Glioblastoma (GBM) is an extremely aggressive and incurable primary tumor of the brain. GBM is characterized by interpatient and intratumoral heterogeneity, making this cancer particularly resistant to therapy and likely to recur. Mapping the complex dynamics that underpin the development and evolution of gliomas with human-based in vitro models is difficult. This study aimed to generate 3D glioma patient-derived tumor constructs (PTCs) using a clinically relevant, Matrigel-free, hyaluronic acid system, evaluate their suitability in drug screening assays, and determine the stability of their genetic profiles compared to originating tumors. In this study, we utilized a synthetically modified hyaluronic acid and gelatin hydrogel system to generate tumor constructs containing cells from clinical glioma biospecimens. PTCs were characterized phenotypically, after which they were deployed in chemotherapy drug screens using temozolomide (TMZ) and a P53 activator compound. Drug responses of these 3D cultures were compared with 2D cultures, as well as PTCs that were generated after passaging in 2D. RNA sequencing was used to evaluate genetic parity between PTCs or 2D cultures with originating tumor tissues, using The Cancer Genome Atlas (TCGA) GBM subpopulations for subcategorizing. PTCs were created successfully from five World Health Organization (WHO) grade 4, two grade 3, and two grade 2 gliomas. PTCs were maintained with high viability. Chemotherapy drug screens demonstrated that expected TMZ responses were observed for Isocitrate dehydrogenase (IDH) mutant diffuse gliomas while drug response was variable for IDH wildtype GBM PTCs. PTCs demonstrated stable drug response over time, while 2D passaging resulted in significant shifts in drug sensitivity. RNA sequencing revealed maintenance of subpopulation signatures for PTCs which clustered with their originating patient tumor tissue. In contrast, 2D cultures largely clustered together regardless of the patient. Our PTC approach utilizes a defined hydrogel biomaterial system that maintains the genotypic and drug response characteristics of patient tumors making this an ideal ex vivo model for translational applications.
Sivakumar et al. (Tue,) studied this question.