Báo cáo khoa học: Antibody-based proteomics Analysis of signaling networks using reverse protein arrays pdf

Antibody-based proteomicsAnalysis of signaling networks using reverse protein arrays Hans Voshol1, Markus Ehrat2, Jens Traenkle2, Eric Bertrand1and Jan van Oostrum2 1 Novartis Institutes

Antibody-based proteomics

Analysis of signaling networks using reverse protein arrays

Hans Voshol1, Markus Ehrat2, Jens Traenkle2, Eric Bertrand1and Jan van Oostrum2

1 Novartis Institutes for BioMedical Research, Basel, Switzerland

2 Zeptosens [a division of Bayer (Schweiz) AG], Witterswil, Switzerland

Introduction

Significant progress has been made during the last

dec-ade in linking pathological conditions to defects in

molecular pathway components Most prominent has

been the linkage of signalling pathway dysregulation

to conditions such as cancer [1] and inflammatory

dis-orders [2] Understanding the information flow

through the various pathways within a signaling

network, and how these pathways can best be

manipu-lated to redirect signal transduction, is a challenging

endeavor A first step would be to describe the full

complexity of signaling networks at a molecular level,

including activities specific to a particular cell type,

dynamic feedback mechanisms, pathway cross-talk,

signaling kinetics and, of course, pathway activation

states in normal and disease situations [3] Even

though both kinases and phosphatases are key

regula-tors in signaling pathways, across the pharmaceutical

industry it is primarily kinases on which a substantial percentage of drug-discovery efforts are currently focused

For a ‘kinase pathway’, the information flow (or pathway flux) mostly depends on the ratio of phos-phorylated and nonphosphos-phorylated protein species, reflecting the activation state of the biological system Comparing cellular activity over time, at various stages

of disease progression or before or after drug treat-ment, provides an opportunity to find a correlation between the activation state, on the one hand, and the biological or disease state, on the other hand

Small molecules that modulate the activity of signal-ing proteins are useful tools for dissectsignal-ing the func-tional roles and connections of the individual nodes in

a pathway [4] Using such a ‘systems approach’, one can begin to build a model that will not only provide

Keywords

antibodies; pathways; phosphoproteomics;

protein arrays; signalling networks

Correspondence

J van Oostrum, Zeptosens, Benkenstrasse

254, CH-4108 Witterswil, Switzerland

Fax: +41 61 726 81 70

Tel: +41 61 726 81 87

E-mail: jan.van_oostrum@zeptosens.com

(Received 11 June 2009, revised 16

September 2009, accepted 22 September

2009)

doi:10.1111/j.1742-4658.2009.07395.x

Protein kinases drive the cellular signal transduction networks that underlie the regulation of growth, survival and differentiation To repair the deregu-lations of signaling cascades that are associated with numerous disease states, therapeutic strategies, based on controlling aberrant protein kinase activity, are emerging To develop such therapies it is crucial to have knowledge of the full complexity of signaling networks at a molecular level

in order to understand the information flow through signaling cascades and their cell and tissue specificity Antibody-based proteomic approaches (such as reverse-phase protein microarrays) are a powerful tool for using to obtain those signaling maps, through the study of phosphorylation states

of pathway components using antibodies that specifically recognize the phosphorylated form of kinase substrates

Abbreviations

ERK, extracellular signal-regulated kinase; MEK, mitogen-activated protein kinase/ERK kinase; RPA, reverse (phase) protein (micro)array.

a contextual understanding of the molecular

mecha-nisms of disease, but also has the potential to facilitate

the validation of therapeutic modulation of regulatory

networks [5,6] A direct benefit of such an approach

would be the early recognition of ‘off target’ and side

effects of drug candidates [7], as well as the

identifica-tion of putative biomarkers

The phosphorylation status of signaling pathway

components can be measured using

anti-phosphopro-tein Igs that specifically recognize their phosphorylated

isoforms Thus, the activity status of multiple signaling

pathways or networks can be probed through parallel

phospho-specific analyses While producing thousands

of western blots could (in theory) accomplish this, only

protein microarrays enable truly multiplexed analysis

by replicating the same sample many times on separate

arrays This type of array, in which a protein extract is

immobilized and queried with antibodies or other

reagents that bind to a specific protein in the sample,

is often referred to as a reverse (phase) protein

micro-array [8–10]

Signaling pathways in health and

disease

Fundamental cellular processes are under tight control

of signaling pathways, many of which are highly

con-served across species [11] Prominent players in these

signaling cascades are protein kinases and

phosphata-ses, which control the activation state of signaling

pathways by the modulation of phosphorylation on

Tyr, Ser and Thr residues on each other and on a

vari-ety of downstream effectors Aberrant cellular

signal-ing is a hallmark of many diseases, and consequently

there is a substantial interest in developing drugs that

can modulate and⁄ or repair defects in signaling

path-ways

In general, drug discovery faces many challenges,

with perhaps the failure of drug candidates during the

development process (e.g as a result of adverse effects

or lack of efficacy) being the most prominent one This

high attrition rate may reflect the fact that we are only

just beginning to understand the complexity of the

response of a biological system to perturbations like a

disease state or drug treatment Hence, a deeper

insight into the molecular mechanisms underlying both

disease processes and drug action will ultimately

contribute to an increased productivity of the

drug-dis-covery process [11–13]

In many compound development projects, different

assay systems are used for the selection and

character-ization of kinase inhibitors Primarily, compounds are

selected with biochemical, cell-free assays using

puri-fied recombinant kinases and artificial peptide sub-strates Cell-based assays are used as a secondary screening step to validate the biological activity of selected compounds against the native kinases in their natural environment For kinase inhibitors, these screens usually comprise the detection of one or a few phosphorylated proteins that are directly related to the action of the targeted kinase Because of the inherent potential promiscuity of kinase inhibitors, a more extensive characterization of compound activities across a wide range of signaling pathways and their components is desirable to select the inhibitors with the appropriate profile [7,14]

Drugs that inhibit kinases have recently entered the market, the most spectacular example being imatinib (Gleevec⁄ Glivec), which inhibits the constitutive kinase activity of the Bcr–Abl fusion protein, the product of

a chromosomal translocation in patients suffering from chronic myelogenous leukemia Several other kinase inhibitors are already on the market, for exam-ple erlotinib (Tarceva) and gefitinib (Iressa), both of which block the epidermal growth factor receptor tyrosine kinase Tyrosine kinase inhibitors act by inhibiting the activation of intracellular signal trans-duction, typically by blockage of the ATP-binding site

in the catalytic domain of the kinase As the majority

of kinase inhibitors that are discovered by high-throughput screening methods target the ATP-binding pocket of the kinase, there is an inherent selectivity problem Even though these ATP-binding sites, and the surrounding areas, differ between kinases, there is enough similarity to make it very difficult, if not impossible, to develop a fully selective compound for each target While at first glance this lack of specific-ity, or ‘promiscuity’ [15], appears to be an obstacle for developing a successful drug, in the case of imatinib it has resulted in approval for the treatment of gastroin-testinal stromal tumors, owing to its inhibitory activity against c-kit, the protein tyrosine kinase that is dys-regulated in that cancer Nevertheless, profiling kinase inhibitors for potential secondary targets is an essen-tial and integral part of drug development so that compounds with a desired (usually narrow) target pro-file can be prioritized over those that are less ‘clean’ and potentially more risky

From biochemical assays to pathway readouts for kinase activity

Profiling of kinase inhibitors can be useful to assess the promiscuity of the inhibitor and how much of a problem that might present The first published screens of that kind emphasized the importance of

such assays, showing that many commercial inhibitors

were everything but specific for the target they claimed

to hit [16,17] The availability of the human genome

and the subsequent prediction of the ‘kinome’, the

complete set of some 500 human kinases [18], have

further accelerated the development of kinase panels

Currently, such collections comprise over 250 kinases;

in other words, around half of the human kinome

While the interaction with, and inhibition of, kinases

in vitro is one important aspect of profiling

com-pounds, it does not take into account the complexity

of the in vivo situation, where compounds encounter a

wide variety of potential interactors, both kinases and

nonkinases

Consequently, cellular assays, preferably in a cell

type that is a reasonable proxy for the targeted

popu-lation, are preferred Here, two basic approaches have

emerged On the one hand there are the ‘chemical

proteomics’ (or chemoproteomics) approaches, which

determine protein–compound interaction rather than

measuring actual inhibition of the enzymatic activity

In chemical proteomics, the kinase inhibitor in

ques-tion is immobilized and used as ‘bait’ to fish for

interacting proteins in cell or tissue lysates [19]

Alternatively, tracing the functional effects of

compounds in cellular systems can be studied using

pathway proteomics approaches (Fig 1)

The last, and undoubtedly most important, piece of

the puzzle when it comes to determining selectivity and

specificity of kinase inhibitors, or ultimately any class

of drugs, is to develop a meaningful assay for the

physiological effect of a compound as early as possible

in drug discovery Ideally such an assay would

com-bine readouts for the two most relevant parameters

that determine the potential of a compound as a drug,

namely (a) the on-target activity as the primary

mea-sure for pharmacological efficacy and (b) the off-target

effects, which should be minimized in order to obtain

a ‘clean’ compound with the smallest risk of side

effects As the example of imatinib has shown,

on-tar-get and off-taron-tar-get effects do not always correlate so

strictly with beneficial and adverse effects as one would

like [20] Nevertheless, understanding and

discriminat-ing the physiological changes that are inevitable (i.e

because of interaction with the primary target) from

those that might be undesirable and avoidable is a key

asset in selecting the best possible compound To

achieve that, the choice of a suitable set of readouts

with the appropriate resolution or granularity is

criti-cal One could resort to monitoring as many individual

cellular components – genes, proteins, metabolites – as

possible Arguably, signaling pathways are currently

the best practical translation of ‘physiology’ because

they allow a sufficient level of granularity while inte-grating the basic organizing principles of the cellular machinery at the same time [11]

Multiple assay formats have evolved for measuring pathway activity, varying in information content and throughput The principle that all these assays have in common is that they attempt to measure the relative activation state of proteins in pathways Because in the majority of cases these proteins are kinases and their activity is regulated by phosphorylation, most assay formats are based on multiplexed or parallel detection

of specific phosphorylation sites

The phosphorylation status of signaling pathway components can be measured using anti-phosphopro-tein Igs that specifically recognize the phosphorylated isoforms of such kinase substrates [5,21] For example, quantitative data sets measuring the effects of kinase inhibition on the phosphorylation status of pathway components may be obtained using a compound titra-tion series (Fig 1) A concentratitra-tion–response analysis allows the calculation of the half maximum effective concentration (EC50) as a reliable quantitative descrip-tion of the phosphoryladescrip-tion changes Thus, the activity status of multiple signaling pathways can be probed through parallel phosphospecific analysis Besides the laborious western blot, which allows only a limited throughput, the current gold standard for this purpose

is the sandwich ELISA, which is available in many custom or commercial formats Sandwich ELISAs have the disadvantage that a carefully matched pair of antibodies must be developed if one aims for site-spe-cific analysis Moreover, the (peptide) epitopes that have been used for the generation of antibodies are not always accessible in the native (nondenatured) protein

Recently, lysate arrays have emerged as an alterna-tive to the sandwich (or forward) assay format [10] This type of array, in which a protein extract is immo-bilized and queried with antibodies or other reagents that bind to a specific protein in the sample, is often referred to as reverse (phase) protein (micro)array (RPA) The term ‘reverse’ serves to contrast the lysate array format with ‘forward arrays’, namely those in which the capture reagent (e.g the antibody) is immo-bilized [22,23] Among the first applications of RPA were microarrays of tissue lysates to study many proteins in microdissected biopsies [8]

RPAs have been used for several years in their most basic form, the dot-blot, in which drops of cell or tis-sue extract are applied to a membrane or a coated glass slide Among the different proteomics technolo-gies that are suitable for that purpose, we employ a reverse array platform utilizing the planar waveguide

technology that allows the detection of a minimum of

1000–2000 molecules present in a single spot, where

the total protein content of a single spot corresponds

to that of a single cell [9] Cells or tissue samples are

subjected to a one-step extraction using denaturing

conditions, under which the potentially labile protein

phosphorylations are effectively ‘frozen’, rendering

most peptide epitopes accessible and making it

rela-tively easy to translate antibody validation by western

blotting into an array format

Although RPAs have gained popularity as an

alter-native to classical western blots because of a

dramati-cally increased throughput, the major bottleneck, as

with most antibody-based proteomics approaches,

remains the validation of antibodies, which should be

highly specific and should not cross-react with any

other protein in the cell lysate As the quality of the

antibodies is key to the successful application of

RPAs, significant effort is required to ensure their

validation before they are applied

Analysis of signaling pathways using RPAs

In our view, RPAs currently provide the best array-based pathway analysis platform when information content and flexibility are the primary criteria In con-trast to classical (forward) arrays, reverse arrays are,

in fact, high-throughput dot-blots: small droplets of the complete protein extract are spotted onto a hydro-phobic surface, which retains the proteins by adhesion Usually, whole tissue or cell extracts, corresponding to the whole cellular proteome, are spotted RPA approaches often utilize denaturing extraction buffer systems [24,25], which have the important advantage that artifacts caused by inappropriate enzyme activity during extraction can be largely avoided [26] In this regard, forward array systems are more challenging because the capture step is typically carried out under native conditions, with the inherent risks of artificial changes in the extracts, particularly in labile

phospho-MEK

Erk

Ras/Raf

MEK

p90RSK

Erk

p90RSK

EGFR

Fig 1 Monitoring of downstream cell sig-naling effects upon kinase inhibition A375 cells were treated with increasing concen-trations of a Raf inhibitor Cells were lysed and the phosphorylation levels of the down-stream pathway elements, mitogen-acti-vated protein kinase/ERK kinase (MEK), extracellular signal-regulated kinase (ERK) and p90RSK were monitored using phos-phospecific antibodies on reverse protein arrays By plotting the percentage activity (inhibition of phosphorylation) versus inhibi-tor concentration one can derive half

for each pathway element from such experi-ments Western blots of replicate samples are shown together with the quantitative

intensity.

rylations Analogous to western blots and dot-blots,

nitrocellulose was originally used as the carrier for

RPAs, albeit in the form of nitrocellulose-coated chips

[8], to facilitate handling and scanning In efforts to

obtain the ideal surface, which should combine high

protein binding with low intrinsic background [24],

other materials and techniques have been explored,

including methodology derived from semiconductor

fabrication [24] Arguably the most advanced,

commer-cially available, substrate for reverse arrays is the

ZeptoCHIP This device combines a hydrophobic

coat-ing (to ensure firm adhesion of proteins) with planar

waveguide technology, which allows for enhanced

sen-sitivity compared with conventional scanners [27] The

principle of the planar waveguide is to propagate the

laser light of the scanner along the chip surface,

result-ing in minimal background from nonsurface-bound

molecules (Fig 2A) Because proteins interact with this

reverse array surface in a noncovalent manner, the

actual composition of the spots depends on the

com-position of the lysates, the lysis buffer and the ‘affinity’

of the individual proteins for the solid phase

Varia-tions in lysis and spotting buffers, and in protein

concentrations, will influence the make-up of the immobilized ‘proteome’ [25,26] Consequently, samples with a few highly abundant proteins, such as serum or plasma, are more challenging to deal with than cell or tissue lysates, where the dynamic range is less extreme Even though limited multiplexing is possible (e.g using antibodies with different fluorescent dyes), reverse arrays are typically not used in a multiplexing mode but mostly with only a single antibody per array This circumvents some of the issues inherent to multiplexing

as it is often used in forward arrays [24] Because it is straightforward to print many identical arrays, RPAs nevertheless allow testing of a practically unlimited number of antibodies in a parallel set up

ZeptoCHIPs, which use the planar waveguide tech-nology for improved sensitivity, are made of planar waveguides consisting of a thin film (150 nm) of mate-rial with a high refractive index (e.g Ta2O5), which is deposited on a transparent support with a lower refractive index, typically glass A laser light beam is coupled into the waveguiding film by a diffractive grat-ing that is etched into the glass The light propagates within this film and creates a strong evanescent field,

Separation of excitation and detection directions

Signal/noise = 2/1

Signal/noise = 200/1

Confocal excitation Evanescent excitation

Evanescent excitation intensity Confocal excitation intensity

PWG principle

C

Fig 2 (A) Planar waveguide (PWG) principle; optical scheme of excitation and detection of surface confined fluorescence on planar wave-guide chips (B) Fluorescence excitation schemes for conventional, confocal scanning leading to background contributions, and for evanes-cent, surface-confined illumination using planar waveguides resulting in reduced background signals (C) Comparison of signal-to-noise ratios from the same microarray obtained by confocal scanning and surface-confined PWG-based fluorescent detection.

perpendicular to the direction of propagation, into the

adjacent medium (Fig 2A) Upon fluorescence

excita-tion by the evanescent field, excitaexcita-tion and detecexcita-tion of

fluorophores is restricted to the sensing surface, while

signals from unbound molecules in the bulk solution

are not detected (Fig 2b) This results in a significant

increase in the signal-to-noise ratio compared with

conventional optical detection methods (Fig 2c)

A typical microarray is a ZeptoCHIP, which has

space for six arrays, each comprising 352 spots (Fig 3)

Each array has four columns of spots that are used to

calibrate the energy loss when the light travels across

the waveguide Typically, 32 samples are spotted in

four dilutions (ensuring one remains always within the

linear part of the binding curve, see above) and in

duplicate Each array is probed with a single antibody

Each spot will have a volume of around 0.5 nL (with a

diameter of 100 lm) and will contain the amount of

protein contained in a single cell Spotting is performed

using a noncontact piezo-electric spotter (inkjet

tech-nology), with a spotting capacity of about 360 arrays

(enabling probing with 360 antibodies) in one overnight

spotting run After printing, the chips are blocked with

albumin (as done for western blots) and can be stored

in this blocked state for longer than 1 year at 4C

RPA applications

The RPA approach was pioneered, among others, by

Liotta and Petricoin [8], driven by the need for an

analytical tool to identify signaling proteins in minute

tissue samples, such as those derived from

laser-cap-ture microdissection Hence, RPA followed an atypical

trajectory, in a sense the opposite of most bioanalytical

tools, which are usually extensively used in model

systems before being applied on animal or human

tissue samples Initial clinical applications were aiming

particularly at screening pathway-activation states in

tumor tissue samples, using antibodies specific for

phosphorylated proteins The underlying hypothesis of

those experiments was that differences in these

path-way profiles could help to stratify patients and predict

response to drug treatment Several studies have

indeed provided indications that this could be a

prom-ising avenue For example, when studying fine needle

aspirates from breast tumors using RPA, Rapkiewicz

et al [28] observed modulation of survival⁄ apoptosis

and growth factor pathways as a function of previous

chemotherapy treatment

However, elucidation of signaling pathways (i.e

understanding how the signal is transmitted through the

cell and what the critical ‘nodes’ are), requires the

inves-tigation of (cellular) model systems RPA applications

in model systems (e.g compound profiling in cell-based models) are only just starting to emerge [7] Whereas a cell-based (in vitro) system can easily be manipulated to increase the amplitude of the signal, in many in vivo situations the effects of altered signaling will be attenuated by steady-state compensatory mechanisms Molecular profiling with gene arrays has provided insight into the expression levels for genes in a variety

of normal and diseased tissue specimens However, gene transcript levels do not necessarily correlate with protein expression levels and, more importantly, do

e.g sample #1

Controls

Column with reference spots

A

B

Distance (pixel) Line profile (as depicted in image)

Fig 3 (A) Illustration of one of the six arrays on a ZeptoCHIP On

a single array, 32 samples are spotted in four different concentra-tions and in duplicate (B) Scan of an array cross-section showing the signal linearity for the four different sample concentrations.

not provide insight into the levels of post-translational

modifications of proteins, such as phoshorylation

events, that play a significant role in cellular signaling

networks Investigations into the protein and

phospho-protein expression levels in normal tissue would be a

prerequisite to understand the alterations in signaling

that are observed in diseased tissues and⁄ or are caused

by in vivo treatment with specific compounds Mouse

models are particularly useful for studying the effects

of compounds in complex organisms, helping to gain

new knowledge about the molecular mechanisms of

disease The creation of a pathway activity atlas for

canonical signaling events would begin with the

estab-lishment of the expression levels of proteins involved

in various organs or tissues Figure 4A represents a

small excerpt from data derived from quantitative pro-tein expression profiling using RPAs in a collection of tissues derived from C57⁄ Bl6 mice Tissues were extracted in a 10-fold excess of Zeptosens CLB1 buffer using a Teflon Potter (8–10 strokes at 800 rpm) fol-lowed by centrifugation (20 min at 100 000 g) to remove insoluble material Tissue lysates were stored

at )80 C before performing RPA analysis, as described previously [8]

The range of protein expression values within a group of animals will provide a range of normal values for protein expression for the corresponding organs and tissues Figure 4B underlines the extent of biologi-cal variation in the expression levels of proteins and their phosphorylated forms between two different

tis-pAkt (Ser473)

0

200

400

600

800

1000

1200

1400

Muscle Hear

Kidney Colon

Intestine Stomach Prostate

Frontal cortex Hippocampus

Cerebellum Thalamus

P44/42 MAP kinase

0

2000

4000

6000

8000

10 000

12 000

14 000

pMEK1/2 (Ser 217/221)

0

1000

2000

3000

4000

5000

6000

Glycogen synthase

0

1000

2000

3000

4000

5000

6000

7000

8000

0 500 1000 1500 2000 2500 3000 3500

0 200 400 600 800 1000 1200 1400

0 500 1000 1500 2000 2500 3000 3500

Heart 1 Heart 2 Heart 3 Heart 4 Heart 5 Heart 6 Heart 7 Heart 8

P P P P P P P P p70 S6 Kinase

0 500 1000 1500 2000 2500 3500 4000

TSC-2

0 500 1000 1500 2000 2500

Phospho-PTEN

0 500 1000 1500 2000 2500

Phospho-mTOR

0 1000 2000 3000 4000 5000 6000 7000 8000

Phospho-p44/42 MAPK

0 500 1000 1500 2000 2500 3000

Fig 4 Towards a protein expression atlas (A) Relative expression levels of selected signaling network components in mouse organs and brain areas (B) Relative expression levels of selected signaling network components from the heart and pancreas derived from eight

sues within a group of eight different C57⁄ Bl6 mice A

second step would involve the measurement of the

activity levels of signaling pathways, indicated by, for

example, the phospho-⁄ nonphospho ratios of pathway

components We envisage that ultimately building such

activation maps across organs will be highly valuable

in the development of drugs that target cellular

signal-ing networks The idea behind this concept, which we

refer to as predictive pharmacodynamics, is that the

activation map of the targeted pathway could serve to

select the optimal intervention point, which is actually

likely to differ depending on the target tissue At the

very least, this approach would deliver useful

pharma-codynamic markers to monitor the effects of different

compounds in the organism Moreover, at least in

the-ory, this methodology for selecting the correct target

would have both the benefit of maximizing the

thera-peutic effect as well as minimizing adverse events

Conclusion

Owing to the high sensitivity and high throughput

capability of the RPA approach, it will be feasible to

obtain protein expression profiles and signaling

path-way information on a wide variety of cell lines and

tissue samples Interesting applications include (a) the

comparative analysis of signaling pathway(s) events in

normal versus diseased tissue, (b) the comparative

analysis of protein expression in various systems, (c)

elucidation of the dynamic aspects of pathway events

and (d) the profiling of compounds to reveal signaling

and cross-pathway effects of drug candidates In

addi-tion, analysis of healthy versus diseased tissue

(includ-ing animal models) will provide insights into the

underlying pathologies of the pathways and provide a

platform for molecular diagnostics In a future

approach, the screening of body fluids with a reverse

array approach may enable the investigation of a large

number of individual body fluid samples for a limited

set of proteins contained within them, to establish

variations in protein expression levels

Acknowledgements

The authors would like to acknowledge Dr A van Gool

(Schering-Plough, Translational Medicine Research

Centre, Singapore) for providing the western blot results

shown in Fig 1

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