A total of 144 colorectal carcinoma samples were collected after obtaining informed consent in our hospital (Fudan University Shanghai Cancer Center, Shanghai, China). None of the patients received chemotherapy or radiotherapy before surgery. Resected specimens were reviewed by two senior pathologists according to the criteria described in the American Joint Committee on Cancer Cancer Staging Manual (6th edition, 2002)[18]. For the screening and confirmation study, 32 primary CRC tissue samples that were obtained from patients who underwent curative resection in 2009 were collected and divided into two groups of LNM CRC and non-LNM CRC, with 16 cases in each group. The number of lymph nodes retrieved was not less than 12 in the non-LNM CRC. None of them had distant metastasis. The fresh colorectal tumor tissues were obtained immediately after surgery, washed twice with chilled phosphate buffered saline (PBS), immediately stored in liquid nitrogen and at -80°C in our tissue bank until further use. The detailed clinical data of these patients is provided in Table 1. For the S100A4 expression study, paraffin-embedded tissues in another independent set of 112 primary CRC samples between January and August 2004 were used for immunohistochemistry assessment. Ethical approval was obtained from the Cancer Center Research Ethics Committee.

Frozen samples were crushed to powder in liquid nitrogen, and dissolved in lysis buffer [7 mol/L urea, 2 mol/L thiourea, 100 mmol/L DTT and 1 × protease inhibitor cocktail (Roche, Penzberg, Germany)] by continuous vortex at 4°C for 1 h. After centrifugation at 15 000 r/min for 45 min at 4°C, equal amounts of each sample from LNM CRC and non-LNM CRC groups were pooled together. One hundred micrograms of proteins from each sample pool were reduced with 10 mmol/L dithiothreitol (60 min, 56°C) and alkylated with 12 mmol/L iodoacetamide in darkness (45 min, 37°C), followed by digestion with 1:20 (w/w) ratio of trypsin (Promega, Madison, WI, USA) overnight at 37°C. The lyophilized peptides from LNM CRC sample were tagged with d0-methanolic HCl, whereas those from non-LNM CRC samples were labeled with d3-methanolic HCl (Sigma-Aldrich, St. Louis, MO, USA) as previously described[13,19]. Briefly, 100 μL of d0-methanolic HCl or d3-methanolic HCl (created by dropwise addition of 160 μL acetyl chloride with stirring to 1 mL d0-methanol or d3-methanol) was added to the corresponding sample. The reaction was allowed to proceed for 2 h at room temperature. After lyophilization and re-dissolving in 100 μL 5% acetonitrile in 0.1% formic acid, the two peptides were mixed, followed by desalination using Sep-Pak Vac C18 (Waters, Milford, MA, USA). They were lyophilized again and re-dissolved in 40 μL of the above-mentioned solution. Subsequently, the resultant sample was separated by a 2D microcapillary HPLC system, followed by MS/MS analysis using an LTQ Orbitrap (Thermo Fisher, San Jose, CA, USA). LC solvent gradients were controlled by the chameleon 6.5 (Dionex, Amsterdam, The Netherlands). The MS scan was operated in the data-dependent mode to switch automatically between MS and MS/MS acquisition. Fragment ion selection was based on ion intensity (above 10 counts) and charge state (+2, +3).

Bioworks 3.3.1 was used to generate the peaklists of all acquired MS/MS spectra, which were then automatically searched against the International Protein Index human protein sequence database, version 3.43 using SEQUEST (University of Washington, licensed to Thermo Fisher), with a 95% confidence level. Except for 57 Da reductive alkylation modification on Cys, static modifications were set on Asp, Glu, C-terminal (+14 Da and +17 Da for light and heavy isotope labeling, respectively). The mass tolerance of the peptides and fragment ions was 10 ppm and 1.0 Da, respectively. The identified peptides were further analyzed with two computer software programs, PeptideProphet and ProteinProphet. PeptideProphet with a probability score of 0.9 and ProteinProphet with a probability score of 0.95 were used to ensure an overall false-positive rate below 0.005. Quantification of the ratio of each protein was achieved using the Xpress program. Proteins with expression fold change > 2.5, P < 0.05 were defined as differentially expressed proteins.

The same protein samples for screening were used for Western blotting. Briefly, 30-μg protein samples from each case were separated by 10% SDS-PAGE and subsequently transferred to PVDF membranes. The membranes were incubated with rabbit polyclonal antibody against S100A4 (1:1000 dilution; Abcam, Cambridge, UK) and then incubated with a horseradish-peroxidase-conjugated secondary antibody (1:100 dilution; Proteintech, Chicago, IL, USA). β-actin was detected simultaneously as a loading control (anti-β-actin, 1:1000 dilution; Kangchen, Beijing, China). All blots were visualized using an ECL detection system (Amersham, Arlington Heights, IL, USA )and quantitated by densitometry using an LAS-3000 imager.

S100A4 expression was examined immunohistochemically using paraffin-embedded tissues. In brief, 4-μm-thick tissue sections were heated in 6.5 mmol/L citrate buffer (pH 6.0) at 100°C for 28 min, and incubated with antibody against S100A4 (1:200 dilution). Immunostaining was performed employing the DAKO En-Vision System (Dako Diagnostics, Zug, Switzerland). In the negative control group, PBS was used instead of primary antibody. S100A4 expression was scored by two independent experienced pathologists. Each sample was graded according to the intensity and extent of staining as described previously[11]. The intensity of staining was scored as 0 (no staining), 1 (weak staining), and 2 (strong staining). The extent of staining was based on the percentage of positive tumor cells: 0 (no staining), 1 (1%-25%), 2 (26%-50%), 3 (51%-75%), and 4 (76%-100%). The final score was assessed by summarizing the results of intensity and extent of staining. The case was considered negative if the final score was 0 or 1 (-) or 2 or 3 (±), and positive if the score was 4 or 5 (+) or 6 or 7 (++). In most cases, the two reviewers provided consistent results. Any inconsistencies were resolved by discussion to achieve a consensus score.

Total tissue RNA was extracted using the Rneasy Mini Kit (Qiagen, Valencia, CA, USA). Real-time quantitative PCR analysis was performed according to the manufacturer’s instructions (the Quant SYBR Green PCR Kit, TIANGEN BIOTECH, Beijing, China). β-actin was applied as an internal control. The primers for β-actin (205 bp) were 5'-TGACGTGGACATCCGCAAAG-3' (sense) and 5'-CTGGAAGGTGGACAGCGAGG-3' (antisense). The primers for S100A4 (185 bp) were 5'-GCCCTGGATGTGATGGTGT-3' (sense) and 5'-TCGTTGTCCCTGTTGCTGTC-3' (antisense). Each assay was done in triplicate, and the average was calculated. For relative quantification, 2^-ΔΔCt was calculated and used as an indication of the relative expression levels.

The Student t test was used to evaluate the differences in S100A4 expression between LNM CRC and non-LNM CRC. The χ² test was used to assess the relationships between S100A4 expression and clinicopathological factors. The cumulative recurrence and survival probability were estimated using the Kaplan-Meier method, and differences were calculated by log-rank test. Prognostic factors were determined using Cox regression analysis. The recurrence-free and overall survival times were calculated from the first resection of the primary tumor to first evidence of recurrence or to death from any cause, respectively. The diagnosis of recurrence was based on the typical features presented on computed tomography/magnetic resonance imaging and elevated serum carcinoembryonic antigen. All P values were two-sided, and P < 0.05 was considered to be significant. Statistical analyses were performed using SPSS 13.0 software.

To perform accurate quantitative analysis, we compared the protein expression profiles between LNM CRC and non-LNM CRC using methyl esterification stable isotope labeling combined with 2D-LC-MS/MS. The quantitative differential expression of 644 proteins was identified, after calibration with β-casein. Significantly, 43 of these (6.7%) proteins were displayed differentially (at least 2.5-fold) in LNM CRC compared with non-LNM CRC. Among these 43 proteins, 28 were found to be upregulated in LNM CRC (Table 2), and 15 were downregulated (Table 2). The identification of S100A4 significantly upregulated in LNM CRC is shown in Figure 1 as an example. These differentially expressed proteins formed the possible protein profiles associated with LNM in CRC.

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Figure 1 Identification of quantitatively dysregulated expression of S100A4. A: Quantification of S100A4 through the isotopically labeled fragment ion signals of the peptide “TDEAAFQK”. The areas under the monoisotopic peaks represent the relative abundance of peptides, light [lymph node metastasis (LNM)]/heavy (non-LNM) = 3.04:1; B: Identification of the peptide “TDEAAFQK” from S100A4 by MS/MS.

We extended the experiments to confirm the differential expression of S100A4 in the same samples described above.

Thirty micrograms of total proteins from LNM CRC and non-LNM CRC were analyzed via Western blotting. The expression of S100A4 was dramatically higher in LNM CRC compared with non-LNM CRC (P < 0.001). A representative Western blotting result is presented in Figure 2A.

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Figure 2 Confirmation of the overexpression of S100A4 in colorectal cancer. A: Western blotting analysis for S100A4 expression in colorectal cancer (CRC) specimens. β-actin was used as the internal loading control. The histogram shows the relative expression levels of S100A4 in non-LNM (16 cases) and lymph node metastasis (LNM) (16 cases) groups. Data represent the mean ± SE (P < 0.001, Student t test); B: Immunohistochemical study of S100A4 distribution and expression in CRC specimens at 20 × 10 magnification. a: There was no immunoreactivity in the normal mucosa; b: Weak staining in cancer cells in the non-LNM group; c: Strong staining in cancer cells in the LNM group; d: Marked metastatic lymph nodes (arrow); C: mRNA level of S100A4 via real-time quantitative polymerase chain reaction. S100A4 was consistently increased in the LNM group (16 cases) compared with non-LNM group (16 cases). The mRNA level was normalized to that of β-actin. Data represent the mean ± SE (P < 0.001, Student t test).

To confirm upregulation of S100A4 at the protein level, we used immunohistochemistry to evaluate S100A4 expression in situ. In normal mucosa, there was no immunoreactivity in cells. In non-LNM CRC, there was weak staining in cancer cells. In LNM CRC, there was notable brown staining in both primary and matched metastatic lymph node cancer cells. Positive staining was present mainly in the cytoplasm and/or nucleus of cancer cells (Figure 2B).

Real-time quantitative PCR revealed that S100A4 mRNA level was higher in LNM CRC than in non-LNM CRC (P < 0.001, Figure 2C), which is consistent with the trend at the protein level.

To detect the relationship between S100A4 expression and clinicopathological features and whether S100A4 could be a prognostic factor in predicting clinical outcomes of CRC patients, we evaluated S100A4 expression in an additional archived 112 CRC samples. In the group of 53 LNM CRC samples, 83% were positive for S100A4 expression, whereas 16.9% of the 59 non-LNM CRC samples had positive expression.

After division of these patients into S100A4-positive and S100A4-negative groups, statistical analysis revealed that positive expression of S100A4 was significantly associated with LNM, and advanced TNM stage (P < 0.001). However, no significant correlations were observed between S100A4 expression and other clinicopathological parameters of sex, age, tumor size, tumor differentiation and tumor location (Table 3).

Furthermore, we found that patients with S100A4-positive CRC had significantly poorer prognosis than those with S100A4-negative CRC. The 5-year cumulative recurrence rate was significantly higher in patients with S100A4-positive CRC than in the S100A4-negative group (P < 0.001, Figure 3A). The 5-year cumulative survival rate in patients with S100A4-positive CRC was much lower than in those with S100A4-negative CRC (P < 0.001, Figure 3B). Univariate analyses revealed that LNM, TNM stage and S100A4 expression were associated with recurrence and overall survival. In multivariate analysis, LNM, TNM stage and S100A4 expression were also independent prognostic factors of recurrence and overall survival (P < 0.05, Table 4).

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Figure 3 Overexpression of S100A4 correlated with poor prognosis in 112 colorectal cancer patients. A: Cumulative recurrence between the S100A4-positive and S100A4-negative groups (P < 0.001, log-rank test); B: Cumulative survival between the S100A4-positive and S100A4-negative groups (P < 0.001, log-rank test).

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide, and it is estimated that half of the patients die from cancer annually. Lymph node metastasis (LNM) is the most common form of metastasis although the mechanism is largely unknown. Studies on metastasis of CRC were performed in order to improve the diagnosis and prognosis.

LNM is a complicated process that involves a variety of dysregulated molecules playing a significant role. Increasingly, it has become a hot research topic to employ proteome analysis to identify proteins associated with tumor development and progression in various diseases.

To date, there has been a limited number of studies regarding specific tumor molecular markers associated with LNM in CRC. In this study, the authors employed more sensitive proteome analysis than conventional strategies to identify a set of differently expressed proteins associated with LNM. Furthermore, the authors confirmed the significant correlation between overexpression of S100A4 and LNM, advanced TNM stage, increased recurrence rate and decreased overall survival rate.

By identifying the protein S100A4 as being associated with LNM, the authors evaluated the biological features and prognosis in CRC, which could improve our understanding of CRC, and provide a scientific basis for the application of S100A4 inhibitors in the treatment of CRC.

Proteome: all proteins that derive from the genome of cells, a tissue or an organism. It is a dynamic collection that reflects both the intrinsic genetic information of the cell and the impact of its immediate environment. Compared with gene analysis, proteome analysis can provide a more accurate view of the biological status and be expected to be more useful for evaluating, for example, disease development, progression and response to treatment.

The authors performed also an extensive proteomics analysis, and identified 43 proteins that were differentially regulated in metastatic cancer, including 16 proteins that were upregulated even more than S100A4. The results indicate that overexpression of S100A4 could be used as biomarker for LNM in CRC. However, none of the latter candidate biomarkers were further examined in terms of prognostic value.