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Pathway Interactions Based on Drug-Induced Datasets
In this study, we identified enrichment pathway connections from MCF7 breast cancer epithelial cells that were treated with 87 drugs. We extracted drug-treated samples, where the sample size was greater than or equal to 5. The drugs included 17-allylamino-geldanamycin, LY294002, trichostatin A, valp...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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SAGE Publications
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6535899/ https://www.ncbi.nlm.nih.gov/pubmed/31205412 http://dx.doi.org/10.1177/1176935119851518 |
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author | Kim, Shinuk |
author_facet | Kim, Shinuk |
author_sort | Kim, Shinuk |
collection | PubMed |
description | In this study, we identified enrichment pathway connections from MCF7 breast cancer epithelial cells that were treated with 87 drugs. We extracted drug-treated samples, where the sample size was greater than or equal to 5. The drugs included 17-allylamino-geldanamycin, LY294002, trichostatin A, valproic acid, sirolimus, and wortmannin, which had sample sizes of 11, 8, 7, 7, 7, and 5, respectively. We found meaningful pathways using gene set enrichment analysis and identified intradrug and interdrug pathway interactions, which implied the influence of drug combination. Among the top 20 enrichment pathways that were wortmannin induced, there were a total of 37 intradrug pathway interactions via common genes. Thirty-seven pathway interactions were induced by valproic acid, 11 induced by trichostatin A, 20 induced by LY294002, and 59 induced by sirolimus, all via common genes. The number of interdrug-induced pathway interactions ranged from one pair of pathways to 23. The pair of ERBB_SIGNALING and INSULIN_SIGNALING pathways showed the highest score from a pair of 2 individual drugs. The highest number of pathway interactions was observed between the drugs 17-allylamino-geldanamycin and LY294002. |
format | Online Article Text |
id | pubmed-6535899 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-65358992019-06-14 Pathway Interactions Based on Drug-Induced Datasets Kim, Shinuk Cancer Inform Original Research In this study, we identified enrichment pathway connections from MCF7 breast cancer epithelial cells that were treated with 87 drugs. We extracted drug-treated samples, where the sample size was greater than or equal to 5. The drugs included 17-allylamino-geldanamycin, LY294002, trichostatin A, valproic acid, sirolimus, and wortmannin, which had sample sizes of 11, 8, 7, 7, 7, and 5, respectively. We found meaningful pathways using gene set enrichment analysis and identified intradrug and interdrug pathway interactions, which implied the influence of drug combination. Among the top 20 enrichment pathways that were wortmannin induced, there were a total of 37 intradrug pathway interactions via common genes. Thirty-seven pathway interactions were induced by valproic acid, 11 induced by trichostatin A, 20 induced by LY294002, and 59 induced by sirolimus, all via common genes. The number of interdrug-induced pathway interactions ranged from one pair of pathways to 23. The pair of ERBB_SIGNALING and INSULIN_SIGNALING pathways showed the highest score from a pair of 2 individual drugs. The highest number of pathway interactions was observed between the drugs 17-allylamino-geldanamycin and LY294002. SAGE Publications 2019-05-23 /pmc/articles/PMC6535899/ /pubmed/31205412 http://dx.doi.org/10.1177/1176935119851518 Text en © The Author(s) 2019 http://www.creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Kim, Shinuk Pathway Interactions Based on Drug-Induced Datasets |
title | Pathway Interactions Based on Drug-Induced Datasets |
title_full | Pathway Interactions Based on Drug-Induced Datasets |
title_fullStr | Pathway Interactions Based on Drug-Induced Datasets |
title_full_unstemmed | Pathway Interactions Based on Drug-Induced Datasets |
title_short | Pathway Interactions Based on Drug-Induced Datasets |
title_sort | pathway interactions based on drug-induced datasets |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6535899/ https://www.ncbi.nlm.nih.gov/pubmed/31205412 http://dx.doi.org/10.1177/1176935119851518 |
work_keys_str_mv | AT kimshinuk pathwayinteractionsbasedondruginduceddatasets |