ReviewNature reviews. Drug discovery2011
Harnessing synthetic lethal interactions in anticancer drug discovery.
Review in Nature reviews. Drug discovery, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 133 papers.
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Who cites it
133 citing papers in PubMed, 267 citations in OpenAlex.
- MVGAE: A Multi-View Graph Auto-Encoder Model for Drug Prediction of Non-Small Cell Lung Cancer Based on Synthetic Lethality.Current issues in molecular biology · 2026Article
- Mutation-informed gene pairs to predict melanoma metastasis.Cell communication and signaling : CCS · 2026Article
- CHD8 interacts with BCL11A to induce oncogenic transcription in triple negative breast cancer.The EMBO journal · 2025Article
- SETD2 loss-of-function uniquely sensitizes cells to epigenetic targeting of NSD1-directed H3K36 methylation.Genome biology · 2025Article
- Potential promising of synthetic lethality in cancer research and treatment.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- PALB2 deficiency may sensitize H3K27M-mutant pediatric HGG cells to BMN673/talazoparib.Frontiers in oncology · 2025Article
- Nuclear to cytoplasmic transport is a druggable dependency in MYC-driven hepatocellular carcinoma.Nature communications · 2024Article
- ELISL: early-late integrated synthetic lethality prediction in cancer.Bioinformatics (Oxford, England) · 2024Article
- Relationship between homologous recombination deficiency and clinical features of breast cancer based on genomic scar score.Breast (Edinburgh, Scotland) · 2023Article
- Review
- Tripartite motif containing 69 elicits ERK2-dependent EYA4 turnover to impart pancreatic tumorigenesis.Journal of Cancer · 2023Article
- The State of Preclinical Modeling for Early Phase Cancer Trials Using Molecularly Targeted Agents with Radiation.Radiation research · 2022Article
- Crosstalk between metabolic reprogramming and epigenetics in cancer: updates on mechanisms and therapeutic opportunities.Cancer communications (London, England) · 2022Review
- MYC and therapy resistance in cancer: risks and opportunities.Molecular oncology · 2022Review
- BRD4 inhibition induces synthetic lethality in ARID2-deficient hepatocellular carcinoma by increasing DNA damage.Oncogene · 2022Article
- Multi-view graph convolutional network for cancer cell-specific synthetic lethality prediction.Frontiers in genetics · 2022Article
- Carbon ion radiotherapy eradicates medulloblastomas with chromothripsis in an orthotopic Li-Fraumeni patient-derived mouse model.Neuro-oncology · 2021Article
- Impact of Chromatin Dynamics and DNA Repair on Genomic Stability and Treatment Resistance in Pediatric High-Grade Gliomas.Cancers · 2021Review
- Review
- Article
73 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Unique features of tumours that can be exploited by targeted therapies are a key focus of current cancer research. One such approach is known as synthetic lethality screening, which involves searching for genetic interactions of two mutations whereby the presence of either mutation alone has no effect on cell viability but the combination of the two mutations results in cell death. The presence of one of these mutations in cancer cells but not in normal cells can therefore create opportunities to selectively kill cancer cells by mimicking the effect of the second genetic mutation with targeted therapy. Here, we summarize strategies that can be used to identify synthetic lethal interactions for anticancer drug discovery, describe examples of such interactions that are currently being investigated in preclinical and clinical studies of targeted anticancer therapies, and discuss the challenges of realizing the full potential of such therapies.
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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.