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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...

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Autores principales: Gupta, Sudheer, Chaudhary, Kumardeep, Kumar, Rahul, Gautam, Ankur, Nanda, Jagpreet Singh, Dhanda, Sandeep Kumar, Brahmachari, Samir Kumar, Raghava, Gajendra P. S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
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/).
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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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