ReviewNature genetics2023
Complex synthetic lethality in cancer.
Review in Nature genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
42 citing papers in PubMed.
- DNA polymerase theta (Polθ): a novel candidate for targeted cancer therapy.Cancer biology & therapy · 2026Review
- RhoA WT allele loss unleashes the cancer driver function of RhoA E40Q.The Journal of clinical investigation · 2026Article
- PUM3 is an essential suppressor of replication stress in homologous recombination deficient breast cancer.Nature communications · 2026Article
- Article
- The PRECISE European initiative for cancer-vulnerability mapping and prediction.Nature genetics · 2026Article
- LIG1 Loss in TP53-mutant Triple Negative Breast Cancer Rewires DNA Repair and Confers Sensitivity to PARP-ATR Inhibitor Combinations.Molecular cancer therapeutics · 2026Article
- Breaking the Efflux Barrier: P-Glycoprotein and Emerging Strategies to Overcome Multidrug Resistance in Cancer.Cancers · 2026Review
- DISCERN: inferring drug sensitivity from single-cell transcriptomes using cell-type-specific genetic interaction networks.Genome medicine · 2026Article
- CME-KGDTI: integrating clustered mutations into knowledge graph embedding for drug-target interaction prediction.BioData mining · 2026Article
- Using cancer profiles to identify synthetic lethal therapeutic targets and predictive biomarkers in cancer gene dependency data.Bioinformatics (Oxford, England) · 2026Article
- KIF23 in disease pathogenesis and its therapeutic and diagnostic potential.Discover oncology · 2026Review
- Synthetic lethality in cancer: mechanism exploration and therapeutic applications.Cell communication and signaling : CCS · 2026Review
- Review
- Inhibition of PRMT5 triggers synthetic lethality in ARID1A-deficient endometrial cancer by promoting aberrant R-loop accumulation.Molecular cancer · 2026Article
- Article
- Quantitative analysis of genetic interactions in human cells from genome-wide CRISPR-Cas9 screens.bioRxiv : the preprint server for biology · 2026Article
- Article
- Synthetic lethality in cancer drug discovery: challenges and opportunities.Nature reviews. Drug discovery · 2026Review
- Synergistic targeting of cancer cells through simultaneous inhibition of key metabolic enzymes.Cell death and differentiation · 2025Article
- Computationally-designed aptamers targeting RAD51-BRCA2 interaction impair homologous recombination and induce synthetic lethality.Nature communications · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The concept of synthetic lethality has been widely applied to identify therapeutic targets in cancer, with varying degrees of success. The standard approach normally involves identifying genetic interactions between two genes, a driver and a target. In reality, however, most cancer synthetic lethal effects are likely complex and also polygenic, being influenced by the environment in addition to involving contributions from multiple genes. By acknowledging and delineating this complexity, we describe in this article how the success rate in cancer drug discovery and development could be improved.
Indexed as
Identifiers
38036785What OpenQuestion holds
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.