Proteomics analysis of a novel compound: Cyclic RGD in breast carcinoma cell line MCF7

RESEARCH ARTICLE

Proteomics analysis of a novel compound: Cyclic RGD in

breast carcinoma cell line MCF-7

Hsueh-Fen Juan 1, 2, I-Hsiu Wang 3, Tsui-Chin Huang 2, 3, Jia-Je Li 4, Shui-Tein Chen 5, 6

and Hsuan-Cheng Huang 4*

1 Department of Life Science, National Taiwan University, Taipei, Taiwan2 Institute of Molecular and Cellular Biology, National Taiwan University, Taipei, Taiwan3 Institute of Chemical Engineering and Institute of Biotechnology,

National Taipei University of Technology, Taipei, Taiwan4 Institute of Bioinformatics, National Yang-Ming University, Taipei, Taiwan5 Institute of Biological Chemistry and the Genomics Research Center, Academia Sinica, Taipei, Taiwan6 Institute of Biochemical Sciences, National Taiwan University, Taipei, Taiwan

In studies of cell adhesion, migration, growth, differentiation, and apoptosis, synthetic peptidescontaining the RGD (Arg-Gly-Asp) motif have been extensively used as the inhibitors of integrin-ligand interactions. The RGD motif is an integrin-recognition motif found in many ligands, so thatthe RGD-containing peptides can be used to probe integrin functions in various biological systems.A linear RGD is a tripeptide consisting of a flexible structure that makes the motif bind to its receptorwith inefficient chelating affinity. Therefore, we designed a cyclic-RGD peptide (Tpa-RGDWPC,cRGD) with rigid skeleton to closely bind with its receptor. The cRGD was obtained by solid-phasepeptide synthesis method using Rink amide resin. We showed that the cRGD exerts more potencythan linear RGD on inhibiting cell growth of MCF-7 breast carcinoma cells. This stimulated us toquestion how cRGD inhibits cell growth of MCF-7 cells. Moreover, understanding what molecularmechanism underlies the effect that RGD motif exerts on MCF-7 cells is also of considerableimportance. We used proteomics and bioinformatics to survey the global changes in proteins aftercRGD treatment in MCF-7 cells. The classification of these proteins is shown according to the dif-ferent biological processes in which they are involved. Most of the proteins that appear to be stronglyinfluenced by cRGD treatment are involved in metabolism, cell growth, responsive to externalstimulus, cell communication, reproduction and cell death. This is the first report which monitorsthe protein expression profile of MCF-7 cells in response to treatment with RGD-containing peptidesin a time-course analysis. The clustering data indicated temporal patterns of altered protein expres-sion that can be categorized into early, intermediate and late response proteins. These patterns ofprotein expression may be important for predicting its response to cRGD. In summary, these resultsprovide a molecular explanation for the properties of cRGD in breast cancer cells and present avaluable in-depth description of their possible impact on breast cancer therapy.

Received: June 12, 2005Revised: November 13, 2005

Accepted: December 21, 2005

Keywords:

Apoptosis / Cluster analysis / MCF-7 / Solid-phase peptide synthesis

Proteomics 2006, 6, 2991–3000 2991

1 Introduction

The tripeptide sequence RGD (Arg-Gly-Asp) is a common cell-recognition motif, which is a part of integrin-binding ligands,like fibronectin, fibrinogen, and vitronectin. This sequence has

Correspondence: Dr. Hsueh-Fen Juan, Department of LifeScience, Institute of Molecular and Cellular Biology, NationalTaiwan University, No 1, Sec. 4, Roosevelt Road, Taipei, 106 Tai-wanE-mail: [email protected]: 1886-2-23673374

Abbreviation: cRGD, cyclic-RGD (Tpa-RGDWPC)* Additional corresponding author: Dr. Hsuan-Cheng Huang

E-mail: [email protected]

DOI 10.1002/pmic.200500435

© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

2992 H.-F. Juan et al. Proteomics 2006, 6, 2991–3000

been used as a leading compound for developing differentintegrin antagonists [1]. RGD-containing peptides have beenfound to be efficient inhibitors of integrin-ligand interactions instudies of cell adhesion, migration, growth and differentiation.Recently, RGD-containing peptides have been shown to be cap-able of inducing cell apoptosis mediated by activation of caspase-3 (an important molecule in the cell death pathway) [2], suggest-ing the potential of developing a more potent RGD-containingpeptide as drug for cancer therapy.

Since the RGD motif is involved in many important bio-chemical mechanisms [3, 4], it is crucial to determine whichwill be the most effective RGD-containing peptide drugs.RGD is a linear peptide with a flexible structure that makesthe motif binds to its acceptor with an inefficient chelating af-finity. Therefore, we designed a cyclic RGD peptide (Tpa-RGDWPC, cyclic-RGD) with rigid skeleton that can bindclosely to its acceptor. Here we proposed a simple methodologyto produce the desired compounds using a solid-phase syn-thesis method. Since resin has become a valuable solid sup-port for the high-throughput synthesis, we chose Rink amideresin, which is used most for peptide synthesis in the resinlibrary, as our starting material.

With the advent of proteomics, the study of systems bi-ology has become plausible [5–7]. Using holistic and biomicstudy of biological transformations, cell death in this case,rapid advances have been made in elucidating these bio-chemical pathways through proteomics methodologies cou-pled with bioinformatics techniques [8]. Proteomics char-acterizes cellular proteins as well as their abundance, state ofmodification, protein complexes and interactions [6, 9, 10].The global changes in cellular protein expression can be vis-ualized by 2-DE and identified by MS analysis [11].

This report demonstrates the usefulness of combiningproteomics and bioinformatics in investigating humanbreast cancer MCF-7 cell death after treatment with a novelcompound, cRGD, at protein level. Our objective was toidentify proteins expressed during MCF-7 cell death and todetermine their functions using bioinformatics technology.We also offer a molecular explanation for the properties ofcRGD on cancer cells and provide a valuable in-depth insightinto its use in cancer therapy.

2 Materials and methods

2.1 Synthesis of linear RGD and cRGD

9-Fluorenylmethoxycarbonyl (Fmoc)-protected amino acidswere purchased from either Bachem or Novabiochem (Ger-many). Rink amide AM resin (loading 0.56 mmol/g) wasobtained from Novabiochem. TFA was from RDG Chemi-cal Co. (Germany).

Peptides for RGD and cyclic-RGD were prepared bysolid-phase peptide synthesis using Fmoc chemistry. Fmoc-protected amino acids were activated in situ in AA cartridgeswith N-methylmorpholine (NMM)/DMF with (benzotriazol-

1-yloxy)-tripyrrolidinophosphonium hexafluorophosphate(PyBOP). Four equivalent amounts of each amino acid deri-vative were used. The coupling yield of each amino acidcoupling cycle was monitored using a ninhydrin test. Theaverage coupling yield was also calculated from the increasein weight of the elongated peptide-resin divided by theweight of protected peptide resin. The sequences of RGDand cRGD (cyclic-3-mercaptopropionic acid-Arg-Gly-Asp-Trp-Pro-Cys) were synthesized on Rink Amide AM resin,which was followed by on-resin disulfide formation afteroxidation by Tl(CF3CO2H)3 in DMF 07C for 80 min. After thefinal Fmoc deprotection with 20% piperidine and pro-grammed wash procedure, the resin complex was driedin vacuo. Peptide side chain deprotection and cleavage werecarried out in TFA under vacuum; the peptide was pre-cipitated by addition of ice-cold dry ether. The precipitate wasfiltered and washed with cold ether on a sintered glass fun-nel, extracted with 20% acetic acid solution and dried by lyo-philization to a white powder. RP-HPLC analysis of the crudeproduct at this stage showed a major peak at 4.5 min forRGD and 11.7 min for cRGD as monitored at 214 nm on aHitachi HPLC system. HPLC analysis was then performedon a C18 column (106250 mm) using the eluent system:0% B in A (A, 5% ACN/95% H2O/0.1% TFA; B, 95% ACN/5% H2O/0.1% TFA) to 100% B with a linear gradient for30 min.

2.2 Cell culture

Human breast carcinoma MCF-7 cells were seeded at aninitial concentration of 105 cells/mL in DMEM (Atlanta Bio-logicals, GA, USA) supplemented with 10% fetal bovineserum (Gibco BRL, NY, USA), 1.5 g/L sodium bicarbonate(Atlanta Biologicals), 4 mM L-glutamine, 1% antibiotic mix-ture, 4.5 g/L glucose, and 1 mM sodium pyruvate (AtlantaBiologicals). Cells were cultured at 377C in an incubator withcontrolled humidified atmosphere containing 5% CO2.

2.3 Induction of cell death

The induction agent, RGD or cRGD, was dissolved inDMEM at a stock concentration of 10 mol/L and stored at2207C. MCF-7 cells (105 cells/mL) were incubated for 24 h,and then the medium was replaced with serum-free mediumand incubated for another 24 h. After that, the cells weretreated with RGD or cRGD at a final concentration of 1 mMand further incubated for 6, 24, 48 or 72 h to induce celldeath. Control samples of un-induced cells were treated inthe same way with same amount of DMEM. We detectedapoptotic cells by 4,6-diamidino-2-phenylindole (DAPI;Sigma, St. Louis, MO, USA) staining. After washing withPBS and fixing with 4% paraformaldehyde for 15 min, thecells were stained with 2 mg/mL DAPI for 20 min. Thestained cells were examined under a fluorescent microscopeand cells were considered to undergo apoptosis based on theappearance of nuclear fragmentation. We also used trypan


Proteomics 2006, 6, 2991–3000 Cell Biology 2993

blue dye exclusion test to determine the average cell countand cell viability. Each data point was tested on triplicatewells, and each experiment was repeated at least three times.

2.4 2-DE and image analysis

MCF-7 cell pellets (16107 cells) were solubilized in lysis buf-fer containing 8% urea (Boehringer Mannheim, Germany),2 M thiourea (Aldrich, WI, USA), and 4% CHAPS (J. T. Ba-ker, NJ, USA). After sonication, 1 mg total protein was loadedinto immobilized pH gradient (IPG) gel strips (pH 3–10, 18-cm long, Amersham Pharmacia Biotech, Uppsala, Sweden);the IPG strips were rehydrated overnight in 7 M urea,2 M thiourea, 4% CHAPS, 40 mM Tris-base, 2% IPG ampho-lyte, 65 mM dithioerythritol (DTE), and 0.0002% bromophe-nol blue prior to use. For the first dimensional separation, IEFwas carried out using the IPGphor system (Amersham Phar-macia Biotech) at 207C with 7000 V for a total of 65 kVh. AfterIEF, the IPG strips were equilibrated for 15 min in an equili-bration solution (50 mM Tris-HCl, pH 8.8, 6 M urea, 2% SDS,30% glycerol, 2% DTE), and then attached with 0.5% agaroseto the top of a vertical 10–15% linear gradient SDS-polyacryl-amide gel. Second-dimensional electrophoresis was carriedout with Protean II Multi-Cell (Bio-Rad, Hercules, CA, USA)at 45 mA per gel for 5 h until the bromophenol blue reachedthe bottom of the gel. The gels were fixed in 10% methanoland 7% acetic acid for 30 min, stained in 350 mL of the SyproRuby protein gel stain solution overnight, and then soaked indeionized water for 20 min to wash residual dye out of thepolyacrylamide matrix. The developed gels were digitallyscanned as 2-D images using a fluorescence image scanningTyphoon 9200 (Amersham Pharmacia Biotech), and then an-alyzed using PDQuest software (Bio-Rad) to automaticallydetect and quantify protein spots. Intensity levels were nor-malized between gels using the proportion of the total proteinintensity detected for the entire gel. At least three replicate gelsof four different time-course preparations were analyzed forconsistence and a representative gel is presented here.

2.5 In-gel digestion

From the 2-D gel analysis of controlled and induced samples,proteins that expressed differentially were selected for identifi-cation by MS. These spots were cut from 2-D gels, sliced into1-mm3 pieces, and then washed three times with 200 mL waterand 50 mM ammonium bicarbonate buffer (pH 8.0) in50% ACN for 15 min. The gel pieces were dehydrated in 50 mMammonium bicarbonate buffer (pH 8.0) for 5 min, and an equalvolume of 100% ACN was added. After 15 min of incubation, allliquid was removed, and 100% ACN was added to cover the gelpieces. After removing the ACN, the gel pieces were dried in avacuum centrifuge. Enzyme digestion was performed by adding15 mL trypsin in 25 mM ammonium bicarbonate to a final con-centration of 5 ng/sample at 567C for 1 h. The peptides frag-ments were extracted with equal volume 100% ACN/2% TFA,and sonicated in a bath for 10 min. The supernatant was recov-

ered and collected in a separate tube, and 20 mL 50% ACN/1% TFA was added to gel slices, with sonication for 10 min, andthe supernatant was added to that previously recovered. The stepwas repeated again. The extracted peptides were concentrated bycentrifugation in a vacuum centrifuge, resolubilized with 5 mL50% ACN/1% TFA, and directly spotted onto the sample plate ofa MALDI-TOFmass spectrometer.

2.6 MALDI-TOF MS

CHCA (0.5 mL, 10 mg/mL) was applied to each spot, and thespots were air-dried at room temperature prior to acquiringmass spectra (M@LDI™, Micromass, Manchester, UK).Monoisotopic peptide mass values were inputted for databasesearch using MASCOT (http://www.matrixscience.com/)against NCBInr and Swiss-Prot protein databases. Swiss-Protpeptide mass mapping, a particularly successful method forthe identification of proteins [10, 12, 13], was used to identifyour proteins. Our protein selection criteria were: a good matchof at least five fragments from a single 2-D gel spot against asingle protein sequence entry in the database, the high cover-age value, and the human-origin sequence; this protein isthen considered as a candidate [14–16]. MS/MS was per-formed using a MALDI-Q-TOF MS hybrid quadrupole/ortho-gonal acceleration TOF spectrometer (M@LDI™, Micromass).The product ion spectra generated by Q-TOF MS/MS weresearched against NCBInr and Swiss-PROTdatabases for exactmatches using the MASCOT search program.

2.7 Bioinformatics analysis

2.7.1 Functional classification of identified proteins

For functional classification, we used BGSSJ (http://bgssj.sourceforge.net/) developed by our laboratory. BGSSJis an XML-based Java application that organizes lists ofinteresting genes or proteins for biological interpretation inthe context of the gene ontology, which organizes informa-tion for molecular function, biological processes and cellularcomponents for a number of different organisms. Theapplication allows for easy and interactive querying usingdifferent gene identifiers (GenBank ID, UniGene, Swiss-Prot, gene symbol), generates a summary page with listingsof the frequencies of gene ontology annotations for eachfunctional category (cluster), separates pages with listings ofannotations for each gene in a cluster, and provides quanti-tative and statistical output files. The visualization browserallows users to navigate the cluster hierarchy displayed in atree-like structure and explores the associated genes or pro-teins of each cluster through a user-friendly interface.

2.7.2 Clustering analysis of protein expression profile

For hierarchical clustering analysis, we used Cluster 3.0 dataclustering software developed at Tokyo University [17], andused Java Treeview visualization software [18] to display the



clustering result. The intensities of protein expression infour time instances measured by PDQuest software werenormalized and subjected to 1-D hierarchical clustering, andthe dendrograms were generated based on the pair-wise cal-culation of uncentered correlation and average-linked clus-tering. The clustering result from Cluster 3.0 was importedinto Java Treeview and displayed in a graded color scheme.Transition of color for each protein from light to dark indi-cates a gradual decrease in expression over time, and fromdark to light indicates an up-regulation of protein expression.

2.8 Western blotting

To verify candidate proteins after PMF, the proteins of inter-est were selected for Western blotting to confirm the resultsof protein database searching. After 2-DE, proteins weretransferred onto PVDF membranes (Amersham Bio-sciences) at 150 V for 1.5 h. After blocking in 5% nonfat milkin PBST containing 0.1% Tween 20 (Sigma) at 47C overnightwith gentle rocking, membranes were probed with anti-bodies. Primary antibodies used in this study include HSPB1and CFL2 (Upstate, Lake Placid, NY, USA) diluted in 1:1000.Membranes were incubated with corresponding primaryantibody and then incubated with secondary antibodies (agoat anti-rabbit conjugated IgG, 1:5000 dilution, Upstate).After incubation with secondary antibodies, immunoblotswere visualized with the ECL detection kit (Amersham Bio-sciences) and exposed to X-ray film.

3 Results and discussion

3.1 Synthesis of RGD and cRGD

RGD (Fig. 1A) is a linear peptide with a flexible structure thathas inefficient chelating affinity when the motif binds totheir receptor. Therefore, we designed a cRGD peptide (Tpa-RGDWPC, Fig. 1B) that has a rigid skeleton to bind closely toits receptor. RP-HPLC analysis of the crude synthesizedproduct shows a major peak at 4.5 min for RGD (Fig. 1C)and 11.7 min for cRGD (Fig. 1D). Purification using HPLCanalysis on a C18 column and freeze-drying yielded a whitepowder for RGD and cRGD. FAB-MS m/z of the new com-pound cRGD was 818.5 (M1).

3.2 Anti-proliferative effect of linear RGD and cRGD

on MCF-7 cells

Incubation of MCF-7 cells with 1 mM cRGD for 48 h causessignificant cell aggregations and anti-proliferative effects.However, incubation with the same concentration of RGDdid not cause this morphological change on MCF-7 cells.Thus, the cRGD has more potency than liner RGD in inhib-iting cell growth on MCF-7 cells (see Supplementary Mate-rial). In Fig. 2, representative photos of DAPI-stainingresults are shown. MCF-7 cells treated with cRGD showingnuclear fragmentation were considered to be undergoingapoptosis. Cell counts and viability of cRGD-free and cRGD-

Figure 1. Structures of RGD (A) and cRGD (B). RP-HPLC analysis of the crude synthesized product shows a majorpeak at 4.5 min for RGD (C) and 11.7 min for cRGD (D), as monitored at 214 nm on a Hitachi HPLC system.



Figure 2. Characterization of the cRGD-induced cell death in human MCF-7cells. Phase-contrast microscopy wasused to detect the morphology of the control (A) and cRGD-treated MCF-7 cells (B). Cell shrinkage, shape irregu-larity, and cellular detachment appear in cRGD-treated cells, but not in control cells. The control (C) and cRGD-treated MCF-7 cells (D) were stained with DAPI.

treated MCF-7 cell lines were determined by trypan blue dyeexclusion test. The cell numbers in cRGD-free and cRGD-treatedcells are (1.39 6 0.17)6105 and (0.24 6 0.04)6105, respectively.The survival rate of MCF-7 cells is calculated to be 17 6 4% afterthe treatment of our synthesized cRGD for 48 h. These resultsdemonstrate the anti-proliferative effect of cRGD on MCF-7 cells.

3.3 Differential expression of proteins in a

time-course analysis

We first monitored the expression profile of MCF-7 cells inresponse to treatment with cRGD in a time-course analysis.Protein analysis of the cells treated with or without cRGD at 6,24, 48, and 72 h was done using 2-DE. Gel electrophoresis wasperformed with pH 3–10 nonlinear strips and linear gradient10–15% SDS polyacrylamide gels. The 2-D gels were digitizedand analyzed simultaneously with PDQuest software. Simul-taneous image matching of MCF-7 control and cRGD-treatedsamples at 6, 24, 48 and 72 h showed 823, 1465, 412, 1130 totalspots from both gels, with 399 (48.5%), 486 (33.2%), 224(54.4%), and 373 (33.0%) matched spots, respectively. Thereare 424 (51.5%), 979 (66.8%), 188 (45.6%) and 757 (67.0%)spots that exhibited detectable quantitative changes between

MCF-7 control and cRGD-treated at 6, 24, 48 and 72 h,respectively. We found 60 proteins to be differentially expres-sed: 22 were up-regulated and 38 were down-regulated atthese four time points (see Supplementary Material).

All these spots were excised and identified by MS/MS orPMF using MALDI-TOF and from Swiss-Prot databasesearches using MASCOT software as described in Sect. 2.6.For clustering analysis, we overlapped four 2-D maps ofcRGD-treated MCF-7 cells from different time points usingPDQuest and extracted the intensities of these overlappedspots. The matching image is shown in Fig. 3. Forty-fourspots are marked by their gene names in this mapping.Western blotting was performed to verify two selected pro-teins, HSPB1 and CFL2. Figure 4 shows the 2-D Westernblotting of the two proteins, which are consistent with theresults from 2-DE and MS-based identification.

3.4 Functional classification and clustering analysis

of differentially expressed proteins

The 44 differentially expressed proteins at the four timepoints were classified according to their subcellular localiza-tion, as shown in Table 1. They are mostly in cytoplasm



Figure 3. 2-DE image matching analysis of four time courses with PDQuest software. The corresponding gene names of proteins aremarked on the map. This quantitatively analytic result was further submitted to function and cluster analysis of proteins.

(48%), nucleus (18%), membrane (10%) and extracellularspace (13%). Our results show that down-regulated proteinslocalized in the cytoplasmic compartment included alphaenolase (ENO1), Merlin (NF2), tubulin-specific chaperone A(TBCA) and Ryanodine receptor 1 (RYR1), whereas tripartitemotif protein 3 (TRIM3), hat shock 27-kDa protein (HSPB1),serine/threonine/tyrosine-interacting protein (STYX), phos-phoglycerate kinase 1 (PGK1), cofilin, muscle isoform(CFL2) and tubulin alpha-6 chain (TUBA6) were up-regu-lated. The differential protein expressions in nucleusincluded nucleolar RNA helicase II (DDX21), zinc fingerprotein 161 homolog (ZFP161), periaxin (PRX) and hetero-geneous nuclear ribonucleoproteins A2/B1 (HNRPA2B1),which decreased, whereas expression of HSPB1 and CFL2increased. The regulation of proteins within the membrane

was observed: levels of PRX, RYR1 and growth factor recep-tor-bound protein 2 (GRB2) decreased, whereas prostatestem cell antigen (PSCA) and platelet glycoprotein IX (GP9)increased. The extracellular proteins metalloproteinase in-hibitor 1 (TIMP1), corticosteroid 11-beta-dehydrogenase,isozyme 2 (HSD11B2), PSCA, and GP9 were up-regulated.Here, GP9 and RYR1 are integral proteins in membrane.Many reports have shown that GP9 mediates cross-linking ofadjacent platelets by interacting with RGD to [19–21].Therefore, cRGD may also be a potent platelet-aggregationinhibitor.

These 44 differentially expressed proteins were also clas-sified according to the biological processes in which they areinvolved. The proteins strongly influenced by cRGD treat-ment are mostly involved in metabolism (51%), cell growth



Figure 4. 2-D Western blot analysis of control and cRGD-treatedMCF-7 cells. The proteins from control MCF-7 cells were sepa-rated by 2-DE, then transferred onto PVDF membrane. Westernblots were performed for HSPB1 (A) and CFL2 (C). The proteinsfrom cRGD-treated MCF-7 cells were also separated by 2-DE, andtransferred to PVDF membrane. Western blots were performedfor HSPB1 (B) and CFL2 (D).

(16%), response to external stimulus (9%), cell communica-tion (6%), reproduction (6%), and cell death (3%). This resultindicates that the growth inhibition effect of cRGD on MCF-7 cells may be caused by changing the metabolic cascadessignificantly in cells.

A subset of the cells, whose functions and biological sig-nificance are related to cRGD action, were selected for hier-archical clustering analysis, and the results are shown inTable 1. The dendrogram of the hierarchical clustering isshown in Fig. 5. The clustering results indicate temporal pat-terns of altered protein expression that can be classified asearly, intermediate and late response proteins. The early re-sponse proteins were induced within 6 h after treatment withcRGD and their expression was undetectable for 24 h. Someof the early response proteins induced by cRGD include heatshock cognate 71-kDa protein (HSPA8), RYR1, MAP kinasephosphatase-like protein MK-STYX (MKSTYX), TBCA andCFL2. These early response proteins including HSPA8, TBCAand CFL2 are involved in protein binding. This result mayimply that these proteins respond to induce or stimulate theexpression of the other proteins such as intermediate and lateresponse proteins by binding with them.

The onset of induction of intermediate response proteinsoccurred 24–48 h after cRGD treatment, and the expression ofthese proteins was shut off by 72 h. They include HNRPA2B1,voltage-dependent anion-selective channel protein 1 (VDAC),NRH dehydrogenase (quinone) 2 (NQO2), pyruvate kinase,M1 isozyme (PKM2), actin, cytoplasmic 2 (ACTG1), TUBA6,HSD11B2, pantothenate kinase 1 (PANK1), deoxyuridine 5’-triphosphate nucleotidohydrolase (DUT), prostate stem cellantigen (PSCA), interleukin-1 receptor-like 1 (ST2), HSPB1,GP9, copper transport protein ATOX1 (ATOX1), STYX, phos-phoglycerate kinase 1 (PGK1), CFL2, and pulmonary surfac-

tant-associated protein D (SFTPD). These intermediate re-sponse proteins, including NME2, DUT, TIMP1, TRIM3,PRDX2, HNRPA2B1, NQO2, PKM2, TUBA6, and PANK1 areinvolved in cellular metabolism such as nucleobase, nucleo-side, nucleotide and nucleic acid metabolism, and cellularmacromolecule metabolism, etc. Dramatic changes in the cel-lular metabolic cascades in cells will induce cell death. Thisresult may explain why these proteins are involved in inter-mediate stage.

The late response protein were induced or repressed be-tween 24 h and 48 h, and their expression either peaked ordeclined by 72 h. There were 20 late response proteins:hemoglobin gamma-A and gamma-G chains (HBG1), fruc-tose-bisphosphate aldolase A (ALDOA), guanylyl cyclaseactivating protein 2 (GUCA1B), arfaptin 1 (ARFIP1), pepti-dyl-prolyl cis-trans isomerase A (PPIA), GRB2, chymase(CMA1), ENO1, glyceraldehyde 3-phosphate dehydrogenase(GAPD), DDX21, ZFP161, mitochondrial dicarboxylate car-rier (DIC), PRX, metalloproteinase inhibitor 1 (TIMP1),nucleoside diphosphate kinase B (NME2), TRIM3, peroxir-edoxin 2 (PRDX2) and NF2. These late response proteins,including GUCA1B, GRB2, PRX, ALDOA, ARFIP1, PPIAand CMA1, are involved in cellular process such as cellcommunication, cell death, and intracellular signaling cas-cade. These are very important in cell communication orsignaling for cell proliferation or growth.

Coordinated changes were found in protein isoformsincluding HSPB1, HNRPA2B1, PPIA and CFL2. For example,HSPB1 (spot 31) (Fig. 3) is the splicing form of HSPB1(spot 24). The three pairs of isoforms have similar molecularweights, but their pI values are shifted (HNRPA2B1, spots 7and 8; PPIA, spots 12 and 13; and CFL2, spots 40 and 41).HSPB1 is a 27-kDa heat shock protein belonging to a family ofabundant and ubiquitous stress proteins [22]. Recent evidencehas shown that HSPB1 regulates apoptosis through its abilityto interact with key components of the apoptotic signalingpathway, in particular, those involved in caspase activation andapoptosis [22–24]. HSPB1 and cofilin are both involved inactin dynamics and are regulated through differential phos-phorylation and subcellular location [25]. HNRPA2B1 is amember of a large family of heterogeneous nuclear ribonu-cleoproteins (hnRNP proteins) involved in a variety of func-tions, including regulation of transcription, mRNA metabo-lism, and translation [26]. Many reports indicate that it couldbe a useful early detection marker for lung carcinoma [26–28].M. Grzmil et al. [29] showed that PPIA had up-regulatedexpression in prostate carcinoma using the cDNA array tech-nique. Our results consistently indicate that HNRPA2B1 andPPIA are down-regulated after cRGD treatment; in addition,HSPB1 and CFL2 were up-regulated in MCF-7 cells.

3.5 Potential molecular mechanism of cRGD treatment

From the observed expression profiles of GRB2, CFL2,HSPB1, and PRDX2 proteins, we propose a hypothesis toexplain the possible molecular mechanism in cRGD-treated


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Figure 5. Hierarchical clustering analysis of cRGD-induced pro-tein profile of MCF-7 cells. Cells were treated with cRGD and thenharvested at the indicated times for proteomics experiments, andthe identified data were then analyzed by PDQuest software asdescribed in Section 2. Proteins with similar expression profileare clustered together in a hierarchical tree-like organization.Transition of color for each protein from light to dark indicates agradual decrease in expression with time, and from dark to lightindicates the up-regulation of protein expression. Three classesof proteins corresponding to different clusters are labeled asearly, intermediate, and late responding proteins, respectively.

MCF-7 breast cancer cells. In a previous report [30], the RGDmotif of integrin-binding ligands (such as fibronectin, fi-brinogen, and vitronectin) was shown to binds to integrin,activating the signal pathway involved in cell growth andproliferation. Our synthesized cRGD may mimic the RGDmotif of integrin-binding ligands to bind to integrin. How-ever, this binding could not induce the signal pathwayinvolved in cell growth and proliferation as indicated by theobserved GRB2 behavior. GRB2 is a component in integrinsignal cascade and was found to be down-regulated after

cRGD treatment. As a result, the MCF-7 cells may proceedto apoptosis pathways. In addition, cofilin (CFL2), whichwas up-regulated in cRGD-treated MCF-7 cells, can stimu-late actin depolymerization and changes in cell structure.When cell apoptosis is under way, actin depolymerizationand changes in cell structure occur. HSPB1 is also up-regu-lated in cRGD-treated MCF-7 cells. One action of HSPB1induced by stress is to protect cells against apoptosis, and acommon component of apoptotic pathways is the mito-chondrial release of cytochrome c [31]. One way that HSPB1reduces apoptosis is by preventing the release of cyto-chrome c and by binding to cytochrome c in the cytosol.Downstream, HSPB1 also blocks caspase-9 activation andthe subsequent activation of caspase-3, inhibiting the rest ofthe proteolytic caspase cascade [23]. The interaction ofHSPB1 with actin filaments may also prevent apoptosis [32].Unphosphorylated HSPB1 monomers regulate actin fila-ment growth by binding to the end of fibers and cappingthem. Finally, HSPB1 appears to prevent damage to cells byreactive oxygen species (ROS), by altering the oxidative en-vironment of the cell through induction of glutathioneexpression, as well as blocking apoptosis induced by ROS. Ina previous study [33], PRDX2 was found not only to protectcells from oxidative damage caused by ROS such as hydro-gen peroxide, but also to endow cancer cells with resistanceto both hydrogen peroxide and cisplatin and to grant themradio-resistance. This is consistent with our observation. IncRGD-treated MCF-7 cells, PRDX2 is up-regulated to protectthe cancer cells against apoptosis. In summary, cRGD maybind to membrane-bound protein integrin, the downstreamprotein GRB2 may not be induced, and cofilin may depoly-merize F-actin. Furthermore, as the cRGD-treated MCF-7cells proceed to apoptosis, these cells may produce manyoxidative agents and depolymerized F-actin; so PRDX2 andHSPB1 may be produced by feedback to inhibit the cancercell apoptosis. This is because cancer cells themselves arelooking for a way out. Together, these results could demon-strate a molecular explanation for the properties of cRGD incancer cells and provide a valuable insight towards their rolein cancer therapy.

4 Concluding remarks

cRGD acts as an anti-cancer compound to decrease the pro-liferation of breast cancer MCF-7 cells. The identification in arepresentative breast cancer cell line of proteins, whoseexpressions are altered by cRGD, may help us understandthe biology of breast carcinoma and the molecular mechan-ism involved in the response to cRGD treatment. This studyconfirms that proteomic analysis is a powerful tool for evi-dencing protein expression related to the effect of antitumordrugs such as cRGD on tumor growth, and this approachopens the way of defining therapeutic targets for treatmentof breast cancer. This information may represent a powerfultool for breast cancer diagnosis and therapy.



This work was supported by National Science Council ofTaiwan (NSC 93-2311-B-010-017 and NSC 94-3112-B-002-011). We gratefully acknowledge Nancy Lin for proofreading themanuscript and the Core Facilities for Proteomics Research,Academia Sinica, Taiwan.

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Proteomics analysis of a novel compound: Cyclic RGD in breast carcinoma cell line MCF7

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