DocumentCode :
3542481
Title :
Predicting drug efficacy based on the integrated breast cancer pathway model
Author :
Huang, Hui ; Wu, Xiaogang ; Ibrahim, Sara ; McKenzie, Marianne ; Chen, Jake Y.
Author_Institution :
Sch. of Inf., Indiana Univ., Indianapolis, IN, USA
fYear :
2011
fDate :
4-6 Dec. 2011
Firstpage :
42
Lastpage :
45
Abstract :
This study is based on a simple hypothesis - “ideal” drugs for a patient can cure the patient´s disease by modulating the gene expression profile of the patient to a similar level with those in healthy people, on the pathway level. To verify this hypothesis, we present a computational framework to evaluate drug effects on gene expression profiles in breast cancer. First, a breast cancer pathway model has been constructed by utilizing a computational connectivity maps (C-Maps) approach. This model includes important protein and drug information. In this pathway, specific drug-protein interactions (i.e. activation/inhibition) are annotated as edge attributes. Thus, we get a novel Pharmacology Effect Network, or PEN. We then develop a ranking algorithm called PET (i.e. Pharmacological Effect on Target) to combine gene expression information and our constructed PEN to evaluate specific drugs´ efficacies. Finally, we applied PET and PEN to evaluate 23 breast cancer drugs. The ranking results clearly show the validity of our framework.
Keywords :
cancer; drugs; genetics; patient treatment; pharmaceutical technology; computational connectivity map approach; computational framework; drug effect evaluation; drug efficacy prediction; drug information; drug-protein interactions; gene expression information; gene expression profile; integrated breast cancer pathway model; patient diseases; patient drugs; pharmacology effect network; protein information; ranking algorithm; Breast cancer; Diseases; Drugs; Educational institutions; Gene expression; Positron emission tomography; Proteins; Algorithms development; Cancer pathway modeling; Data Integration; Drug efficacy prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Genomic Signal Processing and Statistics (GENSIPS), 2011 IEEE International Workshop on
Conference_Location :
San Antonio, TX
ISSN :
2150-3001
Print_ISBN :
978-1-4673-0491-7
Electronic_ISBN :
2150-3001
Type :
conf
DOI :
10.1109/GENSiPS.2011.6169437
Filename :
6169437
Link To Document :
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