Innovative Tools for Cancer Immunotherapies
eBook
Published: April 4, 2023
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Researchers must ensure reproducibility, efficacy and potency of cancer immunotherapy treatments before these reach the clinic.
While different methods exist to evaluate the efficacy of immunotherapy products, more efficient and robust in vitro assays are still required to ensure their safety and consistency.
This eBook highlights innovative tools to evaluate the potency of immunotherapies in vitro. It features an assay that is objective and easy to perform (non-invasive and stain-free), providing quantitative kinetic results under physiologically relevant conditions.
Download this eBook to learn more about:
- The principles of the real-time cell analysis assay
- Evaluating the potency of different types of immunotherapies
- Analyzing liquid tumor targets
Cancer Immunotherapy
Agilent xCELLigence RTCA handbook
2
Table of contents
What is cancer immunotherapy? 4
How can the immune system be harnessed to target tumors? 4
xCELLigence real-time cell analysis 6
Diverse cancer immunotherapy applications 6
How does the xCELLigence real-time cell analysis assay work? 7
Measuring cellular impedance with E-Plates 7
Real-time cellular impedance traces explained 8
xCELLigence instruments for immunotherapy 9
Antibody-dependent cell-mediated cytolysis (ADCC) 11
Using xCELLigence to study antibody-dependent cell-mediated
cytolysis (ADCC) 11
Selected publications 13
Bispecific T cell engagers (BiTEs) and bispecific antibodies 15
Using xCELLigence to study BiTEs 15
Selected publications 17
Checkpoint Inhibitors 19
Using xCELLigence to study checkpoint inhibitors 19
Selected publications 21
Combination therapy 23
Using xCELLigence to study combination therapies 23
Selected publications 24
Genetically engineered T cell-mediated cell killing 26
Using xCELLigence to study genetically engineered T cells 26
Selected publications 28
Macrophage-mediated phagocytosis 32
Using xCELLigence to study macrophage-mediated phagocytosis 32
Selected publications 33
NK cell-mediated cytolysis 35
Using xCELLigence to study NK cell-mediated cytolysis 36
Selected publications 38
3
Oncolytic viruses 40
Selected publications 41
T Cell-mediated cytolysis 44
Selected publications 45
Liquid tumor killing assays 48
Selected publications 50
4
What is cancer immunotherapy?
Cancer immunotherapy consists of multiple approaches that harness and
enhance the innate powers of the immune system to fight the disease. It is
currently viewed as one of the most promising forms of cancer treatment with
12 cancer immunotherapies approved in recent years. In 2018, the Nobel Prize in
Medicine was awarded to two researchers in the field.
Cancer immunotherapies can be divided into four major categories:
– Cytokines/immunomodulation agents
– Monoclonal antibodies
– Cell‑based therapies
– Oncolytic viruses
Though monoclonal antibodies currently represent the largest class of
commercialized cancer immunotherapies, cell‑based therapies are rapidly making
headway. This class of personalized therapies involves collecting immune cells
from an individual, engineering them to recognize and kill cancer cells, before
culturing, and reintroducing them into the same individual.
Immune cell-mediated tumor cell killing can involve components of both the
innate and adaptive immune systems (Figure 1), including:
– Natural killer (NK) cells
– Cytotoxic T cells (MHC-dependent)
– Antibodies secreted by B lymphocytes
– Engineered antibodies such as bispecific antibodies and bispecific T cell
engagers (BiTEs)
– Genetically engineered T cells targeting specific tumor antigens (for example,
CAR-T, MHC-independent)
– Macrophage-mediated phagocytosis
How can the immune
system be harnessed to
target tumors?
5
Figure 1. Various immunotherapy tumor-targeting schemes.
The need for a novel cancer immunotherapy assay
The most significant challenge faced by cancer immunotherapy researchers
is the inability to predict treatment efficacy and response. While many
methods have been developed to screen and evaluate the efficacy of immune
cell‑mediated killing, there is a need for a more robust in vitro assay to accurately
predict the in vivo behavior of therapies. The ideal assay should be objective,
simple to perform, provide quantitative kinetic results, and mimic physiologically
relevant conditions. Other established methods, such as flow cytometry, can then
provide extra data regarding immune cell phenotype, activation, and function.
The most commonly used method for measuring immune cell‑mediated killing
is the release assay, where effector cell‑mediated disruption of the target cell
membrane results in leakage of its cytoplasmic contents into the culture medium.
Endogenous biomolecules (such as lactate dehydrogenase) or previously added
exogenous labels (such as the radioisotope 51Cr) that leak into the media are
then measured as an indirect readout of the damage caused by effector cells.
Alternative endpoint methods include ELISA‑based granzyme measurement and
morphometric analyses by microscopy. While the data provided by these assays
help piece together an understanding of different facets of immune cell‑mediated
killing, it is important to note that the parameters being reported often do not
correlate with target cell killing efficacy in vivo.
Activated
T cell
NK-cell
Macrophage
Target
cancer cell
Oncolytic
virus
Antibody-dependent
(ADCC) BiTE/bispecific
antibody
Checkpoint
inhibitor
CAR-T cells
6
xCELLigence real-time cell analysis
Agilent xCELLigence real-time cell analysis (RTCA) instruments allow users to:
– Measure quantitative, real-time kinetics with exquisite sensitivity
– Real-time cytolysis of target cells are measured at low
effector-to-target ratios
– Easily study diverse effector cells and molecules
– Measure cytotoxic effects of CAR-T cells or monoclonal antibodies,
optimize potency of combination therapies, measure off-target effects, and
much more
– Conduct experiments in label-free conditions
– Measure cytotoxicity with no 51Cr, luciferase, or dyes
Thousands of xCELLigence instruments have been placed globally, resulting in
more than 4,500 xCELLigence publications in peer‑reviewed journals.
xCELLigence RTCA technology is being used extensively for cancer research in
applications that include, but are not limited to:
– Compound‑mediated cytotoxicity
– Cell‑mediated cytotoxicity
– T cells
– NK cells
– CAR T cells
– Macrophages
– Antibody‑dependent cell‑mediated cytotoxicity (ADCC)
– Bispecific antibodies
– Bispecific T cell engagers (BiTEs)
– Checkpoint inhibitors
– Combination therapy
– Tumor microenvironment (cell–cell interactions)
– Cell adhesion/spreading
– Receptor activation
– Oncolytic viruses
– Autophagy
– Solid tumor killing assays
– Liquid tumor killing assays
– Immune cell activation
– Apoptosis
– Inflammation
Diverse cancer
immunotherapy applications
7
xCELLigence RTCA instruments use gold biosensors embedded in the bottom
of specialized microplate wells (Agilent E‑Plates) to noninvasively monitor cell
status including cell number, cell size, and cell‑substrate attachment quality. The
major distinguishing features of this technology include enhanced sensitivity, the
exclusion of labels, and kinetic measurement of cell health/behavior.
Convenient and simple workflow
– Plate target cells, add effector cells, and start reading.
– Generate real-time killing curves for multiple conditions simultaneously,
spanning seconds to days.
– Read an entire 96-well plate in 15 seconds and run up to six plates
independently, with no scheduling conflicts.
Figure 2. Overview of the Agilent xCELLigence RTCA assay.
The gold biosensors in each well of Agilent electronic microplates (E‑Plates)
cover ~75% of the bottom surface area. The circular biosensors in each well
of an E-Plate are linked to strands that form an interdigitating array (Figure 3).
This proprietary design enables large populations of cells to be monitored
simultaneously. The biosensors detect cellular impedance as cells adhere to
and proliferate on the E‑Plates, providing an extremely sensitive readout of cell
number, cell size/morphology, and cell‑substrate attachment quality in real time.
A B C
Figure 3. Biosensors measure cellular impedance on Agilent E-Plates. (A) Photograph of a single
well in an E-Plate. Though cells can also be visualized on the gold biosensor surfaces, the region
in the middle of the well facilitates microscopic imaging. (B) Crystal violet-stained human cells, as
viewed in a compound microscope. (C) Immunofluorescence microscopy.
How does the xCELLigence
real-time cell analysis
assay work?
Step 1
Step 2
Step 3
Step 4
Adherent
target cells
+ Nonadherent
effector cells
Biosensors Adherent target cells (such as tumor cells) are first seeded
into Agilent E-Plate wells. The biosensor signal, also known
as Cell Index, increases as cells attach and proliferate, then
plateaus as cells approach 100% confluence.
When added subsequently, nonadherent effector cells (that
is, immune cells) in suspension do not cause signal changes
due to lack of adherence to the gold biosensors.
If effector cells induce the destruction of the target adherent
tumor cells, the corresponding cytolytic activity can be
sensitively and precisely detected.
Using an intuitive graphical interface designed specifically for
the immuno-oncologist, the RTCA Software Pro
Immunotherapy Module monitors cell killing in real time.
Measuring cellular impedance
with E-Plates
8
The impedance caused by adherent cells is reported using a unitless parameter
called Cell Index (CI), where:
CI =
(Impedance at n) – (Impedance without cells)
(Nominal impedance constant)
Figure 4 illustrates an example of a real-time impedance trace throughout the
course of setting up and running an apoptosis experiment:
1. Rapid increase due to cell adhesion: For the first few hours after cells have
been added to a well, there is a rapid increase in impedance, which is caused
by cell attachment and spreading.
2. Slow increase due to cell proliferation: If cells are subconfluent after the
initial attachment stage, they will start to proliferate, causing a gradual yet
steady increase in CI.
3. Plateau due to cellular confluence: When cells reach confluency, the CI value
plateaus, reflecting the fact that the electrode surface area accessible to bulk
media is no longer changing.
4. Decrease due to cell death/detachment: The addition of an apoptosis inducer
at this point causes a decrease in CI back to zero. This is the result of cells
rounding then detaching from the well bottom. While this generic example
involves addition of the apoptosis inducer at the point of cellular confluence,
impedance-based assays are flexible and can interrogate a wide variety of
phenomena across the full spectrum of cell densities.
Figure 4. Generic real-time impedance trace for setting up and running an apoptosis assay. Each
phase of the impedance trace, and the cellular behavior it arises from, is explained in the text.
Real-time cellular impedance
traces explained
1. Rapid increase due
2. Slow increase due
to cell proliferation
to cell adhesion
Time (hours)
Cell Index
3. Plateau due to
cellular confluence 4. Addition of
apoptosis inducer
5. Decrease due to cell
death/detachment
9
To control the temperature, humidity, and atmospheric composition of RTCA
assays, xCELLigence instruments are housed inside standard tissue culture
incubators or hypoxia chambers, except for the HT model (Figure 5). The
instruments connect through a cable with analysis and control units that are
housed outside the incubator. User‑friendly software allows for real‑time control
and monitoring of the instrument, including real‑time data display and analysis
functions.
Of the nine xCELLigence RTCA instruments, those best suited for immunotherapy
assays are the dual purpose (DP), single plate (SP), multiple plates (MP),
high throughput (HT), and eSight models (Table 1). While each instrument
monitors cell number, cell size, and cell‑substrate attachment quality through
cellular impedance in an identical manner, they differ from one another in plate
configuration and throughput. The DP model has the additional capability to
quantitatively monitor cell invasion/migration by using a specialized plate that
functions as an electronic Boyden chamber. The eSight incorporates imaging
in three colors, plus brightfield. Finally, though the HT model can be run as a
standalone instrument, four of these can be linked to a single control unit to
provide a total of 1,536 wells. HT instruments can also be integrated with a
robotic liquid handler to maximize throughput.
Figure 5. An Agilent xCELLigence RTCA eSight instrument and its control unit are housed inside
and outside an incubator, respectively.
xCELLigence instruments
for immunotherapy
10
Immunotherapy
Applications
Dual
Purpose
(DP)
Single
Plate
(SP)
Multiple
Plates
(MP)
High
Throughput
(HT) eSight
Applicable to both liquid and solid tumor target cells
Cell-mediated cytotoxicity
ADCC
Checkpoint inhibitors
Combination therapies
Antibody-drug conjugates
Immune cell activation
Cell invasion and migration
Live cell imaging
Specifications
Format 3 × 16 wells 1 × 96 wells 6 × 96 wells 1 × 384 wells
3 × 96 wells
impedance
5 × 96 wells
imaging
Maximum throughput 48 wells 96 wells 576 wells
Up to
4 × 382 wells
(1,536 wells
total)
288 wells
impedance
Up to 480 wells
total for imaging
Table 1. Overview of Agilent xCELLigence RTCA instruments.
11
Though the innate and adaptive branches of the immune system are typically
described as being distinct and separate from one another, they often work
in concert to afford protection and combat diseases. When a pathogen is
encountered, cells of the innate immune system typically release cytokines that
cross-talk with components of the adaptive immune system, causing them
to expand and become activated. Many cells involved in the innate immune
response (including NK cells, neutrophils, and eosinophils) also express CD16
(Fc receptor), which is a low-affinity receptor for immunoglobulins such as
IgG. Immunoglobulin binding by CD16 targets innate immune cells to the
immunoglobulin-bound target cell and triggers target cell destruction. This
prophylactic mechanism is known as antibody-dependent cell-mediated cytolysis
(ADCC) and is the basis of many monoclonal antibody therapies.
As shown in Figures 6 and 7, scientists have used the xCELLigence platform
to measure the ability of mononuclear cells (MNCs) from blood to kill different
breast cancer cell lines in the presence or absence of trastuzumab (also known
as Herceptin). Trastuzumab recognizes the tumor cell through its antigen (HER2),
resulting in the specific killing of the tumor cells.
Figure 6. CI values are proportionally reduced with increasing effector-to-target (E:T) ratios in
the presence of trastuzumab. BT474 clone five cells were maintained for 26 hours, then treated
with media alone (control) or with media plus mononuclear cells (MNCs) isolated from human
blood (A). Cells were treated in an identical fashion in (B) except for the inclusion of 0.1 μg/mL
trastuzumab. CI values were normalized at the time of addition. Blue represents growth with no
MNCs (control) while green, orange, purple, and red represent growth in the presence of MNCs
at E:T ratios of 0.5:1, 1:1, 2:1, and 6:1, respectively. Vertical dashed lines indicate the 16 hour
window of time after treatment used to determine AUC values. Normalized CI values are plotted in
15‑minute increments as the average of three replicates with the standard deviation. This figure
has been reproduced with permission from: Understanding Key Assay Parameters that Affect
Measurements of Trastuzumab-Mediated ADCC Against Her2 Positive Breast Cancer Cells.
Kute, T. et al. Oncoimmunology. 2012 Sep 1, 1(6), 810–821.15
Using xCELLigence to
study antibody-dependent
cell-mediated cytolysis
(ADCC)
0
0.5
1.0
1.5
2.0
2.5 A
Normalized Cell Index
0 10 20 30 40 50 60
Time (hours)
Effector:Target
Control
0.5:1
1:1
2:1
6:1
0
0.5
1.0
1.5
2.0
2.5 B
Normalized Cell Index
0 10 20 30 40 50 60
Time (hours)
Effector:Target
Control
0.5:1
1:1
2:1
6:1
Antibody-dependent cell-mediated cytolysis (ADCC)
12
Figure 7. Natural killer cells exhibit the greatest ADCC activity among subpopulations of
mononuclear cells. MNCs were tested for ADCC killing effect (A) or were separated into
subpopulations, then tested. (B) NK cells, (C) monocytes, (D) B cells, (E) T cells. Green lines
represent the control, blue shows 0.1 µg/mL of trastuzumab alone, violet shows MNCs or
subpopulations at E:T = 6:1, and red shows MNCs or subpopulations at E:T = 6:1 in the presence
of 0.1 µg/mL trastuzumab. The flow cytometry results showing the distribution of immune
subtypes among purified cells and MNCs are given in the table. This figure has been reproduced
with permission from: Understanding Key Assay Parameters that Affect Measurements
of Trastuzumab-Mediated ADCC Against Her2 Positive Breast Cancer Cells. Kute, T. et al.
Oncoimmunology. 2012 Sep 1, 1(6), 810–821.15
A
Normalized Cell Index
0 10 20 30 40 50 60
Time (hours)
MNC
Trastuzumab alone
Control
Effector alone
Effector + Trastuzumab
0
1
2
3
4 B Normalized Cell Index
0 10 20 30 40 50
Time (hours)
NK
0
1
2
3
D
Normalized Cell Index
0 10 20 30 40 50
Time (hours)
B cells
0
1
2
3 C
Normalized Cell Index
0 10 20 30 40 50
Time (hours)
Monocyte
0
1
2
3
E
Normalized Cell Index
0 10 20 30 40 50
Time (hours)
T cells
0
1
2
3
Cell Profile and Purity of Subsets (%)
Preparation NK Mono B Cells T Cells Total
14.5 3.8 10.5 71.2 100
89.0 1.7 0.5 8.7 100
15.0 81.4 0.5 3.1 100
15.3 5.2 73.4 6.1 100
2.3 0.0 0.0 95.4 100
MNC
NK Cells
Monocytes
B Cells
T Cells
13
1. Jiao, D. et al. Immunogenic Senescence Sensitizes Lung Cancer to LUNXTargeting Therapy. Cancer Immunol. Immunother. 2022, 71(6), 1403–1417.
doi: 10.1007/s00262-021-03077-1 (University of Science and Technology of
China)
2. Cheng, Z. F. et al. A Novel Endogenous CD16-Expressing Natural Killer Cell
for Cancer Immunotherapy. Biochem. Biophys. Rep. 2021, 26, 100935. doi:
10.1016/j.bbrep.2021.100935 (Acepodia Biotech, Inc)
3. Takahashi, N. et al. Construction of In Vitro Patient-Derived Tumor Models to
Evaluate Anticancer Agents and Cancer Immunotherapy. Oncol. Lett. 2021,
21(5), 406. doi: 10.3892/ol.2021.12667 (Fukushima Medical University)
4. Li, H. K, et al. A Novel off-the-Shelf Trastuzumab-Armed NK Cell Therapy
(ACE1702) Using Antibody-Cell-Conjugation Technology. Cancers (Basel)
2021, 13(11), 2724. doi: 10.3390/cancers13112724 (Acepodia Biotech, Inc)
5. Olofsson, H. G. et al. Vγ9Vδ2 T Cells Concurrently Kill Cancer Cells and CrossPresent Tumor Antigens. Front. Immunol. 2021, 12, 645131. doi: 10.3389/
fimmu.2021.645131 (Copenhagen University Hospital Herlev)
6. Baysal, H. et al. Cetuximab-Induced Natural Killer Cell Cytotoxicity in Head
and Neck Squamous Cell Carcinoma Cell Lines: Investigation of the Role of
Cetuximab Sensitivity and HPV status. Br. J. Cancer. 2020, 123(5), 752–761.
doi: 10.1038/s41416-020-0934-3 (University of Antwerp)
7. Pazina, T. et al. Enhanced SLAMF7 Homotypic Interactions by Elotuzumab
Improves NK Cell Killing of Multiple Myeloma. Cancer Immunol. Res. 2019,
7(10), 1633–1646. doi: 10.1158/2326-6066.CIR-18-0579 (Fox Chase Cancer
Center)
8. Friedman, J. et al. Direct and Antibody-Dependent Cell-Mediated
Cytotoxicity of Head and Neck Squamous Cell Carcinoma Cells by HighAffinity Natural Killer Cells. Oral Oncol. 2019, 90, 38–44. doi: 10.1016/j.
oraloncology.2019.01.017 (National Institutes on Deafness and Other
Communication Disorders, National Institutes of Health)
9. Jang, Y. et al. Development of Immunocompatible Pluripotent Stem Cells Via
CRISPR-Based Human Leukocyte Antigen Engineering. Exp. Mol. Med. 2019,
51(1), 1–11. doi: 10.1038/s12276-018-0190-2 (The Catholic University of
Korea; Seoul St. Mary’s Hospital)
10. Romano, S. Anticancer Activity and Antibody-Dependent Cell-Mediated
Cytotoxicity of Novel Anti-Nucleolin Antibodies. Sci. Rep. 2018, 8(1), 7450.
doi: 10.1038/s41598-018-25816-8 (University of Coimbra)
11. Oberg H. H. et al. Tribody [(HER2)2xCD16] Is More Effective Than
Trastuzumab in Enhancing γδ T Cell and Natural Killer Cell Cytotoxicity
Against HER2-Expressing Cancer Cells. Front. Immunol. 2018, 9, 814. doi:
10.3389/fimmu.2018.00814 (Christian-Albrechts University (CAU) of Kiel)
12. Tóth, G. et al. Quantitating ADCC Against Adherent Cells: Impedance‑Based
Detection is Superior to Release, Membrane Permeability, or Caspase
Activation Assays in Resolving Antibody Dose Response. G Cytometry A
2017, 91(10), 1021–1029 doi: 10.1002/cyto.a.23247 (University of Debrecen)
13. Gomes S. E. et al. miR-143 or miR-145 Overexpression Increases CetuximabMediated Antibody-Dependent Cellular Cytotoxicity in Human Colon Cancer
Cells. Oncotarget 2016, 7(8), 9368-9387. doi: 10.18632/oncotarget.7010
Selected publications
14
14. Tóth, G. et al. The Combination of Trastuzumab and Pertuzumab
Administered at Approved Doses May Delay Development of
Trastuzumab Resistance by Additively Enhancing Antibody-Dependent
Cell-Mediated Cytotoxicity. MAbs 2016, 8(7), 1361–1370. doi:
10.1080/19420862.2016.1204503 (University of Debrecen; MTA-DE Cell
Biology and Signaling Research Group)
15. Schiller, C. B. et al. CD19-Specific Triplebody SPM-1 Engages NK and γδ T
Cells for Rapid and Efficient Lysis of Malignant B‑Lymphoid Cells. Oncotarget
2016, 7(50), 83392–83408 doi: 10.18632/oncotarget.13110 (LudwigMaximilians-University of Munich)
16. Rocca Y. S. et al. Phenotypic and Functional Dysregulated Blood NK Cells in
Colorectal Cancer Patients Can Be Activated by Cetuximab Plus IL‑2 or IL‑15,
Front. Immunol. 2016 , 7, 413. doi: 10.3389/fimmu.2016.00413 (Centro de
Investigaciones Oncológicas CIO-FUCA)
17. Jacobs, J. et al. Unlocking the Potential of CD70 as a Novel
Immunotherapeutic Target for Non-Small Cell Lung Cancer. Oncotarget 2015,
6(15), 13462–13475. doi: 10.18632/oncotarget.3880 (Antwerp University;
Antwerp University Hospital)
18. Seidel, U. J. et al. γδ T Cell-Mediated Antibody-Dependent Cellular Cytotoxicity
with CD19 Antibodies Assessed by an Impedance‑Based Label‑Free
Real‑Time Cytotoxicity Assay. Front. Immunol. 2014, 5. doi: 10.3389/
fimmu.2014.00618 (University Children's Hospital Tübingen)
19. Kute, T. et al. Understanding Key Assay Parameters that Affect
Measurements of Trastuzumab-Mediated ADCC Against Her2 Positive Breast
Cancer Cells. Oncoimmunology 2012, 1(6), 810–821doi: 10.4161/onci.20447
(Wake Forest University School of Medicine)
ADCC – adherent target cells tested
MCF-7, A431, BT-474, NCI-N87, SKOV3, PC8, PC9, PC11, PC12, PC13, HD9, HD10,
HD11, H322, MCF-7- CD19tm, Colo38, and MDA-MB435
Supporting information
– Agilent xCELLigence application note: Real-Time, Label-Free Measurement
of Natural Killer Cell Activity and Antibody-Dependent Cell-Mediated
Cytotoxicity
– Agilent xCELLigence technical overview: Real-Time Antibody-Dependent
Cell-Mediated Cytotoxicity (ADCC) Assays
– Agilent xCELLigence RTCA protocols: In Vitro Functional Assay Using
Real-Time Cell Analysis for Assessing Cancer Immunotherapeutic Agents
– Agilent xCELLigence eSight video: Multiplexed ADCC with xCELLigence
RTCA eSight
15
The therapeutic efficacy of the ADCC technique is decreased by expression of the
CD16 antibody receptor on some, but not all, immune cells. In particular, cytotoxic
and helper T lymphocytes do not express CD16 and, therefore, are not recruited
to antibody‑coated cells. To circumvent this constraint and mobilize the full
capacity of the adaptive immune response against tumors, bispecific antibodies
have been engineered to simultaneously (1) bind specific antigens on the surface
of tumor cells to (2) tether and activate cytotoxic and helper T cells by binding
the CD3 receptor expressed on their surface. This approach has the advantage of
bypassing MHC‑mediated activation of T cells and has the potential to target any
antigen expressed on the surface of tumor cells. Though multiple variations of
bispecific antibodies have been studied, BiTEs stand out as especially promising.
BiTEs targeting the CD19 antigen on B cell malignancies were awarded
"Breakthrough Therapy” status by the FDA.
Figure 8 exemplifies how the xCELLigence RTCA can be utilized to characterize
BiTEs through the killing of adherent PC3 prostate cancer cells by PBMCs. The
study is performed in the presence of a BiTE targeting the EpCAM receptor
(which is expressed on the surface of most cancer cells of epithelial origin,
including PC3 cells).
Data show that in the absence of BiTE treatment, PBMCs displayed no cytolytic
activity at the E:T ratios tested in this experiment. At 1 μg/mL anti-EpCAM/CD3
BiTE and varying E:T ratios, the CI decreases in a dose-dependent manner,
representing PBMCs killing PC3s. At a PBMC:PC3 ratio of 10:1, EpCAM/CD3 BiTE
increases killing efficacy in a dose-dependent manner. Though PC3 cell killing is
stimulated at the lower BiTE concentrations, the killing of PC3 cells is delayed.
Normalized CI can easily be converted to %cytolysis. The data clearly show larger
differences in cytolysis efficiency when fewer effector cells were used.
Using xCELLigence to
study BiTEs
Bispecific T cell engagers (BiTEs) and
bispecific antibodies
16
Figure 8. Impedance assessment of BiTE-mediated cytotoxicity. (A) Normalized CI plot for PC3
target cells incubated with PBMCs at different E:T ratios without the BiTE. (B) Same E:T ratios as
(A) but with 1 μg/mL anti-EpCAM/CD3 BiTE. (C) At E:T ratio of 10:1, different BiTE concentrations
resulted in varied dynamic cytolysis of the target cells. (D) Same result from (C) showed as
%cytolysis. (E) Example of BiTE concentration depended %cytolysis from E:T ratio 10:1 and 1.25:1.
(F) KT50 comparison for result from (E). Significance analysis performed by one-way ANOVA.
(*** p< 0.001; ** p< 0.01; * p< 0.05; NS = Not Significant; N.D. = Not Detected). This figure has been
reproduced with permission from Cerignoli, F. et al. In vitro Immunotherapy Potency Assays Using
Real-Time Cell Analysis. PLOS ONE 2018, 13(3), e0193498.
This work is licensed under the Creative Commons Attribution 4.0 International License. To view a
copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative
Commons, PO Box 1866, Mountain View, CA 94042, USA.
ANormalized Cell Index
0 20 40 60 80 100 120
Time (hours)
E:T ratio
0
1
2
3
4
5 20:1
10:1
5:1
2.5:1
1.25:1
0.625:1
Target only
BNormalized Cell Index
0 20 40 60 80 100 120
Time (hours)
BiTE at 1 µg/mL,E:T ratio
0
1
2
3
4
5 20:1
10:1
5:1
2.5:1
1.25:1
0.625:1
Target only
C
ENormalized Cell Index
0 20 40 60 80 100 120
Time (hours)
E:T = 10:1
E:T
10:1 1.25:1
0
1
2
3
4
5 BiTE at 1 µg/mL
BiTE at 0.25 µg/mL
BiTE at 0.1 µg/mL
No BiTE
Target only
BiTE at 1 µg/mL
BiTE at 0.25 µg/mL
BiTE at 0.1 µg/mL
No BiTE
Target only
D%Cytolysis
%Cytolysis
0 20 40 60 80 100 120
Time (hours)
E:T = 10:1
0
20
40
60
80
100
0
0
20
40
60
80
100
EpCAM BiTE 1 µg/mL
0.25 µg/mL
0.1 µg/mL
F
E:T
10:1 1.25:1
KT50 (hours)
0
0
20
40
60
80
100
EpCAM BiTE 1 µg/mL
0.25 µg/mL
0.1 µg/mL NS
NS
NS
NS
N.D. N.D.
17
1. Li, G. et al. CD3 Engagement as a New Strategy for Allogeneic “Off-the-Shelf”
T Cell Therapy. Mol. Ther. Oncolytics 2022, 24, 887–896. doi: 10.1016/j.
omto.2022.02.024 (Northwestern University)
2. Zappala, F. et al. Rapid, Site-Specific Labeling of “Off-the-Shelf” and Native
Serum Autoantibodies with T Cell-Redirecting Domains. Sci. Adv. 2022, 8(18),
eabn4613. doi: 10.1126/sciadv.abn4613 (University of Pennsylvania)
3. Mandrup, O. A. et al. Programmable Half-Life and Anti-Tumour Effects
of Bispecific T-Cell Engager-Albumin Fusions with Tuned FcRn
Affinity. Commun. Biol. 2022, 4(1), 310. doi: 10.1038/s42003-021-01790-2
(Aarhus University)
4. Kauer, J. et al. CD18 Antibody Application Blocks Unwanted Off-Target T Cell
Activation Caused by Bispecific Antibodies. Cancers (Basel) 2021, 13(18),
4596. doi: 10.3390/cancers13184596 (University of Tübingen; University
Hospital Tübingen)
5. Thakur, A. et al. Anti-Tumor and Immune Modulating Activity of T Cell Induced
Tumor-Targeting Effectors (TITE). Cancer Immunol. Immunother. 2021, 70(3),
633–656. doi: 10.1007/s00262-020-02692-8 (University of Virginia)
6. Thakur, A et al. Bispecific Antibody Armed Metabolically Enhanced
Headless CAR T Cells. Front. Immunol. 2021, 12, 690437. doi: 10.3389/
fimmu.2021.690437 (University of Virginia)
7. Thakur, A. et al. Enhanced Cytotoxicity Against Solid Tumors by Bispecific
Antibody-Armed CD19 CAR T Cells: a Proof-Of-Concept Study. J. Cancer Res.
Clin. Oncol. 2020, 146(8), 2007–2016. doi: 10.1007/s00432-020-03260-4
(University of Virginia)
8. Kauer, J. et al. Tocilizumab, but not Dexamethasone, Prevents CRS without
Affecting Antitumor Activity of Bispecific Antibodies. J. Immunother. Cancer
2020, 8(1), e000621. doi 10.1136/jitc-2020-000621(University of Tübingen
Interfaculty Institute of Cell Biology)
9. Oberg, H. H. et al. Bispecific Antibodies Enhance Tumor-Infiltrating
T Cell Cytotoxicity Against Autologous HER-2-Expressing High-Grade
Ovarian Tumors. J. Leukoc. Biol. 2020, 107(6), 1081–1095. doi: 10.1002/
JLB.5MA1119-265R (Christian-Albrechts University of Kiel)
10. Hendriks, M. A. J. M. et al. Bispecific Antibody Approach for EGFRDirected Blockade of the CD47-SIRPα “Don’t Eat Me” Immune Checkpoint
Promotes Neutrophil-Mediated Trogoptosis and Enhances Antigen
Cross-Presentation. Oncoimmunology 2020, 9(1), 1824323. doi:
10.1080/2162402X.2020.1824323 (University Medical Center Groningen)
11. Tawfik, D. et al. TRAIL-Receptor 4 Modulates γδ T Cell-Cytotoxicity
Toward Cancer Cells. Front. Immunol. 2019, 10, 2044. doi: 10.3389/
fimmu.2019.02044 (Christian-Albrechts-University of Kiel)
12. Karches, C. H. et al. Bispecific Antibodies Enable Synthetic Agonistic
Receptor-Transduced T Cells for Tumor Immunotherapy. Clin. Cancer
Res. 2019, 25(19), 5890–5900. doi: 10.1158/1078-0432.CCR-18-3927
(Ludwig‑Maximilians-University of Munich)
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Cell Analysis. PLoS One 2018, 13(3), e0193498. doi: 10.1371/journal.
pone.0193498 (ACEA Biosciences)
Selected publications
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14. Meng, W. et al. Targeting Human-Cytomegalovirus-Infected Cells by
Redirecting T Cells Using an Anti-CD3/Anti-Glycoprotein B Bispecific
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10.1128/AAC.01719-17 (Merck)
15. Freedman, J. D. et al. Oncolytic Adenovirus Expressing Bispecific Antibody
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16. Schmittnaegel, M. et al. A New Class of Bifunctional Major Histocompatibility
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0207 (Roche Innovation Center Basel)
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(Roche Innovation Center Zurich)
18. Schanzer, J. M. et al. A Novel Glycoengineered Bispecific Antibody Format
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Molecular Properties. J. Biol. Chem. 2014, 289(27), 18693–706. doi: 10.1074/
jbc.M113.528109 (Roche Diagnostics)
19. Oberg, H. H. et al. Novel Bispecific Antibodies Increase γδ T-cell Cytotoxicity
Against Pancreatic Cancer Cells. Cancer Res. 2014, 74(5), 1349–60.
doi: 10.1158/0008-5472.CAN-13-0675 (Christian-Albrechts-University Kiel)
20. Castoldi, R. et al. A Novel Bispecific EGFR/Met Antibody Blocks TumorPromoting Phenotypic Effects Induced by Resistance to EGFR Inhibition
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doi: 10.1038/onc.2013.245 (Roche Diagnostics)
BiTE and bispecific antibody mediated immune cell killing—
adherent target cells tested
PC3 prostate cancer cells, Panc89, Colo357, PancTu-I, PDAC, Colo38,
MDA‑MB435, and HBV-transfected HuH7-S
Supporting information
– Webinar recording: Bispecific Antibody Constructs Mediate
Immunotherapeutic Retargeting of Effector Cells Towards HBV Infected
Target Cells
– Webinar recording: Bispecific Antibody Armed Metabolically Enhanced
Headless CAR-T Cells - Safe, Effective Serial Killers of Solid Tumors
– Agilent xCELLigence application note: Tumor Cell Killing by T Cells -
Quantifying the Impact of a CD19‑BiTE Using Real‑Time Cell Analysis, Flow
Cytometry, and Multiplex Immunoassay
– Agilent xCELLigence RTCA protocols: In Vitro Functional Assay Using RealTime Cell Analysis for Assessing Cancer Immunotherapeutic Agents
19
By disrupting signaling pathways that normally suppress immune cell activation,
checkpoint inhibitors enable immune effector cells to attack cancer cells
more aggressively. From mechanistic validation of novel checkpoint targets
to comparing the relative efficacy of two different checkpoint‑modulating
antibody constructs, xCELLigence RTCA instruments help answer your questions
efficiently under conditions of maximal physiological relevance.
Studies have shown that cancer cells are protected when PDL1 on the surface
of cancer cells bind to PD1 expressed on activated cytotoxic T cells. This
engagement leads to a decrease in cytotoxic activities and the production of
cytokines such as interferon. PDL1/PD1‑blocking antibodies are now being used
as treatment to recover cytotoxic T cell activity and interferon production to inhibit
tumor growth.
Figure 9 demonstrates the xCELLigence RTCA monitoring the impact of an
anti-PD-1 antibody on PBMC killing of prostate cancer PC3 cells. Target PC3
cells are seeded in E-Plates and allowed to attach and proliferate. Frozen PBMCs
are thawed, activated by incubation with Staphylococcus enterotoxin B (SEB)
superantigen, then added on top of the PC3 cells in the presence or absence
of anti-PD-1 antibody. The effector:target ratio was 5:1. As shown in Figure 9A,
PBMCs display a modest capacity for killing PC3 cells (blue trace), but killing
is much more robust in the presence of the anti‑PD‑1 antibody (orange trace).
Using the xCELLigence RTCA software, the primary data are readily converted to
%cytolysis (Figure 9B), which helps elucidate the checkpoint inhibitor’s impact:
earlier onset of target cell killing, increased rate of cytolysis, and a greater total
extent of cell killing.
Using xCELLigence to study
checkpoint inhibitors
Checkpoint Inhibitors
20
0
0.5
1.0
1.5
2.0
2.5
3.0
Time (hours)
Normalized Cell Index
0 20 40 60 80 100 120 140
Target cell
proliferation
A PD-1 checkpoint inhibitor enhances target cell killing
B
Target cell
death
Addition of PBMCs
and α-PD-1
PC3 only
PC3 + PBMCs
PC3 + PBMCs + α-PD-1 (67 nM)
Time (hours)
% Cytolysis
80 100 120 140
%Cytolysis in real time
PC3 only
PC3 + PBMCs
PC3 + PBMCs + α-PD-1 (67 nM)
0
10
20
30
40
50
60
70
80
90
Figure 9. Using an Agilent xCELLigence to monitor the impact of anti-PD-1 antibody on PBMC
killing of prostate cancer PC3 cells. PC3 cells were grown on an Agilent E-Plate. PBMC effector
cells were added with or without the checkpoint inhibitor anti-PD-1 antibody. Impedance was
monitored, and time-dependent cytolytic activity of the effectors was calculated.
21
1. Muik, A. et al. An Fc-inert PD-L1×4-1BB Bispecific Antibody Mediates Potent
Anti-Tumor Immunity in Mice by Combining Checkpoint Inhibition and
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3. Ng, W. et al. Targeting CD155 by Rediocide-A Overcomes Tumour ImmunoResistance to Natural Killer Cells. Pharm. Biol. 2021, 59(1), 47–53.
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5. Liu, X. et al. Tubeimoside-1 Induces TFEB-Dependent Lysosomal Degradation
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6. Wang, H. et al. ROS/JNK/C-Jun Pathway is Involved in Chaetocin Induced
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for Cancer Immunotherapy. Oncoimmunology 2019, 8(10), e1633235.
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Biomedical Research Institute)
13. June, C. H. et al. Enhancing CAR T Cell Persistence Through ICOS and 4‑1BB
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now287 (David Geffen School of Medicine at UCLA)
18. Soto‑Pantoja, D. R. et al. Unfolded Protein Response Signaling Impacts
Macrophage Polarity to Modulate Breast Cancer Cell Clearance and
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Supporting information
– Agilent xCELLigence RTCA protocols: In Vitro Functional Assay Using
Real-Time Cell Analysis for Assessing Cancer Immunotherapeutic Agents
– Agilent xCELLigence RTCA video: Targeting Checkpoint Inhibitors for Cancer
Treatment: The Possibilities
– Agilent xCELLigence RTCA video: Checkpoint Inhibitor Research
– Agilent xCELLigence RTCA video: xCELLigence – A Transformative
Technology in Cancer Research
23
The traditional oncology pharmacopeia of small molecules is rapidly being
supplemented with biologics such as checkpoint inhibitors. It will soon also
include cellular therapies, such as CAR-T cells. With this expanding repertoire
comes the possibility of boosting cancer killing efficacy by combining different
modalities. The optimization of combination therapies would benefit from an
assay platform that, by maintaining high sensitivity under physiologically relevant
conditions, yields in vitro data that are predictive of in vivo behavior. Other
desirable characteristics include an easy workflow and a high-throughput format
to enable diverse permutations of combination therapies so they can be analyzed
simultaneously. xCELLigence RTCA meets all of the above criteria.
Using xCELLigence to study combination therapies
Figure 10 illustrates use of the xCELLigence RTCA to monitor the impact a
combination of PD‑1 and CTLA‑4 checkpoint inhibitors have on PBMC killing of
PC3 cells. In this experiment, target PC3 cells are seeded in E‑Plates and allowed
to attach and proliferate. Frozen PBMCs are thawed, activated by incubation with
Staphylococcal enterotoxin B (SEB) superantigen, then added on top of the PC3
cells in the presence or absence of 38 nM anti-PD-1 antibody and two different
concentrations of anti-CTLA-4 antibodies. The effector:target ratio was 5:1. The
killing efficacy of PBMCs varies dramatically from donor to donor, and, for this
particular batch of cells, adding 38 nM anti‑PD‑1 did not enhance target cell
killing. However, adding anti‑CTLA‑4 along with anti‑PD‑1 promoted target cell
killing in a dose‑dependent manner (green and pink traces).
Figure 10. Anti-PD-1 and anti-CTLA-4 antibodies combination therapy. By analyzing cancer cell
killing with high sensitivity and without the need for labels/modifications, the Agilent xCELLigence
RTCA instruments allow effector and target cells to be studied under conditions that approximate
human physiology more closely than other in vitro techniques. By monitoring combination
therapy-induced target cell killing continuously, these instruments also do away with laborious
endpoints, readily yielding cell killing data under many different conditions simultaneously.
Time (hours)
Normalized Cell Index
0
0.5
1.0
1.5
2.0
2.5
0 20 40 60 80 100 120
Target cell
proliferation
Target cell
Addition of PBMCs death
and α-PD-1/α-CTLA-4
PC3 only
PC3 + PBMCs
PC3 + PBMCs + α-PD-1
PC3 + PBMCs + α-PD-1 + α-CTLA-4 (3 nM)
PC3 + PBMCs + α-PD-1 + α-CTLA-4 (13 nM)
α-PD-1 + α-CTLA-4 combination therapy
Combination therapy
24
1. Ohnesorge, P. V. et al. Efficacy of Oncolytic Herpes Simplex Virus T-VEC
Combined with BET Inhibitors as an Innovative Therapy Approach for NUT
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doi: 10.3390/cancers14112761 (University Hospital Tuebingen)
2. Sonzogni, O. et al. T-SIGn Tumor Reengineering Therapy and CAR T Cells
Synergize in Combination Therapy to Clear Human Lung Tumor Xenografts
and Lung Metastases in NSG Mice. Oncoimmunology 2022, 11(1), 2029070.
doi: 10.1080/2162402X.2022.2029070 (PsiOxus Therapeutics Limited)
3. Hamdan, F. et al. Novel Oncolytic Adenovirus Expressing Enhanced
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Populations Leading to Enhanced Tumor Killing In Vitro, In Vivo and with
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doi: 10.1136/jitc-2021-003000 (University of Helsinki)
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Supporting information
– Agilent xCELLigence RTCA video: RTCA Software Pro for Immunotherapy
Applications | Agilent
26
T cells can be genetically engineered to express a tumor antigen-specific T cell
receptor (TCR) or a chimeric antigen receptor (CAR), composed of an intracellular
signaling domain linked to an extracellular domain derived from a tumor-specific
antibody. The primary motivation for genetically modified T cells is to avoid
the immune tolerance issues associated with nonautologous therapies and
to produce T cells that efficiently target tumors without the need for de novo
activation in people. The efficacy of this approach is highlighted by the convincing
clinical research data that have emerged in recent years (for example, see
Clin. Transl. Immunology 2014, 3(5), e16).
In Figure 11, the antitumor activity of NKG2D CAR-T cells on triple-negative breast
cancer cells (TNBCs) is evaluated by xCELLigence RTCA in vitro. Results show
that a time- and E:T ratio-dependent cytotoxicity for 4-1BB or CD27 costimulated
NKG2D CAR-T cells against NKG2DL (+) MDA-MB-468, and MDA‑MB-436 cells. As
a negative control, untransduced T cells did not inhibit the growth of these cells.
Using xCELLigence to study
genetically engineered T cells
Genetically engineered T cell-mediated cell killing
27
Figure 11. Recognition of human TNBC cells by NKG2D CAR T cells in vitro. (C) Normalized CI plot
for target cells (AE17, BT549, MDA-MB-436, and MDA-MB-468) incubated with UNT or NKG2D CAR
T cells at different E:T ratios for 24 hours. When seeded alone, target cells adhere to the plate and
proliferate, increasing the CI readout (red lines). When T cells are added to target cells, NKG2CD
CAR-T cells cause cell cytolysis and then a progressive decrease in CI. The Y-axis is the normalized
CI generated by the RTCA software displayed in real time. The X-axis is the time of cell culture and
treatment time in hours. Mean values of the CI were plotted ± standard deviation. (D) The CI plot is
converted to %lysis by the Agilent xCELLigence immunotherapy software.
This figure has been reproduced with permission from: Hali, Y. et al. Control of Triple‑Negative
Breast Cancer Using Ex Vivo Self-Enriched, Costimulated NKG2D CAR T Cells. Journal of
Hematology & Oncology 2018, 11, 92.1
This work is licensed under the Creative Commons Attribution 4.0 International License. To view a
copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative
Commons, PO Box 1866, Mountain View, CA 94042, USA.
A B
C
D
UNT
AE17 BT549 MDA-MB-468 MDA-MB-436
GFP-NKG2D-z
GFP-NKG2D-BBz
GFP-NKG2D-27z
28
Heterogeneous antigen expression within a cancer cell population can lead to an
incomplete response to CAR-T cell therapy. While cancer cells that express the
targeted antigen are killed off, cells that lack the antigen continue propagating
undeterred. To minimize this phenomenon, known as antigen/tumor escape,
there is growing interest in targeting multiple tumor cell antigens simultaneously.
Figure 12 compares different scenarios where CARs targeting the HER2 and
IL13Rα2 antigens were expressed in separate T cells (CARpool), as distinct
proteins within the same T cell (biCAR), or as a single fusion protein within T cells
(TanCAR). When incubated with glioblastoma target cells, each of these CART
approaches displayed differential killing capacity and kinetics (Figure 13). These
nuances in serial killing behavior are readily elucidated by continuous impedance
monitoring but would go undetected in traditional endpoint assays.
Figure 12. Using Agilent xCELLigence to monitor killing of the glioblastoma cell line U373 by
CAR-T cells targeting either one or both of the antigens HER2 and IL13Rα2. In the figure legend:
U373 = target cell line alone; NT = target cells treated with nontransfected T cells (not expressing
a CAR); IL13Rα2 = target cells treated with T cells expressing a single CAR targeting IL13Rα2;
Her2 = target cells treated with T cells expressing a single CAR targeting Her2; see the text for
descriptions of CARpool, biCAR, and TanCAR.
Republished with permission of J. Clin. Invest., from "Tandem CAR T Cells Targeting HER2 and
IL13Rα2 Mitigate Tumor Antigen Escape," Hegde, M. et al. 2016 Aug 1, 126, 8, 3036–52, 2019;
permission conveyed through Copyright Clearance Center, Inc.
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the P329G-Mutated Fc Part Of Effector-Silenced Tumor Antigen-Targeting
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0
2
4
6
8
10
0 20 40 60 80 100 120 140
Time (hours)
Cell Index
TanCAR
biCAR
CARpool
HER2
1L13Rα2
NT
U373 NS
Selected publications
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4. Brummer, A. B. et al. Dose-Dependent Thresholds of Dexamethasone
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(University of Pennsylvania)
30
18. Hegde, M. et al. Tandem CAR T Cells Targeting HER2 and IL13Rα2 Mitigate
Tumor Antigen Escape. J. Clin. invest. 2016, 126(8), 3036–52
doi: 10.1172/JCI83416 (Baylor College of Medicine)
19. Davenport, A. J. et al. CAR‑T Cells inflict Sequential Killing of Multiple Tumor
Target Cells. Cancer Immunol. Res. 2015, 3(5), 483–94 doi: 10.1158/2326-
6066.CIR-15-0048 (University of Melbourne)
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CIR-15-0075 (University of Pennsylvania)
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pone.0020235 (Institut Cochin)
Genetically engineered T cell-mediated cell killing– adherent target
cells tested
A375, SW480, MC57, MC57-HER2, U-251MG, and 13-06-MG
Supporting information
– Webinar recording: The Next Generation of CAR T Cells: New Techniques to
Improve Functionality
– Agilent xCELLigence RTCA protocol: A Human In Vitro T Cell Exhaustion
Model for Assessing Immuno-Oncology Therapies
– Agilent xCELLigence application note: Real-Time Specificity and Potency
Assessment of Human Papilloma Virus Specific Engineered T Cells
– Agilent xCELLigence application note: Real-Time Potency Assay for CAR T
Cell Killing of Adherent Cancer Cells
– Agilent xCELLigence eSight video: Car T Killing Cancer Cells with
xCELLigence RTCA eSight
– Agilent xCELLigence technical overview: Real-Time Potency Assay for CAR T
Cell Killing of Adherent Cancer Cells
– Agilent xCELLigence case study: Tmunity Therapeutics - Building a CAR T
Toolbox for More Comprehensive Assessment of Cell Therapies
– Agilent xCELLigence application note: Ex Vivo Phenotyping and Potency:
Using a combined flow cytometry and impedance-based real-time cell
analysis workflow
– Webinar recording: Optimizing B7-H3-CAR T Cells for Targeting Solid Tumors
– Webinar recording: Cell Impedance as a Tool to Measure Potency of
Chimeric Antigen Receptor T cells
– Webinar recording: Novel Bispecific CAR T Cells Against
Hematological Cancers
– Webinar recording: An Effective, High Throughput Impedance-based Assay
to Evaluate Potency of Immunotherapy Products
– Webinar recording: Comprehensive Real-Time Workflow: T-cell Potency and
Metabolic Fitness
31
– Webinar recording: Modeling Anti-tumor Function of Human T Cells with
xCELLigence RTCA eSight
– Agilent xCELLigence application note: Metabolic Preconditioning Improves
Engineered T Cell Fitness and Function
– Agilent xCELLigence brochure: Measure Cell Movement, Health, and
Function with xCELLigence RTCA eSight
32
Macrophages are important effector cells of innate immunity. Depending on
the tissue microenvironment, tumor-associated macrophages (TAMs) can
differentiate into either cytotoxic (M1) or tumor-promoting (M2) states.
While cytotoxic M1 macrophages are typically induced by IFN-γ alone or in
concert with microbial products, tumor-promoting M2 macrophages are induced
by IL-4, IL-13, IL-10, IL-21, TGFβ, immune complexes, or glucocorticoids.
A recent study has shown the secreted glycoprotein thrombospondin 1 (TSP1) is
a positive modulator of innate antitumor immunity by increasing M1 macrophage
recruitment and stimulating reactive oxygen species (ROS)‑mediated tumor
cell killing (Figure 13). These conclusions are drawn, in part, using xCELLigence
RTCA impedance monitoring to evaluate the effect of TSP1 on macrophage/
monocyte activity when cocultured with MDA-MB-231 breast adenocarcinoma
target cells. The %cytolysis data clearly indicate that the tumoricidal activity of
both differentiated U937 human monocytes (A) and activated ANA-1 murine
macrophages (B) are enhanced in the presence of TSP1.
Figure 13. Secreted glycoprotein TSP1 increases macrophage/monocyte-mediated tumoricidal
activity. MDA-MB-231 breast adenocarcinoma target cells were seeded in Agilent E-Plates and
incubated for up to 24 hours. Differentiated U937 human monocytes (A) or activated ANA-1
murine macrophages (B) were then added in the presence or absence of soluble TSP1. This
figure was adapted from: Cancer Res. 2008, 68(17), 7090–9.4
Note that the RT-CES described
in this publication was Agilent's first-generation RTCA system, and has been rebranded as
Agilent xCELLigence RTCA.
Reprinted by permission from the American Association for Cancer Research: Martin-Manso
G, et al. Thrombospondin 1 Promotes Tumor Macrophage Recruitment and Enhances Tumor
Cell Cytotoxicity of Differentiated U937 cells. Cancer Res. 2008 Sep 1, 68(17), 7090–9. DOI:
10.1158/0008-5472.CAN-08-0643
Using xCELLigence to study
macrophage-mediated
phagocytosis
A
B
0
20
40
60
80
0 12 18 24 36
Cytolysis (%)
Time (hours)
U937
U937 + sTSP1 (5 µg/mL)
0 6 12 18
Cytolysis (%)
Time (hours)
ANA-1
ANA-1 + sTSP1 (5 µg/mL)
0
10
20
30
40
50
Macrophage-mediated phagocytosis
33
1. Baris, E. et al. Varenicline Prevents LPS-Induced Inflammatory Response via
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2. Cheok, Y. Y. et al. Podoplanin Drives Motility of Active
Macrophage via Regulating Filamin C During Helicobacter
pylori Infection. Front. Immunol. 2021, 12, 702156
doi: 10.3389/fimmu.2021.702156 (University of Malaya)
3. Liu, C. et al. Danlou Tablets Inhibit Atherosclerosis in Apolipoprotein
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fphar.2021.724670 (University of Macau)
4. Rodriguez-Garcia, A. et al. CAR-T Cell-Mediated Depletion of
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0643 (National Institutes of Health)
Macrophage-mediated phagocytosis – adherent target cells tested
MDA-MB-231, MDA-MB-435, and MCF-7
Supporting information
– Agilent xCELLigence application note: Real-Time Visualization and
Quantitative Analysis of Macrophage Phagocytosis Using the xCELLigence
RTCA eSight
– Agilent xCELLigence eSight video: Effectively Quantify Which
Microorganisms Are Killed by Phagocytosis in Real Time
– Agilent NovoCyte application note: Examining the Kinetics of Neutrophil
Phagocytosis by Flow Cytometry
35
NK cell-mediated cytolysis
NK cells are a type of cytotoxic lymphocyte that play a critical role in the innate
immune system, primarily by recognizing and destroying virus-infected cells.
NK cells express several activating and inhibitory receptors that work in concert
to distinguish infected or diseased cells from normal cells. Once they bind to a
target cell, NK cells become activated and secrete membrane‑permeabilizing
proteins (perforins) and proteases (granzymes), which collectively cause target
cell death through apoptosis or osmotic lysis. NK cells also participate in a
specialized type of cell killing known as antibody-dependent cell‑mediated
cytotoxicity (ADCC). In ADCC, the CD16 low affinity IgG receptor of NK cells
enables them to recognize infected antibody-coated cells that need to be
destroyed. These mechanisms used by NK cells to recognize and destroy
infected cells are also critical for killing cancer cells. Unlike T cells, which
must be activated by antigen-presenting cells before they recognize tumors,
NK cells spontaneously lyse certain types of tumor cells in vivo and in vitro
without requiring immunization or pre-activation. Similar to virally infected
cells, tumor cells may also down-regulate their MHC-1 expression. Recognizing
this change in expression, NK cells destroy such cancer cells through
perforin/granzyme‑mediated lysis. Owing to this capacity, NK cells are being
investigated for the purposes of immunotherapy.
36
Figure 14 shows use of the xCELLigence RTCA to measure target tumor cell
killing by NK cells at low, physiologically relevant E:T ratios in vitro. Results show
that AZD1775, a small molecule inhibitor of WEE1 kinase, was able to sensitize
tumor cells to NK cell lysis.
Figure 14. Target cell killing by KIL at low E:T ratios is enhanced following WEE1 kinase inhibition.
(A) Loss of CI of MOC2 oral carcinoma cells following the addition of KIL at increasing E:T ratios
was measured through real-time impedance analysis. The vertical line at 18 hours indicates the
time at which KIL was added. Control cells were exposed to KIL media alone. (B) %Loss of CI at
12 hours after the addition of KIL (black line) or sorted WT B6 NK cells (gray line) quantified on the
left. On the right, for comparison, KIL (black line) or sorted WT B6 NK cells (gray line) were used to
induce indium release in a standard 12-hour radioactive compound release assay. (C) %Loss of CI
at 72 hours after addition of KIL (black line) or sorted WT B6 NK cells (gray line) quantified. For B
and C, * indicates significantly enhanced killing with KIL cells compared to sorted WT B6 NK cells.
(D) Loss of MOC2 CI following the addition of KIL at low E:T ratios in the presence of AZD1775
(250 nM) or DMSO (volume equivalent). When AZD1775 was present, MOC2 cells were plated in
drug at the start of the assay. Maximum loss of CI was achieved by addition of triton to some wells.
%Loss of CI 48 hours after the addition of KIL to MOC2 cells is quantified on the right. (E) %Loss
of CI of MOC2 cells in the presence (AZD1775 250 nM) or absence (DMSO volume equivalent) of
WEE1 kinase inhibition 12 hours after the addition of KIL at the indicated E:T ratios quantified on
the left. On the right, for comparison, the same was measured in a standard 12-hour radioactive
compound release assay. (F) %Loss of CI of MOC2 cells 48 hours after the addition of KIL.
(G) Impedance analysis of MOC2 cells alone (5 × 103
cells/well) compared to media or KIL cells
alone up to an E:T ratio equivalent of 50:1 (2.5 × 105
KIL/well). Results presented are representative
of three independent experiments with similar results. (*, p <0.05; ***, p <0.001).
This figure has been reproduced with permission from: Friedman, J. et al. Inhibition of WEE1
Kinase and Cell Cycle Checkpoint Activation Sensitizes Head and Neck Cancers to Natural Killer
Cell Therapies. J. Immunother. Cancer. 2018, 6, 59.
This work is licensed under the Creative Commons Attribution 4.0 International License. To view a
copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative
Commons, PO Box 1866, Mountain View, CA 94042, USA.
Using xCELLigence to study
NK cell-mediated cytolysis
A
D
G
B C
E F
37
In Figure 15, xCELLigence RTCA was used to quantitatively measure the cytolytic
activity of NK cells in real time. After growing adherent breast cancer MCF7
cells in the bottom of E‑Plate wells, NK‑92 cells were added at different effector
to target (E:T) ratios. The data clearly demonstrate NK‑92 cell‑mediated lysis of
the MCF7 cells in a dose‑ and time‑dependent manner. Real‑time impedance
monitoring by the xCELLigence system is sensitive enough to detect target cell
killing even at low E:T ratios. For plotting purposes, %cytolysis is readily calculated
using a simple formula:
%Cytolysis =
(Cell Indexno effector – Cell Indexeffector)
Cell Indexno effector
× 100
Figure 15. Real-time monitoring of NK-92 cell-mediated cytolysis of MCF7 breast cancer cells.
Adherent MCF7 target cells were grown in multiple wells of an Agilent E-Plate. Different quantities
of NK-92 cells were added to each well, and impedance was monitored continuously for the next
~20 hours (A). The time-dependent cytolytic activity of NK-92 cells at different E:T ratios (B) was
calculated as described above. Figures adapted from Agilent application note Label-Free Assay for
NK Cell-Mediated Cytolysis.
A
B
40 42 44 46 48 50 52 54 56 58 60 62 64 66 68
Time (hours)
Normalized Cell Index
0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
Add NK 92
16:1
E:T
8:1
4:1
2:1
1:1
0.5:1
No effector
E:T
%Cytolysis
-10
10
30
50
70
90
No
effector
0.5:1 1:1 2:1 4:1 8:1 16:1
2 hours
4 hours
8 hours
38
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NK cell-mediated cytolysis — adherent cell lines tested
HT1080, H460, HepG2, MCF-7, A549, HeLa, MDA-MB-231, NIH3T3, MelC, MelS,
astrocyte-like cell (NT2A), RCC6, RCC4, and mesenchymal stromal cells (MSCs)
Supporting information
– Agilent xCELLigence application note: Label-Free Assay for NK Cell
Mediated Cytolysis
– Agilent xCELLigence application note: Real-Time, Label-Free Measurement
of Natural Killer Cell Activity and Antibody-Dependent Cell-Mediated
Cytotoxicity
– Agilent xCELLigence application note: Evaluating Functional Potency of
Immunotherapies Targeting Liquid Tumors
40
Oncolytic virotherapy is a promising cancer treatment that uses a
replication‑competent virus to selectively infect cancer cells, cause cytotoxicity,
and generate antitumor immunity. This approach has seen major advances in
recent years using wildtype (WT) and genetically engineered viruses.
Analyzing cancer cell killing with high sensitivity and without the need for
labels/modifications, the xCELLigence RTCA instruments allow the interaction
between viruses and target cells to be studied under conditions that
approximate human physiology more closely than other in vitro techniques.
By monitoring target cell killing continuously, these instruments also eliminate
laborious endpoints and readily yield cell killing data under many different
conditions simultaneously.
Figure 16 shows the use of xCELLigence RTCA to monitor killing of A549 lung
cancer cells by a chimeric adenovirus (Enadenotucirev, EnAd). This infects
cells by binding to CD46 or desmoglein, which are widely expressed on many
carcinoma cells. In a potency analysis, the cytotoxicity (killing kinetics) of EnAd at
a range of concentrations is compared with WT adenoviruses Ad11p and Ad5. At
the highest concentration (red, 500 particles per cell (PPC)), EnAd and Ad11p are
seen to cause complete cell killing (cell index decreasing to zero) 36 to 48 hours
after infection. However, at lower virus concentrations (0.8 to 20 PPC) EnAd is
more potent than Ad11p, displaying an earlier onset of cytotoxicity and a more
rapid completion of cytolysis. When compared with EnAd and Ad11p, WT Ad5 is
much less efficient at killing the cancer cells, requiring five days to achieve full cell
killing even at the highest virus concentration.
These data highlight the ability of xCELLigence RTCA assays to quantitatively
capture differences in the potency of different oncolytic viruses.
Oncolytic viruses
41
Figure 16. Killing of A549 lung cancer cells by different adenoviruses. The black arrows indicate
the time of virus addition. Virus concentrations are listed as PPC. Figure adapted from: Mol. Ther.
Oncolytics 2016 Dec 10, 4, 18–30.2
This work is licensed under the Creative Commons Attribution 4.0 International License. To view a
copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative
Commons, PO Box 1866, Mountain View, CA 94042, USA.
1. Ohnesorge, P. V. et al. Efficacy of Oncolytic Herpes Simplex Virus T-VEC
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2. Ferreira, T. et al. Oncolytic H-1 Parvovirus Hijacks Galectin-1 to Enter Cancer
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0
2
4
6
Cell Index
-24 0 24 48 72 96 120
EnAd 500 PPC
100 PPC
20 PPC
4 PPC
0.8 PPC
Mock infected
0
2
4
6
Cell Index
-24 0 24 48 72 96 120
Ad11p
0
2
4
6
Cell Index
-24 0 24 48 72 96 120
Ad5
Selected publications
42
7. Hamdan, F. et al. Novel Oncolytic Adenovirus Expressing Enhanced
Cross-Hybrid IgGA Fc PD-L1 Inhibitor Activates Multiple Immune Effector
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e003000. doi: 10.1136/jitc-2021-003000
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omto.2016.11.003 (University of Oxford)
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17. Schneider, C. C. et al. Metabolic Alteration – Overcoming Therapy Resistance
in Gastric Cancer Via PGK‑1 Inhibition in a Combined Therapy With
Standard Chemotherapeutics. Int. J. Surg. 2015, 22, 92–8. doi: 10.1016/j.
ijsu.2015.08.020 ((University Hospital Tuebingen)
18. Lacroix, J. et al. Oncolytic Effects of Parvovirus H‑1 in Medulloblastoma Are
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43
19. El‑Andaloussi, N. et al. Generation of an Adenovirus‑Parvovirus Chimera with
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0625.2009.00977.x (Skin Cancer Center Charité, Charité-Universitätsmedizin
Berlin)
Supporting information
– Agilent xCELLigence RTCA protocols: In Vitro Functional Assay Using RealTime Cell Analysis for Assessing Cancer Immunotherapeutic Agents
– Agilent xCELLigence eSight video: Imaging Oncolytic Virus-Mediated Killing
on eSight
– Agilent xCELLigence RTCA Handbook: Vaccine and Virology Applications
44
By seeking out and destroying infected cells directly, CD8+ T lymphocytes play
a critical role in adaptive immune response. Every CD8+ T cell clone expresses
a unique variant of specialized receptor, the T cell receptor (TCR), that can
recognize and bind to a specific antigenic peptide presented by MHC class I
(MHC‑I) molecules on the surface of target cells. Engaging infected or cancerous
cells using MCH‑1 complex causes CD8+ cells to secrete perforin and granzymes,
leading to lysis of the target cell.
Tumor cells typically acquire extensive mutations in their genomes, including
the genes of key regulatory and signaling proteins. When cleaved, processed,
and presented by MHC molecules on the surface of antigen presenting cells,
these mutated proteins can elicit a cellular immune response. This explains
T lymphocytes being found inside tumors. Some cancer vaccines exploit this
tumor targeting capacity of T cells by priming the cellular arm of the adaptive
immune response to target cancer cells expressing proteins that are mutated or
expressed at abnormal levels.
While in some contexts, quantifying the number of antigen‑specific CD8+ T cells
in samples using assays such as ELISpot or flow cytometry is useful, there is
often a critical need to assess the functional cytotoxicity of these cells through
killing assays. Measuring cytolytic activity through the chromium‑51 (51Cr) release
assay has long been the gold standard for evaluating CD8+ T cell responses.
Figure 17 shows SKBR-3 breast cancer cells expressing the HER2/Neu protein
prelabeled with 51Cr. They are then co‑incubated with increasing amounts of
a CD8+ T cell clone. This expresses a TCR specific for an antigenic peptide of
HER2/Neu and target cell killing is detected by release of 51Cr into the medium.
An xCELLigence RTCA system performs this assay without prelabeling the target
cells. The RTCA system quantitatively detects the cytolytic activity of CD8+ T cells
against the SKBR-3 target cells in a manner that depends on time and number of
CD8+ T cells added (Figure 17A). Side-by-side comparison with the 51Cr release
assay shows that the sensitivity and dynamic range of the xCELLigence RTCA
assay surpass that of 51Cr (Figure 17B). The preclusion of radiolabeling and the
kinetic data provided by RTCA (including the onset of cytolysis and the rate of
tumor cell killing) make this assay especially attractive.
T Cell-mediated cytolysis
45
Figure 17. CD8+ T cell-mediated cytolysis of SKBR3 tumor cells. In a dose-dependent manner,
CD8+ T cell addition causes the real-time impedance traces to decrease in value, indicative of
a reduction in the number, size, or attachment quality of the SKBR3 tumor cells (A). Plotting the
percentage of tumor cell lysis, as determined by an Agilent xCELLigence RTCA versus the standard
51Cr release assay, demonstrates RTCA to be the more sensitive method (B). Figure adapted from:
J. Vis. Exp. 2012 Aug 8, (66), e3683.10
1. Stirling, E. R. et al. Targeting the CD47/thrombospondin-1 signaling axis
regulates immune cell bioenergetics in the tumor microenvironment to
potentiate antitumor immune response. J. Immunother. Cancer 2022, 10(11),
e004712. doi: 10.1136/jitc-2022-004712
2. Zappala, F. et al. Rapid, site-specific labeling of “off-the-shelf” and native
serum autoantibodies with T cell-redirecting domains. Sci. Adv. 2022, 8(18),
eabn4613. doi: 10.1126/sciadv.abn4613 (University of Pennsylvania)
3. Simões, A. M. C. et al. Patients With Myeloproliferative Neoplasms Harbor
High Frequencies of CD8 T Cell-Platelet Aggregates Associated With
T Cell Suppression. Front. Immunol. 2022, 13, 866610. doi: 10.3389/
fimmu.2022.866610 (University of Copenhagen)
4. Boyd, N. et al. ‘Off-the-Shelf’ Immunotherapy: Manufacture of CD8+ T
Cells Derived from Hematopoietic Stem Cells. Cells 2021, 10(10), 2631.
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5. Otano, I. et al. CD137 (4-1BB) costimulation of CD8+ T cells is more
potent when provided in cis than in trans with respect to CD3-TCR
stimulation. Nat. Commun. 2021, 12(1), 7296. doi: 10.1038/s41467-021-
27613-w (Clínica Universidad de Navarra)
0
0.5
1.0
1.5
Cell Index % Lysis
1 3 5 7 9 11
Time after T cell addition (hours)
No T cells
Tumor:Tcell ratio
Tumor:Tcell ratio
1:1
1:2.5
1:5
1:10
1:20
1:40
1:40 1:20 1:10 1:5 1:2.5 1:1.25
0
20
40
60
80
100 Impedance assay
Chromium release assay
A
B
Selected publications
46
6. Olofsson, G. H. et al. Vγ9Vδ2 T Cells Concurrently Kill Cancer Cells and CrossPresent Tumor Antigens. Front. Immunol. 2021, 12, 645131. doi: 10.3389/
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7. Chulpanova, D. S. et al. Cytochalasin B
-Induced Membrane Vesicles from
Human Mesenchymal Stem Cells Overexpressing IL2 Are Able to Stimulate
CD8+ T-Killers to Kill Human Triple Negative Breast Cancer Cells. Biology
(Basel) 2021, 10(2), 141. doi: 10.3390/biology10020141 (Kazan Federal
University)
8. Aehnlich, P. et al. Expansion With IL-15 Increases Cytotoxicity of Vγ9Vδ2
T Cells and Is Associated With Higher Levels of Cytotoxic Molecules and
T-bet. Front. Immunol. 2020, 11, 1868. doi: 10.3389/fimmu.2020.01868
(Copenhagen University Hospital Herlev)
9. Minutolo, N. G. et al. Quantitative Control of Gene
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doi: 10.1021/jacs.9b11622 (University of Pennsylvania)
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47
19. Pham, P. V. et al. A Simple In Vitro Method for Evaluating Dendritic Cell‑Based
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(College of Medicine, Mayo Clinic)
T cell-mediated cytolysis – adherent target cells tested
TIII melanoma, SK-BR3, HCC1419, MCF-7, BT20, 15-12RM, OAW42, HLA-negative
NCI-ADR-RES cells, murine 4T1 mammary gland tumor cells, BCSC (breast
cancer stem cell), MSC (mesenchymal stem cell), BT20, and HCC1419
Supporting information
– Agilent xCELLigence video: Determining Optimal Cytotoxic Activity of Human
Her2neu Specific CD8 T cells by Comparing the Cr51 Release Assay to the
xCELLigence System
– Webinar recording: Using Impedance-Based Approaches for Measuring
Antigen-Specific Cytotoxic T cell Activity
– Webinar recording: Modeling Anti-tumor Function of Human T Cells with
xCELLigence RTCA eSight
48
Many peer-reviewed studies have been published over the past decade,
establishing xCELLigence RTCA as a prime method of studying immunotherapies
that target solid/adherent cancers. However, approximately 10% of all cancers
are liquid in nature, nonadherent, and cannot be monitored directly by the
standard impedance assay. Moreover, because they are readily accessible
within the blood stream and are not confounded by the microenvironment
complexities/heterogeneities associated with solid tumors, liquid cancers are
prominent immunotherapy targets. To help accelerate research in this area,
Agilent has developed xCELLigence RTCA immunotherapy kits that enable
impedance‑based killing assays to be performed on liquid tumor targets. Five kits
are available, enabling either B cell lines or the K562 myelogenous leukemia
line to be used as targets. In these assays, the wells of E-Plates are precoated
with anti-CD40 or anti-CD19 (for B cells), or anti‑CD29 or anti-CD71 antibody
(for K562 cells), as well as anti-CD9 antibody (for NALM6, RPMI8226 cells). This
enables these cells to be immobilized on the plate bottom before treatment with
effector cells, antibodies, small molecules, and more.
Figure 19 illustrates the utility of the xCELLigence RTCA immunotherapy kit for
B cell killing (anti-CD40) assays. Whereas antibody-immobilized B cells generate
a robust impedance signal and proliferate to the point of confluence (resulting
in a plateaued impedance signal), the growth of untethered B cells is essentially
undetectable (Figures 18A and 18B). With or without anti-CD40 coating of the
wells, effector cells such as the NK-92 cells used here produce minimal signal
on their own (Figure 18B). Addition of NK-92 cells on top of immobilized B cells
results in target cell death in a dose-dependent manner (Figure 18C). Killing is
easily detected even at low effector:target ratios. This sensitivity greatly exceeds
that of traditional release assays which require high effector:target ratios that
are not physiologically relevant. The tethering and killing behaviors shown in
Figures 18B and 18C have been observed in all three of the B cell lymphoma lines
tested (Daudi, Raji, and Ramos), for multiple effector cell types (NK, T, and CART),
and for combination therapies (CART + checkpoint inhibitors). Experiments
looking at killing of human blood‑derived B cells by the effector cells isolated from
the same person are in progress.
Liquid tumor killing assays
49
An important question is whether the physical immobilization of B cells through
antibody tethering affects the efficiency with which they are killed. To assess this,
side-by-side four-hour assays are performed for NK-92 cell-mediated killing of Raji
B cells that are immobilized (analyzed by xCELLigence RTCA) or in suspension
(analyzed by flow cytometry). As shown in Figure 18D, the killing trends observed
by these two methods show high correlation, with the magnitude of %cytolysis
varying minimally. This is consistent with the large number of publications
showing that xCELLigence data consistently recapitulate data obtained by
traditional assays.
Figure 18. The Agilent xCELLigence immunotherapy kit for monitoring B cell killing. (A) Precoating
the wells of Agilent E-Plates with B cell-specific antibody (anti-CD40) enables B cells to proliferate
on, and be detected by, the sensors. (B) Controls showing the selective proliferation of Daudi
B cells on electrodes coated with anti-CD40 antibody. As expected, with or without anti-CD40
coating nonadherent NK-92 effector cells produce minimal signal. Error bars are standard
deviation. (C) The efficiency with which Raji B cells are killed depends on the number of NK-92
cells added per well. (D) The impact of B cell immobilization on killing efficiency. Raji B cells,
either immobilized by antibody or in suspension, were treated with different numbers of NK-92
cells. %Cytolysis was determined after four hours of treatment by xCELLigence (tethered) or flow
cytometry (in suspension).
A C
D
B
anti-CD40 B cell
Electrode
Time (hours)
Normalized Cell Index
%Cytolysis
Time (hours)
Cell Index
0
0.2
0.4
0.6
0.8
1.0
1.2
0
0 5 20 25 30 35 40 45 50
10 20 30 40 50
2:1
1:1
0.75:1
0.5:1
0.25:1
0.1:1
0:1
NK-92:Raji ratio
NK-92:Raji ratio
E:T = 0:1
(untreated)
E:T = 0.0:1
E:T = 0.25:1
E:T = 0.5:1
E:T = 0.75:1
E:T = 1:1
E:T = 2:1
0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2.2
Coated wells + B cells
Uncoated wells + B cells
Coated wells + NK-92 cells
Uncoated wells + NK-92 cells
0
20
40
60
80
100
Flow cytometry
Agilent xCELLigence
B cell seeding
NK-92 cell seeding
50
In a second example of liquid tumor cell killing, Figures 19A and 19B show the
destruction of K562 cells (tethered to E-Plate well bottoms using anti-CD29
antibody) by NK-92 cells. As expected, K562 killing increases as a function of time
and effector cell concentration. Similar to the B cell killing assay, the destruction
of K562 cells is detectable even at low effector:target ratios.
Figure 19. The Agilent xCELLigence immunotherapy kit for monitoring K562 cell killing. (A) K562
cells, immobilized on the bottom of Agilent E-Plate wells by anti-CD29 antibody, are destroyed by
NK-92 cells in a time- and dose-dependent manner. (B) Data from (A) replotted as %cytolysis as a
function of time. Error bars in both are standard deviation.
The liquid tumor killing assays described here are being used in industrial and
academic labs for evaluating/optimizing combination therapies. They are also
used for developing adoptive cell therapies and engineering antibodies. Beyond
the arena of R&D, these liquid tumor killing assays may be used for functional
validation/quality control of manufactured immuno-oncology therapies.
1. Zhang, C. et al. Novel CD19 Chimeric Antigen Receptor T Cells
Manufactured Next-Day for Acute Lymphoblastic Leukemia. Blood Cancer J.
2022, 12(6), 96. doi: 10.1038/s41408-022-00688-4 (Xinqiao Hospital,
Army Medical University)
2. Blanco, B. et al. Overcoming CAR-Mediated CD19 Downmodulation
and Leukemia Relapse with T Lymphocytes Secreting Anti-CD19 T-cell
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3. Kararoudi, M. N. et al. Optimization and Validation of CAR Transduction into
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4. Fousek, K. et al. CAR T-Cells that Target Acute B-Lineage Leukemia
Irrespective of CD19 Expression. Leukemia 2021, 35(1), 75–89.
doi: 10.1038/s41375-020-0792-2 (Children’s Hospital Los Angeles; University
of Southern California Keck School of Medicine)
Time (hours)
Cell Index
0
0.5
1.0
1.5
2.0 A
0 50 100 150
Effector cell addition
Time (hours)
%Cytolysis
B
0 50 100 150
Effector
cell
addition
0
20
40
60
80
100
0:1 (untreated)
NK-92:K562 ratio
0.2:1
0.4:1
0.6:1
0.8:1
1:1
Selected publications
51
5. Kavanagh, H. et al. A Novel Non-Viral Delivery Method that Enables
Efficient Engineering of Primary Human T Cells for Ex Vivo Cell Therapy
Applications. Cytotherapy 2021, 23(9), 852–860.
doi: 10.1016/j.jcyt.2021.03.002 (Maynooth University)
6. Wang, Y. et al. Low-Dose Decitabine Priming Endows CAR T Cells
with Enhanced and Persistent Antitumour Potential Via Epigenetic
Reprogramming. Nat. Commun. 2021, 12(1), 409. doi: 10.1038/s41467-020-
20696-x (Chinese People’s Liberation Army General Hospital)
7. Golubovskaya, V. et al. Novel CD37, Humanized CD37 and
Bi‑Specific Humanized CD37-CD19 CAR-T Cells Specifically Target
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Supporting information
– Agilent xCELLigence application note: Evaluating Functional Potency of
Immunotherapies Targeting Liquid Tumors
– Agilent xCELLigence brochure: Agilent xCELLigence Immunotherapy Kits:
Monitor liquid tumor cell killing in real time
This information is subject to change without notice.
For Research Use Only. Not for use in diagnostic procedures.
RA44903.6900925926
© Agilent Technologies, Inc. 2019, 2023
Published in the USA, January 28, 2023
5994-1303EN
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