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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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2018
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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. |
format | Online Article Text |
id | pubmed-6163034 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
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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