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Jan 14, 2011 - Hunting for Protein Markers of Hypoxia by Combining Plasma Membrane Enrichment with a New Approach to Membrane Protein Analysis...
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Hunting for Protein Markers of Hypoxia by Combining Plasma Membrane Enrichment with a New Approach to Membrane Protein Analysis  † Paolo Cifani,†,# Maria Bendz,‡,# Kristofer Warell, Karin Hansson,† Fredrik Levander,† Marianne Sandin,†  § || ,|| Morten Krogh, Marie Ovenberger, Erik Fredlund,|| Marica Vaapil,|| Alexander Pietras,|| Sven Pahlman,* ,† and Peter James* †

Department of Immunotechnology, CREATE Health, Lund University, Sweden Centre for Biomembrane Research, Department of Biochemistry and Biophysics, Stockholm University, Sweden § Department Computational Biology and Biological Physics, Department of Theoretical Physics, Lund University, Sweden Department of Laboratory Medicine, Centre for Molecular Pathology, University Hospital MAS, Malm€o, CREATE Health, Lund University, Sweden

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‡

bS Supporting Information ABSTRACT: Nontransient hypoxia is strongly associated with malignant lesions, resulting in aggressive behavior and resistance to treatment. We present an analysis of mRNA and protein expression changes in neuroblastoma cell lines occurring upon the transition from normoxia to hypoxia. The correlation between mRNA and protein level changes was poor, although some known hypoxia-driven genes and proteins correlated well. We present previously undescribed membrane proteins expressed under hypoxic conditions that are candidates for evaluation as biomarkers. KEYWORDS: isotopic labeling, HPLC-MS, 2D-PAGE, plasma membrane, protein expression, mRNA expression, correlation, hypoxia, normoxia, neuroblastoma

’ INTRODUCTION Solid tumors cannot grow larger than a few millimeters in diameter before they need to attract blood vessels to the supply of oxygen and nutrients.1-4 One of the major mechanisms behind tumor angiogenesis is the gradient of oxygen shortage occurring in poorly vascularized tumor areas as a consequence of oxygen consumption by dividing tumor cells. In response to hypoxia, cells alter their gene expression by activation of hypoxia-inducible factors HIF-1 and HIF-2. These proteins are heterodimeric transcription factors consisting of distinct R subunits that degrade quickly under normoxic conditions, but are stabilized under low oxygen conditions and form transcriptionally active complexes with the ARNT proteins.5 These complexes trigger expression of genes involved in anaerobic metabolism, oxygen transport and angiogenesis. The tumor-induced vessels are often structurally abnormal resulting in poor circulation maintaining an overall hypoxic microenvironment and creating a selective pressure for tumor cells that can survive and proliferate under low oxygen conditions. This promotes an increase in cells showing aggressive growth, genetic instability, dedifferentiation and metastatic growth as well as insensitivity to ionizing radiation and cytotoxic drugs.6 Neuroblastoma is a childhood malignancy that originates from the sympathetic nervous system and tumor cells retain many characteristics from developing cells of this system, often r 2011 American Chemical Society

including neural crest traits.7,6,8,9 Previously, we have shown that cultured neuroblastoma cells grown at hypoxia develop an immature, stem cell-like phenotype.6 Clinically, immature neuroblastomas are more aggressive than more highly differentiatated tumors,10 suggesting that the hypoxia-driven change in phenotype results in more aggressive tumor cells and that proteins with increased expression at hypoxia may have the potential as treatment targets. In this study, we focus on soluble and membrane protein expression in two neuroblastoma cell lines and how these and their corresponding mRNAs change upon the transition from normoxia to prolonged hypoxia. We used a 2D-PAGE DIGE approach to analyze the soluble protein fraction.11,12 For the membrane proteins from an enriched plasma membrane fraction, we used HPLC-MS approach that we have recently described which combines digestion with a lowspecificity protease with isotopic labeling using a fragmentationdirecting reagent.13,14 We analyze the correlation between the protein results and changes in mRNA expression levels. Since most solid tumors are poorly oxygenated and virtually anoxic in localized areas, a substantial fraction of tumor cells expresses a hypoxic phenotype that is poorly treatable. Several hypoxia Received: September 27, 2010 Published: January 14, 2011 1645

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Journal of Proteome Research markers have been proposed mostly from gene expression studies,15 but none of these have so far proved clinically applicable. This situation is largely tumor-specific and one of our aims was to identify hypoxia induced cell-surface proteins that could be used as markers for hypoxic tissue and targets for antibodybased visualization and/or treatment.

’ MATERIALS AND METHODS Materials

Nicotinic acid, triethylammonium bicarbonate buffer, urea, magnesium acetate, acetonitrile, acrylamide, sodium hydroxide, iodoacetamide, R-cyano-4-hydroxycinnamic acid, N-methyl-piperidine, Protein Assay Kit and solvents for the synthesis of the isotopic labels and HPLC were purchased from Sigma-Aldrich (Stockholm, Sweden). Dithiothreitol (DTT) and Gel-code blue were purchased from Pierce (SDS, Falkenberg, Sweden). Proteinase-K was purchased from Promega (SDS, Falkenberg, Sweden). d4-Nicotinic acid ethyl ester was purchased from Cambridge Isotope Laboratories (Larodan Fine Chemical AB, Malmo, Sweden). CyDyes (Cy2, Cy3, Cy5), immobilized pH gradient strips and pH 4-7 IPG buffer, CHAPS and SDS were purchased from GE Healthcare (Uppsala, Sweden). The synthesis of 1-(nicotinoyloxy) succinimide ester in both light and heavy forms was carried out as described previously.14 Complete Protease Inhibitor mix was from Roche Molecular Biochemicals (Mannheim, Germany). Cell Culture and Hypoxic Treatment

The neuroblastoma cell lines SK-N-BE(2)c and IMR-32 were grown in minimal essential medium with Earle’s salts and Lglutamine, at 37 °C in a 5% CO2/95% air humidified incubator. The medium was supplemented with 10% fetal bovine serum, penicillin (100 IU/mL), and streptomycin (100 μg/mL). Growth medium was obtained from Sigma, St. Louis, MO, and the supplements from Invitrogen, Paisley, U.K. During hypoxic treatment, cells were grown at 37 °C in a Hypoxia workstation 400 (Ruskinn Technology) connected to a Ruskinn gas mixer module, at 1% O2 for 72 h. Before harvesting, the cells were washed in a solution, equilibrated under hypoxic conditions, containing 5 mM Hepes/250 mM sucrose to minimize the salt content of the subsequent cell extractions. Sample Preparation for 2D-DIGE Analyses

Cell pellets were resuspended in lysis buffer, containing 8 M urea, 30 mM Tris, 5 mM magnesium acetate, and 4% (m/v) chaps, pH 8.5. Samples were vortexed for 5 min, followed by vigorous pipetting. Duplicate samples were used for determination of protein concentration according to manufacturer’s protocol. Two technical replicates of 50 μg protein were prepared from each of the triplicate biological samples using dye swapping of the hypoxic and normoxic samples. Each was labeled according to manufacturer’s protocol with Cy3 and Cy5, 240 pmol dye per 50 μg of protein. Equal amounts of proteins from each sample were mixed to form a pool that was labeled with Cy2 in the same manner. Labeled samples were combined with an equal protein amount from the pool and mixed with rehydration buffer, containing 8 M urea, 2% (w/v) chaps, a trace of bromophenol blue, 18.2 mM DTT, and 0.5% (v/v) IPG buffer (pH 4-7). The sample was left to incubate for 30 min at room temperature and centrifuged for 10 min at 13 000 rpm. Each combined sample was applied to a 24 cm immobilized pH gradient strip (pH 4-7) for overnight rehydration. Sample duplicates were run on different

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gels, in presence of the pool, in order to reduce possible systematic errors of single gel preparations. 2D-DIGE Separation and Image Analysis

First-dimension isoelectric focusing was carried out on an Amersham Biosciences IPG-Phor according to manufacturer’s instructions, for a total focusing time of 67 kVh. Strips were equilibrated twice in 12 mL of equilibration solution (6 M urea, 75 mM Tris, 30% (w/v) glycerol, and 2% (w/v) SDS). The first equilibration was carried out for 20 min with 65 mM DTT added. The second equilibration was for 25 min with 135 mM iodoacetamide. The IPG strips were loaded and run on a 12.5% SDS polyacrylamide gel at 25 °C with 1 W/gel overnight, raised to 10 W/gel next morning until the bromophenol blue front ran off the base of the gel. Gels were fixed in 30% ethanol and 10% acetic acid for 30 min and then rinsed and kept in water. Gels were scanned at 100-μm resolution using an Amersham Biosciences Typhoon 9400 variable imager and the robotic equipment described previously.16,17 Spot detection, gel matching and statistical analysis were performed with DeCyder 6.0 (Amersham Biosciences). Each gel resulted in three images, one for the normoxic sample, one for the hypoxic and one for the pool. The pooled samples were used as internal standards, and all intergel matching was made via images from the standard. Automatic spot detection was done in DeCyder DIA, followed by filtering of spots in each gel image to remove those that obviously originated from dust particles and gel artifacts. After filtering, all images contained around 2000 protein spots. Automatic gel image matching in Decyder BVA was supplemented by manual addition of around 100 landmarks to guide the matching algorithm in subsequent rematching attempts. Landmarks were added primarily near the edges and in areas with many spots. Proteins split into separate spots by the spot detection algorithm were manually merged during this process. Statistical Analysis

A merged set of values from the averaged values of the dyeswap corrected samples was used for analysis. When one of the two values was missing, the available measurement was used. When both values were missing, the sample was assigned a missing value for that spot.18 SA is defined as the ratio between the spot volume of the sample and the volume of the corresponding reference spot on the same gel. A set of matched spots across all gel images, from here on called a matched spot set, would typically represent an isoform of a protein, but in rarer cases, it represents two or more unseparated proteins. Expression values of matched spots were compared between treatment group and control group, so that to each spot a score of relative significant difference, in term of p-value, could be assigned performing a statistical analysis. All spots that satisfied both following criteria in any pairwise comparison between the treatment group and the control group were selected for mass spectrometry analysis: fold change between treated and control groups 1.20, and Mann-Whitney U-test p-value below 0.05. The software used for the statistical tests was written in the statistical language R. Mass Spectrometry Analysis of 2D-PAGE Spots

Proteins were identified by either peptide fingerprinting or LC-MS/MS from spots digested from preparative gels run with 700 μg of protein loaded and stained with ruthenium bathrenolate.19 The spot picking, destaining, digestion, extraction, sample preparation, and spotting on MALDI target plates were carried out using a robotic system (ETTAN Spot handling 1646

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Journal of Proteome Research workstation, GE Healthcare) and a standard protocol provided by the manufacturer. An aliquot of 0.5 μL of a tryptic digest originating from each picked spot was applied to a clean MALDI target slide surface and allowed to dry. A total of 0.5 μL of matrix solution (5 mg/mL of R-cyano-4-hydroxy-cinnamic acid in 50% acetonitrile containing 0.05% TFA) and another 0.5 μL of sample were added. When the samples had dried, they were analyzed using a MALDI micro MX mass spectrometer (Waters, Manchester, U.K.). The resulting spectra were search against the nonredundant IPI human database version 2.3020 using Piums software21 as described by Bengtsson et al.22 The protein spots that were not identified by protein mass fingerprinting were then analyzed by MS/MS using a QTof Ultima API (Waters, Manchester, U.K.) coupled to a CapLC HPLC. The digests were separated on a reversed-phase analytical column (Atlantis, C18, 75 μm  150 mm, 3 μm, 100 Å, Waters) using an 80 min linear gradient. Dynamic data acquisition scanning was used over the mass range m/z from 50 to 1900 for both MS and MS/MS. Only spectra from ions with charge state 2 and 3 were acquired. Preparation of Enriched Plasma Membrane Fractions by Two-Phase Partitioning

Cells were collected from 35 subconfluent culture dishes (Ø8.5 cm) of cell line SK-N-BE(2)c and scraped off into icecold PBS supplemented with protease-inhibitors. After centrifugation (500 g, 4 °C, 5 min), cells were resuspended in hypotonic buffer for 15 min on ice and centrifuged as above. All the subsequent enrichment procedures were carried out at 4 °C, all solutions were prechilled before use and the two-phase systems were supplemented with protease inhibitors. The cell pellet was resuspended and homogenized in a Dounce homogenizer in the first two-phase system (5.7% (w/w) PEG 3350, 5.7% (w/w) Dextran T500, and 15 mM Tris/H2SO4, pH 7.8).23 The homogenate was centrifuged as above to remove intact cells and to achieve efficient phase separation. The PEG-rich top-phase was collected and the dextran-rich bottom phase was re-extracted with fresh top-phase from a second two-phase system (5.7% (w/w) PEG 3350, 5.7% (w/w) Dextran T500, and 15 mM Tris/ H2SO4, pH 7.8). Both PEG-phases were combined and subjected to affinity partitioning with a WGA-based bottom phase (PEG 3350, 6.0% (w/w) Dextran T500, 300 μg WGA-Dextran, 15 mM Tris borate, pH 7.8)). After mixing and centrifugation as above, the top phase was removed and the bottom phase was reextracted with a fresh top phase from a 5 g system (6.0% (w/w) PEG 3350, 6.0% (w/w) Dextran T500, 15 mM Tris borate, pH 7.8). The final bottom phase was collected, diluted 10 times with 0.1 M N-acetyl-glucosamine in 5 mM Tris/HCl, pH 8.0, 0.25 M sucrose, to dissociate plasma membrane proteins from WGA, and plasma membranes were recovered by centrifugation at 100 000g for 90 min. The resulting pellet was homogenized in 5 mM Tris/HCl, pH 8.0, 0.25 M sucrose. 50 -Nucleotidase Assay

The assay was performed essentially as described by Avruch and Wallach.24 Briefly, samples from each top and bottom phase were allowed to react with 3H-AMP and MgCl2 for 5 min at 37 °C. The reaction was stopped by addition of ZnSO4 and remaining nonreacted 3H-AMP was precipitated with BaSO4. The samples were centrifuged and the upper solution was transferred to scintillation vials containing scintillation liquid. 3 H-activity was measured with a beta-counter and the specific activity was calculated as counts per minute (cpm) per milligrams of protein.

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Membrane Protein Separation

The membrane-enriched fraction was left to thaw on ice before centrifugation at 48 000g for 40 min. The membrane pellet was washed once with ice-cold 10 mM sodium carbonate buffer, pH 11, once with ice-cold H2O, and finally twice with 10 mM Tris buffer, pH 7 (between each wash, membranes were pelleted by centrifugation at 48 000g for 40 min at 4 °C). After the final centrifugation, the pellet was resuspended in 10 mM Tris buffer, pH 7.0, and protein concentration was determined using Protein Assay Kit (Sigma Diagnostics). Two aliquots from each growth condition, each containing 50 μg of protein, were mixed 1:1 with Laemmli sample buffer and heated at 98 °C for 3 min. Samples were separated on a 12.5% SDS-PAGE gel with a 5% stacking gel at 25 °C using 25 A/gel until the bromophenol blue dye front had run off the base of the gel. The gel was stained using GelCode Blue Stain Reagent (Pierce). Each lane was cut into 11 slices. The slices were destained in 50% acetonitrile and 25 mM NH4HCO3 before reduction with 10 mM DTT in 100 mM NH4HCO3 at 55 °C for 1 h. Alkylation was performed by adding 55 mM iodoacetamide in 100 mM NH4HCO3 to each sample and incubating for 45 min at room temperature in the dark. The slices were then washed once using first 100 mM NH4HCO3, then once with acetonitrile, then two times using H2O, and then a final wash/shrinkage in acetonitrile. Enzymatic Digestion and Peptide Labeling

The quantitative analysis of membrane proteins was carried out in a similar fashion to that previously described.13,14 Twentyfive microliters of Proteinase K (0.64 μg/mL of Proteinase K in 100 mM sodium carbonate buffer, pH 12) was added to the dehydrated gel slice after the acetonitrile wash and the digestion was carried out at 37 °C for 3 h before a second aliquot of enzyme was added and the digestion continued for another 1.5 h. The peptides were extracted twice from the gel by adding 0.1 M HCl in 75% acetonitrile to the slices and incubating at room temperature for 30 min. The samples were concentrated almost to dryness in a Speed-Vac before addition of 20 μL of 200 mM triethylammonium bicarbonate buffer, pH 7. The pH of the samples was adjusted using 6 M NaOH. Ninety percent of the hypoxic cell digest and 10% of the normoxic cell digest were separately modified by adding prechilled 200 mM H4NicNHS dissolved in dimethylformamide (DMF) to a final concentration of 20 mM. Similarly, 10% of the hypoxic cell digest and 90% of the normoxic cell digest were separately modified using D4NicNHS dissolved in dimethylformamide (DMF). The reactions were carried out for 1 h on ice. Then, 90% of the H4 hypoxic digest was mixed with the 10% D4 modified hypoxic digest. Similarly 90% of the D4 normoxic digest was pooled with 10% of the H4 normoxic digest. The side products caused by Ser, Thr and Tyr forming esters were eliminated by treating the samples with 1 μL of 600 μM hydroxylamine in 25 mM Tris buffer, pH 8.5, for 20 min at room temperature. Then, the pH was increased to 11-12 by adding 6 M NaOH and the incubation carried on for 20 min at room temperature. The H4 and D4 samples were pooled and then the pH was decreased to >3 by adding 12 M HCl. HPLC-MS Analysis of the Proteinase-K Digests

Samples were analyzed on a QTOF Ultima API mass spectrometer (Waters, Manchester, U.K.) coupled to a Waters CapLC HPLC. The autosampler injected 6 μL of sample and the peptides were trapped on a precolumn (C18, 300 μm  5 mm, 5 μm, 100 Å, LC-Packings), and separated on a reversed 1647

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Journal of Proteome Research phase analytical column (Atlantis, C18, 75 μm  150 mm, 3 μm, 100 Å, Waters). The flow rate was 200 nL/min. Solvent A consisted of 2% acetonitrile, 98% water with 0.1% formic acid. Solvent B consisted of 90% acetonitrile, 10% Water and 0.1% formic acid. The HPLC method started at 5% B for 18 min, then was raised from 5% to 80% B over 57 min, from 80% to 100% B over 1 min, hold at 100% B for 25 min before reducing from 80% to 5% B in 1 min and re-equilibrating at 5% B for 15 min. The total run time was 115 min. Each sample (three biological replicates of cell line SK-N-BE(2)c) was analyzed three times each. Data Analysis of the Labeled Membrane Protein Derived Peptides

Q-TOF raw data files were converted to mzXML format using the program Wolf (http://sashimi.sourceforge.net). Peak features were extracted using msInspect (build 6584). The output peak lists, which include maximum peak intensities, charge states and apex retention times, were analyzed using MsInspect PairFinder as a plug-in to Proteios 2 (http://www.proteios.org).25 Using the plug-in, each peak list was searched for multiply charged peptide pairs that differed by 4 Da with a tolerance of (0.05 Da, and with apex retention times that differed less than 30 s. Peaks that differed in intensity by at least 20% were put into an include list for MS/MS acquisition. Singly charged peaks were also included if they had a mass of at least 600. Two include lists were generated for the multiply charged ions in each run, one in which the lower mass peaks were more abundant, and one in which the high mass peaks of the pairs were more intense. Finally, a third include list was generated for low intensity multiply charged doublet ions for which one of the doublet was not clearly visible due to the noise level and also including singly charged peaks with a mass of at least 600. Thus all ions scheduled for MS/ MS analysis were from proteins changing in protein expression levels. Analysis of the MS/MS Spectra

Database searches were done using MASCOT (version 2.2), XTandem!26 and PEAKS27 with a parent mass tolerance of 0.1 Da and a fragment tolerance of 0.1 Da against the nonredundant IPI human database version 3.52. For tryptic digestions of 2D gel spots, one missed cleavage was allowed, and searches were performed with fixed carbamidomethylation of cysteines and variable oxidation of methionine residues. For membrane protein digests, the data was analyzed with enzyme set to none. The H4/ D4 NicNHS modification at the N-terminal and the iodoacetamide Cysteine derivative were used as fixed modifications while the H4/D4 NicNHS on Lys epsilon amino groups and methionine oxidation modifications were set to be variable. A false positive cutoff rate for proteins of 95% was used within Mascot. Confirmation of Membrane Protein Expression Changes by Multiple Reaction Monitoring

A duplicate set of biological replicates were obtained and the membranes isolated and the proteins digested and labeled with H4D4 NicNHS as described above. We chose to optimize a set of transitions for peptides from Aquaporin-3. The peptide MS/MS spectra used in the original LC-MS/MS experiments used to identify Aquaporin were manually interpreted and 3 transitions using b ions (since this carries the N-terminal isotopic label) were chosen for the D4 and H4 parents and the retention time window noted. The precursor-to-fragment ion transitions were tested by SRM measurements on a TSQ Vantage triple quadrupole mass

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spectrometer (Thermo Fisher) equipped with a nanoelectrospray ion source (Thermo Fisher). Chromatographic separations of peptides were performed on an Eksigent 1D NanoLC system (Eksigent technologies) using the same chromatographic conditions as described above for the Eksigent 2D NanoLC system. The LC was operated with a flow rate of 400 nL/min. The mass spectrometer was operated in MRM mode, with both Q1 and Q3 settings at unit resolution (fwhm 0.7 Da). A spray voltage of þ1700 V was used with a heated ion transfer setting of 270 °C for desolvation. Data were acquired using the Xcalibur software (version 2.1.0). The dwell time was set to 10 ms and the scan width to 0.01 m/z. All collision energies were calculated using the formula: CE = (Parent m/z)  0.034 þ 3.314. Microarray Analysis

Total RNA was prepared with Trizol reagent (Invitrogen) and hybridized to microarrays (27 000 unique clones) produced at the SCIBLU DNA Microarray Resource Centre, Lund University. Data analyses and statistical computations were performed using BASE,28 Perl (http://www.perl.org/), and R (http://www. r-project.org/). Data Availability

The microarray data has been deposited under the accession number E-MEXP-1374 in the ArrayExpress database (http:// www.ebi.ac.uk/microarray-as/ae/).

’ RESULTS General Overview of Protein Analysis Results

Soluble Protein Analysis. Human neuroblastoma cells were grown to semiconfluency at standard conditions (normoxia, i.e., atmospheric oxygen pressure, ca. 21% O2) and at 1% O2 for 72 h (prolonged hypoxia) as our intention was to mimic the situation of a poorly oxygenated solid tumor environment. Previous studies have shown that neuroblastoma cells grown for 72 h have developed a fairly stable hypoxic phenotype.29 2D-DIGE gels of the normoxic and hypoxic IMR-32 cells were run in biological triplicate and technical triplicate yielding around 2000 spots after filtering and editing. Spot intensity changes between the hypoxic/normoxic gel images were then subject to statistical analysis. The first step consisted of filtering spots to use only those present in at least two of the three technical replicates. Student’s t test was employed to identify spots/proteins whose expressions differ significantly between the normoxic and hypoxic samples. The experiment and analysis was repeated using a second neuroblastoma derived cell line, SK-N-BE(2)c. At p < 0.01, 99 proteins showed a similar significant expression difference in both cell lines (Supplementary Table 1a) and a further 44 were regulated in a different manner in the two cell lines (Supplementary Table 1b). Membrane Protein Analysis. The plasma membrane from the cell line SK-N-BE(2)c was purified by affinity-based twophase partitioning. This method utilizes the differences in surface properties rather than size and density, and separates membranes due to their different affinity for two immiscible aqueous polymer phases. We used two-phase systems consisting of polyethylene glycol (PEG) and dextran, with the top phase enriched in PEG and the bottom phase enriched in dextran. In this setting, a majority of all membranes are found in the top phase and a subsequent affinity partitioning with wheat-germ agglutinin (WGA)-coupled dextran was used to selectively bind plasma membranes (by affinity binding to the N-acetyl-glucosamine 1648

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Figure 1. Purification of plasma membranes. Panel A shows the general flow scheme of the two-phase partioning purification method. Panels B and C show the distribution of the plasma membrane marker 50 nucleotidase activity between the various fractions during the purification. Only the final pellet contains significant activity.

residues of cell surface glycoproteins). We used 50 -nucleotidase activity measurements to track the plasma membrane that was found almost entirely in the WGA fraction (Figure 1). The resultant membranes were then washed with sodium carbonate at pH 11 to remove most noncovalently bound proteins. The subsequent fractions containing highly enriched membrane (and some strongly membrane associated) proteins were separated by 1D-SDS-PAGE, digested using Proteinase-K, modified with light or heavy isotopic charge-fragmentation directing reagents and analyzed by mass spectroscopy to allow a relative quantitative analysis of the protein expression levels. A total of 388 membrane proteins were identified as defined by two independent membrane protein prediction algorithms, SOSUI and TMHMM. The confidence level cutoff chosen for protein identification was 95% though most of the proteins were identified at >99%. Thirty-four membrane proteins were identified as being differentially expressed between normoxic/hypoxic growth conditions (Supplementary Table 2). Fifteen proteins were found that were between 2 and 19 times more abundant under hypoxic stress (Supplementary Table 2a). In addition, 13 proteins were identified that were only induced under hypoxic conditions (Supplementary Table 2b) and six that were completely down-regulated (Supplementary Table 2c). Differences between Cell Lines. The differences in expression changes between the two cell lines appear to be caused by two main effects. First, there is a change in the phosphorylation states of many of the heat shock proteins leading to different spots changing intensity. This must reflect differences in the signaling pathways being used and may not be of functional importance. The other changes appear to be largely downregulation of proteins. This appears to be a result of dedifferentiation of specialized cells and reflects the different origins of the two cell lines. Protein Complex Analysis. We looked at the possibility of groups of proteins being involved in the adaptation to hypoxia.

We entered gene lists into the Gene Central Pro software system (SABiosciences, Frederick, MD) and searched for known and predicted protein complexes. The largest up-regulated group found consists of proteins involved in the maintenance of the nuclear envelope (Figure 2a). Interestingly, quite a few proteins involved in the regulation of mRNA by spliceosome activity are also up-regulated (Figure 2b). These Ser/Arg-rich alternative pre-mRNA splicing factors have recently been identified as receptors for carbohydrate structures that occur on the surface of cancer cells30 and involved in malignancy and metastasis (colonization factors). Proteins involved in Hif degradation, Proteasome subunits and ubiquitin thioesterases31 are found to be down-regulated under hypoxic conditions (Figure 2c) as would be expected. Validation of the Model System

Known Soluble Hypoxia Markers. Cells in neuroblastoma tumors exposed to hypoxia down-regulate neuronal marker genes, including Chromogranin A and Phosphatidylethanolamine-binding protein 1 (PEBP-1) as is shown in these experiments as well (Supplementary Table 1). There is also a clear up-regulation of enzymes involved in anaerobic metabolism (Phosphoglycerate kinase, Pyruvate kinase, and alpha-Enolase) and a down-regulation of aerobic enzymes (ATP synthase alpha and beta subunits). There is also a down-regulation of synthetic pathway enzymes (Fatty acid synthase) and protein breakdown (Proteasome subunit alpha types-1 and 5). Many proteins involved in folding are up-regulated and phosphorylated (Heat shock proteins 90, 75, 70 and 60; Protein disulfide isomerase). This confirmed that the cell culture model system was following the known response expected from the tumor system. The results are also in line with the results from a study of the effect of hypoxia in human cervix cancer and a head and neck cancer cell line32 in which 6 of the 11 proteins identified as up-regulated in hypoxia match those reported here. 1649

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Figure 2. Protein interaction networks in hypoxia. Yellow lines indicate a direct physical interaction; light blue, a predicted interaction. Round symbols indicate proteins in the data set; triangular are proteins not in the set. (a) Proteins involved in maintenance of the nuclear envelope. PRPH, Peripherin-2; LMN, Lamin; TMPO, Lamina-associated polypeptide; AKAP8L, A-kinase anchor protein 8-like; TFPI2, Tissue factor pathway inhibitor 2; C1QBP, Complement component 1 Q subcomponent-binding protein; SFRS1, Splicing factor, arginine/serine-rich 1; NMT1, Glycylpeptide N-tetradecanoyltransferase 1; KNG1, Kininogen1; BAG3, Bcl-2-associated athanogene 3; HSPA4, Heat shock 70 kDa protein 4; SGTA, Small glutamine-rich tetratricopeptide repeat-containing protein alpha; PFN2, Prolifin 2; HSP90, Heat shock protein 90; HSPA8, Heat chock protein 70; STUB1, E3 ubiquitin-protein ligase CHIP; HHIP, Hedgehog-interacting protein; HSF1, Heat shock factor protein 1; BAG1, Bcl-2-associated athanogene 1. (b) Proteins involved in the regulation of mRNA by spliceosome activity. HNRNPD, Heterogeneous nuclear ribonucleoprotein D; SFNRS3, Splicing factor, arginine/serine-rich; HNRNPK, Heterogeneous nuclear ribonucleoprotein K; ELAVL1, embryonic-type cytoplasmic polyadenylation element-binding protein; Myc, Myc proto-oncogene protein; SYNCRP, Synaptotagmin-binding, cytoplasmic RNA-interacting protein; EIF4G2, Eukaryotic translation initiation factor 4 gamma 2; SRC, Proto-oncogene tyrosine-protein kinase Src. (c) Proteins involved in Hif degradation, Proteasome subunits and ubiquitin thioesterases. UHCL, Ubiquitin carboxyl-terminal hydrolase isozyme; PSMA, Proteasome subunit alpha; VIM, Vimentin.

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Soluble Proteins Following Known Hypoxia Induced Biological Changes. The model system was following many of the pathway changes that are known from the biological behavior of the tumors. The Serine protease HTRA2 is down-regulated, leading to decrease in apoptosis since it binds to BIRC proteins leading to an increase in Caspase activity.33 Similarly, Gammaglutamylcyclotransferase is down-regulated since its function is to induce the release of Cytochrome c from mitochondria with a resultant induction of apoptosis.34 One of the first steps toward metastasis is a change in cell adhesion and mobility and this is seen clearly in that the most changes appear to be happening in the cytoskeleton in preparation for the transition from sessile to a more motile form with changes in Vimentin, Cofilin, Laminaassociated polypeptide 2, Profilin, Periferin, Nulceolin like protein, Stomatin-like protein 2, Desmocollin-1 and Cytokeratin 1 being up-regulated which has been shown to be involved in cell spreading.35 Gene silencing of Profilin-1 confirms this and inhibits cell proliferation and migration.36 Up-regulation of Desmocollin-1 (a Cadherin family member involved in desmosomes) and down-regulation of Desmocollin-3 is seen in several epithelial cancers such as colorectal adenocarcinoma lowering the number of intercellular junctions and aiding migration.37 E-Cadherin is a known gene target of HIF38 and is fundamental in controlling the epithelial-like behavior of the cells in the normal state and its down-regulation marking a turn toward dedifferentiation is a direct result of HIF. Isoform 1 of Aquaporin 3 (AQP3), a water channel, was shown to be upregulated in hypoxia and has been reported to be involved in migration and increasing metastatic potential.39 We found upregulation of Ephrin-B3 in hypoxia. Forced expression of ephrinB3 in low expresser cell lines stimulates cell migration and invasion in vitro and ex vivo.40 Changes in Membrane Protein Expression. None of the membrane proteins that we identified have been reported in connection to hypoxia induced changes. However, several have been strongly implicated in cancer progression. Isoform 2 of ATP-binding cassette transporter subfamily C member 11 (ABCC11) is strongly up-regulated in hypoxia. Gene expression profiling suggests that this factor is a strong predictor of lack of pathologic response to neoadjuvant chemotherapy in breast cancer patients41,42 and acute myeloid leukemia.43 Similarly, the uncharacterized protein SLIT1 is up-regulated at the mRNA level in canine malignant mammary tumors.44 Up-regulation of the gene appears to be specific to neuroblastomas.45 However IMR-32 and SK-N-BE(2)c cells show opposite responses at the mRNA level in response to hypoxia. The seizure-like proteins have been found in screens for genes up-regulated in lung cancer, which was subsequently confirmed by immuno-histochemical staining.46 The Inositol 1,4,5-triphosphate receptor type 2 is strongly up-regulated in hypoxia. This ties in the observation above, that profilin-1 is down-regulated in hypoxia, increasing the levels of IP3 and up-regulating the receptor. Finally, the appearance of embryonic/fetal expressed proteins indicating dedifferentiation, a common theme in cancer progression, is seen with the up-regulation of the putative Zinc finger SWIM domaincontaining protein 5 (ZSWIM5). Correlation between Protein and mRNA Expression Level Changes

mRNA Analysis. Total RNA was extracted from normoxic and hypoxic IMR-32 and SK-N-BE(2)c cells grown under the same conditions as those used for the protein expression comparisons. 1650

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Journal of Proteome Research The cDNAs that were generated were hybridized to a 27 000 probe microarray to determine genes transcription variations during cell growth under hypoxic condition. Almost 16 000 transcripts were relatively quantified (Supplementary Table 3). To assess to what extent proteins levels variation was due to transcription regulation, protein fold-changes were compared with those of the respective RNA. Transcript variations were checked for the proteins (both water-soluble and membrane associated) that had been found to be differentially expressed in the first part of this study. An RNA counterpart was found for almost 50% of the hypoxia regulated proteins and the data are given in Supplementary Table 4(a) for the IMR-32 cells and in Supplementary Table 4(b) for the SK-N-Be2c cells. Expression Comparison. The correlation between the fold change in protein and mRNA for the two cells lines is shown in Figure 3a for IMR-32 and Figure 3b for SK-N-Be2c cells. The overall correlation index values between protein and mRNA expression level changes were 0.043 for the IMR-32 cells and 0.013 for the SK-N-Be2c cells. For proteins that were found in multiple spots on the 2D gel, comparisons were done with and without merging the protein values, though this showed no overall change in the lack of correlation (data not shown). Most of the membrane proteins that were identified as being regulated during the transition to hypoxia were not present on the gene chip, or if they were, showed no change in expression whatsoever (Supplementary Table 5). The majority of membrane proteins that were identified but that were not undergoing changes in expression level showed a wide variety of responses at the mRNA level. The degree of correlation between protein and mRNA expression level changes has been shown to be weak. One of the earliest studies from Aebersold’s group47 showed low correlation in yeast and most recently a remarkably study using single Escherichia coli cells has shown a distinct lack of correlation even in prokaryotes.48 Classical hypoxia markers such as those involved in the switching on glycolysis and switching off aerobic metabolism, for example, Enolase up-regulation and ATP synthase subunits down-regulation, agree well on both levels as does the terminal electron acceptor protein, CoX5A which is known to be downregulated at the protein and mRNA level.49 The classical marker Phosphatidylethanolamine-binding protein 1, whose downregulation is associated with progression in neuronal differentiation,50 also agrees on both levels. However, some of the best known markers do not agree. It has been shown that specific mRNA species are regulated in a post-translational manner in response to hypoxia.51 The down-regulation of Chromogranin A protein, a neuronal marker, is clearly at odds with the upregulation found in the mRNA. The reverse is seen in the case of Peroxiredoxin4, which is up-regulated at the protein level and down-regulated at the mRNA. This is unexpected since the protein functions to protect hypoxic cells from apoptosis by breaking down hydrogen peroxide.52 Probably most of these effects will ultimately be explained by the relative degradation rates of the respective proteins and mRNAs. However, this has important implications for markers discovered by transcriptome profiling methods. New Biomarkers for Hypoxia

The plasma membrane protein analysis was the most fruitful in providing interesting data for marker discovery. Most of the proteins were not well characterized and nothing was known about any of them in relation to hypoxia. We wished to have an

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Figure 3. (a) Correlation of protein and mRNA fold-changes in IMR32 cells. For every differentially expressed protein with a measured mRNA variation, both fold changes were plotted (in log2 scale). Protein level variation is plotted on the x-axis while RNA level fold-change is plotted on the y-axis. (b) Correlation of protein and mRNA fold-changes in SK-N-Be2c cells. For every differentially expressed protein with a measured mRNA variation, both fold changes were plotted (in log2 scale). Protein level variation is plotted on the x-axis while RNA level fold-change is plotted on the y-axis.

independent validation of the membrane protein regulation so we carried out MRM experiments focusing on Aquaporin-3 using a new set of two biological replicates. The results agree with the LC-MS results and a set of explanatory spectra are shown in Figure 4. The raw data for the H4 and D4 N-terminally labeled peptides QVVLS are shown. Upper panel a shows the elution 1651

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Journal of Proteome Research profile of the light peptide eluting at 25.37 min and the lower panel shows the three light b-ion transitions. Upper panel b

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shows the heavy version eluting at 25.25 min and the lower the three heavy b-ion transitions. The retention time is in line with

Figure 4. Continued 1652

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Figure 4. MRM validation of the up-regulation of Aquaporin-3 in hypoxia. Panels a and b show biological replicate 1, and panels c and d show biological replicate 2. Panels a and c show the elution profile of the light labeled peptide and the corresponding b-ion transitions, while panels b and d show the corresponding data for the heavy labeled peptides. Replicate 1 shows an up-regulation of 13 upon hypoxia and replicate 2, 9-fold up-regulation which agrees with the original HPLC-MS/MS estimate of >9-fold. 1653

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Journal of Proteome Research that observed in the original LC-MS/MS identification runs, as is the slight retention time difference between the heavy and light labeled peptides. The integrated transition intensities show an up-regulation in hypoxia of ca. 13 which is in line with the original LC-MS value of >9 (Supplementary Table 2). The result from the biological duplicate shown in Figure 4c,d gives an upregulation of 9.1. This was confirmed by results from 2 other Aquaporin peptides. The sodium sulfate cotransporter (Solute carrier family 13 member 1) we found to be highly up-regulated in hypoxia. However, it has been recently shown that knock-down of the gene, causing hyposulphetemia, enhances tumor growth in the mouse model.53 The Immunoglobulin superfamily member 21 has been found to be up-regulated in breast and colorectal cancer at the transcriptional level but its function and ligands are unknown.54 We also found an olfactory receptor (OR51E1) to be up-regulated. Several reports indicate these receptors with unknown ligands are linked to cancer and up-regulated in prostate cancer, for example.55 These could be very good targets for imaging and there are projects to identify the ligands and couple these to dyes for imaging purposes.

’ CONCLUSIONS We have analyzed the response to hypoxia at the protein and mRNA expression levels in two neuroblastoma cell lines; IMR-32 and SK-N-BE(2)c and have also included an analysis of a highly enriched plasma membrane protein fraction from SK-N-BE(2)c. The study shows that there are considerable dangers in using mRNA expression analysis to predict protein markers for molecular responses since the degree of correlation between the two data sets is very low. This study shows that there are considerable changes occurring in membrane protein expression caused by hypoxia. One interesting observation that could be of clinical relevance is that the UV excision repair protein RAD23 homologue A is up-regulated in hypoxia which may help explain the refractory nature of these tumors to radiotherapy. The most promising approach to getting useful markers seems to be the membrane protein analysis. Here, we found the most unique proteins, many of which have unknown function and many of which have not been described before at the protein level. The accessibility of these proteins to circulating antibodies opens up the possibility of using these proteins as targets for PET imaging with radiolabeled antibodies or even treatment with antibodies. ’ ASSOCIATED CONTENT

bS

Supporting Information Supplementary Figure 1(a): Correlation between non-regulated True Membrane Protein and mRNA Expression Change SK-N-Be(2)c Cells. Supplementary Figure 1(b): Correlation between non-regulated Membrane Associated Protein and mRNA Expression Change SK-N-Be(2)c Cells. Supplementary Table 1a: Proteins with similar regulation in both IMR-32 and SK-NBE(2)c cells. Supplementary Table 1b: Proteins with different regulation in IMR-32 and SK-N-BE(2)c cells. Supplementary Table 2a: Membrane proteins up-regulated under hypoxic conditions in SK-N-BE(2)c cells. Supplementary Table 2b: Membrane proteins exclusively induced under hypoxic conditions in SK-N-BE(2)c cells. Supplementary Table 2c: Membrane proteins completely down-regulated under hypoxic conditions in

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SK-N-BE(2)c cells. Supplementary Table 3: Complete list of up- or down-regulated mRNA transcripts in both cell lines. Supplementary Table 4a: Hypoxia regulated soluble proteins with corresponding mRNA from IRM32 cells. Supplementary Table 4b: Hypoxia regulated soluble proteins with corresponding mRNA from SK-N-BE(2)c cells. Supplementary Table 5: Complete list of all hypoxia regulated membrane proteins from SK-N-BE(2)c cells with corresponding mRNA regulation values. This material is available free of charge via the Internet at http://pubs.acs.org.

’ AUTHOR INFORMATION Corresponding Author

*E-mail: (S.P., [email protected], hypoxia biology); (P.J. [email protected], proteomic analysis). Author Contributions #

These authors contributed equally to this study.

Author Contributions

P.C. collected and analyzed the data and performed the comparisons and wrote the manuscript. M.B. performed the membrane protein analysis experiments. K.W. carried out the 2D-PAGE analysis. M.S. and M.K. carried out the statistical analyses. K.H. carried out the MRM experiments. F.L. carried out the comparative MS data analysis. M.O. and A.P. grew the cells and isolated the plasma membranes. E.F. carried out the mRNA analysis and statistical analysis thereof. S.P. initiated and designed the study and contributed to writing the manuscript. P.J. initiated and designed the study and contributed to writing the manuscript. All authors discussed the results and commented on the manuscript. The authors declare that they have no competing financial interests.

’ ACKNOWLEDGMENT This work was supported by grants from the Gothenburg Research School in Functional Genomics (M.B.), Knut and Alice Wallenberg Foundation (P.J.), the Swedish Research Council,  (P.J., S.P.), the Children’s Cancer Foundation Vetenskapsradet of Sweden (S.P.), and from the Swedish Strategic Research Council to CREATE Health (P.J., S.P.) and the Strategic Cancer Research Program, BioCARE (S.P.). ’ ABBREVIATIONS: HIF, hypoxia-induced factor; NicNHS, Nicotinoyl N-hydroxysuccinimide ester; H4, D4 light and heavy isotopomers; DIGE, difference in-gel electrophoresis ’ REFERENCES (1) Brizel, D. M.; Scully, S. P.; Harrelson, J. M.; Layfield, L. J.; Bean, J. M.; Prosnitz, L. R.; Dewhirst, M. W. Tumor oxygenation predicts for the likelihood of distant metastases in human soft tissue sarcoma. Cancer Res. 1996, 56 (5), 941–3. (2) Giaccia, A. J.; Simon, M. C.; Johnson, R. The biology of hypoxia: the role of oxygen sensing in development, normal function, and disease. Genes Dev. 2004, 18 (18), 2183–94. (3) Carmeliet, P.; Jain, R. K. Angiogenesis in cancer and other diseases. Nature 2000, 407 (6801), 249–57. (4) Harris, A. L. Hypoxia--a key regulatory factor in tumour growth. Nat. Rev. Cancer 2002, 2 (1), 38–47. 1654

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