Literature DB >> 26516187

SynLethDB: synthetic lethality database toward discovery of selective and sensitive anticancer drug targets.

Jing Guo1, Hui Liu2, Jie Zheng3.   

Abstract

Synthetic lethality (SL) is a type of genetic interaction between two genes such that simultaneous perturbations of the two genes result in cell death or a dramatic decrease of cell viability, while a perturbation of either gene alone is not lethal. SL reflects the biologically endogenous difference between cancer cells and normal cells, and thus the inhibition of SL partners of genes with cancer-specific mutations could selectively kill cancer cells but spare normal cells. Therefore, SL is emerging as a promising anticancer strategy that could potentially overcome the drawbacks of traditional chemotherapies by reducing severe side effects. Researchers have developed experimental technologies and computational prediction methods to identify SL gene pairs on human and a few model species. However, there has not been a comprehensive database dedicated to collecting SL pairs and related knowledge. In this paper, we propose a comprehensive database, SynLethDB (http://histone.sce.ntu.edu.sg/SynLethDB/), which contains SL pairs collected from biochemical assays, other related databases, computational predictions and text mining results on human and four model species, i.e. mouse, fruit fly, worm and yeast. For each SL pair, a confidence score was calculated by integrating individual scores derived from different evidence sources. We also developed a statistical analysis module to estimate the druggability and sensitivity of cancer cells upon drug treatments targeting human SL partners, based on large-scale genomic data, gene expression profiles and drug sensitivity profiles on more than 1000 cancer cell lines. To help users access and mine the wealth of the data, we developed other practical functionalities, such as search and filtering, orthology search, gene set enrichment analysis. Furthermore, a user-friendly web interface has been implemented to facilitate data analysis and interpretation. With the integrated data sets and analytics functionalities, SynLethDB would be a useful resource for biomedical research community and pharmaceutical industry.
© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Year:  2015        PMID: 26516187      PMCID: PMC4702809          DOI: 10.1093/nar/gkv1108

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  48 in total

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Review 3.  The NCI60 human tumour cell line anticancer drug screen.

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Journal:  Nat Rev Cancer       Date:  2006-10       Impact factor: 60.716

4.  Predicting cancer-specific vulnerability via data-driven detection of synthetic lethality.

Authors:  Livnat Jerby-Arnon; Nadja Pfetzer; Yedael Y Waldman; Lynn McGarry; Daniel James; Emma Shanks; Brinton Seashore-Ludlow; Adam Weinstock; Tamar Geiger; Paul A Clemons; Eyal Gottlieb; Eytan Ruppin
Journal:  Cell       Date:  2014-08-28       Impact factor: 41.582

5.  Analysis of genetic interactions on a genome-wide scale in budding yeast: diploid-based synthetic lethality analysis by microarray.

Authors:  Pamela B Meluh; Xuewen Pan; Daniel S Yuan; Carol Tiffany; Ou Chen; Sharon Sookhai-Mahadeo; Xiaoling Wang; Brian D Peyser; Rafael Irizarry; Forrest A Spencer; Jef D Boeke
Journal:  Methods Mol Biol       Date:  2008

Review 6.  Synthetic lethality: general principles, utility and detection using genetic screens in human cells.

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  40 in total

Review 1.  Exploiting Synthetic Lethality and Network Biology to Overcome EGFR Inhibitor Resistance in Lung Cancer.

Authors:  Simon Vyse; Annie Howitt; Paul H Huang
Journal:  J Mol Biol       Date:  2017-05-03       Impact factor: 5.469

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Review 3.  Marked for death: targeting epigenetic changes in cancer.

Authors:  Sophia Xiao Pfister; Alan Ashworth
Journal:  Nat Rev Drug Discov       Date:  2017-03-10       Impact factor: 84.694

Review 4.  Synthetic lethality and cancer.

Authors:  Nigel J O'Neil; Melanie L Bailey; Philip Hieter
Journal:  Nat Rev Genet       Date:  2017-06-26       Impact factor: 53.242

Review 5.  Conceptual frameworks of synthetic lethality in clear cell carcinoma of the ovary.

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Journal:  Biomed Rep       Date:  2018-06-20

Review 6.  Biomarkers: Delivering on the expectation of molecularly driven, quantitative health.

Authors:  Jennifer L Wilson; Russ B Altman
Journal:  Exp Biol Med (Maywood)       Date:  2017-12-03

Review 7.  Synthetic Lethal Networks for Precision Oncology: Promises and Pitfalls.

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Journal:  J Mol Biol       Date:  2018-06-20       Impact factor: 5.469

8.  DrugCombDB: a comprehensive database of drug combinations toward the discovery of combinatorial therapy.

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9.  SynLeGG: analysis and visualization of multiomics data for discovery of cancer 'Achilles Heels' and gene function relationships.

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Journal:  Nucleic Acids Res       Date:  2021-07-02       Impact factor: 16.971

10.  Transcriptomic heterogeneity of driver gene mutations reveals novel mutual exclusivity and improves exploration of functional associations.

Authors:  Yujia Lan; Wei Liu; Wanmei Zhang; Jing Hu; Xiaojing Zhu; Linyun Wan; Suru A; Yanyan Ping; Yun Xiao
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