Current Challenges and Opportunities in Treating Glioblastoma

Abstract

Glioblastoma multiforme (GBM), the most common and aggressive primary brain tumor, has a high mortality rate despite extensive efforts to develop new treatments. GBM exhibits both intra- and intertumor heterogeneity, lending to resistance and eventual tumor recurrence. Large-scale genomic and proteomic analysis of GBM tumors has uncovered potential drug targets. Effective and "druggable" targets must be validated to embark on a robust medicinal chemistry campaign culminating in the discovery of clinical candidates. Here, we review recent developments in GBM drug discovery and delivery. To identify GBM drug targets, we performed extensive bioinformatics analysis using data from The Cancer Genome Atlas project. We discovered 20 genes, BOC, CLEC4GP1, ELOVL6, EREG, ESR2, FDCSP, FURIN, FUT8-AS1, GZMB, IRX3, LITAF, NDEL1, NKX3-1, PODNL1, PTPRN, QSOX1, SEMA4F, TH, VEGFC, and C20orf166AS1 that are overexpressed in a subpopulation of GBM patients and correlate with poor survival outcomes. Importantly, nine of these genes exhibit higher expression in GBM versus low-grade glioma and may be involved in disease progression. In this review, we discuss these proteins in the context of GBM disease progression. We also conducted computational multi-parameter optimization to assess the blood-brain barrier (BBB) permeability of small molecules in clinical trials for GBM treatment. Drug delivery in the context of GBM is particularly challenging because the BBB hinders small molecule transport. Therefore, we discuss novel drug delivery methods, including nanoparticles and prodrugs. Given the aggressive nature of GBM and the complexity of targeting the central nervous system, effective treatment options are a major unmet medical need. Identification and validation of biomarkers and drug targets associated with GBM disease progression present an exciting opportunity to improve treatment of this devastating disease.

Graphical abstract

Fig. 1.

Classification of brain tumors as reported from the Central Brain Tumor Registry of the United States (Ostrom et al., 2016). Numbers in parentheses indicates incidence or cases per 100,000 individuals and are age-adjusted to the 2000 United States standard population.

Fig. 2.

Common characteristics and diagnostic markers of World Health Organization grade IV glioma compared with lower-grade gliomas. Object images obtained from Servier Medical Art by Servier.

Fig. 3.

Canonical gliomagenesis mediators EGFR, P53, and retinoblastoma protein (RB1) are important for cancer signaling. EGFR is amplified or mutated to the constitutively active EGFRvIII and propagates kinase signaling cascades to promote proliferation, invasion, and angiogenesis. P53 is a tumor suppressor that is mutated in GBM, allowing B-cell lymphoma 2 (BCL2) to inhibit apoptosis. RB is another tumor suppressor that, when inactivated, releases E2F transcription factor 1 (E2F1) to activate cell cycling and growth. Percentages of aberrations of commonly mutated genes (in yellow) are reported, determined from TCGA analysis of patient samples (Brennan et al., 2013).

Fig. 4.

Signaling pathways involving membrane proteins upregulated in GBM as determined by LC-MS/MS and iTRAQ. Results are from proteomic analysis of human GBM tumors with Ingenuity Pathway Analysis software (Polisetty et al., 2012). Representative genes from each category are shown.

Fig. 5.

Twenty genes were identified as associated with reduced survivability in the TCGA GBM patient cohort profiled with RNASeq expression data. Patients were stratified by high and low gene expression based on one of five expression percentile thresholds. Kaplan-Meier survival plots are shown with patients having increased expression in red and all other GBM patients shown in green. Nonadjusted P values generated using the log-rank test are shown. All P values shown survived multiple testing corrections (qValue ≤ 0.1) across all 5 percentile thresholds and 20,531 genes.

Fig. 6.

(A) Hierarchical clustering was performed to identify groups of patients with similar RNASeq expression of 20 genes associated with reduced survivability in the TCGA GBM patient cohort. (B) Patients stratified using clustering dendrogram assignment into high and low expression groups showed significant differences in survival. Heatmap z-scores were calculated per gene. Agglomerative hierarchical clustering with complete linkage was performed using Euclidean and Pearson correlation distance metrics on rows and columns, respectively.

Fig. 7.

Expression of 20 genes significantly associated with reduced survivability in GBM is shown across 33 TCGA diseases. Gene expression from each patient sample was converted to a z-score, and z-scores were recalculated across all diseases for each gene to show relative expression. Regions of the heatmap are circled to highlight genes with consistent higher expression (10th percentile >0.5) and previously published support for relevance to disease progression (cyan) or high expression without previously published support for disease progression (purple). Diseases are ranked by decreasing average expression and ribbon on the right is colored to indicate average expression per patient sample.

Fig. 8.

The blood-brain barrier protects the brain from foreign material with a layer of endothelial cells bound by adherens junctions [i.e., vascular endothelial (VE)-cadherin] and tight junctions [i.e., junction adhesion molecules (JAMs), endothelial cell adhesion molecule (ESAM), claudins, and occludins].

Fig. 9.

CNS MPO Version 2 scores were calculated for 73 of the GBM drug candidates listed in Table 1. Plots are shown for scores calculated for total CNS MPO score (A), molecular weight distribution (B), LogP value distribution (C), polar surface area value distribution (D), hydrogen bond donor total distribution (E), and pK_a value (of the most basic center) distribution (F).

Fig. 10.

Three drug delivery strategies for crossing the blood-brain barrier. In receptor-mediated endocytosis, a drug is conjugated to a ligand that binds to a receptor on the blood-brain barrier to trigger endocytosis. Small lipophilic compounds can be taken up by passive diffusion. Carrier-mediated transport is driven by two major protein families, the solute carrier superfamily and ATP binding cassette transporters, and these transporters can be hijacked for drug delivery.