Predicting tumour radiosensitivity to deliver precision radiotherapy
dc.contributor.author | Price, James M | |
dc.contributor.author | Prabhakaran, Asmithaa | |
dc.contributor.author | West, Catharine M L | |
dc.date.accessioned | 2023-01-16T14:12:51Z | |
dc.date.available | 2023-01-16T14:12:51Z | |
dc.date.issued | 2022 | en |
dc.identifier.citation | Price JM, Prabhakaran A, West CML. Predicting tumour radiosensitivity to deliver precision radiotherapy. Nature reviews Clinical oncology. 2022 Dec 7. PubMed PMID: 36477705. Epub 2022/12/09. eng. | en |
dc.identifier.pmid | 36477705 | en |
dc.identifier.doi | 10.1038/s41571-022-00709-y | en |
dc.identifier.uri | http://hdl.handle.net/10541/625886 | |
dc.description.abstract | Owing to advances in radiotherapy, the physical properties of radiation can be optimized to enable individualized treatment; however, optimization is rarely based on biological properties and, therefore, treatments are generally planned with the assumption that all tumours respond similarly to radiation. Radiation affects multiple cellular pathways, including DNA damage, hypoxia, proliferation, stem cell phenotype and immune response. In this Review, we summarize the effect of these pathways on tumour responses to radiotherapy and the current state of research on genomic classifiers designed to exploit these variations to inform treatment decisions. We also discuss whether advances in genomics have generated evidence that could be practice changing and whether advances in genomics are now ready to be used to guide the delivery of radiotherapy alone or in combination. | en |
dc.language.iso | en | en |
dc.relation.url | https://dx.doi.org/10.1038/s41571-022-00709-y | en |
dc.title | Predicting tumour radiosensitivity to deliver precision radiotherapy | en |
dc.type | Article | en |
dc.contributor.department | Department of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, UK | en |
dc.identifier.journal | Nature Reviews Clinical Oncology | en |
dc.description.note | en] |