An automated network-based tool to search for metabolic vulnerabilities in cancer

Luis V. Valcárcel, Edurne San José-Enériz, Raquel Ordoñez, Iñigo Apaolaza, Danel Olaverri-Mendizabal, Naroa Barrena, Ana Valcárcel, Leire Garate, Jesús San Miguel, Antonio Pineda-Lucena, Xabier Agirre, Felipe Prósper () and Francisco J. Planes ()
Additional contact information
Luis V. Valcárcel: Manuel de Lardizábal 13
Edurne San José-Enériz: CCUN
Raquel Ordoñez: CCUN
Iñigo Apaolaza: Manuel de Lardizábal 13
Danel Olaverri-Mendizabal: Manuel de Lardizábal 13
Naroa Barrena: Manuel de Lardizábal 13
Ana Valcárcel: CCUN
Leire Garate: CCUN
Jesús San Miguel: CCUN
Antonio Pineda-Lucena: CCUN
Xabier Agirre: CCUN
Felipe Prósper: CCUN
Francisco J. Planes: Manuel de Lardizábal 13

Nature Communications, 2024, vol. 15, issue 1, 1-15

Abstract: 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.

Date: 2024
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DOI: 10.1038/s41467-024-52725-4

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