Introduction: Despite positive pre-clinical/clinical trials, a major hurdle in the clinical application of bevacizumab, an anti-angiogenic therapy, in glioblastoma is the development of resistance and progression following a transient response period.

Methods: We established a multi-generational glioblastoma xenograft model of acquired bevacizumab resistance through subcutaneous implantation of U87-cells, bevacizumab treatment, and selection and reimplantation of the fastest growing tumor in each generation to new mice. Whole human genome microarray (Illumina) was performed on 3 tumor samples from generations 1, 4 and 9, and bioinformatic analysis of gene expression data was performed in Matlab2014a.

Results: Utilizing published statistical methods; we identified a set of genes exhibiting significant inter-generational variance. Protein-protein interaction(PPI) scores were extracted of String database(v10); subsequent spectral clustering revealed 13 gene subnetworks of closely interrelated genes. Gene set over-representation (GSO) analysis via ConsensusPathDB suggested biologically meaningful subnetworks mediating distinct functions, including inflammation, extracellular-matrix remodeling, cell-cycle, metabolism, and cytoskeletal dynamics. Gene set enrichment analysis revealed significant overexpression across generations of previously identified gene expression signatures of the mesenchymal subtype. Important markers, including putative tumor-stemness marker CD44 and critical epithelial-mesenchymal-transition transcription factors SNAI2, and ZEB2, were upregulated across generations. These results suggest tumor progression under bevacizumab to be accompanied by a gene expression shift towards the mesenchymal subtype, associated with enhanced invasiveness, resistance, and worse outcomes. Our analysis revealed expression changes in angiogenesis-related pathways. Genes identified via GSO suggested a tumor pro-angiogenic response to bevacizumab, composed of converging pathways involving inflammation, hypoxia, ECM remodeling, upregulation of alternative pro-angiogenic pathways and downregulation of anti-angiogenic factors.

Conclusions: Using microarray analysis of a model of bevacizumab resistance in glioblastoma, we found development of resistance to be accompanied by a gene expression shift towards the mesenchymal subtype, as well as activation of alternative pro-angiogenic pathways. These findings shed light on the mechanisms of resistance to anti-angiogenic therapy in glioblastoma.

Patient Care: Using microarray analysis of a model of bevacizumab resistance in glioblastoma, we found resistance to be accompanied by a gene expression shift towards the mesenchymal subtype, as well as activation of alternative pro-angiogenic pathways. These findings shed light on the mechanisms of resistance to anti-angiogenic therapy in glioblastoma, which will serve as an important launching ground for creating adjuvant therapies to prolong the initial response of glioblastoma to anti-angiogneic therapy such as bevacizumab.

Learning Objectives: By the end of this presentation, attendees should have a clear understanding of the design and necessity of models required in order to study the progression of resistance to anti-angiogneic therapy in preclinical glioblastoma xenograft models . Furthermore, they should take away that under the stress of anti-angiogenic therapy with bevacizumab, tumor cells shift towards the mesenchymal subtype associated with enhanced invasiveness, resistance, and poor outcomes.

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