ArticleNature genetics2025
A multilineage screen identifies actionable synthetic lethal interactions in human cancers.
Article in Nature genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.
What it found
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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.
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Who cites it
14 citing papers in PubMed.
- PARP7 inhibitors enhance the immunogenic effects of radiation in pancreatic cancer cells.Molecular therapy. Oncology · 2026Article
- XYL-1 and Olaparib Synergistically Inhibit the Growth of Pancreatic Cancer by Suppressing the SCD1/BRCA1 Signaling Pathway.Molecules (Basel, Switzerland) · 2026Article
- A novel ILP framework to identify compensatory pathways in genetic interaction networks with GIDEON.Bioinformatics (Oxford, England) · 2026Article
- Context-dependent synthetic lethality - an emerging precision therapeutic approach.Nature reviews. Cancer · 2026Review
- Review
- Prognostic and Immunological Significance of TIPARP in Pancreatic Cancer.Digestive diseases and sciences · 2026Article
- Double-CRISPR Knockout Simulation (DKOsim): A Monte-Carlo randomization system to model cell growth behavior and infer the optimal library design for growth-based double knockout screens.PLoS computational biology · 2026Article
- A Novel ILP Framework to Identify Compensatory Pathways in Genetic Interaction Networks with GIDEON.bioRxiv : the preprint server for biology · 2026Article
- Charting cell-type-specific positive genetic interaction at single-cell resolution for lung adenocarcinoma.NPJ precision oncology · 2026Article
- Analysis of Combinatorial Knockout CRISPR Screens with GRAPE: Genetic interaction Regression Analysis of Pairwise Effects.bioRxiv : the preprint server for biology · 2026Article
- Medea: An omics AI agent for therapeutic discovery.bioRxiv : the preprint server for biology · 2026Article
- Functional modules predict cancer-relevant genetic interactions in mammalian cells.bioRxiv : the preprint server for biology · 2025Article
- Advances and Challenges in Drug Screening for Cancer Therapy: A Comprehensive Review.Bioengineering (Basel, Switzerland) · 2025Review
- Drosophila and human cell studies reveal a conserved role for CEBPZ, NOC2L and NOC3L in rRNA processing and tumorigenesis.Journal of cell science · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
16 authors.
Funding
Abstract
Cancers are driven by alterations in diverse genes, creating dependencies that can be therapeutically targeted. However, many genetic dependencies have proven inconsistent across tumors. Here we describe SCHEMATIC, a strategy to identify a core network of highly penetrant, actionable genetic interactions. First, fundamental cellular processes are perturbed by systematic combinatorial knockouts across tumor lineages, identifying 1,805 synthetic lethal interactions (95% unreported). Interactions are then analyzed by hierarchical pooling, revealing that half segregate reliably by tissue type or biomarker status (51%) and a substantial minority are penetrant across lineages (34%). Interactions converge on 49 multigene systems, including MAPK signaling and BAF transcriptional regulatory complexes, which become essential on disruption of polymerases. Some 266 interactions translate to robust biomarkers of drug sensitivity, including frequent genetic alterations in the KDM5C/6A histone demethylases, which sensitize to inhibition of TIPARP (PARP7). SCHEMATIC offers a context-aware, data-driven approach to match genetic alterations to targeted 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.