Proteomics analysis of human oligodendroglioma proteome

Glioma tumor proteomics: clinically useful protein biomarkers and future perspectives

Introduction: Despite being rare cancers, gliomas account for a significant number of cancer-related deaths. Identification and treatment of these tumors at an early stage would greatly improve the therapeutic outcomes. There is an urgent need for diagnostic and prognostic markers, which can identify disease early and discriminate the subtypes of these tumors thereby improving the existing treatment modalities.Areas covered: In this article, we have reviewed published literature on proteomics biomarkers for gliomas and their importance in diagnosis or prognosis. Proteomic studies for the discovery of protein, autoantibody biomarkers, and biological pathway alterations in serum, CSF and tumor biopsies have been discussed in this review.Expert opinion: The rapid development in the field of mass spectrometry and increased sensitivity and reproducibility in assays has led to the identification and quantification of large number of proteins very precisely. Though genomic markers are the prime focus in the classification of gliomas, incorporating protein markers would further improve the existing classification. In this regard, data mining and studies on large cohorts of glioma patients would help in the identification of diagnostic and prognostic markers ultimately translating to the clinics.

Suberoylanilide hydroxamic acid sensitizes neuroblastoma to paclitaxel by inhibiting thioredoxin-related protein 14-mediated autophagy

Paclitaxel is not as effective for neuroblastoma as most of the front‐line chemotherapeutics due to drug resistance. This study explored the regulatory mechanism of paclitaxel‐associated autophagy and potential solutions to paclitaxel resistance in neuroblastoma. The formation of autophagic vesicles was detected by scanning transmission electron microscopy and flow cytometry. The autophagy‐associated proteins were assessed by western blot. Autophagy was induced and the autophagy‐associated proteins LC3‐I, LC3‐II, Beclin 1, and thioredoxin‐related protein 14 (TRP14), were found to be upregulated in neuroblastoma cells that were exposed to paclitaxel. The inhibition of Beclin 1 or TRP14 by siRNA increased the sensitivity of the tumor cells to paclitaxel. In addition, Beclin 1‐mediated autophagy was regulated by TRP14. Furthermore, the TRP14 inhibitor suberoylanilide hydroxamic acid (SAHA) downregulated paclitaxel‐induced autophagy and enhanced the anticancer effects of paclitaxel in normal control cancer cells but not in cells with upregulated Beclin 1 and TRP14 expression. Our findings showed that paclitaxel‐induced autophagy in neuroblastoma cells was regulated by TRP14 and that SAHA could sensitize neuroblastoma cells to paclitaxel by specifically inhibiting TRP14.

Evaluation of non-supervised MALDI mass spectrometry imaging combined with microproteomics for glioma grade III classification

An integrated diagnosis using molecular features is recommended in the 2016 World Health Organization (WHO) classification. Our aim was to explore non-targeted molecular classification using MALDI mass spectrometry imaging (MALDI MSI) associated to microproteomics in order to classify anaplastic glioma by integration of clinical data. We used fresh-frozen tissue sections to perform MALDI MSI of proteins based on their digestion peptides after in-situ trypsin digestion of the tissue sections and matrix deposition by micro-spraying. The generated 70μm spatial resolution image datasets were further processed by individual or global segmentation in order to cluster the tissues according to their molecular protein signature. The clustering gives 3 main distinct groups. Within the tissues the ROIs (regions of interest) defined by these groups were used for microproteomics by micro-extraction of the tryptic peptides after on-tissue enzymatic digestion. More than 2500 proteins including 22 alternative proteins (AltProt) are identified by the Shotgun microproteomics. Statistical analysis on the basis of the label free quantification of the proteins shows a similar classification to the MALDI MSI segmentation into 3 groups. Functional analysis performed on each group reveals sub-networks related to neoplasia for group 1, glioma with inflammation for group 2 and neurogenesis for group 3. This demonstrates the interest on these new non-targeted large molecular data combining both MALDI MSI and microproteomics data, for tumor classification. This analysis provides new insights into grade III glioma organization. This specific information could allow a more accurate classification of the biopsies according to the prognosis and the identification of potential new targeted therapeutic options. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.