Identification of differentially expressed serum proteins in gastric adenocarcinoma

Abstract

Gastric adenocarcinoma is an aggressive cancer with poor prognosis. Blood based biomarkers of gastric cancer have the potential to improve diagnosis and monitoring of these tumors. Proteins that show altered levels in the circulation of gastric cancer patients could prove useful as putative biomarkers. We used an iTRAQ-based quantitative proteomic approach to identify proteins that show altered levels in the sera of patients with gastric cancer. Our study resulted in identification of 643 proteins, of which 48 proteins showed increased levels and 11 proteins showed decreased levels in serum from gastric cancer patients compared to age and sex matched healthy controls. Proteins that showed increased expression in gastric cancer included inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), Mannose-binding protein C (MBL2), sex hormone-binding globulin (SHBG), insulin-like growth factor-binding protein 2 (IGFBP2), serum amyloid A protein (SAA1), Orosomucoid 1 (ORM1) and extracellular superoxide dismutase [Cu–Zn] (SOD3). We used multiple reaction monitoring assays and validated elevated levels of ITIH4 and SAA1 proteins in serum from gastric cancer patients.

Biological significance

Gastric cancer is a highly aggressive cancer associated with high mortality. Serum-based biomarkers are of considerable interest in diagnosis and monitoring of various diseases including cancers. Gastric cancer is often diagnosed at advanced stages resulting in poor prognosis and high mortality. Pathological diagnosis using biopsy specimens remains the gold standard for diagnosis of gastric cancer. Serum-based biomarkers are of considerable importance as they are minimally invasive. In this study, we carried out quantitative proteomic profiling of serum from gastric cancer patients to identify proteins that show altered levels in gastric cancer patients. We identified more than 50 proteins that showed altered levels in gastric cancer patient sera. Validation in a large cohort of well classified patient samples would prove useful in identifying novel blood based biomarkers for gastric cancers.

This article is part of a Special Issue entitled: Proteomics in India.

1. Introduction

Gastric cancer is a highly aggressive cancer associated with high mortality. High incidence of gastric cancer has been observed throughout the world [1]. High mortality is often due to delayed diagnosis [2] due to non-specific symptoms observed in gastric cancer [3]. Serum-based biomarkers are of considerable importance in early diagnosis of various diseases including cancer. Proteins secreted from tumor tissues have a greater likelihood of reaching systemic circulation and therefore, secreted proteins could serve as potential biomarkers for early detection [4]. However, serum is a complex protein mixture consisting of proteins that exhibit a wide dynamic range of expression [5]. Ten most abundant proteins in serum constitute about 95% of the total protein content. Therefore, identifying candidate biomarkers for diseases from serum has been an immense challenge. To overcome this challenge, various depletion strategies have been developed to reduce sample complexity in serum [6].

Plasma-based tumor markers including CA 19-9, CA 125, and CEA (carcinoembryonic antigen) have been in clinical use for monitoring gastric cancer [7]. These markers have been shown to be useful to detect disease recurrence after curative surgery [8]. However, they display low sensitivity, lack specificity and often are not reproducible [9,10]. Several groups have employed quantitative proteomic approaches to identify novel secreted biomarkers in gastric cancer by analyzing secretome [11–13], and plasma [14].

In this study, we used isobaric tags for relative and absolute quantitation (iTRAQ) based quantitative proteomic strategy to identify proteins that show altered levels in serum of gastric adenocarcinoma patients. We identified 643 proteins of which 48 showed increased levels and 11 showed decreased levels in serum from gastric cancer patients. Large scale validation of these proteins might prove useful in identification of blood-based biomarkers of gastric cancer.

2. Materials and methods

2.1. Patient samples

Patient and control blood samples were collected after obtaining approval from the institutional review board at the Kidwai Memorial Institute of Oncology, Bangalore, India. Ten blood samples each were collected from patients who underwent curative surgery for the removal of tumor and had histologically confirmed gastric adenocarcinoma (details in Supplementary Table 1). None of the patients had previously undergone radio or chemotherapy. Corresponding age and sex matched control serum samples were obtained from individuals with no prior health conditions such as diabetes and cardiovascular disease. Blood was collected from patients and control individuals after obtaining informed consent. Serum was separated from control and test samples using standard centrifugation techniques. The samples were stored immediately at −80 °C.

2.2. Protein estimation and depletion of abundant proteins

The total protein amount was measured for each serum sample using Bicinchoninic acid (BCA) assay [15] (Pierce®. Cat#: 23225). Protein amounts were normalized and equivalent amounts of protein from each of the patient and control serum samples were pooled separately. 10 mg protein each from both patient and control samples were depleted of the top fourteen abundant serum proteins using a Human-14 Multiple Affinity Removal Column (Agilent Technologies, Santa Clara, CA. Cat# 5188-6557; 4.6 × 50 mm). Post-depletion, 600 μg protein from each of the samples was recovered.

2.3. iTRAQ labeling

After depletion, equal amount of protein from gastric cancer and control samples were processed for iTRAQ labeling as previously described [16]. Briefly, 160 μg protein each from both the sample sets was subjected to reduction with 2 μl of reducing agent, TCEP [tris-(2-carboxyethyl) phosphine] at 60 °C for 1 h. The reduced samples were further alkylated with 2 μl methyl methanethiosulfonate (MMTS) at room temperature for 10 min. The samples were then digested with sequencing grade modified trypsin (Promega, Madison, WI. Cat#V5111) at 37 °C overnight. The tryptic digests were vacuum-dried. Both the test and control samples were split into two equal halves serving as technical replicates and labeled with iTRAQ reagents (Applied Biosystems, Cat#: 4352135) as per manufacturer’s instructions. Control samples were labeled with iTRAQ reagents containing reporter ions of 114 and 115 m/z, while test samples were labeled with those containing reporter ions of 116 and 117 m/z. The labeling reaction was quenched using 100 μl milliQ water after 1 h. The labeled samples were pooled and vacuum-dried.

2.4. SCX fractionation

The vacuum-dried iTRAQ labeled sample was reconstituted with SCX solvent A (5 mM KH₂PO₄, 25% acetonitrile solution (pH 2.7)) and fractionated by strong cation exchange (SCX) chromatography using a polysulfoethyl A column (PolyLC, Columbia, MD. Cat#: 204SE0502; 200 Å, 5 μm, 200 × 4.6 mm) connected to Agilent 1200 infinity series HPLC system. Peptides were loaded onto the column and washed for 20 min and fractionated using a 8–50% gradient of 10 mM KH₂PO₄, 350 mM KCl, and 20% acetonitrile solution over a period of 30 min. Eluates were pooled to obtain 20 fractions and vacuum-dried. The dried peptides were reconstituted in 0.1% trifluoro acetic acid and subjected to desalting using C₁₈ Stage Tips (3M Empore high-performance extraction disks) and stored at −20 °C until further analysis.

2.5. LC-MS/MS analysis and data analysis

The peptide digest from SCX fractionation were analyzed on LTQ-Orbitrap Velos mass spectrometer (Thermo Electron, Bremen, Germany) interfaced with Easy-nLC II nanoflow liquid chromatography system (Thermo Scientific, Odense, Southern Denmark). The peptide digests from each fraction were reconstituted in Solvent A (0.1% Formic acid) and loaded onto trap column (75 μm × 2 cm) packed in-house with Magic C₁₈ AQ (Michrom Bioresources, Inc., Auburn, CA, USA) (5 μm particle size, pore size 100 Å) at a flow rate of 5 μl/min with solvent A (0.1% formic acid in water). Peptides were resolved on an analytical column (75 μm × 15 cm) at a flow rate of 300 nl/min using a linear gradient of 7–30% solvent B (0.1% formic acid in 95% acetonitrile) over 60 min. Mass spectrometry analysis was carried out in a data-dependent manner with full scan range of 350–1800 m/z acquired using an Orbitrap mass analyzer at a mass resolution of 60,000 at 400 m/z. Fifteen most intense precursor ions from a survey scan were selected for MS/MS from each duty cycle and detected at a mass resolution of 15,000 at m/z of 400 in Orbitrap mass analyzer. The fragmentation was carried out using higher-energy collision dissociation (HCD) with 41% normalized collision energy. Dynamic exclusion was set for 30 s with a 10 ppm mass window. Internal calibration was done using lock-mass from ambient air (m/z 445.1200025).

The mass spectrometry data (.raw) was searched against human RefSeq Build 50 protein sequence database (containing 33,833 entries along with common contaminants) using SequestHT and Mascot (version 2.2) search algorithms through Proteome Discoverer (Thermo Scientific, Bremen, Germany, version 1.3.0.339). The search criteria included methylthio modification of cysteine, iTRAQ 4-plex modification at peptide N-terminus and lysine (K) as static modifications and oxidation of methionine as dynamic modification. For both the searches, precursor mass tolerance of 20 ppm, fragment mass tolerance of 0.1 Da and two missed cleavage were allowed. The data were searched against a decoy database to calculate the false discovery rate (FDR) at the peptide level. For protein identification, a cutoff of 1% FDR at the peptide spectrum matches (PSMs) level was employed. Relative protein quantitation was carried out using Reporter Ions Quantifier node of Proteome Discoverer.

2.6. Bioinformatics analysis

Gene ontology-based functional classification of identified proteins was done using Human Protein Reference Database [17,18] (HPRD, http://www.hprd.org). Molecule class, molecular function, biological process, subcellular localization, tissue expression and domain information for each protein was obtained from HPRD.

2.7. Validation using MRM

Candidate proteins identified from the proteomics study were validated using multiple reaction monitoring [19]. Five serum samples used in the initial experiment and five independent serum samples from confirmed gastric cancer cases and healthy subjects were used for the validation of differentially expressed proteins by liquid chromatography-multiple reaction monitoring (LC-MRM) approach. Protein estimation was carried out by BCA method [15]. Equal amount of proteins from each sample were subjected to reduction, alkylation and trypsin digestion as described earlier [20]. The samples were stored in −20 °C until further analysis.

Two proteotypic peptides were picked for each protein from the iTRAQ-based discovery data. SRM transitions were created in Skyline 2.5 [21] from the peptide sequences. A minimum of four transitions were selected for each peptide (Supplementary Table 4). All the selected fragments were y-ions. LC-MRM analysis was carried out by triple quadrupole, TSQ Quantum Ultra mass spectrometer (Thermo Fisher Scientific, Bremen, Germany) equipped with Agilent 1100 series HPLC system. Peptides were enriched on a trap column (5 μm, 75 μm × 2 cm.) for 5 min with solvent A (5% ACN in 0.1% formic acid). A linear gradient of 5–30% solvent B (95% ACN in 0.1% formic acid) for 60 min was used to resolve peptides on an analytical column at a constant flow rate of 350 nl/min. Magic C₁₈ AQ (Michrom Bioresources) material was used to pack both columns. The data were acquired in triplicate. Q1 and Q3 were set at resolution of 0.4 and 0.7 respectively. Collision energy for each transition was optimized after analyzing the results of three preliminary LC-MRM runs.

2.8. Accessibility of proteomic data

The data generated in this study was deposited to publicly available data repositories to make it accessible to the scientific community. The lists of proteins and peptides identified in this study were submitted to Human Proteinpedia. (http://www.humanproteinpedia.org). The protein and peptide lists can be visualized using the link http://www.humanproteinpedia.org/data_display?exp_id=00800.

The mass spectrometry data was also deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the dataset identifier PXD001265.

3. Results and discussion

3.1. Identification of proteins that showed altered levels in serum of gastric adenocarcinoma patients

We employed an iTRAQ-based quantitative proteomic approach to identify differentially expressed proteins in serum of patients with gastric adenocarcinoma. Serum samples from patients with gastric adenocarcinoma and control cases were depleted of abundant proteins, labeled with iTRAQ reagents and fractionated by SCX chromatography. Analysis using high resolution Fourier transform mass spectrometry led to the acquisition of 165,445 MS/MS spectra. The schematic of the work flow is shown in Supplementary Fig. 1. MS/MS search against Human RefSeq 50 database using Mascot and Sequest search algorithms led to the identification of 4633 peptides corresponding to 643 proteins (Supplementary tables 2 and 3). A total of 59 proteins were identified to be differentially regulated of which, 48 were upregulated (iTRAQ ratios of ≥2) and 11 were downregulated (iTRAQ ratios of ≤0.5). Fig. 1 depicts significantly dysregulated proteins in gastric cancer serum. A partial list of proteins previously reported to be overexpressed in gastric cancer serum are provided in Table 1. MS/MS spectra for two of the overexpressed proteins-inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) and serum amyloid A protein (SAA1) are provided in Supplementary Fig. 2A and B respectively.

Fig. 1.

Differentially expressed proteins identified in serum of patients with gastric adenocarcinoma. Proteins that showed increased levels in serum from gastric cancer patients is shown in red and those that showed decreased levels are shown in green.

Table 1.

Partial list of proteins that showed increased levels in serum of gastric adenocarcinoma patients.

Gene symbol	Protein name	Function	Disease associations	Fold-change (Cancer/Normal)
ITIH4	Inter-alpha-trypsin inhibitor heavy chain H4	Anti-inflammatory protein	Breast [54] and ovarian cancers [56]	2.2
MBL2	Mannose-binding protein C	Activates classical complement pathway	Acute lymphoblastic leukemia [57] and colon cancers [58]	2.2
SHBG	Sex hormone-binding globulin	Regulation of steroid response	Breast [59], prostate [60] and endometrial cancers [61]	2.3
IGFBP2	Insulin-like growth factor-binding protein 2	Binds to insulin-like growth factors to alter their interaction with cell surface receptors	Colorectal [50] and lung cancers [51]	2.2
LRR1	Leucine-rich repeat protein 1	Negative regulator of TNFRSF9-mediated signaling cascade	Esophageal cancer[62]	2.1
Proteins previously reported to be elevated in serum of gastric adenocarcinoma patients
SAA1	Serum amyloid A protein	Acute phase protein	Liu et al. [63],Sasazuki et al. [25], Chan et al. [26]	5.8
ORM1	Orosomucoid 1	Acute phase protein	Rashid et al. [24]	4.4
SOD3	Extracellular superoxide dismutase [Cu–Zn]	Antioxidant enzyme	Lin et al. [44], Yasuda et al. [45]	3.6
LRG1	Leucine-rich alpha-2-glycoprotein	Cell adhesion and development	Uen et al. [33]	2.6
CHGA	Chromogranin-A preproprotein	Precursor of negative modulators of the neuroendocrine system	Syversen et al. [46]	2.3

Serum amyloid A protein (SAA1) is an apolipoprotein and a major acute-phase reactant [22] secreted in response to cytokines such as interleukin-1 and interleukin-6 [23]. It has been reported to be overexpressed in the serum of patients with gastric adenocarcinoma [24,25]. Increased serum SAA1 concentration was found to be associated with tumor recurrence and predicting survival of patients with gastric cancer [26,27]. Elevated levels of SAA1 have also been observed in various cancers including renal [28] and esophageal [29] cancers. In esophageal cancers, elevated levels of SAA1 have been associated with poor prognosis [29]. SAA1 was overexpressed 5.8-fold in the current study.

Tumor growth and progression are dependent on the malignant potential of the tumor cells as well as the tumor microenvironment [30,31]. Secreted proteins have a greater likelihood of being detected in blood and other body fluids and could potentially reflect the tumor microenvironment [4,32]. However, the presence of high abundant proteins in the serum impedes discovery of blood based biomarkers in cancer. Advances in protein depletion technologies have improved protein identification from serum/plasma. In our study, we identified several proteins that have been previously reported to show increased levels in serum/plasma of gastric cancer patients [14,33–35]. These included Orosomucoid 1 (ORM1), serpin peptidase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 1 (SERPINA1), inter-alpha-trypsin inhibitor heavy chain 3 (ITIH3), leucine-rich alpha-2-glycoprotein 1 (LRG1) and complement 9 (C9). Orosomucoid 1 (ORM1) was found to be overexpressed by 4.4-fold in serum of patients with gastric cancer. The acute phase protein has been previously found to be elevated in plasma of patients with gastric cancer [24], ovarian cancer [36] and glioblastoma multiforme [37]. SERPINA1 is a member of the serine protease inhibitor family. Increased levels of SERPINA1 have been observed in plasma [14] as well as gastric juice [38] of gastric cancer patients. SERPINA1 has been shown to induce invasion and migration of gastric cancer cells and has been associated with poor prognosis [39]. ITIH3 is a member of the inter-alpha-trypsin inhibitor family of plasma serine protease inhibitors. Overexpression of ITIH3 has been previously seen in sera of gastric cancer patients [33]. It has been suggested that ITIH3 could serve as a potential biomarker for early detection due to its overexpression in plasma of early stage gastric cancer patients [40]. ITIH3 has also been shown to play a role in the prevention of tumor metastasis [41]. LRG1 is a member of the leucine-rich repeat family of proteins involved in protein–protein interaction, signaling and cell adhesion processes. LRG1 has been previously shown to be overexpressed in plasma of gastric cancer patients [14]. LRG1 has been shown to promote angiogenesis through endothelial TGF-beta signaling [42]. C9 is a member of the complement system which plays a role in innate and adaptive immune response. Plasma C9 has been previously found to be upregulated in gastric cancer patients [14]. Using label-free proteomics analysis, C9 and its fucosylated form have been found to overexpressed in the sera of patients diagnosed with squamous cell lung cancer (SQLC) [43] suggesting that the elevated C9 could serve as a potential biomarker in cancer diagnosis. Some of the other identified proteins previously reported in gastric cancer serum include extracellular superoxide dismutase [Cu–Zn] (SOD3) (3.6-fold) [44,45], leucine-rich alpha-2-glycoprotein (LRG1) (2.6-fold) [33] and chromogranin-A preproprotein (CHGA) (2.3-fold) [46]. These observations are concordant with previous studies and support the experimental approach used in our study.

In addition, we identified several proteins where we could not find prior reports in serum from gastric adenocarcinoma. These included insulin-like growth factor-binding protein 2 (IGFBP2), inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), mannose-binding protein C (MBL2), sex hormone-binding globulin (SHBG), leucine-rich repeat protein 1 (LRR1). IGFBP2 is a 36 kDa protein belonging to the super family of insulin-like growth factor (IGF) binding proteins [47]. IGFBP2 produced by metastatic cells has been reported to recruit endothelia by modulating IGF1-mediated activation of IGF1R on endothelial cells resulting in enhanced endothelial migration towards metastatic cells [48]. IGFBP2 expression correlated with metastasis and poor survival in lung cancer [49]. Elevated serum levels of IGFBP2 have been observed in colorectal [50] and lung cancers [51]. IGFBP2 was also reported to be overexpressed in gastric cancer tissue when compared to normal gastric mucosa [52]. In our study, it was overexpressed by more than 2-fold in serum of patients with gastric cancer when compared to serum from healthy controls. Since IGFBP2 has been found to be overexpressed in both tissue and serum of patients with gastric cancer, it could serve as a potential biomarker for diagnosis and prognosis of gastric cancer. ITIH4 is a member of the inter-alpha-trypsin inhibitor (ITI) family. It is an acute-phase reactant elevated in response to interleukin-6 [53]. Elevated levels of ITIH4-derived peptides have been observed in serum of breast cancer patients [54]. Increased levels of ITIH4 fragments have also been found in urine of early prostate cancer patients [55]. Reduced levels of ITIH4-derived peptides have also been observed in urine of ovarian cancer patients [56]. ITIH4 was overexpressed by 2.2-fold in this study.

3.2. Functional classification of identified proteins

The proteins identified were classified based on their subcellular localization and biological process using Human Protein Reference Database [17,18] (HPRD) (http://www.hprd.org) that contains gene ontology-based information on human proteins. Signal peptide and domain information for each identified protein was fetched from HPRD. Classification based on subcellular localization revealed that 34.5% (222 proteins) of the identified proteins were extracellular. A further 20% (129 proteins) were found to be plasma membrane proteins. Gene ontology classification based on biological process showed a majority were involved in cell communication and cell signaling (22%, 141 proteins) and protein metabolism (15.5%, 100 proteins). Of the 643 proteins identified, 375 (58%) proteins had a predicted signal peptide, 140 (21.7%) proteins had predicted transmembrane domains and 95 proteins (14.7%) had both signal peptide and transmembrane domains.

3.3. Validation of ITIH4 and SAA1 by multiple reaction monitoring (MRM)

Based on the findings from iTRAQ experiment, we selected two targets overexpressed in gastric cancer, inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) and serum amyloid A protein (SAA1), for MRM-based validation. Skyline 2.5 was used for method development and interpretation of the results. Manual inspection of preliminary data was carried out for method optimization and collision energies were adjusted accordingly. A revised instrument method was employed for data acquisition in triplicate for each serum sample. 2 μg of tryptic digest was loaded onto the column for each LC-MRM run. The data were imported into Skyline and relative quantification for each peptide was determined by calculating the average ratios of peak areas of transitions (Fig. 2). By employing this complementary approach, we confirmed overexpression of ITIH4 and SAA1 in gastric cancer serum samples used for validation. ITIH4 was found to be significantly overexpressed (p-value = 0.038) in 7 of the 10 gastric cancer serum samples analyzed by MRM. SAA1 was found to be significantly overexpressed (p-value = 0.019) in 8 of the 10 gastric cancer serum samples analyzed by MRM. The relative abundance of these proteins across all the ten patients compared to its level in controls (median) is shown in Supplementary Fig. 3.

Fig. 2.

Validation of overexpression of candidate proteins in gastric adenocarcinoma by multiple reaction monitoring (MRM). (A) Box-plot showing relative expression levels of ITIH4 in sera from gastric cancer patients and matched controls. (B) MRM transitions used for quantitation of inter-alpha-trypsin inhibitor heavy chain H4. (C) Box-plot showing relative expression levels of SAA1 in sera from gastric cancer patients and matched controls. (D) MRM transitions used for quantitation of serum amyloid A protein.

4. Conclusions

We identified 643 proteins from the gastric cancer serum proteome using high resolution mass spectrometry. This study revealed 59 proteins that showed altered levels in serum from gastric cancer patients. We validated levels of ITIH4 and SAA1 in a set of serum samples from gastric adenocarcinoma patients using multiple reaction monitoring. In validation experiments using MRM, we could verify increased levels of these two proteins in serum samples from gastric adenocarcinoma patients. Validation of differentially expressed proteins in a large cohort of clinical samples in appropriate clinical conditions should prove useful for identification of blood based markers for gastric cancers.

Abbreviations

iTRAQ

Isobaric tags for relative and absolute quantitation

LC-MS/MS analysis

Liquid chromatography-tandem mass spectrometry

MRM

Multiple reaction monitoring

MMTS

Methyl methanethiosulfonate

TCEP

Tris-(2-carboxyethyl) phosphine