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Cancer Epidemiology Biomarkers & Prevention Vol. 15, 1598-1606, September 2006
© 2006 American Association for Cancer Research

Proteomic Profiling Identifies Cyclooxygenase-2-Independent Global Proteomic Changes by Celecoxib in Colorectal Cancer Cells

Jianrong Lou1,2, Naheed Fatima1,2, Zhen Xiao3, Stacy Stauffer1, Gary Smythers4, Peter Greenwald1 and Iqbal Unnisa Ali1

1 Division of Cancer Prevention, National Cancer Institute, Bethesda, Maryland and 2 Basic Research Program, 3 Laboratory of Proteomics and Analytical Technologies, and 4 Advanced Biomedical Computing Center, Scientific Applications International Corporation, Frederick, Maryland

Requests for reprints: Iqbal Unnisa Ali, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD 20892. Phone: 301-594-0482; Fax: 301-849-6679. E-mail: alii{at}mail.nih.gov


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Celecoxib, a selective inhibitor of the enzyme cyclooxygenase-2 (COX-2), has been shown to be a promising chemoprevention agent. The chemopreventive efficacy of celecoxib is believed to be a consequence of its COX-2-dependent and COX-2-independent effects on a variety of cellular processes including proliferation, apoptosis, angiogenesis, and immunosurveillance. In an attempt to identify proteomic markers modulated by celecoxib that are independent of its inhibitory effect on COX-2, the colorectal cancer cell line HCT-116, a nonexpresser of COX-2, was treated with celecoxib. We used the powerful, state-of-the-art two-dimensional difference gel electrophoresis technology coupled with mass spectrometric sequencing to compare global proteomic profiles of HCT-116 cells before and after treatment with celecoxib. Among the differentially expressed proteins identified following celecoxib treatment were proteins involved in diverse cellular functions including glycolysis, protein biosynthesis, DNA synthesis, mRNA processing, protein folding, phosphorylation, redox regulation, and molecular chaperon activities. Our study presents a comprehensive analysis of large-scale celecoxib-modulated proteomic alterations, at least some of which may be mechanistically related to the COX-2-independent chemopreventive effect of celecoxib. (Cancer Epidemiol Biomarkers Prev 2006;15(9):1598–606)


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
The two major isoforms of the enzyme cyclooxygenase, COX-1 and COX-2, convert arachidonic acid to prostaglandins, which have been implicated in a variety of conditions including inflammation, cardiovascular diseases, and cancer (1, 2). Although the two isoforms are structurally ~60% homologous and produce the same prostaglandin products, they differ in many respects. COX-1 is a constitutively expressed enzyme in many tissues with a housekeeping function, whereas COX-2 is inducible by cytokines during inflammation and carcinogenesis. The structural differences in the enzymes have been exploited for the development of selective inhibitors for COX-2. The most important difference from the pharmacologic perspective is the substitution of a single amino acid isoleucine in position 523 in COX-1 with valine in COX-2, creating a larger cavity in the active center and conferring selectivity of the binding of inhibitors in the additional space (3-5). Celecoxib is one such inhibitor that is highly selective for COX-2.

The chemopreventive efficacy of celecoxib has been shown in colorectal cancer cell lines, mouse models, and human clinical trials (5-7). Despite its high selectivity for COX-2, celecoxib is known to use non-COX-2 targets to mediate its antiproliferative and antitumor activities, which are likely to be multifactorial and are probably directed against numerous cellular targets (8-11). Several lines of evidence suggest that the chemopreventive effects of celecoxib are related to mechanisms other than COX-2 inhibition. First, celecoxib has been shown to inhibit growth of cell lines that are deficient for COX-2 expression (12, 13). Second, treatment with celecoxib resulted in growth inhibition of xenografts of COX-2-deficient colorectal and prostate cancer cell lines in nude mice (8, 14). Third, concentration of celecoxib needed for growth inhibition in vitro is several orders of magnitude higher than the concentration at which COX-2 is inhibited (15, 16). And finally, derivatives of celecoxib devoid of the COX-2 inhibitory activity have recently been shown to mimic celecoxib by affecting processes such as cell cycle progression, apoptosis, neovascularization, growth inhibition in vitro, and tumor formation in vivo (17-20). Clearly, a better understanding of the molecular targets of celecoxib involved in its COX-2-dependent and/or COX-2-independent antiproliferative functions is of considerable clinical significance and would be helpful in enhancing its chemopreventive potential.

Recent advances in proteomic profiling technologies make it possible to take a comprehensive approach toward characterization of molecular events that ensue on treatment of cells with celecoxib. We used state-of-the-art proteomic technologies, two-dimensional difference gel electrophoresis (DIGE) followed by liquid chromatography in conjunction with tandem mass spectrometry (LC/MS/MS), to do a global analysis for sequence identifying molecular targets of celecoxib in a colorectal cancer cell line, HCT-116, which is deficient in COX-2. Two-dimensional DIGE is a powerful technique that enables visualization of relatively large fractions of the cellular proteome with an added dimension of simultaneous quantitative capability (21). The technique is based on prelabeling of protein extracts with fluorescent Cy dyes with specific excitation/emission wavelengths and separating the proteins according to their charge in the first dimension by isoelectric focusing and size in the second dimension by SDS-PAGE (22). The digital images generated by each dye can be visualized and accurately quantified at their respective specific wavelengths. The protein spots displaying quantitative differences are excised and subjected to sequence identification by LC/MS/MS.

In this study, use of the two-dimensional DIGE technique coupled with MS sequencing enabled us to identify a large number of novel celecoxib-modulated proteomic markers in the COX-2-deficient colorectal cancer cell line HCT-116. Validation of some of these proteins by Western blotting in HCT-116 cells and their comparative analysis in another colorectal cancer cell line, HCA-7, which expresses high levels of COX-2, are presented here.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Cell Culture Conditions and Viability Assay
HCT-116 cell line was obtained from American Type Culture Collection (Manassas, VA) and was cultured in McCoy's 5A medium (American Type Culture Collection) supplemented with 10% fetal bovine serum (Life Technologies, Inc., Grand Island, NY). HCA-7 cell line was purchased from European Collection of Cell Cultures (Salisbury, Wiltshire, United Kingdom) and was cultured in DMEM (American Type Culture Collection) with 10% fetal bovine serum. For the viability assay, cells from subconfluent stock flasks were trypsinized and seeded in 96-well plates at 1.5 x 104 per well in 100-µL medium and were allowed to grow for 24 hours at 37°C. Stock solution (stored as 100 mmol/L in DMSO at –20°C) of celecoxib (LKT Laboratories, Inc., St. Paul, MN) was thawed, diluted to appropriate concentrations, and was added in triplicate. Cells were grown for additional 24 hours with various concentrations of celecoxib (0, 5, 10, 20, 50, 75, 100, and 150 µmol/L) or DMSO as the vehicle control. Cytotoxicity was then measured with CellTiter-Blue cell viability assay kit (Promega, Madison, WI). Viable cells possess the metabolic activity to reduce the indicator dye resazurin into a highly fluorescent derivative, resosurfin (579ex/584em); the nonviable cells, on the other hand, due to rapid loss of metabolic capacity, do not generate a fluorescent signal.

Treatment of Cells with Celecoxib
HCT-116 and HCA-7 cells were cultured in T-75 flasks at 7 x 106 per flask and allowed to grow for 24 hours in their respective growth media. Cells were then treated with 0, 5, and 75 µmol/L celecoxib in DMSO for 24 hours. Subsequently, cells were trypsinized, centrifuged at 500 x g for 5 minutes, washed thrice with ice-cold PBS, and frozen at –20°C until use.

Protein Sample Preparation and Fluorescence Labeling
Frozen cell pellets were thawed and washed twice with buffer containing 10 mmol/L Tris (pH 8.0), 5 mmol/L MgCl2 and then resuspended in lysis buffer [30 mmol/L Tris (pH 8.5), 2 mol/L thiourea, 7 mol/L urea, 4% wt/vol CHAPS]. Cell lysate was sonicated intermittently (2-5 seconds) on ice for 1 minute and cellular debris were removed by centrifugation (13,000 x g, 4°C for 3 minutes). Protein concentration was determined with Ettan protein sample kit (Amersham Bioscience, Piscataway, NJ). The DIGE fluors, N-hydroxysuccinimidyl ester derivatives of the cyanine dyes, Cy3 and Cy5 (Amersham Biosciences), were prepared using freshly opened N,N-dimethylformamide (Acros Organics, Morris Plains, NJ). Protein samples (50 µg) were labeled with 400 pmol of Cy3 and Cy5 DIGE fluors in separate tubes on ice for 30 minutes. An internal standard was created by mixing equal amounts of control and celecoxib-treated samples and labeling it with Cy3, whereas individual samples were labeled with Cy5. The labeling reaction was quenched by adding 1 µL of 10 mmol/L lysine.

Two-Dimensional DIGE
The immobilized pH gradient strips (pH 3-10; Bio-Rad, Hercules, CA) were actively rehydrated at 50 V for 12 hours according to the instructions of the manufacturer. The Cy3-labeled internal standard of pooled samples was used to minimize experimental gel-to-gel variation and to facilitate cross-gel quantitative analysis. Equal amounts (50 µg protein per dye per gel) of Cy5-labeled individual samples and the Cy3-labeled internal standard were mixed together (100 µg protein per gel) and loaded onto a 24-cm immobilized pH gradient strip (pH 3-10). The proteins were focused in the first dimension for a total of 80,000 V-h in the PROTEAN IEF system (Bio-Rad). The immobilized pH gradient strips were equilibrated first in buffer I [6 mol/L urea, 2% SDS, 50 mmol/L Tris (pH 8.8), 20% glycerol, 2% DTT] for 15 minutes and then in buffer II (same as buffer I plus 2.5% iodoactamide) for 15 minutes and subsequently transferred onto 24-cm 12.5% gels. Proteins were then separated in the second dimension based on their molecular weight in the PROTEAN Plus Dodeca cell (Bio-Rad). Samples were run in duplicate and a total of six SDS gels were run together at 150 V overnight with the temperature of the running buffer maintained at 18°C to 20°C.

Image Acquisition
Gels were scanned directly between glass plates at 532/580 nm and 633/670 nm (excitation/emission wavelengths) for the Cy3 and Cy5 signals, respectively, using a Typhoon 9200 fluorescent scanner (Amersham Biosciences). Raw data of images were analyzed with PDQuest software (Bio-Rad). Briefly, original images of Cy3 and Cy5 images for each gel were cropped, smoothed, and filtered to clarify spots. The three-dimensional Gaussian spots were then created from filtered images and all subsequent spot quantitation and other analyses were done on the Gaussian image. A MatchSet was created for comparing and analyzing spots from all 12 Gaussian images (6 gels in duplicate), and a master image, which contains the spot data from all the gels in the MatchSet, was then generated. The Cy5 spot data from each gel were normalized on a spot-to-spot basis using respective Cy3 signals of the internal standard from the same gel, and the normalized Cy5 signal was then used for spot intensity comparison and analysis. After scanning for fluorescence images, gels were removed from gel cassettes and total proteins were stained with Biosafe Coommasie blue (Bio-Rad). The images were then captured using the LI-COR Odyssey Infrared Imaging Systems (LI-COR, Inc., Lincoln, NE.). The desired protein spots with at least 2-fold difference in Cy5 intensity were manually picked from the Coommasie blue–stained gels.

Protein Identification
The gel spots excised from two-dimensional DIGE were destained in 50% acetonitrile in 25 mmol/L NH4HCO3 (pH 8.4) and then lyophilized. Trypsin (Promega) was added to the lyophilized gel pieces at 20 ng/µL in 25 mmol/L NH4HCO3 (pH 8.4). Extra trypsin solution was removed and the gel spots were covered with 25 mmol/L NH4HCO3 (pH 8.4). The digestion was kept at 37°C overnight. The tryptic peptides were extracted from the gel spots with 70% acetonitrile, 5% formic acid and purified using ZipTip pipette tips (Millipore, Bellerica, MA). The tryptic peptides were analyzed by nanoflow reversed-phase liquid chromatography coupled online with MS/MS. A 75-µm inner diameter x 360-µm outer diameter x 10-cm-long fused silica capillary column (Polymicro Technologies, Phoenix, AZ) was packed with 3-µm, 300-Å pore size C-18 silica-bonded stationary reversed-phase particles (Vydac, Hysperia, CA). The column was connected to an Agilent 1100 nanoLC system (Agilent Technologies, Palo Alto, CA) and then coupled with an ion trap mass spectrometer (LCQ DecaXP, Thermo Finnigan, San Jose, CA). Mobile phase A was 0.1% formic acid in water and B was 0.1% formic acid in acetonitrile. The peptide samples were injected and gradient elution was done under the following conditions: 2% B at 500 nL/min in 20 minutes; a linear increase of 2% to 42% B at 250 nL/min in 40 minutes; 42% to 98% B in 10 minutes at 250 nL/min; 98% B at 500 nL/min for 10 minutes. The ion trap MS was operated in a data-dependent MS/MS mode where the three most abundant peptide molecular ions in every MS scan were sequentially selected for collision-induced dissociation with a normalized collision energy of 36%. Dynamic exclusion was applied to minimize repeated selection of peptides previously selected for collision-induced dissociation. The capillary temperature and electrospray voltage were set to 180°C and 1.8 kV, respectively. The resulting mass spectra were searched against the UniProt human protein database from the European Bioinformatics Institute5 with the SEQUEST program operating on a 40-node Beowulf cluster. For a tryptic peptide to be considered a legitimate identification, it must achieve certain charge state versus cross correlation (Xcorr) scores (1.9 for [M+H] 1+; 2.2 for [M+H] 2+; 3.1 for [M+H] 3+) and a minimum delta correlation ({Delta}Cn) of 0.08.

Western Blot Analysis
Cell pellets were suspended in radioimmunoprecipitation lysis buffer (Santa Cruz Biotechnology, Inc., Santa Cruz, CA) and sonicated intermittently (5 seconds) on ice for 1 minute. Protein concentration was determined by bicinchoninic acid assay (Sigma, St. Louis, MO). Fifteen micrograms of protein samples were separated on 8% to 16% SDS-PAGE, transferred onto nitrocellulose membrane, and blocked with 5% nonfat milk in TBS [25 mmol/L Tris-HCl (pH 7.4), 150 mmol/L NaCl] containing 0.01% Tween 20. The blots were then incubated with 1:200 dilution of primary antibodies (Santa Cruz Biotechnology) against prohibitin, {alpha}-enolase, creatine kinase, heat shock protein 90 (Hsp90), and glucose-regulated protein 78 (GRP-78). The antibodies against peroxiredoxin (Prx I; 1:200) and cyclophilin A (1:1,000) were purchased from Affinity Bioreagents (Golden, CO) and US Biologicals (Swampscott, MA), respectively. The incubation with primary antibodies was for 1 hour with constant shaking. Subsequently, the membranes were washed thrice with TBS. Horseradish peroxidase–conjugated second antibodies (1:5,000 dilution) were used and signal was detected by enhanced chemiluminescence system (Amersham Bioscience).


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Treatment of Cells with Various Concentrations of Celecoxib
In initial experiments, we determined the optimum cell density, culture conditions, and duration of treatment with celecoxib for the in vitro cell viability assay. Subsequently, the cell viability assay was done by plating the cells in 96-well microtiter plates at 1.5 x 104 per well. The cells were allowed to grow for 24 hours at 37°C and then treated with various concentrations of celecoxib for 24 hours. Figure 1A shows that the IC50 dose of celecoxib for the HCT-116 cell line under the culture conditions used was 75 µmol/L. Similarly, 50% cytotoxicity was also observed in the HCA cell line at 75 µmol/L celecoxib. In all subsequent experiments, both cell lines were treated with 0, 5, and 75 µmol/L of celecoxib (Fig. 1B and C), where 0 µmol/L served as the solvent control, 5 µmol/L was comparable to the achievable physiologic serum levels of celecoxib in patients at which in vitro cell growth and morphology were unaffected, and 75 µmol/L was used as the in vitro IC50 dose.


Figure 1
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  		Figure 1. Antiproliferative effect of celecoxib on colon cancer cell lines. A. The COX-2 nonexpresser HCT-116 cells were treated with indicated concentrations of celecoxib for 24 hours. Cell viability was measured by the ability of cells to reduce the indicator dye, resazurin. The fluorescence value of the untreated control cultures was set at 100%. Points, mean of triplicate wells; representative of three independent experiments. B. COX-2 nonexpresser HCT-116 cells. C. COX-2 expresser HCA-7 cells. The data in (B and C) are representative of many experiments.

 
Proteomic Profiling of COX-2-Deficient HCT-116 Cells
An outline of the proteomic analysis of control and celecoxib-treated HCT-116 cells and subsequent identification of differentially expressed, celecoxib-modulated proteomic markers is shown in Fig. 2 . Cell lysates were pre-electrophoretically labeled with the amine reactive Cy dyes, Cy3 and Cy5. Equal amounts of Cy5-labeled cell lysates and Cy3-labeled internal control (see Materials and Methods) were mixed and subjected to two-dimensional DIGE analysis in the same gel. The pattern of separated proteins was scanned at the respective wavelengths for both dyes and comparison of the composite images was used to identify differential up-regulation or down-regulation of proteins at least by 2-fold in celecoxib-treated cells. The Coommasie blue–stained gels were used to manually excise the desired spots of differentially expressed proteins, which were then subjected to sequence identification by MS/MS.


Figure 2
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  		Figure 2. Identification of celecoxib-modulated proteomic markers using two-dimensional DIGE followed by LC/MS/MS. Individual cell lysates were labeled with Cy5; the internal standard, a pool of equal amounts of all samples, was labeled with Cy3. A mixture of Cy3- and Cy5-labeled samples was separated according to pH in the first dimension and according to mass in the second dimension. Image analysis was conducted using PDQuest and the samples were normalized using internal standard. Differential expression was based on up-regulation or down-regulation by at least 2-fold. Gels were subsequently stained with Coommasie blue for spot picking. Proteins were identified by LC/MS/MS.

 
Identification of Celecoxib-Modulated, COX-2-Independent Proteomic Markers from HCT-116 Colorectal Cancer Cell Line
Two-dimensional profiles of HCT-116 cell lysates labeled with Cy dyes are displayed in Fig. 3 . Approximately 800 to 1,000 protein spots could be easily discerned on a gel labeled with either dye. Representative examples of profiles of the Cy5-labeled cell lysate treated with 5 µmol/L celecoxib and Cy3-labeled internal standard are shown in Fig. 3A and B, respectively. The Cy3 and Cy5 dyes label {varepsilon}-amino groups of lysine, are matched for mass and charge, but are spectroscopically different for excitation and emission wavelengths. The overlapping image of Cy3 and Cy5 fluorescent signals presented in Fig. 3C shows that the migration pattern of Cy5-labeled proteins after two-dimensional separation was remarkably similar to that of Cy3-labeled internal standard. Each gel contained the same internal standard, thus enabling comparison between samples loaded on different gels and ensuring the accuracy of inter-gel comparisons of spot abundance.


Figure 3
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  		Figure 3. Representative two-dimensional DIGE gel images of HCT-116 human colon cancer cells. A. Cy5 image of proteins from cells treated with 5 µmol/L celecoxib. B. Cy3 image of internal standard. C. Overlapping image of Cy3 and Cy5. Note that the images are remarkably similar.

 
Compared with protein expression levels in cells with no celecoxib treatment, the PDQuest software program identified 92 and 117 proteins in HCT-116 cells, treated with 5 and 75 µmol/L dose of celecoxib, respectively, with at least a 2-fold differential expression compared with solvent-treated controls (Table 1 ). Thirty-five of these celecoxib-modulated markers were common between 5 and 75 µmol/L treatment doses, whereas the expression of 60 proteomic markers was altered between cells treated with 5 and 75 µmol/L celecoxib.


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  		Table 1. Celecoxib-modulated gel spots from two-dimensional DIGE in COX-2-deficient colorectal cancer cell line HCT-116

 
Subsequent to scanning of fluorescence images and quantitative estimation of expression levels of individual spots, the gels were stained with Coommasie blue. The overall staining patterns of Cy dye– and Coomassie blue–labeled proteins were very similar. However, despite the overlap, there was a small shift in the electrophoretic mobility of the Cy dye–labeled proteins in the second dimension due to the addition of fluorescence molecules (500 Da). Use of fluorescence dyes also increased the detection sensitivity as more spots were detected in Cy dye images than in Coommasie blue–stained images.

Of a total of 174 differentially expressed spots identified from 5 and 75 µmol/L celecoxib–treated cells, we selected a total of 34 spots marked in the image of the Master Gel displayed in Fig. 4 . These spots were manually excised from Coommasie blue–stained gels, subjected to in-gel trypsin digestion, and further processed for LC/MS/MS sequencing. A list of sequence-identified proteins is presented in Table 2 . Whereas some proteins were identified with low percent sequence coverage, the peptides used to identify the proteins proved to be unique in the Uniprot human protein database. The percent coverage depends on numerous factors such as extraction of the protein, degree of denaturation and possible steric hindrance making some cleaving sites inaccessible, efficiency and specificity of the enzyme used for digestion, presence of impurities, and performance of the mass spectrometer. As is evident from Table 2, the identified proteins have diverse cellular functions.


Figure 4
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  		Figure 4. Master Gel image of two-dimensional DIGE. Locations of 34 differentially expressed-proteins are marked on Master Gel image and these protein spots were manually picked from the Coommasie blue–stained gels.

 

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  		Table 2. Celecoxib-modulated proteins in COX-2-deficient colorectal cancer cell line HCT-116

 
Validation of Celcoxib-Modulated Proteomic Markers by Western Blot Analysis
The quantitative estimation of altered expression levels of celecoxib-modulated proteins by PDQuest Software is believed to be accurate but needs to be validated by conventional platforms. We therefore used Western blotting to confirm the altered expression of several proteomic markers in HCT-116 cells treated with low and high doses of celecoxib. The HCT-116 cell lysate was separated on one-dimensional SDS-PAGE and probed with antibodies specific for 7 of the 34 differentially expressed proteomic markers shown in Table 2. As is obvious from Fig. 5A and B , there was a general concordance between the quantitative estimation of two-dimensional DIGE images and Western blot analysis of five of the seven markers (i.e., {alpha}-enolase, GRP-78, Hsp90, prohibitin, and Prx I). In the case of creatine kinase, the up-regulation of the protein following 5 µmol/L (but not 75 µmol/L) detected by quantifying the dye images could not be confirmed by Western blotting; a trend for celecoxib-mediated up-regulation was, however, present in at least two different experiments only in cells treated with 75 µmol/L. For cyclophilin A, at least two isoforms with up-regulation and down-regulation were visible on two-dimensional DIGE images (Fig. 5A). These isoforms resolved as a single band on a one-dimensional gel with no difference in the level of expression between control and celecoxib-treated cells. Preliminary experiments of the immunoblot of two-dimensional DIGE–separated cyclophilin A, however, showed celecoxib-mediated differential expression of the two isoforms (data not shown).


Figure 5
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  		Figure 5. Validation of the differentially expressed proteins by Western blotting analysis. A. Relative up-regulation or down-regulation of seven differentially expressed protein in 0, 5, and 75 µmol/L celecoxib-treated HCT-116 cells separated on two-dimensional DIGE as estimated by PDQuest software. B and C. Western blots of the seven proteins shown in (A). 0, 5, and 75 µmol/L celecoxib–treated HCT-116 (B) and HCA-7 (C) cell lysates were separated in 8% to 16% linear gradient SDS-PAGE gels and were probed against the respective antibodies. ß-Actin, used as the loading control, is shown for one proteomic marker each of (B and C), but was done for all markers shown in both (B and C). Representative of at least two, in most cases three, separate experiments using different sets of cell lysates.

 
Celecoxib-Modulated Proteomic Markers in COX-2 Expresser Cell Line
As the proteins shown in Fig. 5A and B were identified in a global screen of a COX-2-deficient cell line, we determined if the same proteins were also targeted by celecoxib in a colorectal cancer cell line that is known to be a high expresser of COX-2. Figure 5C presents the differential expression of the same seven proteomic markers in the COX-2 expresser HCA-7 cell line following treatment with low and high doses of celecoxib. As is evident, celecoxib modulation of the proteomic markers examined in the COX-2 expresser cell line HCA-7 was generally similar to that in the nonexpresser HCT-116 cell line. However, there were also dissimilarities; the expression of Prx I and Hsp90, which were clearly down-regulated in the COX-2-deficient HCT-116 cells, were not affected by celecoxib in the COX-2-positive HCA-7 cell line.


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Identification of the molecular targets of celecoxib and delineation of the molecular mechanisms underlying its COX-2-dependent and COX-2-independent chemopreventive effects have been the subject of many recent studies. Multiple proteomic markers have been identified that may mediate cell cycle arrest and induction of apoptosis caused by celecoxib culminating in its antiproliferative effect. These include proteins with crucial roles in cell cycle regulation such as cyclins, cyclin-dependent kinases, inhibitory proteins p21 and p27, and Rb, as well as proteins believed to be involved in celecoxib-induced apoptosis in cancer cell lines such as various caspases, Apaf-1, survivin, nuclear factor {kappa}B, and peroxisome proliferator–activated receptor {gamma} (8, 12, 17, 19, 23). There is also evidence that celecoxib affects both mitogenic and survival pathways by targeting phosphoinositide-dependent kinase-1/Akt, signal transducer and activator of transcription 3, and mitogen-activated protein kinase signaling (17, 24, 25). Furthermore, the clinical usefulness of celecoxib to target neoangiogenesis has also been explored (26, 27).

In contrast to the numerous studies described above, which have sought to analyze specific signaling pathways or crucial proteomic markers such as those involved in cell cycle progression, apoptosis, or angiogenesis, we chose to pursue a more global proteomic approach. The use of the two-dimensional DIGE technology enabled us to identify an array of hitherto unknown celecoxib-modulated proteomic markers. Although our present analysis accessed a very small window in the cellular proteome between pI 3 to 10 and molecular weight 5 to 150 kDa, it was possible to detect celecoxib modulation of numerous proteins in the COX-2-deficient HCT-116 colorectal cancer cell line. Significantly, the expression of many of these proteomic markers was modified at both low and high concentrations of celecoxib used in the analysis.

Several investigators have tested the ability of celecoxib to suppress growth of a variety of cultured cancer cell lines. The concentration of celecoxib required to inhibit growth in these studies varies considerably and is reflective of culture conditions (e.g., cell density, percent fetal bovine serum in the medium), time of addition of celecoxib (at the time of plating versus at later time points), duration of treatment, and probably the type of cancer cell line used (14, 15, 28, 29). Generally, the concentrations of celecoxib required for growth inhibition and apoptosis induction in vitro in a matter of hours to days are higher than those at which attenuation of tumor growth in vivo occurs, albeit after a much longer treatment period of several weeks to months.

In the present study, treatment of a COX-2-deficient colorectal cancer cell line with 5 µmol/L celecoxib—a concentration comparable to the physiologic serum levels of celecoxib in humans and in animal models following treatment with the highest tumor-inhibitory dose of celecoxib (30)—had no discernable effect on cell growth or morphology during the assay period of 24 hours. However, during the same time period, molecular alterations affecting the expression of numerous proteins were evident. As expected, treatment of cells with 75 µmol/L celecoxib, at which 50% cytotoxicity occurred, affected a higher number of proteins. More importantly, ~30% of the proteins with altered expression were common between treatments with low and high concentrations of celecoxib.

Sequence identification of 34 of a total of 174 (20%) differentially expressed spots with at least a 2-fold difference identified by the PDQuest software is listed in Table 2. There was a conspicuous absence of many of the previously reported celecoxib-responsive genes involved in cell cycle regulation, apoptosis, and DNA repair. This could most importantly be due to the sequencing of only 20% of the clecoxib-modulated proteins. Other factors may include a <2-fold difference in the expression levels of these proteins (a threshold set by our software program), specific cell line used in our analysis, dose and length of treatment with celecoxib, and/or a relatively narrow window in the cellular proteome accessed under the experimental conditions. Nevertheless, the list of proteins displayed in Table 2 clearly shows that celecoxib modulates proteomic markers with very diverse cellular functions. Many of these potential molecular targets of celecoxib, as discussed below, are of considerable significance in cancer biology and celecoxib-mediated up-regulation or down-regulation of these proteins is generally consistent with the relevance of their known cellular functions to the process of carcinogenesis.

Glycolytic Enzymes
Among the differentially expressed proteins identified were glycolytic enzymes {alpha}-enolase, three isoforms of fructose biphosphate aldolase, and glyceraldehyde-3-phosphate dehydrogenase. Up-regulation of glycolysis is a near universal phenomenon in cancer that confers a growth advantage on cells (31). Ubiquitous overexpression of glycolytic genes in 24 cancers representing 70% of human cancer cases worldwide has been reported (32). Increased glucose consumption can be observed with clinical tumor imaging using 18F-fluorodeoxyglucose positron-emission tomography (31). Thus, the observation that the expression levels of glycolytic enzymes are decreased in celecoxib-treated cells is consistent with the growth inhibitory effects of celecoxib.

Molecular Chaperones
Members of the molecular chaperones family are evolutionarily conserved proteins involved in the essential functions of multiprotein complex assembly, protein folding, and proteolytic turnover of key regulators of cellular growth and survival, functions that are often subverted in cancer (33). Four members of this family, GRP-78, GRP 94, T complex protein 1, and Hsp90, were among the 34 proteins identified as affected by celecoxib. Overexpression of GRP-78 is believed to confer cytoprotection and may be a predictor of favorable prognosis in lung cancers (34). GRP-78 seems to be an abundant protein in colorectal cancer cell lines and treatment with 75 µmol/L, but not 5 µmol/L celecoxib, further up-regulated its expression levels in both HCT-116 and HCA-7 cells. Celecoxib also down-regulated the expression level of another member of the molecular chaperone family, Hsp90 (35), in HCT-116 cells, but had no effect on Hsp90 in HCA-7 cells. Inhibitors of Hsp90 as anticancer agents against advanced refractory cancers are currently in clinical trials (36).

Prohibitin
Prohibitin is a potential tumor suppressor protein and a regulator of cell cycle progression and apoptosis. It is located in diverse cellular compartments—predominantly in nucleus where it colocalizes with E2F, Rb, and p53—and seems to have versatile roles in cellular functions (37). There is experimental evidence that prohibitin blocks cell cycle at the G1-to-S transition by repressing E2F-mediated transcription (38). Mutations in the prohibitin gene occur in various cancers including those of breast, liver, and lung (39). Celecoxib-mediated up-regulation of prohibitin in the HCT-116 and HCA-7 cell lines suggests that it may be mechanistically linked to the COX-2-independent chemopreventive effect of celecoxib.

Peroxiredoxin I
Prx I belongs to a family of multifunctional antioxidant thioredoxin-dependent peroxidases that are involved in cellular protection against toxicity by reactive oxygen species and regulation of cell proliferation (40). The most abundant member of the family, Prx I, is implicated in regulation of proliferation and apoptosis (41). Prx I seems to be differentially regulated by celecoxib in the HCT-116 and HCA-7 cell lines.

Creatine Kinase
The enzyme seems to have a critical role in ensuring the availability of adequate supply of ATP. Under conditions where ATP supply does not meet demand, creatine kinase supplies chemical energy for ATP-requiring reactions by rapid transfer of the phosphoryl group between phosphocreatine and ATP.

Cyclophilin A
Cyclophilin A is a member of the superfamily of peptidyl-prolyl isomerases (42). Besides catalyzing cis-trans isomerization of the peptide bond on the NH2-terminal side of proline residues in proteins, members of this superfamily have been implicated in a wide array of cellular processes as diverse as trafficking, signal transduction, regulation of the cell cycle, differentiation, transcriptional regulation, and stabilization of multiprotein complexes (43). Preliminary experiments have suggested that celecoxib affects posttranslational modification rather than expression level of cyclophilin A in both COX-2 expresser as well as nonexpresser cell lines (data not shown). Cyclophilin A has been reported to be overexpressed in colorectal, small-cell lung cancer, and pancreatic carcinomas (44, 45).

Others
The two-dimensional DIGE profiles of celecoxib-treated HCT-116 cells also identified altered expression of cytoskeletal proteins, such as tubulin, tropomyosin I, and calponin-2, as well as desmosomal proteins plakoglobin and desmoplakin, which are involved in cell-cell junctions. Three members of the heterogeneous nuclear ribonucleoproteins (hnRNP) superfamily, A3, C-like, and C1, were among the celecoxib-modulated markers. Members of the hnRNP family have been implicated in the regulation of transcription, mRNA processing and turnover, and regulation of telomerase and telomeres (46). The expression of various members of the hnRNP family was found to be altered in lung cancer (47). Three other molecular targets listed in Table 2 are eukaryotic initiation factor 4A (eIF4A), an RNA helicase and a downstream regulator in the mammalian target of rapamycin signaling pathway (48), another initiation factor, eIF5A, and a translation elongation factor, eEF1A-1, implicated in signal transduction, cell proliferation, and apoptosis (49, 50). The expression of all three translation factors in the HCT-116 cell line increased after treatment with celecoxib. The relevance of this observation to the chemopreventive ability of celecoxib remains to be determined. Other markers targeted for altered expression by celecoxib included a multifunctional protein, nucleolin, implicated in ribosomal biogenesis, transcriptional repression, cell survival, and proliferation (51); Annexin, involved in calcium signaling and membrane dynamics (52); SET, a potential oncoprotein and phosphatase inhibitor (53); and S2/Sa, a ribosomal protein kinase (54).

Thus, the global approach for proteomic profiling used in this study has identified numerous proteomic markers modulated by celecoxib (Table 2). Results displayed in Fig. 5 support the previously described notion that celecoxib-mediated growth inhibition involves multiple non-COX-2 targets irrespective of the presence or absence of COX-2. In addition, our data also present evidence for the following contentions: First, celecoxib modulates the expression levels of many proteins (e.g., {alpha}-enolase, Hsp90, prohibitin, Prx I, and cyclophilin A; Fig. 5A and/or B) both at 5 µmol/L, a concentration generally considered to be ineffective for growth inhibition of cultured cells, and 75 µmol/L with, in many cases, somewhat more pronounced effect at the higher dose. Second, the expression of specific proteomic markers may be altered only at a high dose of celecoxib (e.g., GRP-78; Fig. 5). In the context of the toxicity of celecoxib with long-term use of high daily dose in humans, it would be instructive to understand the significance of at least some of the proteomic markers altered at 75 µmol/L. And third, celecoxib modulation of some proteins may be dictated by the presence of COX-2 (e.g., Hsp90 and Prx I; Fig. 5B and C) and therefore differentially affected in COX-2 expresser versus nonexpresser cell lines.

Future studies using pharmacologically comparable low doses over longer time courses may generate distinct and/or overlapping patterns of changes and may provide a clearer understanding of risks and benefits associated with celecoxib. It would also be instructive to compare global proteomic changes associated with two other chemopreventive agents, rofecoxib, which is highly selective for COX-2, and sulindac sulfone, which does not inhibit either COX-2 or COX-1. These studies may reveal new mechanistic insights into the unresolved issues of risks and benefits of the commonly used COX-2 inhibitors.

In conclusion, application of the powerful global proteomic technologies to elucidating mechanisms underlying the growth inhibitory effects of celecoxib has allowed the first description of wide-ranging proteomic changes that are independent of COX-2. Detailed analysis of the functional role of novel candidate molecular targets identified in this study would extend our understanding of the chemopreventive effects of celecoxib and, in the future, enable more specific and concurrent targeting of multiple key molecular pathways leading to more effective chemoprevention.


   Acknowledgments
 
We thank Dr. Tad Guszczynski and Suzanne Specht for help in using Typhoon 9200 fluorescent scanner and in picking protein spots from gels, and Dr. Ron Lubet for his helpful comments on the manuscript.


   Footnotes
 
Grant support: National Cancer Institute, NIH, contract N01-C0-12400.

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.

5 http://www.ebi.ac.uk/. Back

Received 3/22/06; revised 5/10/06; accepted 6/14/06.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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