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The Quantification of Multiple
Signalling Pathway Proteins
in Intact Tissue Sections
By Clifford C Hoyt at
Cambridge Research
& Instrumentation (CRi)
Correlation between signalling pathway activity and clinical outcome plays
an important role in drug R&D; by enabling the accurate quantification of
multiple proteins on a per-cell basis in intact tissue, a new technology
platform will help researchers to better understand the signalling pathways
implicated in a given disease.
In order to obtain an improved determination of the
specific causes of a given disease, a goal of many
researchers is to achieve a better understanding of the
mechanisms of various signalling pathways. Being able
to reveal correlations between signalling pathway
activity and clinical outcome would better support
target validation, trial design, patient selection,
response assessment and – if trials are successful – the
diagnostic component of theranostics. Importantly, the
predictive power of measurements of protein expression
depends on the precision and accuracy of tissue analysis
tools. For example, many techniques deployed today,
such as those based on microarray detection or analysis
of sample lysates, provide data that are in fact averages
from volumes of tissue – including many cells that are
Figure 1: Illustration
of signalling pathways
in a cell, in this case for
apoptotic signalling in a
normal cell. Reproduced
from the University of
Delaware (1)
not of interest. These methods ‘blur-out’ key proteomic
information residing at the cellular level that relates to
the signalling states of individual cells.
THE ROLE OF SIGNAL TRANSDUCTION
PATHWAYS IN CANCER
During the course of tumour progression, cancer cells
acquire a number of characteristic alterations. These
include the capacity to proliferate independently of
exogenous growth-promoting or growth-inhibitory signals,
the tendency to invade surrounding tissues and metastasise
to distant sites, the inclination to elicit an angiogenic
response and the ability to evade mechanisms that limit cell
proliferation, such as apoptosis and replicative senescence.
These properties reflect alterations in the cellular signalling
pathways that in normal cells control cell proliferation,
motility and survival. Many of the proteins currently under
investigation as possible targets for cancer therapy are
signalling proteins that are components of these pathways.
The nature of these signalling pathways and their roles in
tumourigenesis are the subject of intense study by
pharmaceutical companies, motivated by the hope that
progress in understanding cancer as a disease will accelerate
drug development. This is a broad research topic and the
task of identifying relevant pathways, understanding them
and demonstrating correlation with outcome is a
challenging one. An additional level of complexity
arises from the fact that it is often the interrelationship between pathway proteins and their
localisation that helps characterise the pathway, rather
than the mere presence of a protein.
THREE KEY PATHWAY MARKERS
Three key pathway markers – AKT, ERK and S6 – are
widely studied and play a vital role in cancer
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Figure 2: Clinical tissue samples in a tissue microarray TMA are used in
order to confirm that staining is specific, and labels can be reliably unmixed
from autofluorescence. Row A: raw colour images of two TMA cores; Row B:
same with autofluorescence unmixed away to reveal label signals; Row C: with
inForm tissue and cell segmentations; and Item D: a ‘tissue cytometry’ scatter
plot showing relatively expression of two signalling pathway proteins, on a
per-cell basis. Samples courtesy Novartis Institutes of Biomedical Research,
Cambridge, MA, US (2)
A
C
D
Finally, s6 is a ribosomal protein involved in translation.
It is thought to play an important role in controlling cell
growth and proliferation, is a major substrate of
ribosomal protein s6 kinase and plays a role in
regulating translation of RNAs that contain an RNA 5’
terminal oligopyrimidine sequence. It is regulated by
ribosomal s6 kinase.
pS6 versus pERK
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pS6 (Allexa 647)
AKT has recently been found to play a paradoxical
role: on the one hand it increases cancer cells’ survival
capability, while on the other it blocks their motility
and invasion abilities, thereby preventing cancer
from spreading (4). Previously, it had been
presumed that one could promote cancer cell death by
inhibiting AKT; yet now, with this added complexity,
the role of AKT must be understood further so as not
to promote metastases by inhibiting AKT expression
(see Figure 1, page 48).
Activation of the ERK pathway promotes cell division.
This pathway is often up-regulated in human tumours
and is thought to fulfil multiple roles in the acquisition
of a complex malignant phenotype. Accordingly, a
specific blockade of the ERK pathway is expected to
result in not only an anti-proliferative effect, but also in
anti-metastatic and anti-angiogenic effects in tumour
cells. Recently, potent small-molecule inhibitors
targeting components of the ERK pathway have been
developed. Among them, BAY 43-9006 (Raf inhibitor),
and PD184352, PD0325901 and ARRY-142886
(MEK1/2 inhibitors) have reached the clinical trial
stage. The combination of ERK pathway inhibitors
(cytostatic agents) and conventional anticancer drugs
(cytotoxic agents) might provide an excellent basis for
the development of new chemotherapeutic strategies
against cancer.
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AUTOMATED MULTIPLEXED
TISSUE CYTOMETRY
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pERK (Allexa 555)
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pathogenesis. In the example that follows, the goal is
to provide a general-purpose signalling activity
detection kit to assess the AKT, ERK and
S6 pathways.
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Detecting pathway markers using conventional
histology or immunofluorescence is a challenge, given
the need to observe many markers simultaneously (that
is, to multiplex) in order to gain a full understanding of
the pathways involved and the relevant phenotypes.
Conversely, conventional multiplexing techniques, such
as microarrays or flow cytometry, fail to provide the
contextual information needed to confirm intracellular
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localisation; this is also a requirement in
order to confirm pathway state. What is
needed is simultaneous measurement of
multiple proteins, on a per-cell basis, set
within the context of the original anatomy.
Figure 3: Spectral unmixing
explained using examples of
four-component fluorescence
unmixing (2)
Technology now offers us the opportunity
to access this level of information by
utilising an effective, practical and reliable
platform for cytometric analysis of intact
tissue sections. This can be conceptualised
as ‘tissue cytometry’. The platform
supports
preclinical
and
clinical
studies through the integration of
multiplexed immunohistochemical (IHC)
or immunofluorescent (IF) labelling
strategies, robotic slide handling and
automated multispectral image acquisition
and analysis (see Figure 2).
The ideal imaging platform integrates:
a) easy-to-implement multiplexed staining
protocols; b) an automated slide analysis
system (such as CRi’s VectraTM system) that
can isolate marker signals from one another
and from autofluorescence; and c) patternrecognition based image-analysis software
(such as CRi’s inFormTM software) for automatically
segmenting images and extracting data from cellsof-interest.
CRi’s Vectra system is a fully integrated system that
offers robotic slide handling (capacity 200 slides),
automated image acquisition, and the flexibility to
work with IHC or IF, tissue-sections or tissue
microarrays (TMAs) (see Figure 3). The principal
scientific benefits of slide scanning (whether
multispectral or not) can, however, only be realised
when the terabytes of imagery created can be processed
automatically to produce relevant and useful
information. The powerful learn-by-example image
analysis algorithms in CRi’s inForm software provide
trainable tissue segmentation, a key component of
automated image analysis and data extraction. The
software can be trained to differentiate relevant tissue
regions (for example, malignant and normal epithelia,
stroma, necrosis, and so on) and segment cellular
compartments (nuclei, cytoplasm and membrane) to
allow for detailed, spatially-resolved multiparameter
quantification. This is especially powerful when
combined with multispectral imaging, as it provides the
ability to perform tissue cytometry rapidly and on a
large scale, and using many markers at once.
www.iptonline.com
VALIDATION STUDY
For this particular study, a staining panel was developed
targeting phosphoeptitopes of AKT, ERK and s6,
using antibodies of three different isotypes, with
secondaries conjugated to Alexa Fluor® fluorophores
(Alexa Fluor 488, Alexa Fluor 555, and Alexa Fluor
647). DAPI (4’-6-diamidino-2-phenylindole) was used
as a counterstain (2).
Staining protocols were optimised using tissue
microarrays generated from lung tissue samples
prepared using methods designed to preserve
phosphoepitopes. Spectral unmixing libraries were
generated with single-stained control samples. Image
analysis algorithms were trained to segment tissue
regions (for example, malignant and normal epithelia,
stroma, necrosis, and so on), and then cells and cell
compartments within tumour regions, to extract per-cell
data for cytological analysis.
Validation of the platform’s ability to quantify changes
in phosphoepitope expression was performed with cell
blocks of cell lines treated with the relevant inhibitors.
Pilot studies of the TMAs and cell lines revealed
robust and specific signal levels, localised to tissue and
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Figure 4: Classifying patient subtypes with cluster analysis:
the 64-bins shown here contain the various combinations of
expressions of pERK, pAKT and pS6 in the patient population
estimated at greater than 90 per cent, based on visual
review by pathologists.
Data could be further analysed using cluster analysis.
Signals from individual cells were divided into quartiles
of pS6, pAKT and pERK expression, and placed into 64
bins. The number per bin is displayed as a heat map in
Figure 4.
BENEFITS OF MULTISPECTRAL IMAGING
In conjunction with easy-to-use multispectral imaging
systems and advanced learn-by-example software,
quantitative, independent and specific multi-label
protocols have been developed that can greatly accelerate
clinical and pre-clinical studies (3).
pAKT
Multispectral imaging captures information from many
narrow wavelength bands, instead of simply one band,
for each fluorescence emission filter. This added
information enables automated multispectral tools
rapidly to isolate label emissions from each other and also
from autofluorescence, which commonly obscures weak
but important signals in formalin-fixed paraffinembedded tissue sections. This ability to separate signals
applies even when, as is often the case, they are spatially
and spectrally overlapping – whereas conventional fixedbandpass filter approaches cannot do this.
pERK
pS6
cellular structures appropriate for the target
molecules, despite being applied in four-plex. Patternrecognition-based, automated image analysis
algorithms reliably detected tumour cells and
segmented associated cellular compartments, after
having been trained on less than 10 per cent of pilot
study images. Tissue segmentation accuracy was
The imaging platform is expected to enable a better
understanding of the mechanism of disease and the
development of potentially better, more precise avenues
of treatment.
References
1.
Illustration obtained from the University of
Delaware website, http://udel.edu/~apickard/
Cancer%20Website_files/basics.htm
Cliff Hoyt is Co-founder and Chief Technology Officer of
Cambridge Research and Instrumentation Inc (CRi), a biomedical
imaging company. He obtained his BA in Physics from Williams
College (Williamstown, MA) in 1983, and his Masters in
Mechanical Engineering from the Massachusetts Institute of
Technology (MIT) in 1987. Since co-founding CRi in 1985, he has
been involved in the development of many CRi core technologies,
including the liquid crystal tunable filters for multispectral and polarised light imaging,
and then the integration of these core technologies into analytical instruments
for applications such as in vitro fertilisation, high-throughput drug screening, stem
cell research, in vivo small animal imaging, live cell biology and tissue-based
immunohistochemical analysis for signalling pathway research. Cliff has served on US
National Institutes of Health (NIH) study sections, has been the principal investigator
on ten Small Business Innovation Research (SBIR) and Small Business Technology
Transfer (STTR) NIH grants, and is named inventor on approximately 20 patents.
Email: [email protected]
2.
Hoyt C, Wetzel RK, Yang D et al, Tissue
cytometry platform for quantitating multiple
signalling pathways proteins in intact tissue
sections, Poster at 2009 AACR-NCI-EORTC
conference. Alexa Fluor® is a registered
trademark of Invitrogen Corp
3.
Levenson RM, Fornari A and Loda M,
Multispectral imaging and pathology: seeing
and doing more, Expert Opin Med Diagn 2(9):
pp1,067-1,081, 2008
4.
Yoeli-Lerner M, Yiu GK, Rabinovitz I et al, Akt blocks
breast cancer cell motility and invasion through the
transcription factor NFAT, Mol Cell, Nov 23, 20(4):
pp539-550, 2005
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