Syn-Lethality: An Integrative Knowledge Base of Synthetic Lethality towards Discovery of Selective Anticancer Therapies

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Syn-Lethality: An Integrative Knowledge Base of Synthetic Lethality towards Discovery of Selective Anticancer Therapies
Title:
Syn-Lethality: An Integrative Knowledge Base of Synthetic Lethality towards Discovery of Selective Anticancer Therapies
Journal Title:
BioMed Research International
Keywords:
Publication Date:
22 April 2014
Citation:
Xue-juan Li, Shital K. Mishra, Min Wu, Fan Zhang, and Jie Zheng, “Syn-Lethality: An Integrative Knowledge Base of Synthetic Lethality towards Discovery of Selective Anticancer Therapies,” BioMed Research International, vol. 2014, Article ID 196034, 7 pages, 2014. doi:10.1155/2014/196034
Abstract:
Synthetic lethality (SL) is a novel strategy for anticancer therapies, whereby mutations of two genes will kill a cell but mutation of a single gene will not. Therefore, a cancer-specific mutation combined with a drug-induced mutation, if they have SL interactions, will selectively kill cancer cells. While numerous SL interactions have been identified in yeast, only a few have been known in human. There is a pressing need to systematically discover and understand SL interactions specific to human cancer. In this paper, we present Syn-Lethality, the first integrative knowledge base of SL that is dedicated to human cancer. It integrates experimentally discovered and verified human SL gene pairs into a network, associated with annotations of gene function, pathway, and molecular mechanisms. It also includes yeast SL genes from high-throughput screenings which are mapped to orthologous human genes. Such an integrative knowledge base, organized as a relational database with user interface for searching and network visualization, will greatly expedite the discovery of novel anticancer drug targets based on synthetic lethality interactions. The database can be downloaded as a stand-alone Java application.
License type:
http://creativecommons.org/licenses/by/4.0/
Funding Info:
Description:
ISSN:
2314-6133
2314-6141
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