REVIEW ARTICLE Towards discovery-driven translational research in breast cancer Julio E. Celis 1,2 , Jose ´ M. A. Moreira 1,2 , Irina Gromova 1,2 , Teresa Cabezon 1,2 , Ulrik Ralfkiaer 1,2 , Per Guldberg 1,2 , Per thor Straten 1,2 , Henning Mouridsen 1,3 , Esbern Friis 1,4 , Dorte Holm 1,5 , Fritz Rank 1,5 and Pavel Gromov 1,2 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. 2 FEBS Journal 272 (2005) 2–15 ª 2004 FEBS 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 issues 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]. J. E. Celis et al. Translational research in breast cancer FEBS Journal 272 (2005) 2–15 ª 2004 FEBS 3 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 Translational research in breast cancer J. E. Celis et al. 4 FEBS Journal 272 (2005) 2–15 ª 2004 FEBS 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). J. E. Celis et al. Translational research in breast cancer FEBS Journal 272 (2005) 2–15 ª 2004 FEBS 5 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,at4°C in a refrigerated centrifuge. Aliquots for gel analysis are freeze dried while the rest is kept at )80 °C until further use. Translational research in breast cancer J. E. Celis et al. 6 FEBS Journal 272 (2005) 2–15 ª 2004 FEBS 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 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 AB CD 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. J. E. Celis et al. Translational research in breast cancer FEBS Journal 272 (2005) 2–15 ª 2004 FEBS 7 growth factorsÒ 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 function 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 (RayBioÒ 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). Translational research in breast cancer J. E. Celis et al. 8 FEBS Journal 272 (2005) 2–15 ª 2004 FEBS AB C D 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 (RayBioÒ) incubated with FIF as described in Fig. 3. AB C DE F 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). J. E. Celis et al. Translational research in breast cancer FEBS Journal 272 (2005) 2–15 ª 2004 FEBS 9 Wnt ⁄ b-catenin signalling cascade [78–80]. The latter plays an important role in development by augment- ing the signalling 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 activation 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 (PanoramaÒ 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 PanoramaÒ 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,at4°C in a refrigerated centrifuge. Aliquots for gel analysis were freeze dried while the rest is kept at )80 °C until further use. Translational research in breast cancer J. E. Celis et al. 10 FEBS Journal 272 (2005) 2–15 ª 2004 FEBS 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. J. E. Celis et al. 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