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Oncotarget. 2017 Jul 4;8(27):44141-44158. doi: 10.18632/oncotarget.17390.

Differentially expressed proteins in glioblastoma multiforme identified with a nanobody-based anti-proteome approach and confirmed by OncoFinder as possible tumor-class predictive biomarker candidates.

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Medical Centre for Molecular Biology, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Centre for Functional Genomics and Bio-Chips, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Department of Neurosurgery, Foundation Rothschild, Paris, France.
Department of Neurosurgery, University Clinical Centre, Ljubljana, Slovenia.
Institute of Histopathology, Charing Cross Hospital, London, United Kingdom.
Cellular and Molecular Immunology, Vrije Universiteit Brussel, Brussels, Belgium.
International Centre for Genetic Engineering and Biotechnology, Trieste, Italy.
First Oncology Research and Advisory Centre, Moscow, Russia.
National Research Center 'Kurchatov Institute', Center of Convergence of Nano-, Bio-, Information and Cognitive Sciences and Technologies, Moscow, Russia.
Centre for Biogerontology and Regenerative Medicine, IC Skolkovo, Moscow, Russia.
Moscow Institute of Physics and Technology, Moscow, Russia.


Glioblastoma multiforme is the most frequent primary malignancy of the central nervous system. Despite remarkable progress towards an understanding of tumor biology, there is no efficient treatment and patient outcome remains poor. Here, we present a unique anti-proteomic approach for selection of nanobodies specific for overexpressed glioblastoma proteins. A phage-displayed nanobody library was enriched in protein extracts from NCH644 and NCH421K glioblastoma cell lines. Differential ELISA screenings revealed seven nanobodies that target the following antigens: the ACTB/NUCL complex, VIM, NAP1L1, TUFM, DPYSL2, CRMP1, and ALYREF. Western blots showed highest protein up-regulation for ALYREF, CRMP1, and VIM. Moreover, bioinformatic analysis with the OncoFinder software against the complete "Cancer Genome Atlas" brain tumor gene expression dataset suggests the involvement of different proteins in the WNT and ATM pathways, and in Aurora B, Sem3A, and E-cadherin signaling. We demonstrate the potential use of NAP1L1, NUCL, CRMP1, ACTB, and VIM for differentiation between glioblastoma and lower grade gliomas, with DPYSL2 as a promising "glioma versus reference" biomarker. A small scale validation study confirmed significant changes in mRNA expression levels of VIM, DPYSL2, ACTB and TRIM28. This work helps to fill the information gap in this field by defining novel differences in biochemical profiles between gliomas and reference samples. Thus, selected genes can be used to distinguish glioblastoma from lower grade gliomas, and from reference samples. These findings should be valuable for glioblastoma patients once they are validated on a larger sample size.


OncoFinder; biomarkers; cancer biology; glioblastoma multiforme; nanobodies

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