Research Info

Background: Colorectal cancer (CRC) is a malignant tumor with a poor prognosis for advanced cases due to recurrence and metastasis. These issues are largely driven by a subset of cancer stem cells (CSCs), specifically colorectal cancer stem cells (CCSCs). CCSCs are highly tumorigenic and resistant to conventional therapies. Current treatments aim to target stem cell genes and signaling pathways like Notch, Hedgehog, and WNT to suppress CCSCs. However, these methods might also impact normal stem cells in the colon and other tissues. Methods: We utilized in silico techniques to compare normal colorectal stem cells and CCSCs. Microarray data from the GEO database were analyzed using the Transcriptome Analysis Console (TAC). STRING, Cytoscape, and Gephi tools were used for construction and analyzing protein-protein interaction (PPI) network of significant DEGs. Enrichment analysis using the Enrichr platform explored the roles of functional clusters. This approach, coupled with predicting miRNAs associated with important nodes of the PPI network, provides insights into the molecular differences between normal colorectal stem cells and CCSCs, paving the way for effective therapeutics. Results: Based on our microarray analysis, CXCL5, RPS4Y1, CD177, PRAC1, and XIST have the highest fold change. The PPI network analysis revealed IL6, CXCL8, IL1A, KIT, FN1, MMP9, AGT, and COL1A1 as the most critical nodes within the network. The analysis highlighted three functional clusters within the network. The first cluster is predicted to be involved in cytokine-cytokine receptor interaction. The second cluster is responsible for the PI3K-Akt, MAPK, and Ras signaling pathways. The third cluster is involved in extracellular matrix organization and collagen fibrils. The miRNAs analysis predicts hsa-miR-29b-3p, hsa-miR-1-3p, hsa-miR-32-5p, hsa-miR-4267, and hsa-miR-149-5p for genes with positive fold changes. Conclusion: Identifying these criteria offers potential targets for more precise