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Proteomics in Cancer Cell Research: an Analysis of Therapy Resistance

Posted on: Tuesday, 14 September 2004, 06:00 CDT

Abstract

Proteomics, the global analysis of expressed cellular proteins, provides powerful tools for the detailed comparison of proteins from normal and neoplastic tissue. In particular, cancer cell culture models are suited for applying proteomics techniques, such as two- dimensional polyacrylamide gel electrophoresis (2D-PAGE) and mass spectrometry, to identify specific protein expression profiles and/ or proteins that may be associated with a defined phenotype of the cancer cells. As an instance of such an application of proteomics techniques, the detailed proteome analyses of different drug- resistant and thermoresistant cancer cell lines will be discussed. Finally, the potential roles of newly identified factors in a distinct biological mechanism have to be proven by functional studies. This experimental validation strategy will be discussed for two different factors identified by 2D-PAGE analyses of drug- resistant carcinoma cell lines, the "transporter associated with antigen presentation 1" (TAP1) and 14-3-3[sigma].

2004 Elsevier GmbH. All rights reserved.

Keywords: 2D-PAGE; Cancer; Drug resistance; Thermoresistance

Introduction

Since the complete genome sequences of several organisms, including a preliminary version of the human genome [43,80], are available, experimental endeavors have increasingly focused on a global analysis of the proteins, the functional products of the genomes. This approach has been commonly designated as "proteomics". The term "proteome" was first introduced at a conference (Sienna, Italy) on two-dimensional polyacrylamide gel electrophoresis (2D- PAGE) in 1994, and was defined as the total protein complement of a genome [83,84]. The process of studying the proteome became known as proteomics. However, traditionally, proteomics has been associated with displaying a large number of different proteins from a given origin, such as a cell line, a tissue, or a complete organism, by 2D- PAGE [55]. In this sense, proteomics already dates back to the late 1960s, when 2D-PAGE was introduced into biomedical research for determining the protein composition in the small and the large ribosomal subunit of Escherichia coli [33,34]. During the following years, the technique of 2D-PAGE was improved continuously [52].

There are several reasons for the intensified focus on the analysis of protein expression profiles: the mRNA expression level of a given gene frequently does not directly correspond to the cellular amount of biological active protein [4]. Although the amino acids sequence predicts potential modification sites within a given protein, the real posttranslational modifications that may be essential for biological function and activity are not obvious [46]; and reclusive genomic data do not reflect dynamic cellular processes [28]. Moreover, proteomics includes the differential display of proteins for comparison, for example different health or disease states; it includes the characterization of protein localization, the analysis of protein-protein and protein-nucleic acids interactions, as well as the biochemical analysis of protein function. Thus, the proteomic approach may have a major impact on the improved understanding of biological problems associated with clinical questions [5,21,45].

Proteomics technologies

Although 2D-PAGE and mass spectrometry (MS) are currently the two most important proteomics technologies, several other techniques have been introduced and are still under further development. The most commonly applied proteomics technologies include the following.

Two-dimensional polyacrylamide gel electrophoresis

By applying 2D-PAGE, proteins are first separated by their charge through isoelectric focusing (IEF). Immobilized pH gradients (IPGs) were developed to assist in overcoming former problems with pH gradient instability. These have considerably improved the reproducibility in resolving almost the complete spectrum of basic to acidic proteins [18,20]. For separation in a second dimension, the proteins are separated by their molecular size using a polyacrylamide gel and stained, or exposed to X-ray films in the case of radiolabeled proteins. Coomassie brilliant blue stain will detect protein amounts greater than 100ng; silver stain can detect proteins in the 1 ng range. Using silver staining, between 500 and 2000 (up to 3000) spots can usually be detected. Fluorescent dyes have been developed to overcome some of the drawbacks of silver staining by making the proteins more amenable to MS identification. These dyes, such as the Sypro series, offer a similar level of sensitivity to silver staining [75]. However, fluorescence dye- staining, e.g. sypro ruby, or [^sup 35^S]-methionine labeling of proteins may detect proteins in the range of 0.1pg. Using these detection systems, 2D-PAGE can separate more than 10,000 different proteins and their modification products [13]. After staining, the gels can be scanned with densitometers, and the protein data can be processed with software, such as PDQUEST or MELANIE, for spot detection and quantification.

MS

For further protein analysis, protein spots have to be excised from the 2D gels for identification by peptide-mass fingerprinting in a mass spectrometer. For this approach, the protein spot will be digested with an endoproteolytic enzyme, such as trypsin, to produce a protein-specific set of tryptic peptide fragments. The peptide masses can be determined by mass spectrometry (MS). For this procedure, matrix-assisted laser desorption time-of-flight (MALDI- TOF) MS is commonly applied. This technique is highly specific and sensitive to the attomol level [47]. Peptide spectra obtained by this procedure can be used to search databases for identification.

Yeast two-hybrid system

The yeast-two hybrid system (Y2H) is a powerful tool for analyzing protein-protein interactions [14]. This technique uses a protein of interest fused to the DNA-binding domain of the yeast transcription factor GAL4. This transcriptional activator is required for the expression of genes encoding enzymes of galactose utilization. It contains two separable and functionally essential domains: the N-terminal domain, which binds to specific DNA sequences, and a C-terminal domain containing acidic regions, which is necessary to activate transcription. A functional Y2H system consists of two hybrid proteins containing parts of GAL4: the GAL4 DNA-binding domain fused to a first protein, and a GAL4-activating region fused to a second protein. If both proteins can form a protein-protein complex and reconstitute proximity of the GAL4 domains, transcription of a reporter gene occurs. High transcriptional activity is obtained only when both hybrids are present in a cell. Thus, this system can be applied as a method for identifying proteins that interact with a known protein with the use of galactose selection.

Protein microarrays

Protein microarrays consist of antibodies or other affinity reagents directed against a specific protein that are immobilized on a solid support, such as a glass slide [73]. These microarrays can be incubated with a complex mixture, e.g. a cell lysate containing various antigens. Bound antigens can be detected by direct chemical labeling of the complex protein mixture with a fluorescent dye before applying it to the protein microarray, by radioactively labeled proteins, or by using secondary antibodies directed against the antigens. This technique has been successfully applied in order to detect changes in protein expression following radiation of a colon carcinoma cell line [72].

Surface-enhanced laser desorption/ionisation

By surface-enhanced laser desorption/ionisation (SELDI), small proteins or fragments of trypsinized proteins (<20 kDa) are specifically absorbed to chemically or biologically coated surfaces [29]. By applying defined washing conditions, specific peptides can be eluted from the surface and can be identified by MS. SELDI has been successfully applied in order to identify cancer-associated mass spectra in cell lysates [65] and serum samples [59].

Tissue microarrays

The tissue microarray (TMA) technology makes it possible to sample up to 1000 tumor tissue sections on one glass slide, which can then be analyzed by immunohistochemistry for protein expression or in situ hybridization for nucleic acids detection [36]. Thus, TMAs are useful for the rapid evaluation of new potential marker proteins, new antibodies, and large-scale outcome studies. As the stained tissue spots have to be evaluated by an expert in a very time-consuming procedure, algorithms were developed that permit the automated, continuous, and quantitative analysis of TMAs, including the separation of tumor cells from stromal elements and the sub- cellular localization of the signals of interest [6].

Other proteomics techniques

Other commonly used techniques in proteome research include the phage display method [10]. In this approach, recombinant bacteriophages that express a protein of interest fused to a capsid or coat protein are designed. The technique can be used for high throughput screening for peptide epitopes, peptide ligands, enzyme substrates, or single chain antibody fragments.

A powerful technique for monitoring macromolecular interactions is the fluorescence resonance energy transfer (FRET) method [60]. It can be applied to studying all kinds of interactions or conformational changes of proteins, and it can alsobe used for microscopic visualization and subcellular localization of biochemical reactions.

Proteomics in cancer cell research

Various comparative 2D-PAGE experiments for analyzing differences in the protein expression pattern of human cancer cell lines have been performed. A general strategy for this approach is shown in Fig. 1. Cancer cell line-related investigations included pure protein expression studies, e.g. protein expression profiling in hepatocellular carcinoma (HCC) cells [61], gastric carcinoma cells [78], ovarian carcinoma cells [82], or mammary carcinoma cells [1]. However, most of the cancer cell studies were performed on account of functional investigations, e.g. analyses of invasion and metastasis [85], or proliferation and differentiation [76]. Moreover, many of these functional studies concerned the cellular response of cancer cells against stress factors, including heat [77] or drugs [8,49]. Furthermore, proteomics appears as a promising strategy to compare the protein expression profiles in drug- resistant or other therapy-resistant cancer cell lines with those of non-resistant counterparts.

Fig. 1. General strategy to perform proteomics in cancer cell research.

Therapy-resistant cancer cell lines

Therapy resistance, e.g. drug resistance, radiation resistance, or thermoresistance, is the main cause of therapeutic failure and death in patients suffering from malignancies. Tumor cells can be naturally resistant to anticancer treatment, and they are able to develop acquired therapy-resistant phenotypes, which include the multidrug resistance (MDR) phenomenon. The MDR phenotype is characterized by simultaneous resistance of tumor cells to various antineoplastic agents that are unrelated structurally and functionally. Besides the classical MDR phenotype, mediated by the enhanced expression of the adenosine triphosphate-binding cassette (ABC) transporter [42] P-glycoprotein (P-gp) [3], alternative forms of multidrug-resistant tumor cells have been described. Commonly used terms to designate this phenomenon are atypical MDR or non-P- gp-mediated MDR.

In the last few years, some of the mechanisms leading to atypical MDR have been identified. These mechanisms include enhanced expression of alternative ABCtransporters, such as MRP1-MRP8 [37] or BCRP [38], or alterations in apoptotic pathways [35]. However, as all these mechanisms could not explain the MDR phenotype of all drug- resistant cells, other additional resistance mechanisms must be active in cancer cells. Furthermore, the current concept of MDR is based on the hypothesis that MDR is multifactorial and heterogenous.

To improve response rates of cancer patients to chemotherapeutic treatment, chemotherapy has been combined with experimental treatment regimens, e.g. hyperthermia, in recent years. Good responses have been reported with combined thermochemotherapy in several experimental tumor models, as well as in advanced cancer patients [12,86], including tumor cells exhibiting a MDR phenotype [56]. Thus, it turned out that chemotherapy combined with hyperthermia might be considered a promising approach. The clinical success of this combined anticancer treatment may be limited by the induction of MDR phenotypes and additionally by the development of thermoresistance. Consequently, the elucidation of the biological mechanisms involved in drug resistance and thermoresistance is of urgent importance to develop new treatment modalities and to improve response rates in advanced tumors.

In order to gain a deeper understanding of therapy resistance in human neoplasms, various in vitro model systems derived from many tumor entities have been established over the recent years. For this approach, cancer cell lines were usually exposed to stepwise- increased concentrations of different antineoplastic agents for several months, resulting in the selection of drug-resistant sublines [9,41], In analogy, thermoresistant (TR) cell lines were established by exposure to increasing temperatures [39,74,79]. In various biochemical studies using these in vitro systems, marked differences between the therapy-sensitive parental cells and the corresponding therapy-resistant sublines have been described. However, as these studies could not explain all therapy-resistant phenotypes of cancer cells in detail, other additional mechanisms must contribute to drug resistance and thermoresistance. The proteomic approach is a powerful strategy to identify new factors that could play a role in therapy resistance of neoplastic cells. 2D- PAGE or alternative proteomics techniques provide ideal tools to compare the protein expression patterns in parental sensitive cancer cells with those in different drug-resistant, TR, or radiation- resistant cancer cell lines. An overview of comparing 2D-PAGE studies using human cancer cell lines and therapy-resistant cell variants is shown in Table 1.

Proteomic analyses of therapy-resistant cancer cell lines

The first 2D-PAGE studies using cancer cell lines and corresponding drug-resistant sublines were already performed in the mid-1980s [63]. In those experiments, expression patterns of [^sup 35^S]-methionine-labeled proteins prepared from parental KB cells and multidrug-resistant variants selected for resistance against colchicine, doxorubicin or vinblastine were analyzed. Protein alterations in the multidrug-resistant lines included the decreased prevalence of members of a family of proteins of molecular mass in the range of 70-80 kDa, pI 4.8-5.0, and the increased expression of a 170 kDa protein in membrane preparations of these cell lines. Moreover, in the colchicine-selected multidrug-resistant KB cell variant KB-Ch, the increased synthesis of a protein of molecular mass 21 kDa, pI 5.0, could be observed. Although Western blot experiments indicated that the increased expression of a 170 kDa protein is probably identical to P-gp, the identity of the differentially expressed proteins was not determined.

In the last few years, systematic proteomics studies were conducted to identify potential proteins involved in drug resistance [27,30] and thermoresistance using cell culture models derived from breast cancer [22], cervix carcinoma [62], colon carcinoma [19,68], fibrosarcoma [68], gastric carcinoma [57,64,66,70], hepatoma [62], lung cancer [19], melanoma [57,69,71], and pancreatic carcinoma [58,67]. The sensitive parental cell lines and their therapy- resistant sublines were analyzed for differences in the protein expression patterns by 2D-PAGE. For this approach, several independent 2D-PAGEs were regularly performed. Using PDQUEST software, the different gels were scanned. In general, the scanned gels were used for calculating cell line-specific master gel images. Decreased or increased protein levels were determined by comparing differences in the optical density (OD) of corresponding protein spots in cell line-specific gel images. Proteins showing differences in expression level were identified by MALDI-TOF MS, or microsequencing after enzymatic hydrolysis in the gel. After this procedure, for some of the proteins, the differential protein expression level was confirmed by alternative, more specific techniques. Fig. 2 illustrates an example of this strategy: the protein expression patterns of the parental human pancreatic carcinoma cell line EPP85-181P and its TR derivative EPP85-181P-RT were analyzed by 2D-PAGE. The overexpressed protein spot, indicated in Fig. 2A, was hydrolyzed with trypsin, and the MALDT-TOF MS (Fig. 2B) identified the spot as the endoplasmic reticulum (ER) protein reticulocal-bin [54]. A further example is shown in Fig. 3: the protein expression profiles of parental human gastric carcinoma EPG85-257P cells and the TR counterpart EPG85-257P-RT were analyzed by 2D-PAGE. Evaluation of the silver-stained gels using the PDQUEST software revealed at least 19 MALDI-TOF MS-identified proteins exhibiting alterations at the expression level [70]. Fig. 3B shows increased expression of the small heat shock factor Hsp27 and of a variant of Hsp27 in the TR variant EPG85-257P-TR. As shown in Fig. 3C, the increased expression of Hsp27 was confirmed by Western blot analysis. Since expression of Hsp27 may be the result of increased temperature [32], the data are conclusive.

Table 1. Therapy-resistant cancer cell lines used for 2D-PAGE analyses

Fig. 2. Enhanced expression level of reticulocalbin in TR pancreatic carcinoma EPP85-181P-TR cells. (A) 2D-PAGE analysis of silver-stained protein expression patterns in parental EPP85-181P cells and the TR counterpart EPP85-181P-TR. (B) Mass spectrum (MS) of reticulocalbin following in-gel digestion with trypsin. (The 2D- PAGE images were kindly provided by Pranav Sinha, Klagenfurt, Austria; the reticulocalbin-specific MS image was kindly provided by Martina Schnlzer, DKFZ, Heidelberg, Germany.)

Hsp27 may act in signal transduction pathways and is an ATP- independent powerful molecular chaperone, its main chaperone function being protection against protein aggregation [11]. Its activity contributes to mechanisms that enable tumor cells and normal cells to survive and to recover from stressful conditions by as yet incompletely understood mechanisms. Hsp27 is of special clinical interest because of data suggesting its role in thermoresistance by acting as an anti-apototic protein [15,44]. Thus, it is not astonishing that the expression of Hsp27 is differentially regulated in the TR cell variant. However, the exact molecular mechanism of Hsp27, e.g. modulation of apoptotic signals or correct refolding of drug-damaged proteins, by which Hsp27 contributes to thermoresistance, is not yet clear.

Fig. 3. Analysis of protein expression by the proteomic approach in the thermosensitive, parental gastric carcinoma cell line EPG85- 257P and in its TR variant EPG85-257P-TR. (A) 2D-PAGE analysis of silver stained protein expression patterns in both cell lines. (B) Detailed mag\nification of 20-PAGE images. In the TR cell line EPG85- 257P-TR, additional protein spots could be observed. MALDI-TOF MS identified one of them as Hsp27 and another spot as variant of Hsp27. (C) Confirmation of differential Hsp27 expression by Western blot. (The 2D-PAGE images were kindly provided by Pranav Sinha, Klagenfurt, Austria.)

A large number of differentially expressed proteins could be identified by comparing the 2D-PAGE protein expression patterns of sensitive and therapy-resistant cancer cell variants. Only a few of the factors identified in these 2D-PAGE studies have been previously linked to drug resistance or thermoresistance. The role of these proteins in therapy resistance still needs to be clarified. Furthermore, it is also unclear whether they are merely co- regulated, or whether the alterations in expression may be the result of unspecific events. Thus, it is absolutely essential to evaluate the data to find out whether the potentially new factor is functionally involved in therapy resistance, or, e.g. in the case of a specific co-regulation, is useful as diagnostic or prognostic marker.

Validation of the biological relevance in therapy resistance of potential new factors

The potential role of a new factor identified by proteomic techniques in a biological mechanism has to be proven by functional studies. This approach will be discussed for two different factors identified by 2D-PAGE analyses of drug-resistant carcinoma cell lines.

2D-PAGE analyses of a gastric carcinoma-derived drug resistance model demonstrated various alterations in protein expression profiles in the drug-resistant cell lines [57,66,70]. Microsequencing of a protein spot found to be overexpressed in the mitoxantrone-selected atypical multidrug-resistant gastric carcinoma cell line EPG85-257RNOV revealed amino acid sequences that were similar to the "transporter associated with antigen processing" (TAP) 1. Northern and Western blot analyses confirmed that the expression levels of TAP1 and TAP2 are indeed increased in the atypical multidrug-resistant gastric carcinoma cell line [40]. TAP represents an additional member of the ABC-transporter superfamily [42]. TAP, a heterodimer formed by TAP1 and TAP2 subunits, physiologically plays a major role in major histocompatibility complex (MHC) class I-restricted antigen presentation by mediating peptide translocation over the endoplasmic reticulum (ER) membrane [51]. TAP1 and TAP2 are homologous polypeptides, each possessing a hydrophobic N-terminal domain and a C-terminal nucleotide-binding domain. Both monomers are required for peptide binding and translocation, preferentially peptides of 8-15 amino acid residues. It has been reported previously that over-expression of TAP could be detected in MDR cell lines by a TAP1-specific antiserum [31]. This study demonstrated that expression of rat cDNAs encoding TAP1 and TAP2 subunits in the TAP-deficient lymphoblastoid cell line T2 could lead to a slightly elevated tolerance to etoposide. Consistent with these data, a cDNA micro-array study analyzing the mRNA expression profiles in different drug-resistant human hepatoma cell lines likewise revealed that TAP1 is associated with resistance against mitoxantrone [50].

For a functional validation of the potential role of TAP in the mitoxantrone-selected atypical MDR phenotype of the gastric carcinoma cell line EPG85-257RNOV, both TAP subunits encoding cDNA molecules, TAP1 and TAP2, were transfected into the drug-sensitive parental counterpart EPG85-257P [40]. This experimental design conferred a 3.3-fold resistance to mitoxantrone, but no cross- resistance to other antineoplastic agents. Furthermore, cell clones transfected with both, but not singularly expressing TAP1 or TAP2, reduced cellular mitoxantrone accumulation. The data indicate that the heterodimeric TAP complex possesses characteristics of a xenobiotic transporter, and that the TAP dimer is functionally involved in atypical MDR of human cancer cells. However, the question of whether TAP is possibly useful as a diagnostic or prognostic marker for drug resistance has to be evaluated in further studies using clinical specimens.

Fig. 4. Increased expression of 14-3-3[sigma] in the atypical multidrug-rcsistanl pancreatic carcinoma cell line EPP85-181RNOV. (A) 2D-PAGE analysis of silver-stained protein expression patterns in parental EPP85-181P cells and the drug-resistant variant EPP85- 181RNOV. (B) PDQUEST analysis of the OD of the upper protein spot demonstrated a 2.1-fold increased expression level. Error bars represent standard deviation of three independent experiments. MALDI- TOF MS identified the protein spot as 14-3-3[sigma]. (C) Northern blot analysis confirmed a weak elevated 14-3-3[sigma] expression at the transcriptional level. (The 2D-PAGE images were kindly provided by Pranav Sinha, Klagenfurt, Austria.)

Another protein that was found to be altered at the expression level in different therapy-resistant cancer cell models is a member of the family of 14-3-3 proteins [17], 14-3-3[sigma], also named stratifin. As shown in Fig. 4, the expression level of 14-3- 3[sigma] was originally found to be increased in the mitoxantrone- selected atypical MDR pancreatic carcinoma cell line EPP85-181RNOV [58,67], Subsequent 2D-PAGE studies using TR carcinoma cell variants found 14-3-3[sigma] to be overexpressed in TR and drug-sensitive gastric carcinoma EPG85-257P-TR cells [70], but was down-regulated in the TR and drug-sensitive pancreatic carcinoma cell line EPP85- 181P-TR [58].

As 14-3-3 family proteins have many functions in a broad range of organisms, including critical roles in signal transduction pathways and cell cycle regulation [17], 14-3-3[sigma] appeared as an interesting candidate molecule to be potentially involved in drug resistance or thermoresistance. 14-3-3[sigma] was identified as a p53-inducible gene involved in cell cycle checkpoint control after DNA damage [23] and in preventing mitotic death after DNA damage [7]. 14-3-3[sigma] interacts with p53 in response to treatment with DNA-damaging anthracy-clines, and 14-3-3[sigma] expression led to stabilized expression of p53 [87].

However, to test the hypothesis that 14-3-3[sigma] may contribute to any of the therapy-resistant phenotypes of carcinoma cells, the 14-3-3[sigma] encoding cDNA was cloned into a CMV promoter- containing expression vector and used to transfert the drug- sensitive and thermosensitive pancreatic carcinoma cell line EPP85- 181P. Altogether, 72 14-3-3[sigma] cDNA-transfected clones were analyzed for any biological effect of 14-3-3[sigma] overexpression on the drug-resistant phenotype. In Fig. 5, the analyses of two representative clones are shown in detail. A distinct overexpression of transgenic 14-3-3[sigma] could be achieved at the mRNA level (Fig. 5A) as well as at the protein level (Fig. 5B).

To analyze potential effects of 14-3-3[sigma] on cell cycle arrest following mitoxantrone exposure, cell cycle analyses were performed following propidium iodide staining by flow cytometry. As shown in Fig. 5C, mitoxantrone treatment of drug-sensitive EPP85- 181P cells resulted in a typical DNA-damaging, drug-triggered 62 arrest, whereas no shift to G2 arrest could be observed in the drug- resistant cell line EPP85-181RNOV. However, none of the 14-3- 3[sigma]-transfected clones showed any effects on the mitoxantrone- specific response on cell cycle arrest. In accordance with these data, the 14-3-3[sigma] transfectants showed no alterations in IC^sub 50^-values as measured by a cell proliferation assay (Fig. 5D). All these data indicate that 14-3-3[sigma] does not directly contribute to the drug-resistant phenotype of these pancreatic carcinoma cells. However, transfection experiments do not exclude that 14-3-3[sigma] may be part of a multimodal mechanism.

Fig. 5. Transfection of the parental, drug-sensitive pancreatic carcinoma cell line EPP85-181P with a 14-3-3[sigma] encoding CMV- promoter driven cDNA. (A) RT-PCR analysis of transgenic 14-3- 3[sigma] mRNA expression. As control, an aldolase-specific RT-PCR was performed. (B) Western blot analysis of transgenic V5-tagged 14- 3-3[sigma] protein expression. For loading control, the blots were stripped and incubated with an antibody directed against actin. (C) Cell cycle analysis of pancreatic carcinoma cells following exposure to 20 nM mitoxantrone for 1 h. (D) Cell proliferation assay (cellular protein staining with sulforhodamine B) Reassessment of IC^sub 50^ values of 14-3-3[sigma] cDNA-transfected pancreatic carcinoma cells. EPP85-181P, parental, drug-sensitive cells; EPP85- 181P/V, parental, drug-sensitive cells transfected with an empty control vector; EPP85-181P/clonel and EPP-181P/clone2, parental, drug-sensitive cells transfected with a 14-3-3[sigma] encoding expression vector; EPP85-181RNOV, atypical multidrug-resistant pancreatic carcinoma cells.

Although 14-3-3[sigma] protein was found to be differentially expressed in different therapy-resistant cancer cell lines by 2D- PAGE analyses [58,67,70], many other 20-PAGE studies dealing with completely different scientific problems identified 14-3-3[sigma] as differentially regulated compared with a control cell line or normal tissue [2,25,26,48,53,61,81,88,89]. Thus, the question arises whether differences in the 14-3-3[sigma] protein expression level detected by 2D-PAGE indeed reflect a biological, functionally relevant phenotype, or merely represent a consequence of the applied 2D-PAGE technique. 14-3-3[sigma] and other members of the 14-3-3 protein family that are likewise commonly found to be differentially regulated in 2D-PAGE studies [16,24,49,53,57,58,69,70] may represent a family of proteins that is most suitable to be stained following 2D protein separation. This point of view is supported by the observation that additional families of proteins that were identified to be differentially regulated in therapy- resistantcancer cell lines are frequently detected in various 2D- PAGE studies. These families of proteins include for example heat shock proteins (Hsp) [16,24,26,48,57,58,69,70,76] or fatty acid binding proteins (FABP) [48,53,67,76]. The answer to this problem can only be solved by additional extensive experimental endeavors in future studies.

Conclusions

Proteomics provides powerful tools to study pathological processes or clinically important problems at the molecular level and will have a major impact in the future. As cell culture models are widely used and characterized to a large extent, cell lines, in particular cancer cell lines, represent the ideal object for evaluating and improving proteomics techniques. A specific and highly reproducible manipulation of these models, e.g. an acquired drug-resistant phenotype, can be analyzed in detail by methods such as 2D-PAGE. Although functional studies confirmed that potential factors identified by proteomics techniques are indeed involved in the phenotype of interest, other investigations analyzing the role of a potential new factor failed. Thus, expression data obtained by proteomics studies should be considered as preliminary. It is absolutely necessary to perform hypothesis-driven biochemical experiments to evaluate the potential role of a protein of interest. Moreover, considerable technological advances are necessary to improve proteomics technologies, which can then be introduced into clinical practice, improving diagnostics and patient treatment.

Acknowledgements

Our work in this field has been supported by the "Deutsche Krebshilfe" (Grant no. 10-1628-La 4). I am most grateful to Pranav Sinha and Julia Poland (Klagenfurt, Austria) and to Martina Schnlzer (DKFZ, Heidelberg, Germany) for collaboration in the field of proteomics. Last but not least, I would like to thank Alexandra Stege for her experimental work.

References

[1] P.J. Adam, R. Boyd, K.L. Tyson, G.C. Fletcher, A. Stamps, L. Hudson, H.R. Poyser, N. Redpath, M. Griffiths, G. Steers, A.L. Harris, S. Patel, J. Berry, J.A. Loader, R.R. Townsend, L. Daviet, P. Legrain, R. Parekh, J.A. Terrett, Comprehensive proteomic analysis of breast cancer cell membranes reveals unique proteins with potential roles in clinical cancer, J. Biol. Chem. 278 (2003) 6482-6489.

[2] E. Adriaenssens, J. Lemoine, I. El Yazidi-Belkoura, H. Hondermarck, Growth signaling in breast cancer cells: outcomes and promises of protcomics, Biochem. Pharmacol. 64 (2002) 797-803.

[3] S.V. Ambudkar, C. Kimchi-Sarfaty, Z.E. Sauna, M.M. Gottesman, P-glycoprotein: from genomics to mechanism, Oncogenc 22 (2003) 7468- 7485.

[4] L. Anderson, J. Seilhamer, Acomparison of selected mRNA and protein abundances in human liver, Electrophoresis 18 (1997) 533- 537.

[5] R.E. Banks, M.J. Dunn, D.F. Hochstrasser, J.C. Sanchez, W. Blackstock, D.J. Pappin, P.J. Selby, Protcomics: new perspectives, new biomedical opportunities, Lancet 356 (2000) 1749-1756.

[6] R.L. Camp, G.G. Chung, D.L. Rimm, Automated subcellular localization and quantification of protein expression in tissue microarrays, Nat. Med. 8 (2002) 1323-1327.

[7] T.A. Chan, H. Hermeking, C. Lengauer, K.W. Kinzler, B. Vogelstein, 14-3-3[sigma] is required to prevent mitotic catastrophe after DNA damage, Nature 401 (1999) 616-620.

[8] S.T. Chen, T.L. Pan, Y.C. Tsai, C.M. Huang, Proteomics reveals protein profile changes in doxorubicin-treated MCF-7 human breast cancer cells, Cancer Lett. 181 (2002) 95-107.

[9] M. Dietel, H. Arps, H. Lage, A. Niendorf, Membrane vesicle formation due to acquired mitoxantrone resistance in human gastric carcinoma cell line EPG85-257, Cancer Res. 50 (1990) 6100-6106.

[10] I.S, Dunn, Phage display of proteins, Curr. Opin. Biotechnol. 7 (1996) 547-553.

[11] M. Ehrnsperger, S. Graber, M. Gaestel, J. Buchner, Binding of non-native protein to Hsp25 during heat shock creates a reservoir of folding intermediates for reactivation, EMBO J. 16 (1997) 221- 229.

[12] M.H. Falk, R.D. Issels, Hyperthermia in oncology, Int. J. Hyperthermia 17 (2001) 1-18.

[13] S.J. Fey, P.M. Larsen, 2D or not 2D. Two-dimensional gel electrophoresis, Curr. Opin. Chem. Biol. 5 (2001) 26-33.

[14] S. Fields, O. Song, A novel genetic system to detect protein- protein interactions, Nature 340 (1989) 245-246.

[15] A. Fortin, H. Raybaud-Diogene, B. Tetu, R. Deschenes, J. Huot, J. Landry, Overexpression of the 27 kDa heat shock protein is associated with thermoresistance and chemoresistance but not with radioresistance, Int. J. Radiat. Oncol. Biol. Phys. 46 (2000) 1259- 1266.

[16] M. Fountoulakis, R. Hardmeier, H. Hoger, G. Lubec, Postmortem changes in the level of brain proteins, Exp. Neurol. 167 (2001) 86-94.

[17] H. Fu, R.R. Subramanian, S.C. Masters, 14-3-3 proteins: structure, function, and regulation, Annu. Rev. Pharmacol. Toxicol. 40 (2000) 617-647.

[18] A. Gorg, C. Obermaier, G. Boguth, A. Harder, B. Scheibe, R. Wildgruber, W. Weiss, The current state of two-dimensional electrophoresis with immobilized pH gradients, Electrophoresis 21 (2000) 1037-1053.

[19] E.K. Han, S.K. Tahir, S.P. Cherian, N. Collins, S.C. Ng, Modulation of paclitaxel resistance by annexin IV in human cancer cell lines, Br. J. Cancer 83 (2000) 83-88.

[20] S.M. Hanash, Biomedical applications of two-dimensional electrophoresis using immobilized pH gradients: current status, Electrophoresis 21 (2000) 1202-1209.

[21] S. Hanash, Disease proteomics, Nature 422 (2003) 226-232.

[22] Y. Hathout, K. Riordan, M. Gehrmann, C. Fenselau, Differential protein expression in the cytosol fraction of an MCF-7 breast cancer cell line selected for resistance toward melphalan, J. Proteome. Res. 1 (2002) 435-442.

[23] H. Hermeking, C. Lengauer, K. Polyak, T.C. He, L. Zhang, S. Thiagalingam, K.W. Kinzler, B. Vogelstein, 14-3-3[sigma] is a p53- regulated inhibitor of G2/M progression, Mol. Cell 1 (1997) 3-11.

[24] V.M. Hoang, R. Foulk, K. Clauser, A. Burlingame, B.W. Gibson, S.J. Fisher, Functional proteomics: examining the effects of hypoxia on the cytotrophoblast protein repertoire, Biochemistry 40 (2001) 4077-4086.

[25] H. Hondermarck, A.S. Vercoutter-Edouart, F. Revillion, J. Lemoine, I. el-Yazidi-Belkoura, V. Nurcombe, J.P. Peyrat, Proteomics of breast cancer for marker discovery and signal pathway profiling, Proteomics 1 (2001) 1216-1232.

[26] H. Hondermarck, L. Dolle, I. El Yazidi-Belkoura, A.S. Vercoutter-Edouart, E. Adriaenssens, J. Lemoine, Functional proteomics of breast cancer for signal pathway profiling and target discovery, J. Mammary Gland Biol. Neoplasia 7 (2002) 395-405.

[27] Y. Huang, W. Sade, Drug sensitivity and resistance genes in cancer chemotherapy: a chemogenomics approach, Drug Discov. Today 8 (2003) 356-363.

[28] I. Humphery-Smith, S.J. Cordwell, W.P. Blackstock, Proteome research: complementarity and limitations with respect to the RNA and DNA worlds, Electrophoresis 18 (1997) 1217-1242.

[29] T.W. Hutchens, T.T. Yip, New desorption strategies for the mass analysis of macromolecules, Rapid Commun. Mass Spectrom. 7 (1993) 576-580.

[30] G. Htter, P. Sinha, Proteomics for studying cancer cells and the development of chemoresistance, Proteomics 1 (2001) 1233-1248.

[31] M.A. Izquierdo, J.J. Neefjes, A.E. Mathari, M.J. Flens, G.L. Scheffer, R.J. Scheper, Overexpression of the ABC transporter TAP in multidrug-resistant human, Br. J. Cancer 74 (1996) 1961-1967.

[32] C. Jolly, R.I. Morimoto, Role of the heat shock response and molecular chaperones in oncogenesis and cell death, J. Natl. Cancer Inst. 92 (2000) 1564-1572.

[33] E. Kaltschmidt, H.G. Wittmann, Ribosomal proteins. VII. Two- dimensional polyacrylamide gel electrophoresis for fingerprinting of ribosomal proteins, Anal. Biochem. 36 (1970) 401-412.

[34] E. Kaltschmidt, H.G. Wittmann, Ribosomal proteins. XII. Number of proteins in small and large ribosomal subunits of E. coli as determined by two-dimensional gel electrophoresis, Proc. Natl. Acad. Sci. USA 67 (1970) 1276-1282.

[35] S.H. Kaufmann, D.E. Vaux, Alterations in the apoptotic machinery and their potential role in anticancer drug resistance, Oncogene 22 (2003) 7414-7430.

[36] J. Kononen, L. Bubendorf, A. Kallioniemi, M. Barlund, P. Schraml, S. Leighton, J. Torhorst, M.J. Mihatsch, G. Sauter, O.P. Kallioniemi, Tissue microarrays for high-throughput molecular profiling of tumor specimens, Nat. Med. 4 (1998) 844-847.

[37] G.D. Kruh, M.G. Belinsky, The MRP family of drug efflux pumps, Oncogene 22 (2003) 7537-7552.

[38] H. Lage, M. Dietel, Effect of the breast-cancer resistance protein on atypical multidrug resistance, Lancet Oncol. 1 (2000) 169- 175.

[39] H. Lage, A. Jordan, R. Scholz, M. Dietel, Thermosensitivity of multidrug-resistant human gastric and pancreatic carcinoma cells, Int. J. Hyperthermia 16 (2000) 291-303.

[40] H. Lage, C. Perlitz, R. Abele, R. Tamp, M. Dietel, D. Schadendorf, P. Sinha, Enhanced expression of human ABC-transporter tap is associated with cellular resistance to mitoxantrone, FEBS Lett. 503 (2001) 179-184.

[41] H. Lage, M. Dietel, Multiple mechanisms confer different drug-resistant phenotypes in pancreatic carcinoma cells, J. Cancer Res. Clin. Oncol. 128 (2002) 349-357.

[42] H. Lage, ABC-transporters: implications on drug resistance from microorganisms to human cancers, Int. J. Antimicrob. Agents 22 (2003) 188-199.

[43] E.S. Lander, L.M. Linton, B. Birren, C.Zody, Nusbaum, et al., International human genome sequencing consortium, Initial sequencing and analysis of the human genome, Nature 409 (2001) 860- 921.

[44] J.N. Lavoie, G. Gingras-Breton, R.M. Tanguay, J. Landry, Induction of Chinese hamster HSP27 gene expression in mouse cells confers resistance to heat shock. HSP27 stabilization of the microfilament organization, J. Biol. Chem. 268 (1993) 3420-3429.

[45] L.C. Lawrie, J.E. Fothergill, G.I. Murray, Spot the differences: proteomics in cancer research, Lancet Oncol. 2 (2001) 270-277.

[46] M. Mann, O.N. Jensen, Proteomic analysis of post- translational modifications,Nat. Biotechnol. 21 (2003) 255-261.

[47] F.W. McLafferty, E.K. Fridriksson, D.M. Horn, M.A. Lewis, R.A. Zubarev, Techview: biochemistry. Biomolecule mass spectrometry, Science 284 (1999) 1289-1290.

[48] R. Melis, R. White, Characterization of colonic polyps by two-dimensional gel electrophoresis, Electrophoresis 20 (1999) 1055- 6104.

[49] A. Mller, C. Malerczyk, U. Vlker, H. Stppler, E. Maser, Monitoring daunorubicin-induced alterations in protein expression in pancreas carcinoma cells by two-dimensional gel electrophoresis, Proteomics 2 (2002) 697-705.

[50] M. Moriyama, Y. Hoshida, M. Otsuka, S. Nishimura, N. Kato, T. Goto, H. Taniguchi, Y. Shiratori, N. Seki, M. Omata, Relevance network between chemosensitivity and transcriptome in human hepatoma cells, Mol. Cancer Ther. 2 (2003) 199-205.

[51] J.J. Neefjes, F. Momburg, G.J. Hammerling, Selective and ATP- dependent translocation of peptides by the MHC-encoded transporter, Science 261 (1993) 769-771.

[52] P.H. O'Farrell, High-resolution two-dimensional electrophoresis of proteins, J. Biol. Chem. 250 (1975) 4007-4021.

[53] M. Ostergaard, H.H. Rasmussen, H.V. Nielsen, H. Vorum, T.F. Orntoft, H. Wolf, J.E. Celis, Proteome profiling of bladder squamous cell carcinomas: identification of markers that define their degree of differentiation, Cancer Res. 57 (1997) 4111-4117.

[54] M. Ozawa, T. Muramatsu, Reticulocalbin. A novel cndoplasmic rcticulum resident Ca(2+)-binding protein with multiple EF-hand motifs and a carboxyl-terminal HDEL sequence, J. Biol. Chem. 268 (1993) 699-705.

[55] A. Pandey, M. Mann, Proteomics to study genes and genomes, Nature 405 (2000) 837-846.

[56] P. Pantazis, Preclinical studies of water-insoluble camptothecin congeners: cytotoxicity, development of resistance, and combination treatments, Clin. Cancer Res. 1 (1995) 1235-1244.

[57] J. Poland, D. Schadendorf, H. Lage, M. Schnlzer, J.E. Celis, P. Sinha, Study of therapy resistance in cancer cells with functional proteome analysis, Clin. Chem. Lab. Med. 40 (2002) 221- 234.

[58] J. Poland, A. Urbani, H. Lage, M. Schnlzer, P. Sinha, Study of the development of thermoresistance in human pancreatic carcinoma cell lines using proteome analysis, Electrophoresis 25 (2004) 173- 183.

[59] C. Rosty, L. Christa, S. Kuzdzal, W.M. Baldwin, M.L. Zahurak, F. Carnot, D.W. Chan, M. Canto, K.D. Lillemoe, J.L. Cameron, C.J. Yeo, R.H. Hruban, M. Goggins, Identification of hepatocarcinoma-intestine-pancreas/pancreatitis-associated protein I as a biomarker for pancreatic ductal adenocarcinoma by protein biochip technology, Cancer Res. 62 (2002) 1868-1875.

[60] J.A. Schmid, H.H. Sitte, Fluorescence resonance energy transfer in the study of cancer pathways, Curr. Opin. Oncol. 15 (2003) 55-64.

[61] T.K. Seow, S.E. Ong, R.C. Liang, E.C. Ren, L. Chan, K. Ou, M.C. Chung, Two-dimensional electrophoresis map of the human hepatocellular carcinoma cell line, HCC-M, and identification of the separated proteins by mass speclrometry, Electrophoresis 21 (2000) 1787-1813.

[62] D.W. Shen, S. Akiyama, P. Schoenlein, I. Pastan, M.M. Gottesman, Characterisation of high-level cisplatin-resistant cell lines established from a human hepatoma cell line and human KB adenocarcinoma cells: cross-resistance and protein changes, Br. J. Cancer 71 (1995) 676-683.

[63] D.W. Shen, C. Cardarelli, J. Hwang, M. Cornwell, N. Richert, S. Ishii, I. Pastan, M.M. Gottesman, Multiple drug-resistant human KB carcinoma cells independently selected for high-level resistance to colchicine, adriamycin, or vinblastine show changes in expression of specific proteins, J. Biol. Chem. 261 (1986) 7762-7770.

[64] Y. Shi, Y. Han, X. Wang, Y. Zhao, X. Ning, B. Xiao, D. Fan, MGr1-Ag is associated with multidrug-rcsistant phenotype of gastric cancer cells, Gastric Cancer 5 (2002) 154-159.

[65] M. Shiwa, Y. Nishimura, R. Wakatabe, A. Fukawa, H. Arikuni, H. Ota, Y. Kato, T. Yamori, Rapid discovery and identification of a tissue-specific tumor biomarker from 39 human cancer cell lines using the SELDI ProteinChip platform, Biochem. Biophys. Res. Commun. 309 (2003) 18-25.

[66] P. Sinha, G. Htter, E. Kttgen, M. Dietel, D. Schadendorf, H. Lage, Increased expression of annexin I and thioredoxin detected by two-dimensional gel electrophoresis of drug resistant human stomach cancer cells, J. Biochem. Biophys. Methods 18 (1998) 105-116.

[67] P. Sinha, G. Htter, E. Kttgen, M. Dietel, D. Schadendorf, H. Lage, Increased expression of epidermal fatty acid binding protein, cofilin, and 14-3-3-[sigma] (stratifin) detected by two-dimensional gel electrophoresis, mass spectrometry and micosequencing of drug- resistant human adenocarcinoma of the pancreas, Electrophoresis 20 (1999) 2952-2960.

[68] P. Sinha, G. Htter, E. Kttgen, M. Dietel, D. Schadendorf, H. Lage, Search for novel proteins involved in the development of chemoresistance in colorectal cancer and fibrosarcoma cells in vitro using two-dimensional electrophoresis, mass spectrometry and microsequencing, Electrophoresis 20 (1999) 2961-2969.

[69] P. Sinha, S. Kohl, J. Fischer, G. Htter, M. Kern, E. Kttgen, M. Dietel, H. Lage, M. Schnlzer, D. Schadendorf, Identification of novel proteins associated with the development of chemoresistance in malignant melanoma using two-dimensional electrophoresis, Electrophoresis 21 (2000) 3048-3057.

[70] P. Sinha, J. Poland, M. Schnlzer, J.E. Celis, H. Lage, Characterization of the differential protein expression associated with thermoresistance in human gastric carcinoma cell lines, Electrophoresis 22 (2001) 2990-3000.

[71] P. Sinha, J. Poland, S. Kohl, M. Schnlzer, H. Helmbach, G. Htter, H. Lage, D. Schadendorf, Study of the development of chemoresistance in melanoma cell lines using proteome analysis, Electrophoresis 24 (2003) 2386-2404.

[72] A. Sreekumar, M.K. Nyati, S. Varambally, T.R. Barrette, D. Ghosh, T.S. Lawrence, A.M. Chinnaiyan, Profiling of cancer cells using protein microarrays: discovery of novel radiation-regulated proteins, Cancer Res. 61 (2001) 7585-7593.

[73] A. Sreekumar, A.M. Chinnaiyan, Using protein microarrays to study cancer, Biotechniques (Suppl.) (2002) 46-53.

[74] U. Stein, H. Lage, A. Jordan, W. Walther, S.E. Bates, T. Litman, P. Hohenberger, M. Dietel, Impact of BCRP/MXR, MRP1 and MDR1/ P-Glycoprotein on thermoresistant variants of atypical and classical multidrug resistant cancer cells, Int. J. Cancer 97 (2002) 751-760.

[75] T.H. Steinberg, L.J. Jones, R.P. Haugland, V.L. Singer, SYPRO orange and SYPRO red protein gel stains: one-step fluorescent staining of denaturing gels for detection of nanogram levels of protein, Anal. Biochem. 239 (1996) 223-237.

[76] R. Stierum, M. Gaspari, Y. Dommels, T. Ouatas, H. Pluk, S. Jespersen, J. Vogels, K. Verhoeckx, J. Groten, B. van Ommen, Proteome analysis reveals novel proteins associated with proliferation and differentiation of the colorectal cancer cell line Caco-2, Biochim. Biophys. Acta 1650 (2003) 73-91.

[77] K. Takeuchi, K. Nakamura, M. Fujimoto, S. Kaino, S. Kondoh, K. Okita, Heat stress-induced loss of eukaryotic initiation factor 5A (eIF-5A) in a human pancreatic cancer cell line, MIA PaCa-2, analyzed by two-dimensional gel electrophoresis, Electrophoresis 23 (2002) 662-669.

[78] A.J. Tomlinson, M. Hincapie, G.E. Morris, R.M. Chicz, Global proteome analysis of a human gastric carcinoma, Electrophoresis 23 (2002) 3233-3240.

[79] H. Tnnies, J. Poland, P. Sinha, H. Lage, Association of genomic imbalances with drug resistance and thermoresistance in human gastric carcinoma cells, Int. J. Cancer 103 (2003) 752-758.

[80] J.C. Venter, M.D. Adams, E.W. Myers, P.W. Li, R.J. Mural, et al., The sequence of the human genome, Science 291 (2001) 1304- 1351.

[81] A.S. Vercoutter-Edouart, J. Lemoine, X. Le Bourhis, H. Louis, B. Boilly, V. Nurcombe, F. Revillion, J.P. Peyrat, H. Hondermarck, Proteomic analysis reveals that 14-3-3[sigma] is down- regulated in human breast cancer cells, Cancer Res. 61 (2001) 76- 80.

[82] H. Wang, M.T. Kachman, D.R. Schwartz, K.R. Cho, D.M. Lubman, A protein molecular weight map of ES2 clear cell ovarian carcinoma cells using a two-dimensional liquid separations/mass mapping technique, Electrophoresis 23 (2002) 3168-3181.

[83] V.C. Wasinger, S.J. Cordwell, A. Cerpa-Poljak, J.X. Van, A.A. Gooley, M.R. Wilkins, M.W. Duncan, R. Harris, K.L. Williams, I. Humphery-Smith, Progress with gene-product mapping of the Mollicutes: Mycoplasma genitalium, Electrophoresis 16 (1995) 1090- 1094.

[84] M.R. Wilkins, J.C. Sanchez, A.A. Gooley, R.D. Appel, I. Humphery-Smith, D.F. Hochstrasser, K.L. Williams, Progress with proteome projects: why all proteins expressed by a genome should be identified and how to do it, Biotech. Gen. Eng. Rev. 13 (1995) 19- 50.

[85] W. Wu, X. Tang, W. Hu, R. Lotan, W.K. Hong, L. Mao, Identification and validation of metastasis-associated proteins in head and neck cancer cell lines by two-dimensional electrophoresis and mass spcctromelry, Clin. Exp. Metastasis 19 (2002) 319-326.

[86] P. Wust, B. Hildebrandt, G. Sreenivasa, B. Rau, J. Gellermann, H. Riess, R. Felix, P.M. Schlag, Hyperthermia in combined treatment of cancer, Lancet Oncol. 3 (2002) 487-497.

[87] H.Y. Yang, Y.Y. Wen, C.H. Chen, G. Lozano, M.H. Lee, 14-3-3 sigma positively regulates p53 and suppresses tumor growth, Mol. Cell Biol. 23 (2003) 7096-7107.

[88] I.E. Yazidi-Belkoura, E. Adriaenssens, A.S. Vercoutter- Edouart, J. Lemoine, V. Nurcombe, H. Hondermarck, Technol. Cancer Res. Treat 1 (2002) 287-296.

[89] L.R. Yu, X.X. Shao, W.L. Jiang, D. Xu, Y.C. Chang, Y.H. Xu, Q.C. Xia, Proteome alterations in human hepatoma cells transfected with antisense epidermal growth factor receptor sequence, Electrophoresis 22 (2001) 3001-3008.

Hermann Lage*

Humboldt University Berlin, Charit Campus Mitte, Institute of Pathology, Schumannstr. 20/21, D-10117 Berlin, Germany

Received 2 December 2003; accepted 5 January 2004

* Tel: +49-30-450-536-045; fax: +49-30-450-536-900.

E-mail address: hermann.lage@cha\rite.de (H. Lage).

Copyright Urban & Fischer Verlag 2004

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