A Micropatterning-Supported High Throughput CAR-T Cell ... · ibidi GmbH, Gräfelfing, Germany +49...
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ibidi GmbH, Gräfelfing, Germany +49 (0) 89 520 4617 - 0 ibidi.com A Micropatterning-Supported High Throughput CAR-T Cell Potency Assay With Single Cell Resolution M. Balles 1 , A.J. Fischbeck 1 , J. Schwarz 1 , D.A. Thyssen 3 , D. W. Drell 3 , E. Noessner 2 , R. Zantl 1 1 ibidi GmbH, Gräfelfing, GERMANY 2 Helmholtz Zentrum München, Immunoanalytics Core Facility & Reserch Group Tissue Control of Immunocytes, GERMANY 3 MetaVi Labs, Austin Texas, USA Background Autologous T cells that express engineered antigen receptors (CAR-T cells) represent a promising new cancer therapy tool. The evaluation of quality, specificity, and killing efficiency (potency) of CAR-T cell populations is crucial for the development of potent and safe patient-specific CAR-T cell therapies. In contrast to classical T cell potency assays (e.g., Chromium-51), live cell imaging allows to analyze T cell/cancer cell interaction in real time with single cell resolution. However, analysis of confluent cell layers is very time-consuming and therefore not possible in high throughput screens. Additionally, variations in cell size and density require fluorescent labeling for automated T cell and cancer cell registration, which might alter the cell behavior. To facilitate high throughput label-free analysis of T cell potency in a live cell imaging setup, we generated arrays of homogenously distributed single cancer cells or spheroids. By combining optical analysis and advanced image processing, we were able to evaluate cytotoxic T cell activity over time on a single cell level, without the use of any labeling. Additionally, using matrix-embedded 3D arrays, physiological T cell migration conditions could be mimicked. Using the micropatterning technology, target cells (cancer cells) are immobilized (adhered/tethered) on pads offering either homogenous single cell, or multi cell/cell aggregate distribution. In contrast to a confluent cell layer, this allows for detailed optical analysis on a single cell level. Multi-cell / sphe- roid array 3D assay system In order to observe T cell/cancer cell interaction, T cells can either be applied in solution (2D assay), or embedded in a more physiological biological 3D matrix (e.g., collagen). RCC-26 cells immobilized on single and multi cell pads. JB4 effector T cells applied in collagen matrix induce apoptotic body formation of cancer cells. Conclusion ● We use micropatterning of adhesion ligands to immobilize adherent cancer cells in a single cell or multi-cell manner. ● We observe T cell/cancer cell interaction (2D and physiologically relevant 3D environment) using live cell imaging without the necessity of fluorescent markers. ● We analyze T cell/cancer cell interaction in high throughput using artificial intelligence-based cell recognition (“occupied position” approach). The Bioinert Principle • Thin polyol hydrogel layer, covalently bound to the ibidi Polymer Coverslip #1.5 Features • Biologically inert—no cell or protein adhesion • Long-term stable • Ready-to-use • Highest optical quality for imaging Culture medium Bioinert surface (0.2 μm) Bioinert surface ibidi Polymer Coverslip (180 μm) Functionalization • Specific cell adhesion/tethering for weeks. • Unspecific cell and molecule immobilization • Custom-specific adhesion via click chemistry Optics • Very low autofluorescence • No visibility of µ-Patterns in brightfield • Optional µ-Pattern fluorescence Confluent cell layer Micropatterning on the Bioinert Surface Defined Cancer Cell Arrays on a Micropattern T Cell Potency Assays in 2D and 3D Bioinert surface Ligand pattern Crosslinker pattern Site-directed, covalent crosslinker binding Highly specific, covalent coupling Ligand Cell adhesion (e.g., ECM) or tet- hering (e.g., spec. AB) Ligand RCC-26 cells immobilized on single cell pads. JB4 effector T cells applied in suspension induce apoptotic body formation of cancer cells. 2D assay system Single cell array Multi-cell / sphe- roid array T cell Single cancer cells Confluent cancer cell layer ECM network (e.g., collagen) Single cell array Immobilization pattern Single cell array RCC-26 cells Spheroid array NIH3T3 cells Multi-cell array RCC-26 cells Single Cancer Cell Arrays for High Throughput T Cell Killing Efficiency Analysis Arrays of single cancer cells were obtained by seeding RCC-26 cancer cells on small adhesive micropads (red). Probabilities were highest for capturing single cells on each adhesion structure (Graph). 0 1 2 3 4 0 10 20 30 40 50 Probability [%] Number of cells on pad Characteristic kinetic killing profiles of JB4 T cells applied in suspension and RCC-26 cancer cells distributed on a single cell array. 0 10 20 30 0.0 0.5 1.0 Time [h] Cancer cell occupied pads [%] 0.10 x 10 6 T cells/mL 0.15 x 10 6 T cells/mL 0.20 x 10 6 T cells/mL Machine Learning-Based Detection of Cancer Cells on Adhesion Grid Arrays The array information helps to keep the cell number and positions constant thereby facilitating the analysis. The AI-supported algorithm determines over time whether a cancer cell is attached to a single adhesive pad or not. Like this, the T cell killing efficiency can be calculated. 1) Automated grid detection 2) Automated analysis of grid occupancy Cy3 t=1 t=end cancer cell on pad no cancer cell on pad T cell BF High Throughput T Cell Killing Efficiency Analysis on a Single Cancer Cell Array t=0 min t=18 min t=27 min t=36 min t=102 min t=249 min ● We aim at applying the micropatterning approach to soluble cancer cells (e.g., B cells via tethering antibodies). ● We aim at analyzing T cell/cancer cell interaction in detail (“T cell tracking”) using higher magnification objectives. ● ACAS (MetaVi Labs and ibidi) Chemotaxis analysis can be used “on top” of cell recognition in order to identify “secondary T cell effects”. Outlook RCC-26 tumor cell (red) attacked by a JB4 T cell (green).
Transcript of A Micropatterning-Supported High Throughput CAR-T Cell ... · ibidi GmbH, Gräfelfing, Germany +49...
ibidi GmbH, Gräfelfing, Germany +49 (0) 89 520 4617 - 0 ibidi.com
A Micropatterning-Supported High Throughput CAR-T CellPotency Assay With Single Cell ResolutionM. Balles1, A.J. Fischbeck1, J. Schwarz1, D.A. Thyssen3, D. W. Drell3, E. Noessner2, R. Zantl11 ibidi GmbH, Gräfelfing, GERMANY 2 Helmholtz Zentrum München, Immunoanalytics Core Facility & Reserch Group Tissue Control of Immunocytes, GERMANY 3 MetaVi Labs, Austin Texas, USA
BackgroundAutologous T cells that express engineered antigen receptors (CAR-T cells) represent a promising new cancer therapy tool. The evaluation of quality, specificity, and killing efficiency (potency) of CAR-T cell populations is crucial for the development of potent and safe patient-specific CAR-T cell therapies.
In contrast to classical T cell potency assays (e.g., Chromium-51), live cell imaging allows to analyze T cell/cancer cell interaction in real time with single cell resolution. However, analysis of confluent cell layers is very time-consuming and therefore not possible in high throughput screens. Additionally, variations in cell size and density require fluorescent labeling for automated T cell and cancer cell registration, which might alter the cell behavior.
To facilitate high throughput label-free analysis of T cell potency in a live cell imaging setup, we generated arrays of homogenously distributed single cancer cells or spheroids. By combining optical analysis and advanced image processing, we were able to evaluate cytotoxic T cell activity over time on a single cell level, without the use of any labeling. Additionally, using matrix-embedded 3D arrays, physiological T cell migration conditions could be mimicked.
Using the micropatterning technology, target cells (cancer cells) are immobilized (adhered/tethered) on pads offering either homogenous single cell, or multi cell/cell aggregate distribution.In contrast to a confluent cell layer, this allows for detailed optical analysis on a single cell level.
Multi-cell / sphe-roid array
3D a
ssay
sys
tem
In order to observe T cell/cancer cell interaction, T cells can either be applied in solution (2D assay), or embedded in a more physiological biological 3D matrix (e.g., collagen).
RCC-26 cells immobilized on single and multi cell pads. JB4 effector T cells applied in collagen matrix induce apoptotic body formation of cancer cells.
Conclusion● We use micropatterning of adhesion ligands to
immobilize adherent cancer cells in a single cell or multi-cell manner.
● We observe T cell/cancer cell interaction (2D and physiologically relevant 3D environment) using live cell imaging without the necessity of fluorescent markers.
● We analyze T cell/cancer cell interaction in high throughput using artificial intelligence-based cell recognition (“occupied position” approach).
The Bioinert Principle• Thin polyol hydrogel layer, covalently bound to the
ibidi Polymer Coverslip #1.5
Features• Biologically inert—no cell or protein adhesion• Long-term stable• Ready-to-use• Highest optical quality for imaging
CulturemediumBioinert
surface(0.2 µm)
Bioinertsurface
ibidi Polymer Coverslip (180 µm)
Functionalization• Specific cell adhesion/tethering for weeks.• Unspecific cell and molecule immobilization• Custom-specific adhesion via click chemistry
Optics• Very low autofluorescence• No visibility of µ-Patterns in brightfield• Optional µ-Pattern fluorescence
Confluent cell layer
Micropatterning on the Bioinert Surface
Defined Cancer Cell Arrays on a Micropattern
T Cell Potency Assays in 2D and 3D
Bioinert surface
Ligand pattern
Crosslinker pattern
Site-directed, covalentcrosslinker binding
Highly specific,covalent coupling
Ligand
Cell adhesion (e.g., ECM) or tet-hering (e.g., spec. AB) Ligand
RCC-26 cells immobilized on single cell pads. JB4 effector T cells applied in suspension induce apoptotic body formation of cancer cells.
2D a
ssay
sys
tem
Single cell array Multi-cell / sphe-roid array T cell
Single cancer cells
Confluent cancer cell layer
ECM network (e.g., collagen)
Single cell array
Imm
obili
zatio
n pa
ttern
Single cell arrayRCC-26 cells
Spheroid arrayNIH3T3 cells
Multi-cell arrayRCC-26 cells
Single Cancer Cell Arrays for High Throughput T Cell Killing Efficiency Analysis
Arrays of single cancer cells were obtained by seeding RCC-26 cancer cells on small adhesive micropads (red). Probabilities were highest for capturing single cells on each adhesion structure (Graph).
0 1 2 3 40
10
20
30
40
50
Prob
abilit
y [%
]
Number of cells on pad
Characteristic kinetic killing profiles of JB4 T cells applied in suspension and RCC-26 cancer cells distributed on a single cell array.
0 10 20 300.0
0.5
1.0
Time [h]
Can
cer c
ell o
ccup
ied
pads
[%]
0.10 x 106 T cells/mL0.15 x 106 T cells/mL0.20 x 106 T cells/mL
Machine Learning-Based Detection of Cancer Cells on Adhesion Grid Arrays
The array information helps to keep the cell number and positions constant thereby facilitating the analysis. The AI-supported algorithm determines over time whether a cancer cell is attached to a single adhesive pad or not. Like this, the T cell killing efficiency can be calculated.
1) Automated grid detection 2) Automated analysis of grid occupancy
Cy3 t=1 t=end
cancer cell on pad
no cancer cell on pad
T cell
BF
High Throughput T Cell Killing Efficiency Analysis on a Single Cancer Cell Array
t=0 min t=18 min t=27 min
t=36 min t=102 min t=249 min
● We aim at applying the micropatterning approach to soluble cancer cells (e.g., B cells via tethering antibodies).
● We aim at analyzing T cell/cancer cell interaction in detail (“T cell tracking”) using higher magnification objectives.
● ACAS (MetaVi Labs and ibidi) Chemotaxis analysis can be used “on top” of cell recognition in order to identify “secondary T cell effects”.
Outlook
RCC-26 tumor cell (red) attacked by a JB4 T cell (green).
