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

BACKGROUND: Since anaplastic thyroid carcinoma (ATC) has rapid progression and a poor outcome, identification of the key genes and underlying mechanisms of ATC is required. METHODS: Gene expression profiles of GSE29265 and GSE33630 were available from the Gene Expression Omnibus database. The two pr...

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Autores principales: Zhang, Zhi, Zou, Zhenning, Dai, Haixia, Ye, Ruifang, Di, Xiaoqing, Li, Rujia, Ha, Yanping, Sun, Yanqin, Gan, Siyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798237/
https://www.ncbi.nlm.nih.gov/pubmed/35117787
http://dx.doi.org/10.21037/tcr-19-2829
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author Zhang, Zhi
Zou, Zhenning
Dai, Haixia
Ye, Ruifang
Di, Xiaoqing
Li, Rujia
Ha, Yanping
Sun, Yanqin
Gan, Siyuan
author_facet Zhang, Zhi
Zou, Zhenning
Dai, Haixia
Ye, Ruifang
Di, Xiaoqing
Li, Rujia
Ha, Yanping
Sun, Yanqin
Gan, Siyuan
author_sort Zhang, Zhi
collection PubMed
description BACKGROUND: Since anaplastic thyroid carcinoma (ATC) has rapid progression and a poor outcome, identification of the key genes and underlying mechanisms of ATC is required. METHODS: 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. RESULTS: Four genes (CCNB1, CCNB2, CDK1 and CHEK1) 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, CCNB1, CCNB2, CDK1 and CHEK1 were significantly positively associated with these prognosis genes. CONCLUSIONS: CCNB1, CCNB2, CDK1 and CHEK1 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.
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spelling pubmed-87982372022-02-02 Key genes involved in cell cycle arrest and DNA damage repair identified in anaplastic thyroid carcinoma using integrated bioinformatics analysis Zhang, Zhi Zou, Zhenning Dai, Haixia Ye, Ruifang Di, Xiaoqing Li, Rujia Ha, Yanping Sun, Yanqin Gan, Siyuan Transl Cancer Res Original Article BACKGROUND: Since anaplastic thyroid carcinoma (ATC) has rapid progression and a poor outcome, identification of the key genes and underlying mechanisms of ATC is required. METHODS: 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. RESULTS: Four genes (CCNB1, CCNB2, CDK1 and CHEK1) 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, CCNB1, CCNB2, CDK1 and CHEK1 were significantly positively associated with these prognosis genes. CONCLUSIONS: CCNB1, CCNB2, CDK1 and CHEK1 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. AME Publishing Company 2020-07 /pmc/articles/PMC8798237/ /pubmed/35117787 http://dx.doi.org/10.21037/tcr-19-2829 Text en 2020 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
spellingShingle Original Article
Zhang, Zhi
Zou, Zhenning
Dai, Haixia
Ye, Ruifang
Di, Xiaoqing
Li, Rujia
Ha, Yanping
Sun, Yanqin
Gan, Siyuan
Key genes involved in cell cycle arrest and DNA damage repair identified in anaplastic thyroid carcinoma using integrated bioinformatics analysis
title Key genes involved in cell cycle arrest and DNA damage repair identified in anaplastic thyroid carcinoma using integrated bioinformatics analysis
title_full Key genes involved in cell cycle arrest and DNA damage repair identified in anaplastic thyroid carcinoma using integrated bioinformatics analysis
title_fullStr Key genes involved in cell cycle arrest and DNA damage repair identified in anaplastic thyroid carcinoma using integrated bioinformatics analysis
title_full_unstemmed Key genes involved in cell cycle arrest and DNA damage repair identified in anaplastic thyroid carcinoma using integrated bioinformatics analysis
title_short Key genes involved in cell cycle arrest and DNA damage repair identified in anaplastic thyroid carcinoma using integrated bioinformatics analysis
title_sort key genes involved in cell cycle arrest and dna damage repair identified in anaplastic thyroid carcinoma using integrated bioinformatics analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798237/
https://www.ncbi.nlm.nih.gov/pubmed/35117787
http://dx.doi.org/10.21037/tcr-19-2829
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