ArticleNature communications2017
Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data.
Article in Nature communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.
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Who cites it
51 citing papers in PubMed, 1 synthesis or guideline pooled it, 98 citations in OpenAlex.
- Synthetic lethal gene pairs: Experimental approaches and predictive models.Frontiers in genetics · 2022Pooled it
- Synthetic lethality in TP53-mutant acute myeloid leukemia.Blood advances · 2026Article
- Pertuzumab Enhances the Antitumor Activity of T-DXd in HER2-Positive Gastric Cancer Cells.Molecular cancer therapeutics · 2026Article
- Synthetic lethality in cancer drug discovery: challenges and opportunities.Nature reviews. Drug discovery · 2026Review
- Epigenetic synthetic lethality as a cancer therapeutic strategy: synergy of experimental and computational approaches.Epigenomics · 2025Review
- Cell Cycle-Based Molecular Features via Synthetic Lethality and Non-Coding RNA Interactions in Cancer.Genes · 2025Article
- Interpretable high-order knowledge graph neural network for predicting synthetic lethality in human cancers.Briefings in bioinformatics · 2025Article
- Struct2SL: Synthetic lethality prediction based on AlphaFold2 structure information and Multilayer Perceptron.Computational and structural biotechnology journal · 2025Article
- COPZ1: an example of non-oncogene addiction in human tumors.Frontiers in pharmacology · 2025Review
- Von Hippel-Lindau protein signalling in clear cell renal cell carcinoma.Nature reviews. Urology · 2024Review
- Benchmarking machine learning methods for synthetic lethality prediction in cancer.Nature communications · 2024Article
- MAGICAL: A multi-class classifier to predict synthetic lethal and viable interactions using protein-protein interaction network.PLoS computational biology · 2024Article
- Synthetic lethal connectivity and graph transformer improve synthetic lethality prediction.Briefings in bioinformatics · 2024Article
- Pathway-driven analysis of synthetic lethal interactions in cancer using perturbation screens.Life science alliance · 2024Article
- RUNX1 loss renders hematopoietic and leukemic cells dependent on IL-3 and sensitive to JAK inhibition.The Journal of clinical investigation · 2023Article
- SL-scan identifies synthetic lethal interactions in cancer using metabolic networks.Scientific reports · 2023Article
- Precision and strategic targeting of novel mutation-specific vulnerabilities in acute myeloid leukemia: the semi-centennial of 7 + 3.Leukemia & lymphoma · 2023Review
- Synthetic lethality prediction in DNA damage repair, chromatin remodeling and the cell cycle using multi-omics data from cell lines and patients.Scientific reports · 2023Article
- Dysregulated Lipid Synthesis by Oncogenic IDH1 Mutation Is a Targetable Synthetic Lethal Vulnerability.Cancer discovery · 2023Article
- SLGNN: synthetic lethality prediction in human cancers based on factor-aware knowledge graph neural network.Bioinformatics (Oxford, England) · 2023Article
Corrections and comments
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Authors and funding
13 authors at 6 institutions in 4 countries.
Funding
Abstract
Two genes are synthetically lethal (SL) when defects in both are lethal to a cell but a single defect is non-lethal. SL partners of cancer mutations are of great interest as pharmacological targets; however, identifying them by cell line-based methods is challenging. Here we develop MiSL (Mining Synthetic Lethals), an algorithm that mines pan-cancer human primary tumour data to identify mutation-specific SL partners for specific cancers. We apply MiSL to 12 different cancers and predict 145,891 SL partners for 3,120 mutations, including known mutation-specific SL partners. Comparisons with functional screens show that MiSL predictions are enriched for SLs in multiple cancers. We extensively validate a SL interaction identified by MiSL between the IDH1 mutation and ACACA in leukaemia using gene targeting and patient-derived xenografts. Furthermore, we apply MiSL to pinpoint genetic biomarkers for drug sensitivity. These results demonstrate that MiSL can accelerate precision oncology by identifying mutation-specific targets and biomarkers.
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Registered trials
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.