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http://dx.doi.org/10.5483/BMBRep.2010.43.12.836

Relationships between genetic polymorphisms and transcriptional profiles for outcome prediction in anticancer agent treatment  

Paik, Hyo-Jung (Department of Bio and Brain Engineering, KAIST)
Lee, Eun-Jung (Department of Genetics, Brigham and Women's Hospital and Havard Medical School)
Lee, Do-Heon (Department of Bio and Brain Engineering, KAIST)
Publication Information
BMB Reports / v.43, no.12, 2010 , pp. 836-841 More about this Journal
Abstract
In the era of personal genomics, predicting the individual response to drug-treatment is a challenge of biomedical research. The aim of this study was to validate whether interaction information between genetic and transcriptional signatures are promising features to predict a drug response. Because drug resistance/susceptibilities result from the complex associations of genetic and transcriptional activities, we predicted the inter-relationships between genetic and transcriptional signatures. With this concept, captured genetic polymorphisms and transcriptional profiles were prepared in cancer samples. By splitting ninety-nine samples into a trial set (n = 30) and a test set (n = 69), the outperformance of relationship-focused model (0.84 of area under the curve in trial set, P = $2.90{\times}10^{-4}$) was presented in the trial set and validated in the test set, respectively. The prediction results of modeling show that considering the relationships between genetic and transcriptional features is an effective approach to determine outcome predictions of drug-treatment.
Keywords
Anticancer agents; Drug response; Individual variation; Prediction model; Relationship;
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