ArticleBMC systems biology2009
Human synthetic lethal inference as potential anti-cancer target gene detection.
Article in BMC systems biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Causal relationships of inflammatory cytokines and serum metabolites with colorectal carcinoma: A Mendelian randomization study.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026Article
- Synthetic lethality in cancer drug discovery: challenges and opportunities.Nature reviews. Drug discovery · 2026Review
- PHF5A as a new OncoTarget and therapeutic prospects.Heliyon · 2023Review
- Overcoming selection bias in synthetic lethality prediction.Bioinformatics (Oxford, England) · 2022Article
- SLOAD: a comprehensive database of cancer-specific synthetic lethal interactions for precision cancer therapy via multi-omics analysis.Database : the journal of biological databases and curation · 2022Article
- Computational methods, databases and tools for synthetic lethality prediction.Briefings in bioinformatics · 2022Review
- Harnessing synthetic lethality to predict the response to cancer treatment.Nature communications · 2018Article
- Synthetic Lethality-based Identification of Targets for Anticancer Drugs in the Human Signaling Network.Scientific reports · 2018Article
- Using Yeast Synthetic Lethality To Inform Drug Combination for Malaria.Antimicrobial agents and chemotherapy · 2018Article
- Precision Oncology: The Road Ahead.Trends in molecular medicine · 2017Review
- Computational Approaches to Identify Genetic Interactions for Cancer Therapeutics.Journal of integrative bioinformatics · 2017Article
- Epistasis in genomic and survival data of cancer patients.PLoS computational biology · 2017Article
- Synthetic lethality: emerging targets and opportunities in melanoma.Pigment cell & melanoma research · 2017Review
- Article
- Connectivity Homology Enables Inter-Species Network Models of Synthetic Lethality.PLoS computational biology · 2015Article
- LENS: web-based lens for enrichment and network studies of human proteins.BMC medical genomics · 2015Article
- Computational identification of surrogate genes for prostate cancer phases using machine learning and molecular network analysis.Theoretical biology & medical modelling · 2014Article
- In silico prediction of synthetic lethality by meta-analysis of genetic interactions, functions, and pathways in yeast and human cancer.Cancer informatics · 2014Article
- Syn-lethality: an integrative knowledge base of synthetic lethality towards discovery of selective anticancer therapies.BioMed research international · 2014Article
- Proposal for a new therapy for drug-resistant malaria using Plasmodium synthetic lethality inference.International journal for parasitology. Drugs and drug resistance · 2013Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundTwo genes are called synthetic lethal (SL) if mutation of either alone is not lethal, but mutation of both leads to death or a significant decrease in organism's fitness. The detection of SL gene pairs constitutes a promising alternative for anti-cancer therapy. As cancer cells exhibit a large number of mutations, the identification of these mutated genes' SL partners may provide specific anti-cancer drug candidates, with minor perturbations to the healthy cells. Since existent SL data is mainly restricted to yeast screenings, the road towards human SL candidates is limited to inference methods.
resultsIn the present work, we use phylogenetic analysis and database manipulation (BioGRID for interactions, Ensembl and NCBI for homology, Gene Ontology for GO attributes) in order to reconstruct the phylogenetically-inferred SL gene network for human. In addition, available data on cancer mutated genes (COSMIC and Cancer Gene Census databases) as well as on existent approved drugs (DrugBank database) supports our selection of cancer-therapy candidates.
conclusionsOur work provides a complementary alternative to the current methods for drug discovering and gene target identification in anti-cancer research. Novel SL screening analysis and the use of highly curated databases would contribute to improve the results of this methodology.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.