Cargando…
Harnessing genome-wide association studies to minimize adverse radiation-induced side effects
Radiotherapy is used as definitive treatment in approximately two-thirds of all cancers. However, like any treatment, radiation has significant acute and long-term side effects including secondary malignancies. Even when similar radiation parameters are used, 5%–10% of patients will experience adver...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Society for Radiation Oncology
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785837/ https://www.ncbi.nlm.nih.gov/pubmed/33233031 http://dx.doi.org/10.3857/roj.2020.00556 |
_version_ | 1783632507352121344 |
---|---|
author | Benitez, Cecil M. Knox, Susan J. |
author_facet | Benitez, Cecil M. Knox, Susan J. |
author_sort | Benitez, Cecil M. |
collection | PubMed |
description | Radiotherapy is used as definitive treatment in approximately two-thirds of all cancers. However, like any treatment, radiation has significant acute and long-term side effects including secondary malignancies. Even when similar radiation parameters are used, 5%–10% of patients will experience adverse radiation side effects. Genomic susceptibility is thought to be responsible for approximately 40% of the clinical variability observed. In the era of precision medicine, the link between genetic susceptibility and radiation-induced side effects is further strengthening. Genome-wide association studies (GWAS) have begun to identify single-nucleotide polymorphisms (SNPs) attributed to overall and tissue-specific toxicity following radiation for treatment of breast cancer, prostate cancer, and other cancers. Here, we review the use of GWAS in identifying polymorphisms that are predictive of acute and long-term radiation-induced side effects with a focus on chest, pelvic, and head-and-neck irradiation. Integration of GWAS with “omic” data, patient characteristics, and clinical correlates into predictive models could decrease radiation-induced side effects while increasing therapeutic efficacy. |
format | Online Article Text |
id | pubmed-7785837 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Korean Society for Radiation Oncology |
record_format | MEDLINE/PubMed |
spelling | pubmed-77858372021-01-13 Harnessing genome-wide association studies to minimize adverse radiation-induced side effects Benitez, Cecil M. Knox, Susan J. Radiat Oncol J Review Article Radiotherapy is used as definitive treatment in approximately two-thirds of all cancers. However, like any treatment, radiation has significant acute and long-term side effects including secondary malignancies. Even when similar radiation parameters are used, 5%–10% of patients will experience adverse radiation side effects. Genomic susceptibility is thought to be responsible for approximately 40% of the clinical variability observed. In the era of precision medicine, the link between genetic susceptibility and radiation-induced side effects is further strengthening. Genome-wide association studies (GWAS) have begun to identify single-nucleotide polymorphisms (SNPs) attributed to overall and tissue-specific toxicity following radiation for treatment of breast cancer, prostate cancer, and other cancers. Here, we review the use of GWAS in identifying polymorphisms that are predictive of acute and long-term radiation-induced side effects with a focus on chest, pelvic, and head-and-neck irradiation. Integration of GWAS with “omic” data, patient characteristics, and clinical correlates into predictive models could decrease radiation-induced side effects while increasing therapeutic efficacy. The Korean Society for Radiation Oncology 2020-12 2020-11-25 /pmc/articles/PMC7785837/ /pubmed/33233031 http://dx.doi.org/10.3857/roj.2020.00556 Text en Copyright © 2020 The Korean Society for Radiation Oncology https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Benitez, Cecil M. Knox, Susan J. Harnessing genome-wide association studies to minimize adverse radiation-induced side effects |
title | Harnessing genome-wide association studies to minimize adverse radiation-induced side effects |
title_full | Harnessing genome-wide association studies to minimize adverse radiation-induced side effects |
title_fullStr | Harnessing genome-wide association studies to minimize adverse radiation-induced side effects |
title_full_unstemmed | Harnessing genome-wide association studies to minimize adverse radiation-induced side effects |
title_short | Harnessing genome-wide association studies to minimize adverse radiation-induced side effects |
title_sort | harnessing genome-wide association studies to minimize adverse radiation-induced side effects |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785837/ https://www.ncbi.nlm.nih.gov/pubmed/33233031 http://dx.doi.org/10.3857/roj.2020.00556 |
work_keys_str_mv | AT benitezcecilm harnessinggenomewideassociationstudiestominimizeadverseradiationinducedsideeffects AT knoxsusanj harnessinggenomewideassociationstudiestominimizeadverseradiationinducedsideeffects |