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AlloDriver: a method for the identification and analysis of cancer driver targets

Identifying the variants that alter protein function is a promising strategy for deciphering the biological consequences of somatic mutations during tumorigenesis, which could provide novel targets for the development of cancer therapies. Here, based on our previously developed method, we present a...

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Autores principales: Song, Kun, Li, Qian, Gao, Wei, Lu, Shaoyong, Shen, Qiancheng, Liu, Xinyi, Wu, Yongyan, Wang, Binquan, Lin, Houwen, Chen, Guoqiang, Zhang, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602569/
https://www.ncbi.nlm.nih.gov/pubmed/31069394
http://dx.doi.org/10.1093/nar/gkz350
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author Song, Kun
Li, Qian
Gao, Wei
Lu, Shaoyong
Shen, Qiancheng
Liu, Xinyi
Wu, Yongyan
Wang, Binquan
Lin, Houwen
Chen, Guoqiang
Zhang, Jian
author_facet Song, Kun
Li, Qian
Gao, Wei
Lu, Shaoyong
Shen, Qiancheng
Liu, Xinyi
Wu, Yongyan
Wang, Binquan
Lin, Houwen
Chen, Guoqiang
Zhang, Jian
author_sort Song, Kun
collection PubMed
description Identifying the variants that alter protein function is a promising strategy for deciphering the biological consequences of somatic mutations during tumorigenesis, which could provide novel targets for the development of cancer therapies. Here, based on our previously developed method, we present a strategy called AlloDriver that identifies cancer driver genes/proteins as possible targets from mutations. AlloDriver utilizes structural and dynamic features to prioritize potentially functional genes/proteins in individual cancers via mapping mutations generated from clinical cancer samples to allosteric/orthosteric sites derived from three-dimensional protein structures. This strategy exhibits desirable performance in the reemergence of known cancer driver mutations and genes/proteins from clinical samples. Significantly, the practicability of AlloDriver to discover novel cancer driver proteins in head and neck squamous cell carcinoma (HNSC) was tested in a real case of human protein tyrosine phosphatase, receptor type K (PTPRK) through a L1143F driver mutation located at the allosteric site of PTPRK, which was experimentally validated by cell proliferation assay. AlloDriver is expected to help to uncover innovative molecular mechanisms of tumorigenesis by perturbing proteins and to discover novel targets based on cancer driver mutations. The AlloDriver is freely available to all users at http://mdl.shsmu.edu.cn/ALD.
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spelling pubmed-66025692019-07-05 AlloDriver: a method for the identification and analysis of cancer driver targets Song, Kun Li, Qian Gao, Wei Lu, Shaoyong Shen, Qiancheng Liu, Xinyi Wu, Yongyan Wang, Binquan Lin, Houwen Chen, Guoqiang Zhang, Jian Nucleic Acids Res Web Server Issue Identifying the variants that alter protein function is a promising strategy for deciphering the biological consequences of somatic mutations during tumorigenesis, which could provide novel targets for the development of cancer therapies. Here, based on our previously developed method, we present a strategy called AlloDriver that identifies cancer driver genes/proteins as possible targets from mutations. AlloDriver utilizes structural and dynamic features to prioritize potentially functional genes/proteins in individual cancers via mapping mutations generated from clinical cancer samples to allosteric/orthosteric sites derived from three-dimensional protein structures. This strategy exhibits desirable performance in the reemergence of known cancer driver mutations and genes/proteins from clinical samples. Significantly, the practicability of AlloDriver to discover novel cancer driver proteins in head and neck squamous cell carcinoma (HNSC) was tested in a real case of human protein tyrosine phosphatase, receptor type K (PTPRK) through a L1143F driver mutation located at the allosteric site of PTPRK, which was experimentally validated by cell proliferation assay. AlloDriver is expected to help to uncover innovative molecular mechanisms of tumorigenesis by perturbing proteins and to discover novel targets based on cancer driver mutations. The AlloDriver is freely available to all users at http://mdl.shsmu.edu.cn/ALD. Oxford University Press 2019-07-02 2019-05-09 /pmc/articles/PMC6602569/ /pubmed/31069394 http://dx.doi.org/10.1093/nar/gkz350 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Web Server Issue
Song, Kun
Li, Qian
Gao, Wei
Lu, Shaoyong
Shen, Qiancheng
Liu, Xinyi
Wu, Yongyan
Wang, Binquan
Lin, Houwen
Chen, Guoqiang
Zhang, Jian
AlloDriver: a method for the identification and analysis of cancer driver targets
title AlloDriver: a method for the identification and analysis of cancer driver targets
title_full AlloDriver: a method for the identification and analysis of cancer driver targets
title_fullStr AlloDriver: a method for the identification and analysis of cancer driver targets
title_full_unstemmed AlloDriver: a method for the identification and analysis of cancer driver targets
title_short AlloDriver: a method for the identification and analysis of cancer driver targets
title_sort allodriver: a method for the identification and analysis of cancer driver targets
topic Web Server Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602569/
https://www.ncbi.nlm.nih.gov/pubmed/31069394
http://dx.doi.org/10.1093/nar/gkz350
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