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Drug-repositioning map based on protein-protein interactions
단백질-단백질 상호작용 기반의 약물 리포지셔닝 맵

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Authors
양산덕
Advisor
김종일
Major
의과대학 의과학과
Issue Date
2016-02
Publisher
서울대학교 대학원
Keywords
Drug repositioningPPInetwork analysisdatabaseOSE (ovarian serous epithelial cancer)biomarker
Description
학위논문 (박사)-- 서울대학교 대학원 : 의과대학 의과학과 의과학전공, 2016. 2. 김종일.
Abstract
Introduction: The development of new drugs is recognized as a time-consuming and risky process, which has increased interest in drug repositioning, i.e., the identification and development of new uses for FDA-approved drugs, as repurposed drugs can bypass much of the early cost- and time-investment. I have developed the large-scale DreMap tool, featuring a web-based tool to discover new implementations for an existing drugs, based on known protein-protein interactions. According to data released by the Centers for Disease Control and Prevention, Ovarian cancer was ranked the fifth cause of cancer-associated death in women in the USA. To establish proper diagnosis and repositioning functions for ovarian cancer, I analyzed differentially expressed genes between 5-years survival group and 5-years death group of lymphatic invasion in serous ovarian epithelial cancer with DNA microarray. I suggested repositioning available drugs for ovarian cancer using Dremap database.
Methods: I connected the drug–target-protein information, protein-protein interaction information, protein–relevant disease information and protein–function relations to each other. Data from 63 ovarian cancer patients with lymphatic invasion and 35 ovarian cancer patients without lymphatic invasion from TCGA data were analyzed. DEGs identified with Bioconductor R package. Functional analyses of genes were analyzed with DAVID web tool.
Results: DReMap provides possible indications of 8849 drugs. I found 20 DEGs (P-value<0.001) from 35 ovarian cancer patients without lymphatic invasion. To gain insight into the 5-year survival related gene expression signatures, I demonstrated survival score values for 5 prognostic marker genes of patients without lymphatic invasion. I also suggested 13 repositioning available drugs for ovarian cancer using 5 prognostic marker genes and Dremap database.
Conclusions: Until now, most cases of drug repositioning have been the result of serendipitous observations. Through exploring the DreMap, researchers can obtain useful clues in regard to additional therapeutic effects of pre-existing drugs and explore their novel functions. I believe that our database will supply valuable information to users with regard to unknown pathways in drug mechanisms. I also suggested 5 prognostic marker genes and repositioning drug lists of ovarian cancer. These findings may have implications for future diagnosis and treatment of ovarian cancer.
Language
English
URI
https://hdl.handle.net/10371/122305
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College of Medicine/School of Medicine (의과대학/대학원)Dept. of Biomedical Sciences (대학원 의과학과)Theses (Ph.D. / Sc.D._의과학과)
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