Identification of key candidate genes and pathways in anaplastic thyroid cancer by bioinformatics analysis

被引：11
作者：
Ding, Yong-Gang [1 ]
Ren, Yu-Lin [2 ]
Xu, Yang-Shan [3 ]
Wei, Chang-Sheng [4 ]
Zhang, Yong-Bin [5 ]
Zhang, Shou-Kai [6 ]
Guo, Chang-An [1 ]
机构：
[1] Lanzhou Univ, Emergency Dept, Hosp 2, 82 Chuiying Gate, Lanzhou 730030, Gansu, Peoples R China
[2] Northwest Minzu Univ, Peoples Hosp Gansu Prov 2, Dept Urol Surg, Affiliated Hosp, Lanzhou 730030, Gansu, Peoples R China
[3] Liujiaxia Hosp Fourth Engn Bur China Water Resour, Dept Surg, Linxia 731801, Gansu, Peoples R China
[4] Gansu Prov Canc Hosp, Dept Thyroid Mammary Gland, Lanzhou 730030, Gansu, Peoples R China
[5] Gansu Prov Hosp, Dept Gen Surg, Lanzhou 730030, Gansu, Peoples R China
[6] Gansu Prov Hosp, Dept Otolaryngol Head & Neck Surg, Lanzhou 730030, Gansu, Peoples R China
来源：
AMERICAN JOURNAL OF OTOLARYNGOLOGY | 2020年 / 41卷 / 03期
关键词：
Anaplastic thyroid cancer; Bioinformatics analysis; Differentially expressed genes; Quantitative real-time PCR; SPINDLE ASSEMBLY CHECKPOINT; CELL LUNG-CANCER; HEPATOCELLULAR-CARCINOMA; OVEREXPRESSION; PHOSPHORYLATION; GEMCITABINE; APOPTOSIS; GROWTH; BUBR1; CDC20;
D O I：
10.1016/j.amjoto.2020.102434
中图分类号：
R76 [耳鼻咽喉科学];
学科分类号：
100213 ;
摘要：
Background: Anaplastic thyroid carcinoma (ATC) is a refractory and poor prognosis tumor Present study aimed to investigate the underlying biological functions and pathways involved in the development of ATC and to identify potential hub genes and candidate biomarkers of ATC. Materials and methods: Bioinformatics analyses were performed to identify the differentially expressed genes (DEGs) between ATC tissue samples and adjacent normal tissue samples. Protein-protein interaction (PPI) networks of the DEGs were constructed using Search Tool for the Retrieval of Interacting Genes online tool and Cytoscape software and divided into sub-networks using the Molecular Complex Detection (MCODE) plug-in. DEGs in each module was analyzed by enrichment analysis of the KEGG Orthology Based Annotation System (KOBAS) web software version 3.0. Eventually, the hub genes from bioinformatics analysis were verified by qRT-PCR assay in different ATC cell lines. Results: Thirty hub genes were selected and three modules were built by the Cytoscape software from the PPI network. Seven genes (CDK1, CCNB2, BUB1B, CDC20, RRM2, CHEK1 and CDC45) were screened from thirty hub genes. Enrichment analysis showed that these hub genes were primarily accumulated in 'cell cycle', 'p53 signaling pathway', 'viral carcinogenesis', 'pyrimidine metabolism' and 'ubiquitin mediated proteolysis'. The results of qRT-PCR indicated that seven hub genes were unregulated in three ATC cell lines compared with normal thyroid gland cell. Conclusions: These findings suggest that CDK1, CCNB2, BUB1B, CDC20, RRM2, CHEK1 and CDC45 may serve as novel diagnosis biomarkers and potential therapeutic target for ATC.
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页数：11
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