Glioblastoma (GBM) is the most common and most aggressive primary malignant brain tumor
Approach: AI-informed computational antigen predictions derived from tumor DNA- and RNA-sequencing data (Tumor and matched normal tissues from 24 GBM patients 17 long-term survivors >5 years; 7 with <18-month survival
Standard of care: surgical resection followed by chemoradiation
Key challenge: profound immunosuppression and low tumor mutational burden limit traditional mutation-derived neoantigen discovery and reduce responsiveness to immunotherapy
Hypothesis: computational/AI-predicted, personalized GBM-specific Endogenous retroviral elements (ERVs) and neoantigens can be combined to enable a novel personalized cancer vaccine strategy
Purpose: to demonstrate vaccine design feasibility and in vitro antigen proof-of-concept
