Proteomic Analysis of Plasma Membrane from ... - ACS Publications

Proteomic Analysis of Plasma Membrane from Hypoxia-Adapted Malignant Melanoma Luke H. Stockwin,*,† Josip Blonder,‡ Maja A. Bumke,† David A. Lucas,‡ King C. Chan,‡ Thomas P. Conrads,‡ Haleem J. Issaq,‡ Timothy D. Veenstra,‡ Dianne L. Newton,† and Susanna M. Rybak§ Drug Mechanisms Group and Laboratory of Proteomics and Analytical Technologies, SAIC-Frederick Inc., National Cancer Institute at Frederick, and Developmental Therapeutics Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute at Frederick, Frederick, Maryland 21702 Received April 16, 2006

Hypoxic conditions often persist within poorly vascularized tumors. At the cellular level constitutive activation of transcriptional regulators of the hypoxic response leads to the emergence of clones with aggressive phenotypes. The primary interface between the cell and the hypoxic environment is the plasma membrane. A detailed investigation of this organelle is expected to yield further targets for therapeutic perturbation of the response to hypoxia. In the present study, quantitative proteomic analysis of plasma membrane from hypoxia-adapted murine B16F10 melanoma was performed using differential 16O/18O stable isotopic labeling and multidimensional liquid chromatography-tandem mass spectrometry. The analysis resulted in the identification of 24,853 tryptic peptides, providing quantitative information for 2,433 proteins. For a subset of plasma membrane and secreted proteins, quantitative RT-PCR was used to gain further insight into the genomic regulatory events underlying the response to hypoxia. Consistent increases at the proteomic and transcriptomic levels were observed for aminopeptidase N (CD13), carbonic anhydrase IX, potassium-transporting ATPase, matrix metalloproteinase 9, and stromal cell derived factor I (SDF-1). Antibody-based analysis of a panel of human melanoma cell lines confirmed that CD13 and SDF-1 were consistently upregulated during hypoxia. This study provides the basis for the discovery of novel hypoxia-induced membrane proteins. Keywords: quantitative proteomics‚16O/18O stable isotope labeling‚plasma membrane‚malignant melanoma‚hypoxia

Introduction Increased utilization of hypoxia-associated survival pathways is a common feature of many cancers. These responses are mediated primarily by hypoxia-inducible factors (HIFs), a group of oxygen-sensitive heterodimeric transcription factors.1 In reduced O2 environments, stabilized HIFs bind hypoxia response elements [5′-ACGTG(C/G)-3′] and modulate the transcription of selected genes involved in cell proliferation, apoptosis, glycolysis, solute transport, motility, and angiogenesis.2-4 This “starvation” phenotype reduces energy consumption and enhances the secretion of factors that promote restoration of O2 homeostasis (e.g., vascular endothelial growth factor). From a clinical perspective, hypoxia-adapted cancers show an increased metastatic potential and develop resistance to radiotherapy and alkylating agents.5-8 In several studies intratumoral hypoxia has been linked to poor prognosis.9,10 Preliminary data suggest that pharmacological modulation of * To whom correspondence should be addressed. Phone: (301) 846-5431. Fax: (301) 846-7021. E-mail: [email protected]. † Drug Mechanisms Group, SAIC-Frederick Inc. ‡ Laboratory of Proteomics and Analytical Technologies, SAIC-Frederick Inc. § Division of Cancer Treatment and Diagnosis.

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Published on Web 09/29/2006

proteins associated with the hypoxic response (HIF-1R, HIFprolyl hydroxylases, HSP-90) has potential in the treatment of cancer.11,12 The global response to hypoxia has been studied in several biological systems using both transcriptomic (cDNA microarrays) and proteomic (2D gel electrophoresis and antibody arrays) approaches.4,13-15 Aside from the several ubiquitous markers of hypoxia that were defined (GLUT-1, GAPDH), considerable heterogeneity was observed in the response between different cell types. Therefore, it is possible that different cancers express unique and potentially drugable markers of the hypoxic response. A rich potential source of such targets is the plasma membrane. However, proteomic analysis of plasma membrane has previously been complicated by the fact that the integral membrane proteins are generally incompatible with systems such as 2D PAGE.16 Considerable strides toward comprehensive proteomic analysis of plasma membrane have been made with the recent introduction of solutionbased quantitative “shotgun” proteomics.17-20 Here, complex protein mixtures are protease-cleaved and the peptides fractionated with multiple dimensions of liquid chromatography (LC). Finally peptide fractions are analyzed using LC-electrospray ionization mass spectrometry (ESI-MS). Quantitation of 10.1021/pr0601739 CCC: $33.50

 2006 American Chemical Society

Proteomic Analysis of Plasma Membrane from Melanoma

changes in protein abundance for a given variable is performed by differentially “tagging” protein/peptide mixtures with unique functional groups or stable isotopes prior to fractionation.21-23 Using such an approach, it is possible to identify and quantify several thousand proteins, including hydrophobic and lowabundance proteins, from small amounts of sample (100-500 µg).24 Previous work indicated that the murine melanoma cell line B16F10 undergoes a profound in vitro response to hypoxia characterized by increased activity of the VEGF-A/KDR autocrine loop and enhanced cord formation on matrigel.25 B16F10 is also capable of vasculogenic mimicry, an in vivo phenomenon where blood vessels are formed without endothelial cell involvement. In addition, the aggressive behavior of B16F10 xenograft models facilitates in vivo target validation. These combined properties were central to selecting B16F10 for proteome analysis in preference to human lines. The objectives of this investigation were to quantitatively profile hypoxiainduced plasma membrane proteins in B16F10 using stable isotopic labeling, followed by validation of selected hypoxiainduced targets using transcriptomic and antibody-based techniques. Sucrose-gradient-purified plasma membrane preparations, isolated from normoxic and hypoxic B16F10 cells, were solubilized and differentially tagged using 16O/18O stable isotopic labeling.26-28 The labeled digest was resolved initially by strong cation exchange (SCX) LC, and the fractions were analyzed by nanoflow reversed-phase LC coupled online by ESI to tandem mass spectrometry (MS/MS), enabling identification and quantitative profiling of the isotopomeric peptides from normoxic and hypoxic plasma membrane. For a subset of characterized proteome IDs, expression was validated by quantitative RT-PCR. The analysis was then extended to selected human melanoma cell lines with the aim of revealing common denominators of hypoxic response. The present work provides insights into melanoma biology and adaptations to stress and suggests potential targets for the therapeutic disruption of the response to hypoxia.

Experimental Procedures Materials. Melanoma cell lines were from the National Cancer Institute (NCI) at Frederick DCTD Tumor Repository (Frederick, MD). Materials were from the following: phosphatebuffered saline (Quality Biologicals, Gaithersburg, MD), sequencing-grade trypsin (Promega, Madison, WI), reversedphase C18 solid-phase extraction (SPE) columns (Alltech, Deerfield, IL), BCA assay reagents (Pierce, Rockford, IL), GammaBind protein G Sepharose (Amersham, Piscataway, NJ), PVDF membranes (Invitrogen, Carlsbad, CA), complete protease inhibitor tablets (Roche, Indianapolis, IN). All other chemicals were from Sigma, St. Louis, MO. Primary antibodies were from the following: anti-ATP synthase β subunit (Molecular Probes, Eugene, OR), anti-hu/muCD13 and antihuCD97 (Serotec, Raleigh, NC), anti-muCD97 (Dr. Jo¨rg Hamann, Academic Medical Center, Amsterdam, The Netherlands), anti-muCD44, anti-muCD71, and anti-cytochrome c (Biolegend, San Diego, CA), anti-HSP90 (Stressgen, San Diego, CA), anti-hu/muSDF-1 (R&D Systems, Minneapolis, MN), antiGLUT-1 (Chemicon, Temecula, CA), anti-HIF-1R (Novus Biologicals, Littleton, CO), anti-β-actin and anti-Golgi 58K (Sigma, St. Louis, MO), anti-GAPDH and anti-PCNA (Abcam, Cambridge, MA). For Western analysis, secondary HRP-conjugated antibodies were from Jackson Immunoresearch (West Grove,

research articles PA), and for immunocytochemistry secondary biotinylated or Alexa488-conjugated antibodies were from Molecular Probes. Hypoxia Monitoring. Pimonidazole hydrochloride (Hypoxyprobe-1, Chemicon) was used in immunocytochemistry and FACS analysis to confirm the status of cells in culture prior to proteome analysis.29 In brief, cells on coverslips were incubated in a medium supplemented with 400 µM compound for 24 h under hypoxic or normoxic conditions. After incubation, the cells were fixed with 4% formaldehyde and permeabilized with 0.1% saponin. Primary anti-adduct monoclonal antibody (clone 1Mab1) was then added (2 µg/mL). After 1 h, the cells were washed twice, and secondary goat anti-mouse Alexa488-conjugated antibody was added at 5 µg/mL for a further 45 min. The samples were then washed three times with PBS and analyzed using a Leica DM compound fluorescence microscope (Rockville, MD). VEGF ELISA. The concentration of mVEGF in cell-free culture supernatants was determined using a commercially available kit (Quantikine-mVEGF, R&D Systems Inc.). Experimental determination was made with reference to a standard curve of mVEGF. Apoptosis/Necrosis Determination. The percentage of apoptotic and necrotic cells in culture was determined using the Vybrant apoptosis assay kit (Molecular Probes) comprising an annexin V-Alexa488 conjugate and propidium iodide. Acquisition and analysis of data were performed using a FACScan flow cytometer (Becton-Dickinson, Franklin Lakes, NJ) controlled by Cellquest Pro software. Western Blotting. Cells were washed twice in PBS and lysed in RIPA-CHAPS buffer (50 mM Tris-HCl, pH 7.4, 1 mM EDTA, 1% CHAPS, 1% deoxycholate, 1× complete protease inhibitor). Lysates were then sonicated and centrifuged to remove insoluble material, and the protein concentration was determined using the BCA assay (Pierce). SDS-PAGE was then performed using 20 µg of protein per well on a 4-12% Novex Tris-glycine gel (Invitrogen) with subsequent transfer to a PVDF membrane by electroblotting. Membranes were incubated with primary antibody overnight and washed several times before incubation with secondary peroxidase-conjugated antisera for 2 h. Bands were visualized using enhanced chemiluminescence reagents (Amersham) according to the manufacturer’s protocol. Cord Formation Assay. Matrigel (Becton-Dickinson) was added to each well in an eight-well glass chamber slide on ice and allowed to solidify at room temperature for 1 h. B16F10 cells were then added at a range of 1 × 103/mL to 1 × 105/mL in serum-free DMEM. The cells were then placed into a 37 °C humidified incubator (normoxia) or into a modular incubator chamber (Billups Rothenberg, Del Mar, CA) and flushed for 20 min with a mixture of 1% O2, 5% CO2, and 94% N2 (hypoxia). After incubation overnight, images of cords were captured using a Leica DM-LB inverted microscope. Cell Growth and Plasma Membrane Isolation. Forty 75 cm2 flasks of B16F10 cells were cultured to 75% confluence in DMEM and 10% FCS. The flasks were then divided into two groups and subjected to either hypoxic or normoxic conditions for 24 h. Hypoxia was induced by exposing the cells to 1% O2 for 24 h using modular incubator chambers (Billups Rothenberg). The normoxic group was cultured under standard incubator conditions (5% CO2, 95% air). After exposure, the cells were washed three times with ice-cold PBS (Ca2+, Mg2+) and scraped into 20 mL of ice-cold hypotonic buffer (10 mM HEPES, pH 7.5, 1.5 mM MgCl2, 10 mM KCL, 1× complete protease inhibitor tablet, 1 mM sodium orthovanadate). The suspension Journal of Proteome Research • Vol. 5, No. 11, 2006 2997

research articles was then incubated for 30 min on ice followed by disruption of the cells with 50 passes in a dounce homogenizer (Kontes Glass Co., Nineland, NJ) and centrifuged (1000g, 10 min) to remove intact cells or nuclei. The remaining supernatant was layered onto 10 mL of 37.2% sucrose solution and centrifuged at 27000 rpm in an SW28 rotor for 3 h at 4 °C. The white band of plasma membrane at the interface was removed and resuspended in ice-cold 0.2 M sodium carbonate, pH 11. After 30 min, the suspension was centrifuged at 27000 rpm in an SW28 rotor for 1.5 h at 4 °C. The pelleted plasma membrane fractions were resuspended separately in ice-cold distilled water, pelleted, and stored at -80 °C. Solubilization and Trypsin-Facilitated 18O Labeling. Solubilization and 18O labeling were carried out using a previously described method.28 Briefly, the plasma membrane protein fractions isolated from normoxic and hypoxic B16F10 cells were resuspended in 1 mL of 50 mM NH4HCO3, pH 7.9, and the protein content was determined using the BCA assay. Equal amounts of proteins (375 µg each) were reduced using 1 mM TCEP and alkylated with 15 mM iodoacetamide for 30 min at 37 °C. The membranes were pelleted at 100000g for 1 h and the pellets washed twice. Solubilization of each sample was carried out separately in 500 µL of 60% methanol in 25 mM NH4HCO3, pH 7.9, facilitated by intermittent sonication. Trypsin was added at a 1/20 enzyme/protein ratio and each sample incubated for 6 h at 37 °C. After digestion, the samples were lyophilized to dryness. The digest from hypoxia-adapted cells was resuspended in 20% methanol in 25 mM NH4HCO3, pH 7.9, prepared in H218O. Trypsin-catalyzed 18O exchange/labeling was carried out at 37 °C using a 1/20 enzyme/peptide ratio. An identical procedure was performed on the control sample using the same digestion buffer prepared in H216O. The digestions were quenched after 6 h by boiling the samples for 3 min and cooling them to room temperature followed by addition of 0.4% TFA (final concentration). The 18O- and 16O-labeled samples were immediately combined, lyophilized to dryness, and stored at -80 °C. Peptide Fractionation by Strong Cation Exchange Liquid Chromatography. Lyophilized peptides were dissolved in 200 µL of 45% acetonitrile containing 0.1% formic acid prior to SCX chromatography. The sample was resolved into 80 fractions using a microcapillary LC system (model 1100, Agilent Technologies Inc., Palo Alto, CA) with a polysulfoethyl A, 4.6 × 200 mm, 5 m, 300 Å pore size column (PolyLC, Southborough, MA). Peptide fractions were eluted with an ammonium formate multistep gradient at a flow rate of 200 µL/min as follows: 0-1% B in 2 min, 1-10% B in 60 min, 10-62% B in 20 min, 62-100% B in 3 min. Mobile phase A was 45% CH3CN, and mobile phase B was 45% CH3CN and 0.5 M ammonium formate, pH 3. The SCX-LC fractions were lyophilized to dryness and reconstituted in 0.1% formic acid immediately prior to MS analysis. Nanoflow RPLC-MS/MS Analysis. Nanoflow RPLC of each SCX fraction was carried out on an Agilent 1100 nanoflow LC system using a 75 µm (inner diameter) × 360 µm (outer diameter) × 10 cm long in-house-packed fused silica capillary column (Polymicro Technologies Inc., Phoenix, AZ) using a 3 µm, 300 Å pore size C18 medium (Vydac, Hysperia, CA). The capillary column was coupled to a hybrid linear ion trapFourier transform ion cyclotron resonance mass spectrometer (LTQ-FT, ThermoElectron, San Jose, CA) using the nanoelectrospray ionization source supplied by the manufacturer. After injection of 5 µL of sample, the column was washed for 30 min 2998

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(at 0.5 µL/min) with 2% B, and peptides were eluted (at 0.25 µL/min) using a linear gradient as follows: 2-60% B in 100 min, 60-98% B in 20 min, 98% B for 20 min. The column was reequilibrated with 2% B for 30 min prior to subsequent sample loading using a flow rate of 0.5 µL/min. Mobile phase A was 0.1% formic acid in H2O, and mobile phase B was 0.1% formic acid in acetonitrile. The MS instrument was operated in a datadependent mode where the five most intense ions detected in each FTICR-MS scan (m/z 200-2000) were selected for MS/ MS in the ion trap (precursor selection from m/z 400 to m/z 2000). A normalized collision energy of 36% was employed for collision-induced dissociation (CID) along with dynamic exclusion of 90 s to reduce redundant selection of peptides for CID. The ESI voltage and the heated capillary temperature were set at 1.6 kV and 160 °C, respectively. Data Processing. CID spectra were analyzed using SEQUEST, on a Beowulf 20-node parallel virtual machine cluster computer (ThermoElectron) against a nonredundant mouse proteome database (http://www.ebi.ac.uk/integr8/EBI-Integr8-HomePage.do, release date Jan 4, 2005). A dynamic modification of +57.021 Da was set for iodoacetamide alkylated cysteinyl (Cys) residues, and +4.008 Da was set on the C-terminus for 18Olabeled peptides. A mass tolerance of maximum 0.2 Da was used for mass measurements in the MS mode and 1.5 Da for the MS/MS mode. Only peptides possessing tryptic termini (allowing for up to two internal missed cleavages) possessing ∆ correlation scores (∆(CN)) g0.08 and charge-state-dependent cross-correlation (Xcorr) criteria, g1.9 for [M + H]+1 peptides, g2.2 for [M + 2H]+2 peptides, and g3.1 for [M + 3H]+3 peptides, were considered legitimate identifications. The false positive rate of peptide identification was determined by searching acquired MS/MS spectra against the reversed mouse database using the same SEQUEST filtering criteria (Xcorr and ∆(CN)). Only proteins identified by at least two tryptic peptides were considered for quantitative analysis. Relative abundances for differentially labeled isotopomeric peptides were calculated from their monoisotopic peaks and the respective extracted ion chromatogram areas calculated using XPRESS software (ThermoElectron) and are reported as heavy-to-light 18O/16O ratios (i.e., 18O-labeled hypoxia-treated sample/16O-labeled normoxic sample) for a particular peptide/protein. Reverse Transcription. Total RNA was isolated from cells using the RNeasy minikit (Qiagen, Valencia, CA) and reverse transcribed using Omniscript RT according to the manufacturer’s instructions. A standard reaction comprised 2 µg of total RNA, a 0.5 mM concentration of each DNTP, 2 µM random decamers (Ambion, Austin, TX), and 4 units of reverse transcriptase in a 20 µL total volume of 1× RT buffer. The reaction was allowed to proceed for 90 min at 37 °C and the cDNA product diluted to 1 µg/mL and stored at -80 °C. Real-Time PCR. SYBR Green chemistry was used to detect primer-specific amplicons. For each reaction, 12.5 µL of Quantitect SYBR Green PCR master mix (Qiagen, Valencia, CA) was diluted 1/2 in DNase-free water containing 5 ng of cDNA and a 1 µM concentration of a specific primer pair. Reactions were performed in triplicate, and universal 18S RNA primers (Ambion) were used to normalize cDNA amplification. The fluorochrome ROX, included in the PCR master mix, was used as a passive reference. Reactions were performed using an ABI7500 thermocycler (Applied Biosystems, Foster City, CA). Cycling conditions consisted of a single 10 min/95 °C activation step followed by 40 cycles of 95 °C/15 s, 60 °C/60 s, and 72 °C/60 s with fluorescence measurements taken in the elongation step

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Figure 1. Response to hypoxia in B16F10 melanoma. (A) Pimonidazole hydrochloride reacts with hypoxic B16F10 plasma membrane to form adducts that are visualized by immunocytochemistry using the 1Mab1 monoclonal antibody. (B) Western blotting of B16F10 cell lysates with R-HIF-1R and R-GLUT-1 antibodies confirmed increased expression after hypoxia (left panels), and immunocytochemistry confirmed subcellular localization (right panels). (C) B16F10 cells cultured on matrigel in a serum-free medium and exposed to hypoxia for 24 h showed increased “cord” formation. (D) Semiquantitative RT-PCR (lower panel) and supernatant ELISA (upper panel) demonstrated increased VEGF-A levels in hypoxic B16F10. Increased propidium iodide uptake was only evident after 24 h (dashed line). Unless stated otherwise, the cells were exposed to hypoxic conditions (1% O2) for 24 h.

of each cycle. Fold changes in expression were calculated manually from ∆∆Ct values. For each primer pair agarose gel electrophoresis (1%) and melting curve analysis were used to confirm the presence of a single amplicon. Immunocytochemistry and Flow Cytometry. For microscopic analysis cells were grown on coverslips until 50% confluent, washed three times in PBS, and fixed using 4% paraformaldehyde. After four washes in PBS, the cells were blocked in permeabilization (P) buffer (PBS, 4% BSA, 0.2% saponin) for 1 h and resuspended in P buffer containing primary antibody. The cells were then incubated between 4 and 12 h, washed three times in P buffer, and incubated with fluorochrome-conjugated secondary antibody (1 µg/mL) and DAPI nuclear counterstain (5 µg/mL). After incubation for 2 h, the cells were washed four times in PBS, mounted on glass slides, and imaged using a Leica DM compound microscope. For quantitative fluorescence measurements using flow cytometry essentially the same protocol was adopted, with 1 × 106 cells stained per sample and incubations performed on suspension cells on a round-bottom 96-well plate. Flow cytometry data were acquired using the FL1 channel on a FACScan cytometer controlled by CellQuest Pro software (Becton Dickinson).

Results and Discussion Establishing a Model of Hypoxia. The optimum conditions for proteome analysis were defined using several classical assays of the response to hypoxia. Pimonidazole hydrochloride is a compound that reacts with hypoxic cells to produce adducts that can subsequently be visualized using a specific fluorochrome-labeled antibody. Negligible staining was observed when cells were cultured with pimonidazole hydrochloride for 24 h under normoxic conditions, whereas cells incubated in 1% O2 showed intense fluorescence (Figure 1A). Western blotting of B16F10 lysate following incubation under hypoxia for 24 h revealed upregulation of two ubiquitous markers of hypoxia, HIF-1R and GLUT-1 (Figure 1B).2,3 Furthermore, B16F10 melanoma cultured on matrigel forms networks of elongated, hollow structures termed “cords”.25 In response to hypoxia, under serum-free conditions, the number and complexity of these cords were seen to increase markedly relative to those of the control (Figure 1C). An ELISA-based assay was also performed to track hypoxia-associated changes in VEGF-A secretion into cell culture supernatants (Figure 1D). After 8 h, detectable increases in VEGF-A were observed in the hypoxic supernatants. The greatest difference was observed at 24 h of hypoxia, where 10-fold more VEGF was detected relative Journal of Proteome Research • Vol. 5, No. 11, 2006 2999

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fied by at least two tryptic peptides, satisfying stringent chargestate/cross-correlation criteria (see the Experimental Procedures), were considered for quantitative analysis and further validation using Q-PCR and antibody-based techniques. The overall MS analysis resulted in identification and quantitation of 2433 proteins from a pool of 24853 tryptic peptides (Supporting Information). False positive analysis of identified peptides, performed by searching against a “reverse” mouse database, derived a false positive rate of 3.25% (data not shown).31 Bioinformatic analysis was further performed to broadly subdivide the proteome. Results of gene ontology analysis showed that the majority of proteins (66.6%) were annotated to some extent, with the remainder (34.4%) being uncharacterized (data not shown). In terms of subcellular localization, 39.8% of the annotated proteins were identified as membrane proteins and 10.2% as extracellular proteins. This supports a degree of plasma membrane enrichment given that only 20-25% of the proteins in the entire proteome are predicted to be membrane-localized.32 Figure 2. Western blot analysis of sucrose-gradient-purified protein. The extent of plasma membrane enrichment was investigated by comparing crude B16F10 lysate with sucrosegradient-purified material. Equal amounts (20 µg) of protein solubilized in RIPA buffer were separated by SDS-PAGE and blotted onto PVDF membrane. The blots were then probed with antibodies specific for antigens restricted to subcellular compartments including β-actin (cytosolic), cytochrome c (mitochondrial/ cytosolic), GAPDH (cytosolic), PCNA (nucleus), G-58k (Golgi), and transferrin receptor TFR-1 (plasma membrane).

to that of cells cultured under normoxia (964 and 91 pg/mL, respectively). Applying semiquantitative RT-PCR to the same time course showed a rapid enhancement in VEGF-A mRNA after only 2 h of hypoxia. Propidium iodide (PI) exclusion and annexin V staining were also used to quantify the levels of necrosis and apoptosis at each time point (Figure 1D, dotted line). Results showed a profound increase in PI uptake to 65% after 48 h of hypoxia. These results confirmed hypoxic conditions and suggested that 24 h of exposure was a suitable time point for the preparation of hypoxic B16F10 plasma membrane. Proteomic Analysis of Hypoxic Plasma Membrane. Sucrose density centrifugation and carbonate extraction were used to isolate and purify plasma membrane from normoxic and hypoxic B16F10 melanoma cells. The extent of plasma membrane enrichment in gradient-purified B16F10 preparations was determined by Western blotting (Figure 2). Equal amounts of protein were resolved by one-dimensional SDS-PAGE, transferred to a PVDF membrane, and probed for expression of β-actin (cytosolic), cytochrome c (mitochondrial/cytosolic), GAPDH (cytosolic), PCNA (nucleus), G-58K (Golgi), and transferrin receptor TFR-1 (plasma membrane). A high degree of consistency in enrichment was observed from hypoxic and normoxic plasma membrane preparations that were processed concurrently. Results showed significant increases in TFR-1 reactivity after purification with a corresponding decrease in G-58K, GAPDH, cytochrome c, and β-actin. However, PCNA reactivity decreased only slightly relative to that of the crude lysate, indicating that some nuclear contamination may be present. Confirmation of plasma membrane enrichment was followed by solubilization of the hypoxic and normoxic preparations in 60% buffered methanol.30 The samples were then digested with trypsin, differentially labeled using trypsincatalyzed 18O/16O isotopic exchange, fractionated using SCX, and analyzed using nanoRPLC-MS/MS. Only proteins identi3000


It is widely accepted that the number of identified peptides from a given protein within a complex protein mixture correlates well with its abundance. Sodium/potassium-transporting ATPase R-1 (Na+/K+ ATPase 1) and transferrin receptor protein 1 (TFR-1) were identified by 150 and 124 tryptic peptides, respectively, as shown in Table 1. In the list of 2433 identified and quantified proteins, Na+/K+ ATPase 1 was the seventh most abundant protein according to the number of identified peptides while TFR-1 was placed as ninth. Figure 3A shows an expanded mass spectrum of a doubly charged peptide molecular ion pair exhibiting a ∆(m/z) of 2.004 that illustrates detection of both 16O- and 18O-labeled isotopomeric peptide and confirms successful differential stable isotope labeling. Figure 3B shows unambiguous identification of the amino acid sequences of the light 16O isotopomer, while Figure 3C demonstrates identification of heavy 18O-labeled isotopomeric peptide K.LAADEEENADNNMK.A from transferrin receptor TFR-1 shown in Figure 3A. Na+/K+ ATPase and TFR-1 are recognized as well-characterized plasma membrane markers. A selection of representative identified proteins that are likely related to the underlying pathology and hypoxic response of malignant melanoma are shown in Table 1. The identification of several melanoma markers (e.g., tyrosinase), known oncogenes (e.g., hepatocyte growth factor receptor), growth factors (e.g., stromal-cell-derived factor), and angiogenesis-related receptors (e.g., vascular endothelial growth factor receptor 1) authenticates the origin of the starting material. In proteomics a significant number of detected peptides do not uniquely identify only one protein within large mammalian proteome databases due to the numerous protein isoforms and relatively small size of identified tryptic peptides, which occasionally do not possess sufficiently divergent sequences to specifically identify a single protein. To accomplish accurate comparative quantitation at the protein level, it is important to exclude these peptides from quantitative analyses. To address this issue, we developed software able to single out tryptic peptides that identify more than one protein within a proteomic database.33 Applying this filter to our dataset, we were able to measure relative concentrations of truly unique peptides/proteins, resulting in enhanced accuracy of comparative quantitation. Using a nonlinear least-squares regression, applied to the data series of a normalized number of identified proteins and their experimentally determined ratios, it has been determined that abundance ratios greater than 1.71 and less

angiogenesis

growth factors

oncogenes

melanoma antigens

a Column head descriptions: accession no., Swiss-Prot/TrEMBL primary accession number; m/z (MH+), calculated mass; peptide sequence, example peptide identified from the corresponding protein (a left bracket indicates the heavy labeled C-terminus); Xcorr, SEQUEST cross-correlation score; ∆(CN), SEQUEST ∆ correlation score; count, number of identified peptides.

124 150 13 47 2 16 10 21 9 7 6 4 3 16 12 5 6 2 2 3 0.5132 0.5441 0.5227 0.4456 0.2877 0.5292 0.7005 0.5642 0.4477 0.5899 0.6331 0.5541 0.1497 0.6129 0.6062 0.5053 0.4921 0.0943 0.1774 0.1423 5.0886 5.5859 3.9338 3.8047 2.5171 4.2116 4.755 3.6412 4.5832 4.6636 5.4274 5.2292 2.9325 5.8241 5.3307 4.0985 5.7443 2.6231 2.5748 3.0268 K.LAADEEENADNNMK[.A K.MSINAE DVVVGDLVEVK[.G K.VAEDET EAGVK[.F R.LSLQDSVATLALSHVTPHDER[.M K.VCTDTGHMETQRTNPR[.S K.NGGADTEQPVQEWK[.N K.DLGYDYSYLQESDPGFYR.N R.SVSPTTEMVSNESVDYR[.A K.LFGGFNSSDTVTSPQR[.A R.AQFETLQQLVQHYSEK[.A K.LPQLVDMAAQIADGMAYIER.M K.ANINVENAFFTLAR.D R.AIGDFLKDKYDSASEMVVEK.H K.TEFLSFMNTELAAFTK.N K.QELILAEIHNGVEQVR[.V K.SC*AAEPEVEPEAHEGDGDK[.K K.HSSTDVLLSVTGEQYGR[.P K.QKMATTQDYSITLNLVIK[.N K.CQLRKGGWQQPTLNTR[.T R.LKLKSLASMDSR.S transferrin receptor protein 1 (TFR-1) sodium/potassium-transporting ATPase R-1 4F2 cell-surface antigen, heavy chain L-gicerin/MUC18 melanophilin (exophilin 3) membrane-associated transporter protein (AIM-1 protein) tyrosinase precursor (monophenol monooxygenase) hepatocyte growth factor receptor precursor (c-met) neuronal proto-oncogene tyrosine-protein kinase (SRC) proto-oncogene tyrosine-protein kinase FYN (P59-FYN) proto-oncogene tyrosine-protein kinase YES (C-YES) Ras-related protein Rab-8A (oncogene c-mel) Wnt-3 proto-oncogene precursor endothelial monocyte-activating polypeptide (EMAP) endothelial monocyte-activating polypeptide II (EMAP-II) hepatoma-derived growth factor (HDGF) stromal-cell-derived factor 2 precursor (SDF-2) vascular endothelial growth factor receptor 1 (VEGFR-1) vascular endothelial growth factor C precursor (VEGF-C) vascular endothelial growth factor D precursor (VEGF-D) plasma membrane markers

Q62341 Q8VDN2 P10852 Q9EPF1 Q91V27 P58355 P11344 P16056 P05480 P39688 Q04736 P55258 P17553 P50543 P31230 P51859 Q9DCT5 P35969 P97953 P97946

1567.6671 1820.9441 1151.5557 2293.1913 1877.836 1562.7212 2187.9506 1904.8673 1716.8318 1952.9843 2205.1042 1579.8227 2245.1057 1849.9041 1852.0054 2030.8375 1852.9166 2071.1235 1889.9894 1348.7617

Xcorr protein description accession no.

Table 1. A Subset of Proteins Identified during Analysis of B16F10 Plasma Membranea

m/z (MH+)

peptide sequence

∆(CN)

count


research articles than 0.58 are the statistically significant limits for analysis.34 According to these criteria in the dataset of 2433 proteins quantified by at least two tryptic peptides, 292 proteins showed increased expression whereas 580 had decreased levels after hypoxia. We hypothesize that the higher proportion of proteins exhibiting a decreased relative concentration may be a consequence of a reduced protein diversity arising from the global inhibition of protein synthesis that accompanies hypoxia. For the remaining 1561 quantified gene products, hypoxia had no effect on the apparent 18O/16O ratio. Figure 4 illustrates identification and quantitation of aminopeptidase N (CD13), showing a higher concentration of this gene product within the hypoxic plasma membrane proteome and its possible upregulation in response to hypoxia. Figure 4A shows the expanded full-range FTICR mass spectrum detecting the differentially 16O/18O-labeled, doubly charged molecular ion pair, followed by the MS/MS spectrum showing the fragment ion series and identification of heavy isotopomeric peptide R.VMAVDALASSHPLSSPADEIK.T from this protein (Figure 4B). Parts C and D, respectively, of Figure 4 show the extracted ion chromatograms of the light (16O-labeled) and heavy (18Olabeled) isotopomeric peptides of the molecular ion pair shown in Figure 4A. In multidimensional quantitative proteomics, logistical challenges, in terms of sample quantity and instrument access, often limit the number of experimental replicates that can be performed. This fact makes validation using orthogonal biological techniques essential. To this end, quantitative RT-PCR was performed on 50 proteome-defined transcripts, including “known players” in the hypoxic response and several wellcharacterized integral membrane and secreted proteins. Although discrepancies between protein and mRNA levels are well documented,35 the major advantage of conducting RT-PCR as the primary validation technique was that the large dynamic range of detection far exceeds that possible with antibodybased techniques, combined with a high precision of measurement. Total RNA was isolated from hypoxic and normoxic B16F10 cells and reverse transcribed, and expression of specific transcripts measured relative 18s rRNA. Consistent with the induction of hypoxia, VEGF, GAPDH, and TIM mRNA showed marked upregulation whereas the posttranslationally regulated transcripts HIF-1R and HIF-1β were unaltered. Two of these proteins, the glycolytic enzymes GAPDH and TIM, were also identified during proteome analysis and showed 18O/16O ratios of 4.54 and 2.17, respectively. Results provided qualitative support for proteomic data, as specific amplicons were detected for all analyzed transcripts. A direct comparison of the results obtained from isotope labeling and quantitative RT-PCR is shown in Table 2. Any target demonstrating ratios of >1.7 for 18 O/16O and >2.0 for Q-RT-PCR was considered positively regulated by hypoxia. Comparing the proteomic and transcriptomic quantitation in Table 2 shows a trend toward increased expression after hypoxia, with 22 (44%) targets in the subset demonstrating statistically significant increases for both techniques. Eight targets (16%) were considered as neutrally regulated given that threshold values were not met by either technique. The remaining 19 targets (38%) showed some discordance between methodologies. Possible biological explanations for this discordance include protein trafficking, posttranslational regulation of specific proteins, or posttranslational modification of peptides under hypoxic conditions. Quantitative flow cytometry was also performed on selected proteins within the subset Journal of Proteome Research • Vol. 5, No. 11, 2006 3001

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Figure 3. Selected mass spectra of differentially labeled peptide isotopomers from a plasma membrane marker, transferrin receptor TFR-1: (A) zoomed portion of the FTICR mass spectrum of the 16O/18O-labeled doubly charged [M + 2H]2+ molecular ion pair (light, m/z 782.333; heavy, m/z 784.337) showing a typical difference of 2 m/z; (B, C) MS/MS fragmentation ion series of (B) light (unlabeled) 16O-labeled and (C) heavy 18O-labeled isotopomeric peptide showing typical ∼4 Da mass shifts in the singly charged y-type ion series, confirming a successfully 18O-tagged C-terminus.

(Figure 5). Fluorescence measurements were made using hypoxic and normoxic cells that had been fixed and permeabilized to allow quantitation of total cellular protein. Under hypoxic conditions, increased fluorescence was observed for antibodies against two control proteins, HIF-1R and GLUT1. For the majority of analyzed proteins, the results were consistent with the 18O/16O ratio, with CD13 and SDF-1 showing increased fluorescence after hypoxia, whereas CD44, CD97, and TFR-1 fluorescence was unaltered. ATP synthase β fluorescence 3002


increased slightly but was not significant enough to conclusively support the increased 18O/16O ratio. The only apparent contradiction was that HSP-90 fluorescence appeared to decline during hypoxia. These results largely support results from proteomic quantitation. For targets showing signficiant changes in both 18O/16O and Q-PCR, possible biological consequences can be inferred. In the metabolism category, ATP synthase R and β chains, ADP/ ATP carrier protein 2, Na+/K+-transporting ATPase, K+-


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Figure 4. Mass-spectrometry-based identification and quantitation of a selected peptide from aminopeptidase N (CD13): (A) zoomed portion of the FTICR mass spectrum of the 16O/18O-labeled doubly charged [M + 2H]2+ molecular ion pair (light, m/z 1069.555; heavy, m/z 1071.559462); (B) MS/MS fragmentation spectrum of heavy 18O-labeled isotopomeric peptide R.VMAVDALASSHPLSSPADEIK.T; (C, D) extracted ion chromatogram of the light isotopomeric peptide (C) and heavy 18O-labeled isotopomeric peptide (D) of the molecular ion pair shown in (A), indicating a higher relative abundance (concentration) of the 18O-labeled peptide (18O/16O ratio 2.0).

transporting ATPase R, and voltage-dependent anion-selective channel protein 1 showed increased expression during hypoxia. Although proteins such as ATP synthase and VDAC1 were

previously thought to be mitochondrion-restricted, recent evidence also places lower levels of these molecules at the plasma membrane.36,37 Perhaps the most primitive response Journal of Proteome Research • Vol. 5, No. 11, 2006 3003

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Table 2. Quantitation of Hypoxia-Associated Changes in a Subset of Relevant Proteins Using O16/O18 Differential Analysis and Quantitative RT-PCR function

hypoxia controls adhesion

growth factors and receptors

metabolism

chaperones metastasis and angiogenesis

accession no.

protein description

subcellular location

count

O16/O18

Q-PCR

P16858 P17751 Q08857 P15379 Q63961 P11688 P09055 O54890 Q9EPF1 P13595 P50543 P31230 P16056 O35375 O09126 P40224 Q9DCT5 P48962 P51881 Q03265 Q9CQQ7 Q8VDN2 P17809 P32037 P15208 Q60751 P06795 Q9JJX4 Q88343 Q8VEM8 Q64436 Q9JIM1 Q62351 P51863 Q60932 P14211 P63038 P11499 P97449 Q64444 Q8VHB5 Q9WVT6 Q9Z0M6 P29319 P54754 P53690 P41245 Q9QYH6 O35566 Q64302

glyceraldehyde-3-phosphate dehydrogenase triosephosphate isomerase CD36 antigen (collagen type I receptor) CD44 antigen precursor endoglin precursor integrin R-5 precursor integrin β-1 precursor integrin β-3 precursor L-gicerin/MUC8 neural cell adhesion molecule 1 NCAM-1 EMAP-1 EMAP-2 hepatocyte growth factor receptor neuropollin-2 precursor semaphorin 4D precursor SDF-1 SDF-2 ADP,ATP carrier protein 1 ADP,ATP carrier protein 2 ATP synthesis alpha chain ATP synthase B chain ATPase Na+, K+ transport GLUT-1 GLUT-3 insulin receptor precursor IGF-1R MDR-1 PGP P2X purinoreceptor Panc sodium bicarbonate transporter phosphate carrier protein potassium-transporting ATPase R solute carrier family 29 TFR-1 V-ATPase D VDAC-1 calreticulin precursor HSP-60 HSP-90 β aminopeptidase N (CD13) carbonic anhydrase IV precursor carbonic anhydrase IX precursor carbonic anhydrase XIV precursor CD97 antigen precursor ephrin type-A receptor 3 ephrin type-B receptor 3 matrix metalloproteinase-14 precursor matrix metalloproteinase-9 precursor MAGE-D1 antigen membrane glycoprotein SFA-1 tumor-associated antigen L6

cytoplasm cytoplasm plasma membrane plasma membrane plasma membrane plasma membrane plasma membrane plasma membrane plasma membrane plasma membrane secreted secreted plasma membrane plasma membrane plasma membrane secreted secreted mitochondrial mitochondrial mitochondrial mitochondrial plasma membrane plasma membrane plasma membrane plasma membrane plasma membrane plasma membrane plasma membrane plasma membrane mitochondrial plasma membrane plasma membrane plasma membrane vacuolar mitochondrial endoplasmic reticulum mitochondrial cytoplasm plasma membrane plasma membrane plasma membrane plasma membrane plasma membrane plasma membrane plasma membrane plasma membrane plasma membrane plasma mem/ cytoplsm plasma membrane plasma membrane

23 4 8 27 11 12 95 14 47 14 16 12 21 8 2 2 6 25 17 49 10 150 12 2 2 2 3 2 7 9 5 6 124 49 48 115 29 48 34 3 2 19 11 4 2 3 2 2 2 2

4.54 2.17 1.55 0.91 1.06 2.1 2.2 0.94 2.02 2.58 0.45 1.39 0.84 1.45 2.54 2.75 0.77 1.11 2.02 2.11 2.11 2.23 1.21 1.05 1.57 0.61 0.68 1.09 2.03 1.16 8.98 1.29 1.02 1.02 5.4 2.32 1.77 2.76 2.05 0.94 1.89 2.1 1.09 1.74 0.72 1.13 8.5 3.26 1.16 0.81

2.4 5.5 1.5 4.2 2.4 2 3 1.7 4.5 7.8 4.9 3.6 2.7 1.8 1.9 4.2 2.1 1.7 3.5 2.3 3.7 2.7 4.7 2.6 4.2 3.6 0.4 2.3 2.3 1 2.5 1.8 1.2 2.1 5.7 2.2 0.7 2.1 6.5 4.6 36.3 1.5 3.3 2.6 4.9 1.7 3.7 2.4 4.3 3.9

a Column head descriptions: accession no., Swiss-Prot/TrEMBL primary accession number; count, number of identified peptides; proteomic and transcriptomic fold changes in expression with hypoxia.

to hypoxia involves increasing ATP conservation. It is therefore reasonable to expect that subunits of ATP synthase would increase in response to hypoxia. The profound upregulation of K+-transporting ATPase R suggests that this molecule plays an important role in the hypoxic response. This integral membrane protein is a proton pump used primarily in the acidification of the upper gastrointestinal tract.38 Acidification of the extracellular space also plays an important role in metastasis, permitting activation of secreted proteases and promoting degradation of the extracellular matrix.39 Therefore, K+-transporting ATPase probably contributes toward the acidification pheneomenon. In the adhesion molecule division, increased expression was noted for neural cell adhesion molecule 1 (NCAM-1) and L-gicerin/MUC18. In HT-29 cells expression of NCAM-1 has 3004


18

O/16O and Q-PCR,

been shown to decline with hypoxia, which was interpreted as a mechanism to enhance cell detachment and metastasis.40 Increased expression of NCAM-1 in B16F10 may be an example of a genuine difference in the underlying biological response to hypoxia for different cell types. The melanoma-restricted antigen L-gicerin/MUC18 (also known as melanoma adhesion molecule, MCAM) binds neurite outgrowth factor (NOF) and facilitates interactions with endothelial cells. Increased expression of L-gicerin/MUC18 has been shown to increase tumorigencity in nude mice and also to be a useful clinical marker of melanoma progression.41 With respect to growth factors, a consistent increase was observed for stromal-cell-derived factor (SDF-1/CXCL12). This HIF-1R-induced chemokine mediates the arrest and adhesion of circulating CD34+ progenitor cells while enhancing VEGF


Figure 5. Flow cytometric validation of hypoxia-induced changes in protein expression. (A) Hypoxic B16F10 cells were fixed, permeabilized, and stained with nine different antibodies to confirm both expression and subcellular localization. Control slides stained with isotype-matched monoclonal antibody were included and showed negligible fluorescence. (B) Hypoxic and normoxic cells were then processed in parallel using the identical protocol and then analyzed by flow cytometry. Results shown are fold changes in FL1 fluorescence (FL1-H/FL1-N) normalized to isotype control fluorescence values.

secretion and VEGF-induced cell proliferation in endothelial cells.42-44 For tumor cells with active CXCR4 (SDF-1 receptor) signaling gradients of SDF-1 are thought to be partly responsible for metastasis to specific organs (e.g., bone marrow, lungs).45 Antagonists of CXCR4 have recently been shown to limit the extent of pulmonary melanoma metastasis.46 SDF-1 is also a chemoattractant for lymphocytes and monocytes. Transfection of B16 melanoma with SDF-1 results in the rejection of tumors, implying that SDF-1 production is finely balanced between angiogenesis and proinflammatory responses.47 Expression of CXCR4 was not detected by RT-PCR in B16F10 (results not shown). This suggests that this cell line exploits the SDF-1 gradient to attract and stimulate the growth of progenitor/endothelial cells, rather than to utilize an autocrine growth pathway.48 The upregulation of aminopeptidase N (CD13) was of considerable interest. This broad-specificity protease is involved in digestion, chemokine regulation, antigen presentation, and angiogenesis.49 Expression of APN/CD13 has been previously documented in melanoma where neutralizing antibodies were

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Figure 6. Regulation of APN/CD13, CD44, CD97, and SDF-1 expression in a panel of human melanoma cell lines. Q-PCR: Total RNA was prepared from a panel of five human melanoma cell lines cultured under hypoxic or normoxic conditions. Firststrand cDNA synthesis, primer design, and SYBR green Q-PCR analysis were performed as described in the Experimental Procedures. Results are presented as fold changes in mRNA abundance after hypoxia. FACS: Fixed and permeabilized cells were prepared and stained as described previously. Results are shown as percentage changes in FL1 fluorescence of cells under hypoxic conditions relative to control values. Representative immunocytochemical (ICC) analysis is also shown for each monoclonal antibody.

shown to restrict melanoma cell invasiveness by inhibiting type IV collagen degradation.50,51 In addition, the aminoprotease inhibitor bestatin prevents melanoma angiogenesis in an APN/ CD13-dependent fashion.52 In light of this evidence we speculate that APN/CD13 may also contribute toward the “vasculogenic mimicry” phenomenon observed in B16F10.53 The reported ability of APN/CD13 to activate type IV collagen degradation is intriguing given that expression of MMP9, a type IV collagenase, was also elevated in this proteome.50,51 Expression of MMP9 has been linked to tumor progression in B16F10 xenografts and human melanomas.54,55 The largest increase in mRNA levels in the entire study (36.3-fold) was seen for carbonic anhydrase IX (CAIX). Hypoxia-associated increases in CAIX expression have been observed in a wide range of malignancies.56 This membrane-bound enzyme catalyzes the formation of carbonic acid from H2O and CO2, resulting in acidification of the extracellular space. Surprisingly, the 18O/ 16 O ratio for CAIX only increased to 1.89 and expression of the other carbonic anhydrases (CAIV and CAXIV) was not significantly altered. To further the potential clinical relevance of these results, a panel of human melanoma lines (LOX, M14, MALME3M, SKMEL1, and UACC62) was analyzed at the cellular and mRNA levels to determine whether the regulation seen in B16F10 was consistent with human samples (Figure 6). In common with B16F10, expression of APN/CD13 and SDF-1 was markedly elevated in the majority of the cell lines. However, two targets Journal of Proteome Research • Vol. 5, No. 11, 2006 3005

research articles that were observed to have “neutral” regulation in B16F10, CD44 and CD97, were both downregulated in human samples. The hyaluronic acid receptor CD44 plays an important role in tumor growth and progression and the control of cell death.57 Negative regulation of CD44 by hypoxia has been reported in melanoma cell lines.40 In addition, reduced CD44 expression is recognized as a negative prognostic indicator in several tumors, including cutaneous melanoma.58,59 Therefore, it was surprising that downregulation in CD44 was seen in human lines and not in B16F10. The recently characterized seven transmembrane domain protein CD97 binds both CD55/DAF and integrins and is implicated in leukocyte migration, inflammation, and angiogenesis.60,61 In thyroid and colorectal cancers expression of CD97 is correlated with disease severity.62,63 Therefore, neutral regulation of CD97 in B16F10 and downregulation in human melanoma lines during hypoxia would appear at odds with the emerging biological role. Taken together, the results for CD44 and CD97 highlight the need for wider validation prior to drawing broad mechanistic conclusions. In summary, this extended analysis was able to confirm that increases in APN/CD13 and SDF-1 expression were “universal” to the hypoxic response in melanoma.

Conclusions In this investigation, comparative proteomic profiling of plasma membrane proteins from hypoxic and normoxic B16F10 melanoma cells was undertaken. This work reveals significant hypoxia-associated changes in the expression of functionally diverse proteins. The extent of these changes was largely supported by quantitative RT-PCR and antibody-based validation. Adaptations to hypoxia in B16F10 appear primarily concerned with increasing ATP conservation, acidification of the extracellular space, basement membrane degradation, and the establishment of proangiogenic chemotactic gradients. Extending analysis to a panel of hypoxia-adapted human melanoma lines confirmed upregulation of two proteins, APN/ CD13 and SDF-1. These results, combined with an emerging role in cancer pathogenesis, support the continued evaluation of APN/CD13 and CXCR4 antagonists as melanoma therapeutics.46,52 Finally, it is hoped that the large pool of uncharacterized protein identifications will provide a basis for the discovery of novel melanoma antigens and hypoxia-regulated proteins.

Acknowledgment. This project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. NO1-CO-12400. This research was supported (in part) by the Developmental Therapeutics Program in the Division of Cancer Treatment and Diagnosis of the National Cancer Institute. The content of this paper does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. Supporting Information Available: List of unique proteins in plasma membrane of hypoxia-adapted B16F10 identified/quantified by at least two different differentially 16O/ 18 O-labeled peptides. This material is available free of charge via the Internet at http://pubs.acs.org. References (1) Ruas, J. L.; Poellinger, L. Semin. Cell Dev. Biol. 2005, 16, 514522.

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Stockwin et al. (2) Harris, A. L. Nat. Rev. Cancer 2002, 2, 38-47. (3) Koong, A. C.; Denko, N. C.; Hudson, K. M.; Schindler, C.; Swiersz, L.; Koch, C.; Evans, S.; Ibrahim, H.; Le, Q. T.; Terris, D. J.; Giaccia, A. J. Cancer Res. 2000, 60, 883-887. (4) Denko, N. C.; Fontana, L. A.; Hudson, K. M.; Sutphin, P. D.; Raychaudhuri, S.; Altman, R.; Giaccia, A. J. Oncogene 2003, 22, 5907-5914. (5) Vaupel, P.; Thews, O.; Hoeckel, M. Med. Oncol. 2001, 18, 243259. (6) Graeber, T. G.; Osmanian, C.; Jacks, T.; Housman, D. E.; Koch, C. J.; Lowe, S. W.; Giaccia, A. J. Nature 1996, 379, 88-91. (7) Brizel, D. M.; Scully, S. P.; Harrelson, J. M.; Layfield, L. J.; Bean, J. M.; Prosnitz, L. R.; Dewhirst, M. W. Cancer Res. 1996, 56, 941943. (8) Stratford, I. J.; Adams, G. E.; Bremner, J. C.; Cole, S.; Edwards, H. S.; Robertson, N.; Wood, P. J. Int. J. Radiat. Biol. 1994, 65, 8594. (9) Hockel, M.; Schlenger, K.; Aral, B.; Mitze, M.; Schaffer, U.; Vaupel, P. Cancer Res. 1996, 56, 4509-4515. (10) Nordsmark, M.; Hoyer, M.; Keller, J.; Nielsen, O. S.; Jensen, O. M.; Overgaard, J. Int. J. Radiat. Oncol. Biol. Phys. 1996, 35, 701708. (11) Mabjeesh, N. J.; Post, D. E.; Willard, M. T.; Kaur, B.; Van Meir, E. G.; Simons, J. W.; Zhong, H. Cancer Res. 2002, 62, 2478-2482. (12) Temes, E.; Martin-Puig, S.; Acosta-Iborra, B.; Castellanos, M. C.; Feijoo-Cuaresma, M.; Olmos, G.; Aragones, J.; Landazuri, M. O. J. Biol. Chem. 2005, 280, 24238-24244. (13) Scandurro, A. B.; Weldon, C. W.; Figueroa, Y. G.; Alam, J.; Beckman, B. S. Int. J. Oncol. 2001, 19, 129-135. (14) Thongboonkerd, V.; Gozal, E.; Sachleben, L. R., Jr.; Arthur, J. M.; Pierce, W. M.; Cai, J.; Chao, J.; Bader, M.; Pesquero, J. B.; Gozal, D.; Klein, J. B. J. Biol. Chem. 2002, 277, 34708-34716. (15) Manalo, D. J.; Rowan, A.; Lavoie, T.; Natarajan, L.; Kelly, B. D.; Ye, S. Q.; Garcia, J. G.; Semenza, G. L. Blood 2005, 105, 659-669. (16) Santoni, V.; Molloy, M.; Rabilloud, T. Electrophoresis 2000, 21, 1054-1070. (17) Washburn, M. P.; Wolters, D.; Yates, J. R., III. Nat. Biotechnol. 2001, 19, 242-247. (18) Blonder, J.; Terunuma, A.; Conrads, T. P.; Chan, K. C.; Yee, C.; Lucas, D. A.; Schaefer, C. F.; Yu, L. R.; Issaq, H. J.; Veenstra, T. D.; Vogel, J. C. J. Invest. Dermatol. 2004, 123, 691-699. (19) Nielsen, P. A.; Olsen, J. V.; Podtelejnikov, A. V.; Andersen, J. R.; Mann, M.; Wisniewski, J. R. Mol. Cell Proteomics 2005, 4, 402408. (20) Watarai, H.; Hinohara, A.; Nagafune, J.; Nakayama, T.; Taniguchi, M.; Yamaguchi, Y. Proteomics 2005. (21) Wu, C. C.; Yates, J. R., III. Nat. Biotechnol. 2003, 21, 262-267. (22) Blonder, J.; Conrads, T. P.; Veenstra, T. D. Expert Rev. Proteomics 2004, 1, 153-163. (23) Tao, W. A.; Aebersold, R. Curr. Opin. Biotechnol. 2003, 14, 110118. (24) Koller, A.; Washburn, M. P.; Lange, B. M.; Andon, N. L.; Deciu, C.; Haynes, P. A.; Hays, L.; Schieltz, D.; Ulaszek, R.; Wei, J.; Wolters, D.; Yates, J. R., III. Proc. Natl. Acad. Sci. U.S.A. 2002, 99, 11969-11974. (25) Rybak, S. M.; Sanovich, E.; Hollingshead, M. G.; Borgel, S. D.; Newton, D. L.; Melillo, G.; Kong, D.; Kaur, G.; Sausville, E. A. Cancer Res. 2003, 63, 2812-2819. (26) Schnolzer, M.; Jedrzejewski, P.; Lehmann, W. D. Electrophoresis 1996, 17, 945-953. (27) Yao, X.; Afonso, C.; Fenselau, C. J. Proteome Res. 2003, 2, 147152. (28) Blonder, J.; Hale, M. L.; Chan, K. C.; Yu, L. R.; Lucas, D. A.; Conrads, T. P.; Zhou, M.; Popoff, M. R.; Issaq, H. J.; Stiles, B. G.; Veenstra, T. D. J. Proteome Res. 2005, 4, 523-531. (29) Arteel, G. E.; Thurman, R. G.; Yates, J. M.; Raleigh, J. A. Br. J. Cancer 1995, 72, 889-895. (30) Blonder, J.; Conrads, T. P.; Yu, L. R.; Terunuma, A.; Janini, G. M.; Issaq, H. J.; Vogel, J. C.; Veenstra, T. D. Proteomics 2004, 4, 3145. (31) Peng, J.; Elias, J. E.; Thoreen, C. C.; Licklider, L. J.; Gygi, S. P. J Proteome Res. 2003, 2, 43-50. (32) Wallin, E.; von Heijne, G. Protein Sci. 1998, 7, 1029-1038. (33) Hood, B. L.; Zhou, M.; Chan, K. C.; Lucas, D. A.; Kim, G. J.; Issaq, H. J.; Veenstra, T. D.; Conrads, T. P. J. Proteome Res. 2005, 4, 1561-1568. (34) Conrads, K. A.; Yu, L. R.; Lucas, D. A.; Zhou, M.; Chan, K. C.; Simpson, K. A.; Schaefer, C. F.; Issaq, H. J.; Veenstra, T. D.; Beck, G. R., Jr.; Conrads, T. P. Electrophoresis 2004, 25, 1342-1352. (35) Gygi, S. P.; Rochon, Y.; Franza, B. R.; Aebersold, R. Mol. Cell Biol. 1999, 19, 1720-1730.

research articles

Proteomic Analysis of Plasma Membrane from Melanoma (36) Baker, M. A.; Lane, D. J.; Ly, J. D.; De Pinto, V.; Lawen, A. J. Biol. Chem. 2004, 279, 4811-4819. (37) Kim, B. W.; Choo, H. J.; Lee, J. W.; Kim, J. H.; Ko, Y. G. Exp. Mol. Med. 2004, 36, 476-485. (38) Malinowska, D. H.; Koelz, H. R.; Hersey, S. J.; Sachs, G. Proc. Natl. Acad. Sci. U.S.A. 1981, 78, 5908-5912. (39) Cuvier, C.; Jang, A.; Hill, R. P. Clin. Exp. Metastasis 1997, 15, 1925. (40) Hasan, N. M.; Adams, G. E.; Joiner, M. C.; Marshall, J. F.; Hart, I. R. Br. J. Cancer 1998, 77, 1799-1805. (41) Johnson, J. P.; Rummel, M. M.; Rothbacher, U.; Sers, C. Curr. Top. Microbiol. Immunol. 1996, 213 (Part 1), 95-105. (42) Neuhaus, T.; Stier, S.; Totzke, G.; Gruenewald, E.; Fronhoffs, S.; Sachinidis, A.; Vetter, H.; Ko, Y. D. Cell Prolif. 2003, 36, 75-86. (43) Ceradini, D. J.; Kulkarni, A. R.; Callaghan, M. J.; Tepper, O. M.; Bastidas, N.; Kleinman, M. E.; Capla, J. M.; Galiano, R. D.; Levine, J. P.; Gurtner, G. C. Nat. Med. 2004, 10, 858-864. (44) Peled, A.; Grabovsky, V.; Habler, L.; Sandbank, J.; ArenzanaSeisdedos, F.; Petit, I.; Ben-Hur, H.; Lapidot, T.; Alon, R. J. Clin. Invest. 1999, 104, 1199-1211. (45) Libura, J.; Drukala, J.; Majka, M.; Tomescu, O.; Navenot, J. M.; Kucia, M.; Marquez, L.; Peiper, S. C.; Barr, F. G.; JanowskaWieczorek, A.; Ratajczak, M. Z. Blood 2002, 100, 2597-2606. (46) Takenaga, M.; Tamamura, H.; Hiramatsu, K.; Nakamura, N.; Yamaguchi, Y.; Kitagawa, A.; Kawai, S.; Nakashima, H.; Fujii, N.; Igarashi, R. Biochem. Biophys. Res. Commun. 2004, 320, 226232. (47) Dunussi-Joannopoulos, K.; Zuberek, K.; Runyon, K.; Hawley, R. G.; Wong, A.; Erickson, J.; Herrmann, S.; Leonard, J. P. Blood 2002, 100, 1551-1558. (48) Porcile, C.; Bajetto, A.; Barbero, S.; Pirani, P.; Schettini, G. Ann. N. Y. Acad. Sci. 2004, 1030, 162-169. (49) Sjostrom, H.; Noren, O.; Olsen, J. Adv. Exp. Med. Biol. 2000, 477, 25-34.

(50) Saiki, I.; Fujii, H.; Yoneda, J.; Abe, F.; Nakajima, M.; Tsuruo, T.; Azuma, I. Int. J. Cancer 1993, 54, 137-143. (51) Tsushima, H.; Hopsu-Havu, V. K. Neoplasma 1990, 37, 415-425. (52) Aozuka, Y.; Koizumi, K.; Saitoh, Y.; Ueda, Y.; Sakurai, H.; Saiki, I. Cancer Lett. 2004, 216, 35-42. (53) Bhagwat, S. V.; Lahdenranta, J.; Giordano, R.; Arap, W.; Pasqualini, R.; Shapiro, L. H. Blood 2001, 97, 652-659. (54) Zhao, W.; Liu, H.; Xu, S.; Entschladen, F.; Niggemann, B.; Zanker, K. S.; Han, R. Cancer Lett. 2001, 162 Suppl, S49-S55. (55) Nikkola, J.; Vihinen, P.; Vuoristo, M. S.; Kellokumpu-Lehtinen, P.; Kahari, V. M.; Pyrhonen, S. Clin. Cancer Res. 2005, 11, 51585166. (56) Robertson, N.; Potter, C.; Harris, A. L. Cancer Res. 2004, 64, 61606165. (57) Marhaba, R.; Zoller, M. J. Mol. Histol. 2004, 35, 211-231. (58) Karjalainen, J. M.; Tammi, R. H.; Tammi, M. I.; Eskelinen, M. J.; Agren, U. M.; Parkkinen, J. J.; Alhava, E. M.; Kosma, V. M. Am. J. Pathol. 2000, 157, 957-965. (59) Esteban, F.; Bravo, J. J.; Gonzalez-Moles, M. A.; Bravo, M.; RuizAvila, I.; Gil-Montoya, J. A. Anticancer Res. 2005, 25, 1115-1121. (60) Wang, T.; Ward, Y.; Tian, L.; Lake, R.; Guedez, L.; StetlerStevenson, W. G.; Kelly, K. Blood 2004. (61) Leemans, J. C.; te Velde, A. A.; Florquin, S.; Bennink, R. J.; de Bruin, K.; van Lier, R. A.; van der Poll, T.; Hamann, J. J. Immunol. 2004, 172, 1125-1131. (62) Steinert, M.; Wobus, M.; Boltze, C.; Schutz, A.; Wahlbuhl, M.; Hamann, J.; Aust, G. Am. J. Pathol. 2002, 161, 1657-1667. (63) Mustafa, T.; Klonisch, T.; Hombach-Klonisch, S.; Kehlen, A.; Schmutzler, C.; Koehrle, J.; Gimm, O.; Dralle, H.; Hoang-Vu, C. Int. J. Oncol. 2004, 24, 285-294.

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