March 2006
Volume 47, Issue 3
Free
Anatomy and Pathology/Oncology  |   March 2006
Proteomic Analysis of Uveal Melanoma Reveals Novel Potential Markers Involved in Tumor Progression
Author Affiliations
  • Wieke Zuidervaart
    From the Department of Ophthalmology, the
  • Paul J. Hensbergen
    Biomolecular Mass Spectrometry Unit, Department of Parasitology, and the
  • Man-Chi Wong
    From the Department of Ophthalmology, the
  • Andre M. Deelder
    Biomolecular Mass Spectrometry Unit, Department of Parasitology, and the
  • Cornelis P. Tensen
    Department of Dermatology, Leiden University Medical Center, Leiden, The Netherlands.
  • Martine J. Jager
    From the Department of Ophthalmology, the
  • Nelleke A. Gruis
    Department of Dermatology, Leiden University Medical Center, Leiden, The Netherlands.
Investigative Ophthalmology & Visual Science March 2006, Vol.47, 786-793. doi:10.1167/iovs.05-0314
  • Views
  • PDF
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to Subscribers Only
      Sign In or Create an Account ×
    • Get Citation

      Wieke Zuidervaart, Paul J. Hensbergen, Man-Chi Wong, Andre M. Deelder, Cornelis P. Tensen, Martine J. Jager, Nelleke A. Gruis; Proteomic Analysis of Uveal Melanoma Reveals Novel Potential Markers Involved in Tumor Progression. Invest. Ophthalmol. Vis. Sci. 2006;47(3):786-793. doi: 10.1167/iovs.05-0314.

      Download citation file:


      © 2015 Association for Research in Vision and Ophthalmology.

      ×
  • Supplements

purpose. 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. The proteins that are expressed in two cell lines originating from two liver metastases were compared with the proteins expressed in a cell line obtained from the primary uveal melanoma of the same patient, to identify proteins that play a role in tumor progression as well as proteins that are expressed specifically in metastases.

methods. Protein analysis was performed by using two-dimensional gel electrophoresis. A subset of proteins was subsequently identified with mass spectrometry.

results. A set of 24 proteins was differentially expressed in both of the two metastatic cell lines compared with the cell line derived from the primary tumor. These proteins were subdivided into groups according to cellular function, with important roles in tumor development.

conclusions. Tumor progression and development of metastases is a multicomplex system. Comparing protein expression in two cell lines derived from metastases with a cell line derived from a primary uveal melanoma from the same patient identified proteins involved in tumor progression, and proteins specifically expressed in the metastases, which have the potential of becoming clinically useful biomarkers.

The most prevalent primary intraocular malignancy in adults is the melanoma originating from the uveal tract, affecting approximately 7 per 1 million people in the Western world each year. 1 The 5-year survival in uveal melanoma is 72%, but in a 15-year follow-up, 53% of patients have been shown to die of metastatic disease. 2 3 Approximately 95% of patients with metastatic uveal melanoma have 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, 4 resulting in a poor median patient survival: 2 5 to 7 6 months after clinical diagnosis of the lesions. 
Understanding the molecular changes in gene and protein expression that are responsible for the development and progression of uveal melanoma would be an important step toward the identification of biomarkers that are indicative of metastatic melanoma. High-throughput technologies in genomics 7 8 and proteomics 9 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 10 11 12 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 humor from eyes containing a uveal melanoma with eyes undergoing cataract surgery, could separate patients and control subjects on the basis of two proteins. 13  
To identify proteins that are associated with uveal melanoma metastases, 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 gel electrophoresis (2-D-PAGE) and mass spectrometry (MS). We hypothesized that downregulation of proteins with growth-inhibitory capacity would be seen during progression from primary tumor to metastasis, whereas similarly, growth-stimulating proteins would show upregulation in the metastasis-derived cell lines. Markers that are specifically upregulated in metastases may be potential markers of metastases at a stage at which such metastases are not yet clinically recognizable by, for example, echography. Because the two metastatic cell lines were obtained from two different metastases in the same patient, they served as an internal control. Twenty-four differentially expressed proteins were identified, of which most play a role in tumor-promoting cellular mechanisms. 
Materials and Methods
Cell Culture
Three cell lines were included in the study. One was derived from a primary uveal melanoma (Mel 270) and two (Omm 1.3 and -1.5) were derived from liver metastases from this same primary tumor. All cell lines were kindly provided by Bruce R. Ksander (Schepens Eye Institute, Boston, MA). The research complied with the tenets of the Declaration of Helsinki. 
The melanoma cell lines were cultured in RPMI 1640 medium (Invitrogen-Gibco, Breda, The Netherlands), supplemented with 3 mM l-glutamine (Invitrogen-Gibco), 2% penicillin/streptomycin, and 10% FBS (Hyclone, Logan, UT). The cell cultures were incubated at 37°C in a humidified 5% CO2 atmosphere. Cells were harvested at 80% confluence and protein extraction (TRIzol; Invitrogen-Gibco) was performed as described by the supplier. Protein concentrations were determined with the modified Bradford protein assay. 14  
2-D-Polyacrylamide Gel Electrophoresis
From each cell line, 500 μg of protein was loaded on 24-cm isoelectric-focusing ready-made immobilized pH gradient (IPG) strips with a nonlinear gradient of pH 3 to 10 or with a linear gradient of pH 4 to 7 (GE Healthcare, Roosendaal, The Netherlands). Rehydration of the IPG strips was performed for 22 hours at 30 V, after which proteins were focused for 65,000 V/h (IPGphor; GE Healthcare). 
Before the second dimension, IPG strips were equilibrated in 1% dithiothreitol (wt/vol) followed by 2.5% iodoacetamide (wt/vol), both for 15 minutes in 50 mM Tris-HCl (pH 8.8), 6 M urea, 30% glycerol, and 2% SDS. After this procedure, the strips were placed on top of a 200 × 250 × 1.0-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 run at 5 W/gel for 1 hour and subsequently 15 W/gel until the bromophenol blue dye front reached the bottom of the gels (ETTAN Dalt II; GE Healthcare). 
Proteins were visualized with either silver or Coomassie G250 staining and scanned (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 on computer (PDQuest software 7.0; Bio-Rad Laboratories) and relative spot intensities were quantified after normalization. 
Mass Spectrometry
Protein spots of interest were excised from the gel and digested with trypsin, as described previously. 15 Subsequently, samples were desalted (ZipTip; Millipore, Billerica, MA), as described by the supplier. Peptides were directly eluted with matrix solution (0.33 mg α-cyano-4-hydroxy cinnamic acid in acetone-ethanol: 1:2), loaded on the MALDI plate and measured on a matrix-assisted desorption ionization time-of-flight (MALDI-ToF-ToF) system (Ultraflex-ToF; Bruker Daltonics, Bremen, Germany). Mass fingerprints and tandem mass spectra (MS/MS) from selected peptides were searched against the human MSDB database (using Mascot; Matrix Science Ltd., London, UK) 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 legitimate identifications, but these were always verified manually. 
Purification of Phosphopeptides by Immobilized Metal Affinity Chromatography
To separate phosphorylated from nonphosphorylated peptides, tryptic digests of spots of interest were acidified to pH 3 with acetic acid and subsequently applied to a gallium III affinity column (Pierce Biotechnology, Rockford, IL). 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 (Poros 50R2; Applied Biosystems, Forster City, CA). Peptides were eluted with 25% methanol/5% formic acid and measured by electrospray ionization time-of-flight MS (Micromass Q-ToF; Waters, Milford, MA). 
Results
Differential 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 and metastatic growth. Proteins specifically expressed in metastases may be candidates for biomarkers for the early identification of, for example, liver metastases. 
Proteomic profiles were analyzed of a matched set of one primary uveal melanoma cell line (Mel-270) and two of its metastatic cell lines (OMM-1.3 and -1.5) using 2-D-PAGE and MS. In each cell line, four independent 2-D-PAGE runs were performed: two silver-stained with a pH range of 3 to 10, one silver-stained with a pH range of 4 to 7 in the first dimension for a higher resolution in this pH range, and one Coomassie-stained with a pH range of 3 to 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 (OMM-1.3 and -1.5) in the pH range of 3 to 10 (stained with Coomassie) are shown in Figure 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 example, the upregulation of spot number 15 (Table 1)in the metastatic cell lines compared with the primary tumor cell line is shown (Fig. 2A). Using a combination of MS mass fingerprint (Fig. 2B)and MS/MS (Fig. 2C)analysis, this protein spot was unambiguously identified as galectin-1. 
This same procedure was performed for the other differentially expressed protein spots, and 26 spots were successfully identified, representing 24 different proteins (Table 1)
Although the two metastatic 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-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 (HSP)-27, αB-crystallin, cathepsin Z, Ran-binding protein 1, eukaryotic translation initiation factor 5A (eIF5A), and β-hexosaminidase β-subunit. 
Discrepancies between Spot Location on Gel and Theoretical Values for Molecular Weight and Isoelectric Point
After mass spectrometric characterization, there were some proteins that showed a discrepancy in experimental molecular weight and/or isoelectric point (deduced from the location on the gel) and the theoretical values (as determined at ProSite, http://www.expasy.org/tools/pi_tool.html/ provided in the public domain by the Swiss Institute of Bioinformatics, Geneva, Switzerland). 
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 preproprotein 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). 16 Both originate from the same preprotein after 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. 17  
Another discrepancy was found for HSP27 (Fig. 3A). The expected theoretical isoelectric point of HSP27 was more basic (7.8) than the actual pH of the excised spot according to the location on the gel (<7). Because HSP27 can be phosphorylated, 18 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+). 19 Therefore, a tryptic digest of the differentially expressed HSP27 spot was purified by immobilized gallium (III) affinity chromatography (Ga(III)-IMAC) and subsequently analyzed by electrospray ionization (ESI)-MS. The mass chromatogram of the Ga(III)-IMAC affinity-purified digest contained one salient peptide with m/z 578.3 [M+2H]2+ (Fig. 3B) . This m/z was selected for fragmentation using collision-induced dissociation, leading to the MS/MS spectrum shown in Figure 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. 20  
Because similar discrepancies in isoelectric 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 differentially expressed cofilin to be phosphorylated at serine 2. Phosphorylation of enolase-1, however, was not found. 
Discussion
At present, 2-D-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 several protein alterations in tumor cells. 21 22 23 The detection of primarily high-abundance proteins is a limitation of 2-D-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 two cell lines derived from two metastases was compared to the protein profile of a cell line from the primary tumor of the same patient, to get an impression of the changes in the proteomic profile during metastatic tumor progression of uveal melanoma. From these data, we can derive insight into the biological role of some proteins in the development of metastases, and we can try to identify potential biomarkers, that can be used to screen patients for the early development of metastases. 
The use of three cell lines from the same donor allowed exclusion of interindividual differences that do not contribute to tumor progression. 
Twenty-six of the 29 excised protein spots, consistently identified in four independent 2-D-PAGE runs, were characterized by MS and database inquiry (Table 1) . The nature of the other differentially expressed proteins remains unknown, most likely because of an insufficient amount of material. Three separate spots were all identified as glutathione S-transferase, probably because of different modifications of the same protein. In total, we identified 24 different proteins differentially expressed between the primary tumor and the two metastases (Table 1)
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
HSP27 clearly revealed an increased expression in the cell lines derived from metastases. Oxidative stress damages cells, and this damage is causally implicated in the pathogenesis of cancer. 24 HSPs and glutathione S-transferase (GST) are important proteins in cellular defense against various stimuli and stress. HSPs may also have tumor-promoting functions: They 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. 25 26 27 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 a suboptimal cellular environment in poorly vascularized hypoxic tumors or to the growth conditions within the solid tumor. 28 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 activities. Although HSP27 has been found to be overexpressed in uveal melanoma, a recent study showed no correlation between expression of total HSP27 in uveal melanoma and known histopathologic prognostic factors. 29 In our present study, we 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, 30 31 which reduces the activity of HSP27 as a molecular chaperone. 32 Instead, however, HSP27 dimers and monomers contribute to the stabilization of intracellular actin filaments and could play a regulatory role in the organization of the cytoskeleton. 33 34 Thus, it seems that metastasizing uveal melanoma cells preferentially modulate its filament organization instead of cellular resistance against stress. This may come from the necessity for metastasizing cells to have a well-developed invading apparatus for migration. 
A well-known source of free radicals in relation to the development of cutaneous melanoma is exposure to ultraviolet (UV) light. 35 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 metastatic cell lines. Therefore, more reactive oxygen species, in part due to a decreased GST activity, contribute to oncogenicity in metastatic cells, potentially give rise to increased genetic instability due to persistent oxidative stress, and alter the malignant potential of the tumor. 36  
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. 16 The 40-kDa subunit is also expected to be present on the 2-D PAGE gel, but its differential expression may not be as evident as that from the 13-kDa subunit. Their different locations 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. 37 Acid ceramidase was present in the primary uveal melanoma cell line, but no longer in the cell lines derived from the metastases. Acid ceramidase catalyzes the hydrolysis of ceramide, an effector molecule involved in cell death, into fatty acid and sphingosine. 38 The latter byproduct of ceramide metabolism can be converted into sphingosine-1-phosphate, an inhibitor of ceramide-induced apoptosis. 39 Thus, acid ceramidase, which functions as a switch between the proapoptotic (ceramide) and antiapoptotic (sphingosine-1-phosphate) states, can be an important control mechanism of cellular proliferation. Of note, Kanto et al. 40 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 (DCs). This implies the possibility that ceramide plays an essential role in tumor-induced DC apoptosis, inhibiting the specific T-cell-mediated immune response against tumors. 41 Therefore, in the future we will focus on secreted bioactive molecules. These studies would also open the possibility of looking for TIMP3 expression as found differentially expressed in uveal melanoma by van der Velden et al. 42  
Migration
galectin-1 and β-hexosaminidase β-subunit, both involved in cellular interaction with adhesion proteins, were upregulated in the metastatic cell lines. Galectin-1 has been implicated as a key factor in the process of malignant transformation and metastasis. Several studies have shown significantly higher levels of galectin-1 in different tumors, such as cutaneous melanoma, breast carcinoma, and head/neck squamous cell carcinoma. 43 44 45 46 Overexpression of galectin-1 in a variety of gastrointestinal tumors, in comparison with the normal mucosa, is associated with advanced tumor stages and metastasis. 46 47 48 49 50 Furthermore, galectin-1 is involved in tumor-cell adhesion 51 52 and blood-borne metastasis formation 43 and contributes to the immune privilege of cutaneous melanoma. 53 Overproduction of β-hexosaminidase has been shown to contribute to the process of metastasis. 54 Both proteins are candidates that should be evaluated for use as biomarkers of metastasis formation. 
The metastatic cell lines contained increased amounts of phosphorylated inactive cofilin, a protein that plays an important role in cell migration. This observation is consistent with Pavey et al. (manuscript submitted), describing an overexpression of PAK1, a cofilin-inactivating enzyme that leads to stimulation of cell spreading activities 55 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 2-D-PAGE study 56 provided data that phosphorylation of cofilin, together with HSP27, is 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. 57 Pyruvate kinase 3 (PK3) and enolase-1 are critical enzymes in glycolysis regulation. In general, the activity of PK3 is considerably higher in tumorigenic cells than in nontumorigenic cells and is higher in metastatic cells than in tumorigenic cells. 57 Of note, specific forms of PK3, tumor type M2 pyruvate kinase (TuM2-PK), and enolase-1, NSE, are found to be useful predictors of metastasis in different forms of cancer, including cutaneous melanoma. 58 59 60 61 62  
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. 63  
In conclusion, our data provide the first indication that proteomic analysis using 2-D-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 on the list, a specific role in uveal melanoma development has not been described previously. Proteomic analysis, as in this study, can thus provide a more profound insight in the multifactorial mechanisms of the progression of uveal melanoma. The identification of proteins specifically expressed in uveal melanoma metastases may help us to identify biomarkers, leading to earlier identification of liver metastases and thus help us to improve survival in uveal melanoma patients with metastatic disease. 
Figure 1.
 
Visualization of proteomic patterns in (A) Mel-270, (B) OMM-1.3, and (C) OMM-1.5 uveal melanoma cells. Solubilized proteins from these cell lines were resolved by 2-D-PAGE with carrier ampholytes (pH 3–10; nonlinear gradient) 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 computer.
Figure 1.
 
Visualization of proteomic patterns in (A) Mel-270, (B) OMM-1.3, and (C) OMM-1.5 uveal melanoma cells. Solubilized proteins from these cell lines were resolved by 2-D-PAGE with carrier ampholytes (pH 3–10; nonlinear gradient) 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 computer.
Table 1.
 
Mass Spectrometric Identification of Differentially Expressed Proteins in Primary (Mel-270) and Metastatic (OMM-1.3, -1.5) Uveal Melanoma Cell Lines
Table 1.
 
Mass Spectrometric Identification of Differentially Expressed Proteins in Primary (Mel-270) and Metastatic (OMM-1.3, -1.5) Uveal Melanoma Cell Lines
Protein Number Protein Name Accession Number Main Function MALDI-ToF MALDI-ToF-ToF Changes (x-fold)
Peptides* (n) Coverage (%), † Peptide Sequence (MS/MS) 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 αB-crystallin AAP35416 Protein conformation stabilization 11 53 ND ++ ++
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 and LPGLLGNFPGPFEEEMK −− −−
 8 Platelet-activating factor acetylhydrolas e,β-subunit P68402 Degradation of platelet-activating factor 5 34 ELFSPLHALNFGIGGDTTR and 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 ++++++ +++++
 13 Actin P60709 Cytoskeletal component 10 41 SYELPDGQVITIGNER −−−−−− −−−−−−
 14 Tropomodulin 3 Q9NYL9 Actin turnover 18 50 FGYQFTQQGPR ++++++ ++++++
 15 Galectin 1 P09382 Cell–cell extracellular interaction 10 81 VRGEVAPDAK ++ ++
 16 β-Hexosaminidaseβ-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 elF5A XP_016093 Cofactor in nuclear export 3 28 NDFQLIGIQDGYLSLLQDS GEVR and EDLRLPEGDLGK ++++++ ++++++
Translation
 22 Ribosomal protein P0 NP_444505 Part of ribosome 9 43 GTIEILSDVQLIK and IIQLLDDYPK −− −−
 23 Ribosomal protein L12 NP_000967 Part of ribosome 7 55 HSGNITFDEIVNIAR −−− −−−−−−
 24 CRHSP-24 Q9Y2V2 Translation regulating protein 5 43 LQAVEVVITHLAPGTK ++++++ +++++
Figure 2.
 
Differential expression and identification of galectin 1 (A) Cropped images from Coomassie-stained, two-dimensional gels of Mel-270, OMM-1.3, and OMM-1.5 demonstrating differential expression of spot 15 (Table 1) . (B) MALDI fingerprint mass spectrum from the tryptic digest of spot 15 (Table 1) . This fingerprint was identified as that from galectin-1 with a score of 70. *Tryptic fragments of galectin-1. Other fragments corresponded 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.
Figure 2.
 
Differential expression and identification of galectin 1 (A) Cropped images from Coomassie-stained, two-dimensional gels of Mel-270, OMM-1.3, and OMM-1.5 demonstrating differential expression of spot 15 (Table 1) . (B) MALDI fingerprint mass spectrum from the tryptic digest of spot 15 (Table 1) . This fingerprint was identified as that from galectin-1 with a score of 70. *Tryptic fragments of galectin-1. Other fragments corresponded 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.
Figure 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 gallium III affinity chromatography (Ga-IMAC). (C) MS/MS spectrum of m/z 578.3 [M+2H]2+ corresponding to a phosphorylated peptide from HSP27. Phosphorylation was 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.
Figure 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 gallium III affinity chromatography (Ga-IMAC). (C) MS/MS spectrum of m/z 578.3 [M+2H]2+ corresponding to a phosphorylated peptide from HSP27. Phosphorylation was 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.
 
The authors thank Roel van der Schors for technical assistance and Pieter van der Velden for helpful discussions. 
EganKM, SeddonJM, GlynnRJ, GragoudasES, AlbertDM. Epidemiologic aspects of uveal melanoma. Surv Ophthalmol. 1988;32:239–251. [CrossRef] [PubMed]
GamelJW, McLeanIW, McCurdyJB. Biologic distinctions between cure and time to death in 2892 patients with intraocular melanoma. Cancer. 1993;71:2299–2305. [CrossRef] [PubMed]
McLeanIW, GamelJW. Cause-specific versus all-cause survival. Ophthalmology. 1998;105:1989–1990. [CrossRef] [PubMed]
MooyCM, De JongPT. Prognostic parameters in uveal melanoma: a review. Surv Ophthalmol. 1996;41:215–228. [CrossRef] [PubMed]
SeddonJM, AlbertDM, LavinPT, RobinsonN. A prognostic factor study of disease-free interval and survival following enucleation for uveal melanoma. Arch Ophthalmol. 1983;101:1894–1899. [CrossRef] [PubMed]
KathR, HayungsJ, BornfeldN, SauerweinW, HoffkenK, SeeberS. Prognosis and treatment of disseminated uveal melanoma. Cancer. 1993;72:2219–2223. [CrossRef] [PubMed]
DeRisiJ, PenlandL, BrownPO, et al. Use of a cDNA microarray to analyse gene expression patterns in human cancer. Nat Genet. 1996;14:457–460. [CrossRef] [PubMed]
AlizadehAA, RossDT, PerouCM, van de RijnM. Towards a novel classification of human malignancies based on gene expression patterns. J Pathol. 2001;195:41–52. [CrossRef] [PubMed]
WilkinsMR, SanchezJC, GooleyAA, et al. Progress with proteome projects: why all proteins expressed by a genome should be identified and how to do it. Biotechnol Genet Eng Rev. 1996;13:19–50. [CrossRef] [PubMed]
ZuidervaartW, van der VeldenPA, HurksMH, et al. Gene expression profiling identifies tumour markers potentially playing a role in uveal melanoma development. Br J Cancer. 2003;89:1914–1919. [CrossRef] [PubMed]
TschentscherF, HusingJ, HolterT, et al. Tumor classification based on gene expression profiling shows that uveal melanomas with and without monosomy 3 represent two distinct entities. Cancer Res. 2003;63:2578–2584. [PubMed]
OnkenMD, WorleyLA, EhlersJP, HarbourJW. Gene expression profiling in uveal melanoma reveals two molecular classes and predicts metastatic death. Cancer Res. 2004;64:7205–7209. [CrossRef] [PubMed]
MissottenGS, BeijnenJH, KeunenJE, BonfrerJM. Proteomics in uveal melanoma. Melanoma Res. 2003;13:627–629. [CrossRef] [PubMed]
RamagliLS. Quantifying protein in 2D PAGE solubilization buffers. Methods Mol Biol. 1999;112:99–103. [PubMed]
HensbergenP, AlewijnseA, KempenaarJ, et al. Proteomic profiling identifies an UV-induced activation of cofilin-1 and destrin in human epidermis. J Invest Dermatol. 2005;124:818–824. [CrossRef] [PubMed]
BernardoK, HurwitzR, ZenkT, et al. Purification, characterization, and biosynthesis of human acid ceramidase. J Biol Chem. 1995;270:11098–11102. [CrossRef] [PubMed]
KochJ, GartnerS, LiCM, et al. Molecular cloning and characterization of a full-length complementary DNA encoding human acid ceramidase: identification of the first molecular lesion causing Farber disease. J Biol Chem. 1996;271:33110–33115. [CrossRef] [PubMed]
CarlierMF, LaurentV, SantoliniJ, et al. Actin depolymerizing factor (ADF/cofilin) enhances the rate of filament turnover: implication in actin-based motility. J Cell Biol. 1997;136:1307–1322. [CrossRef] [PubMed]
PosewitzMC, TempstP. Immobilized gallium(III) affinity chromatography of phosphopeptides. Anal Chem. 1999;71:2883–2892. [CrossRef] [PubMed]
LandryJ, LambertH, ZhouM, et al. Human HSP27 is phosphorylated at serines 78 and 82 by heat shock and mitogen-activated kinases that recognize the same amino acid motif as S6 kinase II. J Biol Chem. 1992;267:794–803. [PubMed]
CelisJE, OstergaardM, JensenNA, GromovaI, RasmussenHH, GromovP. Human and mouse proteomic databases: novel resources in the protein universe. FEBS Lett. 1998;430:64–72. [CrossRef] [PubMed]
BanksRE, DunnMJ, ForbesMA, et al. The potential use of laser capture microdissection to selectively obtain distinct populations of cells for proteomic analysis: preliminary findings. Electrophoresis. 1999;20:689–700. [CrossRef] [PubMed]
Emmert-BuckMR, GillespieJW, PaweletzCP, et al. An approach to proteomic analysis of human tumors. Mol Carcinog. 2000;27:158–165. [CrossRef] [PubMed]
AmesBN, ShigenagaMK, HagenTM. Oxidants, antioxidants, and the degenerative diseases of aging. Proc Natl Acad Sci USA. 1993;90:7915–7922. [CrossRef] [PubMed]
JaattelaM. Escaping cell death: survival proteins in cancer. Exp Cell Res. 1999;248:30–43. [CrossRef] [PubMed]
FullerKJ, IsselsRD, SlosmanDO. Cancer and the heat shock response. Eur J Cancer. 1994;30A:1884–1891. [PubMed]
ConroySE, LatchmanDS. Do heat shock proteins have a role in breast cancer?. Br J Cancer. 1996;74:717–721. [CrossRef] [PubMed]
GarridoC., OttaviP, FromentinA. HSP27 as a mediator of confluence-dependent resistance to cell death induced by anticancer drugs. Cancer Res. 1997;57:2661–2667. [PubMed]
MissottenGS, Journee-de KorverJGJ, de Wolff-RouendaalD. Heat shock protein expression in the eye and in uveal melanoma. Invest Ophthalmol Vis Sci. 2003;44:3059–3065. [CrossRef] [PubMed]
RogallaT, EhrnspergerM, PrevilleX. Regulation of Hsp27 oligomerization, chaperone function, and protective activity against oxidative stress/tumor necrosis factor alpha by phosphorylation. J Biol Chem. 1999;274:18947–18956. [CrossRef] [PubMed]
ItoH, KameiK, IwamotoI. Phosphorylation-induced change of the oligomerization state of αB-crystallin. J Biochem. 2001;276:5346–5352.
GarridoC. Size matters: of the small HSP27 and its large oligomers. Cell Death Differ. 2002;9:483–485. [CrossRef] [PubMed]
BenndorfR, HayessK, RyazantsevS. Phosphorylation and supramolecular organization of murine small heat shock protein HSP25 abolish its actin polymerization-inhibiting activity. J Biol Chem. 1994;269:20780–20784. [PubMed]
LavoieJN, LambertH, HickeyE. Modulation of cellular thermoresistance and actin filament stability accompanies phosphorylation-induced changes in the oligomeric structure of heat shock protein 27. Mol Cell Biol. 1995;15:505–516. [PubMed]
GilchrestBA, EllerMS, GellerAC. Mechanisms of disease: the pathogenesis of melanoma induced by ultraviolet radiation. N Engl J Med. 1999;340:1341–1348. [CrossRef] [PubMed]
SzatrowskiTP, NathanCF. Production of large amounts of hydrogen peroxide by human tumor cells. Cancer Res. 1991;51:794–798. [PubMed]
MusumarraG, BarresiV, CondorelliDF. A bioinformatic approach to the identification of candidate genes for the development of new cancer diagnostics. Biol Chem. 2003;384:321–327. [PubMed]
RotherJ, Van EchtenG, SchwarzmannG. Biosynthesis of sphingolipids: dihydroceramide and not sphinganine is desaturated by cultured cells. Biophys Biochem Res Commun. 1992;189:14–20. [CrossRef]
CuvillierO, PirianovG, KleuserPG. Suppression of ceramide-mediated programmed cell death by sphingosine-1-phosphate. Nature. 1996;381:800–803. [CrossRef] [PubMed]
KantoT, KalinskiP, HunterOC. Ceramide mediates tumor-induced dendritic cell apoptosis. J Immunol. 2001;167:3773–3784. [CrossRef] [PubMed]
BanchereauJ, SteinmanRM. Dendritic cells and the control of immunity. Nature. 1998;392:245–252. [CrossRef] [PubMed]
van der VeldenPA, ZuidervaartW, HurksMH, et al. Expression profiling reveals that methylation of TIMP3 is involved in uveal melanoma development. Int J Cancer. 2003;106:472–479. [CrossRef] [PubMed]
RazA, LotanR. Lecin-like activities associated with human and murine neoplastic cells. Cancer Res. 1981;41:3642–3647. [PubMed]
RazA, LotanR. Endogenous galactoside-binding lectins: a new class of functional tumor cell surface molecules related to metastasis. Cancer Metastasis Rev. 1987;6:433–452. [CrossRef] [PubMed]
LotanR. Modulation of galactoside-binding lectins in tumor cells by differentiation-inducing agents. Cancer Letters. 1989;48:115–122. [CrossRef] [PubMed]
GillenwaterA, XuXC, el-NaggarAK. Expression of galectins in head and neck squamous cell carcinoma. Head Neck. 1996;18:422–432. [CrossRef] [PubMed]
SchoeppnerHL, RazA, HoSB. Expression of an endogenous galactose-binding lectin correlates with neoplastic progression in the colon. Cancer. 1995;75:2818–2826. [CrossRef] [PubMed]
SanjuanX, FernandezPL, CastellsA. Differential expression of galectin 3 and galectin 1 in colorectal cancer progression. Gasteroenterology. 1997;113:1906–1915. [CrossRef]
AndreS, KojimaS, YamazakiN. Galectins-1 and -3 and their ligand in tumor biology: non-uniform properties in cell-surface presentation and modulation of adhesion to matrix glycoproteins for various tumor cell lines, in biodistribution of free and liposome-bound galectins and in their expression by breast and colorectal carcinomas with/without metastatic propensity. J Cancer Res Clin Oncol. 1999;125:461–474. [CrossRef] [PubMed]
BerberatPO, FriessH, WangL. Comparative analysis of galectins in primary tumors and tumor metastasis in human pancreatic cancer. J Histochem Cytochem. 2001;49:539–549. [CrossRef] [PubMed]
LotanR, RazA. Endogenous lectins as mediators of tumor cell adhesion. J Cell Biochem. 1988;37:107–117. [CrossRef] [PubMed]
AllenHJ, SucatoD, WoynarowskaB. Role of galaptin in ovarian carcinoma adhesion to extracellular matrix in vitro. J Cell Biochem. 1990;43:43–57. [CrossRef] [PubMed]
FuertesMB, MolineroLL, ToscanoMA, et al. Regulated expression of galectin-1 during T-cell activation involves Lck and Fyn kinases and signaling through MEK1/ERK, p38 MAP kinase and p70S6 kinase. Mol Cell Biochem. 2004;267:177–185. [CrossRef] [PubMed]
PlucinskyMC, ProrokJJ, AlhadeffJA. Variant serum beta-hexosaminidase as a biochemical marker of malignancy. Cancer. 1986;58:1484–1487. [CrossRef] [PubMed]
OhashiK, NagatK, MaekawaM. Rho associated kinase ROCK activates LIM-kinase 1 by phosphorylation at threonine 508 within the activation loop. J Biol Chem. 2000;275:3577–3582. [CrossRef] [PubMed]
KeezerSM, IvieSE, KrutzschHC, TandleA, LibuttiSK, RobertsDD. Angiogenesis inhibitors target the endothelial cell cytoskeleton through altered regulation of heat shock protein 27 and cofilin. Cancer Res. 2003;63:6405–6412. [PubMed]
BoardM, HummS, NewsholmeEA. Maximum activities of key enzymes of glycolysis, glutaminolysis, pentose phosphate pathway and tricarboxylic acid cycle in normal, neoplastic and suppressed cells. Biochem J. 1990;265:503–509. [PubMed]
RodeJ, DhillonAP. Neurone specific enolase and S100 protein as possible prognostic indicators of melanoma. Histopathology. 1984;8:1041–1052. [PubMed]
CerwenkaH, AignerR, BacherH. TUM2-PK (pyruvate kinase type tumor M2), CA19–9 and CEA in patients with benign, malignant and metastasizing pancreatic lesions. Anticancer Res. 1999;19:849–851. [PubMed]
LuftnerD, MesterharmJ, AkrivakisC. Tumor type M2 pyruvate kinase expression in advanced breast cancer. Anticancer Res. 2000;20:5077–5082. [PubMed]
RoigasJ, SchulzeG, RaytarowskiS. Tumor M2 pyruvate kinase in plasma of patients with urological tumors. Tumour Biol. 2001;22:282–285. [CrossRef] [PubMed]
FerrignoD, BuccheriG, GiordanoC. Neuron-specific enolase is an effective tumour marker in non-small cell lung cancer (NSCLC). Lung Cancer. 2003;41:311–320. [CrossRef] [PubMed]
RoydsJA, RennieIG, ParsonsMA, TimperleyWR, TaylorCB. Enolase isoenzymes in uveal melanomas: a possible parameter of malignancy. Br J Ophthalmol. 1983;67:244–248. [CrossRef] [PubMed]
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×