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Issue 4, 2019
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Functional genomics in cancer immunotherapy: computational approaches for biomarker and drug discovery

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Abstract

Although immunotherapy has recently proven effective in some cancers, most patients with metastatic cancer do not benefit from this therapy. A lack of understanding of the mechanisms that underpin a successful immunotherapeutic response hamper the development of novel effective treatment combinations. In addition, defining a reliable predictive biomarker is a challenging feature selection problem given the complex and dynamic nature of an effective anti-tumour immune response. Functional genomics is an increasingly common approach to the field of biomarker discovery in cancer immunotherapy. A variety of sequencing technologies are available and data can be analysed on multiple platforms, making it accessible to scientists in many disciplines. This review explores computational strategies that can be leveraged to analyse large amounts of high-dimensional sequencing data to yield biological insight into the processes involved in the immunotherapeutic response and to identify candidate biomarkers and drug targets for laboratory-based validation.

Graphical abstract: Functional genomics in cancer immunotherapy: computational approaches for biomarker and drug discovery

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Publication details

The article was received on 23 Feb 2019, accepted on 03 Jun 2019 and first published on 04 Jun 2019


Article type: Review Article
DOI: 10.1039/C9ME00029A
Mol. Syst. Des. Eng., 2019,4, 689-700

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    Functional genomics in cancer immunotherapy: computational approaches for biomarker and drug discovery

    W. L. Chin, R. M. Zemek, W. J. Lesterhuis and T. Lassmann, Mol. Syst. Des. Eng., 2019, 4, 689
    DOI: 10.1039/C9ME00029A

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