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Identification of Hub Genes in Anaplastic Thyroid Carcinoma: Evidence From Bioinformatics Analysis
Author(s) -
Liqi Li,
Mingjie Zhu,
Huang Hu,
Junqiang Wu,
Meng Dong
Publication year - 2020
Publication title -
technology in cancer research and treatment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.754
H-Index - 63
eISSN - 1533-0346
pISSN - 1533-0338
DOI - 10.1177/1533033820962135
Subject(s) - gene , kegg , computational biology , biology , cyclin dependent kinase 1 , anaplastic thyroid cancer , microarray , microarray analysis techniques , gene expression , bioinformatics , cell cycle , thyroid cancer , cancer , genetics , gene ontology
Anaplastic thyroid carcinoma (ATC) is a rare type of thyroid cancer that results in fatal clinical outcomes; the pathogenesis of this life-threatening disease has yet to be fully elucidated. This study aims to identify the hub genes of ATC that may play key roles in ATC development and could serve as prognostic biomarkers or therapeutic targets. Two microarray datasets (GSE33630 and GSE53072) were obtained from the Gene Expression Omnibus database; these sets included 16 ATC and 49 normal thyroid samples. Differential expression analyses were performed for each dataset, and 420 genes were screened as common differentially expressed genes using the robust rank aggregation method. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted to explore the potential bio-functions of these differentially expressed genes (DEGs). The terms and enriched pathways were primarily associated with cell cycle, cell adhesion, and cancer-related signaling pathways. Furthermore, a protein-protein interaction network of DEG expression products was constructed using Cytoscape. Based on the whole network, we identified 7 hub genes that included CDK1, TOP2A, CDC20, KIF11, CCNA2, NUSAP1, and KIF2C. The expression levels of these hub genes were validated using quantitative polymerase chain reaction analyses of clinical specimens. In conclusion, the present study identified several key genes that are involved in ATC development and provides novel insights into the understanding of the molecular mechanisms of ATC development.

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