AI Article Synopsis

  • Gliomas, particularly glioblastoma multiforme (GBM), are the most prevalent malignant brain tumors with a median survival of just 15 months due to resistance to treatment.
  • Current treatments include surgery, radiotherapy, and chemotherapy, and so far, only 12 anti-brain tumor chemotherapies have been approved, primarily alkylating agents.
  • Researchers used subtype-specific metabolic models to simulate and predict effective drugs and combinations for gliomas, identifying 33 potential single drugs and 17 combinations, some of which could improve survival rates compared to existing treatments.

Article Abstract

Gliomas are the most common type of malignant brain tumors, with glioblastoma multiforme (GBM) having a median survival of 15 months due to drug resistance and relapse. The treatment of gliomas relies on surgery, radiotherapy and chemotherapy. Only 12 anti-brain tumor chemotherapies (AntiBCs), mostly alkylating agents, have been approved so far. Glioma subtype-specific metabolic models were reconstructed to simulate metabolite exchanges, in silico knockouts and the prediction of drug and drug combinations for all three subtypes. The simulations were confronted with literature, high-throughput screenings (HTSs), xenograft and clinical trial data to validate the workflow and further prioritize the drug candidates. The three subtype models accurately displayed different degrees of dependencies toward glutamine and glutamate. Furthermore, 33 single drugs, mainly antimetabolites and TXNRD1-inhibitors, as well as 17 drug combinations were predicted as potential candidates for gliomas. Half of these drug candidates have been previously tested in HTSs. Half of the tested drug candidates reduce proliferation in cell lines and two-thirds in xenografts. Most combinations were predicted to be efficient for all three glioma types. However, eflornithine/rifamycin and cannabidiol/adapalene were predicted specifically for GBM and low-grade glioma, respectively. Most drug candidates had comparable efficiency in preclinical tests, cerebrospinal fluid bioavailability and mode-of-action to AntiBCs. However, fotemustine and valganciclovir alone and eflornithine and celecoxib in combination with AntiBCs improved the survival compared to AntiBCs in two-arms, phase I/II and higher glioma clinical trials. Our work highlights the potential of metabolic modeling in advancing glioma drug discovery, which accurately predicted metabolic vulnerabilities, repurposable drugs and combinations for the glioma subtypes.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11066901PMC
http://dx.doi.org/10.1093/bib/bbae199DOI Listing

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