• Login
    View Item 
    •   Home
    • The Christie Research Publications Repository
    • All Christie Publications
    • View Item
    •   Home
    • The Christie Research Publications Repository
    • All Christie Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of ChristieCommunitiesTitleAuthorsIssue DateSubmit DateSubjectsThis CollectionTitleAuthorsIssue DateSubmit DateSubjectsProfilesView

    My Account

    LoginRegister

    Local Links

    The Christie WebsiteChristie Library and Knowledge Service

    Statistics

    Display statistics

    Clinical biomarkers of tumour radiosensitivity and predicting benefit from radiotherapy: a systematic review

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    cancers-16-01942.pdf
    Size:
    720.8Kb
    Format:
    PDF
    Description:
    Found with Open Access Button
    Download
    Authors
    Bleaney, Christopher W
    Abdelaal, Hebatalla
    Reardon, Mark
    Anandadas, Carmel
    Hoskin, Peter
    Choudhury, Ananya
    Forker, Laura
    Affiliation
    Translational Radiobiology Group, Division of Cancer Sciences, The Oglesby Cancer Research Building, The University of Manchester, 555 Wilmslow Road, Manchester M20 4GJ, UK. Department of Clinical Oncology, The Christie NHS Foundation Trust, 550 Wilmslow Road, Manchester M20 4BX, UK.
    Issue Date
    2024
    
    Metadata
    Show full item record
    Abstract
    Modern advanced radiotherapy techniques have improved the precision and accuracy of radiotherapy delivery, with resulting plans being highly personalised based on individual anatomy. Adaptation for individual tumour biology remains elusive. There is an unmet need for biomarkers of intrinsic radiosensitivity that can predict tumour response to radiation to facilitate individualised decision-making, dosing and treatment planning. Over the last few decades, the use of high throughput molecular biology technologies has led to an explosion of newly discovered cancer biomarkers. Gene expression signatures are now used routinely in clinic to aid decision-making regarding adjuvant systemic therapy. They have great potential as radiotherapy biomarkers. A previous systematic review published in 2015 reported only five studies of signatures evaluated for their ability to predict radiotherapy benefits in clinical cohorts. This updated systematic review encompasses the expanded number of studies reported in the last decade. An additional 27 studies were identified. In total, 22 distinct signatures were recognised (5 pre-2015, 17 post-2015). Seventeen signatures were 'radiosensitivity' signatures and five were breast cancer prognostic signatures aiming to identify patients at an increased risk of local recurrence and therefore were more likely to benefit from adjuvant radiation. Most signatures (15/22) had not progressed beyond the discovery phase of development, with no suitable validated clinical-grade assay for application. Very few signatures (4/17 'radiosensitivity' signatures) had undergone any laboratory-based biological validation of their ability to predict tumour radiosensitivity. No signatures have been assessed prospectively in a phase III biomarker-led trial to date and none are recommended for routine use in clinical guidelines. A phase III prospective evaluation is ongoing for two breast cancer prognostic signatures. The most promising radiosensitivity signature remains the radiosensitivity index (RSI), which is used to calculate a genomic adjusted radiation dose (GARD). There is an ongoing phase II prospective biomarker-led study of RSI/GARD in triple negative breast cancer. The results of these trials are eagerly anticipated over the coming years. Future work in this area should focus on (1) robust biological validation; (2) building biobanks alongside large radiotherapy randomised controlled trials with dose variance (to demonstrate an interaction between radiosensitivity signature and dose); (3) a validation of clinical-grade cost-effective assays that are deliverable within current healthcare infrastructure; and (4) an integration with biomarkers of other determinants of radiation response.
    Citation
    Bleaney CW, Abdelaal H, Reardon M, Anandadas C, Hoskin P, Choudhury A, et al. Clinical Biomarkers of Tumour Radiosensitivity and Predicting Benefit from Radiotherapy: A Systematic Review. Cancers (Basel). 2024 May 20;16(10). PubMed PMID: 38792019. Pubmed Central PMCID: PMC11119069. Epub 2024/05/25. eng.
    Journal
    Cancers (Basel)
    URI
    http://hdl.handle.net/10541/626994
    DOI
    10.3390/cancers16101942
    PubMed ID
    38792019
    Additional Links
    https://dx.doi.org/10.3390/cancers16101942
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.3390/cancers16101942
    Scopus Count
    Collections
    All Christie Publications

    entitlement

    Related articles

    • Biomarkers of Tumour Radiosensitivity and Predicting Benefit from Radiotherapy.
    • Authors: Forker LJ, Choudhury A, Kiltie AE
    • Issue date: 2015 Oct
    • Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.
    • Authors: Crider K, Williams J, Qi YP, Gutman J, Yeung L, Mai C, Finkelstain J, Mehta S, Pons-Duran C, Menéndez C, Moraleda C, Rogers L, Daniels K, Green P
    • Issue date: 2022 Feb 1
    • Gene expression profiling for guiding adjuvant chemotherapy decisions in women with early breast cancer: an evidence-based and economic analysis.
    • Authors: Medical Advisory Secretariat
    • Issue date: 2010
    • Integrating Radiosensitivity and Immune Gene Signatures for Predicting Benefit of Radiotherapy in Breast Cancer.
    • Authors: Cui Y, Li B, Pollom EL, Horst KC, Li R
    • Issue date: 2018 Oct 1
    • Integrating Radiosensitivity Gene Signature Improves Glioma Outcome and Radiotherapy Response Prediction.
    • Authors: Wu S, Xu J, Li G, Jin X
    • Issue date: 2022 Sep 22
    DSpace software (copyright © 2002 - 2025)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.