Precise Mapping of Increased Sialylation Pattern ... - ACS Publications

Precise Mapping of Increased Sialylation Pattern and the Expression of Acute Phase Proteins Accompanying Murine Tumor Progression in BALB/c Mouse by Integrated Sera Proteomics and Glycomics Shu-Yu Lin,† Yi-Yun Chen,† Yao-Yun Fan,‡ Chia-Wei Lin,‡ Shui-Tsung Chen,‡ Andrew H.-J. Wang,*,†,‡ and Kay-Hooi Khoo*,†,‡ NRPGM Core Facilities for Proteomic Research, and Institute of Biological Chemistry, Academia Sinica, Nankang, Taipei 11529, Taiwan Received February 5, 2008

Inbred BALB/c mouse implanted with murine tumors serves as an attractive model system for the studies of cancer biology in immuno-competent individuals. It is anticipated that tumor progression would induce notable pathophysiological consequences, some of which manifested as alteration in serum proteomic and glycomic profiles. Similar to sera derived from human cancer patients and immunocompromised mice bearing human tumors, we show in this work that BALB/c mice of the same genetic background but bearing two distinct tumor origins both exhibited elevated expression levels of acute phase proteins including haptoglobin and serum amyloid P protein, in response to tumor progression. Such common traits are generally not informative nor qualifying as biomarkers. Additional mass spectrometry (MS)-based glycomic mapping nevertheless detected distinctive changes of sialylation pattern on the complex type N-glycans. MALDI MS/MS sequencing afforded a facile but definitive identificationofanincreaseininternalNeu5GcR2-6sialylationontheGlcNAcoftheNeu5Gc2-3Gal1-3GlcNAc terminal sequence as a common feature whereas a substitution of Neu5Gc by Neu5Ac was found to be induced by colonic but not breast tumor. A more pronounced change was similarly detected on N-glycans derived from ascitic fluids representing late tumor progression stages. We next demonstrated that such distinct change in glycotope expression can be localized to a particular protein carrier by LC-MS/MS analysis of glycopeptides. Serotransferrin was identified as one such abundant serum glycoprotein, which changed significantly not in protein expression level but in terminal glycosylation pattern. Keywords: mass spectrometry • serum proteomics • glycomics • acute phase proteins • ascitic fluids

Introduction Proteomic analyses of human serum in search of diagnostic and prognostic biomarkers for tumor bearing or disease states 1–3 are increasingly complemented by serum glycomics and/ or glycoproteomics for a systematic evaluation of changes in glycosylation profiles.4–6 This largely reflects two well-recognized facts, namely, most serum proteins are glycosylated and, more importantly, glyco-epitopes arising from aberrant glycosylation events are often implicated in malignant transformation and tumor progression.7,8 For example, increase in the serum level of sialyl Lewis X and A is known to correlate positively with colon and nonsmall cell lung cancer 9,10 and core R6-fucosylation with liver and pancreatic cancer.4,11–13 In most clinical and biomedical applications, detection of these terminal glyco-epitopes are based on lectins and/or mono* To whom correspondence should be addressed. Dr. Kay-Hooi Khoo, e-mail: [email protected]; or Dr. Andrew H.-J. Wang, e-mail: [email protected]; Institute of Biological Chemistry, Academia Sinica, 128, Academia Rd. Sec 2, Nankang, Taipei 11529, Taiwan. † NRPGM Core Facilities for Proteomic Research. ‡ Institute of Biological Chemistry. 10.1021/pr800093b CCC: $40.75

 2008 American Chemical Society

clonal antibodies, which are rapid and sensitive but can be compromised by cross-reactivities and lack of information with respect to the glycan and protein carriers. Several recent applications of mass spectrometry (MS)-based serum glycomics focusing on mapping the released total N-glycans have now demonstrated the feasibility of detecting glycosylation changes in sera from cancer patients.14–17 From these and other early studies, it is clear that N-glycans released from human sera are mostly dominated by high mannose and complex type bi- to tetra-antennary glycans with Neu5AcR2-3/ 6Galβ1-4GlcNAc (sialyl LacNAc) termini. The most cited alterations in the level of fucosylation and sialylation can be readily identified by the molecular mass information afforded by MS mapping, whereas a more precise delineation of the inferred epitopes especially with respect to the position and linkages can only be obtained through a second tier advanced MS/MS analysis. In principle, an MS/MS-based identification represents a more definitive glycomic approach, which parallels proteomics in allowing discovery of novel epitopes or biomarkers. A targeted glycoproteomic analysis can then be devised to localize the implicated epitopes onto one or more specific Journal of Proteome Research 2008, 7, 3293–3303 3293 Published on Web 06/13/2008

research articles protein carriers, which could itself be a relatively abundant serum protein. Numerous MS-based serum proteomic attempts in the past have failed to match the sensitivity of monoclonal antibodybased immuno-detection in identifying unique cancer markers, despite the promises it once held. Most commonly observed instead are increases in the more abundant acute phase proteins such as haptoglobin and serum amyloid A protein,18–21 irrespective of cancer types. This is equally true for human as well as mouse models in which the most widely investigated are the nude or SCID mice implanted with human tumors.20,22–24 The latter has been popular for the studies of tumor behavior since similar kind of experiments cannot be performed with human subjects. However, the immuno-compromised mice is expected to be deficient in mounting a normal kind of immune response. An alternative model is to use murine tumor implanted back to normal mice. This provides several attractive features for a true evaluation of tumor progression in an immuno-competent background. Although it does not substitute for studies in human, it has the advantage of eliminating substantial genetic and physiological variations among human subjects. To date, however, there has been a lack of report on such systems with respect to whether similar changes in the serum proteomic profiles are observed. Nor is it clear if unique glycan changes may be detected and how well it may serve as experimental model for human since distinct glycosylation patterns are known to be exhibited by human versus mice. We have initiated a complementary glycomic and proteomic analysis of sera from normal BALB/cJ mice and those implanted with two different kinds of mouse tumors to monitor the changes in serum glycoprotein profile as tumor progresses. We demonstrate that by first removing the abundant albumin, 1D gel coupled with MS-based proteomic analysis is a good and quick way of assessing the changes associated with some of the major serum acute phase proteins, which collectively represents a good indicator of cancer states or tumor bearing. Importantly, we show that changes in serum Neu5Gc-sialylation pattern, which are unique to mouse and not previously reported for human, can be critically established by parallel MALDI-MS-based glycomic analysis. Serotransferrin, an abundant serum glycoprotein was further identified as one of the distinctive protein carrier for the observed alteration in the sialylation profile, whereas haptoglobin was found to significantly increase in abundance in addition to carrying the implicated changes in glycosylation pattern.

Methods and Materials Mouse Serum Sample. For tumor progression in inbred mouse model, BALB/cJ mice (eight weeks, 25 g) were used. All animal experiments were carried out at the animal care facility of the Institute of Biological Chemistry at Academia Sinica. Pieces (3 mm) of mouse colon cancer (CT-26) and breast cancer (TSA) tumor-associated tissue were infiltrated into normal male and female mice inguinal lymph node, respectively. Serum from tumor-free mouse was collected before implantation as control and every week thereafter for rapid monitoring of changes by SDS-PAGE analyses. A total of 2 experimental sets (different lot, performed at different date) of 5 male mice were implanted with CT-26 tumor while another set of female mice were implanted with TSA. Four weeks after implantation, the size of tumor in the lymph node of CT-26 and TSA mouse model increased to an average of 17 and 19 mm, respectively. The CT-26 tumor metastasized to liver, kidney, and diaphragm, 3294

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Lin et al. whereas the TSA tumor metastasized to lung, liver, kidney, spleen, intestinal lymph, and diaphragm. Five weeks after implantation, serum and ascite samples were collected from surviving tumor-bearing mice for proteomic and glycomic analyses. Samples from 3 mice bearing a CT-26 tumor and one bearing a TSA tumor were analyzed in details. About 100-200 µL of blood samples were drawn into tubes and allowed to clot at room temperature for 30 min and kept overnight at 4 °C. For each proteomic and glycomic analyses, 20 µL of serum samples were subjected to albumin removal by the TCA/ acetone precipitation method described previously,25 which yielded about 100 µg total proteins as starting materials. Twenty microliters of ascitic fluid samples (out of ∼300 µL total) containing about 50 µg total protein were used for each glycomic analyses. Gel-Based Shotgun Proteomic Analyses. The precipitates and supernatants obtained from the modified TCA/acetone precipitation were analyzed by SDS-PAGE using 12.5% SDSPAGE in a Protean II cell (BioRad), with a loading of about 20 µg total protein per lane. After protein fixation for 1 h with 10% methanol containing 7% acetic acid, the gel was stained with SYPRO RUBY (Molecular Probes) for 3 h. Excess dye was washed out with 10% methanol containing 7% acetic acid and the gel was scanned by Typhoon 9200 (Amersham Biosciences). Excised protein bands were reduced, alkylated, and trypsindigested, as described previously,26 and subjected to parallel LC-ESI-MS and LC-MALDI-MS and MS/MS analyses. For LC-MALDI-MS/MS analysis, nanoLC separation was performed using an LC-Packings Ultimate integrated capillary HPLC system equipped with a Switchos valve switching unit (LC-Packings, Dionex). Eluent from the LC capillary column was channeled to the needle Tee of a robotic Probot micro fraction collector (LC-Packings, Dionex). MALDI-MS detection and MS/MS sequencing of peptides were performed on a 4700 Proteomics Analyzer (Applied Biosystems, Framingham, MA). The software was equipped with LC-MALDI features wherein all spots were regarded as one large sample spot set. Of each LC run, MS and MS/MS on the five most abundant precursors were conducted in positive ion mode. MS, used in reflectron mode, was used to scan an m/z range of 900-4000 with a fixed laser intensity and 1000 laser shots per spectrum. MS/MS was conducted using 1 kV collision energy and argon as collision gas. MS/MS was measured until a S/N ratio of 15 was obtained for at least 20 peaks in the spectrum. Data were processed using the 4700 Explorer software. The peak list files were used to query the Swiss-Prot database using the MASCOT (version 2.0) with the following parameters: peptide mass tolerance, 50 ppm; MS/MS ion mass tolerance, 0.25 Da; allowing up to one missed cleavage; variable modifications considered were methionine oxidation and cysteine carboxyamidomethylation and charge state from 2 to 3. The identification of proteins were based on at least two peptide matches, each with a score greater than 20, and considered as positive hits above significant level by Mascot. LC-ESI-MS detection and MS/MS sequencing of peptides were performed on a QSTAR XL (Applied Biosystems, Framingham, MA) MS system. TOF MS spectra and product ion spectra were acquired using the information dependent data acquisition (IDA) feature in the Analyst QS software. A 1-s survey MS spectrum was followed by up to three 2-s MS/MS spectral acquisitions of multiply charged precursor ions. Dynamic exclusion was used to prevent repeated MS/MS analyses of a given precursor within the next 120 s. All the data were acquired

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Serum Proteomics and Glycomics of Murine Tumor Progression

Figure 1. Schematic illustration of the parallel glycomic and proteomic workflow adopted in this work.

and processed using Analyst QS 1.1 with Bioanalyst 1.1 extension. Peak lists were generated from the LC-MS/MS data using the Mascot script within Analyst and used to query the SwissProt database by MASCOT (version 2.0). Search and protein identification criteria are as described above. Glycopeptide Analyses. Additional LC-ESI-MS/MS analyses of tryptic glycopeptides similarly extracted from excised protein bands of a separate loading of another 20 µg total protein on SDS-PAGE were performed on a Micromass Q-Tof Ultima API mass spectrometer fitted with a nano-LC sprayer, a PepMap C18 m-precolumn cartridge (5 µm, 300 µm id × 5 mm; Dionex, Sunnyvale, CA, USA), and an analytical C18 capillary column (15 cm × 75 µm id, packed with 5 µm, Zorbax 300 SB C18 particles; Micro-Tech Scientific, Vista, CA, USA), at a flow rate of 300 nL/min using a 60 min gradient of 5-80% acetonitrile in 0.1% formic acid. To facilitate identification of glycopeptides, automated MS/MS data dependent acquisition was operated under the Precursor Ion Discovery (PID) mode.27 In brief, alternate low (7 eV) and high (30 eV) collision energy LC-MS survey scans were employed to trigger MS/MS acquisition on the 5 most intense parent ions observed at the low energy survey scans when glycan-specific oxonium ion fragments, m/z 204.084 for HexNac+ and m/z 366.139 for HexHexNac+, were detected at the corresponding high energy scans. MS/MS acquisition on false positive was limited to single scan if the monitored oxonium ions were not afforded, so as to devote more analysis time on true positives. Glycomic Analysis. For glycomic analysis, 20 µL of TCAprecipitated serum samples or ascites were redissolved in 50 mM ammonium bicarbonate (pH 8.4), first reduced with dithiothreitol at 37 °C for 4 h, and then alkylated with iodoacetamide at room temperature for 4 h in the dark, followed by removal of excess reagents by passing through a Sep-Pak C8 cartridge (Waters). Sample was then digested with trypsin (Sigma) overnight at 37 °C. After brief boiling and cooling down, the glycopeptide and peptide mixtures were incubated with PNGase F (Roche) overnight at 37 °C and then passed through a C18 Sep-Pak cartridge (Waters) in 5% acetic acid, as described.28 Typically, 1/10th aliquots of the N-glycans collected in the flow through were permethylated using a modified NaOH/ DMSO method28 prior to MS analysis. For MALDI-TOF MS glycan profiling, 1/10th of the permethyl derivatives in acetonitrile were mixed 1:1 with 2,5-dihydroxybenzoic acid (DHB) matrix (10 mg/ml in acetonitrile), spotted on the target plate, air-dried, and recrystallized on-plate with acetonitrile. Data acquisition was performed manually on a benchtop M@LDI LR system (Micromass) operated in the reflectron mode. Additional 1/10th aliquots of the permethyl derivatives were further analyzed by MALDI-MS and MALDI-MS/MS on both Q-TOF Ultima MALDI (Water Micromass) and 4700 Proteomics Analyzer (Applied BIosystems) exactly as described before.29

Figure 2. 1D gel pattern of serum and ascitic proteins from BALB/c mice bearing tumors. Serum samples were first subjected to albumin removal by TCA/acetone precipitation. Only the 1D gel profiles for the precipitate fractions from tumor-free (Lane 1) and colonic tumor-bearing (Lane 2) mouse sera are shown. Ascites were additionally collected from mice bearing colonic (Lane 3) and breast (Lane 4) tumors and similarly analyzed for comparison. Major serum proteins within each band, as identified by MS/MS analysis, are compiled into Table 1. Further proteomic analysis of the individual bands afforded by the ascitices did not lead to identification of additional proteins that are not found in the sera.

Results A schematic illustration of the concerted proteomic and glycomic workflow as employed in this work is shown in Figure 1. Briefly, albumin-depleted sera collected from tumor bearing mice were used as the primary starting materials in essentially two parallel approaches. For glycomic mapping, N-glycans were released from in solution digested samples equivalent to about 100 µg total protein, permethylated and analyzed directly by MALDI-MS and CID MS/MS. For proteomic identification, 1D gel was used as a simple one-dimensional protein level fractionation. The resulting SDS-PAGE pattern was also found to be a sufficient first indication of changes in the serum proteomic expression pattern following tumor progression. Significant changes were observed starting from second or third weeks after tumor implantation but only samples from week 0 (normal control, before tumor implantation) and week 5 were further analyzed in details. Excised protein bands from a loading of approximately 20 µg total protein per lane were subjected to LC-MS/MS analysis initially for simple protein Journal of Proteome Research • Vol. 7, No. 8, 2008 3295

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Table 1. Proteomic Identification of Major Proteins in Serum Samples from Normal and Tumor-Bearing Mice by LC-MS/MS Analysis of Excised 1D Gel Protein Bands (Figure 2) normal band no.

1

2

3

4

5

6

7 8 9

10

11

12

3296

accession no.

(P11276) (Q61702) (Q61703) (Q07456) (P28665) (Q61838) (P28666) (QP35441) (P11276) (P06909) (Q61838) (P11276) (P28665) (P01027) (Q61838) (P28665) (P06909) (P11276) (QP35441) (P07759) (Q61147) (Q61838) (P07759) (Q61704) (Q07456) (P13635) (P07759) (Q61704) (Q61703) (Q07456) (Q61147) (P01027) (P11276) (Q61703) (P13635) (P01027) (O70362) (P20918) (Q921I1) (P07759) (P01873) (P01027) (P02772) (P23953) (P07724) (P07759) (P23953) (Q91X72) (O08677) (P01027) (Q61247) (Q921I1) (Q61838) (P01027) (P06399) (P07759) (P32261) (Q9QXC1) (Q01339) (P01878) (P07758) (P22599) (P07758) (P29699) (P06399) (P14480) (P01863) (P03987) (Q00897) (P09006) (P01027) (P01869) (P01868) (P02680)

protein name

mol. weighta

Fibronectin precursor Interalpha-trypsin inhibitor heavy chain H1 precursor Interalpha-trypsin inhibitor heavy chain H2 precursor AMBP protein precursor Murinoglobulin 1 precursor Alpha-2-macroglobulin precursor Murinoglobulin 2 precursor Thrombospondin 1 precursor Fibronectin precursor Complement factor H precursor Alpha-2-macroglobulin precursor Fibronectin precursor Murinoglobulin 1 precursor Complement C3 precursor Alpha-2-macroglobulin precursor Murinoglobulin 1 precursor Complement factor H precursor Fibronectin precursor Thrombospondin 1 precursor Serine proteinase inhibitor A3K precursor Ceruloplasmin precursor Alpha-2-macroglobulin precursor Serine proteinase inhibitor A3K precursor Interalpha-trypsin inhibitor heavy chain H3 precursor AMBP protein precursor Ceruloplasmin precursor Serine proteinase inhibitor A3K precursor Interalpha-trypsin inhibitor heavy chain H3 precursor Interalpha-trypsin inhibitor heavy chain H2 precursor AMBP protein precursor Ceruloplasmin precursor Complement C3 precursor Fibronectin precursor Interalpha-trypsin inhibitor heavy chain H2 precursor Ceruloplasmin precursor Complement C3 precursor Phosphatidylinositol-glycan-specific phospholipase D 1 precursor Plasminogen precursor Serotransferrin precursor Serine proteinase inhibitor A3K precursor Ig mu chain C region membrane-bound form Complement C3 precursor (HSE-MSF) alpha-fetoprotein precursor Liver carboxylesterase precursor Serum albumin precursor Serine proteinase inhibitor A3K precursor Liver carboxylesterase precursor Hemopexin precursor Kininogen precursor Complement C3 precursor (HSE-MSF) Alpha-2-antiplasmin precursor Serotransferrin precursor Alpha-2-macroglobulin precursor (Alpha-2-M) Complement C3 precursor Fibrinogen alpha/alpha-E chain precursor Serine proteinase inhibitor A3K precursor Antithrombin-III precursor Fetuin-B precursor Beta-2-glycoprotein I precursor Ig alpha chain C region Alpha-1-antitrypsin 1-1 precursor Alpha-1-antitrypsin 1-2 precursor Alpha-1-antitrypsin 1-1 precursor Alpha-2-HS-glycoprotein precursor Fibrinogen alpha/alpha-E chain precursor Fibrinogen beta chain precursor Ig gamma-2A chain C region, A allele Ig gamma-3 chain C region, membrane-bound form Alpha-1-antitrypsin 1-4 precursor Contrapsin-like protease inhibitor 6 precursor Complement C3 precursor Ig gamma-1 chain C region, membrane-bound form Ig gamma-1 chain C region secreted form Fibrinogen gamma chain precursor

272319 101020 105861 39045 165034 165723 162265 129451 272319 138992 165723 272319 165034 186365 165723 165034 138992 272319 129564 46850 121083 165723 46850 98915 39045 120764 46850 98915 105861 39045 121083 186365 272319 105861 120764 186365 93196


90723 76674 46850 52623 186365 67293 61102 68648 46850 61102 51308 73056 186365 54937 76674 165723 186365 86632 46850 51971 42685 38593 36852 45974 45886 45974 37302 86632 54269 36366 43901 45969 46622 186365 43359 35682 50600

scoreb

peptides matchedc

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*** ** *

** ** *

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*** **

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*

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* *

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*** ** ** ** *

** * * * *

tumor-bearing scoreb

peptides matchedc

*

*

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* * *** *** ** * * *** * ** ** * * **

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Serum Proteomics and Glycomics of Murine Tumor Progression Table 1. Continued

normal band no.

13

14

15 16 17

accession no.

(P01867) (P21614) (P07759) (Q61838) (P02680) (P01869) (P03987) (P07758) (P01869) (P14480) (O88947) (Q61646) (P06728) (P60710) (P01027) (Q60590) (P07724) (Q921I1) (P06399) (P14480) (Q61838) (Q06890) (Q61838) (P12246) (P06399) (P13020) (P97290)

protein name

mol. weighta

Ig gamma-2B chain C region, membrane-bound form Vitamin D-binding protein precursor Serine proteinase inhibitor A3K precursor Alpha-2-macroglobulin precursor Fibrinogen gamma chain precursor Ig gamma-1 chain C region, membrane-bound form Ig gamma-3 chain C region, membrane-bound form Alpha-1-antitrypsin 1-1 precursor Ig gamma-1 chain C region, membrane-bound form Fibrinogen beta chain precursor Coagulation factor X precursor Haptoglobin precursor Apolipoprotein A-IV precursor Actin, cytoplasmic 1 Complement C3 precursor Alpha-1-acid glycoprotein 1 precursor Serum albumin precursor Serotransferrin precursor Fibrinogen alpha/alpha-E chain precursor Fibrinogen beta chain precursor Alpha-2-macroglobulin precursor Clusterin precursor Alpha-2-macroglobulin precursor Serum amyloid P-component precursor Fibrinogen alpha/alpha-E chain precursor Gelsolin precursor Plasma protease C1 inhibitor precursor

44302 53565 76674 165723 50600 43359 43901 45974 43359 54269 53983 38727 45001 41710 186365 23880 68648 76674 86632 54269 165723 51623 165723 26230 86632 85888 55602

a Mol. weight refers to the molecular weight given in the database, as inferred from the gene sequence. as **, 50-100 as *. c Number of matched peptides are denoted: >10 as ***, 5-10 as **, 2-5 as *.

identification. Subsequently, the same in gel digested tryptic peptide pools from individual bands were subjected to targeted analysis of glycopeptides in order to localize the changes observed in the glycomic profile to individual glycoprotein carrier. As a consequence, the characteristic N-glycosylation pattern for a particular serum proteome was actually profiled and sequenced at both levels of released glycans and glycopeptides, from which corroborative evidence was derived for the identified changes. Proteomic Mapping. Albumin removal, along with several other most abundant serum proteins, is now commonly adopted as a first step in most serum proteomic studies.30–32 In our studies, we have adopted a simple trichloroacetic acid/ acetone precipitation method, which resulted in most serum proteins being precipitated while the albumin was collected in the supernatant.25 On the basis of protein staining intensity by 1D gel analysis, the recovery of albumin in the supernatant fraction was found to be decreasing in sera from tumor-bearing mice relative to that from normal mice (data not shown). This observation appears to be in accord with albumin being recognized as a negative acute-phase protein in mice, namely, its serum level would significantly decrease during inflammation.33 For the precipitates, 1D gel pattern shows that most protein bands were reproducibly identified in the sera from mice not bearing and bearing tumors for 5 weeks (Figure 2, Table 1), but with apparent change in expression level. Among the major proteins identified by LC-MS/MS analysis, haptoglobin (band 14) stands out as one representative protein that was identified only in the serum samples from tumor-bearing mice. In contrast, gelsolin (band 17), an Actin-binding protein that was located both intracellularly and extracellularly in blood plasma, represents one major protein that was identified only in serum samples from nontumor bearing mice. Similar changes in band pattern was observed for the serum samples derived from mice bearing two different tumor origins (data

scoreb

b

peptides matchedc

**

*

**

**

*** *

** *

tumor-bearing scoreb

peptides matchedc

** ** ** * ** * * ** * * * *** *** ** *** ** ** * * * * * ** *** *

* * * * * * * ** * * * *** ** * *** * * * * * * * ** ** *

Total Score is denoted >300 as ***, 100-300

shown for colonic tumor only, Figure 2, left panel). Likewise, a side-by-side comparison for the two samples derived from the ascitic fluids of mice bearing the two different tumors also revealed little significant difference (Figure 2, right panel). The proteomic data therefore show that, without extensive fractionation and focusing only on the major proteins, alteration in serum proteomic expression level mapped mainly to a few well-recognized acute phase proteins, which do not constitute specific biomarker for different cancer types. Glycomic Mapping. It is well-known that the N-glycosylation pattern of some of these serum acute phase proteins also changes following tumor progression in cancer patients and during experimental inflammation in mice.34–36 We therefore sought to determine if a global change can be readily detected at the glycomic level for the serum samples derived from mice bearing tumor, in comparison with those of normal mice, as well as those from the ascites. The enzymatically released N-glycan pools from a total of about 100 µg serum protein after albumin removal were subjected to permethylation and directly profiled by MALDI MS analysis, followed by manual MALDI CID MS/MS sequencing on selected peaks to confirm the structural assignment, especially with respect to the location of sialylation and fucosylation. As expected, the overall MS profile of the serum N-glycans from normal mice comprises mainly nonfucosylated, bi-, tri and tetra-antennary complex type structures, each with fully monosialylated antenna (Figure 3A). Single degree of fucosylation can be detected at variable level relative to the intensity of the more abundant nonfucosylated counterparts and shown by MS/MS to be core fucosylated (Figure 3B). Notably, the mouse serum N-glycans differ from those of human in carrying almost exclusively Neu5Gc instead of Neu5Ac sialylation and that a significant proportion additionally contains Neu5Gcdisialylated antenna. An increased level of this disialylated antennae was found to be the most distinctive change induced Journal of Proteome Research • Vol. 7, No. 8, 2008 3297

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Figure 3. MALDI-MS profiles of permethylated N-glycans from the sera of normal BALB/c mice (A), and mice harboring colonic tumor (B), in direct comparison with the corresponding glycomic profiles of the ascitic fluids from mice bearing the same colonic tumor (C), or breast tumor (D). The glycomic profile of sera from mice bearing breast tumor is similar to that shown in (D). Assignments of the major peaks are as annotated, and in the case of additional sialylation, the location of the disialylated antennae was not further defined. The Neu5Ac/Neu5Gc heterogeneity is defined by mass difference of 30 units. The changes in the serum glycosylation pattern became most apparent 5 weeks after tumor implantation, whereas ascitic fluids were collected only at a late stage of tumor progression. Symbols used: [, Neu5Gc; b, Hex (light for Gal and dark for Man respectively but not distinguishable by MS); 9, GlcNAc; 1, Fuc.

by tumor bearing, in both colonic and breast tumor experimental models (Figure 3B-D). Interestingly, only the serum and ascitic N-glycans from colonic tumor bearing mice (Figure 3B,C) additionally exhibited significant substitution of Neu5Gc by Neu5Ac, which implicates a down regulated or impaired functioning of the CMP-Neu5Ac hydroxylase.37 In the MALDI mass spectra of permethylated glycans, the additional presence of Neu5Ac in place of Neu5Gc contributes to peaks at 30 mass units lower, which can be readily detected (Figure 3B,C) and further confirmed by MS/MS analysis (Figure 4A). The disialylated antenna can likewise be unambiguously identified (Figure 4C-E) and the absence of fragment ions corresponding to Neu5Gc-Neu5Gc would imply that disialylation was not due to Neu5GcR2-8 addition to the terminal Neu5Gc. Instead, the extra sialylation was confined to the HexHexNAc sequence. This is positively established by high energy CID MALDI MS/MS analysis, which produced a characteristic D ion at m/z 659, corresponding to a -(Neu5Gc-6)3HexNAcmotif29 (Figure 4E). Collectively, the MS/MS data is consistent withhavinganincreaseintheexpressionoftheNeu5GcR2-3Galβ1(Neu5GcR2-6)3GlcNAc disialylated terminal sequence. In the case of biantennary N-glycans, the molecular ion corresponding to [M+Na]+ of a trisialylated structure (m/z 3242) with one 3298


disialylated antennae was significantly enhanced in intensity relative to the disialylated structure (m/z 2851), whereas the molecular ion corresponding to tetra-sialylated biantennary glycans (m/z 3633) with both antenna being disialylated was detected only in the N-glycan samples from the sera and ascitic fluids of tumor-bearing mice (Figure 3). The enhanced expression of the disialylated antenna is consistently found to be more pronounced in ascites relative to sera. Likewise, more Neu5Ac was found to substitute for Neu5Gc in ascitic samples such that fully Neu5Gc sialylated species (m/z 2851, 3243, 3633) no longer represents the most abundant peaks (Figure 3C). Identification of Representative Protein Carriers for Implicated Glycotopes. Although the disialylated antenna sequence, Neu5GcR2-3Galβ1-3(Neu5GcR2-6)GlcNAcβ1-, is not a common structure occurring on human serum glycoproteins, it has previously been rigorously characterized for mouse serotransferrin.38 In that work, exclusively Neu5Gc disialylated antennae was found to occur on one of the two antenna of the biantennary N-glycans. Seeking evidence if what was currently demonstrated by glycomic mapping would translate into changes carried by any of the more abundant serum glycoproteins, the tryptic peptides from the 1D gel band corresponding to serotransferrin was subjected to selective


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Figure 4. Representative MALDI CID MS/MS analysis of the permethylated N-glycans from the sera and ascitic fluids of normal mice and those bearing tumors. The sodiated molecular ions selected for MS/MS analysis in the spectra shown correspond to (A) biantennary N-glycan sialylated with one Neu5Gc and one Neu5Ac at m/z 2822; (B) fully Neu5Gc-sialylated, core fucosylated biantennary N-glycan at m/z 3026; (C) Neu5Gc trisialylated biantennary N-glycan at m/z 3243; and (D, E) Neu5Gc tetra-sialylated biantennary N-glycan at m/z 3634. All spectra shown are obtained at low energy CID on MALDI Q/TOF except (E) which was obtained at high energy CID on MALDI TOF/TOF to additionally define the location of the additional sialylation. Fragmentation characteristics are as reported previously.29 The critical ions that would establish the presence of Neu5Ac versus Neu5Gc in (A), core fucosylation in (B), mono- versus disialylated antenna in (C), and the nonreducing terminal epitopes are as annotated. In (E), the G ion at m/z 3182 and the D ion at m/z 659 establish the Neu5Gc-3Gal and Neu5Gc-6GlcNAc linkages, respectively, for the disialylated antenna. Symbols used are as defined in Figure 3.

glycopeptide analysis, under Precursor Ion Discovery (PID) mode. Another commonly implicated human serum marker for glycosylation changes in disease, haptoglobin,39–41 was similarly investigated. Under PID, the data-dependent ESI-MS/MS acquisition during an LC-MS run will be triggered when the glycan specific oxonium ions (m/z 204, 366)42 were detected by preceding MS survey scans at alternating low and high CID energy settings.27 The built-in feedback loop that would terminate MS/MS acquisition if the first scan failed to produce the monitored oxonium ions would restrict analysis time mostly to true positive, that is, the glycopeptides. As shown in Figure 5, the glycopeptides of serotransferrin were

successfully detected and several among the glycoforms were selected for automated MS/MS acquisition (Figure 6). Based on the expected m/z values for the tryptic peptides carrying the N-glycosylation site, 498FDEFFSQGCamAPGYEKNSTLCamDLCamIGPLK525 (3252.46 Da), the relevant quadruply charged major molecular ion signals can be assigned as carrying a Neu5Gc-disialylated biantennary glycan (m/z 1373.3), with additional core fucosylation (m/z 1409.8), extra NeuGc sialylation (m/z 1450.0), or both (m/z 1486.8). Upon MS/MS analysis, all yielded a common peptide core + GlcNAc fragment ion at m/z 1152.9 (3+) and 1728.7 (2+), along with a series of fragment ions resulting from loss of various glycosyl residues via glycosidic cleavages (Figure 6). Journal of Proteome Research • Vol. 7, No. 8, 2008 3299

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Figure 5. Serotransferrin glycopeptide profiles derived from sera of tumor-free normal mice (A) and those bearing colonic tumors (B), as detected by nanoLC-nanoESI-MS analysis of the tryptic digests of the corresponding SDS-PAGE protein band. MS survey scans acquired under low CID energy were summed over the total time span during which the designated glycopeptide signals eluted. The doubly charged peptide signal at m/z 1371.1, indicated with an asterisk, can be easily distinguished from all other annotated quadruply charged glycopeptide signals. The inset on (B) represents a magnification of the mass range which contains peaks corresponding to the tumor-specific tetrasialylated glycopeptides not detected in (A). All peaks labeled refer to the monoisotopic peaks within the well resolved isotopic clusters. Symbols used are as defined in Figure 3.

In agreement with the results from glycomic analysis of the released N-glycans, it is clear that the glycopeptide signal corresponding to one carrying a trisialylated biantennary glycan (m/z 1450.0) increases in total ion counts relative to the disialylated glycopeptides (m/z 1373.3, 1409.8), in the sample derived from the serum of mice bearing colonic tumor (Figure 5B). The additional sialylation contributed to the aforementioned disialylated antennae, which gave the specific oxonium fragment ion at m/z 980, corresponding to Neu5Gc2Hex1HexNAc1+, in the MS/MS spectra of m/z 1450 (Figure 6C). In comparison, the disialylated glycopeptide at m/z 1373.3 gave only the oxonium ion at m/z 673, corresponding to Neu5Gc1Hex1HexNAc1+. The Neu5Gc to Neu5Ac substitution as noted in glycomic mapping of the permethylated glycans is reflected in the additional presence of signals at 16 mass units below, namely at m/z 1446.0, the MS/MS of which clearly shows the presence of additional oxonium ions at m/z 657 (Neu5Ac1Hex1HexNAc1+) and 964 (Neu5Ac1Neu5Gc1Hex1HexNAc1+). Another distinctive colonic tumor-associated feature is the presence of tetra-sialylated glycopeptide signal cluster at m/z 1519, 1523, and 1527 (Figure 5B, inset), corresponding to having both antenna of the biantennary N-glycan Neu5Gc-disialylated, with the expected heterogeneity contrib3300


uted by Neu5Ac substitution. Similar sialylation pattern could also be detected for the haptoglobin glycopeptides (data not shown) although its lack of expression in the sera of normal mice prevented a meaningful comparison, as in the case of serotransferrin.

Discussion In summary, both our glycomic and glycoproteomic data defined a significant change in sialylation as the most prominent feature associated with serum acute phase glycoproteins from mice bearing tumors, which concur with a general observation made for the rodent experimental inflammation models,34,43 as well as cases of human disease and cancer. In contrast, another often cited change for the sera of human cancer patients, namely the increase expression of either core or peripheral fucosylation, is not apparently observed, although a wider survey of many other tumor types and origins will naturally be required to allow for a more definitive conclusion. At a more structure-specific level, changes in Neu5Gc to Neu5Ac would seemingly bear no relevance to human because human alone is incapable of making Neu5Gc.44,45 However, in biological studies involving mouse models, this is highly


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Figure 6. Representative nanoESI-MS/MS spectra of serotransferrin glycopeptides as acquired on the quadruply charged parent ions during a data dependent nanoLC-nanoESI-MS/MS run, operated under PID mode. Due to facile fragmentation, the original parent ions at m/z 1373.3 (A), 1446.0 (B), and 1450.0 (C) were no longer visibly present in the MS/MS spectra but a series of doubly and triply charged fragment ions corresponding to the expected loss of variable number of glycosyl residues from the parent ions can be detected, leading to the common peptide core+GlcNAc ion at m/z 1152.9 (3+) and 1728.8 (2+). In addition, common glycan oxonium ions detected at the low mass range include the quintessential HexNAc+, Neu5Gc+-H2O, Neu5Gc+, Hex-HexNAc+, Hex-HexNAc-Hex+, and Neu5Gc1(Hex-HexNAc+) at m/z 204, 290, 308, 366, 528, and 673, respectively. The additional oxonium ion at m/z 511 and 980 correspond respectively to Neu5Gc-HexNAc+ and Neu5Gc2(Hex-HexNAc+), which are specific to the disialylated antennae, present only in the triand tetra-sialylated glycopeptides. Signals at m/z 274, 657, and 964, corresponding to Neu5Ac+-H2O, Neu5Ac1(Hex-HexNAc+), and Neu5Gc1Neu5Ac1(Hex-HexNAc+), respectively, indicate a single substitution of Neu5Gc by Neu5Ac, present in (B) only. Symbols used are as defined in Figure 3. Doubly charged signals are indicated with an asterisk, triply charged signals with a diamond.

significant because it would affect a diverse range of specific interactions with endogenous lectins, particularly the murine sialic acid binding Siglecs, some of which are known to recognize only the NeuGc-sialylated ligands.46 The loss of hydroxylation on the terminal sialic epitopes may thus affect the growth and development of multiple tissues. The preference for Neu5Gc over the more common Neu5Ac in mouse serum glycoproteins has been attributed to a high activity of CMPNeu5Ac hydroxylase in mouse liver.37,38 Apparently, then, this activity was suppressed in mice bearing colonic tumors but not breast tumors in our experimental models. The mechanism underlying this phenomenon is beyond our current studies, but it is interesting to note that such change is not universal to all tumor types and has not been reported in the context of cancer and diseases for mouse sera glycoproteins. A recent glycomic mapping of the serum N-glycans from CD-1 nude mice injected with human head and neck cancer cells47 likewise did not detect such changes, indicating a specific response probably related to murine colonic tumor progression and/or requiring an immuno-competent background. Unlike the more restricted occurrence of Neu5Gc to Neu5Ac substitution, the observed increase in disialylation in the form of Neu5GcR2-3Galβ1-3(Neu5GcR2-6)GlcNAcβ1- appears to be common for both murine tumor types investigated. Similar increase in sialylation was recently reported in the context of inflammatory response in mice but increase in disialylated antenna were deduced to be Neu5Ac2-8Neu5Ac2-3 on GalGlcNAc.43 Curiously, the mRNA expression for all of the known

R-2,8-sialyltransferases (ST8Sia I-VI) in the liver where most of the abundant serum glycoproteins originated from was found to be unchanged. Such terminal disialyl motif was not detected in our current studies based on MS/MS analysis, which instead unequivocally localize the extra sialylation to the C6 of the internal GlcNAc. It is possible that the observed increase in the mRNA transcript of ST6GalNAc VI by the previous report43 may well be contributing to Neu5GcR2-6 sialylation on GlcNAc48 instead of or in addition to the suggested O-glycans. Irrespective of the underlying mechanism and functional implications, we have further demonstrated that such an increase in the disialylated antennae was carried by at least one of the more abundant serotransferin, which itself does not seem to alter appreciably in expression level. Our finding therefore underlines the need for integrating glycomic analysis into proteomics, which would facilitate identification of markers related to changes in glycan epitopes. Current technical limitations in glycoproteomics and glycopeptide analysis often defy a detailed mapping of the changes in glycosylation. Our methodology, as demonstrated here, is powerful and sufficiently informative with respect to the exact location of the modified fucosylation and sialylation pattern, which in turn is important for both biochemical studies and biomarker refinement. In contrast, most clinically relevant protein markers such as R-fetoprotein (AFP), prostate specific antigen (PSA), and carcinoembryonic antigen (CEA), which are only expressed at relatively low amount even after up-regulation in cancer, are mostly not identified by simple serum Journal of Proteome Research • Vol. 7, No. 8, 2008 3301

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proteomic analysis. Instead, a survey of representative literature reveals that most of the implicated changes were related to acute phase proteins,20,51 which are not tumorspecific markers although their characteristic appearance may have potential in initial assessments of tumor development. The mechanistic basis and functional implications for association of an acute phase protein with cancer relapse remain largely unknown. Duan et al.19 established a 2-DE map of mouse serum proteomes from different inbred strains of mice (BALB/cJ and C57BL/6J) and mice subjected to two different inflammatory stimuli (20% burn injury and lipopolysaccharide (LPS) injection). Three major acute phase proteins, that is, haptoglobin, serum amyloid A, and serum amyloid P proteins, were found to be highly induced by both inflammatory stimuli. Juan et al.20 used 2-DE maps to compare the plasma protein profiles of healthy nude mice and nude mice inoculated with one of five human cancer cell lines. The overexpressed proteins were likewise identified as haptoglobin and serum amyloid A protein. Thus, the same acute phase proteins are induced nonspecifically under both inflammatory stimuli and tumor progression, be it in nude mice or BALB/c mice. Yet, these glycoproteins may bear very different glycosylation pattern. An integrated glycomic and proteomic approach would therefore provide a more accurate representation of the changes induced by either inflammation or tumor progression. We have further shown that the serum glycomic changes are faithfully reproduced in the glycomic map of ascites, which in fact carries an even more pronounced glycosylation pattern related to the tumor-bearing state. Although this information has not been reported in the literature and that we have provided first such detailed glycomic mapping, it is somewhat not surprising. Ascites is an abnormal accumulation of serous fluid in the peritoneal cavity and is therefore expected to reflect the serum profile. Yet, its proteomic content and potential value in providing basic understanding of tumor progression are relatively under-explored and would benefit from further detailed glycoproteomic studies. Abbreviations: MS, mass spectrometry; LC, liquid chromatography; MALDI, matrix-assisted laser desorption/ionization; ESI, electrospray ionization; TCA, trichloroacetic acid; SCID, severe combined immunodeficiency; CID, collision-induced dissociation; PID, precursor ion discovery; 2-DE, two-dimensional electrophoresis.

Acknowledgment. This work was supported by Taiwan NSC grants 94-3112-B-001-009-Y and 95-3112-B-001-014 to the NRPGM Core Facilities for Proteomics located at the Institute of Biological Chemistry, Academia Sinica. We gratefully acknowledge the technical assistance of other core personnel, Mr. He-Hsuan Hsiao, Ms. Yuh-Ying Yeh, and Mr. Chen-Chin Yang. References (1) Ciordia, S.; de Los Rios, V.; Albar, J. P. Contributions of advanced proteomics technologies to cancer diagnosis. Clin. Transl. Oncol. 2006, 8 (8), 566–80. (2) Maurya, P.; Meleady, P.; Dowling, P.; Clynes, M. Proteomic approaches for serum biomarker discovery in cancer. Anticancer Res. 2007, 27 (3A), 1247–55. (3) van der Merwe, D. E.; Oikonomopoulou, K.; Marshall, J.; Diamandis, E. P. Mass spectrometry: uncovering the cancer proteome for diagnostics. Adv. Cancer Res. 2007, 96, 23–50. (4) Comunale, M. A.; Lowman, M.; Long, R. E.; Krakover, J.; Philip, R.; Seeholzer, S.; Evans, A. A.; Hann, H. W.; Block, T. M.; Mehta, A. S. Proteomic analysis of serum associated fucosylated glyco-

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