Metabolic modeling-based drug repurposing in Glioblastoma

Tomi-Andrino, Claudio; Pandele, Alina; Winzer, Klaus; King, John; Rahman, Ruman; Kim, Dong-Hyun

Abstract

The manifestation of intra- and inter-tumor heterogeneity hinders the development of ubiquitous cancer treatments, thus requiring a tailored therapy for each cancer type. Specifically, the reprogramming of cellular metabolism has been identified as a source of potential drug targets. Drug discovery is a long and resource-demanding process aiming at identifying and testing compounds early in the drug development pipeline. While drug repurposing efforts (i.e., inspecting readily available approved drugs) can be supported by a mechanistic rationale, strategies to further reduce and prioritize the list of potential candidates are still needed to facilitate feasible studies. Although a variety of ‘omics’ data are widely gathered, a standard integration method with modeling approaches is lacking. For instance, flux balance analysis is a metabolic modeling technique that mainly relies on the stoichiometry of the metabolic network. However, exploring the network’s topology typically neglects biologically relevant information. Here we introduce Transcriptomics-Informed Stoichiometric Modelling And Network analysis (TISMAN) in a recombinant innovation manner, allowing identification and validation of genes as targets for drug repurposing using glioblastoma as an exemplar.

Citation

Tomi-Andrino, C., Pandele, A., Winzer, K., King, J., Rahman, R., & Kim, D.-H. (2022). Metabolic modeling-based drug repurposing in Glioblastoma. Scientific Reports, 12, Article 11189. https://doi.org/10.1038/s41598-022-14721-w

• Journal Article Type: Article
• Acceptance Date: Jun 10, 2022
• Online Publication Date: Jul 1, 2022
• Publication Date: Jul 1, 2022
• Deposit Date: Jun 28, 2022
• Publicly Available Date: Jul 4, 2022
• Journal: Scientific Reports
• Electronic ISSN: 2045-2322
• Publisher: Nature Publishing Group
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Article Number: 11189
• DOI: https://doi.org/10.1038/s41598-022-14721-w
• Keywords: Multidisciplinary
• Public URL: https://nottingham-repository.worktribe.com/output/8764835
• Publisher URL: https://www.nature.com/articles/s41598-022-14721-w