Network-based drug repurposing for HPV-associated cervical cancer

被引:17
作者
Ahmed, Faheem [1 ]
Yang, Young Jin [2 ]
Samantasinghar, Anupama [1 ]
Kim, Young Woo [2 ]
Ko, Jeong Beom [2 ]
Choi, Kyung Hyun [1 ]
机构
[1] Jeju Natl Univ, Dept Mechatron Engn, Jeju, South Korea
[2] Korea Inst Ind Technol, 102 Jejudaehak Ro, Jeju Si 63243, South Korea
关键词
Cervical cancer; Drug repurposing; Human papillomavirus; Protein interactions; Systems biology; HUMAN-PAPILLOMAVIRUS; ENRICHMENT ANALYSIS; INFORMATION; EXPRESSION; INFECTION; DATABASE; THERAPY; RISK; TOOL;
D O I
10.1016/j.csbj.2023.10.038
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
In women, cervical cancer (CC) is the fourth most common cancer around the world with average cases of 604,000 and 342,000 deaths per year. Approximately 50% of high-grade CC are attributed to human papillomavirus (HPV) types 16 and 18. Chances of CC in HPV-positive patients are 6 times more than HPV-negative patients which demands timely and effective treatment. Repurposing of drugs is considered a viable approach to drug discovery which makes use of existing drugs, thus potentially reducing the time and costs associated with de-novo drug discovery. In this study, we present an integrative drug repurposing framework based on a systems biology-enabled network medicine platform. First, we built an HPV-induced CC protein interaction network named HPV2C following the CC signatures defined by the omics dataset, obtained from GEO database. Second, the drug target interaction (DTI) data obtained from DrugBank, and related databases was used to model the DTI network followed by drug target network proximity analysis of HPV-host associated key targets and DTIs in the human protein interactome. This analysis identified 142 potential anti-HPV repurposable drugs to target HPV induced CC pathways. Third, as per the literature survey 51 of the predicted drugs are already used for CC and 33 of the remaining drugs have anti-viral activity. Gene set enrichment analysis of potential drugs in drug-gene signatures and in HPV-induced CC-specific transcriptomic data in human cell lines additionally validated the predictions. Finally, 13 drug combinations were found using a network based on overlapping exposure. To summarize, the study provides effective network-based technique to quickly identify suitable repurposable drugs and drug combinations that target HPV-associated CC.
引用
收藏
页码:5186 / 5200
页数:15
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