4.3 Article

Identification and Functional Characterization of pVHL-Dependent Cell Surface Proteins in Renal Cell Carcinoma

Journal

NEOPLASIA
Volume 14, Issue 6, Pages 535-+

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1596/neo.12130

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Funding

  1. UBS AG
  2. Swiss National Cancer Foundation [3238BO-103145]
  3. Zurich Cancer League
  4. National Center of Competence in Research Neural Plasticity and Repair

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The identification of cell surface accessible biomarkers enabling diagnosis, disease monitoring, and treatment of renal cell carcinoma (RCC) is as challenging as the biology and progression of RCC is unpredictable. A hallmark of most RCC is the loss-of-function of the von Hippel-Lindau (pVHL) protein by mutation of its gene (VHL). Using the cell surface capturing (CSC) technology, we screened and identified cell surface N-glycoproteins in pVHL-negative and positive 786-O cells. One hundred six cell surface N-glycoproteins were identified. Stable isotope labeling with amino acids in cell culture-based quantification of the CSC screen revealed 23 N-glycoproteins whose abundance seemed to change in a pVHL-dependent manner. Targeted validation experiments using transcriptional profiling of primary RCC samples revealed that nine glycoproteins, including CD10 and AXL, could be directly linked to pVHL-mediated transcriptional regulation. Subsequent human tumor tissue analysis of these cell surface candidate markers showed a correlation between epithelial AXL expression and aggressive tumor phenotype, indicating that pVHL-dependent regulation of glycoproteins may influence the biologic behavior of RCC. Functional characterization of the metalloprotease CD10 in cell invasion assays demonstrated a diminished penetrating behavior of pVHL-negative 786-O cells on treatment with the CD10-specific inhibitor thiorphan. Our proteomic surfaceome screening approach in combination with transcriptional profiling and functional validation suggests pVHL-dependent cell surface glycoproteins as potential diagnostic markers for therapeutic targeting and RCC patient monitoring.

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