Relative Quantitation of Proteins in Expressed Prostatic Secretion with

ARTICLE pubs.acs.org/jpr

Relative Quantitation of Proteins in Expressed Prostatic Secretion with a Stable Isotope Labeled Secretome Standard Ting Zhao,†,|| Xuemei Zeng,|| Nicholas W. Bateman,† Mai Sun,|| Pang-ning Teng,†,|| William L. Bigbee,‡,|| Rajiv Dhir,‡ Joel B. Nelson,§ Thomas P. Conrads,*,†,||,^ and Brian L. Hood*,†,||,^ )

Departments of †Pharmacology and Chemical Biology, ‡Pathology, and §Urology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15261, United States Mass Spectrometry Platform, Cancer Biomarkers Facility, University of Pittsburgh Cancer Institute, University of Pittsburgh, Pittsburgh, Pennsylvania 15232, United States

bS Supporting Information ABSTRACT: Expressed prostatic secretion (EPS) is a proximal fluid directly derived from the prostate and, in the case of prostate cancer (PCa), is hypothesized to contain a repertoire of cancerrelevant proteins. Quantitative analysis of the EPS proteome may enable identification of proteins with utility for PCa diagnosis and prognosis. The present investigation demonstrates selective quantitation of proteins in EPS samples from PCa patients using a stable isotope labeled proteome standard (SILAP) generated through the selective harvest of the “secretome” from the PC3 prostate cancer cell line grown in stable isotope labeled cell culture medium. This stable isotope labeled secretome was digested with trypsin and equivalently added to each EPS digest, after which the resultant mixtures were analyzed by liquid chromatography tandem mass spectrometry for peptide identification and quantification. Relative quantification of endogenous EPS peptides was accomplished by comparison of reconstructed mass chromatograms to those of the chemically identical SILAP peptides. A total of 86 proteins were quantified from 263 peptides in all of the EPS samples, 38 of which were found to be relevant to PCa. This work demonstrates the feasibility of using a SILAP secretome standard to simultaneously quantify many PCa-relevant proteins in EPS samples. KEYWORDS: proteomics, mass spectrometry, expressed prostatic secretion, SILAC, prostate cancer

’ INTRODUCTION Prostate cancer (PCa) is the most commonly diagnosed solidorgan malignancy and the second most common cause of cancer death for men in the United States.1 Globally, PCa is the fifth most common cause of cancer death in males, and its incidence is anticipated to increase in developing countries. Prostate specific antigen (PSA) is the only clinically utilized serum biomarker for PCa detection; however, this protein lacks sensitivity and specificity as it is often elevated in benign conditions of the prostate, such as benign prostatic hyperplasia (BPH).2,3 Thus, more effective PCa surrogate biomarkers are urgently needed for early PCa diagnosis and prognosis. There is a growing interest in interrogating proximal fluids and cancer cell secretomes for biomarker discovery as they are hypothesized to be enriched with proteins secreted/shed from the cancer cells and as such represent possible biomarkers for diagnostic and prognostic applications.4 8 Proteomic analyses of expressed prostatic secretion (EPS), a proximal fluid of the prostate, have been reported previously wherein a large number of PCa-relevant proteins have been catalogued. In a study by Li et al.9 114 proteins were identified, while more recently Drake et al.10 identified 916 proteins, demonstrating a level of complexity to this proximal fluid proteome not previously appreciated. While these studies have provided invaluable information regarding the r 2011 American Chemical Society

nature of the EPS proteome, approaches for accurate quantification of protein abundances in EPS will be an essential component to enable biomarker discovery in case-control cohorts. Relative quantitation of proteins by mass spectrometry can be achieved by stable isotope labeling11,12 or label-free approaches.13 Among these approaches, stable isotope labeling by amino acids in cell culture (SILAC) has been proven to be robust and straightforward.14,15 This strategy has been extended to the preparation of stable isotope labeled proteome (SILAP) standards to serve as internal standards for relative quantitation of the proteomes of mouse brain,16 breast epithelial cell lines,17 serum from pancreatic cancer patients,18 secretomes of colon cell lines,19 human cervicovaginal fluid,20 and human tumor tissue.21 This report describes the use of a SILAP standard generated from harvesting the secretome of stable isotope labeled PC3 cells (a PCa cell line) and its use as an internal standard for quantification of proteins from EPS samples collected from 11 PCa patients using high-resolution mass spectrometry (Figure 1). Relative quantification of EPS proteins was determined through calculation of the light to heavy (L/H) ratio of the mass chromatogram peak areas from the isotopomeric peptide pairs. Received: August 26, 2011 Published: November 11, 2011 1089

dx.doi.org/10.1021/pr200829f | J. Proteome Res. 2012, 11, 1089–1099

Journal of Proteome Research

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using heavy DMEM SILAC kits containing 13C6,15N4-arginine and 13C6-lysine (Pierce, Rockford, IL). After six passages in the heavy DMEM medium, 7.5 106 cells were seeded into ten 10-cm tissue culture dishes. When the labeled PC3 cells reached 80% confluence, the cells were washed three times with ice-cold phosphate buffered saline and incubated in serum-free, phenol red-free Minimum Essential Medium (MEM) containing 13C6,15N4-arginine (97% isotope enriched) and 13C6-lysine (98% isotope enriched) (Pierce, Rockford, IL). Culture medium was collected following 48 h of incubation in the “heavy” MEM. Staining with trypan blue indicated 98% cell viability prior to the collection of secretome. The collected culture medium was brought to 10 mM NaF, 5 mM Na3VO4, 1 mM PMSF, and 1 mM EDTA and centrifuged at 100g for 10 min to remove cell debris. The culture media was concentrated and desalted using 3,000 molecular weight cutoff ultracentrifugal filters (Millipore, Billerica, MA). Protein concentration of the SILAP standard was determined using the BCA assay. Trypsin Digestion of the SILAP Standard and the EPS Samples

’ EXPERIMENTAL SECTION

For in-solution trypsin digestion of the SILAP standard and EPS samples, a total of 150 μg of the SILAP standard or 50 μg of proteins from each EPS sample was boiled in the presence of 10 mM dithiothreitol (DTT) for 5 min. After cooling to ambient temperature, proteins were deglycosylated by peptide-N-glucosidase F (PNGase F) (Sigma, Saint Louis, MO) at a concentration of 1 unit/50 μg protein at 37 C for 2 h. Subsequently, proteins were denatured in 6 M urea and alkylated by incubation in 45 mM iodoacetamide (IAA) for 1 h at ambient temperature in the dark. Sufficient 50 mM NH4HCO3 was added to lower the urea concentration to 1 M, and proteins were digested with sequencing-grade modified trypsin (Promega, Madison, WI) at a protein to enzyme ratio of 50:1 for 16 h at 37 C. The digests were desalted and concentrated by solid phase extraction (3 M Empore extraction disk cartridges, Millipore, St. Paul, MN). The concentrated peptide samples were lyophilized and reconstituted in water, and the peptide concentration in each sample was determined by the BCA assay.

Materials

LC MS/MS analyses

Figure 1. Schematic illustration of the workflow for relative quantitation of proteins in EPS samples collected from PCa patients using a SILAP standard generated by selectively collecting the secretome of heavy-isotope labeled PC3 cells. (A) Procedures for generation of the SILAP standard by collecting the secretome of the heavy labeled PC3 cells. (B) Quantitation of the identified proteins in the EPS samples by coupling the SILAP standard with LC MS/MS.

Sequencing grade modified trypsin (Promega, Madison, WI), ammonium bicarbonate, iodoacetamide (IAA), dithiothreitol (DTT), urea, formic acid, methanol, and acetonitrile were from ThermoFisher Scientific (Waltham, MA). Sodium fluoride (NaF), sodium orthovanadate (Na3VO4), phenylmethanesulfonylfluoride (PMSF), and ethylenediaminetetraacetic acid (EDTA) were from Sigma Aldrich (Saint Louis, MO). Clinical Collection of EPS from Prostate Cancer Patients

A total of 11 EPS samples were collected by prostate massage from PCa patients prior to undergoing radical prostatectomy under a University of Pittsburgh approved IRB protocol. Each sample was diluted with 400 μL of 100 mM ammonium bicarbonate followed by centrifugation at 200g for 10 min to remove particulates. Protein concentrations of the EPS samples were determined by the Bicinchoninic Acid Assay (BCA) (Pierce, Rockford, IL). Preparation of SILAP Standard

The PC3 cell line was purchased from the American Type Culture Collection (Manassas, VA) and was cultured using Dulbecco’s Modified Eagle Medium (DMEM) in a humidified incubator at 37 C, 5% CO2. Cells were metabolically labeled

Analysis of the SILAP secretome standard was performed by five replicate LC MS/MS analyses, and the combined SILAP/ EPS samples (1:1 (w/w) ratio) were analyzed in triplicate by LC MS/MS. All LC MS/MS analyses were performed on a nanoflow LC system (Ultimate 3000, Dionex Corporation, Sunnyvale, CA) coupled online with a LTQ-Orbitrap XL MS (ThermoFisher Scientific, San Jose, CA). All of the samples were resolved on a 100 μm i.d. 360 μm o.d. 20 cm long capillary column (Polymicro Technologies, Phoenix, AZ), which was slurry packed in house with 5 μm, 300 Å pore size C-18 silicabonded stationary phase (Jupiter, Phenomenex, Torrance, CA). Each sample was injected onto a reversed-phase (C-18) precolumn (Dionex) and washed for 3 min with mobile phase A (0.1% formic acid, 2% acetonitrile). Peptides were eluted at a constant flow rate of 200 nL/min by development a linear gradient of 0.33% mobile phase B (0.1% formic acid in acetonitrile) per min for 120 min and then to 95% B for an additional 15 min, after which the column was equilibrated with mobile phase A for the next sample injection. The LTQ-Orbitrap XL MS was configured to collect high resolution (R = 60,000 at m/z 400) broadband mass spectra (m/z 375 1800) from which the thirteen most abundant peptide molecular ions dynamically determined from the MS scan were selected for MS/MS using 1090

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a 30% normalized collision-induced dissociation energy. Dynamic exclusion was utilized to minimize redundant selection of peptides for MS/MS. Protein Identification

Tandem mass spectra were searched against the UniProt human protein database (01/2011) from the European Bioinformatics Institute (http://www.ebi.ac.uk/integr8/) using SEQUEST (ThermoFisher Scientific). The database was indexed with the following criteria: methionine oxidation (15.99492), asparagine deamidation (0.98402), and cysteine carboxyamidomethylation (57.02150) were set as dynamic modifications. Static and dynamic modifications of 13C-lysine (6.02010 Da) and 13C6,15N4-arginine (10.00827 Da) were used for the SILAP standard and the EPS/ SILAP mixtures, respectively. A maximum of two missed cleavages were allowed. Peptides were considered legitimately identified if they met specific charge state and proteolytic cleavagedependent cross-correlation scores of 1.9 for [M + H]+, 2.2 for [M + 2H]2+ and 3.5 for [M + 3H]3+, and a minimum delta correlation of 0.08. A false peptide discovery rate of 0.56% was determined by searching the MS/MS data using the same criteria against a decoy database where the protein sequences were reversed.22 Protein Quantitation

The relative abundance of the EPS/SILAP peptides were quantified from the L/H ratio calculated from the mass chromatogram peak areas for each isotopomeric peptide pair using an inhouse application (MATLAB Mathworks Inc., Natrick, MA) described previously.23 In this application, the retention time for each identified peptide was calculated and, using a combination of LOWESS regression and linear regression, aligned across all LC MS/MS analyses relative to a reference LC MS/MS analysis. Heavy peptides identified from the SILAP digest (from the combined 38 LC MS/MS runs) served as accurate mass and time (AMT) tags to predict the retention time and the m/z ratio for the corresponding light peptides from the EPS digests. Mass chromatograms of the light (EPS) and heavy (SILAP) peptides were derived (with a 10 ppm mass tolerance) from the sum of the intensities of the monoisotopic peak and the first 13C isotopic peak (e.g., “A0” and “A1”, respectively) in the peptide isotope envelope. The peptide peaks were integrated only when both A0 and A1 were present to ensure highly confident selection of the peptide peak from the full mass spectra. A mean Pearson’s correlation coefficient was used to assess the reproducibility performance of the mass chromatograms. The relative abundance of EPS proteins were measured using the average L/H ratio of its corresponding peptides. For proteins with 4 or more unique peptides, the L/H ratios of the three peptides with the highest correlation to each other were averaged. Bioinformatics Analysis

Ingenuity Pathways Analysis (IPA) (Ingenuity Systems, Redwood City, CA) and Proxeon ProteinCenter (Proxeon, Cambridge, MA) were utilized to classify the proteins in the EPS samples and the SILAP standard as well as finally quantified EPS proteins based on gene ontology annotation. Molecular and cellular functions were obtained from IPA, and ProteinCenter was used to classify cellular location of the proteins.

’ RESULTS AND DISCUSSION Proteomic Analysis of EPS from Prostate Cancer Patients

Expressed prostatic secretion samples were collected from 11 PCa patients by prostate massage just prior to radical prostatectomy.

Figure 2. Effect of retention time alignment for batch-extraction of peptide mass chromatograms. Scatterplot of retention time (RT) shifts for all of the identified peptides before and after retention time adjustment. Retention time alignment significantly reduced the retention time shifts across the multiple LC MS/MS runs for the majority of peptides. As a result, the mean retention time shift was reduced from 1.97 to 0.41 min.

These 11 EPS samples were digested with trypsin and analyzed by LC MS/MS. A total of 399 proteins were identified by two or more unique peptides. The identified EPS proteins were annotated by gene ontology, which indicated that 51.6% were predicted to be extracellular and 60.7% were membrane proteins, consistent with the expectation that the majority of proteins that comprise EPS were shed and/or secreted. The value of EPS compared to serum/plasma for prostate cancer biomarker discovery can be illustrated by comparing the overall contribution of classic highly abundant proteins in these biofluids. For instance, serum albumin and immunoglobulin proteins, which comprise over 90% of the protein abundance in serum, were found to contribute 9.5% and 8.5% of the total spectral counts of all identified EPS proteins, respectively. On the other hand, a significant contribution of proteins known to be secreted from the prostate was evident in EPS. For example, prostatic acid phosphatase and PSA, present in the ng/mL range in neat serum/plasma, contributed to 4.5% and 2.6% of the total spectral counts of all identified EPS proteins. These results further support the value of EPS for prostate cancer biomarker discovery. Preparation of a SILAP Secretome Standard from PC3 Prostate Cancer Cells

A SILAP secretome standard was generated by collecting the secretome from PC3 cells to serve as an internal standard for quantification of EPS proteins. PC3 cells were passaged six times in 13C6,15N4-arginine, 13C-lysine-enriched medium, followed by incubation in serum-free medium for 48 h. The secretome was concentrated, digested with trypsin, and analyzed by five recursive LC MS/MS injections from which 214 proteins were identified by two or more unique peptides. The percent efficiency of heavy isotope incorporation was globally estimated to be approximately 92% based on the comparison of the total number of heavy isotope-labeled peptides (all arginine and lysine residues) compared with the total number of peptides identified (e.g., containing both light and heavy labeled arginine and lysine residues). 1091



Figure 3. Reconstructed mass chromatograms of a light and heavy peptide pair K.VVLAYEPVWAIGTGK.T arising from triosephosphate isomerase at m/z 801.95 and m/z 804.96 and 78.89 min in the first LC MS/MS runs of 11 different EPS/SILAP mixtures using adjusted retention time scales. The top and bottom panels are mass chromatograms for the light and heavy peptide isotopmeric pairs, respectively, and each isotopmeric pair in the same LC MS/MS run is presented in the same color.

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Figure 5. Scatter plot distribution of the L/H ratio for 2 peptides in the 11 EPS/SILAP mixtures, K.IISNASCTTNCLAPLAK.V and R.GALQNIIPASTGAAK.A from glyceraldehyde-3-phosphate dehydrogenase. Each red symbol represents one EPS/SILAP mixture.

Figure 6. Histogram distribution of the linear Pearson’s correlation coefficients for a total of 544 peptide pairs arising from the 263 peptides corresponding to the 106 quantified proteins.

Figure 4. Scatter plot distribution of the L/H ratio for one quantified peptide (K.AVDTWSWGER.A from galectin-3-binding protein) in two replicate runs across the 11 EPS/SILAP samples. Each red symbol represents one EPS/SILAP mixture.

Gene ontology annotation illustrated that the SILAP standard was highly enriched for extracellular and membrane proteins with 61.1% and 64.0% being predicted to originate from these cellular compartments, respectively. Quantification of EPS Proteins Using the PC3 SILAP Secretome Standard

To quantify EPS proteins, the PC3 SILAP secretome standard was added to each of the 11 EPS samples at a 1:1 ratio (w/w) and each mixture analyzed in triplicate by LC MS/MS. To maximize the pool of SILAP secretome peptides from which our quantitative workflow could be performed, we elected to combine the

proteomic results from the SILAP secretome analyses (5 LC MS/MS analyses) and each of the triplicate SILAP/EPS analyses (33 LC MS/MS analyses). This resulted in the aggregate identification of 1894 SILAP secretome-derived (e.g., “heavy”) peptides from the 38 LC MS/MS analyses. The retention times of the SILAP secretome peptides were aligned across the 33 SILAP/EPS LC MS/MS analyses using LOWESS and linear regression. Figure 2 shows that the retention time shifts of the aligned 1650 heavy peptides identified more than once, which had less than 6 min of retention time shift across all of the LC MS/MS analyses before alignment. After alignment, the mean retention time shift of these peptides was reduced from 1.97 min (1.4%) to 0.41 min (0.3%). Based on the normalized retention time of the SILAP secretome peptides and their theoretical accurate mass, mass chromatograms of the EPS and SILAP isotopomers were constructed for the 33 LC MS/ MS analyses of the EPS-SILAP mixtures, and their ratios were calculated. Figure 3 shows an example of reconstructed mass chromatograms for a peptide pair (VVLAYEPVWAIGTGK; top 1092


Journal of Proteome Research panel, unlabeled isotopomer; bottom panel, labeled isotopomer) arising from triosephosphate isomerase from the first LC MS/ MS analysis of 11 individual samples. To ensure accuracy of the peptide isotopomer mass chromatograms, four criteria were imposed in this analysis: (1) only those peptides arising from proteins identified by at least 2 unique peptides were included, (2) SILAP secretome peptides had to be observed in at least two of three replicate LC MS/MS analyses for each EPS/SILAP sample, (3) the mass tolerance for identification of both EPS and SILAP peptides was within 10 ppm, and (4) the obtained L/H ratios of the extracted peptide pairs had good correlation between the replicate runs (correlation coefficient greater than 0.6). These filtering criteria resulted in a final set of 263 proteotypic peptide EPS/SILAP

Figure 7. Histogram distribution of the linear Pearson’s correlation coefficients for replicate LC MS/MS analyses of 106 proteins across all of the 11 EPS/SILAP mixtures. The majority of protein quantitation showed very strong correlations among replicate LC MS/MS runs with a mean Pearson’s correlation coefficient of 0.89.

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isotopomers, corresponding to 106 proteins, which were promoted for relative quantitation. The fourth criteria was applied to ensure good reproducibility of the isotopomer ratio for the extracted peptide pairs during the triplicate LC MS/MS analyses of the 11 EPS/SILAP mixtures. The reproducibility of the L/H ratio in replicate analyses of each sample was demonstrated by mean correlation coefficients, which were calculated by three pairwise linear Pearson’s correlations (e.g., replicate 1 and replicate 2, replicate 1 and replicate 3, and replicate 2 and replicate 3) of the L/H ratio for each peptide pair from LC MS/MS triplicate analyses of 11 EPS/SILAP mixtures. Figure 4 shows an example of the correlation of quantification of the peptide K. AVDTWSWGER.A from Galectin-3-binding protein in two replicate analyses of the 11 EPS/SILAP samples. We determined the correlation coefficient of the relative quantitative values derived for different peptides arising from the same protein. Figure 5 demonstrates an example of the correlation of the isotopomer ratio for two different peptides (K.IISNASCTTNCLAPLAK.V and R.GALQNIIPASTGAAK.A) derived from glyceraldehyde-3-phosphate dehydrogenase in 11 different EPS/SILAP samples. Figure 6 shows the histogram distribution of the linear Pearson’s correlation coefficients of the isotopomer ratio for a total of 544 different peptide pairs derived from the 263 proteotypic peptides corresponding to the 106 quantified proteins. This distribution demonstrates a strong overall correlation of the isotopomer ratio for the majority of the peptide pairs from the same protein with an average correlation coefficient of 0.78, which strongly supports that the peptide isotopomer ratios represent accurate surrogate measures for relative quantitation of protein abundance. Reproducibility of protein quantification between replicate sample analyses was estimated by averaging the mean Pearson’s correlation coefficient of peptide isotopomer ratios arising from the same protein. Figure 7 shows the histogram distribution for the calculated mean correlation coefficient for 106 quantified

Figure 8. Comparison of biological functions of EPS proteins, SILAP proteins, and the final quantified EPS proteins by statistical testing. 1093



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Table 1. List of 38 PCa-Relevant Proteins Quantified in This Study accession no. P05067-1

protein isoform APP770 of amyloid

cellular location plasma membrane

β A4 protein P07355-1

isoform 1 of

description Amyloid β protein serves as an androgen target gene to promote tumor growth in androgen-dependent PCa.48

plasma membrane

annexin A2 (ANXA2)

ANXA2 is a potential diagnostic biomarker for moderately differentiated PCa because of down-regulation in PCa tissue compared to benign prostatic epithelium.49 Re-expression of ANXA2 in high grade PCa may provide useful information for PCa prognostics.43

P61769

β-2-microglobulin

plasma membrane

Serum B2M levels are elevated in patients with metastatic, androgen-independent PCa.50

P80723-1

isoform 1 of brain acid

extracellular space

Significantly lower levels of BASP1 gene expression were observed in high-grade PCa prostate tissue than were observed in low-grade PCa prostate tissue.51

soluble protein 1 (BASP1) P62158

calmodulin

cytoplasm

Calmodulin is bound to androgen receptor in prostate cancer cells.52

P21926

CD9 antigen

plasma membrane

CD9 expression is reduced and even lost in prostate tissue of PCa patients

P10909-1

isoform 1 of clusterin

extracellular space

CLU expression is lower in PCa tissue than in normal tissue.54 However,

P01034

cystatin-C

extracellular space

CLU levels were increased in PCa tissue specimens following treatment.55 Elevated levels of serum cystatin C were detected in PCa patients than in

P07339

cathepsin D

extracellular space

CTSD is up-regulated in metastatic PCa tissue as compared to localized PCa tissue.57

Q9UBR2

cathepsin Z

extracellular space

CTSZ is involved in PCa progression and metastasis.58

Q14118

dystroglycan

plasma membrane

The expression of dystroglycan was reduced in PCa tumorigenesis.59

P06733-1

isoform 1 of α-enolase

plasma membrane

Alpha enolase at PCa cell surface plays important roles in extracellular matrix

with progression.53

healthy subjects.56

degradation for cancer invasion and metastasis.33 P21333-1

isoform 1 of filamin-A

cytoplasm, plasma membrane

Filamin-A plays important roles in assisting PCa cell migration for tumor metastasis.60

P02751-1

isoform 1 of fibronectin

extracellular space

FN1 plays important roles in PCa cell adhesion. In tissue, a heterogeneous distribution of FN1 was observed in the stroma of PCa tissue.24

Q12841

follistatin-related

extracellular space

P04406

glyceraldehyde-3-phosphate

P28799-1 P09211

isoform 1 of granulins glutathione S-transferase

P07900-1

isoform 1 of heat shock protein

P00338-1

isoform 1 of L-lactate

FSTL1 gene expression was associated with PCa progression and metastasis based on gene expression profiles of two prostate cancer cell lines.61

protein 1 (FSTL1) extracellular space

GAPDH expression is increased in late pathological stage human PCa tissue.62

extracellular space cytoplasm,

Granulin may be a potential therapeutic target for PCa treatment.32 Hypermethylation of GSTP1 was used as a biomarker for prostate cancer.63

dehydrogenase (GAPDH)

P (GSTP1)

plasma membrane cytoplasm

HSP90A is a drug target in the treatment of PCa.27

cytoplasm,

The LDHA gene was upregulated in androgen-independent PCa cells

HSP 90-α (HSP90A) dehydrogenase A chain Q08380

galectin-3-binding

cell surface extracellular space

protein (LGALS3BP) Q14766-1

latent-transforming

as compared to androgen-dependent PCa cells.64 LGALS3BP gene expression was down-regulated in prostatic intraepithelial neoplasia (PIN) cells and PCa cells microdissected from the prostate tissue of PCa patients.65

extracellular space

The expression of LTBP1 was lost in PCa tissue but not in benign tissue.66

plasma membrane

Overexpression of neuropilin-1 was observed in metastatic PCa tumor tissues.67

growth factor β-binding protein 1 O14786-1

isoform 1

P07737

profilin-1

extracellular space

PFN1 was down-regulated in metastatic PCa tissue compared to localized PCa tissue.57

P00558

phosphoglycerate kinase 1

extracellular space

Expression of PGK1 mRNA was significantly reduced in malignant samples compared to benign samples microdissected from the prostate tissue of PCa patients.68

Q06830

peroxiredoxin-1

plasma membrane

Peroxiredoxin-1 is a potential therapeutic target for PCa because it interacts

of neuropilin-1

physically with androgen receptor, which plays important roles in PCa progression.69 P32119

peroxiredoxin-2

plasma membrane

Peroxiredoxin-2 was expressed in greater levels in PCa than in benign tumor.70

P07602-1

isoform Sap-μ-0 of proactivator

extracellular space

PSAP is involved in PCa cell adhesion and PCa invasion. PSAP might be

polypeptide (PSAP)

used as a molecular target for PCa therapy.25 1094



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Table 1. Continued accession no.

protein

cellular location

description

P26022

pentraxin-related protein PTX3

extracellular space

PTX3 was up-regulated in PCa tissue as compared to nontumor biopsies.35

P34096

ribonuclease 4

extracellular space

Ribonuclease 4 activity was significantly increased in the sera of PCa patients.71

P31949

protein S100-A11

cytoplasm

Protein S100-A11 is involved in PCa development and progression.72

P00441

superoxide dismutase

extracellular space

The antioxidant enzyme SOD1 was repressed in PCa epithelium compared to benign epithelium.73

[Cu Zn] (SOD1) Q08629

testican-1

extracellular space

The testican gene was overexpressed in PCa tissue as compared to benign prostatic tissue.74

Q07654

trefoil factor 3 (TFF3)

extracellular space

Advanced PCa patients have higher plasma TFF3 levels than patients with localized PCa.40

P01033

metalloproteinase

extracellular space

TIMP1 is down-regulated in PIN cells and PCa cells microdissected from the prostate tissue of PCa patients.65

inhibitor 1 (TIMP1) P16035

metalloproteinase

extracellular space

Elevated levels of TIMP2 were observed in prostatic tissue of PCa patients at advanced stage.75

inhibitor 2 (TIMP2) P60174-1

isoform 1 of

plasma membrane

TPI1 has been proposed to be a potential serum biomarker for its role in the developmental states of PCa.76

triosephosphate isomerase P08670

vimentin

cell membrane

Study of protein expression in low and highly metastatic cells demonstrated that vimentin was associated with PCa invasion and metastasis.77

proteins in the 11 EPS-SILAP mixtures. As indicated in Figure 7, the majority of proteins had a good correlation among replicate LC MS/MS analyses and the overall mean correlation coefficient was 0.89. These 106 quantified proteins were further filtered on the basis of overall mean correlation coefficient of 0.8 or greater, resulting in a final set of 86 proteins. Functional analysis of the quantified 86 proteins indicated a significant relation to cancer and cell death. Figure 8 shows comparison of biological functions of the EPS proteins, the SILAP proteins, and the quantified EPS proteins. Gene ontology indicated that the quantified EPS proteins were implicated with cancer and cancer-relevant biological functions such as cell growth and function, cell death, and DNA replication recombination, and repair. There was a significant enrichment of cancerrelevant proteins demonstrated by statistical test in the quantified EPS proteins with a p-value of 9.42 10 8. In addition, the application of the SILAP secretome standard enabled selective quantification of PCa-relevant proteins in the EPS samples. Of the 86 quantified EPS proteins in this study, 38 were reported to be associated with prostate cancer (Table 1). Many quantified proteins such as fibronectin24 and prosaposin25 are extracellular matrix (ECM) proteins and play important roles in cell adhesion, migration, and cell-to-cell signaling supporting PCa invasion and metastasis. Fibronectin, an abundant ECM protein, contains binding sites for various cell surface receptors (e.g., collagens and fibrin) and plays an important role in cell adhesion and spreading. Antibody interference of fibronectin has been shown to result in decreased adhesion in LNCaP cells, with concomitant alterations in morphology in the primary stromal cells.24 Secretory prosaposin (PSAP) is wellknown for its role in promoting neurotrophic activities including stimulation of cell growth.26 Koochekpour and co-workers showed that down-regulation of PSAP significantly decreased PCa cell adhesion, migration and invasion.25 Cell adhesion of PSAP knockdown clones was reduced significantly on fibronection and laminin coated plates compared with the control clones. In addition, they demonstrated that down-regulation of PSAP results in decreased migration by 70% in PC-3 cells and 79% in

DU-145 cells, with concomitant reductions in migratory potential by 78% in PC-3 cells and by 85% in DU-145 cells.25 Additional proteins that may be of potential interest as therapeutic targets are heat shock protein 90 (HSP90), granulin, and enolase. HSP90 is a chaperone that assists in folding, stability, and function of proteins that are involved in signal transduction, apoptosis, and cell-cycle regulation. In tumor cells, HSP90 expression is significantly increased as compared to normal cells and is hypothesized to promote survival of tumor cells.27,28 Androgen receptor (AR), a key protein involved in PCa carcinogenesis and progression, is known to complex with HSP90,29 suggesting that HSP90 may be an appealing target for PCa treatment . The inhibition of HSP90 could potentially destabilize AR and concomitantly affect AR-related oncogenic pathways and result in a reduced malignant phenotype.30 Granulin (GRN) is the proteolytic product of PC cell-derived growth factor (PCDGF), which belongs to a class of growth factors that stimulate cell proliferation. Higher expression levels of PCGDF/GRN have been observed in rapidly growing cells as compared to mitotically inactive cells, and has been shown to contribute to the tumorgenic phenotype of several cancers.31 In normal prostate tissue, PCDGF expression is low or undetectable whereas higher expression of PCDGF was detected in prostatic intraepithelial neoplasia (PIN) as well as PCa tissue.32 This suggests that alterations in PCDGF expression may occur as early as PIN and may potentially be a novel molecular target for PCa progression, treatment and/or prevention.32 Degradation of the extracellular matrix is critical for PCa invasion and metastasis. Enolase, which is located on the cell surface, is involved in degrading extracellular matrix proteins by acting as a plasminogen-binding receptor. It serves to concentrate plasminogen on the cell surface which, when converted to plasmin, activates collagenase and triggers degradation of extracellular matrix proteins.33 Many pro-inflammatory proteins were also observed in our analysis. Pentraxin-related protein PTX3 belongs to a superfamily of pentraxins whose expression is regulated by multiple cytokines, including tumor necrosis factor A. PTX3 plays an 1095



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Figure 9. Molecular network illustrating several proteins identified and quantified in this study (in gray) and their interaction with proteins known to be critically involved in promoting prostate carcinogenesis, including p53, androgen receptor, β-catenin (CTNNB1) and transforming growth factor β-1 (TGFB1) as inferred from Ingenuity Pathway Analysis.

important role in mediating innate resistance to pathogens, removal of apoptotic cells and regulation of inflammatory reactions. Under conditions of infection or tissue damage, the abundance of PTX3 increased significantly.34 PTX3 has been detected in greater abundance in PCa biopsies as compared to nontumor controls, which may provide evidence on the activation of the innate immune system during the malignant progression.35 Several quantified proteins have been previously described as being significantly elevated in PCa patients and have been suggested as candidate biomarkers for diagnosis of PCa and potential therapeutic targets. These proteins include β-2-microglobulin,36 trefoil factor 3 (TFF3),37 and phosphoglycerate kinase-1,38 all of which were identified and relatively quantified in this investigation. The trefoil factor family of proteins, of which TFF3 is a member, is produced and cosecreted with mucin proteins by mucin-secreting epithelial cells.39 TFF3 was shown to be overexpressed in PCa as compared to normal and benign prostatic hyperplasia (BPH) tissues.37 While no correlation was found between the TFF3 level and Gleason score, tumor grade, or the rate of recurrence for PCa patients, elevated TFF3 levels were detected in the plasma of metastatic PCa patients when compared

to patients with localized PCa, suggesting the plasma level of TFF3 might be a potential biomarker for distinguishing metastatic versus localized PCa.40 Annexin A2 is a phospholipid binding protein and plays different roles in cell motility, cellular adhesion, signal transduction, and cell cell interactions.41,42 The expression of annexin A2 has been observed at significantly reduced levels in PCa tissue (Gleason score 3 7) compared to benign prostatic epithelium; however, annexin A2 expression has also been observed at elevated levels in high-grade PCa (Gleason score 8 10), suggesting that the levels of annexin A2 may provide useful information toward PCa diagnosis and/or prognosis.43 The subset of proteins identified and quantified in this study were submitted to Ingenuity Pathway Analysis (IPA) to determine whether any cancer-relevant functions or networks (with a score of log10[p value] = 18 as determined from a righttailed Fisher’s exact test) are evident. Several proteins from this study were involved in a network (Figure 9) containing multiple important PCa-relevant genes including p53 gene,44 AR,45 β-catenin (CTNNB1),46 and transforming growth factor β-1 (TGFB1).47 1096



’ CONCLUSIONS Many PCa-relevant proteins were selectively quantified in PCa patient EPS samples through the use of a SILAP standard derived from the secretome of stable isotope labeled PC3 prostate cancer cells. This work contributes substantial evidence in support of the feasibility of using a SILAP standard to quantify PCa-relevant proteins in EPS samples in a multiplexed fashion. Ongoing work is underway to similarly analyze EPS samples from PCa patients (e.g., indolent versus aggressive), men with other prostatic diseases such as BPH, and men without prostate cancer, toward the goal of identifying differentially abundant secreted proteins that are sensitive and selective for clinically relevant applications in PCa management. ’ ASSOCIATED CONTENT

bS

Supporting Information Supplemental Table 1: Peptide isotopomer heavy (SILAP)to-light (EPS) ratios from each sample mixture for the final set of 263 peptides promoted for quantitation following the four filtering criteria used in this analysis and with an overall mean correlation coefficient of 0.6 or greater. Supplemental Table 2: Averaged protein heavy (SILAP)-to-light (EPS) ratios from each sample mixture for the final set of 86 proteins with an overall mean correlation coefficient of 0.8 or greater. This material is available free of charge via the Internet at http://pubs.acs.org.

’ AUTHOR INFORMATION Corresponding Author

*(T.P.C.) Tel: 703-207-3357. Fax: 703-207-3351. E-mail: [email protected]. (B.L.H.) Tel: 703-207-3359. Fax: 703-2073351. E-mail: [email protected]. Present Addresses ^

Women’s Health Integrated Research Center at Inova Health System, 3289 Woodburn Road, Suite 375, Annandale, VA 22003.

’ ACKNOWLEDGMENT We thank Michelle Bisceglia and Patricia Clark for their assistance in EPS collection. This work was supported by an award from the David Scaife Foundation (TPC) and in part by a Cancer Center Support grant from the Department of Health and Human Services (UPCI/TPC, Award P30CA047904). ’ REFERENCES (1) Jemal, A.; Siegel, R.; Xu, J.; Ward, E. Cancer Statistics, 2010. Ca-Cancer J. Clin. 2010, 60 (5), 277–300. (2) Lilja, H.; Ulmert, D.; Vickers, A. J. Prostate-specific antigen and prostate cancer: prediction, detection and monitoring. Nat. Rev. Cancer 2008, 8 (4), 268–78. (3) Shariat, S. F.; Scardino, P. T.; Lilja, H. Screening for prostate cancer: an update. Can. J. Urol. 2008, 15 (6), 4363–74. (4) Piersma, S. R.; Fiedler, U.; Span, S.; Lingnau, A.; Pham, T. V.; Hoffmann, S.; Kubbutat, M. H. G.; Jimenez, C. R. Workflow comparison for label-free, quantitative secretome proteomics for cancer biomarker discovery: method evaluation, differential analysis, and verification in serum. J. Proteome Res. 2010, 9 (4), 1913–22. (5) Chenau, J.; Michelland, S.; de Fraipont, F.; Josserand, V.; Coll, J. L.; Favrot, M. C.; Seve, M. The cell line secretome, a suitable tool for investigating proteins released in vivo by tumors: application to the study

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Relative Quantitation of Proteins in Expressed Prostatic Secretion with

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