Identification of EFEMP2 as a Serum Biomarker for the Early Detection

Article pubs.acs.org/jpr

Identification of EFEMP2 as a Serum Biomarker for the Early Detection of Colorectal Cancer with Lectin Affinity Capture Assisted Secretome Analysis of Cultured Fresh Tissues Ling Yao,†,‡,∥ Weifeng Lao,§,∥ Yan Zhang,†,‡ Xiaorong Tang,†,‡ Xiaotong Hu,§ Chao He,*,§ Xiaofang Hu,*,† and Lisa X Xu*,† †

School of Biomedical Engineering and Med-X Research Institute and ‡School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China § Biomedical Research Center and Key Laboratory of Biotherapy of Zhejiang Province, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China S Supporting Information *

ABSTRACT: Early diagnosis plays a decisive role in the outcome of colorectal cancer (CRC) therapy. The ex vivo culture of fresh CRC tissues and paired normal colorectal tissues provides a feasible way to explore potential serum biomarkers for CRC early detection under near-physiological conditions. In the present work, we applied a lectin affinity based approach to enrich and increase the detection number of secreted proteins in the conditioned media of cultured tissues. The captured proteins were then analyzed by the proteomic strategy of one-dimensional gel electrophoresis coupled to liquid chromatography−tandem mass spectrometry. By quantification with label-free spectral counting, we found 123 differentially expressed secreted proteins (DESPs) with 68 DESPs up-regulated in CRC tissues. EFEMP2, one of the top 10 up-regulated DESPs, was further validated by immunohistochemistry at tissue level and enzyme-linked immunosorbent assay at serum level. We found the expression level of EFEMP2 was dramatically increased in CRC patients, even at the early stage. Moreover, the diagnostic accuracy of EFEMP2 was superior to the established CRC biomarker carcinoembryonic antigen evidenced by the area under the receiver operating characteristic curve for the two biomarkers were 0.923 and 0.728, respectively. These results indicated EFEMP2 is a promising serum biomarker for CRC early detection. KEYWORDS: colorectal cancer, fresh tissue culture, secretome, lectin affinity capture, EFEMP2, biomarker

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INTRODUCTION Colorectal cancer (CRC) is the third most common type of malignancy and the third leading cause of cancer-related deaths for both sexes around the world in 2010.1 The lifetime risk of being diagnosed with CRC is close to 5.5%.1 Early detection plays a decisive role in the outcome of CRC therapy. The 5year survival is approximately 91% when CRC is detected at a localized stage, while it deceases to around 10% if distant metastasis has occurred.1 It should be noted that less than 40% of CRC patients present with a localized stage at the time of diagnosis.1 The current available CRC diagnosis methods mainly include fecal occult blood test, colonoscopy, and serum biomarker tests. Fecal occult blood test, because of its low sensitivity and high false positive/negative rate,2 is often used to preselect high-risk individuals for further colonoscopy. Colonoscopy is a golden criterion for diagnosis of CRC, but its wide application is limited by the invasive and uncomfortable procedures. Compared to colonoscopy, the serum biomarker tests are more convenient and acceptable. At © 2012 American Chemical Society

present, carcinoembryonic antigen (CEA) is the most commonly used serum biomarker for CRC. But CEA lacks high sensitivity for the early detection of CRC.3,4 It is often used in clinical settings to provide prognostic information and to monitor therapy in advanced CRC.5 CEA also lacks specificity for CRC diagnosis because it is a tumor-associated antigen and is up-regulated in various extra-intestinal tumors such as lung, breast, ovarian, and bladder cancers.6 Thus, it is necessary to develop a novel serum biomarker with better sensitivity and specificity for the early detection of CRC. Theoretically, the secreted proteins have the highest chance to enter into circulation and to be detected at an early stage of cancer. Secretome analysis provides a powerful way to identify tumor cell specific secreted proteins that could be further explored as potential cancer serum biomarkers. As a simple and well-controlled model, the cell culture-based system has been Received: January 9, 2012 Published: April 17, 2012 3281

dx.doi.org/10.1021/pr300020p | J. Proteome Res. 2012, 11, 3281−3294

Journal of Proteome Research

Article

more sensitive and more high-throughput proteomic strategy to comprehensively analyze the secretome difference. The application of lectin affinity capture to enrich secreted proteins in CM provides a promising way to increase the detection efficacy of secreted proteins. Considering that secreted proteins are usually glycosylated, the lectin affinity capture could enrich secreted proteins. The enriched proteins can then be detected by a recently developed sensitive and high-throughput proteomic strategy, such as one-dimensional gel electrophoresis combined with liquid chromatography− tandem mass spectrometry (GeLC−MS/MS). In our previous work, we have applied this strategy to enrich and detect secreted proteins in the CM of several cell lines (MCF-10A, MCF-7, and MDA-MB-231).17 We found that, after lectin capture, the percentage of spectral counts of the secreted protein was increased from 23.9% to 59.4% for MCF-10A, 32.3% to 63.5% for MCF-7, and 26.4% to 65.9% for MDA-MB231. Accordingly, the number of secreted proteins was also increased from 183 to 292 for MCF-10A, 196 to 325 for MCF7, 194 to 368 for MDA-MB-231. The lectin affinity capture efficiently reduced the contamination of interfering proteins and increased the detection number of secreted proteins. Considering the contamination of interfering proteins from cell debris is more severe in fresh tissue culture medium than in cell line culture medium, in principle, the application of our strategy could capture secreted proteins from interfering proteins and facilitate the efficient detection and comparison of tissue culture based secretome. In the present study, we applied lectin affinity based approach in the secretome analysis of CRC tumor tissues and paired normal colorectal (NC) tissues to identify potential biomarkers. Nine groups of CM from CRC tumor tissues at the early stage and their paired NC tissues were collected, and the concentrated CM were incubated with Con A and WGA, which are two lectins with broad coverage.18,19 The captured proteins were then analyzed by GeLC−MS/MS. After lectin capture, the percentage of spectral counts of the secreted proteins was significantly increased from 45.1% to 79.9% for the CM of NC tissues (NCM) and 49.2% to 84.8% for the CM of CRC tissues (CCM). The number of the secreted proteins was also increased from 348 to 476 for NCM and from 342 to 491 for CCM. Based on label-free spectral counting, we identified 123 differentially expressed secreted proteins (DESPs), with 68 DESPs up-regulated in CRC tissues. EFEMP2, one of the top 10 up-regulated secreted proteins, was further validated by immunohistochemistry (IHC) at the tissue level and enzymelinked immunosorbent assay (ELISA) at the serum level. We found the expression level of EFEMP2 was dramatically increased in CRC patients, even at an early stage of CRC. These results indicated that EFEMP2 is a promising tissue and serum biomarker for the early detection of CRC.

extensively used in secretome analysis of a variety of cancer types to discover the potential biomarkers for cancer diagnosis, metastasis, drug resistance, etc.7−10 For example, the Diamandis group compared the secretomes of three breast cancer cell lines representing seminormal (MCF-10A), noninvasive (BT474), and metastatic origins (MDA-MB-468) through a shotgun proteomics approach, providing a wealth of secreted proteins expressed differentially between tumor cells and seminormal cell.7 Grønborg et al. compared the secretomes of an immortalized non-neoplastic human pancreatic duct epithelial cell line and a pancreatic ductal adenocarcinoma cell line, providing a number of potential clinically useful biomarkers for pancreatic cancer.8 The Lai group compared the secretomes of a primary CRC cell line SW480 and its lymph node metastatic cell line SW620 and identified a list of proteins related to CRC metastasis.9 Two of the candidates, trefoil factor 3 and growth/ differentiation factor 15, were further validated as potential biomarkers for the prediction of CRC metastasis. Although a cell culture based system is widely used in secretome analysis, this system has some unavoidable disadvantages for the screening of potential cancer biomarkers. First, no single cell line can represent the complex and heterogeneous tumor tissues.11 Second, cultured tumor cells are lack of tumor microenvironment.11 The interplay between tumor cells and their microenvironment plays a pivotal role in modulating and determining the final secretome profile of tumor cells.12,13 Therefore, it is desired to adopt a more near-physiological tumor system to perform the secretome analysis to identify feasible cancer biomarkers. The ex vivo culture of fresh tumor tissue provides a feasible way to explore the secretome of tumor under near-physiological conditions. In the pioneering work of Celis et al., freshly dissected invasive breast carcinomas were cultured in phosphate-buffered saline (PBS) for 1 h and the proteins released into the PBS were analyzed.14 They identified several proteins which were involved in various biological processes, including cell proliferation, invasion, angiogenesis, metastasis, inflammation, protein synthesis, etc. However, proteomic detection of the secreted proteins in conditioned medium (CM) of fresh tissue is challenging, owing to the inherent low concentrations of the secreted proteins and the presence of high amounts of interfering proteins released from cell debris during tissue culture. It should be noted that cell death is more severe in the fresh tissue culture system than in the cell line culture system. The contamination of interfering proteins, such as intracellular proteins and membrane proteins, is the bottleneck for the effective detection of secreted proteins in the CM of fresh tissue. Some efforts have been made to address this problem. Zwickl et al. combined the [35S]-methionine labeling during fresh tissue culture and two-dimensional gel autoradiography of proteins in the CM to detect the de novo synthesized secreted proteins from the human liver tissues.15 Recently, Shi et al. applied this technology to compare the de novo synthesized secreted proteins released from CRC liver metastases and paired normal colon mucosa and identified 32 differentially expressed proteins.16 This strategy is suitable for detecting synthesized secreted proteins. However, it cannot be used to detect and compare the total amount of released proteins, including proteins synthesized before and during culture process. Moreover, [35S]-methionine labeling should be coupled with two-dimensional gel autoradiography to identify differentially synthesized proteins, limiting its coupling with a

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MATERIALS AND METHODS

Sample Collection

Tissue specimens and serum samples were collected by experienced surgeons from Sir Run Run Shaw Hospital of Zhejiang University. The present study was approved by the Sir Run Run Shaw Hospital Ethics Committee and conducted with the consent of all patients. For proteomics analysis and Western blot validation, fresh CRC tissues and paired NC tissues from nine patients were obtained in 2009. The well-differentiated CRC surgical 3282



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Table 1. Histopathological Characteristics of CRC Patients from Whom the CRC Tissues and Paired NC Tissues Were Cultured for the Collection of CM patient

sex

age

location

differentiation grading

TNM staging

UICC staging

1 2 3 4 5 6 7 8 9

female male male male male male female female female

56 55 84 79 68 61 44 56 80

sigmoid colon ascending colon transverse colon rectum rectum rectum rectum rectum descending colon

well well well well well well well well well

T2N0M0 T2N0M0 T2N0M0 T1N0M0 T2N0M0 T2N0M0 T2N0M0 T3N0M0 T3N0M0

I I I I I I I IIA IIA

fractions at 280 nm was close to the blank. The captured proteins were released with 350 μL of elution buffer (20 mM Tris, 0.5 M NaCl, 0.4 M methyl-α-D-mannopyroside, and 0.5 M N-acetylglucosamine, pH 7.0) twice. The eluted samples were dialyzed in 1 L of 1 mM ammonium bicarbonate solution at 4 °C overnight. The protein concentration of dialyzed samples was determined by Bradford assay. The remaining dialyzed samples were lyophilized to dryness. The lectin affinity capture approach was repeated three times for the mixed NCM and CCM.

specimens were collected from various locations in colon and rectum and were classified as UICC stage I or IIA (Table 1). The corresponding NC surgical specimens were obtained from the distal edge of the resection, at least 10 cm off the tumor. One set of fresh tissue samples was immediately prepared for culture study as described below, and the other set of fresh tissue samples was immediately frozen in liquid nitrogen and then stored at −80 °C until use. For the IHC experiments, 123 paraffin-embedded tissue samples were used, including 88 CRC tissues, 19 colorectal adenoma tissues, and 16 distal NC tissues. The clinical features of these tissue samples are shown in Supplementary Table 1 (Supporting Information). For the ELISA experiment, blood samples were collected from 79 healthy individuals, 14 individuals with colorectal adenoma, and 122 patients with CRC. Blood was coagulated at room temperature for 30 min and centrifuged at 2000 g for 15 min, and the obtained serum was added with protease inhibitor cocktail (Roche, Mannheim, Germany) before being stored at −80 °C.

1D Gel Electrophoresis and In-Gel Digestion

Three replicates of 40 μg of glycoproteins obtained from CCM and NCM were separated on the 12% SDS-PAGE gel and stained with Coomassie Blue. After extensive decolorization, each gel lane was excised into 12 slices. Each slice was cut into approximately 1 mm cubes and destained by incubation in 50% acetonitrile in 50 mM ammonium bicarbonate. After destaining, the proteins in the gel were reduced by incubation in a solution of 50 mM tris (2-carboxyethyl) phosphine in 25 mM ammonium bicarbonate at 60 °C for 10 min. For alkylation of proteins, the gel was incubated in a solution of 100 mM iodoacetamide (IAA) at room temperature for 60 min, followed by washing the sample using 50% acetonitrile in 50 mM ammonium bicarbonate three times. After being dehydrated in 100% acetonitrile for 15 min, gel pieces were completely dried by SpeedVac. Then the gel pieces were swollen in 50 μL of 25 mM ammonium bicarbonate buffer containing 0.01 μg/μL trypsin (Promega, Madison, WI) and incubated overnight at 37 °C. Peptides were extracted with 50% acetonitrile containing 5% formic acid four times, dried by vacuum centrifugation at 60 °C, and stored at −20 °C for further analysis.

CM Collection and Concentration

Each tissue sample produced an individual conditioned medium (CM). The fresh tissues were cut into 1−3 mm3 explants using a sterile blade and washed three times with PBS. Then the tissues were incubated in serum-free Dulbecco’s modified Eagle’s medium (DMEM, Gibco, Grand Island, NY) at 37 °C for 24 h. The CM of each tissue was collected, centrifuged at 1500 rpm for 10 min, filtrated through a 0.22 μm filter (Millipore, Bedford, MA), and then added with protease inhibitor cocktail (Roche, Mannheim, Germany) before being stored at −80 °C. The NCM or CCM was pooled with an equal quantity of protein, respectively. The mixed CM were concentrated by Ultra-15 centrifugal filter devices with a 3 kDa cutoff (Millipore, Bedford, MA). The buffer was changed to lectin-binding buffer (20 mM Tris, 0.15 M NaCl, 1 mM MnCl2, and 1 mM CaCl2, pH 7.4) for further analysis. The protein concentration of concentrated samples was determined by Bradford assay.

Nano LC−MS/MS

The tryptic peptide digests of the proteins were analyzed using an MDLC system (Michrom Bioresources Inc., Auburn, CA) coupled with a Thermo Finnigan 2-D linear ion-trap mass spectrometer (LTQXL, Thermo Inc., San Jose, CA). Each peptide sample was redissolved in 5% acetonitrile with 0.1% formic acid and then loaded onto a Peptide Captrap column (Michrom Bioresources Inc., Auburn, CA) with the autosampler of the MDLC system. To desalt and concentrate the sample, the trap column was washed with 5% acetonitrile with 0.1% formic acid at a flow rate of 10 μL/min for 10 min. Then trapped peptides were released and separated on a C18 capillary column (0.1 mm i.d. × 150 mm, 3 μm, 200 Å, Michrom Bioresources Inc., Auburn, CA). The peptides were separated using a solvent system with solvent A consisting of 99.9% water and 0.1% formic acid and solvent B consisting of 99.9% acetonitrile and 0.1% formic acid. The peptides were

Lectin Affinity Capture of Glycoproteins

For the enrichment of glycoproteins, 100 μL of agarose-bound Con A (Vector Laboratories, Burlingame, CA) and 100 μL of agarose-bound WGA (Vector Laboratories, Burlingame, CA) were mixed and equilibrated with lectin-binding buffer in a microspin column (Pierce, Rockford, IL). Concentrated CM with 1.9 mg of proteins was incubated with agarose-bound lectins overnight at 4 °C in 250 μL of lectin-binding buffer. The nonspecific lectin-binding proteins were washed with lectinbinding buffer until the absorbance of the flow-through 3283



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of total spectral counts of all proteins in three replicates for the NCM and CCM, respectively, and f is a correction factor set to 1.25. The subcellular information of identified proteins was analyzed by the software ProteinCenter (Proxeon Bioinformatics, Odense, Denmark) and pedictive algorithms (SignalP 3.0, http://www.cbs.dtu.dk/services/SignalP/).24,25 Protein localizations were classified as secreted, plasma membrane, intracellular, and unknown using the following rationale: to designate a protein as “secreted”, a signal peptide would have to have been predicted via SignalP 3.0 (D-score >0.43 and hidden Markov matrix score >0.5) or have been designated “extracellular” via ProteinCenter. “Plasma Membrane” proteins and “Intracellular” proteins were identified via ProteinCenter. “Unknown” proteins were others which could not be localized via mentioned sources. The information of the molecule functions and biological processes of the selected proteins was obtained by the software ProteinCenter.

eluted with a linear gradient from 5% B to 35% B in 120 min with a constant flow rate of 500 nL/min. The LC setup was coupled online to an LTQ using a nano-ESI source (ADVANCE, Michrom Bioresources Inc., Auburn, CA) in data-dependent acquisition mode (m/z 400−1800). The temperature of the heated capillary was set at 200 °C, and the spray voltage was 1.2 kV. The mass spectrometer was set as one full MS scan followed by 10 MS/MS scans on the 10 most intense ions from the MS spectrum with the following dynamic exclusion settings: repeat count = 2, repeat duration = 15 s, exclusion duration = 30 s. Protein Identification

All data files were created by searching MS/MS spectra against the Human International Protein Index protein sequence database (ipi.HUMAN.v3.72.fasta, 86392 entries) by using the TurboSEQUEST program in the BioWorks 3.3 software suite, with a precursor-ion mass tolerance of 2.0 amu and fragmention mass tolerance of 0.8 amu. Trypsin was set as the protease with two missed cleavage sites allowed. Carbamidomethylation (+57.02150 Da) was searched as a fixed modification on cysteine, representing alkylation with IAA, while oxidized methionine (+15.99492 Da) was searched as a variable modification. The searched peptides and proteins were validated by PeptideProphet20 and ProteinProphet21 in the Trans-Proteomic Pipeline (TPP, v.4.2) using default parameters. Proteins with a ProteinProphet p value greater than 0.9 and with no less than two kinds of unique peptides were considered as true identifications. A randomized database of the ipi.HUMAN.v3.72.fasta was used as a decoy database to calculate the false discovery rate (FDR) of protein identification. The FDR was calculated by the ratio of the number of matches to the randomized database to the combined number of matches to the ipi.HUMAN.v3.72.fasta and its randomized derivative. FDR for ProteinProphet p ≥ 0.9 was less than 1%. Proteins containing the same peptides were grouped, and only one protein with highest probability in each group remained. The .raw files associated with the present work may be downloaded from the Proteome Commons Tranche server (https://proteomecommons.org/tranche/) using the following hash code: tKglJAs8+fyCSwqIaGT6YlA9B7gI86W/ZhB/KcF/ iFfwMH8vz3vEQNGUYbkepOuQ3k2/BqeqKeJsdRUnCx4mGxj03l8AAAAAAAAFAg==.

Western Blot Analysis

To validate the expression level of EFEMP2 in the CM, the 9 pair NCM and CCM (without lectin capture) were individually concentrated by the Ultracel YM-10 centrifugal filter devices with a 10 kDa cutoff (Millipore, Bedford, MA), and protein concentration was determined by Bradford assay. Proteins for each sample (35 μg) were separated by 12% SDS-PAGE gel, and transferred onto Immobilon-P PVDF Membrane (Millipore, Bedford, MA). The membrane was blocked with 5% skimmed milk in Tris-Buffered Saline containing 0.05% Tween20 (TBST) at room temperature for 1 h and then incubated with rabbit antihuman EFEMP2 antibody (Abcam, Hong Kong, China) at 4 °C overnight. The membrane was washed with TBST buffer four times and then incubated with horseradish peroxidase-conjugated goat antirabbit antibody (Beyotime Institute of Biotechnology, Jiangsu, China) for 1 h at room temperature. The membrane was washed with TBST buffer four times and then the reactive protein bands were visualized by chemiluminescent detection with SuperSignal West Pico Chemiluminescent Substrate (Pierce Chemical, Rockford, IL). To assess the expression level of EFEMP2 in the human serum, 0.3 μL of sera from healthy controls or CRC patients were separated by 12% SDS-PAGE gel and then analyzed by the same aforementioned method. After immunodetection, the coomassie staining of PVDF membrane was used as the loading control.26 Briefly, after immunodetection, the PVDF membrane was washed twice with TBST and then stained with Coomassie Blue for 1 min followed by extensive decolorization.

Bioinformatics Analysis

The proteins identified with at least two unique peptides were selected for further analysis. For the normalization, taking the sum of spectral counts of each repeat for the CCM and NCM as 100000, all the spectral counts of every protein in each repeat was adjusted correspondingly. All of the following statistical analyses were calculated on the basis of the normalized spectral counts. To compare the relative abundance of each proteins between CRC tissues and paired NC tissues, we calculated the spectral count fold-change ratios (RSC) using the following algorithm22,23

IHC Assay

IHC staining was completed in the pathology laboratory of Sir Run Run Shaw Hospital. The paraffin-embedded tissue sections (4−6 μm) were deparaffinized in xylene and rehydrated in a series of graded ethanol. For antigen retrieval, the slides were immersed in 10 mM citrate buffer (pH 6.0) and boiled for 15 min in a pressure cooker. The slides were cooled to room temperature naturally and then washed with PBS. Endogenous peroxidase activity was blocked by incubation in 3% H2O2 in methanol for 30 min and then washed with water for 10 min and PBS three times. For EFEMP2-specific staining, the nonspecific antigen were blocked by incubation with 10% goat serum in PBS for 30 min, and then the slides were incubated with the antihuman EFEMP2 antibody (diluted 1:600; Abcam, Hong Kong, China) at 4 °C overnight. After

R SC = log 2[(n2 + f )/(n1 + f )] + log 2[(t1 − n1 + f )/(t 2 − n2 + f )]

(1)

where for each protein, RSC is the log2 ratio of protein abundance between CRC tissues and NC tissues; n1 and n2 are the average of spectral counts of this protein in three replicates for the NCM and CCM, respectively. t1 and t2 are the average 3284



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Figure 1. Workflow for the comparative secretome analysis of CRC tissues and paired NC tissues. Secreted proteins in CM of CRC tissues and paired NC tissues were enriched by lectin affinity capture and then analyzed by GeLC-MS/MS. DESPs were identified on the basis of label-free spectral counting and analyzed by extensive data mining. The potential biomarker was further validated in detail with clinical samples.

blocking solution and incubated for 2 h at room temperature. After eight subsequent washes, the reaction was developed with 100 μL per well of ABTS (mixed ABTS peroxidase substrate solution and peroxidase solution B with 1:1) for 30 min at room temperature. Absorbencies were measured on a microplate reader (BIO-TEK PowerWave XS, BioTek Instruments Inc., Winooski, VT) at 405 nm.

being washed three times with PBS, the slides were incubated with the EnVision-HRP complex (Dako, Carpinteria, CA) for 30 min. Finally, the slides were visualized with diaminobenzidine (Dako, Carpinteria, CA) and counterstained with hematoxylin. For the assessment, five representative fields were assessed per section at 200× magnification with a light microscope (Carl Zeiss, Gö ttingen, Germany). The immunostaining was evaluated according to published standards.27 Briefly, the staining intensity was classified as 0 (lack of staining), 1 (mild staining), 2 (moderate staining), or 3 (strong staining), and the percentage of staining cells was evaluated with 1 (75%). For each section, the semiquantitative score was calculated by multiplying these two values, which ranged from 0 to 12, and the result was defined as negative (0), weakly positive (1−3), positive (4−7), and strongly positive (8−12).

ELISA for CEA

The serum expression level of CEA was assessed by using the Chemiluminescent Microparticle immunoassay technology with the instrument of Abbott Architect i2000SR (Abbott Laboratories, Abbott Park, IL). Statistical Analysis

Statistical calculations were performed by software SPSS 17.0 (SPSS Inc., Chicago, IL). Comparisons of data between two groups were analyzed by Student’s t test and were considered significant when two-tailed p < 0.05. The receiver-operating characteristic (ROC) curve analysis was performed by software GraphPad Prism 5 (GraphPad Software, San Diego, CA). The optimal cutoff point was obtained by selecting the value that yielded highest sensitivity and specificity when used to classify serum from healthy controls and CRC patients.

ELISA for EFEMP2

Detection of EFEMP2 in serum was achieved by indirect ELISA using a Protein Detector ELISA Kit (KPL, Inc., Gaithersburg, MD). Serum samples were diluted with 1 × coating buffer at a final dilution of 1:100. The 96-well ELISA plate (Corning Costar, Cambridge, MA) was coated with the diluted serum (100 μL/well) and incubated overnight at 4 °C. The plate was then washed once with 1 × wash solution and blocked with 300 μL of 1 × bovine serum albumin (BSA) blocking solution per well for 1 h at room temperature. Then, 100 μL of primary antibody (rabbit antihuman EFEMP2, Abcam, Hong Kong, China) was added at a dilution of 1/10000 (v/v) in 1 × BSA blocking solution and incubated for 2 h at room temperature. After four washes, 100 μL of secondary antibody (goat antirabbit IgG-HRP, Beyotime, China) was added to each well with a dilution of 1/250 (v/v) in 1 × BSA

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RESULTS AND DISCUSSION

Workflow and MS Data Overview

In the present study, we aimed to identify the potential biomarkers for the early detection of CRC from the secretome analysis of fresh CRC tissues and their paired NC tissues. Nine groups of CRC tissues at the early stage (UICC stage I or stage IIA) and their paired NC tissues were used to collect CM. To keep the fidelity of proteins released from the tissue samples, once the tissues were resected from the patients during the 3285



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Figure 2. Overview of proteins identified in the NCM and CCM with the application of lectin affinity capture. (A) Overlap of proteins identified in the NCM and the CCM. (B, C) Overlap of proteins identified in three independent replicates of NCM (B) or CCM (C). (D) Subcellular localization analysis of total proteins identified in the NCM and the CCM. (E) Distribution of detected spectral counts which belong to proteins with specific subcellular localization identified in the NCM and the CCM.

surgery, the tissues were immediately cut, washed, and cultured in serum-free DMEM. After 24 h incubation, the CM were collected, added with protease inhibitor cocktail, and stored at −80 °C until the experiment. To evaluate the quality of the tissue culture system, we also evaluated the cell viability of cultured CRC tissues. There is no direct method to accurately determine the cell viability of cultured tissues. Considering the increased abundance of actin in the CM of cell lines indicates the increased cell death rate,16 we compared the abundance of β-actin in the CM and lysates of CRC tissues and the human CRC cell line HT29 to evaluate the cell viability of cultured CRC tissues (Supporting Information). As shown in Supplementary Figure 1 (Supporting Information), similar high β-actin intensities were detected in the CRC tissue lysate and HT29 lysate, and different low βactin intensities were detected in the CM of CRC tissue and HT29 cell. To semiquantitate the β-actin level in different samples, the band intensities were measured by densitometry using ImageQuant TL software, and the resulting values were normalized to that of the HT29 cell lysate. The β-actin densities detected in the CM of HT29 cell and in the CM of CRC tissue were 2.3% and 7.8%, respectively. These results indicated the cell death was more severe in the tissue culture system than in the cell culture system. We further detected that the cell viability of HT29 was ∼98% (cell death rate ∼2%) after 24 h of serum free culture by trypan blue staining (Supporting Information). Considering the cell death rate was correlated with the amount of released β-actin, we could estimate the cell death rate of cultured tissues was around 7%. In the present study, we applied a lectin affinity based approach to enrich the secreted proteins in the CCM and NCM, respectively. Three technical replicates of lectin-captured samples were further analyzed by GeLC−MS/MS as elaborated in Figure 1.

By adopting this strategy, we identified a total of 1446 proteins with at least two unique peptides in lectin-captured samples, including 1066 proteins identified in the NCM and 1054 proteins identified in the CCM (Figure 2A). Among these proteins, 674 proteins (46.6%) were detected in both CM, 392 and 380 proteins were only identified in the NCM and the CCM, respectively. Within the 1066 proteins identified in the NCM, about 74.4% proteins were identified in any two replicates, 692 (64.9%) were detected in all three replicates (Figure 2B). Among the 1054 proteins identified in the CCM, about 75.7% proteins were identified in any two replicates, 701 (66.5%) were detected in all three replicates (Figure 2C). We further analyzed the subcellular distribution of identified proteins. Among the total of 1446 identified proteins, 623 (43.1%) were classified as secreted proteins (Figure 2D), including 413 proteins defined as secreted proteins by ProteinCenter and 210 proteins predicted as potential secreted proteins by predictive software SignalP 3.0. The percentage of identified intracellular proteins was 39.9%. Considering the detected spectral counts are correlated with the abundance of corresponding proteins, we also analyzed the distribution of spectral counts for identified proteins with specific subcellular localizations. As shown in Figure 2E, the percentage of spectral counts of secreted proteins was as high as 82.4%, and the percentage of spectral counts belonging to intracellular proteins was only 11.4%, indicating secreted proteins were effectively enriched by lectin capture method. Except for secreted proteins, a small proportion of plasma membrane proteins (5.8%) and intracellular proteins (11.4%) were also detected via the lectin capture method (Figure 2E). Most plasma membrane proteins were glycosylated,28 and some of them can be hydrolyzed by the enzymes and then released to the CM. The detection of intracellular proteins may be caused by inevitable cell death or other release process. Recent studies 3286



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Figure 3. Enrichment of secreted proteins with lectin affinity capture significantly increased the detection efficiency of secreted proteins in CM. (A) Lectin affinity capture effectively enriched the secreted protein in CM of cultured fresh tissues, evidenced by the significantly increased percentage of spectral counts belonging to the secreted proteins after lectin capture. Data are presented as mean ± SD (n = 3). **, p < 0.01. (B) The number of the secreted proteins detected in each replicate was significantly increased after the lectin affinity capture. Data are presented as mean ± SD (n = 3). **, p < 0.01. (C) The overlap of secreted proteins identified in the NCM and the CCM before or after lectin capture within three replicates.

Figure 4. Classification and analyses of DESPs. (A) Overlap of secreted proteins identified in the NCM and the CCM. (B) Classification of DESPs between NC tissues and CRC tissues. (C) Molecule functional analysis of DESPs between NC tissues and CRC tissues. (D) Biological processes analysis of DESPs between NC tissues and CRC tissues.

show that CRC cells actively release the microvesicles which would release various proteins outside the cell, such as cytoplasm proteins, membrane proteins and nucleus proteins.29 Some of these proteins were glycosylated30,31 and could be captured by lectin affinity. Considering the rate of spectral counts of the plasma membrane proteins and intracellular proteins was below 18%, their effect on the detection of secreted proteins was limited.

secreted proteins. In the present work, we further applied this method to enrich the secreted proteins in the CM of cultured fresh tissues. We compared secreted proteins identified in CM of NC/ CRC tissues before or after lectin capture. As shown in Figure 3A, after lectin capture the percentage of spectral counts of secreted proteins was significantly increased from 45.1% to 79.9% for NCM and 49.2% to 84.8% for CCM, indicating the efficient enrichment for secreted proteins by lectin capture. Accordingly, the detected number of secreted proteins was also significantly increased from 348 to 476 for the NCM, from 342 to 491 for the CCM (Figure 3B). Our data indicated that the lectin capture was a feasible way to enrich the secreted proteins from interfering proteins, facilitating the effective proteomic detection of secreted proteins. Notably, the secreted proteins identified in lectin-captured samples covered most of the secreted proteins identified in CM.

Advantages of Lectin Affinity Capture Strategy

The severe contamination of interfering proteins from dead cells in the fresh tissue-based culture system is the bottleneck for effective detection of secreted proteins. In our previous work, we applied lectin affinity capture approach to enrich secreted proteins in the CM of cell lines and demonstrated that this method was an effective way to reduce the contamination of interfering proteins and increase the detection efficiency of 3287



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Table 2. List of the Top 10 Up-Regulated Secreted Proteins in the CM of CRC Tissues normalized spectral count (mean ± SD)

IPI ID

gene symbol

identified/studied in CRC

a

NCM

CCM

p value

Rsc

1365.0 ± 218.2 585.3 ± 59.9 180.7 ± 31.7

0.000 0.000 0.001

10.113 8.881 7.187

± ± ± ±

37.5 62.8 6.7 27.2

0.003 0.001 0.000 0.005

6.814 6.656 6.580 6.120

60.3 ± 10.0 117.0 ± 11.8 53.7 ± 26.0

0.000 0.000 0.023

5.622 5.517 5.457

IPI00296534 IPI00018769 IPI00018219

FBLN1 THBS2 TGFBI

0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0

IPI00060423 IPI00745313 IPI00302679 IPI00008561

CTHRC1 AEBP1 LTBP1 MMP1

0.0 2.0 0.0 0.0

IPI00023648 IPI00296058 IPI00027192

ISLR EFEMP2 PLOD1

0.0 ± 0.0 1.3 ± 2.3 0.0 ± 0.0

± ± ± ±

0.0 3.5 0.0 0.0

139.3 325.7 118.3 85.7

genomics (ref)b

proteomics (ref)

others (ref)

plasma proteome database √c √ √

38 32, 34, 36, 39 38, 40

60

58

√ √ √

potential serum cancer biomarker (ref) breast (59)

CRC (60), gastric (61), lung (62), melanoma (63)

√ √ √

RSC: the spectral count fold-change ratio for protein between CCM and NCM. It was calculated according to eq 1. bref: reference. c″√″ indicates the protein can be detected in human plasma.

a

As shown in Figure 3C, among the secreted proteins identified from the secretome of NC tissues, 269 proteins were identified both in CM and lectin-captured samples, covering 77.3% of those identified in the corresponding CM without lectin capture. In addition, 207 proteins were only identified in the lectin-captured samples, which was significantly more than the 79 proteins only identified in the corresponding CM. The coverage tendency of secreted proteins identified in the secretome of CRC tissues was similar to the secreted proteins identified in the secretome of NC tissues. These data indicated that the application of lectin capture led toward a more comprehensive profiling of tissue culture based secretome. We then focused on the secreted proteins identified in the lectincaptured samples for further analysis.

factors, cytokines. Among 123 DESPs, 70 proteins could be classified as ECM components (51) and ECM remodeling proteins (enzymes and inhibitors/activators, 31), suggesting the modulation of ECM is a significant event during the initiation of CRC. We further explored the molecular functions of 123 DESPs. As shown in Figure 4C, the top three molecular functions were protein binding activity (101, 82.1%), catalytic activity (49, 39.8%), and metal ion binding activity (48, 39.0%). We also analyzed the involved biological processes of identified DESPs. The DESPs were involved in multiple biological processes (Figure 4D). The top three biological processes were regulation of biological process (81, 65.9%), metabolic process (79, 64.2%) and response to stimulus (77, 62.6%).

Identification and General Analysis of DESPs

Novel Identified DESPs

Among the total of 1446 identified proteins, via ProteinCenter analysis, 413 proteins were defined as secreted proteins. In these proteins, 313 and 341 proteins were identified from the NCM and the CCM, respectively. The overlap of identified secreted proteins were further analyzed. 241 secreted proteins were detected in both CM, while 72 and 100 secreted proteins were only detected in the NCM and the CCM, respectively (Figure 4A). Based on spectral counting of unique peptides, we used the Student’s t test to identify the DESPs between the CRC tissues and NC tissues with the criteria of p value 2. We found 123 DESPs, with 68 up-regulated and 55 down-regulated in CRC tissues (Supplementary Table 2, Supporting Information). The detailed information of the 123 DESPs is shown in Supplementary Table 3 (Supporting Information). To better understand the roles of DESPs in the initiation and progression of CRC, we categorized the 123 DESPs into several classes, including extracellular matrix (ECM) components (51, 41.5%), enzymes and inhibitors/activators (47, 38.2%), immune response related proteins (26, 21.1%), growth factors/cytokines and related proteins (15, 12.2%), and unclassified DESPs (20, 16.3%) (Figure 4B). Notably, the DESPs covered relatively high abundant secreted proteins, such as ECM components and their remodeling proteins, and relatively low abundant secreted proteins, such as growth

To identify novel DESPs found in this work, the 123 DESPs were extensively compared with previous studies to confirm whether they have been reported before. First, we compared DESPs with functional genomics studies of CRC tissues.32−40 For example, Agrawal et al. demonstrated the CRC related genes by comparing the expression of genes in human normal, adenoma, and tumor tissue samples with different stages.37 Among those, 107 genes showed progressive increases or decreases in expression with tumor stage, and six of them coincided with our identified DESPs, including TIMP1, COL1A2, CD55, ADAMDEC1, SPARC, and SERPINA1. Kwong et al. assessed both genes and proteins which expressed differentially among normal, adenoma and CRC tissues at various stages.38 Among the 70 genes which changed more than 3-fold between tumor and normal tissues, 12 genes showed a similar up-/down-regulation tendency with our results, including CTHRC1, POSTN, MMP2, COL1A1, COL5A1, COL12A1, COL5A2, COL4A2, THBS2, BCHE, VCL, and SERPINA1. Combined with other genomics results, we found a total of 28 DESPs were previously reported by transcriptional profiling studies. Second, we compared our DESPs with CRC-related proteins identified by proteomic studies.41−49 Conrotto et al. identified the proteins dysregulated in CRC tissues based on the ex vivo perfusion of surgically resected tumor and normal colon tissues using a reactive biotin ester derivative followed by the 3288



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Table 3. Members of Three Important Families among the DESPs normalized spectral count (mean ± SD)

IPI ID fibulin family IPI00296534 IPI00296058 IPI00029658 IPI00045512 IPI00023824 IPI00294615 serpin family IPI00007118

IPI00009890 IPI00007221 IPI00553177

gene symbol FBLN1 EFEMP2 EFEMP1 HMCN1 FBLN2 FBLN5

NCM 0.0 1.3 7.0 0.0 41.7 13.7

± ± ± ± ± ±

0.0 2.3 8.2 0.0 10.7 8.0

identified/studied in CRC

CCM

p value

± ± ± ± ± ±

0.000 0.000 0.000 0.034 0.000 0.031

10.113 5.517 5.151 3.786 2.690 2.526

1365.0 117.0 291.3 16.0 275.3 84.7

218.2 11.8 41.8 8.7 29.9 36.9

Rsc

a

genomics (refb)

proteomics (ref)

others (ref)

58 41

plasma proteome database √c √ √ √ √ √

breast (59)

CRC (64, 65), glioma (66), head and neck squamous cell carcinoma (67)

SERPINE1

0.0 ± 0.0

10.3 ± 4.5

0.017

3.211

52

√

SERPINE2 SERPINA5 SERPINA1

0.0 ± 0.0 2.0 ± 3.5 419.7 ± 45.5

6.7 ± 2.9 8.7 ± 1.5 1179.7 ± 170.7

0.016 0.038 0.002

2.662 1.608 1.498

53

√ √ √

94.3 ± 6.7

18.0 ± 14.1

0.001

−2.314

± ± ± ± ± ± ± ±

0.004 0.002 0.033 0.045 0.049 0.018 0.000 0.003

5.240 3.678 1.251 1.011 −2.293 −2.365 −3.749 −7.154

IPI00027444 SERPINB1 peptidase S1 family IPI00022246 AZU1 IPI00027769 ELANE IPI00296165 C1R IPI00017696 C1S IPI00028064 CTSG IPI00654888 KLKB1 IPI00024657 GZMA IPI00013937 CMA1

0.0 19.7 115.3 47.3 14.7 10.3 82.7 176.3

± ± ± ± ± ± ± ±

0.0 9.6 46.3 11.7 7.0 3.8 2.1 47.2

46.0 266.0 276.0 96.7 2.0 1.0 5.0 0.0

13.1 56.3 74.0 27.2 3.5 1.7 4.4 0.0

37, 38

45

41

35

potential serum cancer biomarker (ref)

prostate (68) gastrointestinal (69), hepatocellular (70), breast (71), lung (72, 73), prostate (73), myeloma (74)

√ √ √ √ √ √ √ √ √

RSC: the spectral count fold-change ratio for protein between CCM and NCM. It was calculated according to eq 1. bref: reference. c″√″ indicates the protein can be detected in human plasma.

a

proteomic identification of labeled proteins.41 Among the differentially expressed proteins they identified, 11 proteins showed a consistent up-/down-regulation tendency with our DESPs, including LCN2, COL12A1, MMP2, EFEMP1, ELANE, ABP1, PRDX4, ITIH2, GSN, OLFM4, and S100A9. Kim et al. identified 51 differentially expressed proteins by comparing the tumor tissues and paired normal tissues.42 Among those proteins, two coincided with our identified DESPs, including S100A8 and S100A9. Compared with other proteomics studies, 10 proteins were found to be overlapped with our DESPs, including SPARC,43 CALR,44 SERPINB1,45 LGALS3,46 ALDOA,46 S100A8,47 S100A9,47 AGR2,48 and OGN.49 Combining these results together, a total of 19 DESPs were reported by previous proteomics studies. To avoid omission of the DESPs which were identified by other studies, we searched against PubMed with keywords of “gene/protein name and colorectal/colon cancer” for each of the remaining DESPs. This analysis identified additional 20 reported DESPs, such as LOXL2,50 CTSL1,51 SERPINE1,52 and SERPINE2.53 All together, among 123 DESPs, 63 DESPs have been reported to be related with CRC in previous studies (shown in Tables 2 and 3 and Supplementary Table 2, Supporting Information). The remaining 60 novel identified proteins included 21 ECM related proteins, 25 enzymes and inhibitors/ activators, 17 immune response related proteins, and 5 growth factors/cytokines and related proteins.

Top 10 Up-Regulated DESPs and Important Families in DESPs

We further focused on the top 10 up-regulated DESPs (Table 2), including 7 ECM components (FBLN1, THBS2, TGFBI, CTHRC1, LTBP1, EFEMP2 and MMP1), 3 enzymes (AEBP1, MMP1 and PLOD1), 2 growth factors and related proteins (TGFBI and LTBP1), and 1 unclassified protein (ISLR). Within the top 10 up-regulated DESPs, 5 proteins have been reported and 5 proteins are first found in this work. We were also interested in those DESPs belonging to the same family (Table 3). Among the 51 DESPs which were classified as ECM components, we found 6 proteins belonging to the fibulin family, including FBLN1, EFEMP1, EFEMP2, HMCN1, FBLN2, and FBLN5 (Table 3). The fibulin family consists of seven known members which are all secreted glycoproteins with distinctive features of a fibulin-type Cterminal domain preceded by a series of calcium-binding epidermal growth factor (EGF)-like modules, including fibulin 1 (BM90), fibulin 2, fibulin 3 (S15, T16, EFEMP1), fibulin 4 (MBP1, EFEMP2, UPH1, H411), fibulin 5 (DANCE, EVEC, UP50), fibulin 6 (Hemicentin, him4), and fibulin-7 (TM14).54−56 It has been widely reported that fibulins play critical roles in various biological processes, such as embryonic development and organogenesis, hemostasis and thrombosis, fibrogenesis, tissue homeostasis, and remodeling.57 It was also reported that fibulins may directly or indirectly interact with receptors at the cell surface and then contribute to the regulation of cell behavior, such as cell morphology, growth, adhesion, and motility.58 In the present work, 6 out of 7 fibulin 3289



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Figure 5. Comparison of EFEMP2 level in the CM of each paired CRC tissue (T) and NC tissue (N) by Western blot. The proteins in the CM of 9 paired CRC tissues and their NC tissues were separated individually on SDS-PAGE, and the EFEMP2 was then detected with antihuman EFEMP2 antibody.

family members were significantly overexpressed in the CCM (Table 3), indicating the fibulins may play critical roles in the CRC. Besides fibulins, we also identified several members of peptidase S1 family (including AZU1, ELANE, C1R, C1S, CTSG, KLKB1, GZMA, and CMA1) (Table 3) and serpin family (including SERPINE1, SERPINE2, SERPINA1, SERPINA5, and SERPINB1) (Table 3). Then we tried to narrow down the potential serum biomarker candidates from the top 10 up-regulated DESPs and those DESPs belonging to some families. First, we searched against the human plasma proteome database and found most DESPs could be detected in human plasma except CTHRC1 (marked in Tables 2 and 3). Then we searched against PubMed with keywords of “serum, cancer, gene/protein name” to exclude those proteins which have been reported as potential serum cancer biomarkers. We excluded 5 proteins, including FBLN1,59 MMP1,60−63 SERPINE1,64−67 SERPINA5,68 and SERPINA1.69−74 Some DESPs were differentially expressed in the serum of more than one cancer type, such as MMP1 and SERPINA1. Finally we identified 21 potential serum biomarker candidates as listed in Table 2 and Table 3.

Figure 6. IHC analysis of EFEMP2 expression level in NC, colorectal adenoma, and CRC tissues. Representative IHC staining patterns of EFEMP2 were presented. EFEMP2 was absent in NC tissues (a1−3), slightly expressed in colorectal adenoma tissues (b1−3), and strongly expressed in CRC tissues (c1−3). (a2−c2, enlargements of representative portions in a1−c1. a3−c3, enlargements of representative portions in a2−c2.) Scale bar: 100 μm.

Validation of EFEMP2 as CRC Biomarker

Among the 21 potential serum biomarker candidates, we noticed that EFEMP2 was one of the top 10 up-regulated DESPs and it also belongs to fibulin family. The mRNA expression level of EFEMP2 was found to be up-regulated in colon tumor tissues of 7 patients (9 patients total) when compared with paired normal tissues.58 EFEMP2 exhibited oncogenic activity in both mutant p53-dependent and -independent manners.75 Gallagher et al. found that EFEMP2 can synergize with mutant p53 to promote tumor cell growth and increase rates of neoplastic transformation.75 Heine et al. found that hamster EFEMP2 promoted an increased growth rate of stably transfected macrophage cell line.76 Thus, we chose EFEMP2 for further validation. We first validated the level of EFEMP2 in the CM of 9 paired CRC and NC tissues by Western blot experiments (Figure 5). We found that EFEMP2 was up-regulated in the CRC tissues of 6 paired samples (patient 1, 2, 3, 5, 7 and 9). In paired samples from patients 4 and 6, EFEMP2 showed similar level. Only in one paired sample (patient 8) did EFEMP2 show downregulation in the CM of CRC tissue. We also validated the level of EFEMP2 in the lysates of 9 paired CRC and NC tissues by Western blot experiments (Supporting Information). The result (Supplementary Figure 2, Supporting Information) was highly consistent with that from the CM of cultured tissue. These data were consistent with MS data, indicating that most CRC tissues expressed higher levels of EFEMP2 than NC tissues. Then we tested the expression level of EFEMP2 in the CRC, colorectal adenoma and NC tissues by IHC. One hundred and twenty-three paraffin-embedded tissues, including 88 CRC tissues, 19 colorectal adenoma tissues, and 16 NC tissues, were stained against antihuman EFEMP2 antibody. Figure 6 showed the typical staining results. The staining for EFEMP2 was located in the cytoplasm of CRC cells and the stroma of CRC

tissues. The staining of EFEMP2 was usually absent in NC tissues (Figure 6, a1−3). In colorectal adenoma tissues, negative staining and weakly positive staining were usually observed (Figure 6, b1−3). Notably, positive staining and strongly positive staining were observed in CRC tissues (Figure 6, c1−3), including those in early stage. As shown in Table 4, the semiquantitative scoring of IHC results showed that the average score of CRC tissues (5.62 ± 3.79) was significantly higher than that of NC tissues (0.31 ± 0.68) and colorectal adenoma tissues (0.74 ± 1.16), indicating that EFEMP2 was overexpressed in CRC tissues. Noteworthy, the average score of immunoreactivity of CRC tissues at UICC stage I was 3.11 ± 3.94, which was significantly higher than the average score of NC tissues (p < 0.01) and colorectal adenoma tissues (p < 0.05). In stage II−IV, the average scores were further elevated to 5−8. These data indicate CRC tissues overexpress EFEMP2 at all tumor stages. This suggests that EFEMP2 has the potential to be used as a biomarker for early detection of CRC. Next, we assessed the EFEMP2 level in the serum of CRC patients, adenoma, and healthy controls. We first compared the EFEMP2 level in 7 serum samples from CRC patients and 7 serum samples from healthy controls with Western blot experiment. The antihuman EFEMP2 antibody showed good reactive specificity. There was only one main positive band detected at expected EFEMP2 molecular mass of 49 kDa (supplementary Figure 3). Western blot analysis showed the serum level of EFEMP2 was up-regulated in most of CRC patients (Figure 7A). Then we stepped further to assess the serum level of EFEMP2 by ELISA experiments in a large number of samples, including 79 serum samples from healthy 3290



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Table 4. EFEMP2 Immunoreactivity in Normal Colorectal, Adenoma, and CRC Tissues samples controls normal adenoma CRC (all stages) UICC staging I II III IV

cases

negative (%)

weakly positive (%)

positive (%)

strongly positive (%)

average score

16 19 88

81.3 (13/16) 63.2 (12/19) 11.4 (10/88)

18.7 (3/16) 31.6 (6/19) 19.3 (17/88)

0 5.3 (1/19) 40.9 (36/88)

0 0 28.4 (25/88)

0.31 ± 0.68 0.74 ± 1.16 5.62 ± 3.79a,b

23 29 26 10

39.1 (9/23) 3.4 (1/29) 0 0

26.1 (6/23) 13.8 (4/29) 19.2 (5/26) 20.0 (2/10)

21.7 (5/23) 34.5 (10/29) 53.8 (14/26) 70.0 (7/10)

13.0 (3/23) 48.3 (14/29) 26.9 (7/26) 10.0 (1/10)

3.11 7.24 6.20 5.21

± ± ± ±

3.94c,d 3.38e 3.34f 2.94

a

Student’s t test, p < 0.01 (NC versus CRC). bStudent’s t test, p < 0.01 (adenoma versus CRC). cStudent’s t test, p < 0.01 (NC versus UICC I). Student’s t test, p < 0.05 (adenoma versus UICC I). eStudent’s t test, p < 0.01 (UICC I versus UICC II). fStudent’s t test, p < 0.01 (UICC I versus UICC III). d

the IHC results, the serum level of EFEMP2 was significantly elevated in UICC stage I when compared with healthy controls (p = 2.00 × 10−13) and colorectal adenoma subjects (p = 0.003), indicating EFEMP2 is a promising serum biomarker for the early detection of CRC. Since CEA is the most commonly used serum biomarker for CRC in clinic, we compared the performance of CEA with EFEMP2 in CRC diagnostic accuracy and early detection. We first detected the CEA concentration in the same set of serum samples. Consistent with previous studies, the CEA concentration was slightly increased in the early stage CRC patients and increased to a higher level in late-stage CRC patients.3,4 Then we further compared the diagnostic accuracy of EFEMP2 and CEA by performing the ROC analysis. The area under the curve of EFEMP2 was 0.923 (95% confidence interval, 0.8849 to 0.9605), which was greater than that of the CEA (0.728; 95% confidence interval, 0.6587 to 0.7973). The cutoff values for EFEMP2 and CEA allowing optimal accuracy of tests were 1.903 (OD405) and 2.645 ng/mL, respectively. These values yielded sensitivity and specificity of 82.8% and 93.7% for EFEMP2, and 62.9% and 77.2% for CEA, respectively. Notably, when using these cutoff values to diagnose the CRC patients of UICC stage I, the diagnostic positive rate of EFEMP2 was as high as 93.3% (14/15), which was obviously higher than CEA (33.3%, 5/15). These results indicated that EFEMP2 was superior to CEA both in diagnostic accuracy and early detection, indicating EFEMP2 is a promising serum biomarker for CRC early detection.

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Figure 7. Analysis of serum level of EFEMP2 in CRC patients. (A) Detection of the differential EFEMP2 level in the serum of CRC patients and healthy controls by Western blot. Coomassie staining of the PVDF membrane served as a loading control. (B) Comparison of the serum level of EFEMP2 among 79 healthy controls, 14 adenoma subjects, and 122 CRC patients at different UICC stages by ELISA experiment. Horizontal bars represented the mean OD405 value. **, p < 0.01. (C) ROC analysis of EFEMP2 and CEA for the discrimination between CRC patients and normal subjects. AUC, area under the ROC curve.

CONCLUSION The identification of tumor-secreted proteins under nearphysiological conditions facilitates the discovery of promising novel serum biomarkers. In the present study, we compared the secretome of fresh cultured CRC tissues and paired NC tissues. The adoption of lectin affinity capture enriched the secreted proteins in CM, significantly decreasing the severe contamination of interfering proteins from dead cells in fresh tissue based culture system and leading to efficient detection of secreted proteins. We found 123 DESPs between the CRC tissues and NC tissues of which 68 DESPs were up-regulated in CRC tissues. Noteworthy 60 DESPs were first found to be related to CRC in this work. These proteins have the potential to be used as biomarkers for CRC early detection, either used individually or combined with other proteins. One of them, EFEMP2, was further validated as a promising tissue and serum biomarker for CRC early detection evidenced by the

controls, 14 from colorectal adenoma subjects, and 122 from CRC patients at different stages. Compared to the healthy controls, the serum level of EFEMP2 in colorectal adenoma subjects was slightly increased, evidenced by the increase of OD405 from 1.56 ± 0.27 to 1.83 ± 0.35 (Figure 7B). Notably, the serum level of EFEMP2 was significantly increased for CRC samples at UICC I - IV stages. The mean OD405 for each CRC stage was elevated to around 2.2 (Figure 7B). Consistent with 3291



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significantly higher abundance of EFEMP2 in the tissue and serum of CRC patients even at the early stage.

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ASSOCIATED CONTENT

* Supporting Information S

Comparison of β-actin level in the CM and lysates of colorectal tissues and HT29; comparison of EFEMP2 level in the tissue lysates of each paired CRC tissue (T) and NC tissue (N) by Western blot; antigenic specificity of the antihuman EFEMP2 antibody; methodological details for cell conditioned medium collection, HT29 cell viability assay and validation of the EFEMP2 level in tissue lysates; Supplementary Tables 1−3. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*(C.H) Tel: 86-571-86002146. Fax: 86-571-86044817. E-mail: [email protected]. (X.H., L.X.X.) Tel: 86-21-62933234. Fax: 86-21-62933231. E-mail: [email protected], lisaxu@sjtu. edu.cn. Author Contributions ∥

Both authors contributed equally to this work.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We thank the Instrumental Analysis Center of Shanghai Jiao Tong University for support of the mass spectrometry analysis. This work was supported by the Ministry of Science and Technology of China (973 Program, 2010CB834300) and National Natural Science Foundation of China (81071792). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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