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Nội dung

Moreira1,2, Irina Gromova1,2, Teresa Cabezon1,2, Ulrik Ralfkiaer1,2, Per Guldberg1,2, Per thor Straten1,2, Henning Mouridsen1,3, Esbern Friis1,4, Dorte Holm1,5, Fritz Rank1,5and Pavel Gr

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Towards discovery-driven translational research

in breast cancer

Julio E Celis1,2, Jose´ M A Moreira1,2, Irina Gromova1,2, Teresa Cabezon1,2, Ulrik Ralfkiaer1,2, Per Guldberg1,2, Per thor Straten1,2, Henning Mouridsen1,3, Esbern Friis1,4, Dorte Holm1,5,

Fritz Rank1,5and Pavel Gromov1,2

1 The Danish Centre for Translational Breast Cancer Research, Copenhagen, Denmark

2 Institute of Cancer Biology, Danish Cancer Society, Copenhagen, Denmark

3 Department of Oncology, Copenhagen University Hospital, Denmark

4 Department of Breast and Endocrine Surgery, Copenhagen University Hospital, Denmark

5 Department of Pathology, The Centre of Diagnostic Investigations, Copenhagen University Hospital, Denmark

Introduction

The completion of the human genome project, as well

as the current availability of novel and powerful

tech-nologies within genomics, proteomics and functional

genomics, promise to have a major impact on clinical

practice, as these developments are likely to change

the way in which diseases will be diagnosed, treated

and monitored in the near future We are moving

increasingly from the study of single molecules to the analysis of complex biological systems, and one of the main challenges we face is how best to apply these powerful technologies to clinically relevant sam-ples in a well-defined clinical and pathological frame-work [1–6]

Cancer, being a complex disease that impinges on a significant proportion of the world population, has become a prime target for the application of novel

Keywords

breast cancer; proteomics; functional

genomics; signaling pathways; systems

biology; individualised medicine; translational

research

Correspondence

J E Celis, The Danish Centre for

Translational Breast Cancer Research and

Institute of Cancer Biology, Danish Cancer

Society, Strandboulevarden 49, DK-2100

Copenhagen, Denmark

Fax: +4535 25 73 76

Tel: +4535 25 73 63

E-mail: jec@cancer.dk

(Received 10 September 2004, revised 29

September 2004, accepted 29 September

2004)

doi:10.1111/j.1432-1033.2004.04418.x

Discovery-driven translational research in breast cancer is moving steadily from the study of cell lines to the analysis of clinically relevant samples that, together with the ever increasing number of novel and powerful tech-nologies available within genomics, proteomics and functional genomics, promise to have a major impact on the way breast cancer will be diag-nosed, treated and monitored in the future Here we present a brief report

on long-term ongoing strategies at the Danish Centre for Translational Breast Cancer Research to search for markers for early detection and tar-gets for therapeutic intervention, to identify signalling pathways affected in individual tumours, as well as to integrate multiplatform ‘omic’ data sets collected from tissue samples obtained from individual patients The ulti-mate goal of this initiative is to coalesce knowledge-based complementary procedures into a systems biology approach to fight breast cancer

Abbreviations

FIF, fat interstitial fluid; GSK-3, p-glycogen synthase kinase-3; IHC, immunohistochemistry; IL, interleukin; NIF, nonmalignant interstitial fluid; TIF, tumour interstitial fluid.

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technologies – often referred to as the ‘omic’ platforms

– as these may help to identify subgroups of cancer

patients having specific molecular features associated

with clinical outcomes [7–14] This development is

expected to lead to a predictive, individualized

approach to cancer care, and will facilitate the selection

of treatment modalities that are most likely to benefit

the individual patient Currently, patient classification

is based on clinical parameters and cellular

morphol-ogy, as well as immunohistochemical analysis using a

restricted number of prognostic⁄ predictive markers

related to different cell functions such as cell

prolifer-ation, angiogenesis, invasion and metastasis These

parameters can only classify patients into subgroups

with various prognoses, but it is expected that the

com-bination of known risk factors with new expression and

genomic data will be instrumental to clinicians

confron-ted with treatment options

At present, we are experiencing a transition in

cancer research as we move from the use of single

‘omic’ platforms to their integrated use to achieve

‘systems biology’ [15] This integrated approach

should lead to a better understanding of the

under-lying biology of living cells and organisms, resulting

in turn in a more effective translation of basic

dis-coveries into clinical applications [1–5,16] However,

the implementation of discovery-driven translational

cancer research requires the coordination of basic

research activities, facilities and infrastructures, as

well as the creation of an integrated and

multidisci-plinary environment with the participation of all the

stakeholders in the cancer ordeal, i.e basic

research-ers, surgeons, oncologists, pathologists,

epidemiolo-gists, patients, patient advocacy groups, funding

agencies and industrial partners Issues related to

sample collection, handling and storage,

standardiza-tion of protocols, common references, number of

patients, availability of normal controls, access to

bio-banks, tissue arrays, clinical information,

follow-up clinical data, computational and statistical

analy-sis, as well as ethical considerations are critical, and

must be carefully considered and dealt with from the

beginning [1,2,4]

Discovery-driven translational cancer research has

only recently gathered momentum among the basic and

clinical research community, and as a consequence

there are currently few long-term programmes that use

tissue biopsies and bio-fluids as their main sources for

generating multiple data sets [1,2,4,5] The application

of high throughput technologies to the analysis of

tis-sue biopsies is far more demanding than the analysis of

bio-fluids, due to the heterogeneous nature of the

tis-sues and istis-sues related to sample preparation, as well

as to problems associated with managing long-term prospective⁄ retrospective programmes [1,2,5] Tumours usually contain malignant cells showing different degrees of differentiation as well as other cell types, which together compose the ‘tumour microenviron-ment’ [17–29] The cellular heterogeneity problem has generally been addressed using microdissection tech-niques that allow the dissection of a defined set of puri-fied cell populations [30,31] This technology, however, cannot solve the problem altogether, as heterogeneity can be observed even in a small number of cells when several markers are assessed simultaneously using im-munohistochemistry The application of cDNA micro-array-based expression profiling allows the analysis of single cells through elegant amplification strategies, and several studies reporting expression profiles generated from laser-captured cells have demonstrated the feasi-bility of the approach [32–34] Similar single cell analy-sis of cultured cells using gel-based proteomics [35–37],

on the other hand, does not provide a viable alternative

at the moment, as more sensitive protein detection methods are needed to identify a significant number of proteins [38]

Studies of bio-fluids using various proteomic tech-nologies far exceed those of tissues, as the samples are easier to collect and handle One type of analysis in particular, serum proteomics pattern diagnostic analy-sis, pioneered by Liotta, Petricoin and coworkers [39], has shown promise in identifying features that differen-tiate normal from malignant conditions in ovarian, prostate and breast cancer [39–42] This approach uses

a combination of low resolution mass spectra gener-ated by surface-enhanced laser desorption ionization time-of-flight (SELDI-TOF) and artificial intelligence-based informatics algorithms, to search for protein patterns or features in serum that may detect cancer at

an early stage [39] Liotta and coworkers have hypo-thesized that degradation and cleavage of the proteins that perfuse the tumour microenvironment is a major source of the peptides that appear in the blood Once

in the blood circulation, these peptides bind to abun-dant carrier proteins such as albumin that accumulate and transport them [43] Other studies, however, have highlighted several problems associated with the tech-nology, particularly related to the fact that the identity

of the peptides included in the serum features is not known Also, reproducibility, portability and sample source have been a matter of concern and much dis-cussion [44–46] The use of high resolution mass spectrometry platforms to collect the data, on the other hand, is expected to yield superior classification

of serum protein features of a number of cancers in the near future [47]

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Breast cancer

Breast cancer is the most common malignancy among

women in the Western world and constitutes 18% of

all cancers in women In Denmark approximately 3800

women develop breast cancer per year and an

estima-ted 1200 die from the disease In addition, the number

of registered cases has tripled over the past 40 years,

and breast cancer is now the number one cause of

can-cer mortality in women

Today, routine mammography, i.e screening for

breast cancer by X-ray examination, is the only

accep-ted method for early detection of breast cancer and a

recent meta-analysis of seven large-scale studies has

confirmed its value as a screening tool [48] Although

screening-detected cancers are significantly smaller

than nonscreening ones [49], there is a clear need to

improve the efficiency and sensitivity of the method as

it misses about 10% of the cases and gives a certain

percentage of false positive results Parameters such as

axillary lymph node status, tumour size, histological

grade and age in combination with predictive factors

such as oestrogen and progesterone receptors are

cur-rently used for selecting the appropriate systemic

ther-apy [50] The status of immunohistochemistry (IHC) in

diagnostic breast pathology has recently been

thor-oughly reviewed [51] Although pitfalls associated with

performance and interpretation of IHC results are

plentiful, current routine diagnostic breast pathology is

well equipped to provide modern ‘omics’ research with

important complementary information

Patients with primary breast cancer are offered

sur-gery, often followed by adjuvant therapeutics, i.e

che-motherapy, radiotherapy and⁄ or endocrine therapy

Despite these treatments, approximately 40% of

patients with lymph node-positive disease will

experi-ence a relapse, and the majority of these patients will

die from disseminated cancer [52,53] For patients with

lymph node-negative disease, the 5-year recurrence rate

is  25%, suggesting that the risk of recurrence and

subsequent death is closely related to the stage of the

disease at the time of primary surgery It is reasonable

to assume that the survival rate of breast cancer can

be improved, if the number of patients being

diag-nosed with early stage disease, i.e, node-negative

dis-ease, is increased

Chemotherapy and⁄ or endocrine therapy is offered

to patients at low, moderate and high risk of

recur-rence and death, i.e to a prognostically heterogeneous

group of patients with a range of risk from a few

per-cent up to 80% This group, which constitutes about

70% of all new breast cancer patients [54], is

charac-terized according to the following classical prognostic

factors: nodal status (positive); size of the primary tumour (‡ 20 mm); malignancy grade (2–3) and steroid receptor status (negative) With adjuvant systemic ther-apy being offered to this patient group, 30–40% of the expected deaths can be avoided However, in absolute terms, the mortality reduction amounts to only a few percent (i.e from 5 to 3%) in the low risk group, and

to  25% in the high risk group (i.e from 80% to 60%) Thus, although adjuvant systemic therapy has led to a considerable improvement of the prognosis of the breast cancer population, it also carries the signifi-cant adverse effect of overtreatment [55]

It is well known from the treatment of advanced breast cancer that patients nonresponsive to one

speci-fic type of therapy may react to another type, indica-ting that the response to a specific treatment relates

to specific characteristics (predictive factors) of the tumour Thus, there is a need to develop new inde-pendent prognostic and predictive indicators in pri-mary breast cancer to improve patient selection for specific and individual treatments Moreover, it is important to develop new diagnostic methods to detect breast cancer at a very early stage, as early detection increases survival rate Today, many cancers are detec-ted late, when spreading to the surrounding tissue and metastases has taken place

The Danish Centre for Translational Breast Cancer Research

Responding to the above challenges, the Danish Can-cer Society catalysed in 2002 the creation of a multidis-ciplinary, multi-centre research environment, The Danish Centre for Translational Breast Cancer Research (DCTB), to fight breast cancer DCTB hosts scientists working in various areas of preclinical cancer research (cell cycle control, invasion and microenvi-ronmental alterations, apoptosis, cell signalling and immunology) with clinicians (surgeons, oncologists), pathologists and epidemiologists in an integrated, mis-sion-oriented discovery-driven translational research environment The DCTB places the patient at the cen-tre and the ultimate goal is to conduct research to improve survival and quality of life of breast cancer patients

The underlying concept behind this long-term, con-certed approach is the use of multiple experimental paradigms from genomics, proteomics and functional genomics, to the prospective analysis of clinically rele-vant fresh samples obtained from the same patient, along with the systematic integration of the biological and clinical data sets [2,4] The aim of this systematic knowledge-based approach is (a) to understand the

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molecular mechanisms underlying disease pathogenesis,

(b) facilitate early detection and prognosis, and (c) to

provide novel targets for therapeutic intervention For

retrospective studies, the Centre efforts are supported

by the Danish Breast Cancer Cooperative Group

(DBCG), a group that manages a tumour repository

bank containing frozen tissue samples from

approxi-mately 10 000 breast cancer patients with clinical

fol-low-up of up to 10 years In due course, the DBCG is

expected to facilitate the implementation of therapeutic

modalities on a nationwide basis

Below we give a brief account of our long-term

strategies on ongoing long-term strategies within

DCTB to search for markers for early detection and

targets for therapeutic intervention, identify signalling

pathways affected in individual tumours, as well as to

integrate multiplatform ‘omic’ data sets collected from

tissue samples obtained from individual patients

Biomarkers for early detection and

targets for therapeutic intervention

Biomarkers for early detection

Success in detecting markers for early breast cancer

detection depends very much on the sources that are

used to conduct the search To date, two strategies

have been used to search for these biomarkers One is

based on the comparative analysis of the proteome of

peripheral fluids, and the other on similar analysis of

diseased tissues Even though appealing, the first

approach suffers from the drawback that markers are

likely to be present in lower amounts in the blood

cir-culation and, as a result, may be difficult to detect

Diseased tissues on the other hand may express the

markers at relatively higher levels, but it is not an easy

task to identify those that ultimately will appear in the

blood circulation The use of nipple-aspirated fluid as

a source of biomarkers has been explored in a few

cases, but no systematic studies have been reported so

far [56,57]

Our group has recently devised an alternative

approach that is based on the analysis of near fluids,

as these may be enriched in externalized biomarkers

and may justify a systematic long-term search [4,58]

Compelling evidence indicates that tumour growth

and progression is dependent on the malignant

poten-tial of the tumour cells as well as on the

multidirec-tional interactions of local factors produced by all

the cell types – tumour, stroma and endothelial cells,

in addition to immune and inflammatory cells –

pre-sent in the local microenvironment [17–29] All these

cells secrete, shed or release proteins to the interstitial

fluid that bathes the tumour microenvironment and some of these proteins, including biomarkers, may eventually reach the blood circulation through the lymphatic vascular system This ‘near fluid’, the tumour interstitial fluid (TIF) [58], may provide a rich source of biomarkers for early detection as well

as novel targets for therapeutic intervention as its protein composition can be readily compared with its nonmalignant counterpart (NIF) using proteomic technologies Figure 1 illustrates the steps we have undertaken to retrieve this fluid from fresh tumour biopsies, nonmalignant tissue, axillary nodal metasta-sis (MIF), and fat interstitial fluid (FIF) obtained immediately following surgery So far, we have ana-lyzed the protein composition of TIFs recovered from

30 high-risk patients The criteria for high-risk cancer applied by DBCG are age below 35 years old, and⁄ or tumour diameter of more than 20 mm, and⁄ or histo-logical malignancy 2 or 3, and⁄ or negative oestrogen and progesterone receptor status and⁄ or positive axil-lary status Figure 2A shows a two-dimensional iso-electrofocusing (IEF) gel of a representative fluid The protein composition of the TIF is strikingly dif-ferent to that of serum, although both fluids share some of their major components (Fig 2B) The TIF

is highly enriched in proteins that are either secreted via the classical endoplasmic reticulum (ER)⁄ Golgi pathway, shed by membrane vesicles (membrane blebbing), or externalized by plasma membrane trans-porter ([59] and references therein) Quantitation of the ratio of thioredoxin (externalized by an ER⁄ Golgi independent route)⁄ cytokeratin 18 (CK18) in whole tumour lysates and its corresponding TIF, yielded values that differ by a factor of 10 or more (data not shown), suggesting that nonspecific protein release due to cell death is not a major contributor

to TIF

So far, 284 primary translation products, as well as hundreds of post-translational modifications, have been identified using a combination of procedures that include mass spectrometry, 2D gel immunoblotting and cytokine-specific antibody arrays (RayBiotech, Atlanta, GA, USA) [4,58] Cellular function categories assigned to the known proteins include – but are not limited to – ion transport, cell motility, transporter activity, protein transport, signal transduction, response to oxidative stress, immune response, energy pathways, regulation of gene expression, proteolytic pathways, protein metabolism, maintainers of cytoske-leton organization, cell–cell signalling, regulation of cell–cell communication and regulation of cell growth [58] A protein database will soon be available through our web site (http://proteomics.cancer.dk)

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A systematic search for potential biomarkers starts

by comparing the protein profiles of nonmalignant

(NIF) and tumour (TIF) fluids, and the identification

of proteins that are highly deregulated in the latter

(Fig 2C,D) This is a long-term endeavour that will

require the qualitative and quantitative comparison of

hundreds of sample pairs using gel-based proteomics,

the preparation of specific antibodies against putative

markers for validation, as well as the analysis of the

corresponding serum⁄ plasma and other control

sam-ples for the presence of these markers

As the above approach mainly detects proteins

pre-sent at moderate to high levels and is set on a

discov-ery mode, we are establishing in parallel more sensitive

antibody microarray platforms to detect known, lesser

abundant components that may be potential

biomark-ers themselves For example, elevated levels of

interleu-kin (IL)-6 have been observed in the serum of patients

with breast cancer [60], and the levels of this cytokine

have been shown to predict the survival of patients

with metastatic breast cancer [61] These observations

prompted us to assess the levels of IL-6 both in NIF

and TIF Figure 3A shows cytokine-specific antibody

arrays (120 cytokines; RayBiotech) reacted with NIF

and TIF proteins retrieved from the same patient

Increased levels of several cytokines, including IL-6

were observed in the TIF, and some of these changes

could be independently confirmed using the Bio-Plex

system from Bio-Rad (Hercules, CA, USA) which can

quantitatively measure 17 human cytokines

simulta-neously (Fig 3B) Clearly, there is a good correlation

between the levels of IL-6 as determined by the two

platform technologies, a fact that was further validated

by performing IHC on nonmalignant and tumour tis-sues using an IL-6 specific antibody known to work with paraffin-embedded sections As exemplified in Fig 4B, the tumour tissue stains strongly with the antibody as compared to its nonmalignant tissue coun-terpart (Fig 4A, patient 46), indicating that indeed the elevated levels of IL-6 observed in TIF are in part due

to the production of this cytokine by the tumour cells The high levels of IL-6 observed in the sera of cancer patients, however, may not only reflect production of this cytokine by tumour cells, as fat tissue (Fig 4C) – which is very abundant in the mamma (Fig 1) – pro-duces significant levels of IL-6 as judged by antibody array analysis of FIF (Fig 4D) The bona fide origin

of FIF is supported by the presence of leptin, a protein known to be produced by adipose tissue (Fig 4D) Whether IL-6 produced by fat cells reaches the blood circulation is at present unknown [62–65], but this pos-sibility must be taken into consideration when search-ing for specific biomarkers This example illustrates the difficulties one faces in biomarker discovery, and underscores how careful one must be when interpreting data generated from complex samples

Targets for therapeutic intervention – towards identifying and building up pathways affected

in breast tumours The goal of individualized treatment is to provide ther-apies to which the patients may best respond This will require a thorough understanding of the molecular mechanism underlying the particular phenotype in order to identify potential therapeutic agents with a

Fig 1 Recovering the TIF from fresh breast tumours Fresh tissue (about 0.25 g) washed twice in phosphate buffered saline (NaCl ⁄ P i ), is cut in small pieces of about 1–3 mm 3 and placed in a 10-mL conical plastic tube containing 0.8–1 mL of NaCl⁄ P i Samples are then incuba-ted for 1 h at 37 C in a humidified CO 2 incubator Following incubation the samples are centrifuged at 300 g, at room temperature for

1 min and the supernatant is aspirated with the aid of an elongated Pasteur pipette Samples are then further centrifuged at 4000 g, at 4 C

in a refrigerated centrifuge Aliquots for gel analysis are freeze dried while the rest is kept at )80 C until further use.

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high degree of specificity Key biological processes that

harbour potential targets for intervention include cell

proliferation, apoptosis, invasion and metastasis,

angiogenesis and genomic instability [66] Today,

tar-geted therapies are aimed mainly at growth factor

sig-nalling pathways, and tyrosine-kinase receptors such

as Her2⁄ neu and epidermal growth factor receptor

(EGFR) Antibodies and rationally designed

small-molecule drugs developed to target specific small-molecules

involved in key processes of tumour progression

such as Herceptin (trastuzumab), Erbitux

(IMC-C225, cetuximab), Tarceva (erlotinib HCP), Avastin

(bevacizumab), Gleevec (imatinib mesylate), and Iressa (gefitinib) are currently in clinical trials Based on results obtained in preclinical studies with animal mod-els, which showed that systemic administration of growth factor inhibitors could restrain the growth and metastatic potential of human TCC xenografts [67], and the promising results obtained with EGFR inhibi-tors in other tumour types, several trials are now ongoing to test these agents, alone or in combination,

in patients with various cancers [68]

The potential therapeutic applications of proteins present in the TIF is clear as this fluid contains many

Fig 2 Protein profiling of interstitial fluids Isoelectrofocusing (IEF) 2D gels of proteins from (A) TIF 41, (B) serum, (C) NIF 46 and (D) TIF 46.

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growth factors and signalling molecules (Fig 3A)

[58], and it is probable that many additional

interest-ing novel proteins involved in the regulation of the

tumour ecosystem may be found, in particular using

shotgun proteomics [69] and references therein The

TIF can be recovered from tissues using

nondenatur-ing conditions, and as such it can be readily analyzed

using protein biochip technologies that provide

resourceful tools for target identification and

valid-ation, as well as for studying protein interactions

(enzyme substrates, drugs, lipids, etc.) In particular,

antibody-based arrays can detect protein

phosphoryla-tion as a means to assess the funcphosphoryla-tion of a given

sig-nalling pathway [70,71] Phosphorylation is a key

regulatory factor in many aspects of cell proliferation,

and as a result the phosphorylation status of novel

proteins is eagerly being pursued using mass

spectro-metry [72–74]

In an effort to identify signalling pathways affec-ted in individual breast tumours and to focus our search for potential targets for intervention, we have started comprehensive IHC analysis of tumours using phospho-specific antibodies against key signalling molecules [75] In parallel, these studies are being complemented using reverse tissue lysate arrays [76,77] in collaboration with Zeptosens (Zeptosens

AG, Witterswil, Switzerland) In the long run, these studies are expected to provide a framework in which to integrate data on known signalling mole-cules, as well as on forthcoming ‘omics’ information generated from the same tumours (see below) As an example, Fig 5 shows IHCs of two breast tumours probed with antibodies against p53 (Fig 5A,D), p-p53 (Fig 5B,E) and p-glycogen synthase kinase-3 (GSK-3; Fig 5C,F), a serine⁄ threonine kinase involved in various pathways including the

A

B

Fig 3 IL-6 levels in NIF and TIF (A) Cyto-kine-specific antibody arrays (RayBio human cytokine array series 1000) were incubated with 0.5 mL of NIF and TIF accor-ding to manufacturer’s instructions (B) Quantification of cytokines using the BioPlex system (Bio-Rad).

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A B

Fig 4 IHC of nonmalignant epithelial cells

(A) and tumour cells (B) from patient 46

usi-ng IL-6 antibodies (C) Haematoxylin and

eosin staining of fat tissue located far from

a tumour (D) Cytokine-specific antibody

array (RayBio) incubated with FIF as

described in Fig 3.

Fig 5 Aberrant Wnt ⁄ b-catenin pathway in tumour 14 (A–F) immunohistochemistry of paraffin sections of tumours 14 and 7 incubated with antibodies against p53 (A and D), phosphorylated p53 (p-p53, serine 15) (B and E) and phosphorylated GSKb (p-GSKb, C and F).

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Wnt⁄ b-catenin signalling cascade [78–80] The latter

plays an important role in development by

augment-ing the signallaugment-ing activity of b-catenin, a structural

component of the cell-cell adhesions that is known

to be deregulated in various cancers, including breast

cancer [81–85] Both p53 and GSK-3b have been

implicated in regulating the levels of b-catenin [86]

As shown in Fig 5A, tumour 14 depicts activation

of p53 in a region of the lesion in which GSK-3b is

also activated (Fig 5C), while the other tumour does

not When activated, GSK-3b phosphorylates

(tyro-sine phosphorylation) b-catenin, a fact that precludes

its binding to a-catenin and E-cadherin, thus

pre-venting cell adhesion and facilitating spreading

Phosphorylation of b-catenin targets it for

degrada-tion by the proteasome [87], and the p53 activadegrada-tion

is known to feed back and down-regulates b-catenin synthesis [86]

The presence in tumours of known signalling mole-cules involved in various pathways is being performed using antibody specific arrays (Panorama antibody microarray) that contain probes against hundreds of signalling molecules Arrays are incubated with pro-teins extracted from tumours using low concentrations

of Triton X-100 yielding semiquantitative data for many proteins simultaneously Figure 6 shows a rep-resentative protein antibody array analysis of a tumour In addition, quantitative gel-based proteomic (Fig 7) and transcriptomic data are being generated from the same tumour samples in selected cases in an effort to identify groups of coregulated proteins and mRNAs that may provide an integrated view of

Fig 6 Detection of signalling molecules in tumours using the Panorama antibody array (Sigma-Aldrich) Fresh tumours were minced and homogenized at room temperature with 0.1% Triton in phosphate buffered saline (NaCl ⁄ P i ) Samples were centrifuged at 300 g, at room tem-perature for 1 min and the supernatant was aspirated with the aid of an elongated Pasteur pipette The supernatant was then further centrifuged

at 4000 g, at 4 C in a refrigerated centrifuge Aliquots for gel analysis were freeze dried while the rest is kept at )80 C until further use.

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signalling cascades, extend the number of possible

tar-get candidates, as well as provide a more detailed

molecular phenotype of the tumour based on multiple

parameters

Future directions/conclusions

The analysis of tumour samples using single ‘omic’

platform technologies such as microarrays has

exempli-fied the value of this technology to classify tumours as

well as to derive signatures for prognosis and response

to treatment, particularly in lymphomas [7,8,88],

leuk-aemia [89,90] and breast cancer [12–14,91,92] Today,

however, it is becoming increasingly clear that we must

use multiplatform technologies to classify subgroups of

patients for more precise and predictive, individualized

approaches to cancer treatment [93] These efforts must

be accompanied by the development of bioinformatics

tools for integrating and mining the data as well as by

systematic, knowledge-based long-term approaches that

are supported by proper clinical infrastructures

There are several issues, however, that must be care-fully and promptly addressed if we are going to fulfil the dream of bringing individualized cancer care closer

to reality First of all, we must acknowledge the value

of long-term research and provide the appropriate legal and ethical framework to encourage the collabor-ation among all the stakeholders in the cancer ordeal Bridging the gap between basic and clinical research, facilitating the engagement of the industry, creating new infrastructures and bio banks, as well as the cre-ation of innovative clinical trials are among the items that require urgent action The aim of cancer research

is to improve the life expectancy and quality of life of patients and we must make every effort to coordinate current activities in order to achieve this goal

Acknowledgements

We would like to thank Gitte Lindberg Stort, Dorrit Lu¨tzhøft, Hanne Nors, Michael Radich Johansen, Britt Olesen and Signe Trentemøller for expert

Fig 7 Quantitative gel-based proteomics Twenty tumour cryo-sections (8 microns) were dissolved in 100 lL of Zeptosens lysis solution and 40 lL were applied to the first dimension isoelectrofocusing gel The first section of each tumour is routinely kept for histology analysis

in order to facilitate the interpretation of the data.

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