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Tumor-preventing activity of aspirin in multiple cancers based on bioinformatic analyses

BACKGROUND: Acetylsalicylic acid was renamed aspirin in 1899, and it has been widely used for its multiple biological actions. Because of the diversity of the cellular processes and diseases that aspirin reportedly affects and benefits, uncertainty remains regarding its mechanism in different biolog...

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Autores principales: Li, Diangeng, Wang, Peng, Yu, Yi, Huang, Bing, Zhang, Xuelin, Xu, Chou, Zhao, Xian, Yin, Zhiwei, He, Zheng, Jin, Meiling, Liu, Changting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163034/
https://www.ncbi.nlm.nih.gov/pubmed/30280037
http://dx.doi.org/10.7717/peerj.5667
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author Li, Diangeng
Wang, Peng
Yu, Yi
Huang, Bing
Zhang, Xuelin
Xu, Chou
Zhao, Xian
Yin, Zhiwei
He, Zheng
Jin, Meiling
Liu, Changting
author_facet Li, Diangeng
Wang, Peng
Yu, Yi
Huang, Bing
Zhang, Xuelin
Xu, Chou
Zhao, Xian
Yin, Zhiwei
He, Zheng
Jin, Meiling
Liu, Changting
author_sort Li, Diangeng
collection PubMed
description BACKGROUND: Acetylsalicylic acid was renamed aspirin in 1899, and it has been widely used for its multiple biological actions. Because of the diversity of the cellular processes and diseases that aspirin reportedly affects and benefits, uncertainty remains regarding its mechanism in different biological systems. METHODS: The Drugbank and STITCH databases were used to find direct protein targets (DPTs) of aspirin. The Mentha database was used to analyze protein–protein interactions (PPIs) to find DPT-associated genes. DAVID was used for the GO and KEGG enrichment analyses. The cBio Cancer Genomics Portal database was used to mine genetic alterations and networks of aspirin-associated genes in cancer. RESULTS: Eighteen direct protein targets (DPT) and 961 DPT-associated genes were identified for aspirin. This enrichment analysis resulted in eight identified KEGG pathways that were associated with cancers. Analysis using the cBio portal indicated that aspirin might have effects on multiple tumor suppressors, such as TP53, PTEN, and RB1 and that TP53 might play a central role in aspirin-associated genes. DISCUSSION: The results not only suggest that aspirin might have anti-tumor actions against multiple cancers but could also provide new directions for further research on aspirin using a bioinformatics analysis approach.
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spelling pubmed-61630342018-10-02 Tumor-preventing activity of aspirin in multiple cancers based on bioinformatic analyses Li, Diangeng Wang, Peng Yu, Yi Huang, Bing Zhang, Xuelin Xu, Chou Zhao, Xian Yin, Zhiwei He, Zheng Jin, Meiling Liu, Changting PeerJ Bioinformatics BACKGROUND: Acetylsalicylic acid was renamed aspirin in 1899, and it has been widely used for its multiple biological actions. Because of the diversity of the cellular processes and diseases that aspirin reportedly affects and benefits, uncertainty remains regarding its mechanism in different biological systems. METHODS: The Drugbank and STITCH databases were used to find direct protein targets (DPTs) of aspirin. The Mentha database was used to analyze protein–protein interactions (PPIs) to find DPT-associated genes. DAVID was used for the GO and KEGG enrichment analyses. The cBio Cancer Genomics Portal database was used to mine genetic alterations and networks of aspirin-associated genes in cancer. RESULTS: Eighteen direct protein targets (DPT) and 961 DPT-associated genes were identified for aspirin. This enrichment analysis resulted in eight identified KEGG pathways that were associated with cancers. Analysis using the cBio portal indicated that aspirin might have effects on multiple tumor suppressors, such as TP53, PTEN, and RB1 and that TP53 might play a central role in aspirin-associated genes. DISCUSSION: The results not only suggest that aspirin might have anti-tumor actions against multiple cancers but could also provide new directions for further research on aspirin using a bioinformatics analysis approach. PeerJ Inc. 2018-09-26 /pmc/articles/PMC6163034/ /pubmed/30280037 http://dx.doi.org/10.7717/peerj.5667 Text en ©2018 Li et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Li, Diangeng
Wang, Peng
Yu, Yi
Huang, Bing
Zhang, Xuelin
Xu, Chou
Zhao, Xian
Yin, Zhiwei
He, Zheng
Jin, Meiling
Liu, Changting
Tumor-preventing activity of aspirin in multiple cancers based on bioinformatic analyses
title Tumor-preventing activity of aspirin in multiple cancers based on bioinformatic analyses
title_full Tumor-preventing activity of aspirin in multiple cancers based on bioinformatic analyses
title_fullStr Tumor-preventing activity of aspirin in multiple cancers based on bioinformatic analyses
title_full_unstemmed Tumor-preventing activity of aspirin in multiple cancers based on bioinformatic analyses
title_short Tumor-preventing activity of aspirin in multiple cancers based on bioinformatic analyses
title_sort tumor-preventing activity of aspirin in multiple cancers based on bioinformatic analyses
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163034/
https://www.ncbi.nlm.nih.gov/pubmed/30280037
http://dx.doi.org/10.7717/peerj.5667
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