Malignant Mechanism of Anaplastic Thyroid Carcinoma Identified by Integrated Bioinformatics Analysis

OBJECTIVE To elucidate the differential molecular pathways between anaplastic thyroid carcinoma (ATC) and differentiated thyroid cancer, and revealing the malignant mechanism of ATC. METHODS Using the GEO database and R language to analyze differentially expressed genes between ATC and papillary thyroid cancer (PTC), and common differential gene sharing between ATC and PTC compared with normal thyroid tissue, respectively. Protein-protein interactions (PPI) were constructed based on STRING database and Cytoscape software. The key network nodes and gene clusters were analyzed. KEGG, DAVID database, and ClueGO plug-in were used for gene enrichment and annotation. Finally, the expression of key nodes in different thyroid cancer cell lines was detected by RT-PCR. RESULTS Compared with normal thyroid tissue, there were 775 common differential genes in ATC and PTC. Pathways were enriched in the PI3K-Akt signaling pathway, p53 pathway, cancer pathway, cell cycle, which were classic pathways involved in the regulation of tumorigenesis. Tumor microenvironment associated pathways such as inflammatory response, extracellular matrix remodeling, immune response, and angiogenesis also changed. Further screening of differentially expressed gene between ATC and PTC showed that p53 signaling pathway, PI3K-Akt signaling pathway, ECM-receptor interaction, cell cycle, protein digestion and absorption, phagosome, complement and coagulation cascades were significantly activated in ATC. Through the construction of the PPI network, there were 3 key gene clusters, which were related to important biological processes such as cell cycle, double-strand break repair, cell chemotaxis, and protein ubiquitination. Among them, TOP2A, IL8, UBE2S were the key nodes of each gene cluster. CONCLUSION This study unveil the potential molecular mechanisms for the malignancy of ATC by bioinformatics analysis, and reveal key gene clusters and nodes in the network. It provides a theoretical basis for the malignant mechanisms and potential therapeutic targets of ATC.