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Radiogenomics: radiobiology enters the era of big data and team science.
https://repo.qst.go.jp/records/46811
https://repo.qst.go.jp/records/46811382018b8-dc32-45a5-8662-ac9266366dfb
Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2014-09-01 | |||||
タイトル | ||||||
タイトル | Radiogenomics: radiobiology enters the era of big data and team science. | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
アクセス権 | ||||||
アクセス権 | metadata only access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
著者 |
S, Rosenstein Barry
× S, Rosenstein Barry× M, West Catharine× M, Bentzen Søren× Alsner, Jan× Nicolaj, Andreassen Christian× Azria, David× C, Barnett Gillian× Baumann, Michael× Burnet, Neil× Chang-Claude, Jenny× Y, Chuang Eric× E, Coles Charlotte× Dekker, Andre× De, Ruyck Kim× De, Ruysscher Dirk× Drumea, Karen× M, Dunning Alison× Easton, Douglas× Eeles, Rosalind× Fachal, Laura× Gutiérrez-Enríquez, Sara× Haustermans, Karin× Alberto, Henríquez-Hernández Luis× Imai, Takashi× D, D Jones George× L, Kerns Sarah× Liao, Zhongxing× Onel, Kenan× Ostrer, Harry× Parliament, Matthew× D, P Pharoah Paul× R, Rebbeck Timothy× J, Talbot Christopher× Thierens, Hubert× Vega, Ana× S, Witte John× Wong, Philip× Zenhausern, Frederic× 今井 高志 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Radiogenomics is the study of the link between germ line genotypic variations and the large clinical variability observed in response to radiation therapy. The radiogenomics hypothesis is that a proportion of the variance in the phenotype of interest – radiation toxicity - is explained by genotypic variation. Thus, the aim of radiogenomics is to identify the alleles that underlie the inherited dissimilarities in phenotype. However, this hypothesis does not assume that all of the phenotypic differences are due to germ line genetic alterations, but acknowledges that epigenetic changes (inherited and acquired) and other factors could also be important. In order to foster collaborative research, the Radiogenomics Consortium (RGC) was established in 2009 (1). The RGC currently has 174 members from 90 institutions in 20 countries and is an NCI supported cancer epidemiology consortium (2). The goal of the RGC is to facilitate large-scale collaborative research assessing gene-radiation effect relationships, including genome wide association studies (GWAS). The aim of this research is to produce assays for use in the clinic to predict risk of toxicities following radiotherapy, given alone or in multi-modality treatments. The results of this research could also lead to the identification of novel strategies for prevention or mitigation of toxicities. Currently, the radiogenomics landscape is rapidly changing. This is partly a result of research advances within the field of radiogenomics itself and partly due to progress in biotechnology and medical informatics that facilitate the pursuit of novel discovery strategies. Radiogenomics is now rapidly advancing from an effort to screen a limited number of candidate genes towards an open discovery approach. Or, from relatively small studies conducted by a few scientists to the potentially powerful, but challenging, era of Big Data and Team Science. However, the substantial progress in radiogenomics may be largely unnoticed by the broader radiotherapy community leading to underestimation of its potential for improving patient outcomes. Therefore, it is critical to address the following questions at this stage in the development of research in radiogenomics. |
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書誌情報 |
International journal of radiation oncology, biology, physics 巻 89, 号 4, p. 709-713, 発行日 2014-07 |
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出版者 | ||||||
出版者 | Elsevier Science Inc | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 0360-3016 | |||||
PubMed番号 | ||||||
識別子タイプ | PMID | |||||
関連識別子 | 24969789 |