Applied Cancer Immunogenomics: Leveraging Neoantigen Discovery in Glioblastoma

Abstract

Glioblastoma (GBM) remains a significant cause of cancer-related mortality in pediatric and adult patients with limited treatment options. Immunotherapy represents a promising new therapeutic approach in many solid and hematologic malignancies, including GBM, although only a subset of patients responds clinically. Thus, current efforts are focused on identifying patients most likely to benefit from immune-based therapies. The cancer immunogenomics approach identifies candidate neoantigens from genomics information and represents a potentially exciting new space in precision neuro-oncology. In this review, we discuss the role of neoantigens in GBM both as predictive biomarkers and as targets of immunotherapy.

Figure 1

Proposed schema of workflow to incorporate neoantigen burden into treatment decision for patients with GBM. From left to right, tumor tissue following resection will undergo DNA exome and RNA sequencing to quantify the number of expressed, nonsynonymous mutations. Patients with tumors containing high mutational burdens, and thus high neoantigenic potential, would preferentially be treated with checkpoint blockade therapy. Conversely, tumors with reduced mutational load would be targeted with a personalized vaccine with or without checkpoint modulating agents against patient-specific high affinity neoantigen candidates identified using the cancer immunogenomics pipeline.