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Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine
In this study, we investigated drug profile of 24 anticancer drugs tested against a large number of cell lines in order to understand the relation between drug resistance and altered genomic features of a cancer cell line. We detected frequent mutations, high expression and high copy number variatio...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4814902/ https://www.ncbi.nlm.nih.gov/pubmed/27030518 http://dx.doi.org/10.1038/srep23857 |
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author | Gupta, Sudheer Chaudhary, Kumardeep Kumar, Rahul Gautam, Ankur Nanda, Jagpreet Singh Dhanda, Sandeep Kumar Brahmachari, Samir Kumar Raghava, Gajendra P. S. |
author_facet | Gupta, Sudheer Chaudhary, Kumardeep Kumar, Rahul Gautam, Ankur Nanda, Jagpreet Singh Dhanda, Sandeep Kumar Brahmachari, Samir Kumar Raghava, Gajendra P. S. |
author_sort | Gupta, Sudheer |
collection | PubMed |
description | In this study, we investigated drug profile of 24 anticancer drugs tested against a large number of cell lines in order to understand the relation between drug resistance and altered genomic features of a cancer cell line. We detected frequent mutations, high expression and high copy number variations of certain genes in both drug resistant cell lines and sensitive cell lines. It was observed that a few drugs, like Panobinostat, are effective against almost all types of cell lines, whereas certain drugs are effective against only a limited type of cell lines. Tissue-specific preference of drugs was also seen where a drug is more effective against cell lines belonging to a specific tissue. Genomic features based models have been developed for each anticancer drug and achieved average correlation between predicted and actual growth inhibition of cell lines in the range of 0.43 to 0.78. We hope, our study will throw light in the field of personalized medicine, particularly in designing patient-specific anticancer drugs. In order to serve the scientific community, a webserver, CancerDP, has been developed for predicting priority/potency of an anticancer drug against a cancer cell line using its genomic features (http://crdd.osdd.net/raghava/cancerdp/). |
format | Online Article Text |
id | pubmed-4814902 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-48149022016-04-04 Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine Gupta, Sudheer Chaudhary, Kumardeep Kumar, Rahul Gautam, Ankur Nanda, Jagpreet Singh Dhanda, Sandeep Kumar Brahmachari, Samir Kumar Raghava, Gajendra P. S. Sci Rep Article In this study, we investigated drug profile of 24 anticancer drugs tested against a large number of cell lines in order to understand the relation between drug resistance and altered genomic features of a cancer cell line. We detected frequent mutations, high expression and high copy number variations of certain genes in both drug resistant cell lines and sensitive cell lines. It was observed that a few drugs, like Panobinostat, are effective against almost all types of cell lines, whereas certain drugs are effective against only a limited type of cell lines. Tissue-specific preference of drugs was also seen where a drug is more effective against cell lines belonging to a specific tissue. Genomic features based models have been developed for each anticancer drug and achieved average correlation between predicted and actual growth inhibition of cell lines in the range of 0.43 to 0.78. We hope, our study will throw light in the field of personalized medicine, particularly in designing patient-specific anticancer drugs. In order to serve the scientific community, a webserver, CancerDP, has been developed for predicting priority/potency of an anticancer drug against a cancer cell line using its genomic features (http://crdd.osdd.net/raghava/cancerdp/). Nature Publishing Group 2016-03-31 /pmc/articles/PMC4814902/ /pubmed/27030518 http://dx.doi.org/10.1038/srep23857 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Gupta, Sudheer Chaudhary, Kumardeep Kumar, Rahul Gautam, Ankur Nanda, Jagpreet Singh Dhanda, Sandeep Kumar Brahmachari, Samir Kumar Raghava, Gajendra P. S. Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine |
title | Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine |
title_full | Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine |
title_fullStr | Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine |
title_full_unstemmed | Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine |
title_short | Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine |
title_sort | prioritization of anticancer drugs against a cancer using genomic features of cancer cells: a step towards personalized medicine |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4814902/ https://www.ncbi.nlm.nih.gov/pubmed/27030518 http://dx.doi.org/10.1038/srep23857 |
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