Glioma pathophysiology: insights emerging from proteomics

Abstract

Proteomics is increasingly employed in both neurological and oncological research to provide insight into the molecular basis of disease but rarely has a coherent, novel pathophysiological insight emerged. Gliomas account for >50% of adult primary intracranial tumors, with malignant gliomas (anaplastic astrocytomas and glioblastoma multiforme) being the most common. In glioma, the application of proteomic technology has identified altered protein expression but without consistency of these alterations or their biological significance being established. A systematic review of multiple independent proteomic analyses of glioma has demonstrated alterations of 99 different proteins. Importantly 10 of the 99 proteins found differentially expressed in glioma [PHB, Hsp20, serum albumin, epidermal growth factor receptor (EGFR), EA-15, RhoGDI, APOA1, GFAP, HSP70, PDIA3] were identified in multiple publications. An assessment of protein-protein interactions between these proteins compiled using novel web-based technology, revealed a robust and cohesive network for glioblastoma. The protein network discovered (containing TP53 and RB1 at its core) compliments recent findings in genomic studies of malignant glioma. The novel perspective provided by network analysis indicates that the potential of this technology to explore crucial aspects of glioma pathophysiology can now be realized but only if the conceptual and technical limitations highlighted in this review are addressed.

Figure 1

A. Location on two‐dimensional (2D) gels of proteins putatively altered in glioma. B. The distribution of altered proteins in A mirrors the total identifiable protein distribution on a representative 2D gel of human brain tissue. The 99 proteins found altered in glioma proteomic studies (excluding seven proteins with molecular weights above 100 kDa), plotted on a virtual gel. The y‐axis of the virtual gel A has a logarithmic scale of 10 to 100 kDa and the x‐axis has a linear scale of 3–10 pH units to mimic the pattern of protein migration during 2D gel electrophoresis. The proteins altered in glioma are distributed across the gel in a similar fashion (% of proteins per gel quadrant) to total number of proteins in glioma. A representative 2D gel image of a human glioma specimen showing distribution of all proteins (visualized as spots on the gel) is shown in “B”.

Figure 2

Biological functions of the 99 proteins putatively altered in glioma according to Protein Analysis Through Evolutionary Relationships (PANTHER) classification. A pie chart of the 23 functional groups assigned by PANTHER to categorize the proteins putatively altered in glioma. No clear or specific biological processes are highlighted.

Figure 3

Half of proteins specifically altered in glioblastoma form a coherent network centred on TP53/RB1/PTEN/EGFR. Of the 99 proteins altered in glioma, 58 proteins were reported as altered in glioblastoma. A coherent functional network can be created from 28 of these 58 proteins using Ingenuity Pathway Analysis (IPA). Visual representation of the functional network containing the 28 proteins (in blue) is presented. Each node (blue shape) represents a protein and its association with other proteins, is represented by a line (edge). Nodes have different shapes to represent different molecule types (horizontal diamonds = peptidases, vertical diamonds = enzymes, and circles = “other”; see Ingenuity Systems for detailed node information). Solid lines represent direct interactions between proteins. Direct interactions are defined as those where two proteins make direct physical contact with each other with no intermediate step. Direct interactions may include chemical modifications, for example phosphorylation, but only if there is evidence that the protein can cause the chemical modification directly. The evidence for interactions is obtained from putatively peer‐reviewed publications in “high quality” journals. It should be noted with caution that the evidence (accessible online from IPA) varies markedly in quantity and pertinence for each interaction. This protein–protein interaction network is highly connected with a multitude of direct interactions between proteins altered in glioblastoma.