Abstract

Abstract BACKGROUND The standard therapy for glioblastoma patients is tumor resection followed by radiotherapy and temozolomide chemotherapy. Although glioblastoma has been extensively molecularly profiled along with other cancers, this knowledge has not yet been translated into improved survival outcomes. We used a bioinformatics approach to identify potential novel therapeutic strategies for glioblastoma. OBJECTIVES: Comprehensive online datasets which have assessed up to 1376 cancer cell lines in multiple ways were interrogated to identify potential drug candidates for glioblastoma. METHODS Datasets included were from the cancer cell line encyclopedia (mRNA expression), the Achilles project (cell viability following Crispr-Cas9 knockout) and PRISM (drug treatment). A t-test comparing cell viability of glioblastoma cell lines versus other cancers was used to identify potential drug candidates, followed by the use of multiple statistical tools to investigate potential mechanism of action and status of biomarkers. RESULTS Fluvastatin and pitavastatin produced the most significant effects in glioblastoma cell lines. The anti-cancer properties of statins have previously been attributed to the inhibition of HMG-Coa reductase. Here, we found their effects correlated with erastin, an enhancer of ferroptosis and with gene knockout of UBIAD1, which participates in non-mitochondrial ubiquinone synthesis. These effects were both found in glioblastoma cells and other cancers with a mesenchymal-like phenotype. CONCLUSION Statins appeared to be especially effective against glioblastoma lines and the effect could be linked to ferroptosis and inhibition of UBIAD1. In vitro validation of this finding is ongoing.

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