AI Article Synopsis
- The text discusses the creation of gmctool, an online tool designed to predict metabolic weaknesses in cancer cells, which is important for systems biology research.
- This tool utilizes a concept called genetic Minimal Cut Sets (gMCSs) to analyze genome-scale metabolic networks and includes a database of synthetic lethals derived from the latest metabolic map of human cells.
- Notably, gmctool has shown improved performance over earlier algorithms and has been applied to multiple myeloma, a type of blood cancer, providing experimental evidence for the critical roles of specific enzymes in certain patient groups.
Article 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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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11470099 | PMC |
| http://dx.doi.org/10.1038/s41467-024-52725-4 | DOI Listing |
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