Genomic and proteomic analysis in uveal melanoma
Zuidervaart, W.Citation
Zuidervaart, W. (2005, May 25). Genomic and proteomic analysis in uveal melanoma. Retrieved from https://hdl.handle.net/1887/2696
Version: Corrected Publisher’s Version
License: Licence agreement concerning inclusion of doctoral thesis in theInstitutional Repository of the University of Leiden Downloaded from: https://hdl.handle.net/1887/2696
8
P
ROTEOMIC
ANALYSIS
OF UVEAL
MELANOMA
REVEALS NOVEL
POTENTIAL
MARKERS
INVOLVED
IN TUMOR
PROGRESSION
Wieke Zuidervaart1*, Paul J. Hensbergen2*, Man-Chi Wong1, Andre .M. Deelder2, Cornelis .P.Tensen3, Martine J. Jager1, Nelleke A. Gruis3
* These authors contributed equally to this paper
1Department of Ophthalmology, 2Biomolecular Mass spectrometry Unit, Department
of Parasitology, 3Department of Dermatology, Leiden, The Netherlands
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A
BSTRACTPurpose: Patient survival in uveal melanoma may benefit from earlier recognition of potential
metastases to the liver, but as yet, proper markers indicating metastases are not available. Identification of metastasis markers would therefore be of great value. In order to identify proteins involved in metastasis development, we compared protein expression in a cell line obtained from a primary uveal melanoma with two cell lines originating from two liver metastases of the same patient.
Methods: Protein analysis was performed using two-dimensional gel electrophoresis. A subset
of proteins was subsequently identified with mass spectrometry.
Results: A set of 24 proteins was differential expressed in both of the two metastatic cell lines
as compared to the cell line derived from the primary tumor. These proteins could be subdivided in cellular functional groups with important roles in tumor development.
Conclusions: Tumor progression and development of metastases is a multicomplex system.
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I
NTRODUCTIONThe most prevalent primary intra-ocular malignancy in adults is the melanoma originating from the uveal tract, affecting approximately seven per million people in the Western world each year (Egan et al., 1988). The 5-year survival in uveal melanoma is 72%, but within 15 years of follow-up, 53% of patients will eventually die of metastatic disease (Gamel et al., 1993; McLean an Gamel 1998). Approximately 95% of patients with metastatic uveal melanoma will develop liver metastases. Accurate identification of patients with a high probability of development of metastatic disease is important for early intervention, because metastases are usually not detectable at the time of diagnosis. Metastases have often already reached an advanced stage by the time they cause symptoms (Mooy and De Jong 1996), resulting in a poor median patient survival, between two (Seddon et al., 1983) and seven months (Kath et al., 1993) after clinical diagnosis of the lesions.
Understanding the molecular changes in gene and protein expression responsible for the development and progression of uveal melanoma would be an important step toward the identification of biomarkers for invasive uveal melanoma. High throughput technologies in genomics (DeRisi et al., 1996; Alizadeh et al., 2001) and proteomics (Wilkins et al., 1996) offer the potential to find such previously unidentified alterations in malignancies.
In recent years, genomics has increased our insight in gene expression profiles in uveal melanoma (Zuidervaart et al., 2003; Tschentscher et al., 2003; Onken et al., 2004) and has provided potential clinically important screening markers. However, alterations at the RNA level may not be reflected in changes at the protein level. The application of proteomics is a powerful screening method for alterations in protein expression and posttranslational modifications. Recently, our group revealed that comparison of protein profiles of aqueous humour from eyes containing an uveal melanoma with eyes undergoing cataract surgery, could separate patients and controls on the basis of two proteins (Missotten et al., 2003). In order to identify proteins that are associated with uveal melanoma progression, we focused, in this study, on the differential protein expression of primary and metastatic uveal melanoma analyzing three cell lines representing a primary uveal melanoma and two of its metastases, using two-dimensional poly acrylamide gelelectrophoresis (2D-PAGE) and mass
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M
ATERIALS AND METHODSCell culture
Three cell lines were included in this study. One cell line is derived from a primary uveal melanoma (Mel 270) and two cell lines (Omm1.3 and Omm1.5) are derived from liver
metastases from this same primary tumor Mel 270. All cell lines were kindly provided by Prof B.R. Ksander (Schepens Eye Institute, Boston, MA). The research followed the Tenets of the Declaration of Helsinki.
The melanoma cell lines were cultured in RPMI 1640 medium (Gibco, Breda, the
Netherlands), supplemented with 3mM L-glutamine (Gibco), 2% penicillin/streptomycin and 10% FBS (Hyclone, UT). The cell cultures were incubated at 37°C in a humidified 5% CO2
atmosphere. Cells were harvested at 80% confluency and protein extraction was performed using TRIzol method as described by the supplier (TRIzol, GibcoBRL/Life Technologies). Protein concentrations were determined using the modified Bradford protein assay (Ramagli 1999).
2D-PAGE
Of each cell line, 500 µg of protein was loaded on 24-cm isoelectric focusing ready-made IPG strips with a non-linear gradient of pH 3-10 or with a linear gradient of pH 4-7 (Amersham Pharmacia Biotech (ABP), Roosendaal, the Netherlands). Rehydration of the IPG strips was performed for 22 h at 30 V after which proteins were focused for 65000 Vh (IPGphor, APB). Prior to the second dimension, IPG strips were equilibrated in 1% dithiothreitol (w/v)
followed by 2.5% iodoacetamide (w/v), both for 15 min in 50 mM Tris-HCl pH 8.8, 6 M Urea, 30% Glycerol, 2% SDS. After this procedure, the strips were placed on top of a 200x250x1.0 mm polyacrylamide gel (13% homogeneous, 2.6% cross-linking, 0.1% SDS, 375 mM Tris-HCl pH 8.8) sealed in place with agarose and runned at 5 W/gel for one hour and subsequently 15 W/gel until the bromophenol blue dye front reached the bottom of the gels (ETTAN Dalt II, APB).
Proteins were visualized using either silver or Coomassie G250 staining and scanned using a Fluor-S scanner (BIO-RAD Laboratories, Veenendaal, the Netherlands). Differences in protein levels were first defined as clear visual differences in size and/or density of matched protein spots determined by two independent reviewers. Second, gels were analyzed by PDQuest software 7.0 (BIO-RAD Laboratories) where relative spot intensities were quantified following normalization.
Mass Spectrometry
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(Matrix Science Ltd., London, UK) (http://www.matrixscience.com), allowing one missed cleavage site. Carbamidomethylcysteine was taken as a fixed modification and oxidized methionine as a variable modification. Only significant scores higher than 50 were considered as legitimate identifications but were always verified manually.
Purification of phosphopeptides by immobilized metal affinity chromatography (IMAC)
To separate phosphorylated from non-phosphorylated peptides, tryptic digests of spots of interest were acidified to pH 3 using acetic acid and subsequenly applied to a Gallium III affinity column (Pierce, Rockford, IL, USA). The column was washed twice with a solution of 1% acetic acid and once with a solution of 0.1% acetic acid containing 10% acetonitrile. After a wash with water, phosphorylated peptides were eluted with 100 mM
natriumdihydrogenphosphate (pH 9). Eluted phosphopeptides were desalted over Poros 50R2 (Applied Biosystems, Forster City, CA, USA). Peptides were eluted with 25% methanol/5% formic acid and measured by electrospray ionization time of flight MS (Waters Micromass Q-ToF, Milford, USA).
R
ESULTSDifferential protein expression in the metastasis model
We hypothesized that by studying the protein expression profiles of a cell line derived from a primary uveal melanoma and two cell lines derived from two liver metastases from the same patient, we would see a differential protein expression between the three cell lines, related to tumor progression. Proteomic profiles were analyzed of a matched set of one primary uveal melanoma cell line (Mel-270) and two of its metastases cell lines (OMM-1.3 and -1.5) using 2D-PAGE and mass spectrometry (MS). Of each cell line, four independent 2D-PAGE runs were performed: two silver-stained with a pH 3-10 range, one silver-stained with a pH 4-7 range in the first dimension for a higher resolution in this pH range, and one Coomassie-stained with a pH 3-10 range to obtain a more accurate profile for the quantification of the spots. As an example, the gel spot patterns of the primary uveal melanoma cell line (Mel-270) and the cell lines obtained from two metastases of this primary melanoma (OMM1.3 and -1.5) in the pH 3-10 range (stained with Coomassie) are shown in Figure 8.1.
Overall, the expression levels of 1184 spots were assessed using automated imaging software. In total, clear and consistent differences in expression were found for 29 spots. As an
Table 8.1 Mass spectrometric identification of differentially expressed proteins in primary (Mel-270) and metastatic uveal melanoma cell lines (OMM-1.3, -1.5).
2D-PAGE gels from primary (Mel-270) and metastatic uveal melanoma cell lines (OMM-1.3, -1.5) were analysed manually and using the PD-Quest software package (Bio-RAD). Spot quantification using PD-Quest was performed after normalization of spot intensities taking Gaussian representations of spots, as described by the supplier. Differentially expressed proteins were in-gel digested with trypsin and measured on a MALDI-ToF-ToF mass spectrometer. To confirm the identification by MALDI-ToF analysis, MS/MS analysis of selected ions was performed. However, in cases where this was not performed, the fingerprint alone was sufficient for unambiguous
identification. Proteins that were upregulated in the metastatic cell lines are indicated in bold and their fold changes in comparison to the primary tumor cell line are indicated using the following subdivision: 0 - (-)1.5 = +, ≥ 1.5-(-)5= ++, ≥ 5 - (-)10= +++, ≥ 10 - (-)50 = ++++, ≥ 50 - (-)100=+++++, ≥ 100=++++++. Inversely, fold changes of downregulated spots in the metastatic cell lines are indicated in italic, applying the same subdivision but using -.
MALDI-ToF MALDI-ToF-ToF Fold changes Protein
Number Protein Name Accession Number Main Function No. Peptidesa Cover. (%)b Peptide sequence (MS/MS)
c Cell line
Omm 1.3 Cell line Omm 1.5
Cellular defense
1 glutathione S-transferase P09210 regulating intracellular redox state 11 57 FQDGDLTLYQSNTILR -- --
2 HSP27 P04792 protein conformation stabilization 14 64 LFDQAFGLPR ++ ++
3 ααααββββ-crystallin AAP35416 protein conformation stabilization 11 53 ndd ++ ++
Apoptosis/Degradation
4 cathepsin Z NP_001327 lysosomal proteolysis 9 37 NSWGEPWGER ++ ++
5 20S proteasome α2 subunit NP_002778 ubiquitinated protein degradation 10 45 LAQQYYLVYQEPIPTAQLVQR --- --- 6 26S proteasome regulatory
chain 4 A44468 ubiquitinated protein degradation 17 41 IFQIHTSR --- ---
7 acid ceramidase, α-subunit NP_808592 degradation of ceramide 8 21 STYPPSGPTYR & LPGLLGNFPGPFEEEMK
-- -- 8 platelet-activating factor
acetylhydrolase, β-subunit P68402 degradation of platelet-activating factor 5 34 ELFSPLHALNFGIGGDTTR &IIVLGLLPR -- ---- Proliferation
9 annexin 1 P04083 growth factor 15 56 nd ++ ++
10 thioredoxin P10599 growth factor 4 49 TAFQEALDAAGDK - -
Migration
11 cofilin P23528 actin turnover 13 66 KEDLVFIFWAPESAPLK +++ ++
12 CLIM1 O00151 adapter for kinases to actin stress fibers 16 68 VTPPEGYEVVTVFPK ++++++ +++++
14 tropomodulin 3 Q9NYL9 actin turnover 18 50 FGYQFTQQGPR ++++++ ++++++
15 galectin 1 P09382 cell-cell/-extracellular interaction 10 81 VRGEVAPDAK ++ ++
16 ββββ-hexosaminidase ββββ-subunit AAA68620 glycosidase 15 28 GSIVWQEVFDDK ++++++ ++++++ Metabolism
17 pyruvate kinase 3 NP_002645 glycolytic enzyme 22 43 nd -- --
18 enolase 1 P06733 glycolytic enzyme 16 39 nd ---- ----
19 ETHE1 NP_055112 Mitochondrial homeostasis 11 75 EAVLIDPVLETAPR ---- ---
Nuclear transport
20 Ran binding protein 1 NP_002873 promotes RanGAP activity 9 46 FASENDLPEWK ++ ++
21 eIF5A XP_016093 cofactor in nuclear export 3 28 NDFQLIGIQDGYLSLLQDSGEVR
& EDLRLPEGDLGK ++++++ ++++++ Translation
22 ribosomal protein P0 NP_444505 part of ribosome 9 43 GTIEILSDVQLIK & IIQLLDDYPK -- --
23 ribosomal protein L12 NP_000967 part of ribosome 7 55 HSGNITFDEIVNIAR --- ---
24 CRHSP-24 Q9Y2V2 translation regulating protein 5 43 LQAVEVVITHLAPGTK ++++++ +++++
a number of peptides matching with identified protein b amino acid coverage (%) with MALDI-ToF-MS
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Figure 8.1 Visualization of proteomic patterns in Mel-270, OMM-1.3 and -1.5 uveal melanoma cells. Solubilized proteins from Mel-270 (A), OMM-1.3 (B) and OMM-1.5 (C) uveal melanoma cell lines
were resolved by 2D-PAGE using carrier ampholytes pH 3-10 NL in the first dimension. The second dimension runs were performed on 13% linear gradient SDS-PAGE gels. The proteins were visualized by Coomassie staining and evaluated manually and by using the PDQuest system as described under ‘Material and methods’.
This same procedure was performed for the other differentially expressed protein spots and the identity of 27 spots was successfully defined, representing 24 different proteins (Table 8.1).
Although the two metastasis cell lines had been derived from two separate liver metastases, they were very similar in their protein expression profiles. Significant downregulation in the metastatic cell lines compared with the primary uveal melanoma cell line was observed for: ribosomal protein L12 and P0, thioredoxin, actin, enolase-1, pyruvate kinase 3, 20
S-proteasome α2 subunit, 26 S-S-proteasome regulatory chain 4, the α-subunit of acid ceramidase, the β-subunit of platelet-activating factor acetylhydrolase, ETHE1 and
glutathione S-transferase. The following proteins revealed significant upregulation in the two metastatic cell lines: annexin 1, calcium-regulated heat-stable protein (CRHSP-24), cofilin, tropomodulin 3, CLIM1, galectin 1, heat shock protein 27 (HSP27), αβ-crystallin, cathepsin Z, Ran binding protein 1, eukaryotic translation initiation factor 5A (eIF5A) and
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131 Figure 8.2 Differential expression and identification of galectin 1 (A) Cropped images from
Coomassie-stained two-dimensional gels of Mel-270, OMM-1.3 and -1.5 demonstrating differential expression of spot 15 (Table 1). (B) MALDI fingerprint mass spectrum from the tryptic digest of spot 15 (Table 1). By searching the MSDB database using the Mascot search engine, this fingerprint was identified as that from galectin-1 with a score of 70. Fragments marked with an asterix correspond to tryptic fragments of galectin-1. Other fragments correspond primarily to trypsin and keratin fragments. (C) MS/MS spectrum from m/z 1041.4 [M+H]+ corresponding to the tryptic peptide VRGEVAPDAK
from galectin-1.
C
100 0 100 200 300 400 500 600 700 800 900 1000 m/z y2 y3 y5 y4 y6 b2 b3 b5 b4 b6 b8 [M+H]+ 1041.4 R el at iv e in te ns ity (% )V R G E V A P D A K
y2 y3 y5 y4 y6 b2b3b4 b5b6 b8 2HN COOH MALDI-ToF-ToF 100 800 1000 1200 1400 1600 1800 2000 2200 2400*
*
*
*
*
*
MALDI-ToF R el at iv e in te ns ity (% ) m/zB
Mel-270 OMM-1.3 OMM-1.5
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Figure 8.3 Differential expression of phosphorylated HSP27. (A) Differential expression of HSP27
between primary (Mel-270) and metastatic (OMM-1.3 and -1.5) uveal melanoma cell lines (B). ESI-Q-ToF spectrum of a tryptic digest of HSP27 after immobilized galliumIII affinity chromatography (Ga-IMAC). (C) MS/MS spectrum of m/z 578.3 [M+2H]2+ corresponding to a phosphorylated peptide from
HSP27. Phosphorylation could be mapped to Ser-3 based on the identification of a dehydroalanine (mass difference of 69, resulting from neutral loss of phosphoric acid from phosphorylated serine residue) within the mass spectrum. pS: phosphorylated serine.
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133 Discrepancies between spot location on gel and theoretical values for molecular weight and iso-electric point
Following mass spectrometric characterization, there were some proteins that showed a discrepancy in experimental molecular weight and/or iso-electric point (deduced from the location on the gel) and the theoretical values (as determined at
http://www.expasy.org/tools/pi_tool.html ).
Analysis of spot number 7, for example, led to the identification of the protein acid
ceramidase. However, the apparent molecular weight of the product according to the location on the gel was much smaller than the theoretical size of the prepro-protein of acid ceramidase (∼55 kDa). We therefore analyzed the peptides that were obtained from the fingerprint and found that the matched peptides were all located at the N-terminus. According to the
literature, under physiological conditions, the mature acid ceramidase is a heterodimer of ∼50 kDa, but can be reduced into two subunits of ∼13 kDa (α) and ∼40 kDa (β) (Bernardo et al., 1995). Both originate from the same preprotein following proteolytic processing. Therefore, the protein we identified appeared to be the α-subunit of acid ceramidase, most probably released from the β-subunit during the stringent sample preparation and/or electrophoresis procedure (Koch et al., 1996).
Another discrepancy was found for HSP27 (Figure 8.3A). The expected theoretical iso-electric point of HSP27 was more basic (7.8) than the actual pH of the excised spot according to the location on the gel (<7). Since HSP27 can be phosphorylated (Carlier et al., 1997), we attempted to identify the phosphorylation status of HSP27. For this purpose, we took
advantage of the fact that phosphorylated peptides have a tendency to bind to certain heavy metals, e.g. Ga3+ (Posewitz et al., 1999). Therefore, a tryptic digest of the differentially expressed HSP27 spot was purified using immobilised gallium (III) affinity chromatography (Ga(III)-IMAC) and subsequently analysed by mass spectrometry using electrospray
ionisation mass spectrometry. The mass chromatogram of the Ga(III)-IMAC affinity purified digest contained one salient peptide with m/z 578.3 [M+2H]2+(Figure 8.3B). This m/z was
selected for fragmentation using collision-induced dissociation, leading to the MS/MS spectrum shown in Figure 8.3C. Analysis of this spectrum clearly showed that it corresponds to a HSP27 fragment containing a phosphorylated serine residue. This residue is located at position 82 of mature HSP27 and is a known phosphorylation site (Landry et al., 1992). Because similar discrepancies in iso-electric point were found for the spots representing cofilin and enolase-1, we also tested whether these proteins were phosphorylated. After Ga (III)-IMAC and mass spectrometry of the respective tryptic digests, we identified the
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D
ISCUSSIONAt present, 2D-PAGE is still one of the primary analytical tools allowing examination of cellular proteomes. This method has been useful in numerous biological studies over the past two decades and has been successfully used to identify a number of protein alterations in tumor cells (Celis et al., 1998; Banks et al., 1999; Emmert-Buck et al., 2000). The detection of primarily high-abundant proteins is a limitation of 2D-PAGE, but can also be viewed as an advantage because such proteins can be measured and targeted easily, and therefore can be considered as ideal tumor markers.
In the present study, the protein expression of a cell line from a primary tumor was compared with two of its liver metastases, in order to get an impression of the changes in the proteomic profile during metastatic tumor progression of uveal melanoma. The acquisition of cell lines from a primary uveal melanoma and two of its liver metastases from the same donor, allowed exclusion of inter-individual differences which do not contribute to tumor progression. Twenty-seven of the 29 excised protein spots, consistently identified in four independent 2D-PAGE runs, were characterized by mass spectrometry and database inquiry (Table 1). The nature of the other differentially expressed proteins remains unknown, most likely due to an insufficient amount of material. Three separate spots were all identified as glutathione S-transferase, probably due to different modifications of the same protein.
Most of the 24 different candidate proteins have been reported to be associated with distinct and characteristic steps of tumor metastasis such as (increased) motility, (altered) adhesion, spreading, (impaired) apoptosis regulation and cellular defense. According to their possible metastasis-related or tumor progression function, the 24 identified candidate proteins can be divided into seven functional groups. Within these groups, such as cellular defense and migration, we were able to identify proteins that may be implicated in melanocytic neoplasia and tumor development in general.
Cellular defense
Oxidative stress damages cells, and this damage is causally implicated in the pathogenesis of cancer (Ames et al., 1993). Heat shock proteins (HSPs) and glutathione S-transferase (GST) are important proteins in cellular defense against various stimuli and stress. On the other hand, HSPs may also have tumor-promoting functions: HSPs are abundantly expressed in cancer cells and high expression of HSPs, mainly HSP27 and HSP70, has been associated with metastasis and poor prognosis in breast, endometrial and/or gastric cancer (Jaattela 1999; Fuller et al., 1994; Conroy and Latchman 1996). The molecular basis for overexpression of HSPs in tumors is not completely understood and may have different etiologies. For example, it may be due to suboptimal cellular environment in poorly vascularized hypoxic tumors or due to the growth conditions within the solid tumor (Garrido et al., 1997). The contribution of HSPs to tumorigenesis may furthermore be attributed to their pleiotropic activities as
molecular chaperones that provide the cancer cell with an opportunity to alter protein
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known histopathologic prognostic factors (Missotten et al., 2003). In our present study, we have identified an increased expression of phosphorylated HSP27 in the metastatic cell lines in comparison with the primary melanoma cells. HSP27 phosphorylation causes a shift from homotypic multimers down to dimers and monomers (Rogalla et al., 1999; Ito et al., 2001) which reduces the activity of HSP27 as a molecular chaperone (Garrido 2002). Instead, however, HSP27 dimers and monomers contribute to the stabilization of intracellular actin filaments and could play a regulatory role for the organization of the cytoskeleton (Benndorf et al., 1994; Lavoie et al., 1995). Thus, it seems that metastasing uveal melanoma cells preferentially modulate its filament organization instead of cellular resistance against stress. This may come from the necessity of metastasing cells to have a well-developed invading apparatus for migration.
A well-known source of free radicals in relation to cutaneous melanoma development is exposure to ultra violet (UV)-light (Gilchrest et al., 1999). GST is an enzyme that catalyzes the conjugation of electrophilic substrates and prevents oxidative damage. Concerning oxidative stress caused by UV radiation, the role of GST is less obvious in uveal melanoma. We observed a reduced expression of GST in the metastases cell lines. Therefore, more reactive-oxygen species, in part due to a decreased GST activity, can contribute to
oncogenicity in metastatic cells. This can potentially give rise to increased genetic instability due to persistent oxidative stress and alter the malignant potential of the tumor (Szatrowski and Nathan 1991).
Apoptosis
In the functional subgroup of apoptosis and/or degradation, a differential expression pattern of the ∼13 kDa protein as (part of) the protein acid ceramidase was found in our tumor
progression model. The mature form of acid ceramidase is a heterodimer consisting of the mentioned ∼13 kDa (α) and ∼40 kDa (β) subunits (Bernardo et al., 1995). The
40-kDa-subunit is also expected to be present on the 2D PAGE-gel, but its differential expression may not be as evident as that from the 13-kDa-subunit. Their different location on the gel (variable background) or their diverse biochemical properties are possible reasons for this. Moreover, the ~40 kDa fragment is known to be glycosylated.
In a recent study, the acid ceramidase gene was found to be one of the most important candidate tumor markers for melanoma (Musumarra et al., 2003). Acid ceramidase catalyzes the hydrolysis of ceramide, an effector molecule involved in cell death, into fatty acid and sphingosine (Rother et al., 1992). The latter byproduct of ceramide metabolism can be converted into sphingosine-1-phosphate, an inhibitor of ceramide-induced apoptosis (Cuvillier et al., 1996). Thus acid ceramidase, which functions as a switch between pro-apoptotic (ceramide) and anti-pro-apoptotic (sphingosine-1-phosphate) state, can be an important control mechanism of cellular proliferation. Interestingly, Kanto et al. demonstrated that several tumor supernatants, one of which was derived from a melanoma cell line, contained increased ceramide levels and induced apoptosis in bone marrow-derived dendritic cells (DC) (Kanto et al., 2001). This implies the possibility that ceramide plays an essential role in
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tumors (Banchereau and Steinman 1998). Therefore, in the future we will focus on secreted bioactive molecules. These studies would also open the possibility to look for TIMP3 expression as found differentially expressed in uveal melanoma by Van der Velden and co-workers (Van der Velden et al., 2003).
Migration
Our results show that galectin-1 and beta-hexosaminidase beta-subunit, both involved in cellular interaction with adhesion proteins, are upregulated in the metastases cell lines. Galectin-1 has been implicated as a key factor in the process of malignant transformation and metastasis. Several studies showed significantly higher levels of galectin-1 in different tumors such as, cutaneous melanoma, breast carcinoma and head/neck squamous cell carcinoma (Raz and Lotan 1981; Raz and Lotan 1987; Lotan 1989; Gillenwater et al., 1996). Overexpression of galectin-1 in a variety of gastrointestinal tumors in comparison to the normal mucosa is associated with advanced tumor stages and metastasis (Gillenwater et al., 1996; Schoeppner et al., 1995; Sanjuan et al., 1997; Andre et al., 1999; Berberat et al., 2001). Furthermore,
galectin-1 is involved in tumor-cell adhesion (Lotan and Raz 1988; Allen et al., 1990), in blood-borne metastasis formation 43 and contributes to immune privilege of cutaneous melanoma (Fuertes et al., 2004).
Overproduction of beta-hexosaminidase has been shown to contribute to the process of metastasis (Plucinsky et al., 1986).
The metastases cell lines contained increased amounts of phosphorylated inactive cofilin, a protein which plays an important role in cell migration. This observation is consistent with Pavey et al (submitted), describing overexpression of PAK1, a cofilin inactivating enzyme, leading to stimulation of cell spreading activities (Ohashi et al., 2000), in uveal melanoma. Promotion of cell motility and stabilization of cell shape may have become enhanced during acquisition of the metastatic phenotype by phosphorylation of cofilin and could therefore be of great importance for the metastatic potential of uveal melanoma cells. Furthermore, a recent proteomic 2D-PAGE study (Keezer et al., 2003) provided data that phosphorylation of cofilin together with HSP27 are altered in response to angiogenesis inhibitors, affecting the endothelial cell cytoskeleton to prevent endothelial migration.
Metabolism
In neoplastic cells, the capacity for glucose transport is high, requiring high levels of glycolysis. Pyruvate kinase 3 (PK3) and enolase-1 are critical enzymes in glycolysis regulation. The activity of PK3 is considerably higher in tumorigenic cells than in
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Although an increased expression of TUM2-PK and NSE is expected, we observed a
decreased expression of PK3 and enolase in the metastatic uveal melanoma cell lines, which maybe related to their faster growth rate as stated in a previous study by Royds et al. (1983).
In conclusion, our data provide the first indication that proteomic analysis using 2D-PAGE can identify proteins involved in metastasis of uveal melanoma. A few proteins have been described before in the literature as potential tumor markers, but for most proteins of the list, a specific role in uveal melanoma development has not previously been described. Proteomic analysis, as in this study, can thus provide a more profound insight in the multifactorial mechanisms of uveal melanoma progression. The identification of specific proteins involved in uveal melanoma development may help us to identify serological markers, leading to earlier identification of liver metastases and thus help us to improve survival in uveal melanoma patients with metastatic disease.
A
CKNOWLEDGEMENTSThe authors would like to thank Roel van der Schors for technical assistance and Pieter van der Velden for his helpful discussions. W. Zuidervaart is supported by “Landelijke Stichting voor Blinden en Slechtzienden” and “Rotterdamse Vereniging Blindenbelangen”. N.A. Gruis is a recipient of an Aspasia fellowship of the Netherlands Organization for Scientific
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