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Bioinformatics Analysis and Validation Identify CDK1 and MAD2L1 as Prognostic Markers of Rhabdomyosarcoma

PURPOSE: The goal of the current study was to identify potential prognostic biomarkers of rhabdomyosarcoma (RMS). MATERIALS AND METHODS: We screened chip sequencing datasets of RMS through the gene expression omnibus (GEO) database. A total of 74 RMS patient tissues and 39 normal muscle cell tissues...

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Autores principales: Lu, Suying, Sun, Chengtao, Chen, Huimou, Zhang, Chao, Li, Wei, Wu, Liuhong, Zhu, Jia, Sun, Feifei, Huang, Junting, Wang, Juan, Zhen, Zijun, Cai, Ruiqing, Sun, Xiaofei, Zhang, Yizhuo, Zhang, Xing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7705535/
https://www.ncbi.nlm.nih.gov/pubmed/33273853
http://dx.doi.org/10.2147/CMAR.S265779
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author Lu, Suying
Sun, Chengtao
Chen, Huimou
Zhang, Chao
Li, Wei
Wu, Liuhong
Zhu, Jia
Sun, Feifei
Huang, Junting
Wang, Juan
Zhen, Zijun
Cai, Ruiqing
Sun, Xiaofei
Zhang, Yizhuo
Zhang, Xing
author_facet Lu, Suying
Sun, Chengtao
Chen, Huimou
Zhang, Chao
Li, Wei
Wu, Liuhong
Zhu, Jia
Sun, Feifei
Huang, Junting
Wang, Juan
Zhen, Zijun
Cai, Ruiqing
Sun, Xiaofei
Zhang, Yizhuo
Zhang, Xing
author_sort Lu, Suying
collection PubMed
description PURPOSE: The goal of the current study was to identify potential prognostic biomarkers of rhabdomyosarcoma (RMS). MATERIALS AND METHODS: We screened chip sequencing datasets of RMS through the gene expression omnibus (GEO) database. A total of 74 RMS patient tissues and 39 normal muscle cell tissues were analyzed. Limma R software was used to identify the differentially expressed genes (DEGs) between RMS tissues and normal controls. The GO plot R package was used to visualize the results of the GO analysis. We screened for pathaffy package enrichment of DEGs by the Kyoto Encyclopedia of Genes and Genomes (KEGG). The cutoff criterion was a P-value <0.05. Immunohistochemistry (IHC) was applied to validate the expression of CDK1 (cyclin-dependent kinases 1) and MAD2L1 (Mitotic Arrest Deficient 2 Like 1) in RMS. RESULTS: We obtained a total of 498 up- and 480 down-regulated DEGs. The hub genes are mainly involved in the cell cycle and P53 singling pathway. CDK1 expression was associated with tumor size and COG-STS (Children’s Oncology Group-soft tissue sarcoma) staging of RMS. For the low CDK1 expression group and high CDK1 expression group, the 5-year overall survival (OS) rate was 83.0% vs 63.5% (P = 0.004), and the 5-year event-free survival (EFS) rate was 47.5% vs 27.5% (P = 0.049) respectively. When compared low MAD2L1 expression group with high MAD2L1 expression group, the 5-year OS rate was 80.0% vs 43.2% (P = 0.001), and the 5-year EFS rate was 45.1% vs 21.8% (P = 0.038), respectively. If patients were divided into three groups: low CDK1 and low MAD2L1 expression group, high CDK1 or high MAD2L1 expression group, and high CDK1 and high MAD2L1 expression group, the 5-year OS rate was 87.1%, 58.6%, 39.6% (P = 0.001), while the 5-year EFS rate of RMS patients was 54.2%, 23.2%, 21.7% (P = 0.028), respectively. CONCLUSION: This study has identified that CDK1 and MAD2L1 were adverse prognostic factors of RMS.
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spelling pubmed-77055352020-12-02 Bioinformatics Analysis and Validation Identify CDK1 and MAD2L1 as Prognostic Markers of Rhabdomyosarcoma Lu, Suying Sun, Chengtao Chen, Huimou Zhang, Chao Li, Wei Wu, Liuhong Zhu, Jia Sun, Feifei Huang, Junting Wang, Juan Zhen, Zijun Cai, Ruiqing Sun, Xiaofei Zhang, Yizhuo Zhang, Xing Cancer Manag Res Original Research PURPOSE: The goal of the current study was to identify potential prognostic biomarkers of rhabdomyosarcoma (RMS). MATERIALS AND METHODS: We screened chip sequencing datasets of RMS through the gene expression omnibus (GEO) database. A total of 74 RMS patient tissues and 39 normal muscle cell tissues were analyzed. Limma R software was used to identify the differentially expressed genes (DEGs) between RMS tissues and normal controls. The GO plot R package was used to visualize the results of the GO analysis. We screened for pathaffy package enrichment of DEGs by the Kyoto Encyclopedia of Genes and Genomes (KEGG). The cutoff criterion was a P-value <0.05. Immunohistochemistry (IHC) was applied to validate the expression of CDK1 (cyclin-dependent kinases 1) and MAD2L1 (Mitotic Arrest Deficient 2 Like 1) in RMS. RESULTS: We obtained a total of 498 up- and 480 down-regulated DEGs. The hub genes are mainly involved in the cell cycle and P53 singling pathway. CDK1 expression was associated with tumor size and COG-STS (Children’s Oncology Group-soft tissue sarcoma) staging of RMS. For the low CDK1 expression group and high CDK1 expression group, the 5-year overall survival (OS) rate was 83.0% vs 63.5% (P = 0.004), and the 5-year event-free survival (EFS) rate was 47.5% vs 27.5% (P = 0.049) respectively. When compared low MAD2L1 expression group with high MAD2L1 expression group, the 5-year OS rate was 80.0% vs 43.2% (P = 0.001), and the 5-year EFS rate was 45.1% vs 21.8% (P = 0.038), respectively. If patients were divided into three groups: low CDK1 and low MAD2L1 expression group, high CDK1 or high MAD2L1 expression group, and high CDK1 and high MAD2L1 expression group, the 5-year OS rate was 87.1%, 58.6%, 39.6% (P = 0.001), while the 5-year EFS rate of RMS patients was 54.2%, 23.2%, 21.7% (P = 0.028), respectively. CONCLUSION: This study has identified that CDK1 and MAD2L1 were adverse prognostic factors of RMS. Dove 2020-11-26 /pmc/articles/PMC7705535/ /pubmed/33273853 http://dx.doi.org/10.2147/CMAR.S265779 Text en © 2020 Lu et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Lu, Suying
Sun, Chengtao
Chen, Huimou
Zhang, Chao
Li, Wei
Wu, Liuhong
Zhu, Jia
Sun, Feifei
Huang, Junting
Wang, Juan
Zhen, Zijun
Cai, Ruiqing
Sun, Xiaofei
Zhang, Yizhuo
Zhang, Xing
Bioinformatics Analysis and Validation Identify CDK1 and MAD2L1 as Prognostic Markers of Rhabdomyosarcoma
title Bioinformatics Analysis and Validation Identify CDK1 and MAD2L1 as Prognostic Markers of Rhabdomyosarcoma
title_full Bioinformatics Analysis and Validation Identify CDK1 and MAD2L1 as Prognostic Markers of Rhabdomyosarcoma
title_fullStr Bioinformatics Analysis and Validation Identify CDK1 and MAD2L1 as Prognostic Markers of Rhabdomyosarcoma
title_full_unstemmed Bioinformatics Analysis and Validation Identify CDK1 and MAD2L1 as Prognostic Markers of Rhabdomyosarcoma
title_short Bioinformatics Analysis and Validation Identify CDK1 and MAD2L1 as Prognostic Markers of Rhabdomyosarcoma
title_sort bioinformatics analysis and validation identify cdk1 and mad2l1 as prognostic markers of rhabdomyosarcoma
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7705535/
https://www.ncbi.nlm.nih.gov/pubmed/33273853
http://dx.doi.org/10.2147/CMAR.S265779
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