Cancer Immunotherapy
Agilent xCELLigence RTCA handbook

Table of contents
What is cancer immunotherapy?
How can the immune system be harnessed to target tumors?

xCELLigence real-time cell analysis

4

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

9Antibody-dependent cell-mediated cytolysis (ADCC)

11

Using xCELLigence to study antibody-dependent cell‑mediatedcytolysis (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

2

4

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

Oncolytic viruses

40

Selected publications

41

T Cell-mediated cytolysis

44

Selected publications

45

Liquid tumor killing assays

48

Selected publications

50

3What is cancer immunotherapy?
Cancer immunotherapy consists of multiple approaches that harness andenhance the innate powers of the immune system to fight the disease. It iscurrently 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 ofcommercialized 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.

How can the immune
system be harnessed totarget tumors?

Immune cell-mediated tumor cell killing can involve components of both theinnate 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

4Antibody-dependent(ADCC)

Activated
T cell

BiTE/bispecificantibody

Oncolytic
virus
Checkpoint
inhibitor

Targetcancer cell

CAR-T cells

NK-cell

Macrophage
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 manymethods 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 thenprovide extra data regarding immune cell phenotype, activation, and function.
The most commonly used method for measuring immune cell‑mediated killingis 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 arethen measured as an indirect readout of the damage caused by effector cells.
Alternative endpoint methods include ELISA‑based granzyme measurement andmorphometric analyses by microscopy. While the data provided by these assays
help piece together an understanding of different facets of immune cell‑mediatedkilling, it is important to note that the parameters being reported often do notcorrelate with target cell killing efficacy in vivo.

5

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, andmuch more– Conduct experiments in label-free conditions– Measure cytotoxicity with no 51Cr, luciferase, or dyes

Diverse cancer
immunotherapy applications

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 inapplications 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

6

How does the xCELLigencereal-time cell analysis
assay work?

xCELLigence RTCA instruments use gold biosensors embedded in the bottomof specialized microplate wells (Agilent E‑Plates) to noninvasively monitor cellstatus including cell number, cell size, and cell‑substrate attachment quality. The
major distinguishing features of this technology include enhanced sensitivity, theexclusion 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.
Step 1

Step 2Adherenttarget cells

Biosensors+ Nonadherent
effector cells

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, thenplateaus as cells approach 100% confluence.

When added subsequently, nonadherent effector cells (thatis, immune cells) in suspension do not cause signal changes
due to lack of adherence to the gold biosensors.

Step 3If effector cells induce the destruction of the target adherent
tumor cells, the corresponding cytolytic activity can besensitively and precisely detected.

Step 4Using an intuitive graphical interface designed specifically forthe immuno-oncologist, the RTCA Software Pro
Immunotherapy Module monitors cell killing in real time.

Figure 2. Overview of the Agilent xCELLigence RTCA assay.

Measuring cellular impedancewith E-Plates

The gold biosensors in each well of Agilent electronic microplates (E‑Plates)
cover ~75% of the bottom surface area. The circular biosensors in each wellof 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 toand proliferate on the E‑Plates, providing an extremely sensitive readout of cellnumber, 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, asviewed in a compound microscope. (C) Immunofluorescence microscopy.

7

Real-time cellular impedance
traces explained

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 thecourse of setting up and running an apoptosis experiment:
1. Rapid increase due to cell adhesion: For the first few hours after cells havebeen 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 ofphenomena across the full spectrum of cell densities.
3. Plateau due tocellular confluence

2. Slow increase due
to cell proliferation

4. Addition of
apoptosis inducer

Cell Index

5. Decrease due to cell
death/detachment

1. Rapid increase due
to cell adhesion
Time (hours)

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.

8

xCELLigence instruments
for immunotherapy

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 arehoused 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 throughcellular impedance in an identical manner, they differ from one another in plate
configuration and throughput. The DP model has the additional capability toquantitatively monitor cell invasion/migration by using a specialized plate thatfunctions as an electronic Boyden chamber. The eSight incorporates imaging
in three colors, plus brightfield. Finally, though the HT model can be run as astandalone instrument, four of these can be linked to a single control unit toprovide a total of 1,536 wells. HT instruments can also be integrated with arobotic liquid handler to maximize throughput.

Figure 5. An Agilent xCELLigence RTCA eSight instrument and its control unit are housed insideand outside an incubator, respectively.

9Table 1. Overview of Agilent xCELLigence RTCA instruments.

Immunotherapy
Applications

Dual
Purpose(DP)

SinglePlate(SP)

Multiple
Plates(MP)

High
Throughput(HT)eSightApplicable 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

FormatMaximum throughput

10

3 × 16 wells 1 × 96 wells 6 × 96 wells 1 × 384 wells

48 wells

96 wells

576 wells

Up to
4 × 382 wells(1,536 wells
total)

3 × 96 wells
impedance
5 × 96 wells
imaging
288 wells
impedance
Up to 480 wells
total for imaging

Antibody-dependent cell-mediated cytolysis (ADCC)
Though the innate and adaptive branches of the immune system are typicallydescribed as being distinct and separate from one another, they often workin concert to afford protection and combat diseases. When a pathogen is
encountered, cells of the innate immune system typically release cytokines thatcross-talk with components of the adaptive immune system, causing themto 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 theimmunoglobulin-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.

2.0
1.5

2.5

A
Effector:Target
Control
0.5:1
1:1
2:1
6:1

Normalized Cell Index

2.5

Normalized Cell Index

Using xCELLigence tostudy antibody-dependentcell‑mediated cytolysis(ADCC)

1.0
0.5
0

2.0
1.5

B
Effector:Target
Control
0.5:1
1:1
2:1
6:1

1.0
0.5
0

0

10

20
30
40
Time (hours)

50

60

0

10

20
30
40
Time (hours)

50

60

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 treatedwith media alone (control) or with media plus mononuclear cells (MNCs) isolated from humanblood (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 AffectMeasurements of Trastuzumab-Mediated ADCC Against Her2 Positive Breast Cancer Cells.
Kute, T. et al. Oncoimmunology. 2012 Sep 1, 1(6), 810–821.15

11

ControlTrastuzumab alone
Effector alone
Effector + Trastuzumab

A

B
3

MNC
3

Normalized Cell Index

Normalized Cell Index

4

2
1

2

1

0

0
0

3

10

20
30
40
Time (hours)

50

0

60

3

C

Normalized Cell Index

Normalized Cell Index

NK

Monocyte
2

1

10

20
30
Time (hours)

40

50

20
30
Time (hours)

40

50

D
B cells

2

1

0

0
0

10

20
30
Time (hours)

40

50

0

10

Cell Profile and Purity of Subsets (%)

Normalized Cell Index

3

E
T cells21

Preparation

NK

Mono B Cells T Cells

Total

MNC

14.5

3.8

NK Cells

89.0

Monocytes

15.0

B Cells
T Cells

10.5

71.2

100

1.7

0.5

8.7

100

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

0
0

10

20
30
Time (hours)

40

50

Figure 7. Natural killer cells exhibit the greatest ADCC activity among subpopulations ofmononuclear 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 presenceof 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 reproducedwith permission from: Understanding Key Assay Parameters that Affect Measurementsof Trastuzumab-Mediated ADCC Against Her2 Positive Breast Cancer Cells. Kute, T. et al.
Oncoimmunology. 2012 Sep 1, 1(6), 810–821.15

12Selected publications

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 ofChina)

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 Headand Neck Squamous Cell Carcinoma Cell Lines: Investigation of the Role ofCetuximab 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-MediatedCytotoxicity 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-MediatedCytotoxicity 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

1314. Tóth, G. et al. The Combination of Trastuzumab and Pertuzumab
Administered at Approved Doses May Delay Development ofTrastuzumab 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 inColorectal 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 deInvestigaciones 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 AffectMeasurements 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 Measurementof Natural Killer Cell Activity and Antibody-Dependent Cell-MediatedCytotoxicity– 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

14

Bispecific T cell engagers (BiTEs) andbispecific antibodies
The therapeutic efficacy of the ADCC technique is decreased by expression of theCD16 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 surfaceof 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 ofbispecific 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.

Using xCELLigence tostudy BiTEs

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 isstimulated 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.

15

4
3
2

C

20

40
60
80
Time (hours)

100

2

120

E:T = 10:1
BiTE at 1 µg/mL
BiTE at 0.25 µg/mL
BiTE at 0.1 µg/mL
4
No BiTE
Target only
3
2

20

40
60
80
Time (hours)

100

120

100

120

E:T = 10:1
BiTE at 1 µg/mL
BiTE at 0.25 µg/mL
BiTE at 0.1 µg/mL
No BiTE
Target only

80
60
40
20

1

0

20

40
60
80
Time (hours)

E

100

120

0

0

20

100

80

NS
NS

NS

40
20

KT50 (hours)

80

60

40
60
80
Time (hours)
EpCAM BiTE 1 µg/mL
0.25 µg/mL
0.1 µg/mL

F

EpCAM BiTE 1 µg/mL
0.25 µg/mL
0.1 µg/mL

NS100%Cytolysis

0

D 100

%Cytolysis

Normalized Cell Index

3

0
0

5

0

4

1

1
0

BiTE at 1 µg/mL,E:T ratio
20:1
10:1
5:1
2.5:1
1.25:10.625:1
Target only

B 5

E:T ratio
20:1
10:1
5:1
2.5:1
1.25:10.625:1
Target only

5

Normalized Cell Index

Normalized Cell Index

A

60
40
20
N.D. N.D.

0

0

10:1

E:T

1.25:1

0

0

10:1

E:T

1.25:1Figure 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 acopy 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.

16

Selected publications

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 Effectsof 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)
13. Cerignoli, F. et al. In Vitro Immunotherapy Potency Assays Using Real‑Time
Cell Analysis. PLoS One 2018, 13(3), e0193498. doi: 10.1371/journal.
pone.0193498 (ACEA Biosciences)1714. Meng, W. et al. Targeting Human-Cytomegalovirus-Infected Cells by
Redirecting T Cells Using an Anti-CD3/Anti-Glycoprotein B Bispecific
Antibody. Antimicrob. Agents Chemother. 2017, 62(1), e01719–17. doi:
10.1128/AAC.01719-17 (Merck)
15. Freedman, J. D. et al. Oncolytic Adenovirus Expressing Bispecific Antibody
Targets T‑Cell Cytotoxicity In Cancer Biopsies. EMBO Mol. Med. 2017, 9(8),1067–1087. doi: 10.15252/emmm.201707567 (University of Oxford)
16. Schmittnaegel, M. et al. A New Class of Bifunctional Major Histocompatibility
Class I Antibody Fusion Molecules to Redirect CD8 T Cells. Mol.
Cancer Ther. 2016, 15(9), 2130–42. doi:10.1158/1535-7163.mct-160207 (Roche Innovation Center Basel)
17. Schanzer J. M. et al. XGFR*, a Novel Affinity-Matured Bispecific
Antibody Targeting IGF-1R and EGFR with Combined Signaling Inhibition
and Enhanced Immune Activation for the Treatment of Pancreatic
Cancer. MAbs 2016, 8(4), 811–827. doi: 10.1080/19420862.2016.1160989(Roche Innovation Center Zurich)
18. Schanzer, J. M. et al. A Novel Glycoengineered Bispecific Antibody Format
for Targeted Inhibition of Epidermal Growth Factor Receptor (EGFR) andInsulin‑Like Growth Factor Receptor Type I (IGF‑1R) Demonstrating Unique
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
and Has Potent Antitumor Activity. Oncogene 2013, 32(50), 5593–5601.
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 Agents18

Checkpoint Inhibitors
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.

Using xCELLigence to study
checkpoint inhibitors

Studies have shown that cancer cells are protected when PDL1 on the surfaceof cancer cells bind to PD1 expressed on activated cytotoxic T cells. This
engagement leads to a decrease in cytotoxic activities and the production ofcytokines such as interferon. PDL1/PD1‑blocking antibodies are now being usedas treatment to recover cytotoxic T cell activity and interferon production to inhibit
tumor growth.
Figure 9 demonstrates the xCELLigence RTCA monitoring the impact of ananti-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 absenceof 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 killingis 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.

19

A

PD-1 checkpoint inhibitor enhances target cell killing
3.0
PC3 only
PC3 + PBMCs
PC3 + PBMCs + α-PD-1 (67 nM)

Normalized Cell Index

2.5
2.0
1.5

Target cellproliferation

1.0
0.5
0

B

Target cell
death

Addition of PBMCs
and α-PD-1
0

90
80
70

20

40

60
80
Time (hours)

100

120

140

%Cytolysis in real timePC3 only
PC3 + PBMCs
PC3 + PBMCs + α-PD-1 (67 nM)% Cytolysis

60
50
40
30
20
10
0
80

100

120

140

Time (hours)

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 wasmonitored, and time-dependent cytolytic activity of the effectors was calculated.

20

Selected publications

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 andConditional 4-1BB Co-Stimulation. Oncoimmunology 2022, 11(1), 2030135.
doi: 10.1080/2162402X.2022.2030135 (BioNTech)

2.

Pinkert, J. et al. T Cell-Mediated Elimination of Cancer Cells by Blocking
CEACAM6-CEACAM1 Interaction. Oncoimmunology 2021, 11(1), 2008110.
doi: 10.1080/2162402X.2021.2008110 (University Hospital Regensburg)

3.

Ng, W. et al. Targeting CD155 by Rediocide-A Overcomes Tumour ImmunoResistance to Natural Killer Cells. Pharm. Biol. 2021, 59(1), 47–53.
doi: 10.1080/13880209.2020.1865410 (Shanghai University of Traditional
Chinese Medicine)

4.

Grote, S. et al. In Vitro Evaluation of CD276-CAR NK-92 Functionality,
Migration and Invasion Potential in the Presence of Immune Inhibitory
Factors of the Tumor Microenvironment. Cells 2021, 10(5), 1020.
doi: 10.3390/cells10051020 (University Hospital Tuebingen)5.

Liu, X. et al. Tubeimoside-1 Induces TFEB-Dependent Lysosomal Degradationof PD-L1 and Promotes Antitumor Immunity by Targeting mTOR. Acta Pharm.
Sin. B 2021, 11(10), 3134–3149. doi: 10.1016/j.apsb.2021.03.039 (Chinese
Academy of Medical Sciences & Peking Union Medical College)

6.

Wang, H. et al. ROS/JNK/C-Jun Pathway is Involved in Chaetocin Induced
Colorectal Cancer Cells Apoptosis and Macrophage Phagocytosis
Enhancement. Front. Pharmacol. 2021, 12, 729367. doi: 10.3389/
fphar.2021.729367 (Sun Yat-sen University)

7.

Yang, C. Y. et al. Engineering Chimeric Antigen Receptor T Cells against
Immune Checkpoint Inhibitors PD-1/PD-L1 for Treating Pancreatic
Cancer. Mol. Ther. Oncolytics 2020, 17, 571–585. doi: 10.1016/j.
omto.2020.05.009 (Taipei Medical University)

8.

Verdura, S. et al. Resveratrol targets PD-L1 Glycosylation and Dimerization to
Enhance Antitumor T-Cell Immunity. Aging (Albany NY). 2020, 12(1), 8–34.
10.18632/aging.102646 (Catalan Institute of Oncology; Girona Biomedical
Research Institute)

9.

Liu, Y. et al. Berberine diminishes cancer cell PD-L1 Expression and Facilitates
Antitumor Immunity Via Inhibiting the Deubiquitination Activity of CSN5. Acta
Pharm. Sin. B 2020, 10(12), 2299–2312. 10.1016/j.apsb.2020.06.014(Qingdao University)

10. Zhang, N. et al. SA-49, a Novel Aloperine Derivative, Induces MITF-Dependent
Lysosomal Degradation of PD-L1. EBioMedicine 2019, 40, 151–162.
10.1016/j.ebiom.2019.01.054 (Chinese Academy of Medical Sciences &Peking Union Medical College)
11. Takahashi, N. et al. An In Vitro System for Evaluating Molecular Targeted
Drugs Using Lung Patient-Derived Tumor Organoids. Cells 2019, 8(5), 481.
doi: 10.3390/cells8050481(Fukushima Medical University)
12. Verdura S. et al. Metformin as an Archetype Immuno-Metabolic Adjuvant
for Cancer Immunotherapy. Oncoimmunology 2019, 8(10), e1633235.
10.1080/2162402X.2019.1633235 (Catalan Institute of Oncology; Girona
Biomedical Research Institute)
13. June, C. H. et al. Enhancing CAR T Cell Persistence Through ICOS and 4‑1BB
Costimulation. JCI insight 2018 Jan 11, 3(1).

2114. Chen, N. et al. KRAS Mutation-Induced Upregulation of PD-L1 Mediates
Immune Escape in Human Lung Adenocarcinoma. Cancer Immunol.
Immunother. 2017, 66(9), 1175–1187. doi: 10.1007/s00262-017-2005-z(Sun Yat-Sen University Cancer Center)
15. Gato‑Cañas, M. et al. PDL1 Signals Through Conserved Sequence Motifs toOvercome interferon‑Mediated Cytotoxicity. Cell Rep. 2017, 20(8),1818–1829.
doi: 10.1016/j.celrep.2017.07.075 (Navarrabiomed-Biomedical ResearchCentre; Rayne Institute, University College London)
16. Morisada, M. et al. Dose‑Dependent Enhancement of T‑Lymphocyte
Priming and CTL Lysis Following Ionizing Radiation in an Engineered
Model of Oral Cancer. Oral Oncol. 2017, 71, 87–94. doi: 10.1016/j.
oraloncology.2017.06.005 (National Institute on Deafness and Other
Communication Disorders, NIH)
17. Antonios, J. P. et al. Immunosuppressive Tumor‑infiltrating Myeloid Cells
Mediate Adaptive Immune Resistance Via a PD‑1/PD‑L1 Mechanism in
Glioblastoma. Neuro. Oncol. 2017, 19(6), 796–807. doi: 10.1093/neuonc/
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 andMelanoma Immune Checkpoint Therapy Responsiveness. Oncotarget 2017,8(46), 80545–80559. doi: 10.18632/oncotarget.19849 (Wake Forest Schoolof Medicine)
19. Delconte, R. D. et al. CIS Is a Potent Checkpoint in NK Cell‑Mediated Tumor
Immunity. Nat. Immunol. 2016, 17(7), 816–24. doi: 10.1038/ni.3470(The University of Melbourne)
20. Antonios, J. P. et al. PD‑1 Blockade Enhances The Vaccination‑Induced
Immune Response in Glioma. JCI insight 2016, 1(10). pii, e87059. doi:
10.1172/jci.insight.87059 (David Geffen School of Medicine at UCLA)
21. Hong, S. et al. Upregulation of PD‑L1 by EML4‑ALK Fusion Protein
Mediates the Immune Escape in ALK Positive NSCLC, Implication for
Optional Anti‑PD‑1/PD‑L1 Immune Therapy for ALK‑TKIs Sensitive andResistant NSCLC Patients. Oncoimmunology 2015, 5(3), e1094598. doi:
10.1080/2162402X.2015.1094598 (Sun Yat-Sen University Cancer Center)

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

22Combination therapy
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 anassay 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 ofPC3 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 thisparticular batch of cells, adding 38 nM anti‑PD‑1 did not enhance target cellkilling. However, adding anti‑CTLA‑4 along with anti‑PD‑1 promoted target cellkilling in a dose‑dependent manner (green and pink traces).
α-PD-1 + α-CTLA-4 combination therapy
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)

Normalized Cell Index

2.5

2.0

1.5
Target cellproliferation

1.0

0.5

Target cell
death

Addition of PBMCs
and α-PD-1/α-CTLA-4
0

0

20

40

60

80

100

120

Time (hours)

Figure 10. Anti-PD-1 and anti-CTLA-4 antibodies combination therapy. By analyzing cancer cellkilling 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.

23Selected publications

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
Carcinoma. Cancers (Basel) 2022, 14(11), 2761.
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
Cross-Hybrid IgGA Fc PD-L1 Inhibitor Activates Multiple Immune Effector
Populations Leading to Enhanced Tumor Killing In Vitro, In Vivo and with
Patient‑Derived Tumor. J. Immunother. Cancer 2021, 9(8), e003000.
doi: 10.1136/jitc-2021-003000 (University of Helsinki)

4.

Afolabi, L. O. et al. Synergistic Tumor Cytolysis by NK Cells in Combination
With a Pan-HDAC Inhibitor, Panobinostat. Front. Immunol. 2021, 12, 701671.
doi: 10.3389/fimmu.2021.701671 (Shenzhen Institutes of Advanced
Technology, Chinese Academy of Sciences)5.

Park, A. K. et al. Effective Combination Immunotherapy Using Oncolytic
Viruses to Deliver CAR Targets to Solid Tumors. Sci. Transl. Med. 2020,12(559), eaaz1863. doi: 10.1126/scitranslmed.aaz1863 (City of Hope)

6.

Huang, C. et al. Combination Therapy with B7H3-Redirected Bispecific
Antibody and Sorafenib Elicits Enhanced Synergistic Antitumor
Efficacy. Theranostics 2020, 10(23), 10498-10512. doi: 10.7150/thno.49480(Sichuan University)

7.

Hartmann, L. et al. Photon Versus Carbon Ion Irradiation: Immunomodulatory
Effects Exerted on Murine Tumor Cell Lines. Sci. Rep. 2020, 10(1), 21517.
doi: 10.1038/s41598-020-78577-8 (University Medical Center Göttingen)

8.

Klose, C. et al. Biological Treatment of Pediatric Sarcomas by Combined
Virotherapy and NK Cell Therapy. BMC Cancer 2019, 19(1), 1172.
doi: 10.1186/s12885-019-6387-5 (University Hospital Tuebingen)

9.

Feliz-Mosquea, Y. R. et al. Combination of Anthracyclines and Anti-CD47
Therapy Inhibit Invasive Breast Cancer Growth While Preventing Cardiac
Toxicity by Regulation of Autophagy. Breast Cancer Res. Treat. 2018, 172(1),69–82. doi: 10.1007/s10549-018-4884-x (Wake Forest School of Medicine)

10. Fenerty, K. E. et al. Immunotherapy Utilizing The Combination of Natural
Killer- and Antibody Dependent Cellular Cytotoxicity (ADCC)-Mediating Agentswith Poly (ADP-Ribose) Polymerase (PARP). J. Immunother. Cancer 2018,
6(1), 133. doi: 10.1186/s40425-018-0445-4 (National Cancer Institute, NIH)
11. Jacobs, J. et al. Preclinical Data on the Combination of Cisplatin andAnti‑CD70 Therapy in Non-Small Cell Lung Cancer as an Excellent Match in
the Era of Combination Therapy. Oncotarget 2017, 8(43), 74058–74067.
doi: 10.18632/oncotarget.18202 (University of Antwerp)
12. Fajardo, C. A. et al. Oncolytic Adenoviral Delivery of an EGFR‑Targeting T‑Cell
Engager Improves Antitumor Efficacy. Cancer Res. 2017, 77(8), 2052–2063.
doi: 10.1158/0008-5472.CAN-16-1708 ( IDIBELL-Institut Català d’Oncologia;
University of Pennsylvania)
13. Ruf, B. et al. Combination of the Oral Histone Deacetylase Inhibitor
Resminostat with Oncolytic Measles Vaccine Virus as a New Option for EpiVirotherapeutic Treatment of Hepatocellular Carcinoma. Mol. Ther. Oncolytics
2015, 2, 15019. doi: 10.1038/mto.2015.19 (University Hospital Tuebingen)2414. Deben, C. et al. The MDM2-Inhibitor Nutlin-3 Synergizes with Cisplatin
to Induce p53 Dependent Tumor Cell Apoptosis in Non-Small Cell
Lung Cancer. 2015, 6(26), 22666–79. doi: 10.18632/oncotarget.4433(University of Antwerp)
15. Kasukabe, T. et al. Cotylenin A and Arsenic Trioxide Cooperatively
Suppress Cell Proliferation and Cell Invasion Activity in Human Breast
Cancer Cells. Int. J. Oncol. 2015, 46(2), 841–8. doi: 10.3892/ijo.2014.2760(Shimane University)
16. Chang, H. Y. et al. Combination Therapy Targeting Ectopic ATP Synthase and
26S Proteasome Induces ER Stress in Breast Cancer Cells. Cell Death Dis.
2014, 5, e1540. doi: 10.1038/cddis.2014.504 (National Taiwan University)
17. Von Mallinckrodt, B. et al. Dianthin‑EGF is an Effective Tumor Targeted
Toxin in Combination with Saponins in a Xenograft Model for Colon
Carcinoma. Future Oncol. 2014, 10(14), 2161–75. doi: 10.2217/fon.14.164(Charité - Universitätsmedizin Berlin)
18. Li, J. et al. Synergistic Combination of Valproic Acid and Oncolytic
Parvovirus H-1PV as a Potential Therapy Against Cervical and Pancreatic
Carcinomas. EMBO Mol. Med. 2013, 5(10), 1537–1555. doi: 10.1002/
emmm.201302796 (Laboratory of Oncolytic Virus Immuno-Therapeutics,
German Cancer Research Centre)
19. Tsamis, K. I. et al. Combination Treatment for Glioblastoma Cells
with Tumor Necrosis Factor‑Related Apoptosis‑Inducing Ligand andOncolytic Adenovirus Delta‑24. Cancer Invest. 2013, 31(9), 630–8.
doi: 10.3109/07357907.2013.849724 (University of Ioannina)

Supporting information– Agilent xCELLigence RTCA video: RTCA Software Pro for Immunotherapy
Applications | Agilent

25Genetically engineered T cell-mediated cell killing
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 intracellularsignaling domain linked to an extracellular domain derived from a tumor-specificantibody. The primary motivation for genetically modified T cells is to avoid
the immune tolerance issues associated with nonautologous therapies andto 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).

Using xCELLigence to study
genetically engineered T cells

26

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 showthat 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. Asa negative control, untransduced T cells did not inhibit the growth of these cells.

A

B

AE17

C

BT549

MDA-MB-468

MDA-MB-436

UNT

GFP-NKG2D-z

GFP-NKG2D-BBz

GFP-NKG2D-27z

D

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 andproliferate, 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 andtreatment time in hours. Mean values of the CI were plotted ± standard deviation. (D) The CI plot isconverted 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 acopy 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.

27

Heterogeneous antigen expression within a cancer cell population can lead to an
incomplete response to CAR-T cell therapy. While cancer cells that express thetargeted 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 andIL13Rα2 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 impedancemonitoring but would go undetected in traditional endpoint assays.
TanCARbiCAR
CARpool
HER2
1L13Rα2
NT
U373

10

Cell Index

8

NS

6

4

2

0

0

20

40

60

80

100

120

140

Time (hours)

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 andIL13Rα2 Mitigate Tumor Antigen Escape," Hegde, M. et al. 2016 Aug 1, 126, 8, 3036–52, 2019;permission conveyed through Copyright Clearance Center, Inc.

Selected publications

28

1.

Stock, S. et al. Chimeric Antigen Receptor T Cells Engineered to Recognize
the P329G-Mutated Fc Part Of Effector-Silenced Tumor Antigen-Targeting
Human IgG1 Antibodies Enable Modular Targeting of Solid Tumors. J.
Immunother. Cancer 2022, 10(7), e005054. doi: 10.1136/jitc-2022-005054

2.

Chandran, S. S. et al. Immunogenicity and Therapeutic Targeting of a Public
Neoantigen Derived from Mutated PIK3CA. Nat. Med. 2022, 28(5), 946–957.
doi: 10.1038/s41591-022-01786-3

3.

Glienke, W. et al. GMP-Compliant Manufacturing of TRUCKs: CAR T Cells
targeting GD2 and Releasing Inducible IL-18. Front. Immunol. 2022, 13,
839783. doi: 10.3389/fimmu.2022.839783 (Hannover Medical School)

4.

Brummer, A. B. et al. Dose-Dependent Thresholds of Dexamethasone
Destabilize CAR T-Cell Treatment Efficacy. PLoS Comput. Biol. 2022, 18(1),e1009504. doi: 10.1371/journal.pcbi.1009504 (Beckman Research Institute,
City of Hope National Medical Center)

5.

Zou, Y. et al. IKZF3 Deficiency Potentiates Chimeric Antigen Receptor T Cells
Targeting Solid Tumors. Cancer Lett. 2022, 524, 121–130. doi: 10.1016/j.
canlet.2021.10.016 (Shanghai Tech University)

6.

June, C. H. et al. An NK-Like CAR T Cell Transition in CAR T Cell
Dysfunction. Cell 2021, 184(25), 6081–6100.e26. doi: 10.1016/j.
cell.2021.11.016 (University of Pennsylvania)

7.

Müller, T. R. et al. Targeted T Cell Receptor Gene Editing Provides Predictable
T Cell Product Function For Immunotherapy. Cell Rep. Med. 2021, 2(8),100374. doi: 10.1016/j.xcrm.2021.100374 (Technical University of Munich)

8.

Seitz, C. M. et al. Novel Adapter CAR-T Cell Technology for Precisely
Controllable Multiplex Cancer Targeting. Oncoimmunology 2021, 10(1),2003532. doi: 10.1080/2162402X.2021.2003532 (University Children’s
Hospital Tuebingen)

9.

Li, W. et al. Targeting Wnt Signaling in the Tumor Immune Microenvironment
to Enhancing EpCAM CAR T-Cell therapy. Front. Pharmacol. 2021, 12, 724306.
doi: 10.3389/fphar.2021.724306 (Fudan University)

10. Shu, R. et al. Engineered CAR-T Cells Targeting TAG-72 and CD47 in
Ovarian Cancer. Mol. Ther. Oncolytics 2021, 20, 325–341. doi: 10.1016/j.
omto.2021.01.002 (Cartherics Pty, Ltd.)
11. 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)
12. Shrestha, B. et al. Generation of Antitumor T Cells For Adoptive Cell TherapyWith Artificial Antigen Presenting Cells. J. Immunother. 2020, 43(3), 79–88.
doi: 10.1097/CJI.0000000000000306 (H. Lee Moffitt Cancer Center)
13. Hu, M. et al. Discovery of the First Potent Proteolysis Targeting Chimera(PROTAC) Degrader of Indoleamine 2,3-Dioxygenase 1. Acta Pharm. Sin.
B 2020, 10(10), 1943-1953. doi: 10.1016/j.apsb.2020.02.010 (Sichuan
University and Collaborative Innovation Center of Biotherapy)
14. Sureban, S. M. et al. DCLK1 Monoclonal Antibody-Based CAR-T Cells asa Novel Treatment Strategy against Human Colorectal Cancers. Cancers(Basel) 2019, 12(1), 54. doi: 10.3390/cancers12010054 (University ofOklahoma)
15. Berahovich, R. et al. Hypoxia Selectively Impairs CAR-T Cells In Vitro. Cancers(Basel) 2019, 11(5), 602. doi: 10.3390/cancers11050602 (ProMab
Biotechnologies)
16. June, C. H. et al. Improving CAR T-Cell Therapy of Solid Tumors with Oncolytic
Virus-Driven Production of a Bispecific T-cell Engager. Cancer Immunol. Res.
2018, 6(5), 605–616. doi: 10.1158/2326-6066.CIR-17-0314 (University ofPennsylvania)
17. June, C. H. et al. Pancreatic Cancer Therapy with Combined MesothelinRedirected Chimeric Antigen Receptor T Cells and Cytokine-Armed Oncolytic
Adenoviruses. JCI Insight. 2018, 3(7), e99573. doi: 10.1172/jci.insight.99573(University of Pennsylvania)

29

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: 10.1158/23266066.CIR-15-0048 (University of Melbourne)
20. June, C. H. Serial Killers and Mass Murderers, Engineered T Cells Are Up to
the Task. Cancer Immunol. Res. 2015, 3(5), 470–2 doi: 10.1158/2326-6066.
CIR-15-0075 (University of Pennsylvania)
21. Lengagne, R. et al. T Cells Contribute to Tumor Progression by Favoring
Pro‑Tumoral Properties of intra‑Tumoral Myeloid Cells in A Mouse Model For
Spontaneous Melanoma. PLoS One 2011, 6(5), e20235 doi: 10.1371/journal.
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 withxCELLigence 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 andMetabolic Fitness30

– Webinar recording: Modeling Anti-tumor Function of Human T Cells withxCELLigence RTCA eSight– Agilent xCELLigence application note: Metabolic Preconditioning Improves
Engineered T Cell Fitness and Function– Agilent xCELLigence brochure: Measure Cell Movement, Health, andFunction with xCELLigence RTCA eSight

31

Macrophage-mediated phagocytosis
Macrophages are important effector cells of innate immunity. Depending on
the tissue microenvironment, tumor-associated macrophages (TAMs) candifferentiate into either cytotoxic (M1) or tumor-promoting (M2) states.
While cytotoxic M1 macrophages are typically induced by IFN-γ alone or inconcert 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) isa 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 ofboth differentiated U937 human monocytes (A) and activated ANA-1 murine
macrophages (B) are enhanced in the presence of TSP1.
A

80

Cytolysis (%)

Using xCELLigence to study
macrophage-mediatedphagocytosis

60

U937
U937 + sTSP1 (5 µg/mL)

40
20
0

0

12

18

24

36

Time (hours)

B

50

Cytolysis (%)

40

ANA-1
ANA-1 + sTSP1 (5 µg/mL)

30
20
10
0

0

6

12

18

Time (hours)

Figure 13. Secreted glycoprotein TSP1 increases macrophage/monocyte-mediated tumoricidal
activity. MDA-MB-231 breast adenocarcinoma target cells were seeded in Agilent E-Plates andincubated 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 describedin 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

32

Selected publications

1.

Baris, E. et al. Varenicline Prevents LPS-Induced Inflammatory Response via
Nicotinic Acetylcholine Receptors in RAW 264.7 Macrophages. Front. Mol.
Biosci. 2021, 8, 721533 doi: 10.3389/fmolb.2021.721533 (Izmir Universityof Economics)

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
E-Deficient Mice by Inducing Macrophage Autophagy: The Role of thePI3K-Akt-mTOR Pathway. Front. Pharmacol. 2021, 12, 724670 doi: 10.3389/
fphar.2021.724670 (University of Macau)

4.

Rodriguez-Garcia, A. et al. CAR-T Cell-Mediated Depletion of
Immunosuppressive Tumor-Associated Macrophages Promotes Endogenous
Antitumor Immunity and Augments Adoptive Immunotherapy. Nat. Commun.
2021, 12(1), 877 doi: 10.1038/s41467-021-20893-2 (University ofPennsylvania)

5.

Guo, L. et al. Lipopolysaccharide-Anchored Macrophages Hijack Tumor
Microtube Networks for Selective Drug Transport and Augmentation of
Antitumor Effects in Orthotopic Lung Cancer. Theranostics 2019, 9(23),6936–6948 doi: 10.7150/thno.37380 (Sun Yat-sen University)

6.

Barrett, T. J. et al. Platelet Regulation of Myeloid Suppressor of Cytokine
Signaling 3 Accelerates Atherosclerosis. Sci. Transl. Med. 2019, 11(517),
eaax0481. doi: 10.1126/scitranslmed.aax0481 (New York University Schoolof Medicine)7.

Recio, C. et al. Activation of the Immune-Metabolic Receptor GPR84
Enhances Inflammation and Phagocytosis in Macrophages. Front. Immunol.
2018, 9, 1419 doi: 10.3389/fimmu.2018.01419 (University of Oxford)

8.

Cooks, T. et al. Mutant p53 Cancers Reprogram Macrophages to Tumor
Supporting Macrophages Via Exosomal miR-1246. Nat. Commun. 2018, 9(1),771 doi:10.1038/s41467-018-03224-w (National Institutes of Health)9.

Soto-Pantoja, D. R. Unfolded Protein Response Signaling Impacts
Macrophage Polarity to Modulate Breast Cancer Cell Clearance andMelanoma Immune Checkpoint Therapy Responsiveness. Oncotarget 2017,8(46), 80545–80559 doi: 10.18632/oncotarget.19849 (Wake Forest Schoolof Medicine)

10. Hoefert, S. et al. Altered Macrophagic THP‑1 Cell Phagocytosis and Migrationin Bisphosphonate‑Related Osteonecrosis of the Jaw (BRONJ). Clin. Oral
Investig. 2016, 20(5), 1043–54 doi: 10.1007/s00784-015-1584-3 (University
Hospital Tuebingen)
11. Pirilä, E. et al. Macrophages Modulate Migration and Invasion of Human
Tongue Squamous Cell Carcinoma. PLoS One 2015, 10(3), e0120895 doi:
10.1371/journal.pone.0120895 (University of Oulu)
12. Shi, Y. et al. Trastuzumab Triggers Phagocytic Killing of High HER2 Cancer
Cells In Vitro and In Vivo b Interaction with Fcγ Receptors on Macrophages.
J. Immunol. 2015 May 1, 194(9), 4379–86.

33

13. Halai, R. et al. Derivation of Ligands for the Complement C3a Receptor fromthe C-terminus of C5a. Eur. J. Pharmacol. 2014, 745, 176–181. doi: 10.1016/j.
ejphar.2014.10.041 (Princeton University)
14. Cook, K. L. et al. Hydroxychloroquine Inhibits Autophagy to Potentiate
Antiestrogen Responsiveness in ER+ Breast Cancer. Clin. Cancer Res. 2014,20(12), 3222–32. doi: 10.1158/1078-0432.CCR-13-3227 (Georgetown
University Medical Center, NIH)
15. Rietkötter, E. et al. Zoledronic Acid Inhibits Macrophage/Microglia-Assisted
Breast Cancer Cell Invasion. Oncotarget 2013, 4(9), 1449–1460. doi:
10.18632/oncotarget.1201 (University Medical Center Göttingen)
16. Iqbal, A J. et al. A Real Time Chemotaxis Assay Unveils Unique Migratory
Profiles Amongst Different Primary Murine Macrophages. PLoS One 2013,
8(3), e58744. doi: 10.1371/journal.pone.0058744 (University of Oxford)
17. Martin‑Manso, G. et al. Thrombospondin 1 Promotes Tumor Macrophage
Recruitment and Enhances Tumor Cell Cytotoxicity of Differentiated U937
cells. Cancer Res. 2008, 68(17), 7090–9. doi: 10.1158/0008-5472.CAN-080643 (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 Cytometry34

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 atarget 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‑mediatedcytotoxicity (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, whichmust 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 throughperforin/granzyme‑mediated lysis. Owing to this capacity, NK cells are being
investigated for the purposes of immunotherapy.

35

Using xCELLigence to study
NK cell-mediated cytolysis

Figure 14 shows use of the xCELLigence RTCA to measure target tumor cellkilling by NK cells at low, physiologically relevant E:T ratios in vitro. Results showthat AZD1775, a small molecule inhibitor of WEE1 kinase, was able to sensitize
tumor cells to NK cell lysis.
A

B

C

D

E

F

G

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 thetime 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 theleft. On the right, for comparison, KIL (black line) or sorted WT B6 NK cells (gray line) were used toinduce 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 representativeof 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 acopy 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.

36

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 impedancemonitoring by the xCELLigence system is sensitive enough to detect target cellkilling even at low E:T ratios. For plotting purposes, %cytolysis is readily calculatedusing a simple formula:%Cytolysis =2.0(Cell Indexno effector – Cell Indexeffector)
Cell Indexno effector

× 100

E:T

A

16:1
8:1
4:1
2:1
1:1
0.5:1
No effector

1.8

Normalized Cell Index

1.6
1.4
Add NK 92

1.2
1.0
0.8
0.6
0.4
0.2
0
40

42

44

46

48

50

52
54
56
Time (hours)

58

60

62

64

66

68

B
90

%Cytolysis

70

2 hours
4 hours
8 hours

50
30
10
-10

No
effector

0.5:1

1:1

2:1

4:1

8:1

16:1

E:T

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.

37Selected publications

1.

Kararoudi, M. N. et al. Optimization and validation of CAR transduction into
human primary NK cells using CRISPR and AAV. Cell Rep. Methods 2022,2(6), 100236. doi: 10.1016/j.crmeth.2022.100236 (Nationwide Children’s
Hospital; Ohio State University)2.

Klapdor, R. et al. NK Cell-Mediated Eradication of Ovarian Cancer Cells with a
Novel Chimeric Antigen Receptor Directed against CD44. Biomedicines 2021,
9(10), 1339. doi: 10.3390/biomedicines9101339 (Hannover Medical School)

3.

Morimoto, T. et al. CRISPR-Cas9-Mediated TIM3 Knockout in Human
Natural Killer Cells Enhances Growth Inhibitory Effects on Human Glioma
Cells. Int. J. Mol. Sci. 2021, 22(7), 3489. doi: 10.3390/ijms22073489 (NaraMedical 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.

Lee, M.Y. et al. Chimeric antigen receptor engineered NK cellularimmunotherapy overcomes the selection of T-cell escape variant cancer
cells. J. Immunother. Cancer 2021, 9(3), e002128. doi: 10.1136/jitc-2020002128 (National Institutes of Health)6.

Banu, N. et al. B7-H6, an immunoligand for the natural killer cell activating
receptor NKp30, reveals inhibitory effects on cell proliferation and migration,
but not apoptosis, in cervical cancer derived-cell lines. BMC Cancer 2020,20(1), 1083. doi: 10.1186/s12885-020-07608-4 (Universidad de Guadalajara)

7.

Robbins, Y. et al. Tumor control via targeting PD-L1 with chimeric antigen
receptor modified NK cells. Elife 2020, 9, e54854. doi: 10.7554/eLife.54854(National Institutes of Health)8.

Sayitoglu, E. C. et al. Boosting Natural Killer Cell-Mediated Targeting of
Sarcoma Through DNAM-1 and NKG2D. Front. Immunol. 2020, 11, 40. doi:
10.3389/fimmu.2020.00040 (Nova Southeastern University)

9.

Zhang, X. et al. Low-Dose Gemcitabine Treatment Enhances
Immunogenicity and Natural Killer Cell-Driven Tumor Immunity in Lung
Cancer. Front. Immunol. 2020, 11, 331. doi: 10.3389/fimmu.2020.00331(University of Science and Technology of China)

10. Frazao, A. et al. BRAF inhibitor resistance of melanoma cells triggers
increased susceptibility to natural killer cell-mediated lysis. J. Immunother.
Cancer 2020, 8(2), e000275. doi: 10.1136/jitc-2019-000275 (Universitéde Paris)
11. Clar, K. L. et al. Inhibition of NK Reactivity Against Solid Tumors by
Platelet-Derived RANKL. Cancers (Basel) 2019, 11(3), 277. doi: 10.3390/
cancers11030277 (German Cancer Consortium (DKTK) and Research Center(DKFZ))
12. Klapdor, R. et al. Characterization of a Novel Third-Generation Anti-CD24CAR against Ovarian Cancer. Int. J. Mol. Sci. 2019, 20(3), 660. doi: 10.3390/
ijms20030660 (Hannover Medical School)
13. Ao, X. et al. Anti-αFR CAR-engineered NK-92 Cells Display Potent Cytotoxicity
Against αFR-positive Ovarian Cancer. J. Immunother. 2019, 42(8), 284–296.
doi: 10.1097/CJI.0000000000000286 (Third Military Medical University)
14. Du, X. et al. CD226 regulates natural killer cell antitumor responses via
phosphorylation-mediated inactivation of transcription factor FOXO1. Proc.
Natl. Acad. Sci. USA 2018, 115(50), E11731–E11740. doi: 10.1073/
pnas.1814052115 (Genentech, Inc.)38

15. 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(1), 59. doi: 10.1186/s40425018-0374-2 (National Institutes on Deafness and Other Communication
Disorders, National Institutes of Health; Johns Hopkins School of Medicine)
16. Fasbender, F.; Watzl, C. Impedance‑Based Analysis of Natural Killer Cell
Stimulation. Scientific Reports 2018, 8(1), 4938. doi: 10.1038/s41598-01823368-5 (Technical University Dortmund (IfADo))
17. Pantic, J. M. et al The Frog Skin Host‑Defense Peptide Frenatin 2.1S
Enhances Recruitment, Activation and Tumoricidal Capacity of NK Cells.
Peptides 2017, 93, 44–50. doi: 10.1016/j.peptides.2017.05.006 (University ofKragujevac)
18. Fregni, G. et al. Phenotypic and Functional Characteristics of Blood Natural
Killer Cells from Melanoma Patients at Different Clinical Stages. PLoS ONE
2013, 8(10). 10.1371/journal.pone.0076928 (University Paris Descartes)
19. Park, K. H. et al. Evaluation of NK Cell Function by FlowcytometricMeasurement and Impedance Based Assay Using Real‑Time Cell Electronic
Sensing System. Biomed. Res. Int. 2013, 210726. doi: 10.1155/2013/210726(Catholic University of Korea)
20. Moodley, K. et al. Real‑Time Profiling of NK Cell Killing of Human Astrocytes
Using xCELLigence Technology. J. Neurosci. Methods 2011, 200(2), 173–80.
doi: 10.1016/j.jneumeth.2011.07.005 (University of Auckland)

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 Measurementof Natural Killer Cell Activity and Antibody-Dependent Cell-MediatedCytotoxicity– Agilent xCELLigence application note: Evaluating Functional Potency of
Immunotherapies Targeting Liquid Tumors

39

Oncolytic viruses
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 inrecent years using wildtype (WT) and genetically engineered viruses.
Analyzing cancer cell killing with high sensitivity and without the need forlabels/modifications, the xCELLigence RTCA instruments allow the interaction
between viruses and target cells to be studied under conditions thatapproximate 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 lungcancer 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 areseen 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 ismuch less efficient at killing the cancer cells, requiring five days to achieve full cellkilling 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.

40

500 PPC
100 PPC
20 PPC
4 PPC
0.8 PPC
Mock infected

Cell Index

6 EnAd
4
2
0
-24

0

24

48

72

96

120

0

24

48

72

96

120

0

24

48

Cell Index

6 Ad11p4
2
0-24

Cell Index

6 Ad5
4
2
0
-24

72

96

120

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 acopy 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.

Selected publications

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 Carcinoma. Cancers (Basel) 2022, 14(11), 2761. doi: 10.3390/
cancers14112761 (University Hospital Tuebingen)2.

Ferreira, T. et al. Oncolytic H-1 Parvovirus Hijacks Galectin-1 to Enter Cancer
Cells. Viruses 2022, 14(5), 1018. doi: 10.3390/v14051018 (Laboratory of
Oncolytic Virus Immuno-Therapeutics, German Cancer Research Centre)

3.

Tian, L. et al. Targeting Fc Receptor-Mediated Effects and the “Don’t Eat Me”
Signal with an Oncolytic Virus Expressing an Anti-CD47 Antibody to Treat
Metastatic Ovarian Cancer. Clin. Cancer Res. 2022, 28(1), 201–214. doi:
10.1158/1078-0432.CCR-21-1248 (City of Hope National Medical Center)

4.

Zhang, C. et al. Oncolytic Adenovirus-Mediated Expression of
Decorin Facilitates CAIX-Targeting CAR-T Therapy Against Renal Cell
Carcinoma. Mol. Ther. Oncolytics 2021, 24, 14–25. doi: 10.1016/j.
omto.2021.11.018 (Xuzhou Medical University)

5.

Khalique, H. et al. Oncolytic Herpesvirus Expressing PD-L1 BiTE for Cancer
Therapy: Exploiting Tumor Immune Suppression as an Opportunity for
Targeted Immunotherapy. J. Immunother. Cancer 2021, 9(4), e001292. doi:
10.1136/jitc-2020-001292 (University of Oxford)

6.

Kulkarni, A. et al. Oncolytic H-1 Parvovirus Binds to Sialic Acid on Laminins for
Cell Attachment and Entry. Nat. Commun. 2021, 12(1), 3834. doi: 10.1038/
s41467-021-24034-7 (Laboratory of Oncolytic Virus Immuno-Therapeutics,
German Cancer Research Centre)

41

7.

Hamdan, F. et al. Novel Oncolytic Adenovirus Expressing Enhanced
Cross-Hybrid IgGA Fc PD-L1 Inhibitor Activates Multiple Immune Effector
Populations Leading to Enhanced Tumor Killing In Vitro, In Vivo and with
Patient-Derived Tumor Organoids. J. Immunother. Cancer 2021, 9(8),e003000. doi: 10.1136/jitc-2021-003000

8.

Ma, J. et al. Characterization of Virus-Mediated Immunogenic Cancer Cell
Death and the Consequences for Oncolytic Virus-Based Immunotherapy ofCancer. Cell Death. Dis. 2020, 11(1), 48. doi: 10.1038/s41419-020-2236-3(Uppsala University)

9.

Ammour, Y. et al. The Susceptibility of Human Melanoma Cells to Infection
with the Leningrad-16 Vaccine Strain of Measles Virus. Viruses 2020, 12(2),173. doi: 10.3390/v12020173 (I.I. Mechnikov Research Institute for Vaccines
and Sera)

10. Kloker, L. D. et al. Oncolytic Vaccinia Virus GLV-1h68 Exhibits ProfoundAntitumoral Activities in Cell Lines Originating from Neuroendocrine
Neoplasms. BMC Cancer 2020, 20(1), 628. doi: 10.1186/s12885-020-07121-8(University Hospital Tuebingen)
11. Ferreira, T. et al. Oncolytic H-1 Parvovirus Enters Cancer Cells throughClathrin-Mediated Endocytosis. Viruses 2020, 12(10), 1199. doi: 10.3390/
v12101199 (Laboratory of Oncolytic Virus Immuno-Therapeutics, German
Cancer Research Centre)
12. Lacroix, J. et al. Preclinical Testing of an Oncolytic Parvovirus in Ewing
Sarcoma: Protoparvovirus H-1 Induces Apoptosis and Lytic Infection In Vitro
but Fails to Improve Survival In Vivo. Viruses 2018, 10(6), 302. doi: 10.3390/
v10060302 (German Cancer Research Center)
13. Dyer, A. et al. Oncolytic Group B Adenovirus Enadenotucirev Mediates
Non-apoptotic Cell Death with Membrane Disruption and Release of
Inflammatory Mediators. Mol. Ther. Oncolytics 2016, 4, 18–30. doi: 10.1016/j.
omto.2016.11.003 (University of Oxford)
14. Freedman, J. D. et al. Oncolytic adenovirus expressing bispecific antibody
targets T-cell cytotoxicity in cancer biopsies. EMBO Mol. Med. 2017, 9(8),1067–1087. doi: 10.15252/emmm.201707567 (University of Oxford)
15. Dyer, A. et al. Oncolytic Group B Adenovirus Enadenotucirev Mediates
Non‑Apoptotic Cell Death with Membrane Disruption and Release of
Inflammatory Mediators. Mol. Ther. Oncolytics 2016, 4, 18–30. doi: 10.1016/j.
omto.2016.11.003 (University of Oxford)
16. Ellerhoff, T. P. et al. Novel Epi‑Virotherapeutic Treatment of Pancreatic
Cancer Combining the Oral Histone Deacetylase Inhibitor Resminostat With
Oncolytic Measles Vaccine Virus. Int. J. Oncol. 2016, 49(5), 1931–1944.
doi: 10.3892/ijo.2016.3675 (University Hospital Tuebingen)
17. Schneider, C. C. et al. Metabolic Alteration – Overcoming Therapy Resistancein 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
Associated with Repression of Master Regulators of Early Neurogenesis.
Int. J. Cancer 2014, 134(3), 703–16. doi: 10.1002/ijc.28386 (German Cancer
Research Center (DKFZ))

42

19. El‑Andaloussi, N. et al. Generation of an Adenovirus‑Parvovirus Chimera with
Enhanced Oncolytic Potential. J. Virol. 2012, 86(19), 10418–31. doi: 10.1128/
JVI.00848-12 (German Cancer Research Center (DKFZ))
20. Fecker, L. F. et al. Efficient and Selective Tumor Cell Lysis and Inductionof Apoptosis in Melanoma Cells by a Conditional Replication‑Competent
CD95L Adenovirus. Exp. Dermatol. 2010, 19(8), e56–66. doi: 10.1111/j.16000625.2009.00977.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

43

T Cell-mediated cytolysis
By seeking out and destroying infected cells directly, CD8+ T lymphocytes playa critical role in adaptive immune response. Every CD8+ T cell clone expresses
a unique variant of specialized receptor, the T cell receptor (TCR), that canrecognize 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 thistumor 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 isoften a critical need to assess the functional cytotoxicity of these cells throughkilling assays. Measuring cytolytic activity through the chromium‑51 (51Cr) releaseassay 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 ofa 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 ofCD8+ T cells added (Figure 17A). Side-by-side comparison with the 51Cr releaseassay 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 oftumor cell killing) make this assay especially attractive.

44

1.5

A

Tumor:Tcell ratio
No T cells
1:1
1:2.5

1.0
Cell Index

1:5
1:10
0.5

1:20
1:40

0

1

3

5

7

9

11

Time after T cell addition (hours)
100

Impedance assay
Chromium release assay

B% Lysis

80

60

40

20

0

1:40

1:20

1:10
1:5
Tumor:Tcell ratio

1:2.5

1:1.25Figure 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 ofa reduction in the number, size, or attachment quality of the SKBR3 tumor cells (A). Plotting thepercentage of tumor cell lysis, as determined by an Agilent xCELLigence RTCA versus the standard
51
Cr release assay, demonstrates RTCA to be the more sensitive method (B). Figure adapted from:
J. Vis. Exp. 2012 Aug 8, (66), e3683.10

Selected publications

1.

Stirling, E. R. et al. Targeting the CD47/thrombospondin-1 signaling axis
regulates immune cell bioenergetics in the tumor microenvironment topotentiate 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 HarborHigh 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.
doi: 10.3390/cells10102631 (Cartherics Pty Ltd.)

5.

Otano, I. et al. CD137 (4-1BB) costimulation of CD8+ T cells is morepotent when provided in cis than in trans with respect to CD3-TCR
stimulation. Nat. Commun. 2021, 12(1), 7296. doi: 10.1038/s41467-02127613-w (Clínica Universidad de Navarra)

45

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/
fimmu.2021.645131 (Copenhagen University Hospital Herlev)

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 andT-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-Engineered T-Cell
Activity through the Covalent Attachment of Targeting Ligands to a
Universal Immune Receptor. J. Am. Chem. Soc. 2020, 142(14), 6554–6568.
doi: 10.1021/jacs.9b11622 (University of Pennsylvania)

10. Fischer, C. et al. Vaccine-Induced CD8 T Cells Are Redirected with PeptideMHC Class I-IgG Antibody Fusion Proteins to Eliminate Tumor Cells In
Vivo. MAbs 2020, 12(1), 1834818. doi: 10.1080/19420862.2020.1834818(Roche Innovation Center)
11. Westergaard, M. C. W. et al. Tumour-reactive T Cell Subsets in theMicroenvironment of Ovarian Cancer. Br. J. Cancer 2019, 120(4), 424–434.
doi: 10.1038/s41416-019-0384-y (University of Copenhagen)12. Bardwell, P. D. et al. Potent and Conditional Redirected T Cell Killing of Tumor
Cells Using Half DVD-Ig. Protein Cell 2018, 9(1), 121–129. doi: 10.1007/
s13238-017-0429-z (AbbVie Bioresearch Center)13. Ueda, O. et al. Entire CD3ε, δ, and γ Humanized Mouse to Evaluate Human
CD3-Mediated Therapeutics. Sci. Rep. 2017, 7, 45839. doi: 10.1038/
srep45839 (Chugai Pharmaceutical Co., Ltd.)
14. Morisada, M. et al. Dose‑dependent Enhancement of T‑Lymphocyte
Priming and CTL Lysis Following Ionizing Radiation in an Engineered
Model of Oral Cancer. Oral Oncol. 2017, 71, 87–94. doi: 10.1016/j.
oraloncology.2017.06.005 (National Institute on Deafness and Other
Communication Disorders, NIH)
15. Hillerdal, V. et al. Avidity Characterization of Genetically Engineered T‑Cells
with Novel and Established Approaches. BMC Immunol. 2016, 17(1), 23.
doi: 10.1186/s12865-016-0162-z (Uppsala University)
16. Schirmer, D. et al. Transgenic Antigen‑Specific, HLA‑A*02, 01‑Allo‑Restricted
Cytotoxic T Cells Recognize Tumor‑Associated Target Antigen
STEAP1 with High Specificity. Oncoimmunology 2016, 5(6), e1175795.
doi: 10.1080/2162402X.2016.1175795 (Technical University of Munich)
17. Schmittnaegel, M. et al. Committing Cytomegalovirus‑Specific CD8 T Cells
to Eliminate Tumor Cells by Bifunctional Major Histocompatibility ClassI Antibody Fusion Molecules. Cancer Immunol. Res. 2015, 3(7), 764–76.
doi: 10.1158/2326-6066.cir-15-0037 (Roche Innovation Center Penzberg)
18. Soto‑Pantoja, D. R. et al. CD47 in the Tumor Microenvironment Limits
Cooperation Between Antitumor T‑Cell Immunity And Radiotherapy. Cancer
Res. 2014, 74(23), 6771–83. doi: 10.1158/0008-5472.CAN-14-0037-T(National Cancer Institute, NIH)

46

19. Pham, P. V. et al. A Simple In Vitro Method for Evaluating Dendritic Cell‑Based
Vaccinations. Onco. Targets Ther. 2014, 7, 1455–64. doi: 10.2147/OTT.
S67057 (Vietnam National University)
20. Peper, J. K. et al. An Impedance‑Based Cytotoxicity Assay for Real‑Time
and Label‑Free Assessment of T‑Cell‑Mediated Killing of Adherent Cells.
J. Immunol. Methods 2014, 405, 192–8. doi: 10.1016/j.jim.2014.01.012(University of Tübingen, German Cancer Consortium (DKFZ))
21. Erskine, C. L. et al. Determining Optimal Cytotoxic Activity of Human
Her2neu Specific CD8 T Cells by Comparing the Cr51 Release Assay to
the xCELLigence System. J. Vis. Exp. 2012, (66), e3683. doi: 10.3791/3683(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 thexCELLigence 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 withxCELLigence RTCA eSight

47

Liquid tumor killing assays
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 thestandard 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 areprominent 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 precoatedwith 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 witheffector 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 generatea 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 thewells, 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 iseasily detected even at low effector:target ratios. This sensitivity greatly exceedsthat of traditional release assays which require high effector:target ratios thatare 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 fromthe same person are in progress.

48

An important question is whether the physical immobilization of B cells throughantibody 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 observedby 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 bytraditional assays.

A

Normalized Cell Index

B cellanti-CD40

Electrode

1.2
1.0
0.8
0.6
0.4
0.2
0

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

D
Coated wells + B cells
Uncoated wells + B cells
Coated wells + NK-92 cells
Uncoated wells + NK-92 cells
B cell seeding
NK-92 cell seeding10

20 30 40
Time (hours)

100%Cytolysis

80

50

Agilent xCELLigence
Flow cytometry

60
40
20

0

5

20

25

30

35

Time (hours)

40

45

50

1:
0. 1
75
:1
0.
5:
0. 1
25
:1
0.
1:
1
0:
1

0

2:
1

Cell Index

B
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0

NK-92:Raji ratio
E:T = 0:1
(untreated)

C

NK-92:Raji ratio

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 proliferateon, 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).

49

In a second example of liquid tumor cell killing, Figures 19A and 19B show thedestruction 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 timeand effector cell concentration. Similar to the B cell killing assay, the destructionof K562 cells is detectable even at low effector:target ratios.

2.0

A

NK-92:K562 ratio
0:1 (untreated)
0.2:1
0.4:1
0.6:1
0.8:1
1:1

Effector cell addition

Cell Index

1.5
1.0
0.5
0

0

50

100

150

100

150

Time (hours)
100

B%Cytolysis

80
60

Effectorcell
40 addition
20
0

0

50
Time (hours)

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 afunction of time. Error bars in both are standard deviation.

The liquid tumor killing assays described here are being used in industrial andacademic 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.

Selected publications

50

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 Downmodulationand Leukemia Relapse with T Lymphocytes Secreting Anti-CD19 T-cell
Engagers. Cancer Immunol. Res. 2022, 10(4), 498–511. doi: 10.1158/23266066.CIR-21-0853 (Hospital Universitario12 de Octubre)

3.

Kararoudi, M. N. et al. Optimization and Validation of CAR Transduction into
Human Primary NK cells Using CRISPR and AAV. Cell Rep. Methods 2022,2(6), 100236. doi: 10.1016/j.crmeth.2022.100236 (Nationwide Children’s
Hospital, Ohio State University)

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; Universityof Southern California Keck School of Medicine)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/s41467-02020696-x (Chinese People’s Liberation Army General Hospital)

7.

Golubovskaya, V. et al. Novel CD37, Humanized CD37 andBi‑Specific Humanized CD37-CD19 CAR-T Cells Specifically Target
Lymphoma. Cancers (Basel) 2021, 13(5), 981.
doi: 10.3390/cancers13050981 (Promab Biotechnologies)

8.

Roselli, E. et al. 4-1BB and Optimized CD28 Co-Stimulation Enhances
Function of Human Mono-Specific and Bi-Specific Third-Generation CAR T
Cells. J. Immunother. Cancer 2021, 9(10), e003354. doi: 10.1136/jitc-2021003354 (H Lee Moffitt Cancer Center)9.

Berahovich, R. et al. Hypoxia Selectively Impairs CAR-T Cells In
Vitro. Cancers (Basel) 2019, 11(5), 602. doi: 10.3390/cancers11050602(ProMab Biotechnologies)

10. Xi, B. et al. A Real-time Potency Assay for Chimeric Antigen Receptor T Cells
Targeting Solid and Hematological Cancer Cells. J. Vis. Exp. 2019, (153),
10.3791/59033. doi:10.3791/59033 (ProMab Biotechnologies)
11. Hou, A. J. TGF-β-Responsive CAR-T Cells Promote Anti-Tumor Immune
Function. Bioeng. Transl. Med. 2018, 3(2), 75–86. doi: 10.1002/btm2.10097(University of California, Los Angeles)
12. Cerignoli, F. et al. In Vitro Immunotherapy Potency Assays Using Real‑Time
Cell Analysis. PLoS One 2018, 13(3), e0193498. doi: 10.1371/journal.
pone.0193498 (ACEA Biosciences)

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 time51

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