STEM-17. CHARACTERIZATION OF THE CELL SURFACE PROTEOME IN RECURRENT GLIOBLASTOMA INITIATING CELLS Journal Articles uri icon

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abstract

  • Abstract Glioblastoma (GBM) is the most common and aggressive malignant primary brain tumor in humans, bearing an overwhelmingly poor prognosis and characterized by a diverse cellular phenotype and genetic heterogeneity. Despite multimodal therapy, patients on average experience relapse at 9¬†months and median survival rarely extends beyond 15¬†months. Treatment of human GBM with standard-of-care (SOC) chemo-radiotherapy invariably leads to resistance. Poor patient survival correlates with marker expression of brain tumor-initiating cells (BTICs), which are implicated in therapeutic resistance and may explain tumor relapse. Targeting the cells that drive GBM formation as well as its inevitable and rapid recurrence post-therapy has remained a major challenge, likely due to intra-tumoral heterogeneity. Proteomic profiling constitutes a promising tool to identify novel cancer targets. In this study, we have adopted a non-biased mass spectrometry approach to identify cell surface peptides isolated from patient-derived GBM BTIC lines through a glycocapture approach. We have identified proteins that are differentially expressed in recurrent GBM BTICs compared to primary GBM BTICs. Moreover, we perform comparative proteomics from recurrent GBM BTICs generated from our in vivo mouse-adapted therapy model, which has the distinct advantage of generating recurrent, treatment-refractory GBM. Our surface proteomic profiling thus provides a comprehensive network of signaling molecules selectively enriched in recurrent GBM cells. Identification of cell surface proteins that may drive treatment resistance will contribute greatly to identify novel immunotherapeutic targets for GBM.

authors

  • Seyfrid, Mathieu
  • Chokshi, Chirayu
  • Kuhlmann, Laura
  • Venugopal, Chitra
  • Vora, Parvez
  • Sinha, Ankit
  • Ignatchenko, Vladimir
  • Macklin, Andrew
  • Kislinger, Thomas
  • Singh, Sheila

publication date

  • November 2017