ArticleMolecules (Basel, Switzerland)2018
Facilitating Anti-Cancer Combinatorial Drug Discovery by Targeting Epistatic Disease Genes.
Article in Molecules (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 21 citations in OpenAlex.
- EpiSNPdb: A Comprehensive Database of Genetic Epistasis Across Multiple Cancer Types.Current issues in molecular biology · 2026Article
- Multimodal multiobjective optimization with structural network control principles to optimize personalized drug targets for drug discovery of individual patients.Briefings in bioinformatics · 2024Article
- Profibrotic Inflammatory Cytokines and Growth Factors Are Predicted as the Key Targets ofPharmaceuticals (Basel, Switzerland) · 2024Article
- A Bayesian approach to differential edges with probabilistic interactions: applications in association and classification.Bioinformatics advances · 2023Article
- Systems Pharmacology-Based Precision Therapy and Drug Combination Discovery for Breast Cancer.Cancers · 2021Article
- Network controllability-based algorithm to target personalized driver genes for discovering combinatorial drugs of individual patients.Nucleic acids research · 2021Article
- Three-dimensional genome: developmental technologies and applications in precision medicine.Journal of human genetics · 2020Article
- Turning genome-wide association study findings into opportunities for drug repositioning.Computational and structural biotechnology journal · 2020Review
- A novel network control model for identifying personalized driver genes in cancer.PLoS computational biology · 2019Article
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Due to synergistic effects, combinatorial drugs are widely used for treating complex diseases. However, combining drugs and making them synergetic remains a challenge. Genetic disease genes are considered a promising source of drug targets with important implications for navigating the drug space. Most diseases are not caused by a single pathogenic factor, but by multiple disease genes, in particular, interacting disease genes. Thus, it is reasonable to consider that targeting epistatic disease genes may enhance the therapeutic effects of combinatorial drugs. In this study, synthetic lethality gene pairs of tumors, similar to epistatic disease genes, were first targeted by combinatorial drugs, resulting in the enrichment of the combinatorial drugs with cancer treatment, which verified our hypothesis. Then, conventional epistasis detection software was used to identify epistatic disease genes from the genome wide association studies (GWAS) dataset. Furthermore, combinatorial drugs were predicted by targeting these epistatic disease genes, and five combinations were proven to have synergistic anti-cancer effects on MCF-7 cells through cell cytotoxicity assay. Combined with the three-dimensional (3D) genome-based method, the epistatic disease genes were filtered and were more closely related to disease. By targeting the filtered gene pairs, the efficiency of combinatorial drug discovery has been further improved.
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