Immune Cell-Mediated Killing

T Cells

​The differences in clinical efficacy of immunotherapy between non-solid and solid tumours are multifactorial. These include physical restrictions, such as the limited accessibility of cancer cells, intrinsic properties of the tumor cells that influence their immunogenicity and sensitivity to immune effectors, and the presence of inhibitory metabolic processes and soluble inhibitors in the parenchyma surrounding cancer cells, all of which can adversely affect T cell immunotherapy efficacy.

Preclinical testing to evaluate the efficacy of the different modifications introduced in engineered T cells for cancer immunotherapy still relies on expensive animal models that are not fully able to recapitulate human pathology; additionally, tests in animal models lack the flexibility to control individual parameters in distinct anatomical locations. In vitro testing offers an alternative, but 2D in vitro models cannot mimic the spatiotemporal dynamics encountered by T cells targeting cancer cells within solid parenchyma. In addition, such testing methodologies have neglected the obvious 3D morphology of solid tumors and the tumor cell clusters necessary for metastasis formation.

An easily reproducible and simple system was recently developed (1) to test whether TCR-engineered T cells can overcome the physical and metabolic barriers present in the tumor microenvironment. AIM chips can be used to quantify the killing efficiency of engineered T-cells against dispersed or aggregated cancer cells.  interactions between cancer cells and T cells take place in a realistic 3D space. Conditions can be precisely regulated and the ability of distinct preparations of engineered T cells to reach and kill cancer cells can be tracked over time.
T Cell Therapy
T Cells Single Cells

T Cells Single Cells

Dispersed GFP-expressing HepG2-Env liver cancer cells (green) in 3D collagen matrix were targeted by engineered T-cells (blue) and killed specifically (red, labelled with DRAQ7). Killing efficiency can be calculated by dividing the number of live cancer cells at the endpoint by the number of live cancer cells at time 0. 

T Cells Organiods

T Cells Organiods

HepG2-Env aggregates embedded in a 3D collagen matrix and exposed to engineered T-cells resulted in a quantifiable increase in killed cells (red). Quantifying live & dead cells in cancer aggregates is usually less accurate as the cancer cells clump together. Therefore, the % of cell death is estimated based on the volumes of DRAQ7-positive cells and GFP-positive cells. The killing efficiency of T cells can be obtained by comparing the % of cell death before the addition of T cells with that after 15 h incubation. The greater the difference in % of cell death between the two time points, the more potent the T cells. 


This protocol is based on work by Pavesi et al in reference (1). We thank Dr. Andrea Pavesi for his contribution to the preparation of this document.

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  1. *A 3D microfluidic model for preclinical evaluation of TCR-engineered T cells against solid tumors. Pavesi et al JCI Insight. 2017;2(12):e89762
  2. “Characterizing the Role of Monocytes in T Cell Cancer Immunotherapy Using a 3D Microfluidic Model”.  Lee SWL, Adriani G, Ceccarello E, Pavesi A, Tan AT, Bertoletti A, Kamm RD and Wong SC (2018) Front. Immunol. 9:416. doi: 10.3389/ mmu.2018.00416
  3. *Molecular recalibration of PD-1+ antigen-specific T cells from blood and liver.  Otano I, Escors D, Schurich A, Singh H, Robertson F, Davidson BR…  Maini MK. Molecular Therapy (2018), doi: 10.1016/j.ymthe.2018.08.013.​
  4. *Suppression of STING associated with LKB1 loss in KRAS-driven lung cancer. Kitajima SIvanova EGuo SYoshida RCampisi M… Barbie DA. Cancer Discov. Epub 8 Oct 2018 DOI: 10.1158/2159-8290.CD-18-0689

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