Engineered Glioblastoma Tumor Immunity for Personalized Immunotherapy Glioblastoma (GBM) is the most common, malignant primary adult brain tumor and patients succumb to relapse despite aggressive regimens of surgery, chemotherapy and radiotherapy. PD-1 immune checkpoint blockades are considered promising avenues in GBM clinical trials by empowering pre-existing patient immunity against malignant GBM tumors. However, there are no accurate biomarkers to stratify responders and nonresponders and reliable approach to evaluate PD-1 immunotherapy efficacy. Despite promising clinical trial results, a prolonged challenge in GBM immunotherapies is suboptimal responses and frequent resistance to PD-1 immune checkpoint blockades. Traditional patient-derived xenografts, patient explant cultures, and in vitro dissociated cell cultures all fail to predict patient responses and expose therapeutic resistance mechanisms, because they do not accurately reconstitute GBM pathology: tumor-immune-vascular interactions, altered cell-ECM interactions, elevated hypoxic and interstitial fluid pressure. In this study, we surpass such discrepancies by integrating notable hallmarks of the interactive GBM tumor microenvironment in an ex vivo organotypic system consist of diffuse tumor-associated macrophage (TAMs) and T-lymphocyte infiltration and immunosuppression, GBM-associated microvascular angiogenesis, elevated hypoxic and interstitial fluid pressure. Simultaneously, we will monitor in situ inflammatory cytokine secretions of patient immunity during real-time GBM tumor immunosuppression and immunotherapy. The objective of this research is to engineer a novel, microfluidics-based, integrated, tunable ?Glioma-on- a-Chip? organotypic model that recapitulates the in vivo brain tumor microenvironment and immunity for a multiparametric analysis of GBM interactions during PD-1 immunotherapy.
We aim to optimize immune checkpoint blockade efficacy using our ex vivo ?Glioma-on-a-chip? that integrates controllable intercellular interactions (patient-derived GBM and endothelial cell spheroids, TAMs and T cells), tunable matrix mechanics (alterable intercellular and extracellular adhesive signatures, matrix stiffness), controllable extracellular dynamics (on-chip hypoxia and interstitial fluid pressure regulators) and measurable immunosuppressive conditions (on-chip nanoplasmonic biosensing for real-time mapping of patient immune responses under GBM immunosuppression and immunotherapy). Our tunable and multifunctional microsystem allows us to probe the dynamic tumor immunity and unravel a crosstalk mechanism for immunotherapeutic resistance. We propose a new brain cancer immunotherapeutic strategy of ?hacking? the immunosuppressive GBM niche to co-target tumor angiogenesis and immune checkpoints for effectively combating GBM. This may significantly accelerate the pace for identifying immune checkpoint biomarkers, developing patient-specific immunotherapeutic strategies, and optimizing therapeutic effect and long-term management for a broader GBM patient population.

Public Health Relevance

Glioblastoma (GBM) is the most common, deadly primary brain tumor, and newly-diagnosed patients survive less than 15 months despite aggressive surgery, chemotherapy and radiotherapy. With promising trends of adopting PD-1/PD-L1 immunotherapy and smaller, flexible clinical trials for GBM patients, there is an urgency to rapidly identify and test GBM immunotherapy efficacy according to a patient?s tumor immunology, which is currently unavailable for doctors and patients. We therefor develop a patient-specific brain cancer-on-a-chip precision medicine system to quickly assess and personalize immunotherapy treatment with patient-derived tumors to significantly improve GBM patient survival.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21EB025406-02
Application #
9772458
Study Section
Cellular and Molecular Technologies Study Section (CMT)
Program Officer
Rampulla, David
Project Start
2018-09-01
Project End
2021-05-31
Budget Start
2019-06-01
Budget End
2020-05-31
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
New York University
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
041968306
City
New York
State
NY
Country
United States
Zip Code
10012