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An Integrative Pharmacogenomic Approach Identifies Two-drug Combination Therapies for Personalized Cancer Medicine
An individual tumor harbors multiple molecular alterations that promote cell proliferation and prevent apoptosis and differentiation. Drugs that target specific molecular alterations have been introduced into personalized cancer medicine, but their effects can be modulated by the activities of other...
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/PMC4768263/ https://www.ncbi.nlm.nih.gov/pubmed/26916442 http://dx.doi.org/10.1038/srep22120 |
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author | Liu, Yin Fei, Teng Zheng, Xiaoqi Brown, Myles Zhang, Peng Liu, X. Shirley Wang, Haiyun |
author_facet | Liu, Yin Fei, Teng Zheng, Xiaoqi Brown, Myles Zhang, Peng Liu, X. Shirley Wang, Haiyun |
author_sort | Liu, Yin |
collection | PubMed |
description | An individual tumor harbors multiple molecular alterations that promote cell proliferation and prevent apoptosis and differentiation. Drugs that target specific molecular alterations have been introduced into personalized cancer medicine, but their effects can be modulated by the activities of other genes or molecules. Previous studies aiming to identify multiple molecular alterations for combination therapies are limited by available data. Given the recent large scale of available pharmacogenomic data, it is possible to systematically identify multiple biomarkers that contribute jointly to drug sensitivity, and to identify combination therapies for personalized cancer medicine. In this study, we used pharmacogenomic profiling data provided from two independent cohorts in a systematic in silico investigation of perturbed genes cooperatively associated with drug sensitivity. Our study predicted many pairs of molecular biomarkers that may benefit from the use of combination therapies. One of our predicted biomarker pairs, a mutation in the BRAF gene and upregulated expression of the PIM1 gene, was experimentally validated to benefit from a therapy combining BRAF inhibitor and PIM1 inhibitor in lung cancer. This study demonstrates how pharmacogenomic data can be used to systematically identify potentially cooperative genes and provide novel insights to combination therapies in personalized cancer medicine. |
format | Online Article Text |
id | pubmed-4768263 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-47682632016-03-02 An Integrative Pharmacogenomic Approach Identifies Two-drug Combination Therapies for Personalized Cancer Medicine Liu, Yin Fei, Teng Zheng, Xiaoqi Brown, Myles Zhang, Peng Liu, X. Shirley Wang, Haiyun Sci Rep Article An individual tumor harbors multiple molecular alterations that promote cell proliferation and prevent apoptosis and differentiation. Drugs that target specific molecular alterations have been introduced into personalized cancer medicine, but their effects can be modulated by the activities of other genes or molecules. Previous studies aiming to identify multiple molecular alterations for combination therapies are limited by available data. Given the recent large scale of available pharmacogenomic data, it is possible to systematically identify multiple biomarkers that contribute jointly to drug sensitivity, and to identify combination therapies for personalized cancer medicine. In this study, we used pharmacogenomic profiling data provided from two independent cohorts in a systematic in silico investigation of perturbed genes cooperatively associated with drug sensitivity. Our study predicted many pairs of molecular biomarkers that may benefit from the use of combination therapies. One of our predicted biomarker pairs, a mutation in the BRAF gene and upregulated expression of the PIM1 gene, was experimentally validated to benefit from a therapy combining BRAF inhibitor and PIM1 inhibitor in lung cancer. This study demonstrates how pharmacogenomic data can be used to systematically identify potentially cooperative genes and provide novel insights to combination therapies in personalized cancer medicine. Nature Publishing Group 2016-02-26 /pmc/articles/PMC4768263/ /pubmed/26916442 http://dx.doi.org/10.1038/srep22120 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 Liu, Yin Fei, Teng Zheng, Xiaoqi Brown, Myles Zhang, Peng Liu, X. Shirley Wang, Haiyun An Integrative Pharmacogenomic Approach Identifies Two-drug Combination Therapies for Personalized Cancer Medicine |
title | An Integrative Pharmacogenomic Approach Identifies Two-drug Combination Therapies for Personalized Cancer Medicine |
title_full | An Integrative Pharmacogenomic Approach Identifies Two-drug Combination Therapies for Personalized Cancer Medicine |
title_fullStr | An Integrative Pharmacogenomic Approach Identifies Two-drug Combination Therapies for Personalized Cancer Medicine |
title_full_unstemmed | An Integrative Pharmacogenomic Approach Identifies Two-drug Combination Therapies for Personalized Cancer Medicine |
title_short | An Integrative Pharmacogenomic Approach Identifies Two-drug Combination Therapies for Personalized Cancer Medicine |
title_sort | integrative pharmacogenomic approach identifies two-drug combination therapies for personalized cancer medicine |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4768263/ https://www.ncbi.nlm.nih.gov/pubmed/26916442 http://dx.doi.org/10.1038/srep22120 |
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