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    Lost in application: Measuring hypoxia for radiotherapy optimisation

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    Authors
    Thiruthaneeswaran, Niluja
    Bibby, Becky A
    Yang, Lingjian
    Hoskin, P J
    Bristow, Robert G
    Choudhury, Ananya
    West, Catharine M L
    Affiliation
    Division of Cancer Sciences, The University of Manchester, Manchester
    Issue Date
    2021
    
    Metadata
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    Abstract
    The history of radiotherapy is intertwined with research on hypoxia. There is level 1a evidence that giving hypoxia-targeting treatments with radiotherapy improves locoregional control and survival without compromising late side-effects. Despite coming in and out of vogue over decades, there is now an established role for hypoxia in driving molecular alterations promoting tumour progression and metastases. While tumour genomic complexity and immune profiling offer promise, there is a stronger evidence base for personalising radiotherapy based on hypoxia status. Despite this, there is only one phase III trial targeting hypoxia modification with full transcriptomic data available. There are no biomarkers in routine use for patients undergoing radiotherapy to aid management decisions, and a roadmap is needed to ensure consistency and provide a benchmark for progression to application. Gene expression signatures address past limitations of hypoxia biomarkers and could progress biologically optimised radiotherapy. Here, we review recent developments in generating hypoxia gene expression signatures and highlight progress addressing the challenges that must be overcome to pave the way for their clinical application.
    Citation
    Thiruthaneeswaran N, Bibby BAS, Yang L, Hoskin PJ, Bristow RG, Choudhury A, et al. Lost in application: Measuring hypoxia for radiotherapy optimisation. Eur J Cancer. 2021;148:260-76.
    Journal
    European Journal of Cancer
    URI
    http://hdl.handle.net/10541/623961
    DOI
    10.1016/j.ejca.2021.01.039
    PubMed ID
    33756422
    Additional Links
    https://dx.doi.org/10.1016/j.ejca.2021.01.039
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.ejca.2021.01.039
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