were differentially expressed in CRC. Then, using FunRich software, we created Venn diagrams to visualize these genes. From the 191 upregulated genes we found, we focused on potential “hub genes” by looking at their network connections and strength, using the STRING database.To understand the roles of these hub genes, we performed functional analyses like Gene Ontology (GO) and pathway enrichment through the DAVID platform. This helped us pinpoint key biological processes and pathways linked to the genes we identified. We also looked at patient survival data from GEPIA, along with information on gene expression related to disease stages and metastatic progression. This helped us identify which hub genes were most relevant for CRC.In addition, we examined genetic changes and gene expression patterns in CRC patients through databases like cBioPortal and the Human Protein Atlas. This gave us more evidence supporting the involvement of these genes in the disease. Ultimately, our analysis highlighted CXCL8, FOXC1, ICOS, and MCF2 as potential hub genes with important roles in CRC. These genes may serve as useful biomarkers for both diagnosing CRC and predicting patient outcomes, and they could also help guide the development of targeted treatments to improve survival rates.