Extracellular Remodelling During Oncogenic Ras ... - ACS Publications

Extracellular Remodelling During Oncogenic Ras-Induced Epithelial-Mesenchymal Transition Facilitates MDCK Cell Migration Rommel A. Mathias,† Yuan-Shou Chen,†,‡ Bo Wang,‡ Hong Ji,† Eugene A. Kapp,† Robert L. Moritz,† Hong-Jian Zhu,‡ and Richard J. Simpson*,† Joint Proteomics Laboratory, Ludwig Institute for Cancer Research and the Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia, and Department of Surgery, Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia Received October 9, 2009

Epithelial-mesenchymal transition (EMT) describes a process whereby immotile epithelial cells escape structural constraints imposed by cellular architecture and acquire a phenotype characteristic of migratory mesenchymal cells. Implicated in carcinoma progression and metastasis, EMT has been the focus of several recent proteomics-based studies aimed at identifying new molecular players. To gain insights into extracellular mediators associated with EMT, we conducted an extensive proteomic analysis of the secretome from MDCK cells following oncogenic Ras-induced EMT (21D1 cells). Using Orbitrap technology and a label-free quantitative approach, differential expression of several secreted modulators were revealed. Proteomic findings were further substantiated by mRNA transcript expression analysis with 71% concordance. MDCK cells undergoing Ras-induced EMT remodel the extracellular matrix (ECM) via diminished expression of basement membrane constituents (collagen type IV and laminin 5), upregulation of extracellular proteases (MMP-1, kallikreins -6 and -7), and increased production and secretion of ECM constituents (SPARC, collagen type I, fibulins -1 and -3, biglycan, and decorin). Collectively, these findings suggest that hierarchical regulation of a subset of extracellular effectors may coordinate a biological response during EMT that enhances cell motility. Transient silencing of MMP-1 in 21D1 cells via siRNA-mediated knockdown attenuated cell migration. Many of the secretome proteins identified broaden our understanding of the EMT process. Keywords: epithelial-mesenchymal transition • MDCK • Ras • secretome • proteomics • MMP-1 • siRNA • Orbitrap

Introduction Epithelia are generally organized as continuous cell sheets tightly connected to surrounding cells via intercell adhesive junctions, which mediate apical-basal polarity and restrict movement.1 Epithelial-mesenchymal transition (EMT) describes a morphogenetic process whereby uniform epithelial cells lose apical-basal polarity, undergo changes in shape, and acquire increased mobilitysproperties typical of mesenchymal cells.2 Cells undergoing EMT appear elongated, exhibit a leading edge front-back polarity,3 and reorganize their cytoskeleton to facilitate cell migration.4 Commonly described in developmental events such as gastrulation and organogenesis, as well as fibrosis, wound healing, and tissue remodelling,5,6 EMT has been more recently implicated as a mechanism during the initial stages of metastasis.7,8 * To whom correspondence should be addressed. Professor Richard J. Simpson, Ludwig Institute for Cancer Research, PO Box 2008, Royal Melbourne Hospital, Royal Parade, Parkville, Victoria 3050, Australia. Tel: +61 03 9341 3155. Fax: +61 03 9341 3192. E-mail: Richard.Simpson@ ludwig.edu.au. † Ludwig Institute for Cancer Research and the Walter and Eliza Hall Institute of Medical Research. ‡ The University of Melbourne. 10.1021/pr900907g

 2010 American Chemical Society

EMT progression requires cells to overcome the structural integrity and attachment to neighboring cells mediated by E-cadherin.1 E-cadherin is considered one of the caretakers of the epithelial phenotype, and loss of expression is an EMT hallmark.2,9 Several transcription factors (TFs) including zinc finger proteins of the Snail/Slug family, δEF1/ZEB1, SIP1, and the basic helix-loop-helix factor E12/E47 have been shown to bind to proximal E-box promoters of the E-cadherin gene to repress its transcription.2,10,11 Additionally, these TFs also promote EMT by repressing a subset of genes that encode cadherins, claudins, integrins, and zonula occludens.6 Following disassembly of the main cell-cell junctions, a number of signaling pathways orchestrate an elaborate genetic program instrumental for EMT induction.12 These include the Wnt, Transforming growth factor β (TGFβ), Hedgehog, Notch and nuclear factor-κB signaling pathways. External EMT inducingstimuli include collagen, hyaluronic acid, Wnt, TGFβ, epidermal growth factor and hepatocyte growth factor.13,14 Mesenchymal protein markers noted to increase expression during EMT include N-cadherin, vimentin, and fibronectin.15 Although the list of molecular signatures defining EMT is expanding, our current knowledge of extracellular molecules that maintain and Journal of Proteome Research 2010, 9, 1007–1019 1007 Published on Web 12/02/2009

research articles enhance mesenchymal cell morphology and migratory behavior remains incomplete. In an unambiguous manner, proteomics can monitor the global expression of multiple targets simultaneously, and so possesses tremendous potential in revealing the molecular players and signaling networks controlling complex biological processes.16 Proteomic profiling has the ability to identify context-dependent expression patterns, and several EMT studies have implemented proteomic strategies to uncover new insights and candidate markers that might have implications in cancer diagnosis, prognosis, and treatment,17-22 for a recent review see Mathias et al.23 For example, Keshamouni and colleagues studied expression changes resulting from TGFβinduced EMT in human lung adenocarcinoma A549 cells, using an iTRAQ-based quantitative strategy.24,25 Proteomic techniques have identified proteins with dysregulated expression during EMT; however they have generally been proteins of high cellular abundance such as vimentin and members of the cytokeratin family.20,21 In all studies to date, excluding Keshamouni et al.24,25 and Hill et al.,26 complex cell lysates were analyzed via two-dimensional electrophoresis (2-DE). This method has a dynamic range of protein separation typically between 104 and 105 and is generally limited to the most abundant proteins in a complex mixture.27 In an attempt to identify novel EMT effectors, we have developed a subproteome strategy to enrich for the secretome, a cellular subproteome comprising both secreted proteins/peptides, as well as membrane-derived nanoparticles termed exosomes that are released from cells.28,29 The secretome is a likely source of bioactive molecules that include secreted growth factors, proteases, extracellular matrix (ECM) components, cytokines, and motility factors,30 and is representative of dynamic cellular processes that occur in the extracellular microenvironment.31 Secreted molecules perform integral functions during differentiation, invasion and metastasis, and are capable of trafficking to body fluids such as lymph, blood, and urine.32 Furthermore, while secretome analysis emerges as a promising tool to discover novel cancer biomarkers, application in the context of EMT may enable us to better understand acquisition of mesenchymal cell attributes and phenotype. Previously, we analyzed secretome protein profiles from MDCK cells as they undergo EMT following oncogenic Rastransformation (21D1 cells), using 2-D fluorescence difference gel electrophoresis (DIGE) technology.33 This pilot study revealed that cells undergoing EMT down-regulate cell-cell and cell-matrix adhesion proteins that normally restrict movement (desmocollin 2, clusterin, collagen XVII, and transforming growth factor-β induced protein ig-h3), and concomitantly increase expression of proteases and factors that promote migration (MMP-1, kallikrein 6, TIMP-1, and S100A4/metastasin). In the present study, we have employed the sensitivity, increased duty cycle, and high-mass accuracy of the LTQOrbitrap mass spectrometer,34,35 along with 1D SDS-PAGE protein separation,36 to penetrate deeper into the MDCK and 21D1 cell secretomes. Adopting a label-free quantitative approach based on spectral counting,37 we have identified several proteins that are significantly dysregulated during EMT, and our proteomic findings are further substantiated via microarray mRNA transcript analysis. Data generated during global secretome profiling suggests that extracellular remodelling occurs during EMT via the expression of a defined subset of extracellular effectors including proteases, protease inhibitors, and 1008

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Mathias et al. ECM substrates. Furthermore, their expression may be regulated by a hierarchical mechanism and facilitate cell motility.

Experimental Procedures Cell Culture. MDCK cells38 and the oncogenic mutated Rastransformed MDCK derivative 21D1 were routinely cultured in Dulbecco’s modified Eagle’s medium (DMEM) (GIBCO) supplemented with 10% FCS (CSL), 60 µg/mL penicillin (CSL), 100 µg/mL streptomycin (Sigma) at 37 °C with 10% CO2. 21D1 cells were generated by transfecting pcDNA3 (Invitrogen) containing v-Ha-Ras under the control of a CMV promoter and a SV40driven neomycin resistance plasmid gene into MDCK cells using Fugene6 (Roche), according to manufacturer’s instructions. Clones stably expressing Ras were isolated by confirmation of Ras expression by Western blot analysis and immunofluorescence from G418 (Invitrogen) resistant clones. The 21D1 clone was selected as the mesenchymal model for further studies.33 Confocal Immuno-Fluorescence Microscopy. MDCK and 21D1 cells were plated onto 15-mm glass coverslips in 6-well plates (Nunc) and grown for 24 h in an incubator in preparation for confocal immuno-fluorescence microscopy. Cells were washed twice with PBS and fixed in 100% methanol at room temperature for 8 min. For actin staining, cells were fixed with 3.7% formaldehyde for 10 min, then permeabilised with 1% Triton X-100 (Merck) for 5 min. Cells were washed three times with PBS and blotted with 5% BSA in PBS for 1 h. Cells were incubated with either E-cadherin (Transduction laboratories), ZO-1 (ZYMED), or vimentin (Chemicon) primary antibodies diluted in PBS containing 1% BSA and 1.5 mM NaN3 at room temperature for 1-2 h or at 4 °C overnight. After three PBS washes, secondary antibodies Alexa Fluor 488 goat antimouse or antirabbit IgG (H+L), Alexa Fluor 546 goat antimouse or antirabbit IgG (H+L) (Molecular Probes) were incubated for 1 h and then washed three times with PBS. For actin staining, formaldehyde-fixed cells were stained with 546 conjugated Phalloidin (Molecular Probes) at room temperature for 1 h and washed three times with PBS. Immuno-fluorescence imaging was performed on a Bio-Rad MRC-1000 confocal microscope. Wound Healing Assay. Migration/motility of MDCK and 21D1 cells was analyzed in vitro using the wound healing assay as previously described.39 Briefly, confluent cell monolayers were wounded (lightly scratched) with a pipet tip. After careful washing to remove detached cells, fresh medium was added and the cells left to culture for 24 h. Phase contrast images were taken at 0 and 24 h, and migration evaluated based on the percentage of wound closure. Phase contrast microscopy and imaging was performed using a Nikon TE 2000-E microscope equipped with a DP-70 camera. Transwell Assay. Two × 105 cells were seeded in serum-free DMEM containing 1% BSA (Sigma) onto 6.5 mm 8 µm polycarbonate membrane transwell inserts (Corning). Inserts were then submerged in DMEM containing 10% FCS and cells left to culture for 24 h. Inserts were washed in PBS and fixed with 100% methanol before being stained with hematoxylin for 30 min. Cells on the inner side of the insert were removed via gentle wiping with a cotton bud. The number of cells that migrated through the insert toward the bottom chamber was counted in ten random fields using phase contrast microscopy. Cell Viability Assay. MDCK and 21D1 cell viability was estimated using the in vitro Toxicology Assay kit (Sigma) which is based on the lactate dehydrogenase (LDH) assay.40 The assay was performed according to manufacturer’s instructions. Briefly,

Extracellular EMT Remodelling MDCK and 21D1 cells were lysed and the amount of LDH per cell measured to generate a standard curve. Culture medium (CM) collected from cells cultured in 10% FCS or serum-free DMEM after 24 h was then measured for LDH to determine the number of dead cells. All readings were performed in triplicate. Secretome Purification. Secretome purification was performed as previously described.33 Briefly, MDCK and 21D1 cells were grown to 70% confluence in DMEM containing 10% FCS, washed three times with serum-free DMEM, and left to culture in this medium at 37 °C with 10% CO2 for 24 h. CM from 10 dishes (a total of 100 mL from 5 × 107 cells for each line) was harvested and centrifuged twice (480× g 5 min, 2000× g 10 min) to sediment floating cells and remove cellular debris. Complete EDTA-free protease inhibitor cocktail tablets (Roche) were added to the resultant supernatant and the solution filtered through a 0.1 µm Supor membrane VacuCap 60 Filter Unit (Pall). The filtrate was concentrated to 1 mL using 5K NMWL Amicon Ultra Centrifugal Filter Devices (Millipore), and total protein precipitated using the 2-D Clean-Up Kit (GE Healthcare). Proteins were resolubilised in 2× NuPAGE LDS Sample Buffer (Invitrogen) and concentrations determined using the 2-D Quant Kit (GE Healthcare). SDS-PAGE. Thirty micrograms from each MDCK and 21D1 secretome sample was electrophoresed on a NuPAGE Novex 4-12% Bis-Tris Gel (Invitrogen). Electrophoresis was performed at 150 V in NuPAGE MES Running Buffer (Invitrogen) until the tracking dye had reached the bottom of the gel. Proteins were visualized by incubating the gels in Imperial Protein Stain (PIERCE) according to manufacturer’s instructions. Gel Excision and Tryptic Digestion. For each secretome sample, 32 2-mm gel bands were excised from the gel lane and each band subjected to automated in-gel reduction, alkylation, and tryptic digestion36 using the MassPREP Robotic Liquid Handling Station (Micromass). Briefly, gel sections were reduced with 10 mM DTT (Calbiochem) for 30 min, alkylated for 20 min with 25 mM iodoacetic acid (Fluka), and digested with 150 ng trypsin (Worthington) for 4.5 h at 36 °C. Extracted peptide solutions were concentrated to approximately 10 µL by centrifugal lyophilization using a SpeedVac AES 1010 (Savant) for subsequent LC-MS/MS analysis. LC-MS/MS. A 96-well plate containing extracted tryptic peptides was loaded into the microwell plate autosampler for injection and fractionation by nanoflow reverse-phase liquid chromatography on a 1200 series LC system (Agilent) using a nano-Acquity C18 150 × 0.15 mm i.d. column (Waters) developed with a linear 60-min gradient with a flow rate of 0.8 µL/ min at 45 °C from 0-100% solvent B, where solvent A was 0.1% aqueous formic acid and solvent B was 0.1% aqueous formic acid/60% acetonitrile. The nano HPLC was coupled online to an LTQ-Orbitrap mass spectrometer equipped with a nanoelectrospray ion source (Thermo Fisher Scientific) for automated MS/MS. The Orbitrap was operated in positive ion mode for data-dependent acquisition. Survey MS scans were acquired with the resolution set to a value of 30 000. Real time recalibration by corrections of mass shift was performed by the use of a background ion from ambient air in the C-trap.41 Up to five most peptide intense ions per cycle were fragmented and analyzed in the linear trap, with target ions already selected for MS/MS being dynamically excluded for 3 min. Database Searching and Protein Identification. Peak lists were extracted using extract-msn as part of Bioworks 3.3.1 (Thermo Fisher Scientific). The parameters used to generate

research articles the peak lists were as follows: minimum mass 700, maximum mass 5000, grouping tolerance 0.01 Da, intermediate scans 200, minimum group count 1, 10 peaks minimum and total ion current of 100. Peak lists for each LC-MS/MS run were merged into a single MGF file for MASCOT searches. Automatic charge state recognition was used because of the high-resolution survey scan (30000). MGF files were searched using the MASCOT v2.2.01 search algorithm (Matrix Science) against the Q408 LudwigNR_subset database with a taxonomy filter for human, cow and dog, comprising 166 124 entries (http://www.ludwig.edu.au/ archive/LudwigNR/LudwigNR.pdf). The search parameters consisted of carboxymethylation of cysteine as a fixed modification (+58 Da), NH2-terminal acetylation (+42 Da) and oxidation of methionine (+16 Da) as variable modifications. A peptide mass tolerance of (20 ppm, #13C defined as 1, fragment ion mass tolerance of (0.8 Da, and an allowance for up to three missed tryptic cleavages was used. Protein identifications were first clustered and analyzed by an in-house developed program MSPro, as previously described.42 Briefly, peptide identifications were deemed significant if the Ion score was g the Homology score. False-positive protein identifications were estimated by searching MS/MS spectra against the corresponding reverse-sequence (decoy) database.43 MDCK and 21D1 secretome lists were generated with identifications with a protein score above the 1% false discovery rate cutoff of 48. Protein annotation was obtained from the Ensembl database, and where an annotation was not available, the amino acid sequence of the protein was proteinBLAST searched against the Uniprot database, and the human homologue’s properties inferred. Differential Protein Expression Determination and Significance. Significant spectral count fold change ratios (RSC) were determined using a modified formula from a previous serial analysis of gene expression study by Beissbarth et al.44 RSC ) log2[(n21D1 + f )/(nMDCK + f )] + log2[(tMDCK - nMDCK + f )/(t21D1 - n21D1 + f )]

(1)

Where, n is the significant protein spectral count (a peptide spectrum is deemed significant when the Ion score g the Homology score), t is the total number of significant spectra in the sample, and f a correction factor set to 1.25.45 Binomial testing was also applied to the significant spectral count values using the constant probability p ) 0.64 (tMDCK/(tMDCK + t21D1)). The resulting P-values were then corrected for multiple testing using the Benjamini-Hochberg procedure.46 Significance was set below P-value of 0.05 after correction. RNA Isolation and mRNA Gene Expression Analysis. Microarray analysis was performed as previously described.33 Briefly, MDCK and 21D1 cells were gown under the same conditions as described in culture medium collection for proteome analysis, before total RNA was isolated using an RNeasy Mini Kit (Qiagen) according to the manufacturer’s instructions. RNA quality was assessed on the Agilent Bioanalyser 2100 using the NanoChip protocol. Seven micrograms of total RNA was labeled using the Affymetrix One Cycle cDNA synthesis kit (Millennium Sciences) and the resultant cDNA was cleaned using the Affymetrix GeneChip Sample Cleanup kit (Millennium Sciences). Incorporation of biotin into the resultant cRNA was achieved using the Affymetrix IVT labeling kit (Millennium Sciences), and the labeled cRNA cleaned with the Journal of Proteome Research • Vol. 9, No. 2, 2010 1009

research articles Cleanup kit, before being quantified on the Bioanalyser. Twenty micrograms of biotin-labeled cRNA was then fragmented to the 50-200 bp size range, and quality control checked on the Bioanalyser. cRNA (0.05 µg/µL) and a probe cocktail including, 1× Hybridization Buffer (100 mM MES, 1 M NaCl, 20 mM EDTA, 0.01% Tween-20), 0.1 mg/mL Herring Sperm DNA, 0.5 mg/mL BSA, and 7% DMSO were then prepared for hybridization to the Canine Genome 2.0 GeneChip Array (Affymetrix). A total hybridization volume of 200 µL per sample was loaded onto each Canine GeneChip, for hybridization at 45 °C for 16 h with 60 rpm rotation. Chips were then washed using the appropriate fluidics script in the Affymetrix Fluidics Station 450, and scanned using the Affymetrix GeneChip Scanner 3000. The scanners GeneChip Operating Software (GCOS), was then used to convert the signal from the chip into a DAT file. Subsequent CEL and CHP files were generated for analysis, and fold change differences calculated between samples. siRNA Design and 21D1 Cell Transfection. All 25-base double stranded Stealth RNAi duplexes were purchased from Invitrogen. The sense and antisense strands for MMP-1 were designed using the Invitrogen RNAi Designer with the GenBank accession number XM_546546. Stealth siRNA duplexes targeting MMP-1 were delivered to 3 × 105 21D1 cells using Lipofectamine 2000 Reagent (Invitrogen) in 6-well plates, according to manufacturer’s instructions. Transfection of negative control siRNA (Invitrogen), or negative control siRNA labeled with Alexa Fluor 555 (Qiagen) was performed similarly. Medium was replaced 6 h after transfection, and cells further cultured for 42 h before western immuno-blotting or the wound healing or transwell migration assays were performed. Western Immuno-Blotting. To assess MMP-1 expression, cell lysates were prepared with lysis buffer (2% SDS, 125 mM Tris-HCl pH 7.4, 12.5% glycerol, 0.02% bromophenol blue) on ice for 30 min, followed by centrifugation to remove insoluble cellular debris. Supernatants were collected and quantified using the 2-D Quant Kit (GE Healthcare). Expression of laminin 5 γ2 and SPARC were confirmed in secretome samples. For all westerns, 15 µg of protein sample was subjected to SDS-PAGE electrophoresis (as above). Proteins were then electro-transferred to nitrocellulose membranes using the iBlot Dry Blotting System (Invitrogen), and blocked with PBS buffer containing 0.2% Tween-20 and 5% powdered milk overnight at 4 °C. Membranes were probed with either a rabbit anti-MMP-1, rabbit anti-SPARC or goat anti-laminin 5 γ2 (Santa Cruz Biotechnology) primary antibody for 1 h, followed by incubation with the corresponding goat anti-rabbit IgG IRDye 680 (LICOR Biosciences), or donkey anti-goat H&L Cy5.5 (Abcam) secondary antibody for 1 h. Antigen-antibody complex detection was performed using an Odyssey Infrared Imaging System (LI-COR Biosciences).

Results MDCK Cells Undergo EMT after Oncogenic Ras-Transformation. Following MDCK cell transfection with oncogenic Ras, four clones resistant to G418 (21D1, 21F3, 21A7, 3F10) were isolated and examined for cell morphology and Ras expression. Phase contrast images show that all four clones have an elongated spindle-shaped morphology, while western immuno-blotting analysis revealed elevated expression of Ras compared with MDCK cells in all four clones (Supporting Information Figures S1A and S1B). Given that the highest expression of Ras was observed in the 21D1 clone, it was selected as the mesenchymal cell model for further characterization of molecular markers 1010


Mathias et al. and phenotypic behavior associated with EMT (Figure 1A-D).33 21D1 cells appear scattered in culture compared to MDCK cells which tightly adhere to neighboring cells and have a cobblestone-like morphology (Figure 1A). Confocal microscopy revealed that MDCK cells, unlike 21D1 cells, exhibit positive staining for the epithelial markers E-cadherin and ZO-1 between adjoining cells (Figure 1B). In contrast, the mesenchymal marker vimentin was only expressed throughout the cytoplasm in 21D1 cells (Figure 1B). To observe cytoskeletal structures, actin was stained with fluorescently labeled phalloidin and imaged at apical and basal transverse sections (Figure 1B). MDCK cells display apical actin rings, and weak parallel stress fibres and heavy bundles that localize to the basal cell periphery. In comparison, 21D1 cells do not have an apical ring or highly organized basal bundles, but contain a more diffuse pattern consisting of very weak actin stress fibres. This disordered actin pattern is indicative of cells that lack polarity. When cell motility was evaluated using the wound healing assay (Figure 1C), the MDCK cell monolayer displayed restricted epithelial sheet migration after 24 h. In contrast, 21D1 cell migration was enhanced with individual cells moving into the open area to close the wound entirely after 24 h. Similarly, 21D1 cells exhibited elevated mobility when the transwell cell migration assay was performed (Figure 1D). Only one single MDCK cell was able to migrate through the transwell filter after 24 h, while an average of 28 21D1 cells moved through the insert toward the lower chamber. MDCK and 21D1 Cells Remain Viable during 24 h SerumFree Culture. Serum-free culture conditions were employed during secretome isolation to minimize the number of FCS contaminants identified. We performed the lactate dehydrogenase (LDH) assay on cell culture medium from MDCK and 21D1 cells to estimate the proportion of cells that had lysed during the 24 h culture period. The data shows that both MDCK and 21D1 cell viability decreased (∼1-4%) under serum-free conditions (Figure 2). When the culture conditions for MDCK cells were changed from 10% FCS to serum-free DMEM, the viability reduced 1.6% (from 98.9 to 97.3). In contrast, 21D1 cell viability reduced 3% (from 99.2 to 96.2) under identical conditions. Because cell death was minimal, secretome isolation was performed under serum-free conditions over 24 h. Secretome Analysis and Spectral Counting Reveals Proteins that are Dysregulated during EMT. To identify proteins in MDCK and 21D1 secretomes, samples were separated via 1D SDS-PAGE. Gel lanes were excised into 32 2-mm bands and individually digested with trypsin, and the generated tryptic peptides subjected to LC-MS/MS using LTQ-Orbitrap technology. Utilizing the increased duty cycle and sensitivity of this instrument during secretome analysis47 resulted in a total of 777 protein identifications (Supporting Information Table S1). The distribution of peptides identified and spectral counts observed for each individual protein across the entire gel lane was visualized using the PROTOMAP proteomic platform. Of the 731 proteins identified in the MDCK secretome (Supporting Information Table S2), clusterin was the most abundant with 1364 significant spectral counts and 39 unique significant peptides (Figure 3A), while fibronectin was identified by 144 peptides and 1767 spectral counts (Figure 3A) in the 21D1 secretome comprising 505 proteins (Supporting Information Table S3). Proteins significantly dysregulated following Ras-transformation were determined using protein spectral count fold change ratios (RSC) as proposed previously.37,44,45 This calculation

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Figure 1. MDCK cells undergo EMT following oncogenic Ras-transformation. (A) Phase contrast microscopy reveals MDCK cells lose their round cobblestone-like appearance in favor of an elongated spindle-shaped morphology following Ras-induced EMT. (B) Confocal microscopy imaging shows reduced expression of epithelial markers E-cadherin and ZO-1 between cell junctions, but increased expression of the mesenchymal marker vimentin during the EMT process. Apical actin rings and heavy basal bundles localize to the MDCK cell periphery, while the actin pattern of 21D1 cells is considerably more diffuse and consists of weak stress fibres. (C) Wound healing assay reveals that 21D1 cells have enhanced migration compared to MDCK cells. (D) 21D1 cells demonstrate elevated cell motility over MDCK cells in the transwell cell migration assay. Bar graphs show mean + S.D.

Figure 2. Cell viability of MDCK and 21D1 cells during secretome purification. Cell viability measured via the lactate dehydrogenase assay following 24 h culture in serum-free DMEM or 10% FCS. The viability of both cell lines decreased in the absence of FCS but remained above 96%. Bar graphs show mean ( S.D.

peptides and 160 significant spectral counts (RSC of -6.2) identified only in the MDCK secretome (Figure 3B). The most up-regulated protein (RSC of 7.4) following Ras-transformation was collagen alpha-2(I), identified exclusively in the 21D1 secretome with 15 unique significant peptides and 117 significant spectral counts (Figure 3B). While there is some variable band spreading that could be due to sample carryover between runs, both SPINK5 and collagen alpha-2(I) can be proteolytically processed by furin and MMP-1, respectively, which may account for smaller fragments observed. Dysregulated expression of laminin 5 γ2, and SPARC (secreted protein acidic and rich is cysteine) revealed by proteomic profiling was confirmed by western immuno-blotting and confocal immuno-microscopy (Figure 4A).

provides the log2 ratio of estimated abundance of a protein in one sample relative to the other. In addition we calculated P-values for each protein RSC based on the number of significant spectral counts observed (Supporting Information Table S1). From the 777 proteins identified, 287 showed differential expression during EMT that was deemed statistically significant with a P-value of less than 0.05. We focused our analysis on the 70 proteins which had extracellular annotation according to Uniprot or Gene Ontology (Table 1). Interestingly, serine protease inhibitor Kazal-type 5 (SPINK5) was the most downregulated protein during EMT, with 44 unique significant

Gene Expression Profiling Correlates with SecretomeBased Proteomic Data. mRNA expression profiling using the Affymetrix Canine Genome 2.0 Array was performed to examine the correlation between protein expression and mRNA levels during EMT. In total, the microarray experiment revealed that 7251 probe sets were down-regulated, and 4530 were upregulated following Ras-transformation in MDCK cells. However, we restricted our analysis to those transcripts whose protein levels were found to be dysregulated via proteomic profiling. Strong correlation was observed between the regulation of protein and mRNA levels for 50 out of the 70 (71%) differentially expressed secretome proteins in Table 1 (detailed Journal of Proteome Research • Vol. 9, No. 2, 2010 1011

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Figure 3. Secretome profiling and label-free spectral counting reveals extracellular modulators of EMT. (A) Peptographs displaying significant spectral counts identified across the SDS-PAGE gel for the most abundant secretome proteins; 1364 significant spectral counts were detected for clusterin in the MDCK secretome, while the most abundant protein in the 21D1 secretome was fibronectin with 1767 counts. (B) Peptographs displaying spectral count distributions for the most differentially expressed proteins during EMT. Spectral count fold change ratios (RSC, eq 1) determined serine protease inhibitor Kazal-type 5 to be the most down-regulated protein with 160 significant spectral counts detected uniquely in the MDCK secretome. Conversely, the most up-regulated protein was collagen alpha-2(I), with 117 significant spectral counts identified exclusively in the 21D1 secretome. Peptographs were generated using the PROTOMAP proteomic platform,89 and adapted. Dashed lines indicate calculated protein molecular weight. Green represents the MDCK secretome and red the 21D1 secretome.

gene expression data for these individual probe sets can be found in Supporting Information Table S4). Further analysis and investigation was limited to these 50 proteins. Interestingly, this orthogonal approach used to confirm our proteomic findings revealed that expression of SPINK5 mRNA was down-regulated 79 fold, while transcription of the collagen alpha-2(I) gene was up-regulated 4096 fold following Ras-transformation. In addition, our microarray data revealed that mRNA levels for MMP-1 were the most upregulated during the EMT process (8780 fold), and this was consistent with the elevated protein expression observed during secretome analysis (RSC of 5.7). RNA Interference of MMP-1 Attenuates 21D1 Cell Migration. To evaluate the contribution of up-regulated MMP-1 levels on enhanced 21D1 cell migration during EMT, we knockdown its expression using transient siRNA transfection (Figure 5). Stealth Select RNAi sequences were designed using the BLOCKiT RNAi Designer (Invitrogen), and four MMP-1 target duplexes synthesized for RNA interference (Supporting Information Figure S2-A). Lipofectamine 2000 Reagent (Invitrogen) was used to deliver a fluorescent negative control siRNA labeled with Alexa Fluor 555 (Qiagen). Using fluorescence microscopy, the transfection efficiency of 21D1 cells was estimated to be approximately 75% (Supporting Information Figure S2-B). We proceeded to transfect 3 × 105 21D1 cells at 40% confluency in a 6-well plate with 100 pmol of each of the four siRNA Targets to MMP-1, or the scrambled negative control. Western blot analysis of cell lysates 48 h post transfection revealed that 1012


the most promising knockdown of MMP-1 was achieved using siRNA Target II and Target IV (Figure 5A). siRNA concentrations of 100, 200, and 300 pmol were then used to optimize silencing. We found that using 300 pmol of siRNA reduced MMP-1 in 21D1 cells to levels that were comparable with MDCK cells (Figure 5B). Functionally, the wound healing assay revealed that reduced expression of MMP-1 restricted 21D1 cell migration (Figure 5C). 21D1 cells transfected with the negative control were still able to close the wound entirely after 24 h, while 21D1 cells with reduced MMP-1 expression were only able to close the wound partially. The transwell cell migration assay revealed similar findings as transfection of 21D1 cells with MMP-1 siRNA reduced the number of cells that passed though the insert (Figure 5D). Only approximately one-third of 21D1 cells were able to migrate though the insert toward the lower chamber following knock-down of MMP-1 (Figure 5D). Thus, it is evident from both cell migration assays that reducing MMP-1 expression in 21D1 cells restricts cell mobility, which confirms the notion that elevated levels of MMP-1 during EMT enhances cell movement.

Discussion While proteomics has been employed to shed light on the intracellular mechanisms of EMT,24-26 very little is known about extracellular proteins involved in the cellular process. In this study we have used a subproteome approach targeting the secretome for proteomic analysis to identify proteins secreted from MDCK cells whose levels may be differentially

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Extracellular EMT Remodelling Table 1. Selected Secretome Proteins Dysregulated during Ras-Induced EMT in MDCK Cells accession numbera

Affymetrix identifierb

protein descriptionc

Q4 VYB4 ENSCAFP00000026847 ENSCAFP00000003954 ENSCAFP00000014582 Q867A2 ENSCAFP00000017535 ENSCAFP00000030073 ENSCAFP00000014923 ENSCAFP00000005813 ENSCAFP00000028581 ENSCAFP00000008768 ENSCAFP00000030943 ENSCAFP00000009112 ENSCAFP00000005275 ENSCAFP00000013796 ENSCAFP00000029402 ENSCAFP00000011264 ENSCAFP00000016115 ENSCAFP00000014094 ENSCAFP00000001531

CfaAffx.10944.1.S1_at CfaAffx.27826.1.S1_s_at CfaAffx.4939.1.S1_s_at Cfa.3470.1.S1_s_at Cfa.135.1.S1_at CfaAffx.18514.1.S1_at CfaAffx.31052.1.S1_s_at Cfa.15679.1.A1_at CfaAffx.6792.1.S1_at Cfa.10757.1.S1_s_at CfaAffx.9754.1.S1_s_at CfaAffx.17212.1.S1_s_at CfaAffx.10091.1.S1_s_at CfaAffx.6252.1.S1_s_at CfaAffx.14775.1.S1_at CfaAffx.30396.1.S1_s_at CfaAffx.29528.1.S1_at Cfa.17266.1.S1_s_at CfaAffx.15079.1.S1_s_at CfaAffx.2510.1.S1_at

ENSCAFP00000018639 ENSCAFP00000013392 ENSCAFP00000013111 P25473 ENSCAFP00000008092 ENSCAFP00000012843 ENSCAFP00000022174 ENSCAFP00000019493 P38486 ENSCAFP00000028575 ENSCAFP00000021860 ENSCAFP00000003380

CfaAffx.19618.1.S1_at Cfa.21600.1.S1_s_at CfaAffx.14090.1.S1_at Cfa.1254.1.S1_s_at CfaAffx.9071.1.S1_s_at CfaAffx.13822.1.S1_s_at CfaAffx.23153.1.S1_at CfaAffx.20472.1.S1_s_at CfaAffx.22164.1.S1_s_at CfaAffx.29554.1.S1_s_at Cfa.496.1.A1_s_at CfaAffx.4359.1.S1_s_at

ENSCAFP00000025819 ENSCAFP00000009565 ENSCAFP00000008777 Q9TTY1 ENSCAFP00000014115 ENSCAFP00000011583 ENSCAFP00000025652 ENSCAFP00000008880 ENSCAFP00000012448

CfaAffx.26798.1.S1_at CfaAffx.10544.1.S1_s_at Cfa.18785.1.S1_s_at Cfa.3497.1.A1_s_at CfaAffx.15117.1.S1_s_at CfaAffx.12560.1.S1_s_at Cfa.18809.1.S1_at CfaAffx.9859.1.S1_s_at CfaAffx.13441.1.S1_s_at

ENSCAFP00000009513 ENSCAFP00000004287 ENSCAFP00000010704 ENSCAFP00000021176 ENSCAFP00000011722 ENSCAFP00000016449 Q29393 ENSCAFP00000001209 ENSCAFP00000022333 ENSCAFP00000001150 ENSCAFP00000000926

CfaAffx.10489.1.S1_s_at Cfa.6089.1.A1_s_at CfaAffx.11683.1.S1_s_at Cfa.3707.2.S1_at CfaAffx.12701.1.S1_s_at CfaAffx.17428.1.S1_at Cfa.3762.1.A1_s_at CfaAffx.2188.1.S1_at Cfa.3680.1.S1_s_at Cfa.6009.2.A1_at CfaAffx.1905.1.S1_at

ENSCAFP00000005199 ENSCAFP00000020876 ENSCAFP00000029982 ENSCAFP00000021146 ENSCAFP00000000260 ENSCAFP00000017697 ENSCAFP00000010340

CfaAffx.6176.1.S1_s_at CfaAffx.21858.1.S1_s_at CfaAffx.30961.1.S1_at Cfa.15078.1.S1_s_at CfaAffx.1239.1.S1_s_at CfaAffx.18675.1.S1_s_at Cfa.858.1.A1_s_at

ENSCAFP00000017536 ENSCAFP00000017530

Cfa.18100.1.S1_s_at Cfa.21156.1.S1_at

Serine protease inhibitor Kazal-type 5 Laminin subunit alpha-3 precursor Collagen alpha-1(XII) chain precursor Matrix metalloproteinase-9 precursor (MMP-9) Laminin-5 gamma 2 Laminin beta 3 Protein CYR61 precursor Probable carboxypeptidase PM20D1 precursor Fibroblast growth factor 21 precursor (FGF-21) Interferon-induced 17 K protein precursor Latent transforming growth factor binding protein-1 Tubulointerstitial nephritis antigen-like precursor Collagen type IV alpha 2 chain Inhibin beta A chain precursor Kunitz-type protease inhibitor 1 precursor Collagen alpha-1(V) chain precursor Brain-specific serine protease 4 precursor Nephronectin precursor Chitinase domain-containing protein 1 precursor Transforming growth factor-beta-induced protein ig-h3 precursor Laminin subunit alpha-5 Stanniocalcin-1 precursor Lipopolysaccharide-binding protein precursor (LBP) Clusterin Ribonuclease 4 precursor Thrombospondin-1 precursor Matrix metalloproteinase-13 Laminin subunit gamma-1 precursor Galectin-3 Agrin precursor Collagen alpha-2(V) chain precursor Insulin-like growth factor-binding protein 7 precursor Sushi repeat-containing protein SRPX2 precursor Semaphorin-3C precursor Protein disulfide-isomerase precursor Metalloproteinase inhibitor 2 (TIMP-2) Bone morphogenetic protein 1 precursor (BMP-1) Plasma protease C1 inhibitor precursor Retinoid-inducible serine carboxypeptidase precursor Biotinidase precursor EGF-like repeat and discoidin I-like domain-containing protein 3 Attractin precursor Kallikrein-7 Gamma-glutamyl hydrolase precursor Fibronectin Procollagen C-endopeptidase enhancer 2 precursor Protein FAM20C precursor Decorin Ribonuclease T2 precursor Metalloproteinase inhibitor 1 precursor (TIMP-1) Fibulin-1 precursor Collagen triple helix repeat-containing protein 1 precursor Pappalysin-1 precursor Granulins precursor Olfactomedin-like protein 2A precursor Procollagen C-endopeptidase enhancer 1 precursor Connective tissue growth factor precursor Extracellular matrix protein 1 precursor Platelet-derived growth factor receptor-like protein precursor Collagen alpha-2(VI) chain precursor Collagen alpha-1(VI) chain precursor

spectral count ratio (RSC)d

microarray fold changee

-6.2 -5.7 -5.5 -5.5 -5.0 -4.3 -3.8 -3.5 -3.4 -3.4 -3.1 -3.1 -3.0 -3.0 -3.0 -2.9 -2.6 -2.6 -2.5 -2.5

-78.8 -3.5 -34.3 -7.5 -2.5 -7.0 0.0 0.0 -14.9 -18.4 0.0 -55.7 -27.9 -5.3 -22.6 0.0 -19.7 -168.9 0.0 -13.9

-2.4 -2.4 -2.3 -2.1 -2.0 -1.7 -1.6 -1.6 -1.5 -1.5 0.7 1.2

-7.5 -14.9 -64.0 0.0 -8.6 -4.3 -10.6 -1.5 0.0 -11.3 1.9 1.7

1.3 1.4 1.4 1.6 2.5 2.5 2.6 2.6 2.7

1.5 -1.9 -39.4 2.1 -19.7 2.0 0.0 0.0 1.6

2.8 2.9 2.9 3.0 3.1 3.2 3.2 3.3 3.5 3.6 3.7

0.0 19.7 1.7 4.9 6.5 -4.6 10.6 0.0 29.9 8.6 73.5

4.0 4.0 4.1 4.2 4.3 4.3 4.4

0.0 -9.8 0.0 97.0 104.0 5.3 64.0

4.6 4.8

0.0 0.0

Journal of Proteome Research • Vol. 9, No. 2, 2010 1013

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Mathias et al.

Table 1. Continued accession numbera

Affymetrix identifierb

protein descriptionc

ENSCAFP00000023923 ENSCAFP00000026348

CfaAffx.24902.1.S1_s_at CfaAffx.27328.1.S1_s_at

ENSCAFP00000033419 ENSCAFP00000004327

CfaAffx.5267.1.S1_s_at CfaAffx.5306.1.S1_s_at

ENSCAFP00000022188 ENSCAFP00000027152 ENSCAFP00000030617

CfaAffx.23166.1.S1_at CfaAffx.28131.1.S1_at Cfa.3709.1.S1_s_at

O02678 O46392

Cfa.3763.1.S2_at Cfa.1262.1.S1_s_at

Glia-derived nexin precursor SPARC precursor (Secreted protein acidic and rich in cysteine) Kallikrein-6 precursor EGF-containing fibulin-like extracellular matrix protein 1 precursor Matrix metalloproteinase-1 (MMP-1) Endothelial cell-specific molecule 1 precursor Platelet-activating factor acetylhydrolase precursor Biglycan Collagen alpha-2(I) chain

spectral count ratio (RSC)d

microarray fold changee

5.2 5.4

18.4 18.4

5.5 5.7

13.0 207.9

5.7 6.2 6.4

8780.0 32.0 9.8

6.4 7.4

2.5 4096.0

a Protein accession numbers obtained from the Ensembl database (http://www.ensembl.org/index.html). b Affymetrix identifiers obtained from the Ensembl database. c Protein description obtained via the description or orthologue prediction section of Ensembl entry. d Spectral count fold change ratio - the log2 ratio of estimated protein abundance between samples (eq 1 Experimental Procedures). e Microarray fold change differences calculated using Affymetrix GeneChip Operating Software (http://www.affymetrix.com).

Figure 4. Validation of dysregulated EMT effectors revealed during proteomic profiling. A, confocal immuno-fluorescence and western immuno-blotting of secretome samples confirms reduced levels of laminin 5 γ2 during EMT. B, confocal immuno-fluorescence and western immuno-blotting of SPARC in secretome samples reveal up-regulated expression following Ras-transformation. Peptographs were generated using the PROTOMAP proteomic platform,89 and adapted. Dashed lines indicate calculated protein molecular weight. Green represents the MDCK secretome and red the 21D1 secretome.

expressed as a consequence of Ras-induced EMT. Of the 777 proteins identified, we restricted our analysis to known secreted proteins that were significantly dysregulated (P-value less than 0.05, Table 1), and focused on those that had concordant protein and transcript regulation during EMT. Global examination of secretome profiling data revealed that MDCK cells undergoing EMT: (i) reduce expression of basement membrane (BM) constituents, (ii) selectively increase production of proteases, and (iii) elevate secretion of a defined subset of ECM proteins. In a biological sense, these alterations may work in tandem to enable greater cell mobility, create a passage for cell movement, and direct cell migration during EMT. Basement Membrane Structural Components Are Diminished during EMT. The BM, comprising laminin, collagen type IV, nidogen/entactin, and heparin sulfate proteoglycans,48 is a specialized extracellular structure responsible for providing 1014


mechanical stability to cells and tissues.49 As laminin and collagen type IV regulate cell adhesion and restrict cell mobility,50,51 their diminished expression during EMT is a key feature of our proteomic study. The collagen family of proteins are represented by characteristic right-handed triple helices composed of three R-chains, and collagen type IV is predominantly composed of two R1 chains and one R2 chain.52 The latter was found to be downregulated with an RSC of -3 and a 28 fold reduction in mRNA transcript levels during MDCK EMT. Cross-linking and helical domain interactions are critical in forming a stable collagen type IV network,53 and loss of expression and/or mutations in the R chains hamper triple helix formation, and can result in premature death during development.52 Given that cells anchor directly to BM collagen type IV via integrin R1β1 receptor binding, its deficiency during EMT progression may lead to


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Figure 5. Transient RNA silencing of MMP-1 reduces 21D1 cell migration. (A) Western immuno-blotting analysis shows Target II to be the most effective siRNA construct in knocking-down MMP-1 expression in 21D1 cell lysates. (B) siRNA Target II (300 pmol) was required to reduce MMP-1 expression to levels comparable with that of MDCK cells. (C) Wound healing assay reveals that 21D1 cell migration is attenuated following transfection with 300 pmol MMP-1 siRNA. (D) Transwell migration assay reveals that cell migration is reduced in 21D1 cells transfected with MMP-1 siRNA. NC, negative control. Bar graphs show mean + S.D.

fundamental changes in cellular architecture due to the lack of specific cell adhesion sites.54 Laminins are a family of BM glycoproteins whose heterotrimeric structure is composed of R, β, and γ polypeptide subunits.55 They control cell attachment to the ECM, and regulate differentiation, proliferation, and cell death.49 Our secretome analysis of EMT revealed the down-regulation of R3, -β3, and -γ2 chains (Table 1), that together comprise laminin 5.56 The down-regulation of the γ2 chain was further confirmed by immuno-fluorescence and western immuno-blotting (Figure 4B). Laminin 5 is highly adhesive, providing mechanical stability and protecting against cell invasion via interactions with integrin R3β1, R6β1, and R6β4.57,58 Thus, its downregulation during EMT may compromise BM architecture. Interestingly, under certain circumstances, proteolytic processing of the γ2 chain of laminin 5 by membrane-type MMP1, and to a lesser extent MMP-2, releases a fragment that triggers cell migration.59-61 A 105 K fragment from the γ2 chain is reported to have biological activity,62 however no laminin 5 peptides were identified in the entire 21D1 secretome. Nonetheless, given the significant protease dysregulation observed in this study, it is tempting to speculate that proteolytic fragments of this nature are generated during EMT and promote cell migration. Presumably, decreased levels of major BM constituents following Ras-transformation impede the structural integrity of the entire BM. Moreover, absence of key BM components or disruption via proteolytic degradation may permit greater cell mobility during EMT. Ras-Transformed MDCK Cells Exhibit Dysregulated Levels of Secreted Proteases and Inhibitors. Despite MMP-9 and MMP-13 being previously reported to be up-regulated in MDCK cells undergoing EMT,63,64 both MMPs were found to be downregulated in our secretome study as well as at the mRNA level (Table 1). The initiating EMT stimuli in these previously published studies were HGF63 and Snail,64 which suggests the stimulus driving the EMT may dictate the effectors that are employed to mediate the cellular process. Moreover, activation

of the MAPK pathway has been shown to increase expression of MMP-9 and MMP-13,65,66 but as Ras has several downstream effectors, the divergent observations reported in this study could result from activation of other pathways by oncogenic Ras, for example the PI3K/AKT pathway. Consistent with our previous DIGE study,33 MMP-1 and the serine protease kallikrein 6 were found to be up-regulated in this study with RSC values of 5.7, and 5.5, respectively. As the kallikrein family emerge as important mediators of EMT in prostate cancer,67 mRNA transcript profiling in our study revealed a 7.5 fold up-regulation of kallikrein 4 (data not shown). Kallikrein 4 alone is sufficient to induce an EMT phenotype in prostate cancer cells that includes reduced E-cadherin expression, changes toward a spindle-shaped morphology, increased vimentin expression, and elevated cell migration.68 While we did not identify the kallikrein 4 protein during secretome analysis, we did observe the up-regulation of kallikrein 7 (RSC of 2.9). Interestingly, the most downregulated protein identified during EMT was SPINK5, which is negative regulator (inhibitor) of kallikrein 6.69 SPINK5 is a 125 K secretory serine protease inhibitor that is cleaved by proprotein convertases such as furin to yield several independently working inhibitory domains.70 SPINK5 peptides were identified primarily from 10 gel bands in the MDCK secretome, corresponding to relative molecular weights between 20 and 90 K, while not a single peptide was observed in the entire 21D1 secretome (Figure 3B). Loss of SPINK5 expression may perturb the regulation of kallikrein 6, and most likely also kallikrein 7, thus leading to enhanced protease activity. This in turn could have two effects during EMT: (i) create a passage for migrating cells to move into, and (ii) generate functionally distinct protein fragments with biological activity. The precise roles of proteases during EMT remain to be elucidated. Ras-Induced EMT Amplifies Production and Secretion of ECM Constituents. Recognized as extracellular modulators of cell function, matricellular proteins are defined as secreted molecules that do not primarily serve structural roles, but rather Journal of Proteome Research • Vol. 9, No. 2, 2010 1015

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Mathias et al. levels observed in this study could be due to increased SPARC expression as it is a positive regulator.82

Figure 6. Proposed hierarchical regulation of extracellular effectors during Ras-induced EMT in MDCK cells. Extracellular modulators coordinate a biological response following Ras-transformation. Elevated protease levels detected in the 21D1 secretome (MMP-1, kallikrein 6) may enhance EMT via degradation of the basement membrane that normally restricts cell mobility, and/ or by generating bioactive fragments that stimulate migration and invasion. Concurrently, production and secretion of ECM that have implications in motility (biglycan, decorin, fibronectin, SPARC) could provide directional cues for cell movement. Substrate accumulation is potentially propagated via downregulation of MMP-9 and MMP-13, while inhibitor dysregulation (SPINK5, TIMP-1) might further impair protease activity. Proteins with up-regulated expression are indicated by v and downregulated by V, while ¬ represents an inhibitory effect on a protease, and f represents known protease action on an ECM target.

mediate interactions between cell surface receptors, growth factors, proteases, and other components of the ECM.71 This interesting class of molecules has not been described in the context of EMT, but a striking feature of our secretome analysis is that several of them are differentially expressed following Ras-transformation. The proteotypic matricellular protein SPARC72 was upregulated with an RSC of 5.4 at the protein level, and by 18.4 fold in mRNA transcript expression during EMT. Its elevated expression in the 21D1 secretome compared to the MDCK secretome was further confirmed via immuno-fluorescence and western immuno-blotting (Figure 4A). SPARCs involvement in EMT has been reported in the context of tumor progression, where microarray profiling of melanoma and breast cancers revealed its up-regulation in tumor samples displaying an EMT phenotype.73,74 SPARC is a multifunctional protein that may play many diverse roles during EMT as it contains an Nterminal domain that binds hydroxyapatite and calcium, a follistatin-like domain that stabilizes two weakly interacting modules, and a C-terminal domain that binds calcium and contains structural similarity to the Kazal family of serine proteases.75 Additionally, SPARC peptides generated by protease cleavage can modulate cell shape, control cell proliferation, and stimulate cell migration.75 Its antiadhesive description might result from directly interfering with the binding of cellsurface integrins to components of the ECM.72 Moreover, its common appearance during metastasis has led some to believe that it may fulfill several aspects of Pagets “seed and soil” hypothesis,76,77 whereby it facilitates tumor cell, stromal cell, and ECM interactions.78,79 While the contribution of SPARC during EMT remains largely unknown, it was recently shown to decrease E-cadherin expression, increase vimentin expression, and induce TGFβ secretion.80,81 In addition, elevated collagen alpha-2(I) protein (RSC of 7.4) and transcript (4096 fold) 1016


Fibulins represent another family of matricellular proteins that were found to be up-regulated following Ras-induced EMT, with EGF-containing fibulin-like extracellular matrix protein 1 (fibulin 3) and fibulin 1 having RSC ratios of 5.7 and 3.6, respectively. Such findings are of interest as fibulins are not typically expressed in epithelial cells, but readily in mesenchymal and stromal cells.83,84 Fibulins act as molecular bridges to mediate interactions between ECM molecules such as aggrecan and versican,85 as well as regulate certain cell signaling events.84 Differential expression of fibulin -1 and -3 is novel in the context of EMT, although dysregulated levels of fibulin 1 have been linked to cancer progression.85 Interestingly, a recent study described the induction of fibulin 5 during EMT.86 Fibulin 5 initiates and enhances EMT via stimulating MMP-2 and -9 proteolytic activity, and Twist expression leading to reduced E-cadherin expression. In light of these findings, it is possible that fibulin -1 and/or -3 have similar effects in our MDCK model of EMT. Inspection of the differentially expressed secretome proteins in Table 1 reveal up-regulation of the leucine-rich proteoglycans biglycan (RSC of 6.4) and decorin (RSC of 3.2) following Rastransformation. Although widely distributed in connective tissue, this is the first report of significant extracellular dysregulation of biglycan and decorin in the context of EMT. Interestingly, these proteins have been reported to induce properties in lung fibroblasts similar to those observed during EMT such as formation of long protruding filamentous processes, altered stress fiber formation, and increased cell migration.87 Secretome-based proteomic profiling has revealed that biglycan and decorin along with SPARC and fibulin -1 and -3 are dysregulated during EMT, however their precise contributions are yet to be determined. Nonetheless, the ability of matricellular proteins to organize the ECM, stimulate expression of other ECM constituents, and induce MMP synthesis,88 highlights them as an important subset of extracellular EMT effectors. Undoubtedly, further elucidation of this class of proteins in the future will provide novel insights into the mechanisms associated with extracellular remodelling during EMT. Hierarchical Regulation of Extracellular Effectors May Potentiate 21D1 Cell Motility. Our integrated proteomic and transcriptomic analyses have revealed the extracellular constituents whose regulation is perturbed following oncogenic Ras-induced EMT. To understand how these molecules might unite to mediate a dynamic biological response, we have modeled our findings on known inhibitor-protease-substrate interactions using the MEROPS database (http://merops.sanger. ac.uk/) and the literature. Interestingly, ECM substrates of down-regulated MMP -9, and -13 were up-regulated, that is, biglycan, decorin, fibronectin, and SPARC, while the protease inhibitor TIMP-1 also had increased expression during EMT (Figure 6). Conversely, the substrates and inhibitors, that is, laminin 5 and SPINK5, of up-regulated kallikrein 6, were downregulated themselves following Ras-transformation. We propose that a higher order level of control above transcriptional reprogramming, is operational during EMT, and that this hierarchical regulation allows a defined subset of extracellular effectors to accumulate to perform biological functions. By these means, elevated proteases may abolish structural BM constraints and create a passage for cells to move into, while

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Extracellular EMT Remodelling motile cells themselves secrete new ECM that promote and direct cell migration. Given that proteases are central to this hypothesis, and the findings from this study are consistent with our previous DIGE study,33 MMP-1 was targeted for further functional studies using siRNA technology. Despite some cells still migrating into the wounded area, the migration of 21D1 cells was generally impaired following transient MMP-1 knockdown (Figure 5C). Given that 21D1 cells had a transfection efficiency of 75% (Supporting Information Figure S2), cells displaying motility could be derived from the 25% that were not transfected. In addition, it is also reasonable to predict that other extracellular modulators up-regulated during EMT continue to stimulate and promote cell movement (in the presence of reduced MMP-1), resulting in attenuated and not abolished 21D1 cell migration. Thus combination-type siRNA silencing may have additive effects on reducing cell motility. siRNA silencing of other targets is currently being performed to ascertain whether migration may be further attenuated during EMT.

Concluding Remarks As the extracellular microenvironment governs cell-cell and cell-matrix interactions, it can ultimately control EMT progression or regression. On the basis of our global secretome analysis of EMT, we propose that extracellular remodelling events drive EMT and facilitate cell motility. MDCK cells undergoing Rasinduced EMT may initially disengage from the restrictive basement membrane via the down-regulation of collagen type IV and laminin 5. Concurrently, increased expression of key proteases (MMP-1 and kallikrein -6 and -7) might create a passage for cell movement and potentially generate proteolytic fragments that stimulate cell migration. At the same time, elevated secretion of a defined subset of ECM constituents (SPARC, collagen type I, fibulin -1 and -3, biglycan, and decorin) possibly provides the motile cells with new directional cues and sites for attachment. We suspect that the regulation of these extracellular effectors may be hierarchically coordinated, and MMP-1 is an important mediator of 21D1 cell motility as siRNA knockdown attenuated cell migration. We are currently performing further functional studies to other EMT modulators. Abbreviations: EMT, epithelial-mesenchymal transition; ECM, extracellular matrix; MDCK, Madin-Darby canine kidney; 21D1, Ras-transformed MDCK cells; TGFβ, transforming growth factor beta; MMP, matrix metalloproteinase; DMEM, Dulbecco’s modified Eagle’s medium; CM, culture medium; SPINK5, serine protease inhibitor Kazal-type 5; TIMP-1, tissue inhibitor of metalloproteinase 1; SPARC, secreted protein acidic and rich in cysteine; CTGF, connective tissue growth factor; GCOS, GeneChip operating software; TF, transcription factor; LDH, lactate dehydrogenase; RSC, spectral count fold change ratio.

Acknowledgment. This work was supported by the National Health & Medical Research Council of Australia for program grant #487922 (R.J.S.), grants #280913 and #433619 (H.-J.Z.), and The University of Melbourne Research Scholarship (R.A.M.). Analysis of proteomic data described in this work was supported using the Australian Proteomics Computational Facility funded by the National Health & Medical Research Council of Australia grant #381413. We also thank Martin O’Hely for assistance with statistical analysis and Gabriel Simon for modifying the PROTOMAP proteomic platform for this study.

Supporting Information Available: All peptides and proteins identified during proteomic profiling as well as detailed microarray probe expression data. This material is available free of charge via the Internet at http://pubs.acs.org. References (1) Baum, B.; Settleman, J.; Quinlan, M. P. Transitions between epithelial and mesenchymal states in development and disease. Semin. Cell Dev. Biol. 2008, 19 (3), 294–308. (2) Thiery, J. P. Epithelial-mesenchymal transitions in tumour progression. Nat. Rev. Cancer 2002, 2 (6), 442–454. (3) Berx, G.; Raspe, E.; Christofori, G.; Thiery, J. P.; Sleeman, J. P. PreEMTing metastasis? Recapitulation of morphogenetic processes in cancer. Clin. Exp. Metastasis 2007, 24 (8), 587–597. (4) Radisky, D. C. Epithelial-mesenchymal transition. J. Cell Sci. 2005, 118 (Pt 19), 4325–4326. (5) Thiery, J. P. Epithelial-mesenchymal transitions in development and pathologies. Curr. Opin. Cell Biol. 2003, 15 (6), 740–746. (6) Thiery, J. P.; Sleeman, J. P. Complex networks orchestrate epithelial-mesenchymal transitions. Nat. Rev. Mol. Cell Biol. 2006, 7 (2), 131–142. (7) Thompson, E. W.; Newgreen, D. F.; Tarin, D. Carcinoma invasion and metastasis: a role for epithelial-mesenchymal transition. Cancer Res. 2005, 65 (14), 5991–5995. (8) Yang, J.; Weinberg, R. A. Epithelial-mesenchymal transition: at the crossroads of development and tumor metastasis. Dev. Cell 2008, 14 (6), 818–829. (9) Behrens, J.; Mareel, M. M.; Van Roy, F. M.; Birchmeier, W. Dissecting tumor cell invasion: epithelial cells acquire invasive properties after the loss of uvomorulin-mediated cell-cell adhesion. J. Cell Biol. 1989, 108 (6), 2435–2447. (10) Bolos, V.; Peinado, H.; Perez-Moreno, M. A.; Fraga, M. F.; Esteller, M.; Cano, A. The transcription factor Slug represses E-cadherin expression and induces epithelial to mesenchymal transitions: a comparison with Snail and E47 repressors. J. Cell Sci. 2003, 116 (Pt 3), 499–511. (11) Kang, Y.; Massague, J. Epithelial-mesenchymal transitions: twist in development and metastasis. Cell 2004, 118 (3), 277–279. (12) Wu, Y.; Zhou, B. P. New insights of epithelial-mesenchymal transition in cancer metastasis. Acta Biochim. Biophys. Sin. 2008, 40 (7), 643–650. (13) De Wever, O.; Pauwels, P.; De Craene, B.; Sabbah, M.; Emami, S.; Redeuilh, G.; Gespach, C.; Bracke, M.; Berx, G. Molecular and pathological signatures of epithelial-mesenchymal transitions at the cancer invasion front. Histochem. Cell Biol. 2008, 130 (3), 481– 494. (14) Gavert, N.; Ben-Ze’ev, A. Epithelial-mesenchymal transition and the invasive potential of tumors. Trends Mol. Med. 2008, 14 (5), 199–209. (15) Lee, J. M.; Dedhar, S.; Kalluri, R.; Thompson, E. W. The epithelialmesenchymal transition: new insights in signaling, development, and disease. J. Cell Biol. 2006, 172 (7), 973–981. (16) Simpson, R. J.; Dorow, D. S. Cancer proteomics: from signaling networks to tumor markers. Trends Biotechnol. 2001, 19 (10 Suppl), S40–48. (17) Cai, Z.; Zhou, Y.; Lei, T.; Chiu, J. F.; He, Q. Y. Mammary serine protease inhibitor inhibits epithelial growth factor-induced epithelial-mesenchymal transition of esophageal carcinoma cells. Cancer 2009, 115 (1), 36–48. (18) Moreira, J. M.; Gromov, P.; Celis, J. E. Expression of the tumor suppressor protein 14-3-3 sigma is down-regulated in invasive transitional cell carcinomas of the urinary bladder undergoing epithelial-to-mesenchymal transition. Mol. Cell. Proteomics 2004, 3 (4), 410–419. (19) Qi, Y. J.; He, Q. Y.; Ma, Y. F.; Du, Y. W.; Liu, G. C.; Li, Y. J.; Tsao, G. S.; Ngai, S. M.; Chiu, J. F. Proteomic identification of malignant transformation-related proteins in esophageal squamous cell carcinoma. J. Cell. Biochem. 2008, 104 (5), 1625–1635. (20) Wei, J.; Xu, G.; Wu, M.; Zhang, Y.; Li, Q.; Liu, P.; Zhu, T.; Song, A.; Zhao, L.; Han, Z.; Chen, G.; Wang, S.; Meng, L.; Zhou, J.; Lu, Y.; Ma, D. Overexpression of vimentin contributes to prostate cancer invasion and metastasis via src regulation. Anticancer Res. 2008, 28 (1A), 327–334. (21) Willipinski-Stapelfeldt, B.; Riethdorf, S.; Assmann, V.; Woelfle, U.; Rau, T.; Sauter, G.; Heukeshoven, J.; Pantel, K. Changes in cytoskeletal protein composition indicative of an epithelialmesenchymal transition in human micrometastatic and primary breast carcinoma cells. Clin. Cancer Res. 2005, 11 (22), 8006–8014. (22) Zhou, C.; Nitschke, A. M.; Xiong, W.; Zhang, Q.; Tang, Y.; Bloch, M.; Elliott, S.; Zhu, Y.; Bazzone, L.; Yu, D.; Weldon, C. B.; Schiff,


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(41)

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R.; McLachlan, J. A.; Beckman, B. S.; Wiese, T. E.; Nephew, K. P.; Shan, B.; Burow, M. E.; Wang, G. Proteomic analysis of tumor necrosis factor-alpha resistant human breast cancer cells reveals a MEK5/Erk5-mediated epithelial-mesenchymal transition phenotype. Breast Cancer Res. 2008, 10 (6), R105. Mathias, R. A.; Simpson, R. J. Towards understanding epithelialmesenchymal transition: A proteomics perspective. Biochim. Biophys. Acta 2009, 1794 (9), 1325–1331. Keshamouni, V. G.; Jagtap, P.; Michailidis, G.; Strahler, J. R.; Kuick, R.; Reka, A. K.; Papoulias, P.; Krishnapuram, R.; Srirangam, A.; Standiford, T. J.; Andrews, P. C.; Omenn, G. S. Temporal Quantitative Proteomics by iTRAQ 2D-LC-MS/MS and Corresponding mRNA Expression Analysis Identify Post-Transcriptional Modulation of Actin-Cytoskeleton Regulators During TGF-beta-Induced Epithelial-Mesenchymal Transition. J. Proteome Res. 2009, 8 (1), 35–47. Keshamouni, V. G.; Michailidis, G.; Grasso, C. S.; Anthwal, S.; Strahler, J. R.; Walker, A.; Arenberg, D. A.; Reddy, R. C.; Akulapalli, S.; Thannickal, V. J.; Standiford, T. J.; Andrews, P. C.; Omenn, G. S. Differential protein expression profiling by iTRAQ-2DLC-MS/MS of lung cancer cells undergoing epithelial-mesenchymal transition reveals a migratory/invasive phenotype. J. Proteome Res. 2006, 5 (5), 1143–1154. Hill, J. J.; Tremblay, T. L.; Cantin, C.; O’Connor-McCourt, M.; Kelly, J. F.; Lenferink, A. E. Glycoproteomic analysis of two mouse mammary cell lines during transforming growth factor (TGF)-beta induced epithelial to mesenchymal transition. Proteome Sci. 2009, 7 (1), 2. Wu, L.; Han, D. K. Overcoming the dynamic range problem in mass spectrometry-based shotgun proteomics. Expert Rev. Proteomics 2006, 3 (6), 611–619. Mathias, R. A.; Lim, J. W.; Ji, H.; Simpson, R. J. Isolation of extracellular membranous vesicles for proteomic analysis. Methods Mol. Biol. 2009, 528, 227–242. Simpson, R. J.; Jensen, S. S.; Lim, J. W. Proteomic profiling of exosomes: current perspectives. Proteomics 2008, 8 (19), 4083– 4099. Chevallet, M.; Diemer, H.; Van Dorssealer, A.; Villiers, C.; Rabilloud, T. Toward a better analysis of secreted proteins: the example of the myeloid cells secretome. Proteomics 2007, 7 (11), 1757–1770. Chen, S. T.; Pan, T. L.; Juan, H. F.; Chen, T. Y.; Lin, Y. S.; Huang, C. M. Breast tumor microenvironment: proteomics highlights the treatments targeting secretome. J. Proteome Res. 2008, 7 (4), 1379– 1387. Xue, H.; Lu, B.; Lai, M. The cancer secretome: a reservoir of biomarkers. J. Transl. Med. 2008, 6, 52. Mathias, R. A.; Wang, B.; Ji, H.; Kapp, E. A.; Moritz, R. L.; Zhu, H. J.; Simpson, R. J. Secretome-Based Proteomic Profiling of RasTransformed MDCK Cells Reveals Extracellular Modulators of Epithelial-Mesenchymal Transition. J. Proteome Res. 2009, 8 (6), 2827–2837. Hu, Q.; Noll, R. J.; Li, H.; Makarov, A.; Hardman, M.; Graham Cooks, R. The Orbitrap: a new mass spectrometer. J. Mass Spectrom. 2005, 40 (4), 430–443. Perry, R. H.; Cooks, R. G.; Noll, R. J. Orbitrap mass spectrometry: instrumentation, ion motion and applications. Mass Spectrom. Rev. 2008, 27 (6), 661–699. Simpson, R. J.; Connolly, L. M.; Eddes, J. S.; Pereira, J. J.; Moritz, R. L.; Reid, G. E. Proteomic analysis of the human colon carcinoma cell line (LIM 1215): development of a membrane protein database. Electrophoresis 2000, 21 (9), 1707–1732. Liu, H.; Sadygov, R. G.; Yates, J. R. 3rd, A model for random sampling and estimation of relative protein abundance in shotgun proteomics. Anal. Chem. 2004, 76 (14), 4193–4201. Madin, S. H.; Andriese, P. C.; Darby, N. B. The in vitro cultivation of tissues of domestic and laboratory animals. Am. J. Vet. Res. 1957, 18 (69), 932–941. Cano, A.; Perez-Moreno, M. A.; Rodrigo, I.; Locascio, A.; Blanco, M. J.; del Barrio, M. G.; Portillo, F.; Nieto, M. A. The transcription factor snail controls epithelial-mesenchymal transitions by repressing E-cadherin expression. Nat. Cell Biol. 2000, 2 (2), 76–83. Legrand, C.; Bour, J. M.; Jacob, C.; Capiaumont, J.; Martial, A.; Marc, A.; Wudtke, M.; Kretzmer, G.; Demangel, C.; Duval, D.; et al. Lactate dehydrogenase (LDH) activity of the cultured eukaryotic cells as marker of the number of dead cells in the medium. J. Biotechnol. 1992, 25 (3), 231–243. Olsen, J. V.; de Godoy, L. M.; Li, G.; Macek, B.; Mortensen, P.; Pesch, R.; Makarov, A.; Lange, O.; Horning, S.; Mann, M. Parts per million mass accuracy on an Orbitrap mass spectrometer via lock mass injection into a C-trap. Mol. Cell. Proteomics 2005, 4 (12), 2010– 2021.


Mathias et al. (42) Greening, D. W.; Glenister, K. M.; Kapp, E. A.; Moritz, R. L.; Sparrow, R. L.; Lynch, G. W.; Simpson, R. J. Comparison of human platelet-membrane cytoskeletal proteins with the plasma proteome: Towards understanding the platelet-plasma nexus. Proteom. Clin. Appl. 2008, 2, 63–77. (43) Kapp, E. A.; Schutz, F.; Connolly, L. M.; Chakel, J. A.; Meza, J. E.; Miller, C. A.; Fenyo, D.; Eng, J. K.; Adkins, J. N.; Omenn, G. S.; Simpson, R. J. An evaluation, comparison, and accurate benchmarking of several publicly available MS/MS search algorithms: sensitivity and specificity analysis. Proteomics 2005, 5 (13), 3475– 3490. (44) Beissbarth, T.; Hyde, L.; Smyth, G. K.; Job, C.; Boon, W. M.; Tan, S. S.; Scott, H. S.; Speed, T. P. Statistical modeling of sequencing errors in SAGE libraries. Bioinformatics 2004, 20, i31–39. (45) Old, W. M.; Meyer-Arendt, K.; Aveline-Wolf, L.; Pierce, K. G.; Mendoza, A.; Sevinsky, J. R.; Resing, K. A.; Ahn, N. G. Comparison of label-free methods for quantifying human proteins by shotgun proteomics. Mol. Cell. Proteomics 2005, 4 (10), 1487–1502. (46) Benjamini, Y.; Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B: Stat. Methodol. 1995, 57 (1), 289–300. (47) Makarov, A.; Denisov, E.; Lange, O.; Horning, S. Dynamic range of mass accuracy in LTQ Orbitrap hybrid mass spectrometer. J. Am. Soc. Mass Spectrom. 2006, 17 (7), 977–982. (48) Nguyen, N. M.; Senior, R. M. Laminin isoforms and lung development: all isoforms are not equal. Dev. Biol. 2006, 294 (2), 271– 279. (49) Paez, M. C.; Gonzalez, M. J.; Serrano, N. C.; Shoenfeld, Y.; Anaya, J. M. Physiological and pathological implications of laminins: from the gene to the protein. Autoimmunity 2007, 40 (2), 83–94. (50) Engbring, J. A.; Kleinman, H. K. The basement membrane matrix in malignancy. J. Pathol. 2003, 200 (4), 465–470. (51) Rowe, R. G.; Weiss, S. J. Breaching the basement membrane: who, when and how. Trends Cell Biol. 2008, 18 (11), 560–574. (52) Gelse, K.; Poschl, E.; Aigner, T. Collagens--structure, function, and biosynthesis. Adv. Drug Delivery Rev. 2003, 55 (12), 1531–1546. (53) Hudson, B. G.; Reeders, S. T.; Tryggvason, K. Type IV collagen: structure, gene organization, and role in human diseases. Molecular basis of Goodpasture and Alport syndromes and diffuse leiomyomatosis. J. Biol. Chem. 1993, 268 (35), 26033–26036. (54) Heino, J. The collagen family members as cell adhesion proteins. Bioessays 2007, 29 (10), 1001–1010. (55) Jones, J. C.; Dehart, G. W.; Gonzales, M.; Goldfinger, L. E. Laminins: an overview. Microsc. Res. Tech. 2000, 51 (3), 211–213. (56) Aumailley, M.; Bruckner-Tuderman, L.; Carter, W. G.; Deutzmann, R.; Edgar, D.; Ekblom, P.; Engel, J.; Engvall, E.; Hohenester, E.; Jones, J. C.; Kleinman, H. K.; Marinkovich, M. P.; Martin, G. R.; Mayer, U.; Meneguzzi, G.; Miner, J. H.; Miyazaki, K.; Patarroyo, M.; Paulsson, M.; Quaranta, V.; Sanes, J. R.; Sasaki, T.; Sekiguchi, K.; Sorokin, L. M.; Talts, J. F.; Tryggvason, K.; Uitto, J.; Virtanen, I.; von der Mark, K.; Wewer, U. M.; Yamada, Y.; Yurchenco, P. D. A simplified laminin nomenclature. Matrix Biol. 2005, 24 (5), 326– 332. (57) Patarroyo, M.; Tryggvason, K.; Virtanen, I. Laminin isoforms in tumor invasion, angiogenesis and metastasis. Semin. Cancer Biol. 2002, 12 (3), 197–207. (58) Aumailley, M.; El Khal, A.; Knoss, N.; Tunggal, L. Laminin 5 processing and its integration into the ECM. Matrix Biol. 2003, 22 (1), 49–54. (59) Koshikawa, N.; Giannelli, G.; Cirulli, V.; Miyazaki, K.; Quaranta, V. Role of cell surface metalloprotease MT1-MMP in epithelial cell migration over laminin-5. J. Cell Biol. 2000, 148 (3), 615–624. (60) Giannelli, G.; Antonaci, S. Biological and clinical relevance of Laminin-5 in cancer. Clin. Exp. Metastasis 2000, 18 (6), 439–443. (61) Quaranta, V. Motility cues in the tumor microenvironment. Differentiation 2002, 70 (9-10), 590–598. (62) Hintermann, E.; Quaranta, V. Epithelial cell motility on laminin5: regulation by matrix assembly, proteolysis, integrins and erbB receptors. Matrix Biol. 2004, 23 (2), 75–85. (63) Hellman, N. E.; Spector, J.; Robinson, J.; Zuo, X.; Saunier, S.; Antignac, C.; Tobias, J. W.; Lipschutz, J. H. Matrix metalloproteinase 13 (MMP13) and tissue inhibitor of matrix metalloproteinase 1 (TIMP1), regulated by the MAPK pathway, are both necessary for Madin-Darby canine kidney tubulogenesis. J. Biol. Chem. 2008, 283 (7), 4272–4282. (64) Jorda, M.; Olmeda, D.; Vinyals, A.; Valero, E.; Cubillo, E.; Llorens, A.; Cano, A.; Fabra, A. Upregulation of MMP-9 in MDCK epithelial cell line in response to expression of the Snail transcription factor. J. Cell Sci. 2005, 118 (Pt 15), 3371–3385. (65) Komatsu, K.; Buchanan, F. G.; Otaka, M.; Jin, M.; Odashima, M.; Horikawa, Y.; Watanabe, S.; Dubois, R. N. Gene expression profiling

research articles


(66)

(67)

(68)

(69)

(70)

(71) (72) (73)

(74)

(75)

following constitutive activation of MEK1 and transformation of rat intestinal epithelial cells. Mol. Cancer 2006, 5, 63. Li, H.; Mittal, A.; Paul, P. K.; Kumar, M.; Srivastava, D. S.; Tyagi, S. C.; Kumar, A. Tumor necrosis factor-related weak inducer of apoptosis augments matrix metalloproteinase 9 (MMP-9) production in skeletal muscle through the activation of nuclear factorkappaB-inducing kinase and p38 mitogen-activated protein kinase: a potential role of MMP-9 in myopathy. J. Biol. Chem. 2009, 284 (7), 4439–4450. Lawrence, M. G.; Veveris-Lowe, T. L.; Whitbread, A. K.; Nicol, D. L.; Clements, J. A. Epithelial-mesenchymal transition in prostate cancer and the potential role of kallikrein serine proteases. Cells Tissues Organs 2007, 185 (1-3), 111–115. Whitbread, A. K.; Veveris-Lowe, T. L.; Lawrence, M. G.; Nicol, D. L.; Clements, J. A. The role of kallikrein-related peptidases in prostate cancer: potential involvement in an epithelial to mesenchymal transition. Biol. Chem. 2006, 387 (6), 707–714. Komatsu, N.; Saijoh, K.; Otsuki, N.; Kishi, T.; Micheal, I. P.; Obiezu, C. V.; Borgono, C. A.; Takehara, K.; Jayakumar, A.; Wu, H. K.; Clayman, G. L.; Diamandis, E. P. Proteolytic processing of human growth hormone by multiple tissue kallikreins and regulation by the serine protease inhibitor Kazal-Type5 (SPINK5) protein. Clin. Chim. Acta 2007, 377 (1-2), 228–236. Mitsudo, K.; Jayakumar, A.; Henderson, Y.; Frederick, M. J.; Kang, Y.; Wang, M.; El-Naggar, A. K.; Clayman, G. L. Inhibition of serine proteinases plasmin, trypsin, subtilisin A, cathepsin G, and elastase by LEKTI: a kinetic analysis. Biochemistry (Mosc.) 2003, 42 (13), 3874–3881. Bornstein, P.; Sage, E. H. Matricellular proteins: extracellular modulators of cell function. Curr. Opin. Cell Biol. 2002, 14 (5), 608–616. Clark, C. J.; Sage, E. H. A prototypic matricellular protein in the tumor microenvironment--where there’s SPARC, there’s fire. J. Cell. Biochem. 2008, 104 (3), 721–732. Alonso, S. R.; Tracey, L.; Ortiz, P.; Perez-Gomez, B.; Palacios, J.; Pollan, M.; Linares, J.; Serrano, S.; Saez-Castillo, A. I.; Sanchez, L.; Pajares, R.; Sanchez-Aguilera, A.; Artiga, M. J.; Piris, M. A.; Rodriguez-Peralto, J. L. A high-throughput study in melanoma identifies epithelial-mesenchymal transition as a major determinant of metastasis. Cancer Res. 2007, 67 (7), 3450–3460. Lien, H. C.; Hsiao, Y. H.; Lin, Y. S.; Yao, Y. T.; Juan, H. F.; Kuo, W. H.; Hung, M. C.; Chang, K. J.; Hsieh, F. J. Molecular signatures of metaplastic carcinoma of the breast by large-scale transcriptional profiling: identification of genes potentially related to epithelial-mesenchymal transition. Oncogene 2007, 26 (57), 7859– 7871. Tai, I. T.; Tang, M. J. SPARC in cancer biology: its role in cancer progression and potential for therapy. Drug Resist. Updates 2008, 11 (6), 231–246.

(76) Fidler, I. J.; Poste, G. The “seed and soil” hypothesis revisited. Lancet Oncol. 2008, 9 (8), 808. (77) Paget, S. The distribution of secondary growths in cancer of the breast. Lancet 1889, 133, 571–573. (78) Fidler, I. J. The pathogenesis of cancer metastasis: the ‘seed and soil’ hypothesis revisited. Nat. Rev. Cancer 2003, 3 (6), 453–458. (79) Framson, P. E.; Sage, E. H. SPARC and tumor growth: where the seed meets the soil. J. Cell. Biochem. 2004, 92 (4), 679–690. (80) Bassuk, J. A.; Pichler, R.; Rothmier, J. D.; Pippen, J.; Gordon, K.; Meek, R. L.; Bradshaw, A. D.; Lombardi, D.; Strandjord, T. P.; Reed, M.; Sage, E. H.; Couser, W. G.; Johnson, R. Induction of TGF-beta1 by the matricellular protein SPARC in a rat model of glomerulonephritis. Kidney Int. 2000, 57 (1), 117–128. (81) Smit, D. J.; Gardiner, B. B.; Sturm, R. A. Osteonectin downregulates E-cadherin, induces osteopontin and focal adhesion kinase activity stimulating an invasive melanoma phenotype. Int. J. Cancer 2007, 121 (12), 2653–2660. (82) Zhou, X.; Tan, F. K.; Guo, X.; Arnett, F. C. Attenuation of collagen production with small interfering RNA of SPARC in cultured fibroblasts from the skin of patients with scleroderma. Arthritis Rheum. 2006, 54 (8), 2626–2631. (83) Chu, M. L.; Tsuda, T. Fibulins in development and heritable disease. Birth Defects Res. Part C: Embryo Today 2004, 72 (1), 25– 36. (84) Argraves, W. S.; Greene, L. M.; Cooley, M. A.; Gallagher, W. M. Fibulins: physiological and disease perspectives. EMBO Rep. 2003, 4 (12), 1127–1131. (85) Gallagher, W. M.; Currid, C. A.; Whelan, L. C. Fibulins and cancer: friend or foe. Trends Mol. Med. 2005, 11 (7), 336–340. (86) Lee, Y. H.; Albig, A. R.; Regner, M.; Schiemann, B. J.; Schiemann, W. P. Fibulin-5 initiates epithelial-mesenchymal transition (EMT) and enhances EMT induced by TGF-beta in mammary epithelial cells via a MMP-dependent mechanism. Carcinogenesis 2008, 29 (12), 2243–2251. (87) Tufvesson, E.; Westergren-Thorsson, G. Biglycan and decorin induce morphological and cytoskeletal changes involving signalling by the small GTPases RhoA and Rac1 resulting in lung fibroblast migration. J. Cell Sci. 2003, 116 (Pt 23), 4857–4864. (88) Kinsella, M. G.; Bressler, S. L.; Wight, T. N. The regulated synthesis of versican, decorin, and biglycan: extracellular matrix proteoglycans that influence cellular phenotype. Crit. Rev. Eukaryot. Gene Expr. 2004, 14 (3), 203–234. (89) Dix, M. M.; Simon, G. M.; Cravatt, B. F. Global mapping of the topography and magnitude of proteolytic events in apoptosis. Cell 2008, 134 (4), 679–691.

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