Models for the pathogenesis of colorectal cancer tend to focus on the localized lesion, with less attention paid to changes in normal-appearing mucosa. Here we used two-dimensional gel electrophoresis and mass spectrometry to define patterns of protein expression in morphologically normal colonic mucosa from 13 healthy subjects, 9 patients with adenomatous polyps, and 9 with cancer. Tumor samples were also compared with the normal mucosa. Systematic gel comparisons identified a total of 839 spots that differed significantly between one or more groups (P < 0.05). Principle component analysis indicated that the first three components accounted for ∼37% of the total variation and provided clear evidence that flat mucosa from healthy subjects differed significantly from that of patients with polyps or cancer. Sixty-one proteins differed significantly between mucosa from healthy subjects and all other tissue types, and 206 differed significantly between healthy mucosa and polyp mucosa. Several of the proteins showing significant underexpression in tumor tissue were cytokeratins and other cytoskeletal components. In contrast, cytokeratins, including several isoforms of cytokeratin 8, were overexpressed in apparently normal mucosa from polyp and cancer patients compared with mucosa from healthy subjects. These findings indicate that protein expression in the apparently normal colonic mucosal field is modified in individuals with neoplastic lesions at sites distant from the lesion. Recognition and further characterization of this field effect at the molecular level may provide protein biomarkers of susceptibility to colorectal cancer and facilitate development of hypotheses for the role of diet and other environmental factors in its causation. (Cancer Res 2006; 66(13): 6553-62)

The central paradigm for the pathogenesis of colorectal cancer is the adenoma-carcinoma sequence, a complex stepwise series of changes in cellular proliferation and differentiation, driven by a progressive accumulation of genetic abnormalities, leading to malignancy via adenomatous polyps (1). It is increasingly recognized that this model is probably inadequate in that other molecular abnormalities, including modified epigenetic marks, also contribute and may define alternative pathways to neoplasia (2). However, most current mechanistic models focus almost exclusively on the localized lesion, with much less attention paid to pathologic changes occurring in the normal-appearing mucosa from which such lesions emerge. Physiologic anomalies in the flat mucosa, including abnormal cell proliferation (3, 4), apoptosis (5), and gene expression (6), have previously been reported but the nature, duration, and causes of such putative field effects are poorly defined.

The physiologic state of a complex tissue is reflected in the full complement of proteins expressed by its constituent cells. The pattern of expressed proteins thus constitutes a “library” of information about the functional status and health of the tissue. The development of new methods for protein extraction, display, and analysis has led to the emergence of a new field of clinical proteomics, in which these techniques are harnessed to identify biomarkers of cancer and other diseases (7), but there are few studies on the differential expression of proteins during early colorectal carcinogenesis.

Tracy et al. (8) described reproducible patterns of protein expression associated with the normal mucosa and specific differences associated with tumors. Similarly, Anderson et al. (9) compared hepatic and colorectal tumors with their normal host tissues, and with each other, and identified characteristic patterns of protein expression that could be used to distinguish primary and secondary tumors from their adjacent uninvolved tissues. Several other groups have reported similar findings and the development of proteomic technology has enabled a more comprehensive analysis of protein expression (10, 11). Among the most recent of these studies is that of Friedman et al. (12), who employed two-dimensional difference gel electrophoresis to compare tumor samples and macroscopically normal mucosa. Using this approach, Friedman's group observed 52 proteins for which statistically significant differences in abundance were detectable within the mucosa/tumor pairs from the same patients.

Although many different techniques for the collection and fractionation of tissues have been employed, virtually all previous studies have compared tumors with flat mucosa from the same individual. Whereas this approach provides a comparison of anatomically normal and neoplastic tissues against the same genetic background, it does not address the possibility that the apparently normal mucosa of healthy individuals differs from that of those with neoplastic lesions. The possibility of precancerous field changes that render the mucosa more vulnerable to the emergence of localized lesions has long been recognized but seldom explored. In the present study, we used proteomic techniques to test the hypothesis that colonic mucosa from disease-free patients would exhibit patterns of protein expression distinct from the mucosa of patients with adenomatous polyps or cancer. Tumors from the cancer patients were also compared with each group of normal mucosal samples.

Patients and biopsies. Volunteers were either patients with previously diagnosed colorectal cancer or outpatients with no known major pathology, typically presenting for investigation of symptoms, including abnormal bowel habit or rectal bleeding, and undergoing flexible sigmoidoscopy or colonoscopy as a diagnostic procedure. All patients were recruited from the gastroenterology outpatient and surgical lists of the Wansbeck General Hospital, Ashington, Northumberland, United Kingdom. Ethical approval for the project was received from the Northumberland Local Research Ethics Committee (project reference NLREC2/2001). Patients were contacted in advance and sent an information leaflet, and those patients consenting to the study were advised to attend endoscopy or theatre as expected. Experimental biopsies were collected from the rectum of the endoscopy patients, in addition to those obtained for diagnostic purposes. For the cancer patients, samples of normal rectal mucosa (>10 cm from tumor margin) and tumor tissue were collected at surgery. All samples were immediately snap frozen in liquid nitrogen and transferred to a −80°C freezer. Medical notes for each volunteer were reviewed 6 to 8 weeks after the procedure and the findings of the pathology report and the conclusions of the responsible consultant were recorded. The final groups were composed of 13 “normal” individuals [9 females (mean age, 54.8 years; SD, 8.4 years) and 4 males (mean age, 68 years; SD, 3.6 years)] showing no evidence of neoplasia; 9 “polyp” patients [5 females (mean age, 66.6 years; SD, 15.4 years) and 4 males (mean age, 55.8 years; SD, 4.3 years)] in whom adenomatous polyps were detected at endoscopy; and 10 “cancer” patients. The latter group was composed of six females (mean age, 64.5 years; SD, 8.4 years) and four males (mean age, 66.5 years; SD, 11.6 years), most of whom had moderately differentiated adenocarcinomas of the recto-sigmoidal region (Table 1). Two-dimensional gel electrophoresis was done on 41 samples; one mucosal biopsy from a cancer patient was lost.

Table 1.

Characteristics of cancer patients from whom mucosal and tumor biopsies were obtained in the present study

Patient no.SexAge (y)Tumor siteDuke's stageHistology
51 Rectum Poorly differentiated adenocarcinoma 
66 Hepatic flexure Histopathology report incomplete 
60 Hepatic flexure Moderately differentiated adenocarcinomas 
72 Sigmoid colon C1 Moderately differentiated adenocarcinoma 
64 Sigmoid colon/rectum Moderately differentiated adenocarcinoma 
74 Hepatic flexure Moderately differentiated adenocarcinoma 
66 Ascending colon Moderately differentiated adenocarcinoma 
60 Sigmoid colon/rectum C1 Moderately differentiated adenocarcinoma 
83 Sigmoid colon/rectum Moderately differentiated adenocarcinoma 
10 57 Sigmoid colon/rectum Moderately differentiated adenocarcinoma 
Patient no.SexAge (y)Tumor siteDuke's stageHistology
51 Rectum Poorly differentiated adenocarcinoma 
66 Hepatic flexure Histopathology report incomplete 
60 Hepatic flexure Moderately differentiated adenocarcinomas 
72 Sigmoid colon C1 Moderately differentiated adenocarcinoma 
64 Sigmoid colon/rectum Moderately differentiated adenocarcinoma 
74 Hepatic flexure Moderately differentiated adenocarcinoma 
66 Ascending colon Moderately differentiated adenocarcinoma 
60 Sigmoid colon/rectum C1 Moderately differentiated adenocarcinoma 
83 Sigmoid colon/rectum Moderately differentiated adenocarcinoma 
10 57 Sigmoid colon/rectum Moderately differentiated adenocarcinoma 

Protein extraction. Mucosal biopsies and samples of tumor were thawed, weighed, and extracted without further manipulation. Resected mucosa was allowed to thaw and subsamples of mucosal tissue (10-15 mg) were scraped from the underlying muscle layers using a glass microscope slide. The tissue was extracted using Bio-Rad ReadyPrep Sequential Extraction Kit (Bio-Rad, Hemel Hempstead, United Kingdom) with the following additions to Reagent 1 just before use: MgCl2 (3 mmol/L), protease inhibitor cocktail (Sigma, Poole, United Kingdom; 2.5 μL/mL), DNase I (RNase-free; 5 units/mL), and RNase A (5 μg/mL). Modified Reagent 1 (25 μL) was added and each tissue sample was hand homogenized. A further 175 μL of Reagent 1 were added and the whole volume was sonicated for 10 minutes at room temperature, centrifuged to obtain a pellet, and the supernatant was removed. The volume equivalent to 100 μg protein was determined using a Bio-Rad Protein Assay according to the instructions of the manufacturer, with bovine γ globulin as standard. The extraction supernatants were stored at −80°C.

Two-dimensional gel electrophoresis. For isoelectric focusing in the first dimension, a sample volume equivalent to 100 μg protein was added to a rehydration mix, containing urea (7 mol/L), thiourea (2 mol/L), CHAPS (2%), bromophenol blue, DTT (18.2 mmol/L), and IPG buffer (0.5%, pH 4-7; GE Healthcare, Little Chalfont, United Kingdom) to make a final volume of 450 μL. The whole volume was transferred into a well of the Immobiline DryStrip re-swelling tray and IPG strips (24 cm, pH 4-7; GE Healthcare) were rehydrated overnight at 20°C. Each strip was then transferred to a ceramic strip-holder and submerged in DryStrip Cover Fluid (∼3.5 mL). The isoelectric focusing was run on an Ettan IPGphor bed (GE Healthcare) with a gradient of 500 V for 1 hour (500 V-h), 4,000 V for 1.5 hours (6,000 V-h), and a “step-n-hold” of 8,000 V for 6.75 hours (51,600 V-h). After completion of isoelectric focusing, the strips were stored at −80°C.

The second-dimension protein separation was carried out on 1-mm-thick 10% gels, prepared in 28 × 23-cm gel-plate cassettes. Focused strips were rinsed free of excess mineral oil, conditioned in modified Tris Acetate Equilibration Buffer (Genomic Solutions, Huntingdon, United Kingdom), treated first with 8 mg/mL DTT in equilibration buffer (9 mL; 30 minutes with gentle shaking), transferred to 25 mg/mL iodoacetamide in equilibration buffer (9 mL; 30 minutes with gentle shaking), and placed in a gel cassette before transfer to the gel tank. The top reservoir contained the cathode buffer (200 mmol/L Tris base, 200 mmol/L Tricine, 14 mmol/L SDS; Sigma) and the bottom reservoir contained the anode buffer (25 mmol/L Tris-acetate buffer, pH 8.3). Electrophoresis conditions were set to give an upper voltage of 500 V, power of 20,000 mW/gel, and a total run time of ∼3.5 hours.

Gel imaging and analysis. After electrophoresis, the gels were fixed and stained using SYPRO Ruby Protein Gel Stain (Bio-Rad) and imaged using ProXPRESS Proteomics Imaging System and Perkin-Elmer imaging software. Images were saved as TIF files and analysis was carried out using ProteomWeaver analysis software (Definiens, Munich, Germany). Four gel groups were established representing the anatomically normal mucosa from 13 healthy patients (“healthy mucosa”), 9 polyp patients (“polyp mucosa”), and 9 cancer patients (“cancer mucosa”), and samples of tumor from 10 cancer patients (“tumor tissue”). Each gel underwent automatic spot detection and manual editing before automatic spot matching both within and between groups. Manual matching was done where necessary. Base-paired normalization was done on all the gels before examination of spot volume data. Average gels were constructed using spots that were detectable in a minimum of 50% of the gels in each group. Selected spots were picked from a gel using the ProPick spot-picking robot (Genomic Solutions) and gel plugs were transferred to a modified 96-well microtitre plate.

Protein analysis. In-gel trypsin digestion was carried out using a ProGest Protein Digester (Genomic Solutions). After preincubation, the digestions were carried out at 37°C for 3 hours using 50 ng of sequencing grade porcine trypsin (5 μL/well; Promega, Southampton, United Kingdom). The digests were analyzed using a Reflex III MALDI/ToF (Bruker Ltd., Coventry, United Kingdom) with Scout 384 ion source, fitted with a nitrogen laser (wavelength, 337 nm) to desorb/ionize the matrix/analyte material from the sample substrate. All spectra were acquired in a positive-ion reflector set at the following variables: 25 kV acceleration voltage, 28.7 kV reflection voltage, 20.9 kV ion source acceleration voltage, and 1.65 kV reflector-detector voltage. Calibration was carried out using a set of peptide standards having an approximate concentration of 1 pmol/μL from spots adjacent to the samples. In some cases, quadrupole time-of-flight mass spectrometry was done using a Micromass quadrupole time-of-flight electrospray fitted with a Waters Cap LC system.

Peptide masses obtained from the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry were searched (on the basis of mass) against the MSDB protein database using the Mascot peptide mass fingerprint program from Matrix Science.4

The search parameters were as follows: (a) tryptic digest was assumed to have a maximum number of one missed cleavage; (b) peptide masses were stated to be monoisotopic; (c) methionine residues were assumed to be partially oxidized; (d) the carbamidomethylation of cysteine residues was considered; (e) the mass tolerance was kept at 75 ppm; and (f) the taxonomy group searched was Homo sapiens. The results give a Probability Based Mowse Score (13), equal to −10×Log(P), where P is the probability that the observed match is a random event. Protein scores >63 are considered statistically significant (P < 0.05) under the above parameters.

Statistical analysis. Gels were normalized in accordance with ProteomWeaver software protocols using base-paired normalization. The spot-density data were transferred to Excel spreadsheets for statistical analysis using a nonparametric inference approach. Statistical filtering retained only those spots for which average spot-density was >0.07 (arbitrary units), the within-group frequency was >50%, or which were present in more than 6 of the 41 gels. To test the null hypothesis of equal distribution of protein expression between groups, a nonparametric one-way ANOVA (Kruskal-Wallis) was done on the ranked data (14). The null hypothesis was rejected for any protein where the rank differed significantly (P < 0.05) in at least one of the four groups. For all proteins showing evidence of unequal expression between groups, principal component analysis was carried out on the correlation matrix of the ranks of the 41 independent samples. F tests were used to assess the significance of differences between groups and combinations of groups (15). Models were set up to determine whether a particular protein differed significantly between independent subsets of the four groups of observations. Differences were considered significant when the P value associated with the F statistic was <0.05.

Figure 1A is a two-dimensional protein map based on the average gel for the healthy mucosa. The equivalent map for cancer mucosa is shown in Fig. 1B. Gel-analysis software identified a total of 6,494 unique spots across all the 41 gels and statistical filtering yielded 1,910 spots of potential interest. Among these, the Kruskal-Wallis test identified a total of 839 spots for which the average density in one set of gels differed significantly (P < 0.05) from that in at least one other set. For these proteins, principle component analysis was carried out on the correlation matrix of the ranks of the 41 independent samples; the first three principal components were found to account for 37% of the total variability. Principal component 1, which was highly correlated with 166 proteins (correlation coefficient > 0.6) and represented ∼21% of the total variation, indicated that the greatest differences in the ranks of proteins occurred between the tumor tissues and the three sets of morphologically normal mucosa. A total of 72 of the 839 proteins differed significantly between tumor tissue and all three sets of mucosal tissues. The second principal component accounted for ∼10% of the total variation and was highly correlated with 56 proteins, 35 of which differed significantly among the three sets of normal mucosal samples. The third component accounted for about 6% of the total variation and was most highly correlated with the polyp mucosa. Figure 1C illustrates the coordinates for each tissue sample on the first three principal components. Each sample is numbered to indicate its origin from healthy mucosa (1), polyp mucosa (2), cancer mucosa (3), or tumor tissue (4). The separation of the tumor samples and the three sources of mucosa into discreet clusters is clearly apparent, with some evidence of a further segregation within group 3.

Figure 1.

Two-dimensional protein map based on the average gel for the healthy mucosa. A, arrows, positions and spot numbers for all the identified proteins listed in Table 2. B, a similar map of cancer mucosa is shown together with spot numbers and positions for proteins identified as cytokeratins. C, coordinates for each tissue sample on the first three principal components, following principal component analysis carried out on 839 proteins that differed significantly across the 41 samples of tissue analyzed. Each sample is numbered to indicate its origin from healthy mucosa (1), polyp mucosa (2), cancer mucosa (3), or tumor tissue (4).

Figure 1.

Two-dimensional protein map based on the average gel for the healthy mucosa. A, arrows, positions and spot numbers for all the identified proteins listed in Table 2. B, a similar map of cancer mucosa is shown together with spot numbers and positions for proteins identified as cytokeratins. C, coordinates for each tissue sample on the first three principal components, following principal component analysis carried out on 839 proteins that differed significantly across the 41 samples of tissue analyzed. Each sample is numbered to indicate its origin from healthy mucosa (1), polyp mucosa (2), cancer mucosa (3), or tumor tissue (4).

Close modal

Differential expression of proteins in tumor tissue compared with flat mucosa. Use of the F test for between-group comparisons indicated differential expression of 588 proteins in tumor tissue compared with healthy mucosa, 536 compared with polyp mucosa, and 520 compared with cancer mucosa. A total of 291 proteins differed significantly between tumor tissue and all three groups of flat mucosal samples; of these, 90 were underexpressed in tumor tissue and 201 were overexpressed. A large proportion of these proteins were so weakly expressed that analysis was impractical, but 26 were positively identified by mass spectrometry and are listed in Table 2.

Table 2.

Characteristics of 26 identified proteins differentially expressed in tumor tissue compared with healthy mucosa, polyp mucosa, and cancer mucosa

Spot no.Protein nameScoreAccession no.Theo. pITheo. MWAct. pIAct. MWExpression in tumorExpression in healthy mucosaFold changeExpression in polyp mucosaFold changeExpression in tumor mucosaFold changeP
117903 β-Actin 157 P60709 5.55 40,536 5.12 42,093 1.104 0.141 0.125 0.12 9.7 × 10−5 
17654 α1-Antitrypsin precursor 235 P01009 5.37 46,878 4.98 59,532 0.788 1.853 -2.3 1.692 -2.1 2.997 -3.8 8.8 × 10−4 
3385 Apolipoprotein A-I precursor 162 P02647 5.56 30,759 5.24 24,471 3.031 6.876 -2.3 5.381 -1.8 7.257 -2.4 2.3 × 10−3 
9315 Calgizzarin 70 P31949 6.56 11,847 5.86 12,048 2.032 0.594 3.4 0.56 3.6 0.765 2.7 5.5 × 10−7 
9669 Creatine kinase 261 P12277 5.34 42,902 5.43 42,655 2.571 9.158 -3.6 14.158 -5.51 8.004 -3.1 7.47 × 10−5 
12691 Cytokeratin 9 76 P35527 5.14 62,178 4.81 50,192 0.07 0.365 -5.2 0.809 -11.6 0.322 -4.6 1.9 × 10−3 
18566 Cytokeratin 19 268 P08727 5.04 44,065 4.87 45,588 0.298 1.45 -4.9 2.005 -6.7 1.76 -5.9 1.99 × 10−5 
17043 Cytokeratin 19 260 P08727 5.04 44,065 4.82 45,484 0.275 1.408 -5.1 2.064 -7.5 1.42 -5.2 6.24 × 10−5 
16185 Cytokeratin 19 223 P08727 5.04 44,065 4.78 45,640 0.449 1.467 -3.3 1.868 -4.2 1.03 -2.3 1.08 × 10−3 
64231 Cytokeratin 19 66 P08727 5.04 44,065 4.92 44,917 1.012 1.869 -1.8 2.24 -2.2 2.469 -2.4 8.05 × 10−3 
7046 Glycyl-tRNA synthetase 148 P41250 6.61 83,828 5.95 77,814 0.597 0.226 2.6 0.188 3.2 0.199 6.8 × 10−5 
17391 IgG Fc binding protein 59 O95784 5.56 81,017 5.31 132,499 0.147 0.667 -4.5 0.952 -6.5 0.547 -3.7 4.47 × 10−6 
16796 IgG Fc binding protein 52 O95784 5.56 81,017 5.22 135,256 0.113 0.467 -4.1 0.649 -5.7 0.339 -3 1.6 × 10−6 
86052 Maspin 76 P36952 5.72 42,586 5.75 42,325 0.395 0.058 6.8 0.09 4.4 0.188 2.1 2.3 × 10−4 
17865 Nucleoside diphosphate kinase A 164 P15531 5.42 17,309 5.57 19,758 1.154 0.462 2.5 0.424 2.7 0.494 2.3 5.3 × 10−7 
114132 Protein disulfide isomerase 46 P07237 4.76 57,480 4.77 58,722 0.301 0.738 -2.5 0.806 -2.7 0.551 -1.8 1.0 × 10−3 
145857 Serum albumin, human 147 1AO6_A 5.73 68,126 5.45 52,323 0.207 0.821 -4 0.568 -2.7 0.639 -3.1 7.9 × 10−3 
13756 Serum albumin, human 91 1A06A 5.63 67,690 5.43 41,401 0.539 1.888 -3.5 1.613 -3 1.336 -2.5 4.63 × 10−4 
16253 Human serum albumin complexed with myristic acid 131 1BJ5 5.73 68,126 5.77 24,841 0.447 1.285 -2.9 1.054 -2.4 1.083 -2.4 2.2 × 10−3 
5764 Stathmin 107 P16949 5.77 17,161 5.64 18,761 0.412 0.135 3.1 0.143 2.9 0.181 2.3 2.1 × 10−3 
10280 Transthyretin (prealbumin) complex with thyroxine (T4) 93 2ROX_A 5.33 12,996 5.48 16,838 1.144 1.839 -1.6 1.661 -1.5 2.677 -2.3 1.6 × 10−3 
8115 Tropomyosin α4 chain (tropomyosin 4; TM30-pl) 63 P67936 4.67 28,487 4.68 31,786 1.928 1.127 1.7 0.991 1.9 1.024 1.9 4.3 × 10−4 
9264 Ubiquitin thiolesterase 125 P15374 4.48 26,337 4.79 28,835 0.414 0.241 1.7 0.252 1.6 0.217 1.9 3.1 × 10−4 
17404 Vinculin (metavinculin) 165 P18206 5.51 124,161 5.56 127,631 0.104 0.68 -6.5 0.516 -5 0.621 -6 1.37 × 10−6 
18975 14-3-3 β 120 P31946 4.76 28,179 4.76 28,296 4.11 2.628 1.6 2.658 1.5 2.568 1.6 1.3 × 10−3 
17784 21K tumor protein 93 P13693 4.84 19,697 4.84 25,485 1.723 0.867 0.873 1.044 1.7 1.3 × 10−5 
Spot no.Protein nameScoreAccession no.Theo. pITheo. MWAct. pIAct. MWExpression in tumorExpression in healthy mucosaFold changeExpression in polyp mucosaFold changeExpression in tumor mucosaFold changeP
117903 β-Actin 157 P60709 5.55 40,536 5.12 42,093 1.104 0.141 0.125 0.12 9.7 × 10−5 
17654 α1-Antitrypsin precursor 235 P01009 5.37 46,878 4.98 59,532 0.788 1.853 -2.3 1.692 -2.1 2.997 -3.8 8.8 × 10−4 
3385 Apolipoprotein A-I precursor 162 P02647 5.56 30,759 5.24 24,471 3.031 6.876 -2.3 5.381 -1.8 7.257 -2.4 2.3 × 10−3 
9315 Calgizzarin 70 P31949 6.56 11,847 5.86 12,048 2.032 0.594 3.4 0.56 3.6 0.765 2.7 5.5 × 10−7 
9669 Creatine kinase 261 P12277 5.34 42,902 5.43 42,655 2.571 9.158 -3.6 14.158 -5.51 8.004 -3.1 7.47 × 10−5 
12691 Cytokeratin 9 76 P35527 5.14 62,178 4.81 50,192 0.07 0.365 -5.2 0.809 -11.6 0.322 -4.6 1.9 × 10−3 
18566 Cytokeratin 19 268 P08727 5.04 44,065 4.87 45,588 0.298 1.45 -4.9 2.005 -6.7 1.76 -5.9 1.99 × 10−5 
17043 Cytokeratin 19 260 P08727 5.04 44,065 4.82 45,484 0.275 1.408 -5.1 2.064 -7.5 1.42 -5.2 6.24 × 10−5 
16185 Cytokeratin 19 223 P08727 5.04 44,065 4.78 45,640 0.449 1.467 -3.3 1.868 -4.2 1.03 -2.3 1.08 × 10−3 
64231 Cytokeratin 19 66 P08727 5.04 44,065 4.92 44,917 1.012 1.869 -1.8 2.24 -2.2 2.469 -2.4 8.05 × 10−3 
7046 Glycyl-tRNA synthetase 148 P41250 6.61 83,828 5.95 77,814 0.597 0.226 2.6 0.188 3.2 0.199 6.8 × 10−5 
17391 IgG Fc binding protein 59 O95784 5.56 81,017 5.31 132,499 0.147 0.667 -4.5 0.952 -6.5 0.547 -3.7 4.47 × 10−6 
16796 IgG Fc binding protein 52 O95784 5.56 81,017 5.22 135,256 0.113 0.467 -4.1 0.649 -5.7 0.339 -3 1.6 × 10−6 
86052 Maspin 76 P36952 5.72 42,586 5.75 42,325 0.395 0.058 6.8 0.09 4.4 0.188 2.1 2.3 × 10−4 
17865 Nucleoside diphosphate kinase A 164 P15531 5.42 17,309 5.57 19,758 1.154 0.462 2.5 0.424 2.7 0.494 2.3 5.3 × 10−7 
114132 Protein disulfide isomerase 46 P07237 4.76 57,480 4.77 58,722 0.301 0.738 -2.5 0.806 -2.7 0.551 -1.8 1.0 × 10−3 
145857 Serum albumin, human 147 1AO6_A 5.73 68,126 5.45 52,323 0.207 0.821 -4 0.568 -2.7 0.639 -3.1 7.9 × 10−3 
13756 Serum albumin, human 91 1A06A 5.63 67,690 5.43 41,401 0.539 1.888 -3.5 1.613 -3 1.336 -2.5 4.63 × 10−4 
16253 Human serum albumin complexed with myristic acid 131 1BJ5 5.73 68,126 5.77 24,841 0.447 1.285 -2.9 1.054 -2.4 1.083 -2.4 2.2 × 10−3 
5764 Stathmin 107 P16949 5.77 17,161 5.64 18,761 0.412 0.135 3.1 0.143 2.9 0.181 2.3 2.1 × 10−3 
10280 Transthyretin (prealbumin) complex with thyroxine (T4) 93 2ROX_A 5.33 12,996 5.48 16,838 1.144 1.839 -1.6 1.661 -1.5 2.677 -2.3 1.6 × 10−3 
8115 Tropomyosin α4 chain (tropomyosin 4; TM30-pl) 63 P67936 4.67 28,487 4.68 31,786 1.928 1.127 1.7 0.991 1.9 1.024 1.9 4.3 × 10−4 
9264 Ubiquitin thiolesterase 125 P15374 4.48 26,337 4.79 28,835 0.414 0.241 1.7 0.252 1.6 0.217 1.9 3.1 × 10−4 
17404 Vinculin (metavinculin) 165 P18206 5.51 124,161 5.56 127,631 0.104 0.68 -6.5 0.516 -5 0.621 -6 1.37 × 10−6 
18975 14-3-3 β 120 P31946 4.76 28,179 4.76 28,296 4.11 2.628 1.6 2.658 1.5 2.568 1.6 1.3 × 10−3 
17784 21K tumor protein 93 P13693 4.84 19,697 4.84 25,485 1.723 0.867 0.873 1.044 1.7 1.3 × 10−5 

Abbreviations: Theo, theoretical data based on whole sequence in database; Act, actual gel pI and MW data from calibrated gel; Score, probability-based Mowse score (see ref. 15); pI, isoelectric point.

Many of the spots showing differential expression among the four groups of tissues were identified as cytoskeletal proteins. Among these, we noted two separate spots identified as β-actin. This protein is widely regarded as a “housekeeping gene,” characterized by stable expression across a range of cell types, although variations in expression in colorectal cancer (10) and other tissues (16) have previously been reported. Most of the variation in β-actin expression was associated with a weakly expressed spot (117903) which was more prominent in tumor tissue (Table 2). Figure 2 indicates that the only detectable difference between spots 3476 and 117903 was the absence in the latter of the peptide of mass 1,516.75 Da. This corresponds to the peptide sequence QEYDESGPSIVHR, found at the COOH-terminal of the protein, which was the fourth highest intensity peptide of the 14 used to derive the identity. As all the other tryptic peptides were detected, it seems probable that it was genuinely absent from spot 117903 and that a limited COOH-terminal clipping accounted for the small shifts in molecular mass and charge observed on the gel.

Figure 2.

Mass spectrometric data (mass and intensity) and sequences identified by peptide mass fingerprinting for two spots (117903 and 3476) identified as β-actin. The relative positions and intensities of the spots are shown in detail from Fig. 1A. The two spots apparently differ because of a single peptide (highlighted in 3476) that is absent in 117903.

Figure 2.

Mass spectrometric data (mass and intensity) and sequences identified by peptide mass fingerprinting for two spots (117903 and 3476) identified as β-actin. The relative positions and intensities of the spots are shown in detail from Fig. 1A. The two spots apparently differ because of a single peptide (highlighted in 3476) that is absent in 117903.

Close modal

Other cytoskeletal proteins showing evidence of differential expression in tumor tissue included cytokeratin 9 (CK9), four isoforms of cytokeratin 19 (CK19), and vinculin. The latter is involved in the attachment of actin-based microfilaments to the inner surface of the plasma membrane (17). Conversely, β-actin and tropomyosin (TM30-pl) both showed strong evidence of overexpression in tumor tissue. Other proteins showing evidence of significant underexpression included α1-antitrypsin precursor, creatine kinase, protein disulfide isomerase, immunoglobulin G (IgG) Fc binding protein, and the putative plasma proteins transthyretin, human serum albumin and APO A1. S100A11 (calgizzarin), stathmin, 14-3-3 β, glycyl-tRNA synthetase, and ubiquitin thiolesterase all showed evidence of increased expression in tumor compared with morphologically normal mucosa.

Differential expression of proteins in mucosa of patients with and without neoplasia. The expression of 61 proteins differed significantly between healthy mucosa and all of the other tissue types (polyp mucosa, cancer mucosa, and tumor tissue). Moreover, a total of 206 proteins differed significantly between healthy mucosa and polyp mucosa. Sixteen positively identified proteins with expression in polyp mucosa differing significantly compared with healthy mucosa are listed in Table 3. In contrast with tumor tissue, in which there was reduced expression of cytokeratins, three proteins identified as CK8 and two identified as CK9 were overexpressed in polyp mucosa compared with healthy mucosa. Two isoforms of α1-antitrypsin precursor were identified; one was markedly increased in expression and the other was significantly reduced, an effect which may reflect differing posttranslational modification of this protein in polyp mucosa. Of the seven identified proteins that were underexpressed in polyp mucosa compared with healthy mucosa (Table 3), two proteins, desmin and transgelin, are cytoskeleton-associated proteins. Other proteins showing evidence of underexpression in polyp mucosa included calvasculin, 14-3-3 ϵ, and 70K thyroid antigen fragment (Ku protein).

Table 3.

Characteristics of 15 proteins differentially expressed in polyp mucosa compared with healthy mucosa

Spot no.Protein nameScoreAccession no.Theo. pITheo. MWAct. pIAct. MWExpression in healthy mucosaExpression in polyp mucosaFold changeP
3476 β-Actin 178 P60709 5.29 42,052 5.25 42,893 51.2 71.73 1.4 1.3 × 10−2 
24831 α1-antitrypsin precursor 85 P01009 5.37 46,878 5.02 58,483 0.629 2.04 3.1 2.1 × 10−3 
163130 α1-Antitrypsin precursor 168 P01009 5.37 46,878 5.03 58,483 2.045 0.596 −3.5 6.6 × 10−5 
18889 Calcyclin 88 P06703 5.33 10,230 5.05 9,671 6.29 8.32 1.3 2.2 × 10−2 
12155 Calvasculin 49 P26447 5.85 11,949 5.19 10,727 0.208 0.103 −2 3.1 × 10−2 
68702 Cytokeratin 8 75 P05787 5.52 53,510 5.04 51,491 0.167 0.534 3.2 9.1 × 10−3 
64844 Cytokeratin 8 116 P05787 5.52 53,510 5.10 52,913 0.195 0.686 3.5 1.9 × 10−3 
65803 Cytokeratin 9 82 P35527 5.14 62,178 5.06 62,008 0.026 0.135 5.2 1.7 × 10−2 
12691 Cytokeratin 9 76 P35527 5.14 62,178 4.81 50,192 0.365 0.81 2.2 4.5 × 10−2 
63453 Desmin 70 P17661 5.21 53,429 4.86 48,541 0.794 — 3.2 × 10−10 
2887 Fibrinogen γ chain, isoform γ-A precursor 79 P02679 5.70 49,465 5.63 49,356 0.553 0.36 −1.5 3.8 × 10−2 
17391 IgG Fc binding protein 59 O95784 5.56 81,017 5.31 132,499 0.667 0.952 1.4 2.1 × 10−2 
17076 Transgelin-2 (SM22-α homologue) 59 P37802 8.45 22,417 5.22 18,242 0.205 0.067 −3 1.6 × 10−2 
19586 14-3-3 ϵ 53 P62258 4.63 29,326 4.68 30,803 0.158 0.072 −2.2 7.0 × 10−3 
72917 70K thyroid antigen fragment 66 P12956 6.23 69,953 5.14 32,121 0.169 — 2.1 × 10−5 
Spot no.Protein nameScoreAccession no.Theo. pITheo. MWAct. pIAct. MWExpression in healthy mucosaExpression in polyp mucosaFold changeP
3476 β-Actin 178 P60709 5.29 42,052 5.25 42,893 51.2 71.73 1.4 1.3 × 10−2 
24831 α1-antitrypsin precursor 85 P01009 5.37 46,878 5.02 58,483 0.629 2.04 3.1 2.1 × 10−3 
163130 α1-Antitrypsin precursor 168 P01009 5.37 46,878 5.03 58,483 2.045 0.596 −3.5 6.6 × 10−5 
18889 Calcyclin 88 P06703 5.33 10,230 5.05 9,671 6.29 8.32 1.3 2.2 × 10−2 
12155 Calvasculin 49 P26447 5.85 11,949 5.19 10,727 0.208 0.103 −2 3.1 × 10−2 
68702 Cytokeratin 8 75 P05787 5.52 53,510 5.04 51,491 0.167 0.534 3.2 9.1 × 10−3 
64844 Cytokeratin 8 116 P05787 5.52 53,510 5.10 52,913 0.195 0.686 3.5 1.9 × 10−3 
65803 Cytokeratin 9 82 P35527 5.14 62,178 5.06 62,008 0.026 0.135 5.2 1.7 × 10−2 
12691 Cytokeratin 9 76 P35527 5.14 62,178 4.81 50,192 0.365 0.81 2.2 4.5 × 10−2 
63453 Desmin 70 P17661 5.21 53,429 4.86 48,541 0.794 — 3.2 × 10−10 
2887 Fibrinogen γ chain, isoform γ-A precursor 79 P02679 5.70 49,465 5.63 49,356 0.553 0.36 −1.5 3.8 × 10−2 
17391 IgG Fc binding protein 59 O95784 5.56 81,017 5.31 132,499 0.667 0.952 1.4 2.1 × 10−2 
17076 Transgelin-2 (SM22-α homologue) 59 P37802 8.45 22,417 5.22 18,242 0.205 0.067 −3 1.6 × 10−2 
19586 14-3-3 ϵ 53 P62258 4.63 29,326 4.68 30,803 0.158 0.072 −2.2 7.0 × 10−3 
72917 70K thyroid antigen fragment 66 P12956 6.23 69,953 5.14 32,121 0.169 — 2.1 × 10−5 

There was further evidence of increased expression of cytokeratins in cancer mucosa compared with healthy mucosa (Fig. 1B; Table 4). Seven proteins positively identified as cytokeratins (CK8, CK9, and CK20) were overexpressed but α2-actin and other proteins associated with the cytoskeleton (desmin, transgelin, and vimentin) were all underexpressed. As in polyp mucosa, there was evidence for modified expression of members of the serpin superfamily of protease inhibitors. One isoform of α1-antitrypsin precursor (24831) was increased by 4.7-fold, but again this was associated with a reduction in a second isoform of the same protein (163130). There was increased expression of the related proteins, elastase inhibitor and maspin. Other proteins listed in Table 4 are associated with the regulation of a variety of cellular functions including proliferation and apoptosis.

Table 4.

Characteristics of 37 identified proteins differentially expressed in cancer mucosa compared with healthy mucosa

Spot no.Protein nameScoreAccession no.Theo. pITheo. MWAct. pIAct. MWExpression in healthy mucosaExpression in cancer mucosaFold changeP
19076 α2-Actin 104 P62736 5.23 42,381 5.30 43,815 2.997 1.46 −2.1 9.9 × 10−3 
17372 α2-Actin 167 P62736 5.23 42,381 5.22 43,570 12.4 7.3 −1.7 1.1 × 10−2 
3476 β-Actin 178 P60709 5.29 42,052 5.25 42,893 51.23 63.95 1.3 4.3 × 10−2 
24831 α1-Antitrypsin precursor 85 P01009 5.37 46,878 5.02 58,483 0.629 2.97 4.7 3.1 × 10−5 
163130 α1-Antitrypsin precursor 168 P01009 5.37 46,878 5.03 58,483 2.045 0.969 −2.1 3.0 × 10−3 
50128 ATPase β-chain 98 P06576 5.26 56,525 5.09 54,474 0.209 − 2.5 × 10−4 
18889 Calcyclin 88 P06703 5.33 10,230 5.05 9,671 6.29 9.21 1.5 3.4 × 10−3 
12155 Calvasculin 49 P26447 5.85 11,949 5.19 10,727 0.208 0.034 −6.1 2.5 × 10−4 
3013 Calpain 69 P04632 5.05 28,469 4.95 27,853 0.187 0.31 1.7 1.1 × 10−2 
66557 Cytokeratin 8 102 P05787 5.52 53,510 5.06 48,199 0.357 — 8.1 × 10−4 
68702 Cytokeratin 8 75 P05787 5.52 53,510 5.04 51,491 0.167 0.869 5.2 8.5 × 10−4 
64844 Cytokeratin 8 116 P05787 5.52 53,510 5.10 52,913 0.195 0.888 4.6 2.0 × 10−3 
68667 Cytokeratin 8 136 P05787 5.52 53,510 5.21 50,928 0.168 0.918 5.5 2.3 × 10−3 
88139 Cytokeratin 8 130 P05787 5.52 53,510 5.28 52,781 0.076 0.709 9.3 2.5 × 10−3 
162428 Cytokeratin 8 154 P05787 5.52 53,510 5.13 48,714 0.018 0.079 4.4 2.9 × 10−3 
163121 Cytokeratin 8 101 P05787 5.52 53,510 5.06 47,359 0.322 0.743 2.3 3.0 × 10−2 
65803 Cytokeratin 9 82 P35527 5.14 62,178 5.06 62,008 0.026 0.125 4.8 2.5 × 10−2 
80605 Cytokeratin 20 126 P35900 5.60 48,599 5.38 49,415 0.154 0.581 3.8 3.8 × 10−3 
63453 Desmin 70 P17661 5.21 53,429 4.86 48,541 0.794 0.274 −2.9 1.1 × 10−5 
10872 Fatty acid-binding protein 132 P07148 6.60 14,256 6.02 13,502 5.002 12.452 2.5 4.3 × 10−3 
2887 Fibrinogen γ chain, isoform γ-A precursor 79 P02679 5.70 49,465 5.63 49,356 0.553 0.219 −2.5 2.2 × 10−4 
90505 Hemopexin 61 P02790 6.55 52,385 5.65 65,289 0.295 — 9.4 × 10−4 
11118 Leukocyte elastase inhibitor 153 P30740 5.90 42,829 5.94 42,750 0.289 0.847 2.9 1.0 × 10−3 
66836 Mannose-6-phosphate isomerase 76 P34949 5.63 47,065 5.57 44,917 0.301 0.191 −1.6 9.9 × 10−3 
86052 Maspin 76 P36952 5.72 42,586 5.75 42,325 0.058 0.188 3.3 2.3 × 10−2 
146954 Peroxiredoxin 2 (thiol-specific antioxidant protein; natural killer cell-enhancing factor B) 82 P32119 5.67 21,918 5.24 24,131 0.259 2.033 7.8 7.4 × 10−3 
11873 Rho GDi, ly 88 P52566 5.10 23,031 5.10 28,896 0.952 0.58 −1.6 7.5 × 10−3 
16534 Sarcomeric tropomyosin κ; TPM1-κ 67 AAT68294 4.65 32,688 4.70 40,372 2.171 1.298 −1.7 0.4 × 10−2 
18169 Secernin 2 54 AAH17317 5.44 46,989 5.54 44,512 0.692 0.347 −2 2.3 × 10−3 
18889 S100A6 (calcyclin) 88 P06703 5.33 10,230 5.05 9,671 6.29 9.21 1.5 3.4 × 10−3 
12155 S100A4 (calvasculin) 94 P26447 5.85 11,949 5.19 10,727 0.208 0.034 −6.1 2.5 × 10−4 
17076 Transgelin-2 (SM22-α homologue) 59 P37802 8.45 22,417 5.22 18,242 0.205 0.016 −12.8 1.8 × 10−4 
13202 Vimentin 58 P08670 5.06 53,545 4.73 46,273 0.259 0.064 −4 2.5 × 10−2 
72917 70K thyroid antigen frag 66 P12956 6.23 69,953 5.14 32,121 0.169 0.056 −3 4.2 × 10−3 
19586 14-3-3 ϵ 53 P62258 4.63 29,326 4.68 30,803 0.158 — 1.9 × 10−4 
18349 14-3-3 protein ζ/δ (protein kinase C inhibitor protein 1, KCIP-1) 199 P63104 4.73 27,899 4.72 28,504 5.42 4.68 −1.2 3.1 × 10−2 
17784 21K tumor protein 93 P13693 4.84 19,697 4.84 25,485 0.867 1.04 1.2 1.2 × 10−2 
Spot no.Protein nameScoreAccession no.Theo. pITheo. MWAct. pIAct. MWExpression in healthy mucosaExpression in cancer mucosaFold changeP
19076 α2-Actin 104 P62736 5.23 42,381 5.30 43,815 2.997 1.46 −2.1 9.9 × 10−3 
17372 α2-Actin 167 P62736 5.23 42,381 5.22 43,570 12.4 7.3 −1.7 1.1 × 10−2 
3476 β-Actin 178 P60709 5.29 42,052 5.25 42,893 51.23 63.95 1.3 4.3 × 10−2 
24831 α1-Antitrypsin precursor 85 P01009 5.37 46,878 5.02 58,483 0.629 2.97 4.7 3.1 × 10−5 
163130 α1-Antitrypsin precursor 168 P01009 5.37 46,878 5.03 58,483 2.045 0.969 −2.1 3.0 × 10−3 
50128 ATPase β-chain 98 P06576 5.26 56,525 5.09 54,474 0.209 − 2.5 × 10−4 
18889 Calcyclin 88 P06703 5.33 10,230 5.05 9,671 6.29 9.21 1.5 3.4 × 10−3 
12155 Calvasculin 49 P26447 5.85 11,949 5.19 10,727 0.208 0.034 −6.1 2.5 × 10−4 
3013 Calpain 69 P04632 5.05 28,469 4.95 27,853 0.187 0.31 1.7 1.1 × 10−2 
66557 Cytokeratin 8 102 P05787 5.52 53,510 5.06 48,199 0.357 — 8.1 × 10−4 
68702 Cytokeratin 8 75 P05787 5.52 53,510 5.04 51,491 0.167 0.869 5.2 8.5 × 10−4 
64844 Cytokeratin 8 116 P05787 5.52 53,510 5.10 52,913 0.195 0.888 4.6 2.0 × 10−3 
68667 Cytokeratin 8 136 P05787 5.52 53,510 5.21 50,928 0.168 0.918 5.5 2.3 × 10−3 
88139 Cytokeratin 8 130 P05787 5.52 53,510 5.28 52,781 0.076 0.709 9.3 2.5 × 10−3 
162428 Cytokeratin 8 154 P05787 5.52 53,510 5.13 48,714 0.018 0.079 4.4 2.9 × 10−3 
163121 Cytokeratin 8 101 P05787 5.52 53,510 5.06 47,359 0.322 0.743 2.3 3.0 × 10−2 
65803 Cytokeratin 9 82 P35527 5.14 62,178 5.06 62,008 0.026 0.125 4.8 2.5 × 10−2 
80605 Cytokeratin 20 126 P35900 5.60 48,599 5.38 49,415 0.154 0.581 3.8 3.8 × 10−3 
63453 Desmin 70 P17661 5.21 53,429 4.86 48,541 0.794 0.274 −2.9 1.1 × 10−5 
10872 Fatty acid-binding protein 132 P07148 6.60 14,256 6.02 13,502 5.002 12.452 2.5 4.3 × 10−3 
2887 Fibrinogen γ chain, isoform γ-A precursor 79 P02679 5.70 49,465 5.63 49,356 0.553 0.219 −2.5 2.2 × 10−4 
90505 Hemopexin 61 P02790 6.55 52,385 5.65 65,289 0.295 — 9.4 × 10−4 
11118 Leukocyte elastase inhibitor 153 P30740 5.90 42,829 5.94 42,750 0.289 0.847 2.9 1.0 × 10−3 
66836 Mannose-6-phosphate isomerase 76 P34949 5.63 47,065 5.57 44,917 0.301 0.191 −1.6 9.9 × 10−3 
86052 Maspin 76 P36952 5.72 42,586 5.75 42,325 0.058 0.188 3.3 2.3 × 10−2 
146954 Peroxiredoxin 2 (thiol-specific antioxidant protein; natural killer cell-enhancing factor B) 82 P32119 5.67 21,918 5.24 24,131 0.259 2.033 7.8 7.4 × 10−3 
11873 Rho GDi, ly 88 P52566 5.10 23,031 5.10 28,896 0.952 0.58 −1.6 7.5 × 10−3 
16534 Sarcomeric tropomyosin κ; TPM1-κ 67 AAT68294 4.65 32,688 4.70 40,372 2.171 1.298 −1.7 0.4 × 10−2 
18169 Secernin 2 54 AAH17317 5.44 46,989 5.54 44,512 0.692 0.347 −2 2.3 × 10−3 
18889 S100A6 (calcyclin) 88 P06703 5.33 10,230 5.05 9,671 6.29 9.21 1.5 3.4 × 10−3 
12155 S100A4 (calvasculin) 94 P26447 5.85 11,949 5.19 10,727 0.208 0.034 −6.1 2.5 × 10−4 
17076 Transgelin-2 (SM22-α homologue) 59 P37802 8.45 22,417 5.22 18,242 0.205 0.016 −12.8 1.8 × 10−4 
13202 Vimentin 58 P08670 5.06 53,545 4.73 46,273 0.259 0.064 −4 2.5 × 10−2 
72917 70K thyroid antigen frag 66 P12956 6.23 69,953 5.14 32,121 0.169 0.056 −3 4.2 × 10−3 
19586 14-3-3 ϵ 53 P62258 4.63 29,326 4.68 30,803 0.158 — 1.9 × 10−4 
18349 14-3-3 protein ζ/δ (protein kinase C inhibitor protein 1, KCIP-1) 199 P63104 4.73 27,899 4.72 28,504 5.42 4.68 −1.2 3.1 × 10−2 
17784 21K tumor protein 93 P13693 4.84 19,697 4.84 25,485 0.867 1.04 1.2 1.2 × 10−2 

The multivariate analysis illustrated in Fig. 1C provides confirmation that colorectal tumor tissue can be distinguished from morphologically normal mucosa on the basis of protein expression. This is not unexpected, given the many histologic, metabolic, and cytokinetic differences between normal and neoplastic tissues, and our findings are consistent with a number of other proteomics studies in which tumor tissue has been compared with flat mucosa from the same patients (9, 11, 12). However, it is also clear that the three sources of morphologically normal mucosa do not form a single coherent group; of particular interest is the fact that the cluster of samples derived from patients without polyps or cancer is clearly separated from both sets of patients with neoplastic lesions. This observation contradicts the conventional, but largely unexamined, assumption that the morphologically normal mucosa of cancer patients is also functionally normal. However, individuals with a history of multiple colorectal polyps or cancer are well known to be at a greater risk of developing another cancer at sites remote from the original lesion. This implies that the whole mucosal field of such individuals has undergone functional changes that make it persistently vulnerable to neoplasia. Chen et al. (6) established that, for a panel of genes, the expression profiles measured in polyp-free mucosa differed significantly between APCmin and wild-type mice and between human patients with and without colorectal cancer. A later study from the same group reported consistent differences in gene expression in subjects with a family history of cancer compared with those without (18). Our present results are consistent with these findings and show that the changes in gene expression associated with increased vulnerability to colorectal cancer encompass a larger number of genes than previously reported and extend to the level of protein expression. Although it was not our primary intention to conduct a comprehensive analysis of all the proteins showing differential expression in polyp and cancer mucosa, some of our observations may shed light on the functional changes taking place in the mucosal field of individuals at increased risk of bowel cancer.

Epithelial cells contain 20 different cytokeratins, numbered 1 to 8 (type II CKs) and 9 to 20 (type I CKs); cytokeratins 1 to 6 are characteristic of squamous epithelia whereas the columnar epithelia of the gastrointestinal tract typically contain CKs 7, 8, and 18 to 20 (19). In the present study, we observed differential expression of seven isoforms of CK8, four of CK19, and one each of CK9 and CK20. All four isoforms of CK19 were underexpressed in tumor tissue compared with morphologically normal mucosa, regardless of source, and one of the spots identified as CK9 was absent from tumor samples (Table 2). In contrast, four CK8 isoforms and both CK9s were overexpressed in polyp mucosa relative to normal mucosa (Table 3) and seven CK8 isoforms, one of CK9 and one of CK20, were overexpressed in cancer mucosa relative to healthy mucosa (Table 4). The increased abundance of cytokeratins in cancer mucosa is highlighted in Fig. 1B. Overall, these findings indicate that expression of CK8 increases in the morphologically normal mucosa as the adenoma-carcinoma sequence progresses, with multiple isoforms differing slightly in mass and charge.

In this complex situation, the increased abundance of certain isoforms may be balanced by reductions in others so that total amounts of protein remain the same. A full characterization of the subtle changes in peptide structure and abundance that we have identified presents a considerable technical challenge, which is beyond the scope of the present study, although further work to identify their structure and cellular localization is certainly warranted.

Apart from the maintenance of normal epithelial architecture, cytokeratins have functional roles in epithelial physiology. CK8-null mice develop chronic inflammation of the colon (20) and have impaired electrolyte and fluid transport (21). Mutations affecting the structure of CK8 in humans also lead to epithelial fragility in the gut and may play a role in some types of inflammatory bowel disease (22). The colitis of CK8-null mice is due to a primary epithelial defect rather than an immune deficiency, and colonic bacteria are required for its development (23). Thus, CK-8 may be directly involved in the defense of the mucosal epithelium against proinflammatory stimuli that contribute to neoplastic change (24).

α1-Antitrypsin [α1 proteinase inhibitor (API)] is a member of the serine-protease superfamily (25) and an anti-inflammatory protein, the main function of which is to prevent degradation of connective tissues by opposing the activity of endogenous proteases (26). In the present study, four distinct spots were positively identified as API precursor, which is a 52-kDa polypeptide that subsequently becomes glycosylated to form the 55-kDa secreted protein. One spot (24831) was significantly overexpressed in both polyp mucosa and cancer mucosa relative to healthy mucosa, but expression in tumor tissue was not significantly different from healthy mucosa. A second isoform (17654) was overexpressed in cancer mucosa only and two others were unchanged or underexpressed. Overall, the data suggest that modified expression of API isoforms in the morphologically normal mucosal field occurs during development of neoplasia. API has previously been shown to be synthesized by hepatocytes, macrophages, and intestinal epithelial cells (27), and gastric cancer has been reported to be associated with high levels of API in the gastric juice (28). It is also detectable in the feces of both healthy subjects and patients with inflammatory bowel disease (29), and in vitro evidence suggests that it is secreted in response to certain proinflammatory cytokines (30). There are also reports suggesting that high levels of API expression in sporadic colorectal tumors are associated with poor prognosis (31). A second serpin, elastase inhibitor, also showed evidence of increased expression in cancer mucosa compared with healthy mucosa. BLAST searches confirmed that both proteins were members of the serpin superfamily but a comparison of their sequences established that they were products of different genes, with 31.4% homology across the amino acid sequence.

A third member of the serine protease family, maspin, was shown to be overexpressed in tumor and cancer mucosa relative to healthy mucosa. Maspin is an unusual serpin in that it lacks protease inhibitory activity and is classified as a tumor suppressor gene. It has been shown to induce apoptosis in tumor cells via Bax (32) and Bcl-2 (33), but in prostate cancer the tumor suppressor function is associated with increased cell adhesion, thereby suppressing cell mobility and malignant behavior (34). Overexpression of maspin in colorectal tumor tissue has previously been described (35) and a recent report suggests that this is particularly associated with microsatellite instability (36). The present study seems to be the first in which the expression of maspin in morphologically normal mucosa has been described.

Several other cytoplasmic proteins with diverse regulatory functions were shown to be differentially regulated in polyp and cancer mucosa. The S100 proteins are calcium-activated signaling molecules involved in cell proliferation, differentiation, and cytoskeletal dynamics. In the present study, S100A11 (calgizzarin) was overexpressed in tumor tissue compared with healthy mucosa, polyp mucosa, and cancer mucosa. Three S100 proteins, including S100A11, were previously identified by Chaurand et al. (37) as tumor-specific markers of colorectal neoplasia. Stulik et al. (11) also identified overexpression of S100A11 in their proteomic analysis of human colorectal tumors. We observed statistically significant overexpression of S100A6 (calcyclin) in both polyp mucosa and cancer mucosa compared with healthy mucosa (Tables 2 and 3) whereas S1004A (calvasculin) was underexpressed in these tissues. Stulik et al. (11) reported a statistically significant correlation between the development of colorectal neoplasia and the expression of different isoforms of S1006A (38), and Bronckart et al. (39) also reported characteristic patterns of expression of S100 proteins, including reduced expression of S100A4, associated with colorectal dysplasia and neoplasia. A high expression of S100A4 has been reported to be positively associated with risk of metastasis of colorectal tumors (40) and of many other tumor types (41). The present study shows that S100A4 is expressed in healthy mucosa, albeit at a low level, and that reduced expression was associated with the development of neoplasia.

Overall, the present study provides evidence for progressive changes in protein expression patterns in the colonic mucosal field, associated with the development of neoplastic lesions at distant sites. This observation has a number of important implications. The use of proteomic techniques to characterize tumors is becoming increasingly common and many groups have described studies in which tumor tissue was compared with supposedly normal mucosa obtained from the same patient. The present study shows that this is a misleading strategy if it is assumed that the paired mucosal sample is equivalent to the healthy mucosa of disease-free individuals. This is well illustrated by the example of liver fatty acid binding protein, which was reported recently by Lawrie et al. (42) to be reduced consistently in colorectal tumor tissue compared with adjacent normal colon. This observation is consistent with our own study in which the level of liver fatty acid binding protein expression in cancer mucosa was 3.9-fold higher than in tumor tissue (P = 0.0004). However, the level in cancer mucosa was also ∼2.5-fold higher compared with healthy mucosa (P = 0.004) whereas there was no statistically significant difference between expression levels in tumor tissue and healthy mucosa.

The existence of characteristic patterns of protein expression associated with enhanced vulnerability to neoplasia provides opportunities for development of biomarkers of increased risk. Kinzler and Vogelstein (43) proposed that the adverse effects of certain dietary factors on the risk of colorectal cancer were attributable not to food-borne carcinogens but to hypothetical effects they described as chronic “irritation,” causing the colorectal mucosa to enter a perpetual state of tissue regeneration. Under these conditions, the survival of cells carrying preneoplastic mutations would be favored and the vulnerability to cancer would increase. Since Kinzler and Vogelstein's review, evidence for the importance of apoptosis as a protective mechanism against carcinogenesis has grown (5, 44), but little direct biological evidence for the putative state of chronic tissue regeneration has emerged. The results of the present study do not provide conclusive evidence that the mucosal field defect involves a heightened state of tissue repair but the observed changes in cytoskeletal proteins and serine protease inhibitors may be consistent with this hypothesis. Some of the differences in protein expression that we have observed may reflect altered gene expression occurring as a consequence of aberrant CpG island methylation (2, 45). Recognition and further characterization of the field effect will provide a framework on which to build hypotheses for future research on the role of diet as an etiologic factor in the development of colorectal cancer.

Note: Present address for E. A Williams: Centre for Human Nutrition, Northern General Hospital, University of Sheffield, Sheffield S5 7AU, United Kingdom.

Grant support: Food Standards Agency (UK) and the Biotechnology and Biological Sciences Research Council.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

We thank Drs. Mike Naldrett and Andrew Bottrill for the MALDI-T of analysis and Wendy Bal, Julie Coaker, and Catherine Lamb for technical support.

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