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A review of radiation genomics: integrating patient radiation response with genomics for personalised and targeted radiation therapy. JOURNAL OF RADIOTHERAPY IN PRACTICE 2018. [DOI: 10.1017/s1460396918000547] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
AbstractBackgroundThe success of radiation therapy for cancer patients is dependent on the ability to deliver a total tumouricidal radiation dose capable of eradicating all cancer cells within the clinical target volume, however, the radiation dose tolerance of the surrounding healthy tissues becomes the main dose-limiting factor. The normal tissue adverse effects following radiotherapy are common and significantly impact the quality of life of patients. The likelihood of developing these adverse effects following radiotherapy cannot be predicted based only on the radiation treatment parameters. However, there is evidence to suggest that some common genetic variants are associated with radiotherapy response and the risk of developing adverse effects. Radiation genomics is a field that has evolved in recent years investigating the association between patient genomic data and the response to radiation therapy. This field aims to identify genetic markers that are linked to individual radiosensitivity with the potential to predict the risk of developing adverse effects due to radiotherapy using patient genomic information. It also aims to determine the relative radioresponse of patients using their genetic information for the potential prediction of patient radiation treatment response.Methods and materialsThis paper reports on a review of recent studies in the field of radiation genomics investigating the association between genomic data and patients response to radiation therapy, including the investigation of the role of genetic variants on an individual’s predisposition to enhanced radiotherapy radiosensitivity or radioresponse.ConclusionThe potential for early prediction of treatment response and patient outcome is critical in cancer patients to make decisions regarding continuation, escalation, discontinuation, and/or change in treatment options to maximise patient survival while minimising adverse effects and maintaining patients’ quality of life.
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Dainiak N, Feinendegen LE, Hyer RN, Locke PA, Waltar AE. Synergies resulting from a systems biology approach: integrating radiation epidemiology and radiobiology to optimize protection of the public after exposure to low doses of ionizing radiation. Int J Radiat Biol 2017; 94:2-7. [DOI: 10.1080/09553002.2018.1407461] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Nicholas Dainiak
- Radiation Emergency Assistance Center/Training Site (REAC/TS), Oak Ridge Institute for Science and Education, Oak Ridge, TN, USA
- Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, CT, USA
| | - Ludwig E. Feinendegen
- Department of Nuclear Medicine, Heinrich-Heine University, Dusseldorf, Germany
- Medical Department, Brookhaven National Laboratory, Upton, NY, USA
| | - Randall N. Hyer
- CrisisCommunication.net and Center for Risk Communication, New York, NY, USA
- Dynavax Europe GmbH, Dynavax Technologies Corporation, Dusseldorf, Germany
| | - Paul A. Locke
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Alan E. Waltar
- Pacific Northwest National Laboratory, Fast Reactor Safety and Fuels Organizations, Westinghouse Hanford Company, Richland, WA, USA
- Department of Nuclear Engineering, Texas A&M University, College Station, TX, USA
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Acute skin toxicity management in head and neck cancer patients treated with radiotherapy and chemotherapy or EGFR inhibitors: Literature review and consensus. Crit Rev Oncol Hematol 2015; 96:167-82. [DOI: 10.1016/j.critrevonc.2015.06.001] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2014] [Revised: 04/26/2015] [Accepted: 06/04/2015] [Indexed: 12/27/2022] Open
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Ortuño FM, Rojas I. Advances in bioinformatics and biomedical engineering--special issue of IWBBIO 2013. Theor Biol Med Model 2014; 11 Suppl 1:I1. [PMID: 25079561 PMCID: PMC4108894 DOI: 10.1186/1742-4682-11-s1-i1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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