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Syn-lethality: an integrative knowledge base of synthetic lethality towards discovery of selective anticancer therapies.

Li XJ, Mishra SK, Wu M, Zhang F, Zheng J - Biomed Res Int (2014)

Bottom Line: It integrates experimentally discovered and verified human SL gene pairs into a network, associated with annotations of gene function, pathway, and molecular mechanisms.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.

View Article: PubMed Central - PubMed

Affiliation: Bioinformatics Research Centre (BIRC), School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798.

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.

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Related in: MedlinePlus

SL network of human cancer constructing based on SL literatures. Each node in the network denotes a gene/protein and each edge represents an SL interaction (the arrow direction leads from mutation gene to target gene).
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fig2: SL network of human cancer constructing based on SL literatures. Each node in the network denotes a gene/protein and each edge represents an SL interaction (the arrow direction leads from mutation gene to target gene).

Mentions: In this paper, we present an integrative knowledge base dedicated to SL in human cancer, called Syn-Lethality. From literature, we collected SL gene pairs that have been experimentally discovered and verified and integrated them into a network (Figure 2), where each node is a gene and each edge represents an SL interaction. We call such a network as SL network. Moreover, we associated the SL network with related gene annotations and pathway information, to facilitate mechanistic understanding of SL. In addition to human specific SL, we also collected yeast SL, which were mapped to human genes through orthologous correspondence. The information collected as such has been organized into a relational database with user friendly interface. When users input cancer genes (e.g., TP53), Syn-Lethality will search for SL partners of the query genes and display related annotations (e.g., pathways, gene functions, and hyperlinks to the related literature). The SL network we constructed serves as a roadmap for the whole knowledge base.


Syn-lethality: an integrative knowledge base of synthetic lethality towards discovery of selective anticancer therapies.

Li XJ, Mishra SK, Wu M, Zhang F, Zheng J - Biomed Res Int (2014)

SL network of human cancer constructing based on SL literatures. Each node in the network denotes a gene/protein and each edge represents an SL interaction (the arrow direction leads from mutation gene to target gene).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4016865&req=5

fig2: SL network of human cancer constructing based on SL literatures. Each node in the network denotes a gene/protein and each edge represents an SL interaction (the arrow direction leads from mutation gene to target gene).
Mentions: In this paper, we present an integrative knowledge base dedicated to SL in human cancer, called Syn-Lethality. From literature, we collected SL gene pairs that have been experimentally discovered and verified and integrated them into a network (Figure 2), where each node is a gene and each edge represents an SL interaction. We call such a network as SL network. Moreover, we associated the SL network with related gene annotations and pathway information, to facilitate mechanistic understanding of SL. In addition to human specific SL, we also collected yeast SL, which were mapped to human genes through orthologous correspondence. The information collected as such has been organized into a relational database with user friendly interface. When users input cancer genes (e.g., TP53), Syn-Lethality will search for SL partners of the query genes and display related annotations (e.g., pathways, gene functions, and hyperlinks to the related literature). The SL network we constructed serves as a roadmap for the whole knowledge base.

Bottom Line: It integrates experimentally discovered and verified human SL gene pairs into a network, associated with annotations of gene function, pathway, and molecular mechanisms.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.

View Article: PubMed Central - PubMed

Affiliation: Bioinformatics Research Centre (BIRC), School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798.

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.

Show MeSH
Related in: MedlinePlus