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.

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.

TRIM28 and ß-actin identified via nanobody-based reverse proteomics approach as possible human glioblastoma biomarkers.

Malignant gliomas are among the rarest brain tumours, and they have the worst prognosis. Grade IV astrocytoma, known as glioblastoma multiforme (GBM), is a highly lethal disease where the standard therapies of surgery, followed by radiation and chemotherapy, cannot significantly prolong the life expectancy of the patients. Tumour recurrence shows more aggressive form compared to the primary tumour, and results in patient survival from 12 to 15 months only. Although still controversial, the cancer stem cell hypothesis postulates that cancer stem cells are responsible for early relapse of the disease after surgical intervention due to their high resistance to therapy. Alternative strategies for GBM therapy are thus urgently needed. Nanobodies are single-domain antigen-binding fragments of heavy-chain antibodies, and together with classical antibodies, they are part of the camelid immune system. Nanobodies are small and stable, and they share a high degree of sequence identity to the human heavy chain variable domain, and these characteristics offer them advantages over classical antibodies or antibody fragments. We first immunised an alpaca with a human GBM stem-like cell line prepared from primary GBM cultures. Next, a nanobody library was constructed in a phage-display vector. Using nanobody phage-display technology, we selected specific GBM stem-like cell binders through a number of affinity selections, using whole cell protein extracts and membrane protein-enriched extracts from eight different GBM patients, and membrane protein-enriched extracts from two established GBM stem-like cell lines (NCH644 and NCH421K cells). After the enrichment, periplasmic extract ELISA was used to screen for specific clones. These nanobody clones were recloned into the pHEN6 vector, expressed in Escherichia coli WK6, and purified using immobilised metal affinity chromatography and size-exclusion chromatography. Specific nanobody:antigen pairs were obtained and mass spectrometry analysis revealed two proteins, TRIM28 and ß-actin, that were up-regulated in the GBM stem-like cells compared to the controls.