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Using Prognosis-Related Gene Expression Signature and Connectivity Map for Personalized Drug Repositioning in Multiple Myeloma

BACKGROUND: Multiple myeloma (MM) is the second most common hematologic cancer with poor prognosis. Novel therapeutic strategies are needed to decrease the high mortality rate. The aim of this study was to identify prospective agents for MM. MATERIAL/METHODS: A microarray dataset was mined, which co...

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Autores principales: Zhu, Fang-xiao, He, Yu-chan, Zhang, Jun-yan, Wang, Hang-fei, Zhong, Chen, Wang, Xiao-tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510057/
https://www.ncbi.nlm.nih.gov/pubmed/31048671
http://dx.doi.org/10.12659/MSM.913970
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author Zhu, Fang-xiao
He, Yu-chan
Zhang, Jun-yan
Wang, Hang-fei
Zhong, Chen
Wang, Xiao-tao
author_facet Zhu, Fang-xiao
He, Yu-chan
Zhang, Jun-yan
Wang, Hang-fei
Zhong, Chen
Wang, Xiao-tao
author_sort Zhu, Fang-xiao
collection PubMed
description BACKGROUND: Multiple myeloma (MM) is the second most common hematologic cancer with poor prognosis. Novel therapeutic strategies are needed to decrease the high mortality rate. The aim of this study was to identify prospective agents for MM. MATERIAL/METHODS: A microarray dataset was mined, which contains the transcriptome profiles of 588 MM patients. Univariate Cox analysis was performed to analyze the relationships between genes and clinical outcome. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were determined. Protective and risky genes were uploaded to Connectivity Map (CMAP) database to identify the potentially unknown effects of existing drugs. An example was selected to be docked on the known molecules. RESULTS: A total of 1445 genes significantly correlated with the event free survival (EFS) of MM patients were identified and included 676 protective and 769 risky indicators. KEGG pathway analysis revealed that these prognosis-associated genes were enriched in the “cell cycle,” “DNA replication,” and “P53 signaling pathway”. The top t3 most significant potential molecules were vorinostat, trifluoperazine, and thioridazine. CDK1 (cyclin-dependent kinase-1) ranked as the core in the class of prognosis-related genes in MM based on protein-protein interaction (PPI) network analysis. With Sybyl-X 2.0, the majority of the top 10 molecules aforementioned displayed high binding forces with CDK1. Among these molecules, trichostatin A had the greatest ability in combining with CDK1. CONCLUSIONS: Genes that mainly accumulate in the cell cycle pathway play an essential role in the prognosis of MM, and these prognosis-related genes also have great value in drug development.
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spelling pubmed-65100572019-05-22 Using Prognosis-Related Gene Expression Signature and Connectivity Map for Personalized Drug Repositioning in Multiple Myeloma Zhu, Fang-xiao He, Yu-chan Zhang, Jun-yan Wang, Hang-fei Zhong, Chen Wang, Xiao-tao Med Sci Monit Lab/In Vitro Research BACKGROUND: Multiple myeloma (MM) is the second most common hematologic cancer with poor prognosis. Novel therapeutic strategies are needed to decrease the high mortality rate. The aim of this study was to identify prospective agents for MM. MATERIAL/METHODS: A microarray dataset was mined, which contains the transcriptome profiles of 588 MM patients. Univariate Cox analysis was performed to analyze the relationships between genes and clinical outcome. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were determined. Protective and risky genes were uploaded to Connectivity Map (CMAP) database to identify the potentially unknown effects of existing drugs. An example was selected to be docked on the known molecules. RESULTS: A total of 1445 genes significantly correlated with the event free survival (EFS) of MM patients were identified and included 676 protective and 769 risky indicators. KEGG pathway analysis revealed that these prognosis-associated genes were enriched in the “cell cycle,” “DNA replication,” and “P53 signaling pathway”. The top t3 most significant potential molecules were vorinostat, trifluoperazine, and thioridazine. CDK1 (cyclin-dependent kinase-1) ranked as the core in the class of prognosis-related genes in MM based on protein-protein interaction (PPI) network analysis. With Sybyl-X 2.0, the majority of the top 10 molecules aforementioned displayed high binding forces with CDK1. Among these molecules, trichostatin A had the greatest ability in combining with CDK1. CONCLUSIONS: Genes that mainly accumulate in the cell cycle pathway play an essential role in the prognosis of MM, and these prognosis-related genes also have great value in drug development. International Scientific Literature, Inc. 2019-05-02 /pmc/articles/PMC6510057/ /pubmed/31048671 http://dx.doi.org/10.12659/MSM.913970 Text en © Med Sci Monit, 2019 This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) )
spellingShingle Lab/In Vitro Research
Zhu, Fang-xiao
He, Yu-chan
Zhang, Jun-yan
Wang, Hang-fei
Zhong, Chen
Wang, Xiao-tao
Using Prognosis-Related Gene Expression Signature and Connectivity Map for Personalized Drug Repositioning in Multiple Myeloma
title Using Prognosis-Related Gene Expression Signature and Connectivity Map for Personalized Drug Repositioning in Multiple Myeloma
title_full Using Prognosis-Related Gene Expression Signature and Connectivity Map for Personalized Drug Repositioning in Multiple Myeloma
title_fullStr Using Prognosis-Related Gene Expression Signature and Connectivity Map for Personalized Drug Repositioning in Multiple Myeloma
title_full_unstemmed Using Prognosis-Related Gene Expression Signature and Connectivity Map for Personalized Drug Repositioning in Multiple Myeloma
title_short Using Prognosis-Related Gene Expression Signature and Connectivity Map for Personalized Drug Repositioning in Multiple Myeloma
title_sort using prognosis-related gene expression signature and connectivity map for personalized drug repositioning in multiple myeloma
topic Lab/In Vitro Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510057/
https://www.ncbi.nlm.nih.gov/pubmed/31048671
http://dx.doi.org/10.12659/MSM.913970
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