Glycosylation Changes in Serum Proteins Identify Patients with

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Glycosylation changes in serum proteins identify patients with pancreatic cancer Anna Drabik, Anna Bodzon-Kulakowska, Piotr Suder, Jerzy Silberring, Jan Kulig, and Marek Sierzega J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.6b00775 • Publication Date (Web): 28 Feb 2017 Downloaded from http://pubs.acs.org on March 1, 2017

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Journal of Proteome Research

Glycosylation changes in serum proteins identify patients with pancreatic cancer Anna Drabik1*, Anna Bodzon-Kulakowska1, Piotr Suder1, Jerzy Silberring1,2, Jan Kulig3, Marek Sierzega3 1 AGH University of Science and Technology, Krakow, Poland 2 Centre of Polymer and Carbon Materials, Polish Academy of Sciences, Zabrze, Poland 3 First Department of Surgery, Jagiellonian University Medical College, Krakow, Poland KEYWORDS: glycosylation, pancreatic cancer, HPT, LIFR, CE350, VP13A.

Abstract

After more than a decade of biomarker discovery using advanced proteomic and genomic approaches, very few biomarkers have been involved in clinical diagnostics. Most candidate biomarkers are focused on the protein component. Targeting posttranslational modifications (PTM’s) in combination with the protein sequences will provide superior diagnostic information in regards to sensitivity and specificity. Glycosylation is one of the most common and functionally important PTM’s. It plays a central role in many biological processes, including

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protein folding, host-pathogen interaction, immune response, and inflammation. Cancer associated aberrant glycosylation has been identified in various types of cancer. Expression of cancer-specific glycan epitopes represents an excellent opportunity for diagnostics and potentially specific detection of tumors. Here we report four proteins (LIFR, CE350, VP13A, HPT) found in sera from pancreatic cancer patients carrying aberrant glycan structures, as compared to controls.

INTRODUCTION Nature has created a very unique mechanism of communication much more complex than the alphabet we use. The identification system used for the proper recognition between cells or whole organisms is based on the combination of proteins and oligosaccharides fragments1. The reason for the complexity of glycosylation is not clear, but it seems that evolution has selected the most diverse molecules as the communication interface between cells and the extracellular environment. As with other major classes of macromolecules, the biological roles of glycoproteins span the spectrum from those that appear to be trivial, to those that are crucial for the organism development, growth, protection, maintenance of homeostasis or survival2. Glycoproteins have been extensively studied for the discovery of disease-specific modifications that can be used for both diagnosis and therapy monitoring3. Recent improvements in glycoprotein isolation techniques, bioinformatics, and mass spectrometry instrumentation have stimulated the subfield of proteomics known as glycoproteomic research4. Glycosylation plays an important role in the development and progression of human cancers4-6. During malignant transformation cells acquire properties enabling them dissociation from the primary tumor, degradation of the extracellular matrix, followed by invasion, adhesion, and metastasis to distant organs5. Therefore, alteration of tumor cell surface glycoproteins is one of


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the key mechanisms involved in developing malignant potential4. Moreover, alterations from the normal glycosylation pathways found in malignant cells are potentially related to the formation of novel, cancer specific glycan epitopes7. This poses a great opportunity for identification of novel diagnostic and therapeutic targets, including tumors of the digestive system8,9. There is, however a series of technical and biological obstacles in the emerging assays that reflect the potential glycoprotein biomarker. We believe that mass spectrometry (MS) is the most promising tool for detection and quantification of protein changes in cancer, and the results of such discoveries can be translated into clinic3. Pancreatic cancer is the fourth leading cause of cancer deaths in the US with the worst prognosis among all cancers9. This poor survival rate is mostly due to the lack of a reliable early detection method. Consequently, most patients are diagnosed with either locally advanced or metastatic disease that precludes radical treatment9. Unfortunately, a reliable blood marker with clinically acceptable sensitivity and specificity is still missing as the most commonly used serum-based marker (CA 19-9) demonstrates high false positive rates10. On the other hand, some early reports suggest that novel glycosylation-based assays may have much better diagnostic performance11,12. Therefore in the present study we investigated the serum N-glycome profiles of patients with pancreatic cancer and non-malignant controls to identify potential new biomarkers.

EXPERIMENTAL METHODS Sample collection The study population included 76 patients with treatment-naïve pancreatic cancer along with 26 age- and gender-matched controls treated for non-malignant chronic pancreatic disorders (chronic pancreatitis and pseudocysts). The study was approved by the Bioethics Committee of


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the Jagiellonian University and all participants gave their written consent on initial recruitment. The collected whole blood was allowed to clot for 60 minutes at room temperature and then samples were centrifuged for 10 minutes at 2000 x g at 4°C. The resulted supernatant was stored at -86°C in 1ml aliquots.

Immunodepletion Multiple Affinity Removal System MARS® HSA/IgG was purchased from Agilent (Agilent, USA). Depletion was performed at room temperature, according to the manufacturer’s protocol. Serum samples were diluted with the wash/load A buffer supplied by the manufacturer and the remaining particulates in diluted serum were removed with a 0.22 µm syringe filter. After equilibration with the 4 ml of A buffer, the MARS® HSA/IgG column was loaded with 200 µl of the filtered serum and centrifuged for 1.5 min at 100 x g. After washing twice the column with the 400 µl of buffer A, the flow-through fractions, representing depleted serum, were collected. The bound proteins were released with the 2 ml elution of B buffer using the Luer lock adapter and a syringe. The MARS® HSA/IgG column was re-equilibrated using syringe with 4 ml of A buffer and the following sample was immunodepleted.

Glycoprotein enrichment As

the purpose of those studies was to identify, using MS-based technique, the changes in N-

glycosylation profiles that are characteristic for proteins in pancreatic cancer, Phaseolus Vulgaris Leucoagglutinin Lectin PHA-L was selected. PHA-L specifically binds to the wide group of highly branched, type N-glycans that are representative for many tumor cells. Therefore such choice enables the enrichment of all kinds of complex N-glycoproteins and their further analysis


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using mass spectrometry technique. Immunodepleted serum samples were incubated with 50 µl PHA-L lectin linked to agarose (Vector Laboratories, USA) for 1 h at room temperature in the presence of 300 µl 10 mM HEPES buffer, pH 7.5 with 0.15 M NaCl (Sigma-Aldrich, Poland), and 0.1 mM CaCl2; 0.01 mM MnCl2 (Sigma-Aldrich, Poland), followed by 16 h incubation at 4°C. Subsequently, suspensions were centrifuged at 22,000 × g for 5 min at 4°C. Precipitates were washed three times with 1 ml of PBS (Sigma-Aldrich, Poland) followed by the incubation with 1ml of 100 mM acetic acid (Sigma-Aldrich, Poland) for 16 hours at 4°C. Eluted fractions were divided in two parts and evaporated to dryness in a vacuum centrifuge, one for further twodimensional capillary chromatography combined with tandem mass spectrometry approach, second for the electrophoretical separation followed by nanoLC-MS/MS analysis (Figure 1).

Figure1. Scheme of the workflow (Image courtesy of Anna Drabik. Copyright 2016).


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Two dimensional capillary chromatography combined with tandem mass spectrometry One set of dried samples, representative of each patient was prepared for 2D nanoLC-MS/MS analysis by dissolving in 20 µl 50 mM NH4HCO3, followed by addition of 5 µl 50 mM ditiotreitol DTT (Sigma-Aldrich, Poland) and 10 minutes incubation at 90°C. The reduced proteins were carbamidomethylated by addition of 5 µl 100 mM iodoacetamide (IAA) (SigmaAldrich, Poland) during incubation for 10 minutes at 90°C. Samples were divided into two separate Eppendorf tubes, and one of each was additionally treated with PNGase F (Promega, USA) for 2 hours at 37°C to cleave N-linked oligosaccharides. Subsequently, all samples were digested using 5 µl of 0.1 µg/µl trypsin (Promega, USA). The digestion was performed for 16 hours at 37°C. Subsequently, the samples were evaporated to dryness in a vacuum centrifuge. Finally, the resulting peptides were dissolved in 20 µl 0.1 % formic acid (Sigma-Aldrich, Poland). The 2D nanoLC-MS/MS analysis, used to separate the digests, was performed with the aid of the Proxeon nanocapillary chromatography system (Bruker Daltonics, Germany). The separation was performed in the first dimension in a capillary column filled with the SeQuant® ZIC®HILIC material (15 cm long, 75 µm ID, Merck, USA), and the PepMap reversed-phase material (15 cm long, 75 µm ID, C18, 3 µm particle size, 100 Å pore size, Thermo-Scientific, USA) in the second dimension. The gradient was formed using 0.1 % HCOOH in water (solvent A) and 0.1 % HCOOH in acetonitrile (solvent B), and it was delivered at a flow rate of 300 nl/min. The system was controlled by the Hystar software (Bruker Daltonics, Germany). A gradient was produced from 2 to 50 % B in 30 min and up to 90 % B at 35 min, then kept until 45 min, and again reduced to 2 % until 55 min. The chromatographic system was directly coupled to the Amazon ETD mass spectrometer (Bruker Daltonics, Germany). The instrument operated in a


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positive-ion mode. During analysis, two most intense peaks (threshold above 100,000) in the range 450–1800 m/z were automatically fragmented using both ETD and CID in the datadependent acquisition mode. Active exclusion parameters: exclude after 2 spectra with absolute intensity threshold over 250 000, and release after 1 minute. Charge state parameters: preferable charge state 2+ and 3+, however other charge states were not excluded. Reaction time for EDT was tuned automatically, based on the Ion Charge Control ICC target selection. For CID and ETD fragmentation techniques, ICC target was selected as 40 000. Accumulation time to achieve this number of ions entering the trap was less than 1ms. Trap drive was set as 35. Search parameters applied in the GlycoQuest were set as follows: minimal precursor m/z 600 Da; occurrence of oxonium ions (IonTrapOxoniumIons List) with absolute mass tolerance 0.3 Da; minimum intensity coverage 50%, distance-based glycopeptides pattern was established with the minimal number of consecutive m/z distances required 2; MS tolerance 0.3 Da; MS/MS tolerance 0.35 Da. Peptide mass offset 204.09 Da. The acquired spectra were analyzed using the Bruker Data Analysis 4.0 software and were identified using the Mascot 2.4.1 algorithm against the Swiss-Prot/TrEMBL sequence database 2012_03 (535248 sequences; 189901164 residues). Two technical replicates were run respectively. Search parameters were set as follows: taxonomy: human; modification: carbamidomethyl (fixed); methionine dioxidation (variable); up to 1 missed cleavage, peptide charges +1; +2, and +3; mass tolerance 0.8 Da for precursor mass, and 0.6 Da for fragment mass. Proteins with at least two fragmented unique peptides detected were considered, and an additional criterion was an ions score above 40, which is due to the level of false positive p≤ 0.05.

SDS-PAGE


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One-dimensional electrophoresis was performed. Thirty microliters of Laemmli sample buffer (Bio-Rad, USA) was added to the second set of the dried fraction obtained after PHA-L enrichment. Proteins were separated by the 10 % SDS-PAGE Mini Protean system, according to the Bio-Rad protocol. One part of the gel was stained with Coomassie Brilliant Blue G (CBB G) (Sigma-Aldrich, Poland) prior to nanoLC-MS/MS analysis, and the second part was electrotransferred onto the PVDF membrane (Bio-Rad, USA) to confirm the type of proteinlectin interactions.

Western blot analysis The presence of specific glycan epitopes, highly complex antennary N-oligosaccharides, was confirmed by the biotinylated PHA-L lectin (Vector Laboratories, USA). The blotted membranes were treated with casein solution (Vector Laboratories, USA) as a blocking agent for 1 h at room temperature, washed three times with Tris buffered saline (TBS; Sigma-Aldrich, Poland), and subsequently incubated with biotinylated PHA-L lectin for 2 h, according to the manufacturer’s recommendations. After extensive washes, the blots were incubated with alkaline phosphatase conjugated streptavidin (Vector Laboratories, USA) for 2 h with TBS supplemented with 0.1% Tween 20. Finally, the blots were visualized by alkaline phosphatase substrate kit II (Vector Laboratories, USA). Simultaneously, negative controls were included in the presence of lectin blocked with 100mM CH3COOH (Sigma-Aldrich, Poland) that is responsible for blocking glycan-binding sites on the receptor surface. The nonspecific interactions were not considered for further investigations (Figure 2).


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Figure 2. SDS-PAGE based approach for potential biomarker targeting.

Identification of N-glycoproteins The bands corresponding to specific lectin interactions on the PVDF membrane were excised from the CBB-stained gel with a scalpel, chopped into cubes, rinsed with water, and transferred to siliconized tubes. CBB stain was removed with 100 µl of 100 mM NH4HCO3 and an equal volume of acetonitrile was added after 10–15 min. Then, the gel pieces were treated with 100 µl of 100 % acetonitrile and re-swollen in 25 µl of 50 mM dithiothreitol DTT (Sigma-Aldrich, Poland), followed by 10 minutes incubation at 90°C. DTT solution was removed. Subsequently, the reduced proteins were carbamidomethylated by addition of 25 µl 100 mM iodoacetamide (IAA; Sigma-Aldrich, Poland) during incubation for 10 minutes at 90°C. Finally, 50 µl of 10 ng/µl trypsin (Promega, USA) in 50 mM NH4HCO3 were added and incubated on ice for 45 min. The supernatants, which were not absorbed by gel particles, were removed, and the gel pieces


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were immersed in 100 µl of 50 mM NH4HCO3 and incubated overnight at 37°C. After completion of digestion, the supernatants were transferred into another tube, followed by addition 100 µl of 50 mM NH4HCO3, and after 10–15 min, an equal volume of acetonitrile was added. The samples were incubated under shaking at 60°C for 10 min. Extraction of peptides was repeated twice with 5 % formic acid (v/v) in acetonitrile, and combined extracts were evaporated to dryness in a vacuum centrifuge. Prior the nanoLC-MS/MS analysis the peptides were resuspended in 20 µl 0.1 % formic acid (Sigma-Aldrich, Poland).

Capillary chromatography combined with tandem mass spectrometry The separation and identification was made under conditions corresponding to the secondary dimension of 2D nanoLC-MS/MS analyses, using the PepMap RP column (Thermo Scientific, USA) and the Proxeon/AmaZon (Bruker Daltonics, Germany). The acquired spectra were analyzed and searched using conditions described in paragraph “Two dimensional capillary chromatography combined with tandem mass spectrometry”. The molecular weight determined using SDS-PAGE band position was considered as an additional verification criterion to confirm proper identification using MS/MS technique for protein sequencing.

Data Processing Analysis of proteins and glycopeptides from 102 patients’ serum samples was obtained, including 76 cancer patients and 26 controls. In total, 3607 proteins were identified based on the selected criteria, therein 482 proteins differed with statistical significance among the studied groups based on the ProteinScape 3.1 software assessment (Bruker Daltonics, Germany) (Figure 3) (Associated Content available).


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Figure 3. Scheme representing the total number of identified proteins.

Data set collected during two-dimensional nanoLC-MS/MS analysis for each individual sample was combined using ProteinScape software and the Protein List Combination script. Subsequently, the results obtained for particular patients were paralleled across the Compare Search Results script. Final outcomes were analyzed based on the following principles: (i) only proteins identified in more than 50% of the samples (at least in 39 cancer patients and 14 controls); (ii) the N-glycan attachment localized in the consensus sequence (asparagine residue that is a part of Asn-X-Ser/Thr, where X is any amino acid except proline), and were considered for subsequent studies. Authentication of the collected results was accomplished using lectin affinity on PVDF membrane. Corresponding bands representing specific protein-lectin interactions only, were excised from CBB stained SDS-PAGE gels. Protein identification was performed against the Swiss-Prot database using identical searching criteria as for the two-dimensional nanoLCMS/MS analysis.

For detailed analyses of the dataset we used the GlycoQuest (Bruker Daltonics, Germany) application, and for the mining glycan array data, the GlycomeDB (Heildelberg, Germany)


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database was applied using parameters defined in paragraph two-dimensional nanoLC-MS/MS analysis. Concluding results correspond to the protein targets identified using both proteomic approaches.

RESULTS AND DISCUSSION Demographic and Clinical Characteristics of the Study Subjects Clinical and demographic data of the selected population are summarized in Table 1. Patient cohort closely reflects population of patients referred to surgical departments for suspected pancreatic cancer, and is similar to a ‘real life’ scenario commonly found in daily clinical practice. Such a group mostly consists of stage 2 cancers with much smaller proportions of stages 1, 3, and 4. As the purpose of this study was based on investigation for an overall but not stage-specific biomarker of pancreatic cancer, the differences in the distribution of patients across individual stages did not influence those findings. There were 66 males and 36 females with a median age of 59 years (range 21 to 83). There were no significant differences in age or gender between patients with pancreatic cancer and control subjects. Twenty-one patients with pancreatic cancer required endoscopic drainage of obstructive jaundice; however, their blood samples were collected after normalization of bilirubin levels.

Table 1. Baseline characteristics of the patients Pancreatic cancer

Controls

(n=76)

(n=26)

27:49

9:17

Variable

Gender (female : male)


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Pancreatic cancer

Controls

(n=76)

(n=26)

Age, median (IQR) yrs.

59 (46–67)

62 (51–69)

Diabetes mellitus, n (%)

27 (36)

9 (35)

head

53 (70)

NA

body and tail

23 (30)

Variable

Tumour location, n (%)

Tumour staging (AJCC 2010), n (%) I

8 (11)

II

50 (66)

III

12 (16)

IV

6 (7)

NA

AJCC – American Joint Committee on Cancer; IQR, interquartile range; NA, not applicable

Serum Glycoproteins of Patients with Pancreatic Cancer The purpose of this study was to determine putative glycan serum biomarkers of pancreatic cancer. PHA-L lectin enrichment and affinity binding on PVDF membranes combined with liquid-chromatography mass spectrometry were used to characterize alterations of the N-linked oligosaccharides structure of glycoproteins found in serum samples. Such a multi-step separation and identification procedure has been shown previously to allow the detailed characterization of glycan changes associated with human malignancies7,8,12. A total of 221 glycosylated proteins were found in sera collected from patients with pancreatic cancer. Four of them were identified in at least 50% of the cancer subjects and presented distinct glycosylation patterns absent in the controls, i.e. haptoglobin (HPT, n=52), leukemia inhibitory factor receptor (LIFR, n=47), centrosome-associated protein 350 (CE350, n=42), and vacuolar


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protein sorting-associated protein 13A (VP13A, n=41) (Table 2). Such qualitative differences provide convincing evidence for developing a diagnostic test suitable for differentiation of cancer patients from other individuals.

Table 2. Unique N-glycosylation sites found in pancreatic cancer serum

Haptoglobin


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Haptoglobin is involved in various aspects of the acute phase response, receptor mediated endocytosis, homeostasis, and in the positive regulation of cell apoptosis13 It is also one of the most commonly reported proteins affected by oligosaccharide modifications in human malignancies, including ovarian14 liver15-17, colon18, and pancreatic cancers19-21. In the latter case, increased fucosylation was demonstrated using various quantitative and qualitative methods, suggesting the presence of significantly fucosylated glycans particularly at N21119. In the present study, we found haptoglobin to be highly glycosylated at 241 asparagine side chain in patients with pancreatic cancer and this distinguished patients’ sera from control subjects.

Leukemia inhibitory factor receptor (LIFR) LIFR is a 124 kDa signal-transducing protein involved in the cell surface receptor signaling pathway22. The molecule participates in the regulation of cellular differentiation and survival acting as an inhibitor of apoptotic processes and promoter of cell proliferation23. LIFR plays important roles in various malignancies, including breast, colon, and pancreatic cancer23-25. However, despite potential importance of N-glycosylation of the receptor chain for its stability and function, little is known about changes typical for pancreatic cancer26,27. The present study identified a novel glycosylation site of LIFR (Figure 4)28. Additional carbohydrate structure was recognized at the 64 Asp residue of the transmembrane domain.


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Figure 4. Example of the MS/MS spectra based upon identification of the additionally recognized carbohydrate structure of protein.

Centrosome-associated protein 350 (CE350) CE350 is a 351 kDa protein necessary for anchoring microtubules to the centrosomes and for maintaining integrity of the microtubules network29-31. Therefore, it participates in many important processes, including cell replication and intracellular payload traffic. Since centrosome alterations were frequently reported in human tumors, CE350 is potentially associated with malignant progression31,32. However, there are no previous literature data on post-translational protein modification by glycosylation. In the present study glycosylation of CE350 was revealed for the first time at the 2336 Asp side chain in patients with pancreatic cancer and no such alterations were identified in controls.

Vacuolar protein sorting-associated protein 13A (VP13A) VP13A, called also chorein, is involved in the control of protein turnover and transport33. This protein was described to be associated with gastric cancer, especially with malignant


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progression, such as distant metastasis, lymph node metastasis, invasion depth, and advanced stage34. Despite the fact, that VP13A is a membrane component, there is no evidence for its glycosylation. Here we report attachment of the oligosaccharide structure, which was identified at the 877 residue of this 360 kDa protein.

Diagnostic performance of glycan biomarkers A total of 61 of 76 pancreatic cancer patients had two proteins with altered glycosylation profile in their sera. However, three or all four identified glycoproteins were found in 26 and 8 patients, respectively. A logistic regression model with backward stepwise selection was developed to evaluate the diagnostic potential of various glycosylation sites in discriminating pancreatic cancer from non-malignant disorders. The probability for entering the model was 0.05 and for removal from the model 0.100. The final model included HPT, CE350, and VP13A with odd ratios of 18.68 (95% CI 4.06–85.98, P

Glycosylation Changes in Serum Proteins Identify Patients with

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