Quantitative Targeted Absolute Proteomics-Based Large-Scale

Article pubs.acs.org/jpr

Quantitative Targeted Absolute Proteomics-Based Large-Scale Quantification of Proline-Hydroxylated α‑Fibrinogen in Plasma for Pancreatic Cancer Diagnosis Toshihiro Yoneyama,† Sumio Ohtsuki,*,†,§ Masaya Ono,‡ Ken Ohmine,† Yasuo Uchida,† Tesshi Yamada,‡ Masanori Tachikawa,† and Tetsuya Terasaki† †

Division of Membrane Transport and Drug Targeting, Graduate School of Pharmaceutical Sciences, Tohoku University, Aoba, Aramaki, Aoba-ku, Sendai 980-8578, Japan ‡ Division of Chemotherapy and Clinical Research, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan § Department of Pharmaceutical Microbiology, Faculty of Life Sciences, Kumamoto University, 5-1 Oe-honmachi, Kumamoto 862-0973, Japan S Supporting Information *

ABSTRACT: Pancreatic cancer is a devastating disease and early diagnosis and treatment are essential to improve the prognosis. We previously showed that α-fibrinogen containing hydroxylated proline residues at positions 530 and 565 is increased in plasma of pancreatic cancer patients. However, no antibody specific for hydroxylated proline-530 is available. Therefore, the purposes of this study were to develop a quantification method specific for both proline-hydroxylated α-fibrinogens by selected/multiple reaction monitoring (SRM/MRM), and to validate these modifications as pancreatic cancer markers. The target peptide for hydroxylated proline-530 contained methionine, and since variable partial oxidation of this residue would affect the quantification, hydrogen peroxide treatment was carried out to ensure complete oxidation. Quantification values of modified and unmodified αfibrinogen were well correlated with those obtained by immunoblotting. Concentrations of modified and unmodified αfibrinogen were quantified in 70 pancreatic cancer patients and 27 healthy controls. Percent hydroxylation of α-fibrinogen and concentration of hydroxylated α-fibrinogen were significantly greater in the plasma of patients. Furthermore, among 8 carbohydrate antigen 19-9 (CA19-9)-negative patients in stages I/II, 6 were positive for proline-hydroxylated α-fibrinogen. These results indicate that plasma concentration of proline-hydroxylated α-fibrinogen measured by SRM/MRM analysis may be a good pancreatic cancer marker, especially in CA19-9-negative patients. KEYWORDS: pancreatic cancer, α-fibrinogen, selected/multiple reaction monitoring, hydroxylated proline, post-translational modification, quantification

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Pancreatic cancer is a devastating disease with a five-year survival rate of about 5%.4 This is partly because currently available biomarkers, such as CA19-9, do not have sufficient sensitivity and specificity for detection of pancreatic cancer, especially in the early stage.5 It is important to discover new biomarkers for early diagnosis, because early treatment is critical to improve the prognosis in pancreatic cancer. We have shown that proline-hydroxylated α-fibrinogen is increased in plasma of pancreatic cancer patients. Prolyl hydroxylation is essential for stability of collagen,6 and collagen has long been considered to be the only protein that is hydroxylated on its

INTRODUCTION

Post-translational modifications (PTMs), such as phosphorylation, glycosylation, ubiquitination, and acetylation, are potentially valuable as biomarkers; for example, phosphorylated cardiac troponin I, phosphorylated fibrinogen, and glycoproteins have been suggested to be biomarkers for chronic heart disease, ovarian cancer, and a range of cancers, respectively.1−3 However, to validate PTMs as markers, the modified protein must be quantified in many clinical samples, and this has usually been done by means of ELISA or immunoblot analysis using specific antibodies. But the availability of antibodies specific for target PTMs is limited and, moreover, the preparation of specific antibodies is time-consuming. © 2013 American Chemical Society

Received: August 29, 2012 Published: January 9, 2013 753

dx.doi.org/10.1021/pr3008144 | J. Proteome Res. 2013, 12, 753−762

Journal of Proteome Research

Article

proline residues. However, the function of hypoxia-inducible factor 1α (HIF1α) was recently revealed to be regulated by prolyl hydroxylation.7 Furthermore, it has been reported that prolyl hydroxylation regulates the stability of Argonaute 2 and affects the folding and biological activity of conotoxins.8,9 These findings suggest that prolyl hydroxylation may be a relatively common PTM, and should be considered as a candidate biomarker. We found proline-hydroxylated α-fibrinogen by employing a quantitative proteomic analysis technology known as two-dimensional image converted analysis of liquid chromatography and mass spectrometry (2DICAL).10,11 2DICAL is a label-free proteomics platform that simply compares liquid chromatography and mass spectrometry (LC/MS) data and detects a protein modification on the basis of changes in the mass-to-charge ratio (m/z) and retention time. We found that two proline residues at positions 530 and 565 were preferentially hydroxylated in plasma from patients. We were able to obtain a specific antibody for hydroxylated proline at residue 565, but a corresponding antibody for hydroxylated proline at residue 530 could not be prepared. Therefore, we could not validate proline hydroxylation at residue 530 of αfibrinogen as a biomarker for pancreatic cancer. Protein quantification by LC/MS/MS with selected reaction monitoring or multiple reaction monitoring (SRM/MRM) has recently been employed for quantification of various proteins,12−14 including phosphorylated proteins.15 SRM/ MRM analysis is able to distinguish between modified and unmodified forms of a target tryptic peptide, so that highly specific quantification of PTMs can be achieved. Furthermore, we have recently developed in silico criteria for selecting appropriate tryptic peptides in a target protein for quantification with SRM/MRM analysis.16,17 These criteria include amino acid composition, peptide length, and hydrophobicity index, and they provide a means to assess the suitability and limitations of tryptic peptides for quantitative analysis of PTMs. The purpose of the present study was to develop a quantification method specific for α-fibrinogen hydroxylated at proline residues 530 and 565, employing a simple and rapid sample preparation procedure and ultra-high-performance LC(UPLC)/MS/MS. The developed method was used to quantify proline hydroxylation at residues 530 and 565 of αfibrinogen in plasma samples from 70 pancreatic cancer patients and 27 healthy controls in order to validate these modifications as pancreatic cancer biomarkers.

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Table 1. Characteristics of Subjects N

median age

stagea

male

female

male

female

healthy controls

16

11

I

3

3

II

17

7

III

11

9

IV

14

6

65 (48−85) 72 (66−73) 66 (45−79) 66 (48−82) 59 (50−78)

68 (46−91) 70 (63−85) 69 (60−74) 65 (58−78) 70 (61−83)

a

Clinical stage was classified according to the Union for International Cancer Control.

committees of the National Cancer Research Institute and the Graduate School of Pharmaceutical Sciences, Tohoku University. The plasma samples were taken before treatment from pancreatic cancer patients, who had been diagnosed as having invasive ductal carcinoma based on pathological examination. The clinical stages were classified according to the TNM classification of the Union for International Cancer Control, and the subjects’ characteristics are summarized in Table 1. Patients having other cancers or jaundice were excluded. Control plasma samples were collected from individuals with no history of either cancer or jaundice. CA19-9, carcinoembryonic antigen (CEA) and Duke pancreatic monoclonal antibody type 2 (DUPAN-2) were measured at SRL Co. (Tokyo, Japan). Sample Preparation and LC/MS/MS Analysis

Ten microliters of 10-fold-diluted plasma samples and standard human serum spiked with α-fibrinogen was solubilized in 8 M urea in 100 mM Tris-HCl (pH 8.5), and S-carbamoylmethylated with dithiothreitol and iodoacetamide as described.16,20 The S-carbamoylmethylated samples were diluted 5-fold with protease MAX surfactant (Promega, Madison, WI; final concentration 0.1%) and 100 mM Tris-HCl (pH 8.5), and treated with lysyl endopeptidase (Wako Pure Chemical Industries) at an enzyme/substrate ratio of 1:100 at room temperature for 3 h. Subsequently, samples were digested with sequence-grade modified trypsin (Promega) at an enzyme/ substrate ratio of 1:100 at 37 °C for 16 h. For methionine oxidation, 500 fmol of stable isotope-labeled internal standard peptides was added to 1/5 of the tryptic digest of a sample, corresponding to 0.2 μL of plasma. Then, the sample solutions were treated with 10 mM H2O2 at 40 °C for 30 min or 1 h to oxidize methionine.21,22 The samples were acidified with formic acid and subjected to LC/MS/MS analysis.

EXPERIMENTAL PROCEDURES

Materials

The stable isotope-labeled and unlabeled peptides listed in Table 1 were synthesized at Peptide Institute, Inc. (Ibaraki, Osaka, Japan) or Thermoelectron Corporation (Sedantrabe, Germany). Standard human serum was purchased from Sigma Chemical Co. (St. Louis, MO). All other reagents were commercial products of analytical grade.

Multiplexed SRM/MRM Analysis with LC/MS/MS

The HPLC system (Agilent 1100 system; Agilent, Santa Clara, CA) was equipped with C18 capillary columns (XBridge BEH130 C18, 1.0 mm i.d. × 100 mm, 3.5 μm particles; Waters, Milford, MA) and was coupled to an ESI-triple quadrupole mass spectrometer (API5000; Applied Biosystems, Foster City, CA). Mobile phases A and B consisted of 0.1% formic acid in water and 0.1% formic acid in acetonitrile, respectively. The peptides were separated and eluted from the column with a linear gradient sequence (120-min run time at a flow rate of 50 μL/min), as follows (A:B): 99:1 for 5 min after injection, 50:50

Clinical Samples

Frozen plasma samples were collected from seven medical institutions associated with the “Third-Term Comprehensive Control Research for Cancer” project and stored at −80 °C at the National Cancer Center Research Institute until analysis as described previously.18,19 Written informed consent was obtained from every subject. The research protocols for the present study were reviewed and approved by the ethics 754



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Table 2. Target Peptide Sequences and Selected Ions for Quantificationa SRM/MRM transition (m/z) peptide name ESS Hyp-ESS TFP Hyp-TFP TFP(O) Hyp-TFP(O) Hyp-TFP(O2) GLI

peptide sequence

Q1/Q3-1

Q1/Q3-2

Q1/Q3-3

Q1/Q3-4

ESSSHHPGIAEFPSR ESSSHHPGIAEFPSR* ESSSHHP(O)GIAEFPSR ESSSHHP(O)GIAEFPSR* TFPGFFSPMLGEFVSETESR TFPGFFSPMLGEFVSETESR* TFP(O)GFFSPMLGEFVSETESR TFP(O)GFFSPMLGEFVSETESR* TFPGFFSPM(O)LGEFVSETESR TFPGFFSPM(O)LGEFVSETESR* TFP(O)GFFSPM(O)LGEFVSETESR TFP(O)GFFSPM(O)LGEFVSETESR* TFP(O)GFFSPM(O2)LGEFVSETESR TFP(O)GFFSPM(O2)LGEFVSETESR* GLIDEVNQDFTNR GLIDEVNQDFTNR*

546.6/706.4 549.9/716.4 551.9/989.5 555.2/999.5 755.7/807.4 759.0/817.4 761.0/807.4 764.3/817.4 761.0/807.4 764.3/817.4 766.3/807.4 769.7/817.4 771.6/807.4 775.0/817.4 760.8/894.4 765.8/904.4

546.6/506.3 549.9/516.3 551.9/706.4 555.2/716.4 755.7/708.3 759.0/718.3 761.0/708.3 764.3/718.3 761.0/708.3 764.3/718.3 766.3/708.3 769.7/718.3 771.7/708.3 775.0/718.3 760.8/1237.4 765.8/1247.4

546.6/359.2 549.9/369.2 551.9/506.3 555.2/516.3 755.7/621.3 759.0/631.3 761.0/621.3 764.3/631.3 761.0/621.3 764.3/631.3 766.3/621.3 769.7/631.3 771.7/621.3 775.0/631.3 760.8/993.3 765.8/1003.3

410.2/359.2 412.7/369.2 414.2/359.2 416.7/369.2 755.7/1009.0 759.0/1014.0 761.0/492.2 764.3/502.2 761.0/492.2 764.3/502.2 766.3/492.2 769.7/502.2 771.7/492.2 775.0/502.2 760.8/652.3 765.8/662.3

a

Conditions of SRM/MRM analysis were optimized for high signal intensity following direct injection of peptide solution into the mass spectrometer through a turbo ion spray source. Theoretical m/z values of multi-charged ions of intact peptides (Q1) assumed as precursor ions are shown. Four singly or doubly charged fragment ions derived from a precursor ion are indicated as Q3-1, -2, -3, and -4. Bold letters with asterisks indicate amino acid residues labeled with stable isotope (13C and 15N).

Immunoblot Assay

at 55 min, 0:100 at 56 min and up to 58 min, 99:1 at 60 min and up to 120 min. For multiplexed SRM/MRM analysis using the UPLC system (Waters), UPLC was performed with C18 capillary columns (XBridge BEH130 C18, 1.0 mm i.d. × 100 mm, 3.5 μm particles; Waters). Mobile phases A and B consisted of 0.1% formic acid in water and 0.1% formic acid in acetonitrile, respectively. The peptides were separated and eluted from the column with a linear gradient sequence (28 min run time, with a flow rate of 200 μL/min for 1−20 min and 400 μL/min for 21−28 min), as follows (A:B): 99:1 for 5 min after injection, 50:50 at 15 min, 0:100 at 16 min and up to 18 min, 99:1 at 20 min and up to 28 min. Each target peptide was quantified using four specific sets of SRM/MRM transitions for four product ions.23 Four other transitions were measured for the product ions derived from the corresponding stable isotope-labeled internal standard peptide. In the UPLC/MS/MS analysis, α-fibrinogen protein was quantified using 10 peptides (unlabeled and isotope-labeled peptides for ESS, Hyp-ESS, TFP(O), Hyp-TFP(O), and GLI) and 40 SRM/MRM transitions (Table 2). Dwell time of one transition was 10 ms and total cycle time was 0.6 s ((10 ms dwell time + 5 ms pause time) × 4 transitions × 10 peptides). The peak width of GLI peptide was 12 s, which gave 20 data points in the chromatogram in the case of the 10 min gradient (1−50% B) used for UPLC. A standard curve was prepared by spiking serial dilutions of the peptides (10, 50, 100, 500, 1000, and 5000 fmol) and 500 fmol of internal standard peptide into tryptic digests of standard human serum corresponding to 0.2 μL. The ion counts in the chromatograms were determined by using an auto analysis system established in our laboratory. Quantification value was calculated from the peak area ratio of each transition for unlabeled peptide to that for labeled peptide, and the amount of peptide was calculated as the average of the 4 quantification values determined from the 4 sets of transitions.

Ten plasma samples were separated by SDS-PAGE and electroblotted onto polyvinylidene difluoride membranes (Millipore, Billerica, MA). Blots were visualized with an enhanced chemiluminescence kit (GE Healthcare, Bucks, U.K.). Antibodies used for detection were described previously.11 Statistical Analysis

Student’s t-test was used to determine the statistical significance of differences between two groups. A p-value of less than 0.05 was considered as statistically significant. Receiver operating characteristics (ROC) analysis was performed using PRISM5 (Graph Pad, La Jolla, CA)

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RESULTS

Target PTM Peptide Selection and Complete Oxidation of Methionine in Peptides

The target tryptic peptides for α-fibrinogen (Accession No. P02671) with and without hydroxylated proline at residue 565 (Hyp-ESS and ESS peptides, respectively) and at residue 530 (Hyp-TFP and TFP peptides, respectively) are shown in Table 2. Our previously reported selection criteria16 indicate some unfavorable factors for quantification, i.e., Hyp-ESS and ESS peptides contain histidine residues, and Hyp-TFP and TFP peptides (20 aa) are longer than the optimal length, which is expected to result in reduced peak intensity. Examination with enhanced signature peptide predictor (ESPPredictor) software, which can predict high-responding peptides for mass spectrometry assay,24 also indicated that ESS and TFP would not be high-responding peptides, since their scores were less than 0.5 (0.367 for ESS and 0.0879 for TFP). However, αfibrinogen is an abundant plasma protein, and has been detected by means of LC/MS/MS with 2DICAL.11 Therefore, these issues should not be critical for quantification of prolinehydroxylated α-fibrinogen in plasma by SRM/MRM analysis, which provides greater sensitivity than information dependent MS/MS acquisition mode. 755



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Figure 1. SRM/MRM chromatograms of trypsin-digested plasma of a pancreatic cancer patient. The plasma (1 μL) of pancreatic cancer patient #5 shown in Figure 4 was digested with trypsin. Tryptic digest of plasma corresponding to 0.2 μL plasma was spiked with stable isotope-labeled peptides (500 fmol), and treated with (E−J) or without (A−D) 10 mM H2O2 at 40 °C for 1 h. The digested samples were subjected to LC/MS/MS and analyzed with the following SRM/MRM transitions (Q1/Q3): 755.7/807.4 for unlabeled TFP (A and E), 759.0/817.4 for labeled TFP (B and F), 761.0/807.4 for unlabeled TFP(O) and Hyp-TFP (C and G), 764.3/817.4 for labeled TFP(O) and Hyp-TFP (D and H), 766.3/807.4 for unlabeled Hyp-TFP(O) (I) and 769.7/817.4 for labeled Hyp-TFP(O) (J).

sulfone formation in Hyp-TFP was detected at 771.7/807.4 (Figure 2L). In Figure 2E, the two peaks were not fully separated, though they were separated in Figure 1C. The compositions of HypTFP and TFP(O) were the same, and the time difference between the two peaks (0.3−1.6 min) was small compared with the gradient time (50 min). Slight differences in LC conditions, such as equilibration, may have affected the separation of these peaks, although the precise reason is unclear. When patients’ plasma samples were prepared under these conditions, a single peak was detected at 761.0/807.4 for TFP(O) and at 766.3/807.4 for Hyp-TFP(O) (Figure 1G,I). Peak identification was based on the fact that the unlabeled peptides showed identical retention times to the corresponding labeled peptides (Figure 1H,J). No peak was seen at 755.7/ 807.4 and 759.0/817.4 for unlabeled and labeled TFP, respectively (Figure 1E,F). These results suggested that HypTFP and TFP were completely oxidized by hydrogen peroxide treatment. Furthermore, no significant interfering peak was observed in the chromatogram of either unlabeled or stable isotope-labeled TFP(O) and Hyp-TFP(O) (Figure 1G−J). In the following experiments, Hyp-TFP and TFP were quantified using the SRM/MRM transitions for Hyp-TFP(O) and TFP(O), respectively, after oxidation under the optimized conditions.

Hyp-TFP and TFP peptides also contain methionine. Oxidation of methionine changes the mass of peptides, and consequently affects the quantification values. Furthermore, TFP with oxidized methionine (TFP(O)) has the same mass as Hyp-TFP. Indeed, as shown in Figure 1C, two peaks were detected at 761.0/807.4, which is an SRM/MRM transition for unlabeled Hyp-TFP, in plasma of a pancreatic cancer patient even after reduction with dithiothreitol during sample preparation. Two peaks were also detected in the internal standard SRM/MRM transition for spiked stable isotopelabeled Hyp-TFP (764.3/817.4) at the same retention times (Figure 1D), suggesting that the two peaks in Figure 1C were both derived from TFP or Hyp-TFP peptide in the plasma sample. To optimize the conditions for complete methionine oxidation, synthesized Hyp-TFP and TFP were treated with 10 mM hydrogen peroxide for different times and analyzed by SRM/MRM (Figure 2). After 30 min treatment, two peaks were detected in the SRM/MRM transition for Hyp-TFP and TFP(O) (761.0/807.4, Figure 2E), indicating that the peptides were only partially oxidized. After 1 h treatment, a single peak was detected at 761.0/807.4 for TFP(O) and at 766.3/807.4 for Hyp-TFP(O) (Figure 2F,I), while no peak was detected at 755.7/807.4 for TFP (Figure 2C), indicating that both peptides had been completely oxidized. Furthermore, no peak for 756



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Figure 2. SRM/MRM chromatograms of synthetic TFP and Hyp-TFP peptides after oxidation. Synthetic TFP and Hyp-TFP peptides (5 pmol each) were oxidized in tryptic digests of standard human serum with 10 mM H2O2 at 40 °C for 30 min (B, E, H, and K) or 1 h (C, F, I, and L), or were analyzed without oxidation (A, D, G, and J). The peptides were subjected to LC/MS/MS and analyzed using the following SRM/MRM transitions (Q1/Q3): 755.7/807.4 for TFP (A−C), 761.0/807.4 for TFP(O) and Hyp-TFP (D−F), 766.3/807.4 for Hyp-TFP(O) (G−I), and 771.7/807.4 for Hyp-TFP(O2) (J−L.

Figure 3. Standard curves for absolute quantification of unmodified and modified peptides of α-fibrinogen. Serial dilutions of the peptides (10, 50, 100, 500, 1000, and 5000 fmol) and 500 fmol of internal standard peptide spiked into tryptic digests of standard human serum (0.2 μL) were analyzed by UPLC/MS/MS. Each data point represents the mean ± SD (n = 10−12) of data collected for 4 SRM/MRM transitions at 50−5000 fmol and 2−4 SRM/MRM transitions at 10 fmol in 3 experiments conducted on different days. Chromatograms of 50 fmol unlabeled peptides are shown in Supplemental Figure 1 in Supporting Information.

Validation of Proline-Hydroxylated α-Fibrinogen in Human Plasma

points for the target peak, as described in Experimental Procedures. The standard curve for each peptide spiked in tryptic digest of standard human serum (corresponding to 0.2 μL) is shown in Figure 3. The quantification range for all peptides was from 50 to 5000 fmol (minimum range among 4 sets of SRM/MRM transitions for each peptide), with an r2 value of more than 0.999. The values of %CV of slope were 17.4%, 7.31%, 15.1%, and 13.0% for ESS, Hyp-ESS, TFP, and Hyp-TFP, respectively (n = 12, 4 sets of SRM/MRM

To shorten the analysis time, the quantification method for the peptides was optimized using UPLC/MS/MS under the conditions described in Experimental Procedures, including gradient time and dwell time. The gradient time was shortened from 50 to 10 min and the total analysis time, including equilibration and washing, was shortened from 2 h to 28 min. The dwell time was set to give a sufficient number of data 757



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Furthermore, the sum of Hyp-ESS and ESS was not significantly different from that of Hyp-TFP and TFP in each of the 10 samples (p = 0.577). These results indicated that the established quantification method provides absolute levels of each peptide with sufficient reliability for marker validation.

transitions for each peptide in 3 experiments conducted on different days). Chromatograms of 50 fmol unlabeled peptides are shown in Supplemental Figure 1. Furthermore, to validate the simple preparation procedure with urea denaturation, as described in Experimental Procedures, quantification values of α-fibrinogen spiked in standard human serum were compared after the standard preparation procedure reported previously25 and the simpler preparation procedure. The quantitation ratio (standard preparation to simpler preparation) was 0.938 for ESS, 0.997 for Hyp-ESS, 1.20 for TFP, and 1.02 for Hyp-TFP; there was no significant difference between the two methods (n = 5). Moreover, the values of %CV of the quantification values among 5 experiments were 7.47%, 10.2%, 7.33%, and 15.0% for ESS, Hyp-ESS, TFP, and Hyp-TFP, respectively. Proline-hydroxylated α-fibrinogen was quantified in the plasma of 5 pancreatic cancer patients and 5 healthy controls using our established method (Figure 4). To validate the

Large-Scale Quantification of Proline-Hydroxylated α-Fibrinogen in Human Plasma

Proline-hydroxylated α-fibrinogen was quantified in 97 plasma samples from 70 pancreatic cancer patients and 27 healthy controls in order to validate Hyp-ESS and Hyp-TFP as pancreatic cancer biomarkers. Total α-fibrinogen was also quantified using GLI peptide, which is a tryptic peptide of αfibrinogen that has not been reported to contain PTMs (Table 2). As shown in Figure 5A, percent hydroxylation obtained for Hyp-ESS was well correlated with that obtained for Hyp-TFP (slope = 0.801, r2 = 0793, Figure 6A). Furthermore, the sum of Hyp-ESS + ESS and that of Hyp-TFP + TFP also coincided well with total α-fibrinogen determined using GLI peptide (slope values = 0.913 and 1.094, r2 = 0753 and 0619, respectively, Figure 5B,C). The ratios of Hyp-ESS + ESS/GLI and Hyp-TFP + TFP/GLI were 0.971 ± 0.116 and 1.23 ± 0.20 (mean ± SD), respectively. The percent hydroxylation and quantification values were compared between controls and patients. For both Hyp-ESS and Hyp-TFP, these values of the patients were significantly greater than those of the controls (Figure 6). Evaluation of Hyp-ESS and Hyp-TFP as Biomarkers

To assess proline-hydroxylated α-fibrinogen as a pancreatic cancer biomarker, ROC analysis was performed to evaluate biomarker performance and to calculate the threshold (Table 3 and Supplemental Figure 2). ROC curve analysis revealed that the percent hydroxylation and quantification values gave similar AUC values in the range from 0.650 to 0.689 (Table 3). Among them, the quantification value of Hyp-TFP gave the greatest AUC and odds ratio, which are lower than those of CA19-9 and DUPAN-2, but similar to or greater than those of CEA. To assess compensatory ability for CA19-9, the values of each marker in CA19-9-negative patients are listed in Table 4. Greater numbers of patients were positive for Hyp-ESS or Hyp TFP than CEA and DUPAN-2. Especially, in early stages I and II, the percent hydroxylation and quantification values of HypESS or Hyp-TFP were positive in 5 or 6 patients among the 8, while only one patient was positive for CEA and none was positive for DUPAN-2. This suggests that Hyp-ESS and HypTFP would be useful as pancreatic cancer markers in CA19-9negative patients.

Figure 4. Quantification of nonproline-hydroxylated (ESS and TFP) and proline-hydroxylated (Hyp-ESS and Hyp-TFP) α-fibrinogen in plasma by LC/MS/MS (A and B) and immunoblotting (C). (A and B) Plasma (1 μL) was digested with trypsin. The digested samples corresponding to 0.2 μL plasma were oxidized with 10 mM H2O2 for 1 h and subjected to LC/MS/MS with SRM/MRM analysis. Each bar and line represent the mean ± SEM of data collected for 4 sets of SRM/MRM transitions. (C) The corresponding plasma samples were analyzed by immunoblotting with antibodies against Hyp-ESS peptide (Anti-Hyp-ESS) and α-fibrinogen (Anti-a-FG).

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DISCUSSION We have developed a quantification method specific for proline hydroxylation at residues 530 and 565 of α-fibrinogen by means of LC/MS/MS with SRM/MRM analysis. Each of these PTMs was validated as a biomarker for pancreatic cancer based on quantification of nearly 100 samples with the developed method. In the quantification of these PTMs, oxidation of methionine in the target peptides, TFP and Hyp-TFP, was expected to affect the quantification values. As shown in Figures 1 and 2, a pair of target tryptic peptides from the plasma sample contained partially oxidized methionine, whereas methionine was not oxidized in the synthesized unlabeled peptides. The different levels of oxidation result in inaccuracy of quantification values. For this reason, our reported in silico criteria exclude target peptides containing methionine.16 However, if

established SRM/MRM method, we selected typical high HypESS level patient plasma samples and typical low Hyp-ESS level control plasma samples based on the result of immunoblotting with an antibody specific for Hyp-ESS (Figure 4C). All four peptides from α-fibrinogen, Hyp-ESS, ESS, Hyp-TFP, and TFP, were quantified simultaneously in all 10 plasma samples. The quantified values of Hyp-ESS and total α-fibrinogen, estimated as the sum of Hyp-ESS and ESS, were well matched with the corresponding band intensities in immunoblots (Figure 4A,C). 758



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Figure 6. Comparison of percent hydroxylation (A) and quantification values (B) of proline-hydroxylated α-fibrinogen (Hyp-ESS and HypTFP) in plasma between pancreatic cancer patients and healthy controls. Box-and-whisker diagram showing the differences of percent hydroxylation and quantification values of Hyp-ESS and Hyp-TFP between healthy controls (n = 27) and pancreatic cancer patients (n = 70). Boxes represent the 25−75 percentile range with horizontal lines indicating the median values. Whiskers indicate 1.5 times the interquartile range from the boxes, and extreme data points are indicated.

Table 3. Receiver Operating Characteristics (ROC) Analysis of Markers for Pancreatic Cancera

CA19-9 CEA DUPAN-2 Hyp-ESS (%) Hyp-TFP (%) Hyp-ESS (value) Hyp-TFP (value)

Figure 5. Comparisons of percent hydroxylation between Hyp-ESS and Hyp-TFP (A), quantification values of Hyp-ESS + ESS and GLI (B), and quantification values of Hyp-TFP + TFP and GLI (C). The plasma samples of pancreatic cancer patients (n = 70) and healthy controls (n = 27) were analyzed by means of LC/MS/MS. Closed circles and open squares represent data of pancreatic cancer patients and healthy controls, respectively. Each data point represents the mean of data collected for 4 sets of SRM/MRM transitions. Percent hydroxylation was calculated as the percentage of hydroxylated αfibrinogen with respect to the sum of nonhydroxylated and hydroxylated α-fibrinogen (Hyp-ESS/(Hyp-ESS + ESS) or HypTFP/(Hyp-TFP + TFP)). r2 indicates the correlation coefficient of all data points.

sensitivity (%)

specificity (%)

odds ratio

37 U/mLb 2.5 ng/mLb 150 U/mLb 18%

75.7 64.3 62.9 68.6

96.3 59.3 100 59.3

22.7 1.58 1.69

0.668

23%

62.9

59.3

1.55

0.675

2.2 pmol/μL plasma 3.8 pmol/μL plasma

74.3

59.3

1.83

65.7

70.4

2.22

AUC

threshold

0.903 0.682 0.892 0.650

0.689

a

Thresholds for Hyp-ESS and Hyp-TFP were determined as the points with minimum distance from 100% sensitivity and 0% 1 − specificity in the ROC curve for pancreatic cancer patients (n = 70) against healthy controls (n = 27). AUC was the area under the ROC curve, and odds ratio was calculated as sensitivity (%)/(1 − specificity (%)). ROC curves were shown in Supplemental Figure 2 in Supporting Information. bThresholds for CA19−9, CEA and DUPAN-2 are standard values used in clinical diagnosis.

the present oxidation procedure is included, target peptides containing methionine can be selected. This is important for increasing the scope for applying SRM/MRM analysis for quantification of particular PTMs, since PTM protein quantification requires the selection of a tryptic peptide containing the PTM residue irrespective of the presence of methionine, as in the present case.

Sample preparation is a critical procedure for accurate quantification. Various procedures have been reported, 759



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induced in pancreatic cancer, and expression of PHD3 in tumor tissue was associated with a tendency for worse overall diseasespecific survival in pancreatic adenocarcinomas.33,34 Therefore, it remains possible that PHD1 and/or 3 are also involved in hydroxylation of ESS and TFP. Quantification values and percent hydroxylation of both Hyp-ESS and Hyp-TFP were greater in plasma of pancreatic cancer patients than in plasma of healthy controls (Figure 6). The previous report shown that the plasma level of fibrinogen is increased in pancreatic cancer patients, possibly due to the deposition of fibrinogen (fibrin) in tumor tissue.35 However, the range of plasma levels of total α-fibrinogen in healthy controls (Figure 5B and C, open squares) was as broad as that of patients (closed circles), and no significant difference was observed between them (p = 0.117). Fibrinogen is a complex of three proteins: α, β and γ-fibrinogen. The previous report measured whole fibrinogen, while we measured only αfibrinogen. In addition, proteomics analysis indicated that γfibrinogen is increased in serum of pancreatic cancer patients.36 Therefore the previous result likely reflects an increased level of γ-fibrinogen. Evaluation by ROC analysis revealed that the quantification values of Hyp-TFP gave a slightly higher score than CEA for pancreatic cancer. Biomarkers that would be available for diagnosis of CA19-9-negative pancreatic cancer are important to improve diagnosis. As shown in Table 4, all CA19-9 negative patients in late stages III and IV were positive for CEA, suggesting that CEA compensates for CA19-9 in late stages. However, in early stages I and II, neither CEA nor DUPAN-2 compensated for CA19-9, since only one patient was positive for CEA, and none for DUPAN-2. This result is consistent with a previous report that the values of CEA were significantly greater in later stages.37 In contrast, many of the early stage CA19-9 negative patients were positive in terms of quantification values and percent hydroxylation of either Hyp-ESS or Hyp-TFP (or both). Therefore, Hyp-ESS and/or Hyp-TFP might be effective markers to identify CA19-9negative early stage pancreatic cancer. Furthermore, the use of a combination of CA19-9 and Hyp-ESS and/or Hyp-TFP might improve the detection rate. In this regard, SRM/MRM analysis would be advantageous for diagnosis based on combinations of markers, because it is possible to quantify different molecules and different PTMs simultaneously.

Table 4. Levels of Markers in Plasma of CA19-9-Negative Pancreatic Cancer Patientsa

a

Values greater than the thresholds shown in Table 3 are marked in grey. Thresholds for Hyp-ESS and Hyp-TFP were determined as the points with minimum distance from 100% sensitivity and 0% (1 − specificity) in the ROC curve for pancreatic cancer patients (n = 70) against healthy controls (n = 27).

including denaturing with guanidine chloride, urea or heat, with or without liquid−liquid phase extraction, affinity precipitation and in-gel digestion.23,26−30 In the present case, it is important that α-fibrinogen should be completely digested and the procedure should be simple and short for diagnostic application. Hence, the target protein was simply denatured with urea, followed by addition of buffer and reagents, including trypsin, in the present study. The quantification values were validated by comparison with those obtained by SRM/MRM using a sample preparation procedure that had been validated with membrane proteins in our previous report.16 The simple sample preparation procedure described here should be applicable for high-throughput applications. The present method allowed us to quantify α-fibrinogen hydroxylated at the proline residue at position 530 by using Hyp-TFP, for which it has not so far been possible to prepare an antibody. This clearly illustrates the potential value of SRM/ MRM analysis in PTM research. The percent hydroxylation and quantification values of Hyp-TFP were generally similar to those of Hyp-ESS (Figures 4 and 5A), though in some samples there were differences in percent hydroxylation between HypTFP and Hyp-ESS (Figure 5A). This resulted in slight differences in ROC analysis (Table 3 and Supplemental Figure 2). These results indicate that proline residues in TFP and ESS may have been hydroxylated via similar mechanisms, but other factors also influence the extent of hydroxylation. There are two types of prolyl-4-hydroxylase, that is, collagen type (P4HA1, P4HA2, P4HA3 and P4HB) and HIF1 type (PHD1, PHD2 and PHD3).6 In a siRNA knockdown study, we previously showed that P4HA1 is involved in hydroxylation of ESS in hepatocellular carcinoma cells, among P4HA1, P4HA2, P4HB, and PHD2.11 P4HA1 is increased under hypoxic conditions31 and pancreatic cancer shows a high level of hypoxia.32 In addition, PHD1 and 3 were reported to be

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CONCLUSIONS We modified our previously developed LC/MS/MS method with SRM/MRM analysis for specific quantification of αfibrinogen hydroxylation at proline-530 and proline-565, and we quantified these PTMs as well as unmodified α-fibrinogen in 97 plasma samples from pancreatic cancer patients and controls in order to validate these PTMs as biomarkers. The results indicate that these PTMs are available as biomarkers of pancreatic cancer, and would be especially useful for identifying CA19-9-negative early stage cancer. Multiple-marker quantification by SRM/MRM analysis might be an effective strategy to improve cancer diagnosis.

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ASSOCIATED CONTENT

S Supporting Information *

Additional materials as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org. 760



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of HIF-alpha to the von Hippel-Lindau ubiquitylation complex by O2regulated prolyl hydroxylation. Science 2001, 292 (5516), 468−72. (8) Qi, H. H.; Ongusaha, P. P.; Myllyharju, J.; Cheng, D.; Pakkanen, O.; Shi, Y.; Lee, S. W.; Peng, J. Prolyl 4-hydroxylation regulates Argonaute 2 stability. Nature 2008, 455 (7211), 421−4. (9) Lopez-Vera, E.; Walewska, A.; Skalicky, J. J.; Olivera, B. M.; Bulaj, G. Role of hydroxyprolines in the in vitro oxidative folding and biological activity of conotoxins. Biochemistry 2008, 47 (6), 1741−51. (10) Ono, M.; Shitashige, M.; Honda, K.; Isobe, T.; Kuwabara, H.; Matsuzuki, H.; Hirohashi, S.; Yamada, T. Label-free quantitative proteomics using large peptide data sets generated by nanoflow liquid chromatography and mass spectrometry. Mol. Cell. Proteomics 2006, 5 (7), 1338−47. (11) Ono, M.; Matsubara, J.; Honda, K.; Sakuma, T.; Hashiguchi, T.; Nose, H.; Nakamori, S.; Okusaka, T.; Kosuge, T.; Sata, N.; Nagai, H.; Ioka, T.; Tanaka, S.; Tsuchida, A.; Aoki, T.; Shimahara, M.; Yasunami, Y.; Itoi, T.; Moriyasu, F.; Negishi, A.; Kuwabara, H.; Shoji, A.; Hirohashi, S.; Yamada, T. Prolyl 4-hydroxylation of alpha-fibrinogen: a novel protein modification revealed by plasma proteomics. J. Biol. Chem. 2009, 284 (42), 29041−9. (12) Fan, H.; Li, R.; Gu, Y.; Si, D.; Liu, C. Quantitation of bentysrepinine (Y101) in rat plasma by liquid chromatography tandem mass spectrometry: application to pharmacokinetic study. J. Chromatogr., B: Anal. Technol. Biomed. Life Sci. 2012, 889−890, 103−9. (13) Keshishian, H.; Addona, T.; Burgess, M.; Kuhn, E.; Carr, S. A. Quantitative, multiplexed assays for low abundance proteins in plasma by targeted mass spectrometry and stable isotope dilution. Mol. Cell. Proteomics 2007, 6 (12), 2212−29. (14) Andersen, J. S.; Wilkinson, C. J.; Mayor, T.; Mortensen, P.; Nigg, E. A.; Mann, M. Proteomic characterization of the human centrosome by protein correlation profiling. Nature 2003, 426 (6966), 570−4. (15) Zhang, G.; Fang, B.; Liu, R. Z.; Lin, H.; Kinose, F.; Bai, Y.; Oguz, U.; Remily-Wood, E. R.; Li, J.; Altiok, S.; Eschrich, S.; Koomen, J.; Haura, E. B. Mass spectrometry mapping of epidermal growth factor receptor phosphorylation related to oncogenic mutations and tyrosine kinase inhibitor sensitivity. J. Proteome Res. 2011, 10 (1), 305−19. (16) Kamiie, J.; Ohtsuki, S.; Iwase, R.; Ohmine, K.; Katsukura, Y.; Yanai, K.; Sekine, Y.; Uchida, Y.; Ito, S.; Terasaki, T. Quantitative atlas of membrane transporter proteins: development and application of a highly sensitive simultaneous LC/MS/MS method combined with novel in-silico peptide selection criteria. Pharm. Res. 2008, 25 (6), 1469−83. (17) Ohtsuki, S.; Uchida, Y.; Kubo, Y.; Terasaki, T. Quantitative targeted absolute proteomics-based ADME research as a new path to drug discovery and development: methodology, advantages, strategy, and prospects. J. Pharm. Sci. 2011, 100 (9), 3547−59. (18) Matsubara, J.; Honda, K.; Ono, M.; Sekine, S.; Tanaka, Y.; Kobayashi, M.; Jung, G.; Sakuma, T.; Nakamori, S.; Sata, N.; Nagai, H.; Ioka, T.; Okusaka, T.; Kosuge, T.; Tsuchida, A.; Shimahara, M.; Yasunami, Y.; Chiba, T.; Yamada, T. Identification of adipophilin as a potential plasma biomarker for colorectal cancer using label-free quantitative mass spectrometry and protein microarray. Cancer Epidemiol., Biomarkers Prev. 2011, 20 (10), 2195−203. (19) Murakoshi, Y.; Honda, K.; Sasazuki, S.; Ono, M.; Negishi, A.; Matsubara, J.; Sakuma, T.; Kuwabara, H.; Nakamori, S.; Sata, N.; Nagai, H.; Ioka, T.; Okusaka, T.; Kosuge, T.; Shimahara, M.; Yasunami, Y.; Ino, Y.; Tsuchida, A.; Aoki, T.; Tsugane, S.; Yamada, T. Plasma biomarker discovery and validation for colorectal cancer by quantitative shotgun mass spectrometry and protein microarray. Cancer Sci, 2011, 102 (3), 630−8. (20) Mawuenyega, K. G.; Kaji, H.; Yamuchi, Y.; Shinkawa, T.; Saito, H.; Taoka, M.; Takahashi, N.; Isobe, T. Large-scale identification of Caenorhabditis elegans proteins by multidimensional liquid chromatography-tandem mass spectrometry. J, Proteome Res, 2003, 2 (1), 23− 35.

AUTHOR INFORMATION

Corresponding Author

*Address: Department of Pharmaceutical Microbiology, Faculty of Life Sciences, Kumamoto University, 5-1 Oehonmachi, Chuo-ku, Kumamoto 862-0973, Japan. Tel: +8196-371-4323. Fax: +81-96-371-4329. E-mail: sohtsuki@ kumamoto-u.ac.jp. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS

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REFERENCES

We thank Ms. Ayako Ikarashi, Ms. Tomoko Umaki and Ms. Yuka Nakamura for their technical assistance, Dr. Kazufumi Honda, Dr. Shoji Nakamori, Dr. Takuji Okusaka, Dr. Tomoo Kosuge, Dr. Naohiro Sata, Dr. Hideo Nagai, Dr. Tatsuya Ioka, Dr. Sachiko Tanaka, Dr. Akihiko Tsuchida, Dr. Tatsuya Aoki, Dr. Masashi Shimahara, Dr. Yohichi Yasunami, Dr. Takao Itoi and Dr. Fuminori Moriyasu for sample collection, and Dr. Akitomo Miyamoto for providing the antibody for proline-565hydroxylated tryptic peptide of α-fibrinogen. This study was supported in part by the Industrial Technology Research Grant Program from the New Energy and the Industrial Technology Development Organization of Japan, and the Funding Program for Next Generation World-Leading Researchers by the Cabinet Office, Government of Japan. This study was also supported by the Program for Promotion of Fundamental Studies in Health Sciences conducted by the National Institute of Biomedical Innovation of Japan and the Third-Term Comprehensive Control Research for Cancer, Research on Biological Markers for New Drug Development and Health Labour Sciences Research Grant by the Ministry of Health, Labour and Welfare of Japan. These sponsors had no role in the design of the study, collection of the data, analysis or interpretation of the data, decision to submit the manuscript for publication, or writing of the manuscript.

(1) Zhang, J.; Guy, M. J.; Norman, H. S.; Chen, Y. C.; Xu, Q.; Dong, X.; Guner, H.; Wang, S.; Kohmoto, T.; Young, K. H.; Moss, R. L.; Ge, Y. Top-down quantitative proteomics identified phosphorylation of cardiac troponin I as a candidate biomarker for chronic heart failure. J. Proteome Res. 2011, 10 (9), 4054−65. (2) Ogata, Y.; Heppelmann, C. J.; Charlesworth, M. C.; Madden, B. J.; Miller, M. N.; Kalli, K. R.; Cilby, W. A.; Bergen, H. R., 3rd; Saggese, D. A.; Muddiman, D. C. Elevated levels of phosphorylated fibrinogenalpha-isoforms and differential expression of other post-translationally modified proteins in the plasma of ovarian cancer patients. J. Proteome Res. 2006, 5 (12), 3318−25. (3) Polanski, M.; Anderson, N. L. A list of candidate cancer biomarkers for targeted proteomics. Biomarker Insights 2007, 1, 1−48. (4) Siegel, R.; DeSantis, C.; Virgo, K.; Stein, K.; Mariotto, A.; Smith, T.; Cooper, D.; Gansler, T.; Lerro, C.; Fedewa, S.; Lin, C.; Leach, C.; Cannady, R. S.; Cho, H.; Scoppa, S.; Hachey, M.; Kirch, R.; Jemal, A.; Ward, E. Cancer treatment and survivorship statistics. CA Cancer J. Clin. 2012, 62 (4), 220−41. (5) Ballehaninna, U. K.; Chamberlain, R. S. Serun CA 19-9 as a biomarker for pancreatic cancerA comprehensive review. Indian J. Surg. Oncol. 2011, 2 (2), 88−100. (6) Gorres, K. L.; Raines, R. T. Prolyl 4-hydroxylase. Crit. Rev. Biochem. Mol. Biol. 2010, 45 (2), 106−24. (7) Jaakkola, P.; Mole, D. R.; Tian, Y. M.; Wilson, M. I.; Gielbert, J.; Gaskell, S. J.; Kriegsheim, A.; Hebestreit, H. F.; Mukherji, M.; Schofield, C. J.; Maxwell, P. H.; Pugh, C. W.; Ratcliffe, P. J. Targeting 761



Article

(21) Ji, J. A.; Zhang, B.; Cheng, W.; Wang, Y. J. Methionine, tryptophan, and histidine oxidation in a model protein, PTH: mechanisms and stabilization. J. Pharm. Sci. 2009, 98 (12), 4485−500. (22) Zong, W.; Liu, R.; Wang, M.; Zhang, P.; Sun, F.; Tian, Y. The oxidative products of methionine as site and content biomarkers for peptide oxidation. J, Pept, Sci, 2010, 16 (3), 148−52. (23) Kawakami, H.; Ohtsuki, S.; Kamiie, J.; Suzuki, T.; Abe, T.; Terasaki, T. Simultaneous absolute quantification of 11 cytochrome P450 isoforms in human liver microsomes by liquid chromatography tandem mass spectrometry with in silico target peptide selection. J. Pharm. Sci. 2011, 100 (1), 341−52. (24) Fusaro, V. A.; Mani, D. R.; Mesirov, J. P.; Carr, S. A. Prediction of high-responding peptides for targeted protein assays by mass spectrometry. Nat. Biotechnol. 2009, 27 (2), 190−8. (25) Ohtsuki, S.; Schaefer, O.; Kawakami, H.; Inoue, T.; Liehner, S.; Saito, A.; Ishiguro, N.; Kishimoto, W.; Ludwig-Schwellinger, E.; Ebner, T.; Terasaki, T. Simultaneous absolute protein quantification of transporters, cytochromes P450, and UDP-glucuronosyltransferases as a novel approach for the characterization of individual human liver: comparison with mRNA levels and activities. Drug Metab. Dispos. 2012, 40 (1), 83−92. (26) Kawakami, H.; Kamiie, J.; Yasuno, K.; Kobayashi, R.; Aihara, N.; Shirota, K. Dynamics of absolute amount of nephrin in a single podocyte in puromycin aminonucleoside nephrosis rats calculated by quantitative glomerular proteomics approach with selected reaction monitoring mode. Nephrol. Dial. Transplant. 2012, 27 (4), 1324−30. (27) Kuhn, E.; Wu, J.; Karl, J.; Liao, H.; Zolg, W.; Guild, B. Quantification of C-reactive protein in the serum of patients with rheumatoid arthritis using multiple reaction monitoring mass spectrometry and 13C-labeled peptide standards. Proteomics 2004, 4 (4), 1175−86. (28) Wang, M. Z.; Wu, J. Q.; Dennison, J. B.; Bridges, A. S.; Hall, S. D.; Kornbluth, S.; Tidwell, R. R.; Smith, P. C.; Voyksner, R. D.; Paine, M. F.; Hall, J. E. A gel-free MS-based quantitative proteomic approach accurately measures cytochrome P450 protein concentrations in human liver microsomes. Proteomics 2008, 8 (20), 4186−96. (29) Langenfeld, E.; Zanger, U. M.; Jung, K.; Meyer, H. E.; Marcus, K. Mass spectrometry-based absolute quantification of microsomal cytochrome P450 2D6 in human liver. Proteomics 2009, 9 (9), 2313− 23. (30) Ciccimaro, E.; Hanks, S. K.; Yu, K. H.; Blair, I. A. Absolute quantification of phosphorylation on the kinase activation loop of cellular focal adhesion kinase by stable isotope dilution liquid chromatography/mass spectrometry. Anal. Chem. 2009, 81 (9), 3304−13. (31) Fahling, M.; Mrowka, R.; Steege, A.; Nebrich, G.; Perlewitz, A.; Persson, P. B.; Thiele, B. J. Translational control of collagen prolyl 4hydroxylase-alpha(I) gene expression under hypoxia. J. Biol. Chem. 2006, 281 (36), 26089−101. (32) Koong, A. C.; Mehta, V. K.; Le, Q. T.; Fisher, G. A.; Terris, D. J.; Brown, J. M.; Bastidas, A. J.; Vierra, M. Pancreatic tumors show high levels of hypoxia. Int. J .Radiat. Oncol. Biol. Phys. 2000, 48 (4), 919−22. (33) Su, Y.; Loos, M.; Giese, N.; Hines, O. J.; Diebold, I.; Gorlach, A.; Metzen, E.; Pastorekova, S.; Friess, H.; Buchler, P. PHD3 regulates differentiation, tumour growth and angiogenesis in pancreatic cancer. Br. J. Cancer 2010, 103 (10), 1571−9. (34) Gossage, L.; Zaitoun, A.; Fareed, K. R.; Turley, H.; Aloysius, M.; Lobo, D. N.; Harris, A. L.; Madhusudan, S. Expression of key hypoxia sensing prolyl-hydroxylases PHD1, -2 and -3 in pancreaticobiliary cancer. Histopathology 2010, 56 (7), 908−20. (35) Guo, Q.; Zhang, B.; Dong, X.; Xie, Q.; Guo, E.; Huang, H.; Wu, Y. Elevated levels of plasma fibrinogen in patients with pancreatic cancer: possible role of a distant metastasis predictor. Pancreas 2009, 38 (3), e75−9. (36) Bloomston, M.; Zhou, J. X.; Rosemurgy, A. S.; Frankel, W.; Muro-Cacho, C. A.; Yeatman, T. J. Fibrinogen gamma overexpression in pancreatic cancer identified by large-scale proteomic analysis of serum samples. Cancer Res. 2006, 66 (5), 2592−9.

(37) Ni, X. G.; Bai, X. F.; Mao, Y. L.; Shao, Y. F.; Wu, J. X.; Shan, Y.; Wang, C. F.; Wang, J.; Tian, Y. T.; Liu, Q.; Xu, D. K.; Zhao, P. The clinical value of serum CEA, CA19−9, and CA242 in the diagnosis and prognosis of pancreatic cancer. Eur. J. Surg. Oncol. 2005, 31 (2), 164− 9.

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