'Big data' approaches for novel anti-cancer drug discovery

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Benstead-Hume, Graeme, Wooller, Sarah K and Pearl, Frances M G (2017) 'Big data' approaches for novel anti-cancer drug discovery. Expert opinion in drug discovery, 12 (6). pp. 599-609. ISSN 1746-045X

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Abstract

Introduction: The development of improved cancer therapies is frequently cited as an urgent unmet medical need. Here we review how recent advances in platform technologies and the increasing availability of biological ‘big data’ are providing an unparalleled opportunity to systematically identify the key genes and pathways involved in tumorigenesis. We then discuss how these discoveries may be amenable to therapeutic interventions.

Areas covered: We discuss the current approaches that use ‘big data’ to identify cancer drivers. These approaches include genomic sequencing, pathway data, multi-platform data, identifying genetic interactions such as synthetic lethality and using cell line data. We review how big data is being used to assess the tractability of potential drug targets and how systems biology is being utilised to identify novel drug targets. We finish the review with an overview of available data repositories and tools being used at the forefront of cancer drug discovery.

Expert opinion: Targeted therapies based on the genomic events driving the tumour will eventually inform treatment protocols. However, using a tailored approach to treat all tumour patients may require developing a large repertoire of targeted drugs.

Item Type: Article
Schools and Departments: School of Life Sciences > Biochemistry
School of Life Sciences > Sussex Centre for Genome Damage and Stability
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Depositing User: Frances Pearl
Date Deposited: 08 Aug 2018 12:14
Last Modified: 02 Jul 2019 15:00
URI: http://sro.sussex.ac.uk/id/eprint/77645

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