516 Functional Impact of Intratumoral Heterogeneity in Therapeutic Vulnerabilities Across Enhancing and Non-Enhancing Tumor Components of Glioblastoma: A Paradigm-Shifting Personalized Medicine Approach

Abstract

INTRODUCTION: Glioblastoma (GBM) remains a fatal disease without effective targeted therapeutics. This is largely attributed to molecular and spatial heterogeneity and absence of clinically applicable models to guide patient care. Moreover, as standard surgical resection is aimed at contrast-enhancing (CE) tumor, the molecular landscape and treatment response of the remaining non-contrast enhancing (nCE) component remains unknown despite its active role in tumor progression and local recurrence. METHODS: Freshly resected tumor tissue was subjected to the generation of 3D tumor models (brain tumor initiating-enriched cell lines [BTICs] and microcancers). To identify the best treatment strategy, a panel of 25 brain penetrant drugs (alone/ in combination) targeting GBM drivers (i.e. RTK/Ras/PI3K, RB, p53/apoptosis, DNA damage repair, transcription addiction) was developed and used to test therapeutic vulnerabilities. Comprehensive sequencing including genome and transcriptome profiling and pathway analysis from these different tumor regions is ongoing. RESULTS: Thirty-two patients have been prospectively enrolled, with generation of 38 microcancers and 17 BTICs, and drug screening completed in 26 patients. For a subset, four tumor regions (two CE and two nCE) were collected under neuronavigation. Among 25 drugs tested, 5 ± 3 (mean ± SD) treatment strategies showed strong (≥70%) growth inhibition at Cmax, with inter-tumor drug response heterogeneity ranging from 18.9% to 5.4% (p = 0.02). Intra-tumor drug response heterogeneity varied from high (5/25 drugs tested) to low (0/25, p < 0.05) and was independent of enhancement status or spatial proximity. CONCLUSIONS: This is the first study to systematically assess treatment response from both CE and nCE patient-derived GBM models. By interrogating molecular landscapes and vulnerability profiles, we will be able to personalize and prioritize effective targeted interventions for GBM treatment.