Metabolic modeling-based drug repurposing in Glioblastoma.

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.

Integrated Metabolomics and Transcriptomics Using an Optimised Dual Extraction Process to Study Human Brain Cancer Cells and Tissues.

The integration of untargeted metabolomics and transcriptomics from the same population of cells or tissue enhances the confidence in the identified metabolic pathways and understanding of the enzyme-metabolite relationship. Here, we optimised a simultaneous extraction method of metabolites/lipids and RNA from ependymoma cells (BXD-1425). Relative to established RNA (mirVana kit) or metabolite (sequential solvent addition and shaking) single extraction methods, four dual-extraction techniques were evaluated and compared (methanol:water:chloroform ratios): cryomill/mirVana (1:1:2); cryomill-wash/Econospin (5:1:2); rotation/phenol-chloroform (9:10:1); Sequential/mirVana (1:1:3). All methods extracted the same metabolites, yet rotation/phenol-chloroform did not extract lipids. Cryomill/mirVana and sequential/mirVana recovered the highest amounts of RNA, at 70 and 68% of that recovered with mirVana kit alone. sequential/mirVana, involving RNA extraction from the interphase of our established sequential solvent addition and shaking metabolomics-lipidomics extraction method, was the most efficient approach overall. Sequential/mirVana was applied to study a) the biological effect caused by acute serum starvation in BXD-1425 cells and b) primary ependymoma tumour tissue. We found (a) 64 differentially abundant metabolites and 28 differentially expressed metabolic genes, discovering four gene-metabolite interactions, and (b) all metabolites and 62% lipids were above the limit of detection, and RNA yield was sufficient for transcriptomics, in just 10 mg of tissue.

Actinomycin D downregulates Sox2 and improves survival in preclinical models of recurrent glioblastoma.

BACKGROUND: Glioblastoma (GBM) has been extensively researched over the last few decades, yet despite aggressive multimodal treatment, recurrence is inevitable and second-line treatment options are limited. Here, we demonstrate how high-throughput screening (HTS) in multicellular spheroids can generate physiologically relevant patient chemosensitivity data using patient-derived cells in a rapid and cost-effective manner. Our HTS system identified actinomycin D (ACTD) to be highly cytotoxic over a panel of 12 patient-derived glioma stemlike cell (GSC) lines. ACTD is an antineoplastic antibiotic used in the treatment of childhood cancers. Here, we validate ACTD as a potential repurposed therapeutic for GBM in 3-dimensional GSC cultures and patient-derived xenograft models of recurrent glioblastoma. METHODS: Twelve patient-derived GSC lines were screened at 10 µM, as multicellular spheroids, in a 384-well serum-free assay with 133 FDA-approved compounds. GSCs were then treated in vitro with ACTD at established half-maximal inhibitory concentrations (IC50). Downregulation of sex determining region Y-box 2 (Sox2), a stem cell transcription factor, was investigated via western blot and through immunohistological assessment of murine brain tissue. RESULTS: Treatment with ACTD was shown to significantly reduce tumor growth in 2 recurrent GBM patient-derived models and significantly increased survival. ACTD is also shown to specifically downregulate the expression of Sox2 both in vitro and in vivo. CONCLUSION: These findings indicate that, as predicted by our HTS, ACTD could deplete the cancer stem cell population within the tumor mass, ultimately leading to a delay in tumor progression. KEY POINTS: 1. High-throughput chemosensitivity data demonstrated the broad efficacy of actinomycin D, which was validated in 3 preclinical models of glioblastoma.2. Actinomycin D downregulated Sox2 in vitro and in vivo, indicating that this agent could target the stem cell population of GBM tumors.