Agilent Cell Analysis Application Note

Application Note

Cell Analysis

Dynamic Monitoring of Receptor
Tyrosine Kinase Activation in

LivingCells

xCELLigence real-time cell analysis

Author

Brandon Lamarche,
JoyceVelez, and Leyna Zhao
Agilent Technologies, Inc.

Introduction

Over 500 different protein kinases have been identified, constituting ~1.7% of the
human genome. Of these, 11% are known to be receptor tyrosine kinases (RTKs).1
RTKs and their growth factor ligands mediate important cellular processes including
proliferation, survival, differentiation, metabolism, motility, and gene expression.
Loss of regulation of RTK expression or activity has been implicated in initiation
and progression of cancer, inflammation, diabetes, and cardiovascular disease.
Their central role in these cellular processes and disease states has made RTKs
an attractive and important target for the development of inhibitors that could
be therapeutic for these diseases. Several antibody- and small molecule-based
inhibitors specific for various RTKs have been approved by the FDA for the treatment
of different cancers.

RTKs are membrane receptors that
contain an intracellular kinase domain,
which transfers a phosphate group from
an ATP molecule to the hydroxyl group
on tyrosine residues. When binding to

ligands, RTKs dimerize or oligomerize,

causing autophosphorylation
and increased activation of their
intrinsic kinase activity. This leads to
phosphorylation of several downstream
effector proteins, resulting in activation
of multiple signaling pathways.
These pathways include activation of
Ras/MAPK, phosphoinositide-3 kinase,
and PLC pathways. Another pathway
activated is the phosphorylation of
effector proteins such as Src, Paxillin,
and FAK. Activation or phosphorylation
of these proteins leads to cytoskeletal
changes including membrane ruffling,
lamellipodia, and filopodia formation.2
These cellular changes are a result of
actin remodeling and are mediated by
the activities of small GTPases Rac, Rho,
and Cdc42.3

Numerous screening platforms have
been developed for the identification of
inhibitors for RTK. They are generally
subdivided into:

– Antibody-dependent technologies,

including AlphaScreen, TR-FRET, FP,
TRF, SPA, Luminex, and ELISA

– Antibody-independent methods, such

as incorporation of radioactivity,
ATP consumption, and technologies

based on change of substrate size

and charge

Although these technologies offer
some advantages, they are limited by
one or more of the following factors:

complicated and tedious optimization

steps, limited substrate capacity, assay
component interference, and expensive
assay components. All of these issues
can affect the signal, throughput, time,
and utility of the assay.

The xCELLigence system offers a unique
cell sensor arrangement, with electrodes
integrated into the wells of a microplate
(E-Plate). These sensors are arrayed in a
design covering 80% of the well surface
area, allowing for sensitive, quantitative
detection of cellular changes. Signals
from these sensors are relayed in real
time to the xCELLigence to monitor

and analyze the kinetic aspects of
cellularbehavior.

The signals relayed to the system are
impedance changes resulting from an
ionic environment created by application
of an electric field. Disruption of this
ionic environment on the sensor
surface, due to the presence of cells or
changes in cell morphology, can cause
changes in measured impedance.
This is then converted to a Cell Index
value. The extent of the cell-electrode
impedance response depends on the
quality of the cell attachment and the
sensor area covered by the cell. When
cell number or degree of attachment
increases, it causes a corresponding
increase in measured impedance value,
and, therefore, in observed Cell Index.
This system has been successfully
used in monitoring cell proliferation
and cytotoxicity, cell adhesion, and
G-protein-coupled receptor function.

This application note highlights
the development and utility of an
alternative RTK assay that uses the
impedance-based system. This assay
addresses several of the limitations
in previous methods and provides a
simple and user-friendly platform for

identification and further characterization

of RTK inhibitors.

It is known that growth factor binding to
RTK results in immediate morphological
changes. The impedance-based system
makes it possible to quantitatively
assay these cellular changes and,
hence, measure receptor tyrosine kinase
activity and function. Experiments
described here show that these cell

assays are specific, robust, reproducible,
and in concurrence with other RTK
cell-based assays, such as ELISA. The
impedance-based system was used
to screen a small, diverse library of
inhibitors and a collection of kinase
inhibitors. This screen identified a
specific and potent EGFR inhibitor.
The assay was also used to generate
dose-response curves, further

characterizing the inhibitor.

Materials and methods

Cell culture and reagents

COS7 cells were acquired from ATCC.
They were maintained in DMEM
supplemented with 10% fetal bovine
serum and incubated at 37 °C with
5% CO2. Cells were plated in E-Plates

at 1×104 cells per well and incubated

overnight. On the day of the assay,
cells were serum-starved in DMEM
supplemented with 0.25% BSA for a total
of 4 hours. If pretreated with inhibitors,
cells were incubated with the inhibitors
during the last hour of serum starvation
and then stimulated with growth factors.
Inhibitors (Calbiochem) and LOPAC

enzyme inhibitor ligand set (Sigma) were

resuspended and stored according to
manufacturers’ instructions.

RTK assays using impedance
technology

Cells were continuously monitored with
the xCELLigence system. RTK-induced
effects were detected as changes in

impedance and expressed in CellIndex

units.

ELISA

Cells were plated on E-Plates at

1×104cells per well and incubated

overnight. On the day of assay, cells were
serum-starved in DMEM supplemented
with 0.25% BSA for a total of 4 hours.
If pretreated with inhibitors, cells were
incubated with the inhibitors during
the last hour of serum starvation and

2

then stimulated with growth factor

Normalized Cell Index

2.0

Normalized Cell Index

r

for 15minutes. After growth factor

stimulation, cells were washed twice
with cold PBS and lysed. EGFR and
phospho-EGFR (1068) were detected by
ELISA at 450 nm.

Statistical and data analysis

All dose-response curves were generated
by plotting the average %control
(±standard deviation) versus ligand or
inhibitor concentrations. The average
%control was calculated relative to
samples treated with growth factor
alone without inhibitor. Samples were
measured in quadruplicate. The EC50
for ligands and IC50 for inhibitors were
determined from a fitted curve generated
by XLfit 4.0.

Results and discussion

Specificity of cellular response to EGF
and insulin treatments

Cells plated in the E-Plates were
monitored from the time of plating to
the end of the experiment. This allowed
the cells and assay conditions to be
monitored constantly before and during

the experiment. 1×104 COS7 cells in

E-Plates were serum-starved for a total
of 4 hours and stimulated with 25 ng/mL
EGF or insulin, then monitored every
minute from the time of ligand addition.
Ligand addition resulted in a rapid and

transient increase in CellIndex for both
EGF- and insulin-treated cells (Figure1A).

This increase was immediately
followed by a decrease in Cell Index,
with EGF-treated cells showing a faster
decrease than insulin-treated cells. The
transient increase in Cell Index was a
result of cytoskeletal rearrangements
due to growth factor treatment,
which is a well-documented effect of

RTKactivation.2

To characterize the specificity of these

responses to ligand treatment, cells
were pretreated for 1 hour with 10 µM
of the EGFR inhibitor (EGFRI), 4557W,
before addition of EGF or insulin. Since
the inhibitor was specific to EGFR,
application of the EGFRI should only
affect cellular changes induced by EGF

The absence of cell response in
EGF-treated cells was a result of the
specific inhibition of EGFR and its
signaling pathways by the EGFRI. The
specificity of this inhibitor and ligand
response was demonstrated by the
lack of effect on the transient Cell Index

increase in insulin-treated cells.
treatment. Indeed, after ligand addition,
insulin-treated cells showed the transient
increase in Cell Index, but EGF-treated
cells did not (Figure 1B).

A

1.8

1.6

1.4

1.2

1.0

0.8
0 2 4 6 8 10 12

Time (hours)

2.0

B

1.8

1.6

1.4

1.2

1.0

0.8
0 2 4 6 8 10 12

Time (hours)

Figure 1. Assessment of specificity of cellular response to EGF and insulin treatments.
COS7 cells were pretreated for 1 hour with either a specific EGFR inhibitor or vehicle. Cells
were then stimulated with insulin or EGF. (A) Cells treated with insulin or EGF showed a
characteristic rise in Cell Index. (B) When pretreated with 10 µM EGFR inhibitor, 4557W,
the EGF response is inhibited while the insulin response remains intact.

EGF
Insulin

EGF+EGF inhibitor
Insulin+EGF inhibito

3