Enhancing CAR T-cell persistence for effective treatment of childhood brain tumours

Background:
Medulloblastomas (MBs) are the most common malignant paediatric brain tumour; group3 MBs account for ~25% of all cases and are associated with the highest rate of metastases and mortality rate. Chimeric Antigen Receptors T-cells (CARTs) have shown promising results using conventional 2nd generation CARTs and locoregional CSF delivery against group3 MBs1; the lead supervisor has been instrumental in generating powerful pre-clinical data for cerebellar tumours2.

Clinical studies in humans have shown IL13RA2 CARTs as a compelling therapeutic target of solid tumours, however as many patients show limited response, the identification of enhanced persistency is a research priority3,4. To evaluate an array of different CART combinations/engineering approaches to enhance persistence, 3-D MB organoid cultures will be used5. This high throughput system (HTS) for CART screening is the latest advancement for cancer therapeutics, using 3-D cell culture models which more closely mimic the in vivo micro-environment but with much higher throughput than possible with animal studies. Organoid models will be made in close collaboration with Dr Taylor (UofT/SickKids, Toronto). Results from this project are critical for direct translation into novel, genetically engineered mouse models of group3 MBs, for the next generation of pre-clinical trials.

Hypothesis:
Organoid model systems will allow for HTS evaluation of CART designs to identify an optimal CART structure for immunotherapy of group3 MBs.

Aims/Objectives:
Aim-1: Formation of human group3 MB spheroid models. Obj-1: Development of 3-D spheroid models for the HTS evaluation of group3 MBs in response to IL13RA2 CARTs.
Aim-2: Development of human IL13RA2 CARTs. Obj-2: Production of 2nd generation CARTs using optimized backbones +/- IL15 signalling domains, and characterisation of optimal functionality.
Aim-3: Introduction of persistence solutions in IL13RA2 CARTs. Obj-3: Engineering of optimal IL13RA2 CARTs with next generation exhaustion resistance interventions.
Aim-4: Characterisation of next generation IL13RA2 CARTs as single agent compounds and combinatorial studies. Obj-4: Functional in vitro characterisation of IL13RA2 CARTs with re-engineered exhaustion solutions as single and combined engineering studies in MB organoid models.

Methods:
Md-1: Production and effective transduction of lentiviruses. Optimizing 3-D cell culture modelling of MB under defined oxygen tensions, including plating densities, viability and proliferation assays, and immunofluorescence.
Md-2: Genetic cloning of ScFv IL13RA2 into differing CART backbones (BB-Z, 28-Z, +/-IL15) for the effective production and transduction of IL13RA2 lentiviruses into human T-cells. Characterisation of CARTs functionality using flow cytometry and ELISAs. HTS analyses of IL13RA2 CARTs with differing backbones and effector:target (E:T) ratios in MB spheroid models (developed in Aim-1).
Md-3: Genetic engineering of the optimal IL13RA2 CART backbone (optimized from Aim-2) with exhaustion resistance solutions, including overexpression of c-Jun/TCF-1/SLAMF6. Molecular approaches such as cDNA cloning, RT-PCRs, viral preps, CRISPR-Cas9 system will be used for engineering purposes.
Md-4: HTS functional characterisation of the next generation IL13RA2 CARTs as single agents with combinations of engineering solutions to define E:T ratios, and as combination studies in MB spheroid models. HTS bioassays such as ELISAs, microarrays, fluorescence and protein assays will be used to determine the optimal next generation IL13RA2 CART.

Timeline:
Year 1: Aims 1 and 2;
Year 2: Aim 2 and 3;
Year 3: Aim 4.

References:
1. Donovan, et al., Nat Med, 2020. https://doi.org/10.1038/s41591-020-0827-2.
2. Vladiou, El-Hamamy, Donovan, et al., Nature, 2019. https://doi.org/10.1038/s41586-019-1158-7.
3. Lynn, et al., Nature, 2019. https://doi.org/10.1038/s41586-019-1805-z.
4. Hurton, et al., PNAS, 2016. https://doi.org/10.1073/pnas.1610544113.
5. Barton, et al., F1000Research, 2019. https://doi.org/10.12688/f1000research.18209.1.