ArticleNPJ systems biology and applications2023
Synthetic lethality in large-scale integrated metabolic and regulatory network models of human cells.
Article in NPJ systems biology and applications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Review and meta-analysis of the genetic Minimal Cut Set approach for gene essentiality prediction in cancer metabolism.Briefings in bioinformatics · 2024Pooled it
- Context-dependent synthetic lethality - an emerging precision therapeutic approach.Nature reviews. Cancer · 2026Review
- Simultaneous Inhibition of ACLY and OGDH Has a Synergistic Effect on Hepatocellular Carcinoma Cell Lines.bioRxiv : the preprint server for biology · 2026Article
- gMISpy: integration of complex regulatory networks and genome scale metabolic models.Bioinformatics (Oxford, England) · 2026Article
- Higher order synthetic lethals are keys to minimize cancer treatment effects on non-tumor cells.PloS one · 2026Article
- Beyond synthetic lethality in large-scale metabolic and regulatory network models via genetic minimal intervention set.Bioinformatics advances · 2026Article
- Synthetic lethality in cancer drug discovery: challenges and opportunities.Nature reviews. Drug discovery · 2026Review
- The impact of epigenetics on tumor metabolism: Friend or foe in drug response?Frontiers in epigenetics and epigenomics · 2026Review
- Constraint based modeling of drug induced metabolic changes in a cancer cell line.NPJ systems biology and applications · 2025Article
- TARGET-SL: precision essential gene prediction using driver prioritisation and synthetic lethality.Briefings in bioinformatics · 2025Article
- Interpretable high-order knowledge graph neural network for predicting synthetic lethality in human cancers.Briefings in bioinformatics · 2025Article
- New Horizons of Synthetic Lethality in Cancer: Current Development and Future Perspectives.Journal of medicinal chemistry · 2024Review
- gMCSpy: efficient and accurate computation of genetic minimal cut sets in Python.Bioinformatics (Oxford, England) · 2024Article
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Authors and funding
5 authors.
Funding
Abstract
Synthetic lethality (SL) is a promising concept in cancer research. A wide array of computational tools has been developed to predict and exploit synthetic lethality for the identification of tumour-specific vulnerabilities. Previously, we introduced the concept of genetic Minimal Cut Sets (gMCSs), a theoretical approach to SL developed for genome-scale metabolic networks. The major challenge in our gMCS framework is to go beyond metabolic networks and extend existing algorithms to more complex protein-protein interactions. In this article, we take a step further and incorporate linear regulatory pathways into our gMCS approach. Extensive algorithmic modifications to compute gMCSs in integrated metabolic and regulatory models are presented in detail. Our extended approach is applied to calculate gMCSs in integrated models of human cells. In particular, we integrate the most recent genome-scale metabolic network, Human1, with 3 different regulatory network databases: Omnipath, Dorothea and TRRUST. Based on the computed gMCSs and transcriptomic data, we discovered new essential genes and their associated synthetic lethal for different cancer cell lines. The performance of the different integrated models is assessed with available large-scale in-vitro gene silencing data. Finally, we discuss the most relevant gene essentiality predictions based on published literature in cancer research.
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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.