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A network based approach to drug repositioning identifies plausible candidates for breast cancer and prostate cancer
BACKGROUND: The high cost and the long time required to bring drugs into commerce is driving efforts to repurpose FDA approved drugs—to find new uses for which they weren’t intended, and to thereby reduce the overall cost of commercialization, and shorten the lag between drug discovery and availabil...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4967295/ https://www.ncbi.nlm.nih.gov/pubmed/27475327 http://dx.doi.org/10.1186/s12920-016-0212-7 |
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author | Chen, Hsiao-Rong Sherr, David H. Hu, Zhenjun DeLisi, Charles |
author_facet | Chen, Hsiao-Rong Sherr, David H. Hu, Zhenjun DeLisi, Charles |
author_sort | Chen, Hsiao-Rong |
collection | PubMed |
description | BACKGROUND: The high cost and the long time required to bring drugs into commerce is driving efforts to repurpose FDA approved drugs—to find new uses for which they weren’t intended, and to thereby reduce the overall cost of commercialization, and shorten the lag between drug discovery and availability. We report on the development, testing and application of a promising new approach to repositioning. METHODS: Our approach is based on mining a human functional linkage network for inversely correlated modules of drug and disease gene targets. The method takes account of multiple information sources, including gene mutation, gene expression, and functional connectivity and proximity of within module genes. RESULTS: The method was used to identify candidates for treating breast and prostate cancer. We found that (i) the recall rate for FDA approved drugs for breast (prostate) cancer is 20/20 (10/11), while the rates for drugs in clinical trials were 131/154 and 82/106; (ii) the ROC/AUC performance substantially exceeds that of comparable methods; (iii) preliminary in vitro studies indicate that 5/5 candidates have therapeutic indices superior to that of Doxorubicin in MCF7 and SUM149 cancer cell lines. We briefly discuss the biological plausibility of the candidates at a molecular level in the context of the biological processes that they mediate. CONCLUSIONS: Our method appears to offer promise for the identification of multi-targeted drug candidates that can correct aberrant cellular functions. In particular the computational performance exceeded that of other CMap-based methods, and in vitro experiments indicate that 5/5 candidates have therapeutic indices superior to that of Doxorubicin in MCF7 and SUM149 cancer cell lines. The approach has the potential to provide a more efficient drug discovery pipeline. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12920-016-0212-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4967295 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49672952016-07-31 A network based approach to drug repositioning identifies plausible candidates for breast cancer and prostate cancer Chen, Hsiao-Rong Sherr, David H. Hu, Zhenjun DeLisi, Charles BMC Med Genomics Research Article BACKGROUND: The high cost and the long time required to bring drugs into commerce is driving efforts to repurpose FDA approved drugs—to find new uses for which they weren’t intended, and to thereby reduce the overall cost of commercialization, and shorten the lag between drug discovery and availability. We report on the development, testing and application of a promising new approach to repositioning. METHODS: Our approach is based on mining a human functional linkage network for inversely correlated modules of drug and disease gene targets. The method takes account of multiple information sources, including gene mutation, gene expression, and functional connectivity and proximity of within module genes. RESULTS: The method was used to identify candidates for treating breast and prostate cancer. We found that (i) the recall rate for FDA approved drugs for breast (prostate) cancer is 20/20 (10/11), while the rates for drugs in clinical trials were 131/154 and 82/106; (ii) the ROC/AUC performance substantially exceeds that of comparable methods; (iii) preliminary in vitro studies indicate that 5/5 candidates have therapeutic indices superior to that of Doxorubicin in MCF7 and SUM149 cancer cell lines. We briefly discuss the biological plausibility of the candidates at a molecular level in the context of the biological processes that they mediate. CONCLUSIONS: Our method appears to offer promise for the identification of multi-targeted drug candidates that can correct aberrant cellular functions. In particular the computational performance exceeded that of other CMap-based methods, and in vitro experiments indicate that 5/5 candidates have therapeutic indices superior to that of Doxorubicin in MCF7 and SUM149 cancer cell lines. The approach has the potential to provide a more efficient drug discovery pipeline. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12920-016-0212-7) contains supplementary material, which is available to authorized users. BioMed Central 2016-07-30 /pmc/articles/PMC4967295/ /pubmed/27475327 http://dx.doi.org/10.1186/s12920-016-0212-7 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Chen, Hsiao-Rong Sherr, David H. Hu, Zhenjun DeLisi, Charles A network based approach to drug repositioning identifies plausible candidates for breast cancer and prostate cancer |
title | A network based approach to drug repositioning identifies plausible candidates for breast cancer and prostate cancer |
title_full | A network based approach to drug repositioning identifies plausible candidates for breast cancer and prostate cancer |
title_fullStr | A network based approach to drug repositioning identifies plausible candidates for breast cancer and prostate cancer |
title_full_unstemmed | A network based approach to drug repositioning identifies plausible candidates for breast cancer and prostate cancer |
title_short | A network based approach to drug repositioning identifies plausible candidates for breast cancer and prostate cancer |
title_sort | network based approach to drug repositioning identifies plausible candidates for breast cancer and prostate cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4967295/ https://www.ncbi.nlm.nih.gov/pubmed/27475327 http://dx.doi.org/10.1186/s12920-016-0212-7 |
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