Key genes involved in cell cycle arrest and DNA damage repair identified in anaplastic thyroid carcinoma using integrated bioinformatics analysis

• Published in: Translational cancer research Vol. 9; no. 7; pp. 4188 - 4203
• Main Authors: Zhang, Zhi, Zou, Zhenning, Dai, Haixia, Ye, Ruifang, Di, Xiaoqing, Li, Rujia, Ha, Yanping, Sun, Yanqin, Gan, Siyuan
• Format: Journal Article
• Language: English
• Published: China AME Publishing Company 01.07.2020
• Subjects: Original; key genes; bioinformatics analysis; Anaplastic thyroid carcinoma (ATC)
• ISSN: 2218-676X; 2219-6803
• DOI: 10.21037/tcr-19-2829

Since anaplastic thyroid carcinoma (ATC) has rapid progression and a poor outcome, identification of the key genes and underlying mechanisms of ATC is required. Gene expression profiles of GSE29265 and GSE33630 were available from the Gene Expression Omnibus database. The two profile datasets included 19 ATC tissues, 55 normal thyroid tissues and 59 papillary thyroid cancer (PTC) tissues. Differentially expressed genes (DEGs) between ATC tissues and normal thyroid tissues as well as ATC tissues and PTC tissues were identified using the GEO2R tool. Common DEGs between the two datasets were selected via Venn software online. Then, we applied the Database for Annotation, Visualization and Integrated Discovery for Kyoto Encyclopedia of Gene and Genome pathway and gene ontology (GO) analyses. Additionally, protein-protein interactions (PPIs) of these DEGs were visualized via Cytoscape with Search Tool for the Retrieval of Interacting Genes. In the PPI networks analyzed by the Molecular Complex Detection plug-in, all 54 upregulated core genes were selected. Furthermore, Kaplan-Meier analysis was applied to analyze overall survival based on these 54 genes. Then, we used the DrugBank database to identify drug relationships for the 54 genes. Additionally, we validated the correlations between genes enriched in pathways and genes identified as prognosis biomarkers of THCA by Gene Expression Profiling Interactive Analysis. Four genes ( and ) involved cell cycle arrest and DNA repair were significantly enriched in the G2/M phase of the cell cycle pathway and before G2 phase arrest of the P53 pathway. Inhibitors of CHEK1, CDK1 and TOP2A were identified in the DrugBank database. ANLN, DEPDC1, KIF2C, CENPN, TACC3 CCNB2 and CDC6 were hypothesized to be prognostic biomarkers of ATC. Furthermore, , , and were significantly positively associated with these prognosis genes. and may be key genes involved cell cycle arrest and DNA damage repair in ATC. Further studies are required to confirm the contributions of the identified genes to ATC progression and survival.