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A computational drug repositioning method applied to rare diseases: Adrenocortical carcinoma
Rare or orphan diseases affect only small populations, thereby limiting the economic incentive for the drug development process, often resulting in a lack of progress towards treatment. Drug repositioning is a promising approach in these cases, due to its low cost. In this approach, one attempts to...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7264316/ https://www.ncbi.nlm.nih.gov/pubmed/32483162 http://dx.doi.org/10.1038/s41598-020-65658-x |
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author | Lotfi Shahreza, Maryam Ghadiri, Nasser Green, James R. |
author_facet | Lotfi Shahreza, Maryam Ghadiri, Nasser Green, James R. |
author_sort | Lotfi Shahreza, Maryam |
collection | PubMed |
description | Rare or orphan diseases affect only small populations, thereby limiting the economic incentive for the drug development process, often resulting in a lack of progress towards treatment. Drug repositioning is a promising approach in these cases, due to its low cost. In this approach, one attempts to identify new purposes for existing drugs that have already been developed and approved for use. By applying the process of drug repositioning to identify novel treatments for rare diseases, we can overcome the lack of economic incentives and make concrete progress towards new therapies. Adrenocortical Carcinoma (ACC) is a rare disease with no practical and definitive therapeutic approach. We apply Heter-LP, a new method of drug repositioning, to suggest novel therapeutic avenues for ACC. Our analysis identifies innovative putative drug-disease, drug-target, and disease-target relationships for ACC, which include Cosyntropin (drug) and DHCR7, IGF1R, MC1R, MAP3K3, TOP2A (protein targets). When results are analyzed using all available information, a number of novel predicted associations related to ACC appear to be valid according to current knowledge. We expect the predicted relations will be useful for drug repositioning in ACC since the resulting ranked lists of drugs and protein targets can be used to expedite the necessary clinical processes. |
format | Online Article Text |
id | pubmed-7264316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-72643162020-06-05 A computational drug repositioning method applied to rare diseases: Adrenocortical carcinoma Lotfi Shahreza, Maryam Ghadiri, Nasser Green, James R. Sci Rep Article Rare or orphan diseases affect only small populations, thereby limiting the economic incentive for the drug development process, often resulting in a lack of progress towards treatment. Drug repositioning is a promising approach in these cases, due to its low cost. In this approach, one attempts to identify new purposes for existing drugs that have already been developed and approved for use. By applying the process of drug repositioning to identify novel treatments for rare diseases, we can overcome the lack of economic incentives and make concrete progress towards new therapies. Adrenocortical Carcinoma (ACC) is a rare disease with no practical and definitive therapeutic approach. We apply Heter-LP, a new method of drug repositioning, to suggest novel therapeutic avenues for ACC. Our analysis identifies innovative putative drug-disease, drug-target, and disease-target relationships for ACC, which include Cosyntropin (drug) and DHCR7, IGF1R, MC1R, MAP3K3, TOP2A (protein targets). When results are analyzed using all available information, a number of novel predicted associations related to ACC appear to be valid according to current knowledge. We expect the predicted relations will be useful for drug repositioning in ACC since the resulting ranked lists of drugs and protein targets can be used to expedite the necessary clinical processes. Nature Publishing Group UK 2020-06-01 /pmc/articles/PMC7264316/ /pubmed/32483162 http://dx.doi.org/10.1038/s41598-020-65658-x Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Lotfi Shahreza, Maryam Ghadiri, Nasser Green, James R. A computational drug repositioning method applied to rare diseases: Adrenocortical carcinoma |
title | A computational drug repositioning method applied to rare diseases: Adrenocortical carcinoma |
title_full | A computational drug repositioning method applied to rare diseases: Adrenocortical carcinoma |
title_fullStr | A computational drug repositioning method applied to rare diseases: Adrenocortical carcinoma |
title_full_unstemmed | A computational drug repositioning method applied to rare diseases: Adrenocortical carcinoma |
title_short | A computational drug repositioning method applied to rare diseases: Adrenocortical carcinoma |
title_sort | computational drug repositioning method applied to rare diseases: adrenocortical carcinoma |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7264316/ https://www.ncbi.nlm.nih.gov/pubmed/32483162 http://dx.doi.org/10.1038/s41598-020-65658-x |
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