ArticleNature communications2024
An automated network-based tool to search for metabolic vulnerabilities in cancer.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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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
10 citing papers in PubMed.
- Context-dependent synthetic lethality - an emerging precision therapeutic approach.Nature reviews. Cancer · 2026Review
- A community reconstruction of Chinese hamster metabolism and structural systems biology elucidate metabolic rewiring in lactate-free CHO cells.Cell systems · 2026Article
- Beyond synthetic lethality in large-scale metabolic and regulatory network models via genetic minimal intervention set.Bioinformatics advances · 2026Article
- UAP1 as a prognostic biomarker regulating malignant biological functions in multiple myeloma cells.Frontiers in oncology · 2026Article
- Constraint based modeling of drug induced metabolic changes in a cancer cell line.NPJ systems biology and applications · 2025Article
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- Article
- Minimal cut sets in metabolic networks: from conceptual foundations to applications in metabolic engineering and biomedicine.Briefings in bioinformatics · 2025Review
- An automated network-based tool to search for metabolic vulnerabilities in cancer.Nature communications · 2024Article
- Synthetic lethality in large-scale integrated metabolic and regulatory network models of human cells.NPJ systems biology and applications · 2023Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
The development of computational tools for the systematic prediction of metabolic vulnerabilities of cancer cells constitutes a central question in systems biology. Here, we present gmctool, a freely accessible online tool that allows us to accomplish this task in a simple, efficient and intuitive environment. gmctool exploits the concept of genetic Minimal Cut Sets (gMCSs), a theoretical approach to synthetic lethality based on genome-scale metabolic networks, including a unique database of synthetic lethals computed from Human1, the most recent metabolic reconstruction of human cells. gmctool introduces qualitative and quantitative improvements over our previously developed algorithms to predict, visualize and analyze metabolic vulnerabilities in cancer, demonstrating a superior performance than competing algorithms. A detailed illustration of gmctool is presented for multiple myeloma (MM), an incurable hematological malignancy. We provide in vitro experimental evidence for the essentiality of CTPS1 (CTPS synthase) and UAP1 (UDP-N-Acetylglucosamine Pyrophosphorylase 1) in specific MM patient subgroups.
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Registered trials
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