ArticleScientific reports2018
Synthetic Lethality-based Identification of Targets for Anticancer Drugs in the Human Signaling Network.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 32 citations in OpenAlex.
- Article
- New Insights into Colorectal Cancer through the Lens of Precision Oncology and Personalized Medicine: Multi-Omics Helps Aging of Predisposed People.Current aging science · 2025Review
- Benchmarking machine learning methods for synthetic lethality prediction in cancer.Nature communications · 2024Article
- Computational Approaches: A New Frontier in Cancer Research.Combinatorial chemistry & high throughput screening · 2024Review
- Unleashing the Power of Synthetic Lethality: Augmenting Treatment Efficacy through Synergistic Integration with Chemotherapy Drugs.Pharmaceutics · 2023Review
- The Future of Precision Oncology.International journal of molecular sciences · 2023Review
- Multi-level characteristics recognition of cancer core therapeutic targets and drug screening for a broader patient population.Frontiers in pharmacology · 2023Article
- Discovery of synthetic lethal interactions from large-scale pan-cancer perturbation screens.Nature communications · 2022Article
- Computational methods, databases and tools for synthetic lethality prediction.Briefings in bioinformatics · 2022Review
- Functional buffering via cell-specific gene expression promotes tissue homeostasis and cancer robustness.Scientific reports · 2022Article
- Identification of anticancer drug target genes using an outside competitive dynamics model on cancer signaling networks.Scientific reports · 2021Article
- In Silico Inference of Synthetic Cytotoxic Interactions from Paclitaxel Responses.International journal of molecular sciences · 2021Article
- Development of synthetic lethality in cancer: molecular and cellular classification.Signal transduction and targeted therapy · 2020Review
- Advances in synthetic lethality for cancer therapy: cellular mechanism and clinical translation.Journal of hematology & oncology · 2020Review
- Identifying Drug Targets in Pancreatic Ductal Adenocarcinoma Through Machine Learning, Analyzing Biomolecular Networks, and Structural Modeling.Frontiers in pharmacology · 2020Article
- p21 in Cancer Research.Cancers · 2019Review
Corrections and comments
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chemotherapy agents can cause serious adverse effects by attacking both cancer tissues and normal tissues. Therefore, we proposed a synthetic lethality (SL) concept-based computational method to identify specific anticancer drug targets. First, a 3-step screening strategy (network-based, frequency-based and function-based screening) was proposed to identify the SL gene pairs by mining 697 cancer genes and the human signaling network, which had 6306 proteins and 62937 protein-protein interactions. The network-based screening was composed of a stability score constructed using a network information centrality measure (the average shortest path length) and the distance-based screening between the cancer gene and the non-cancer gene. Then, the non-cancer genes were extracted and annotated using drug-target interaction and drug description information to obtain potential anticancer drug targets. Finally, the human SL data in SynLethDB, the existing drug sensitivity data and text-mining were utilized for target validation. We successfully identified 2555 SL gene pairs and 57 potential anticancer drug targets. Among them, CDK1, CDK2, PLK1 and WEE1 were verified by all three aspects and could be preferentially used in specific targeted therapy in the future.
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Registered trials
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