Toward precision medicine in glioblastoma: the promise and the challenges

Abstract

Integrated sequencing strategies have provided a broader understanding of the genomic landscape and molecular classifications of multiple cancer types and have identified various therapeutic opportunities across cancer subsets. Despite pivotal advances in the characterization of genomic alterations in glioblastoma, targeted agents have shown minimal efficacy in clinical trials to date, and patient survival remains poor. In this review, we highlight potential reasons why targeting single alterations has yielded limited clinical efficacy in glioblastoma, focusing on issues of tumor heterogeneity and pharmacokinetic failure. We outline strategies to address these challenges in applying precision medicine to glioblastoma and the rationale for applying targeted combination therapy approaches that match genomic alterations with compounds accessible to the central nervous system.

Keywords: clinical trial; genomics; glioblastoma; precision medicine; targeted therapy.

Fig. 1.

Potential therapeutic implications of significantly mutated genes identified in the primary glioblastoma TCGA dataset. (A) Pathway representation of frequently altered pathways and selected potential therapeutic agents. (B) Table of frequently mutated genes from TCGA mapped to potential FDA-approved therapeutic agents. (Right) Bar chart of level of evidence for the association between an alteration and the therapeutic implication using the levels of evidence defined in Table 1.

Fig. 2.

Genomic alterations in recurrent glioblastoma tumors. (A) The spectrum of alterations identified within the cohort of recurrent GBM samples was mapped against the subset of frequently altered genes previously identified in primary GBM. Red indicates copy number loss, green is copy number gain, an asterisk (*) Indicates nonsynonymous mutation, where missense mutations are colored blue, nonsense mutations colored purple, and frameshift mutations colored orange. Tan indicates a structural variant. Chromatin remodeling gene alterations are colored gray and include missense, nonsense and splice site mutations. The most dominant molecular subtype for each sample, based on the gene expression classifications of Verhaak et al, is shown. C, classical; M, mesenchymal; N, neural; P, proneural; ind, indeterminant. The bar chart indicates frequency of genomic alteration for each gene within the TCGA primary GBM dataset (white bars) and the recurrent GBM samples presented here (black bars).

Fig. 3.

Potential therapeutically actionable alterations identified in recurrent glioblastoma samples. The strength of evidence for therapeutic association for each alteration is depicted as in Fig. 1B. An asterisk (*) Indicates nonsynonymous mutation. Drug classes mapping to each alteration are shown on the right. Selection of investigational agents was limited to agents currently being tested in clinical trials for glioblastoma.