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Incorporating Genetic Biomarkers into Predictive Models of Normal Tissue Toxicity.
Barnett, G C; Kerns, S L; Noble, D J; Dunning, A M; West, C M L; Burnet, N G.
Affiliation
  • Barnett GC; Oncology Centre, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK. Electronic address: gillian.barnett@addenbrookes.nhs.uk.
  • Kerns SL; Rubin Center for Cancer Survivorship, Department of Radiation Oncology, University of Rochester Medical Center, Rochester, NY, USA.
  • Noble DJ; Oncology Centre, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
  • Dunning AM; Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK.
  • West CM; Institute of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Christie Hospital, Manchester, UK.
  • Burnet NG; University of Cambridge Department of Oncology, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge, UK.
Clin Oncol (R Coll Radiol) ; 27(10): 579-87, 2015 Oct.
Article in En | MEDLINE | ID: mdl-26166774
ABSTRACT
There is considerable variation in the level of toxicity patients experience for a given dose of radiotherapy, which is associated with differences in underlying individual normal tissue radiosensitivity. A number of syndromes have a large effect on clinical radiosensitivity, but these are rare. Among non-syndromic patients, variation is less extreme, but equivalent to a ±20% variation in dose. Thus, if individual normal tissue radiosensitivity could be measured, it should be possible to optimise schedules for individual patients. Early investigations of in vitro cellular radiosensitivity supported a link with tissue response, but individual studies were equivocal. A lymphocyte apoptosis assay has potential, and is currently under prospective validation. The investigation of underlying genetic variation also has potential. Although early candidate gene studies were inconclusive, more recent genome-wide association studies are revealing definite associations between genotype and toxicity and highlighting the potential for future genetic testing. Genetic testing and individualised dose prescriptions could reduce toxicity in radiosensitive patients, and permit isotoxic dose escalation to increase local control in radioresistant individuals. The approach could improve outcomes for half the patients requiring radical radiotherapy. As a number of patient- and treatment-related factors also affect the risk of toxicity for a given dose, genetic testing data will need to be incorporated into models that combine patient, treatment and genetic data.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radiation Tolerance / Radiotherapy / Genetic Markers / Neoplasms Type of study: Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: Clin Oncol (R Coll Radiol) Journal subject: NEOPLASIAS Year: 2015 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radiation Tolerance / Radiotherapy / Genetic Markers / Neoplasms Type of study: Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: Clin Oncol (R Coll Radiol) Journal subject: NEOPLASIAS Year: 2015 Document type: Article