Application of blood brain barrier models in pre-clinical assessment of glioblastoma- targeting CAR-T based immunotherapies
Bibliographic record
Abstract
Abstract Human blood brain barrier (BBB) models derived from induced pluripotent stem cell (iPSC) have become an important tool for discovery and preclinical evaluation of central nervous system (CNS) targeting cell and gene-based therapies. Chimeric antigen receptor (CAR)-T cell therapy is a revolutionary form of gene-modified cell-based immunotherapy with potential for targeting solid tumors, such as glioblastomas. Crossing the BBB is an important step in the systemic application of CART therapy for the treatment of glioblastomas and other CNS malignancies. In addition, even CART therapies targeting non-CNS antigens such as the well-known CD19-CART therapies, are known to trigger CNS side-effects including brain swelling due to BBB disruption. In this study, we used iPSC-derived brain endothelial-like cell (iBEC) transwell co-culture model to assess BBB extravasation of CART based immunotherapies targeting U87MG human glioblastoma (GBM) cells overexpressing the tumor-specific mutated protein EGFRvIII (U87vIII). Two types of anti-EGFRvIII targeting CART cells with varying tonic signaling profiles (CAR-F263 and CAR-F269) and control Mock T cells were applied on the luminal side of BBB model in vitro. CAR-F263 and CAR-F269 T cells triggered a decrease in transendothelial electrical resistance (TEER) and an increase in permeability. CART cell extravasation and U87vIII cytotoxicity were assessed from the abluminal compartment using flow cytometry and IncuCyte real-time viability imaging, respectively. A significant decrease in U87vIII cell viability was observed over 48 hrs, with the most robust cytotoxicity response observed for the constitutively activated CAR-F263. CAR-F269 T cells showed a similar cytotoxic profile but were both approximately 4-fold less efficient at killing the U87vIII cells compared to CAR-F263, despite similar transmigration rates. Visualization of CART cell extravasation across the BBB was further confirmed using iBEC-on-CHIP models. The described BBB assay was able to discriminate cytotoxic efficacies of the different EGFR-CARs and to provide a measure of potential alterations to BBB integrity. Collectively, we illustrate how BBB models in vitro can be a valuable tool in deciphering the mechanisms of CAR-T–induced BBB disruption, accompanying toxicity and effector function on post-barrier target cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".