TIMP-1 Increases Expression and Phosphorylation ... - ACS Publications

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TIMP‑1 Increases Expression and Phosphorylation of Proteins Associated with Drug Resistance in Breast Cancer Cells Omid Hekmat,§,# Stephanie Munk,§,# Louise Fogh,†,‡,# Rachita Yadav,‡,∥ Chiara Francavilla,§ Heiko Horn,§ Sidse Ørnbjerg Würtz,†,‡ Anne-Sofie Schrohl,†,‡ Britt Damsgaard,†,‡ Maria Unni Rømer,†,‡ Kirstine C. Belling,†,‡ Niels Frank Jensen,†,‡ Irina Gromova,⊥ Dorte B. Bekker-Jensen,§ José M. Moreira,†,‡ Lars J. Jensen,§ Ramneek Gupta,∥,‡ Ulrik Lademann,†,‡ Nils Brünner,†,‡,# Jesper V. Olsen,*,§,# and Jan Stenvang*,†,‡,# †

Institute of Veterinary Disease Biology, Faculty of Health and Medical Sciences and ‡Sino-Danish Breast Cancer Research Centre, University of Copenhagen, Dyrlægevej 88, 1., 1870 Frederiksberg C, Denmark § Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3b, Bldg. 6.1, 2200, Copenhagen, Denmark ∥ Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Building 208, 2800, Kongens Lyngby, Denmark ⊥ Cancer Proteomics, Genome Integrity Unit, Danish Cancer Society Research Center, DK-2100 Copenhagen, Denmark S Supporting Information *

ABSTRACT: Tissue inhibitor of metalloproteinase 1 (TIMP-1) is a protein with a potential biological role in drug resistance. To elucidate the unknown molecular mechanisms underlying the association between high TIMP-1 levels and increased chemotherapy resistance, we employed SILAC-based quantitative mass spectrometry to analyze global proteome and phosphoproteome differences of MCF-7 breast cancer cells expressing high or low levels of TIMP-1. In TIMP-1 high expressing cells, 312 proteins and 452 phosphorylation sites were up-regulated. Among these were the cancer drug targets topoisomerase 1, 2A, and 2B, which may explain the resistance phenotype to topoisomerase inhibitors that was observed in cells with high TIMP-1 levels. Pathway analysis showed an enrichment of proteins from functional categories such as apoptosis, cell cycle, DNA repair, transcription factors, drug targets and proteins associated with drug resistance or sensitivity, and drug transportation. The NetworKIN algorithm predicted the protein kinases CK2a, CDK1, PLK1, and ATM as likely candidates involved in the hyperphosphorylation of the topoisomerases. Upregulation of protein and/or phosphorylation levels of topoisomerases in TIMP-1 high expressing cells may be part of the mechanisms by which TIMP-1 confers resistance to treatment with the widely used topoisomerase inhibitors in breast and colorectal cancer. KEYWORDS: tissue inhibitor of metalloproteinase 1, SILAC, quantitative mass spectrometry, phosphoproteomics, topoisomerase, breast cancer, resistance to chemotherapy, two-dimensional PAGE

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INTRODUCTION Resistance to systemic chemotherapy is considered the main cause for the annual death of thousands of breast cancer patients worldwide.1,2 Although many different mechanisms for drug resistance have been suggested it is still neither clinically possible to predict nor to reverse drug resistance. Tissue inhibitors of metalloproteinases (TIMPs) are a family with four members known to regulate the proteolytic activity of matrix metalloproteinases (MMPs).3,4 However, these protease inhibitors have other and non-MMP dependent biological functions, including regulation of cell proliferation, angiogenesis, and apoptosis.4,5 A number of studies suggest that the regulation of apoptosis by some of the TIMPs may have an © 2013 American Chemical Society

impact on cellular sensitivity/resistance to apoptotic stimuli, including some chemotherapeutic drugs being used in cancer treatment.6−11 For example, lack of TIMP-1 protein either alone12 or in combination with topoisomerase 2A (TOP2A) gene aberrations13 was associated with an increased benefit from adjuvant treatment with a TOP2 inhibitor (epirubicin containing combination chemotherapy). Of specific interest was that this association was not observed in patients treated with a combination chemotherapy regimen not including a TOP2 inhibitor.13 Similarly, low versus high TIMP-1 plasma Received: May 15, 2013 Published: August 5, 2013 4136

dx.doi.org/10.1021/pr400457u | J. Proteome Res. 2013, 12, 4136−4151

Journal of Proteome Research

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levels showed an association with an increased objective response rate, increased progression-free survival and increased survival of metastatic colorectal cancer patients treated with combination chemotherapy including the topoisomerase 1 (TOP1) inhibitor irinotecan.14 A similar association was not seen in metastatic colorectal cancer patients treated with combination chemotherapy without a TOP1 inhibitor.15 In addition, many publications support the link between TIMP-1 and tumor cell survival demonstrating a highly statistically significant association between high tumor or plasma levels of TIMP-1 and poor cancer patient outcome.16−18 Recent preclinical studies have supported the above-mentioned findings exemplified by the fact that human breast cancer cells, which are genetically modified to overexpress TIMP-1, showed a massive increase in expression of genes involved in signal transduction, apoptosis, adhesion and proliferation19 and the TIMP-1 overexpressing cells had decreased sensitivity to the TOP2 inhibitor epirubicin and the taxane paclitaxel.10,11 The TIMP-1-mediated decrease in sensitivity to epirubicin and paclitaxel was associated with enhanced degradation of cyclin B110 and activation of the PI3K/Akt/NF-kβ pathway.11 Other possible mechanisms of action of TIMP-1-mediated drug resistance came from studies demonstrating an antiapoptotic activity of TIMP-1 being mediated by activation of the Akt cell survival pathways, focal adhesion kinase (FAK) and the extracellular signal-regulated kinase (ERK) pathway.6−8 In addition, TIMP-1 can bind to the tetraspanin cell surface protein CD6320,21 and in a human breast epithelial cell line this interaction induced antiapoptotic effects by activation of the Akt survival pathway.9 Collectively, these studies suggest that TIMP-1 confers resistance to chemotherapy, including treatment with TOP1 and 2 inhibitors and taxanes, supporting the idea of measuring the level of TIMP-1 as a predictive biomarker for topoisomerase inhibitor response in patients.12−14,22,23 Moreover, if the exact biological functions of TIMP-1 in relation to chemotherapy resistance are identified, it might be possible to interfere with the mechanisms leading to chemotherapy resistance and possibly reverse the resistance mechanisms. In order to elucidate the mechanisms underlying the association between high TIMP-1 levels and increased chemotherapy resistance, a quantitative global investigation of high TIMP-1 expressing breast cancer cells is required. Recent breakthroughs in the proteomics technology of high-resolution mass spectrometry (MS) instrumentation allows identification of thousands of proteins in various proteomes, quantification of thousands of post-translational modifications (PTMs) such as phosphorylations and determination of protein−protein interactions.24 In particular, quantitative proteomics, which combines stable isotope labeling by amino acids in cell culture (SILAC) with enrichment strategies of modified peptides and high-performance MS, represents a powerful approach to monitor intracellular events in a global fashion. Our laboratories have generated single cell clones from the human breast cancer cell line MCF-7 expressing high or low levels of TIMP-1. We selected two clones with low TIMP-1 protein expression and two clones with high TIMP-1 protein expression. These cell clones were employed in a SILACbased25 quantitative MS approach to investigate the proteome and phospho-proteome changes between cells expressing high or low levels of TIMP-1 in two biological replicates.

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EXPERIMENTAL PROCEDURES

Cell Cultures and SILAC Labeling

The parental MCF-7S1 breast cancer cell line (kindly provided by Professor Marja Jäaẗ tela, The Danish Cancer Society, Copenhagen, Denmark)26 was stably transfected with pcDNA(hyg)-TIMP-1 by FuGENE trasfection reagent (Roche, Denmark) and subsequently single cell cloned by limited dilution. Eleven single cell clones were screened for TIMP-1 expression levels and two high and two low expressing TIMP-1 single cell clones were chosen for further analyses. The cells were propagated in complete media: RPMI 1640 (Gibco, Invitrogen, Denmark) with 10% FCS (Gibco, Invitrogen, Denmark) and 100 μg/mL hygromycin (Calbiochem, VWR, Denmark). For quantitative MS, cells were labeled in SILAC RPMI 1640 (PAA Laboratories GmbH, Germany)27 supplemented with 10% dialyzed FCS (Sigma, Denmark) and 200 μM glutamine (Gibco, Invitrogen, Denmark) for 12 days to ensure complete incorporation of amino acids (Figure 1). After the 12 days incorporation of amino acids, cells from each condition were seeded with same cell density in T300 flasks and media was changed two days before cell harvest. The two TIMP-1 low single cell clones were labeled with natural variants (light label) of the amino acids, one of theTIMP-1 high single clones with medium variants of amino acids (L-[13C6]Arg (+6) and L[2H4]Lys (+4)), and the second TIMP-1 high expressing single cell clone was labeled with heavy variants of the amino acids (L[13C6,15N4]Arg (+10) and L-[13C6,15N2]Lys (+8)) (Cambridge Isotope Laboratories, Andover, MA). Cells were propagated using 0.1% trypsin/EDTA (Gibco, Invitrogen, Denmark). TIMP-1 wild type (TWT-III) and TIMP-1 knockout (TKOIII) murine fibrosarcoma cell lines were previously established in our laboratory as described in ref 28. These cells were grown in M199 media (Gibco), supplemented with 10% FCS. All cells were grown at 37 °C in humidified air containing 5% CO2. Cell Lysis and In-Solution Digestion

Cells from light/medium/heavy SILAC conditions were lysed separately at 4 °C in ice cold modified RIPA buffer [50 mM Tris, pH 7.5, 150 mM NaCl, 1% NP-40, 0.1% sodium deoxycholate, 1 mM EDTA, 5 mM β-glycerolphosphate, 5 mM NaF, 1 mM sodium orthovanadate, 1 complete inhibitor cocktail tablet per 50 mL (Roche, Basel, Switzerland)]. Proteins were precipitated overnight at −20 °C in 4-fold excess of ice cold acetone. The acetone-precipitated proteins were resolubilized in denaturation buffer (10 mM HEPES, pH 8.0, 6 M urea, 2 M thiourea) and the lysates from light/medium/heavy SILAC conditions were mixed 1:1:1 based on protein concentrations (Figure 1). The soluble proteins were reduced for 60 min at room temperature (RT) with 1 mM DTT and alkylated for 60 min at RT with 5.5 mM chloroacetamide (CAA). Endoproteinase Lys-C (Wako, Osaka, Japan) was added (1:100 m/m) and the samples were incubated for 3 h at RT. The samples were then diluted 4-fold with deionized water, and digested with trypsin (modified sequencing grade, Promega, Madison, WI) (1:100 m/m) overnight at RT. Trypsin and Lys-C activities were quenched by acidification of the samples (2% v/v of TFA, pH ∼ 2). For each of the samples, the peptide mixture was desalted and concentrated on a C18-SepPak cartridge (Waters, Milford, MA) and eluted with 1 × 2 mL of 40% acetonitrile (ACN) in 0.1% TFA followed by 1 × 2 mL 60% ACN in 0.1% TFA. A sample of each of the eluates (total tryptic proteome) was desalted and concentrated on a C18 STAGE-tip31 and 4137



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30% ACN) for 30 min, followed by isocratic (100%) buffer B for 6 min at a flow rate of 1.0 mL/min. Fractions of 2 mL were collected of which some were pooled. A sample of each fraction or fraction pool was desalted and concentrated on a C18 STAGE-tip and eluted with 2 × 10 μL 40% ACN in 0.5% acetic acid before LC-MS/MS (for proteome analysis). Phospho-peptides were enriched using Titansphere chromatography as described.29 Briefly, titanium dioxide beads (10 μm Titansphere, GL Sciences, Japan) were precoated with 2,5dihydroxybenzoic acid (2,5-DHB) by incubating the beads in a solution of 20 mg/mL 2,5-DHB in 80% ACN, 1% TFA for 20 min at RT. Approximately 1 mg of coated beads was added to each SCX fraction or fraction pool and incubated under rotation for 30 min at RT. Early SCX fractions, mostly enriched in phospho-peptides, were incubated with coated TiO2 beads twice consecutively for better coverage. The beads were washed once with 100 μL SCX buffer B and once with 100 μL 40% ACN in 0.5% TFA and transferred in 50 μL 80% ACN in 0.5% acetic acid on top of a C8 STAGE-tip. The bound phosphopeptides were eluted directly into a 96-well plate by 2 × 10 μL 5% NH4OH followed by 2 × 10 μL 10% NH4OH/25% ACN, pH > 11. The eluate was immediately concentrated in a speedvac at 60 °C to a final volume of about 5−10 μL and acidified using 20 μL 5% ACN in 1% TFA. Each sample was then desalted and concentrated on a C18 STAGE-tip and eluted with 2 × 10 μL 40% ACN in 0.5% acetic acid before LC-MS/MS. LC-MS/MS of Peptides

All LC-MS/MS experiments were performed on an EASY-nLC system (Proxeon Biosystems, Odense, Denmark) interfaced with a hybrid LTQ-Orbitrap Velos (Thermo Electron, Bremen, Germany)31 through a nanoelectrospray ion source. All peptides were autosampled and separated on a 15 cm column (75 μm internal diameter) packed in-house with 3 μm C18 beads (Reprosil-AQ Pur, Dr. Maisch, Germany), where the tip of the column formed the electrospray (in-house pulled by a Sutter P-2000). For liquid chromatography, a linear gradient of ACN in 0.5% acetic acid (either: 8−24% ACN for 90 min, then 24−48% ACN for 15 min, then 60% ACN for 1 min; or: 8− 24% ACN in 150 min, then 24−48% ACN in 30 min, then 60% ACN for 1 min) was used at a constant flow rate of 250 nL/ min. The effluent from the HPLC was directly electrosprayed into the mass spectrometer using 2.1 kV spray voltage through a liquid junction connection and a heated capillary temperature of 275 °C. A lock-mass ion (m/z 445.120024) was used for internal calibration in all experiments as described earlier.32 MS was performed in a data dependent acquisition mode where up to the 10 most intense peaks were chosen for fragmentation after acquiring each full scan using Higher energy Collisional Dissociation (HCD)33 for all MS/MS events. Dynamic exclusion was used to avoid picking peaks more than once. The settings were a mass window of 10 ppm, a max list size of 500, and a time window of 90 s. Full scans were acquired in the m/z range of 300−2000 with an R = 30,000 at m/z 400 and a target value of 1e6 ions with a maximum injection time of 500 ms. For fragment scans the settings were an isolation window of 4 Da, a minimum signal intensity of 5000, R = 7500 at m/z 400, and a target value of 5e4 ions with a maximum injection time of 250 ms.

Figure 1. Experimental workflow of the SILAC-based quantitative proteomics and phospho-proteomics for the analyses of the biological role of TIMP-1 in breast cancer. Two TIMP-1 low expressing and two TIMP-1 high expressing populations derived from MCF-7 human breast cancer cells were labeled by triple SILAC. Lysates were mixed 0.5:0.5:1:1 as shown. Proteins were digested by endoproteinase Lys-C and trypsin and tryptic peptides were fractionated by SCX. Phosphopeptides were enriched using TiO2 beads precoated with DHB. Samples were analyzed by high resolution nanoLC-MS/MS. The proteome data were determined directly from the SCX fractions.

eluted with 2 × 10 μL 40% ACN in 0.5% acetic acid before LCMS/MS. SCX Fractionation, Phospho-Peptide Enrichment, and Proteome Preparation

Peptide fractionation by SCX chromatography29,30 was performed in a 1 mL Resource S column (GE Healthcare, Sweden) on an Ä KTA FPLC system (GE Healthcare, Sweden). The peptide mixture, eluted off C18-SepPak, was loaded directly onto a 10 mL injection loop and separated by a linear gradient from 100% SCX buffer A (5 mM KH2PO4, pH 2.7, 30% ACN) to 30% SCX buffer B (5 mM KH2PO4, pH 2.7, 350 mM KCl, 4138



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Analysis of Total Peptide and Enriched Phospho-Peptide Data Sets by MASCOT and MaxQuant

All raw Orbitrap full-scan MS and MS/MS data were analyzed together using the software MaxQuant34 version 1.0.14.7. Proteins were identified by searching the HCD-MS/MS peak lists against a total of 174 122 protein entries encompassing a concatenated forward and reversed version of the International Protein Index (IPI) database for humans (v. 3.68) supplemented with commonly observed contaminants such as porcine trypsin and bovine serum proteins using the MASCOT search engine version 2.3.02. Tandem mass spectra were initially matched with a mass tolerance of 7 ppm on precursor masses and 0.02 Da for fragment ions, set to recognize tryptic cleavage sites and allowed for up to three missed cleavage sites. Cysteine carbamidomethylation (Cys +57.021464 Da) was searched as a fixed modification. N-Acetylation of protein (N-term +42.010565 Da), N-pyro-glutamine (Gln −17.026549 Da), oxidized methionine (+15.994915 Da), and for phosphopeptides: phosphorylation of serine, threonine, and tyrosine (Ser/Thr/Tyr +79.966331 Da) were searched as variable modifications. Labeled lysine and arginine were specified as fixed or variable modification, depending on prior knowledge about the parent ion (MaxQuant SILAC triplet identification). Peptide identifications were filtered based on their Mascot score, SILAC state, number of arginine and lysine residues and peptide length (minimum peptide length was specified to be six amino acids) to achieve a maximum false discovery rate of one percent. Protein groups were assembled and quantified based on the Occam’s razor principle. Finally, to pinpoint the actual phosphorylated amino acid residue(s) within all identified phospho-peptide sequences, MaxQuant calculated the localization probabilities of all putative serine, threonine, and tyrosine phosphorylation sites using the PTM score algorithm as described.35 Statistical Determination of SILAC Ratio Cutoffs for Expression and Phosphorylation

Medians of the log2-transformed normalized SILAC ratios were calculated using the SILAC ratio sets from the biological replicates thus reflecting the high TIMP-1/low TIMP-1 ratios of expression and phosphorylation for all identified proteins and phospho-sites, respectively. The statistical P-values were calculated for detection of significant outlier ratios (Significance A values). Three levels of significance were chosen, P-value 0.05 as shown in Figure 2. STRING Network and Ingenuity Pathway Analysis

Proteins with median normalized SILAC ratios ≥ 2.3 at the expression level and/or median normalized SILAC ratios ≥ 3.0 at phosphorylation level (460 entries) were used to build a protein−protein interaction network from the STRING database system (http://string-db.org/36) at a reliability score of at least 0.7.37 The same set of proteins was analyzed for enrichment of pathways and functional classes using the tools Ingenuity Pathway Analysis (IPA, www.ingenuity.com) and Explain (Biobase, http://www.biobase-international.com/) as well as in-house phenotypically related gene collections. The 460 UniProt entries, mapping to 453 encoding genes (six

Figure 2. Statistical determination of the median normalized SILAC ratio cutoffs for proteins up-regulated at expression and/or phosphorylation. (A) Median log2-transformed normalized SILAC ratios for proteins plotted as a function of the log10-transformed summed peptide intensities and categorized based on significance A values for the regulation. (B) Median log2-transformed normalized SILAC ratios for class I phospho-sites plotted as a function of the log10-transformed phospho-peptide intensities and categorized based on significance A values for the regulation. 4139



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etoposide cytotoxicity in the MCF-7 cells and cytotoxicity of epirubicin and SN-38 in the murine TWT-III and TKO-III cells. All MTT and LDH assays were performed at least three times and each time in triplicates.

protein entries were obsolete in UniProt, two were not mapped to genes, and one demerged into two genes) were further analyzed for different functional class enrichments and drug interactions using gene ontology. Targets of the used chemotherapies epirubicin, irinotecan, etoposide, and cisplatin were queried from ChemProt database38 and DrugBank.39 This gene annotation data was layered on the protein−protein interaction network from the STRING database using Cytoscape40 and its MultiColoredNodes plugin.41

Western Blotting and TIMP-1 ELISA

Lysates from each of the four selected cell clones were harvested individually by scraping off the cells in ice cold PBS, spun down at 300g at 4 °C and lysed by incubation in ProteoJET Mammalian Cell Lysis Reagent (Fermentas, Germany) containing protease inhibitors (Aprotinin, Leupeptin, Pepstatin A and Pefa Block, 1 μg/mL) (Calbiochem, VWR, Denmark) and phosphatase inhibitors (sodiumfluoride and sodiumorthovanadate, 1 mM) (Calbiochem, VWR, Denmark) for 10 min at RT. The cells were then spun at 18 000g for 15 min at 4 °C, and each of the four supernatants was transferred to a new tube. The total amount of protein was determined by the BCA Protein Assay kit (Pierce, VWR, Denmark) according to manufacturer’s instructions. The NuPAGE system (Invitrogen A/S, Denmark) was used for SDS-PAGE gel separation of proteins according to manufacturer’s instructions. In brief, lysates were mixed with NuPAGELDS loading buffer and NuPAGE sample reducing agent. Samples were then incubated at 70 °C for 10 min. Samples were loaded onto NuPAGE Novex 4−12% Bis-Tris gels with 50 μg/lane and were run in NuPAGE MOPS buffer with NuPAGE antioxidant according to the manufacturer’s instructions. Gels were blotted on polyvinylidene difluoride membranes with 2× NuPAGEtransfer buffer with 20% ethanol. Blots were blocked in washing buffer (PBS + 0.1% Tween 20) containing either 5% nonfat dry milk (for TOP1, TOP2B) or 2% ECL prime blocking reagent (for TIMP-1, β-actin, TOP2A) for 1 h and incubated overnight with the appropriate primary antibody diluted in blocking reagent: In-house mouse monoclonal anti-TIMP-1 antibody VT-7, 0.1 μg/mL,45 rabbit monoclonal anti-TOP1 1:10 000 (Epitomics, Abcam, Burlingame, CA), rabbit monoclonal anti-TOP2A 1:1000 (Cell signaling, VWR, Denmark), sheep polyclonal anti-TOP2B 1:500 (R&D systems, Trichem, Denmark), and mouse monoclonal anti-β-actin 1:1 500 000 (Sigma-Aldrich, Denmark). Blots were washed four times for a period of 30 min in washing buffer and incubated with secondary horseradish peroxidase-conjugated antibody (Dako A/S, Denmark) diluted in blocking reagent. The blots were washed four times for a period of 30 min and developed using the Amersham ECL plus Western Blotting Detection Kit (for TOP2B) or Amersham ECL Advance Western Blotting Detection Kit (for TIMP-1, βactin, TOP2A) (GE Health/Amersham Bioscience, VWR, Denmark) according to the manufacturer’s instructions. Blots were visualized with a CCD camera (BioSpectrum Imaging System, UVP BioImaging, Upland, CA). During experiments, the differences in cellular expression of TIMP-1 among the selected clones were routinely assayed with an in-house sandwich ELISA assay employing a sheep polyclonal anti-TIMP-1 antibody in the catching step and the MAC15 anti-TIMP-1 monoclonal antibody in the detection step, as described in ref 46. The levels of murine TIMP-1 in the wild-type and knockout cells were measured by a commercial quantikine mouse TIMP-1 ELISA kit (R&D Systems) according to the manufactures recommendations.

Phosphorylation Sites Sequence Bias Analysis

Sequence bias around the up-regulated phosphorylation sites was visualized using the IceLogo software42 which compared class I up-regulated phosphorylation sites (median normalized ratios ≥ 3.0) with reference class I phosphorylation sites (0.8 ≤ median normalized ratios ≤ 1.2), all from the same data set. The outcome of the IceLogo analysis was compared to known kinase substrate motifs (www.phosida.com35) in order to obtain over-represented, unbiased, and under-represented known kinase substrate motifs for the up-regulated phospho-sites. NetPhorest and NetworKIN Kinase Prediction Analysis

The NetworKIN algorithm43 combines kinase consensus motifs, extracted from the NetPhorest atlas,44 with contextual information of the kinases and their substrates in protein association networks extracted from the STRING database. It was applied on all phosphorylation sites obtained by MS analysis. Since NetworKIN incorporates data from NetPhorest, the results include not only the specific kinase but also the name of the NetPhorest group. Growth Assay and Sensitivity to Chemotherapy

For the growth assay, 40 000 cells/well of each cell line were plated in six 6-well plates. Each day, one plate was harvested: media were removed from all wells and cells were washed with PBS before the addition of 1 mL trypsin. After incubation for 60 s, 1 mL of media was added and cells were resuspended. Three individual samples from each cell suspension were counted using a hemocytometer, and the doubling time for each cell line was calculated based on three independent experiments. Growth medium was renewed on the fourth day after plating the cells. Viability of the four included TIMP-1 cell clones were tested upon treatment with the TOP2 inhibitor epirubicin (Meda AS, Denmark), the TOP1 inhibitor SN-38 (the active metabolite of irinotecan) (Sigma-Aldrich, Denmark), the TOP2B inhibitor 2(4-((7-chloro-2-quinoxalinyl)oxy)phenoxy)propionic acid (XK 469) (Sigma-Aldrich, Denmark), the TOP2 inhibitor etoposide (Meda AS, Denmark), and cis-diamminedichloroplatinum (Cisplatin) (Hospira, Denmark). Cells were seeded in 96-well plates with 8000 cells/well and allowed to plate overnight. Cells were then treated with the appropriate drug for 48 h, and cell viability was determined by addition of MTT (Sigma-Aldrich, Denmark) dissolved in PBS. MTT was added to the cells in complete media at a final concentration of 0.5 mg/mL. Cells were incubated at 37 °C for 3 h and generated formazan crystals were dissolved with 20% SDS in 0.02 M HCl overnight and measured at 570 and 690 nm. Based on the dose response curves generated for the low and high TIMP-1 cell clones in response to each of chemotherapeutics, the inhibitory concentration resulting in 50% viability (IC50) for each of chemotherapeutics was estimated. As previously described28 a lactate dehydrogenase (LDH) release assay (Cytotoxicity Detection Kit; Roche A/S, Denmark) was applied to evaluate

Two-Dimensional Gel Electrophoresis and Immunoblotting

Cellular lysates were subjected to IEF (pI 4−7) twodimensional PAGE (2D PAGE) as previously described.47 4140



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(median normalized ratio ≥ 3.0), whereas 542 proteins (median normalized ratio ≤ 0.4) and 443 phosphorylation sites (median normalized ratio ≤0.3) were down-regulated (Table 1). Spearman’s correlation coefficients of 0.9 between

Between 20 and 30 μL of sample was applied to the first dimension, and IEF gels were run for each sample. Proteins were visualized using a silver staining procedure. Immunoblotting using Western blots of lysates were prepared as previously described. Briefly, proteins were resolved by 2D-gel electrophoresis, blotted onto Hybond-C nitrocellulose membranes (Amersham Biosciences), and reacted with a TOP1 specific rabbit antibody (1:2000 TOP1 antibody, Epitomics) followed by detection of immune complexes with a horseradish peroxidase-labeled polymer (1:200) (Envision+ detection kit; DAKO). Blocking of antibody cross-reactivity was done using a protein-free blocking buffer (Thermo Fischer Scientific, Waltham, MA). Membranes were reversibly stained with Ponceau S solution (Sigma-Aldrich) to match the location of proteins in the membrane with the Western blot signal and to ensure proper focusing of protein spots. To identify the phosphorylation state of TOP1, one aliquot of each of low TIMP-1 A or high TIMP-1 B cell lysates was treated for 30 min at 37 °C with lambda protein phosphatase (Lambda PP), a Mn2+-dependent protein phosphatase with activity toward phosphorylated serine, threonine, and tyrosine residues according to the manufacturer’s instructions. One aliquot of each cell clone was mock-treated prior to resolving by 2D gel electrophoresis.

Table 1. Summary of Quantitative Proteomics and PhosphoProteomics Data identified protein groups

identified phospho-sitesc total ratio ≥ 3.0b ratio ≤ 0.3b

5421a 452 443

a

Nonredundant total number identified in both experimental replicates 1 and 2. bRatios are medians of the normalized High TIMP-1/low TIMP-1 SILAC ratios from both experimental replicates 1 and 2; ratio cutoffs were determined from the statistical analyses based on significance A values (Figure 2). cMASCOT score ≥ 10; PTM score ≥ 25; localization probability ≥ 0.8.

normalized SILAC ratios for proteins identified in both experiments and coefficients of 0.6−0.8 between normalized SILAC ratios for phosphorylation sites in both experiments (Supporting Information Figures 2A and B) were in line with previous phosphoproteomics experiments.48 Similar to what has been observed in most SILAC experiments,49,50 the majority of proteins (>75%) and phosphoproteins (>60%) were found to have SILAC ratios between 0.5 and 2.0 and to exemplify the general validity of the data set, housekeeping proteins such as Heat shock 70 kDa protein 4 (hsp74) (Figure 3B, left) and β-tubulin (data not shown) were found to be expressed in equal amounts in both TIMP-1 low and high expressing clones. Differential expression of TIMP-1 among the cells expressing low and high levels was verified in the proteome data set (Figure 3B, right), in concordance with Western blot and ELISA analyses (Figure 3A).

Statistical Analysis of Cell Viability Data and Cell Growth

All calculations were performed using SAS software (version 9.2, SAS Software, Inc., Cary, NC). For statistical analyses, the relationship between TIMP-1 concentration and cell survival was analyzed with mixed model solution. It is a generalization of general linear model solution containing both fixed and random effects. Within the model, drug doses and TIMP-1 levels were set as fixed effects, whereas cell line, plate placement, and experiment number were set as random effects. Mean values of the doubling times for the low TIMP-1A/B and the high TIMP-1A/B cells were analyzed by Student’s t test. The level of significance was set at P < 0.05.

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6709a 312 542

total ratio ≥ 2.3b ratio ≤ 0.4b

RESULTS

Proteomic and Phosphoproteomic Analysis of TIMP-1 Expressing Cells

Pathway and Functional Category Enrichment in TIMP-1 High Expressing Cells

TIMP-1 transfected single cell clones obtained from the human breast cancer cell line MCF-7S1 were used as the cellular model, and the clones were SILAC labeled (Figure 1). Based on TIMP-1 protein expression levels as determined by ELISA, we selected two low high and two low expressing clones from our panel of 11 single cell clones. From both replicates combined, we found 41 417 unique peptides originating from 6709 protein groups and 5421 unique class I phospho-sites mapped to 1640 protein groups (Supporting Information Tables 1−4). The overlap of the identified protein groups between the two biological replicates was 68%, (Supporting Information Figure 1A). Serine (Ser), threonine (Thr), and tyrosine (Tyr) phosphorylation sites comprised 92.2%, 7.4%, and 0.4% of the total phosphorylation sites, respectively (Supporting Information Table 5), with similar percentages for the up-regulated Ser/Thr/Tyr sites. Moreover, one or two phosphorylation sites were detected in most phosphorylated peptides (Supporting Information Figures 1B and C). Comparative analysis of the proteomic data from the TIMP-1 clones revealed that the TIMP-1 high expressing cells overexpressed 312 proteins (median normalized ratio ≥ 2.3) and 452 class I phosphorylation sites were up-regulated

Proteins found to be up-regulated (median normalized ratio ≥ 2.3) and/or hyper-phosphorylated (median normalized ratio ≥ 3.0) in the TIMP-1 high expressing cells were selected for further analysis. The cutoff values were selected based on the significance of regulation at both expression and phopshorylation levels (Figure 2). Using these cutoff values, a combined list of 460 highly up-regulated proteins was generated. An interaction network of 146 nodes was obtained for these proteins at a high confidence level (0.7) in the STRING database (Figure 4). In Table 2A, we list the up-regulated and/ or hyperphosphorylated proteins with known biological relation to TIMP-1. Interestingly, TIMP-1 was directly connected to the CD44 antigen (up-regulated 2.7 fold, Table2A), which has been shown to bind TIMP-1,51 and to clusterin (CLU) (up-regulated 4 fold, Table 2A), which has been associated with drug resistance to both TOP1 and TOP2 inhibitors.52,53 These 460 proteins were used for pathway and functional enrichment analysis (Supporting Information Table 7). IPA mapped 460 proteins to 453 entries in ingenuity database. The JAK/STAT signaling pathway and cell cycle G2/M DNA damage checkpoint regulation pathway were among the significantly 4141



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Figure 3. Validation of the model system. (A) Western blot analysis of TIMP-1 with β-actin as a loading control. The quantitative ELISA measurements of TIMP-1 are shown below the blot. (B) Representative peptide from HSP74 showing 1:1:1 ratios independent of TIMP-1 (left) and representative unmodified peptide from TIMP-1 (right). All peptides are in SILAC triplets. Different colors correspond to the colors in Figure 1, representing the SILAC L/M/H labels.

members JunB (up-regulated 3.0 fold in the TIMP-1 high expressing cell lines) and Fos-related antigen 2 (FRA2 or FosL2) (up-regulated 2.6 fold in the TIMP-1 high expressing cell lines) are also in the network (Figure 4). Noteworthy among other proteins of particular interest in relation to TIMP1 that did not show up in the protein interaction network but were nevertheless found to be up-regulated in TIMP-1 high expressing cells (Table 2A) was the membrane protein CD63, previously shown to bind to TIMP-1.9,21,51 CD63 was upregulated approximately 2-fold (statistical cutoff 2.3).

perturbed in the data set. The JAK/STAT pathway is one of the main signaling pathways in eukaryotic cells and is involved in the control of cell proliferation, differentiation, survival, and apoptosis.54 The G2/M damage checkpoint is often deficient in cancer, resulting in survival of cells with DNA damage and mutations leading to resistance and sustained proliferation.55 The same gene set was further analyzed for biological function, molecular processes enrichment and drug interactions. Proteins overexpressed in TIMP-1 high expressing cells participate in several functional categories including: apoptosis (e.g., CLU, FosL2, mTOR, TIMP-1, CD44, TOP1, TOP2B, ABCC1), cell cycle (e.g., mTOR, TOP1, TOP2B), DNA repair (e.g., TOP1, CLU), drug resistance or sensitivity (e.g., NDRG1, TOP2A, CD59, CLU), drug targets (e.g., TOP1, TOP2A, TOP2B), and drug transport (e.g., ABCC1, -3, -6). For a complete list of functional groups and the proteins discovered in each group, see Supporting Information Table 7. The most relevant functional classes were layered on the protein−protein interaction network from STRING with color-coding representing different functional classes (Figure 4). This analysis aimed to search for novel links between TIMP-1 and cancer related pathways, thereby identifying potential new functional roles of TIMP-1 in cancer. In addition to TIMP-1 and its direct interactors CD44 and CLU in the functional network (Figure 4), noteworthy among other proteins in the network are TOP1, TOP2A, and TOP2B, all of which are involved in maintaining DNA topology during DNA replication, transcription, or repairing DNA double strand breaks. Interestingly, we also identified the mammalian target of rapamycin (mTOR), which has been implicated in the resistance to TOP2 inhibitors.56 Activator protein-1 (AP-1) transcription factor complex

High TIMP-1 Protein Level Is Associated with Increased Levels and Phosphorylation of Topoisomerases

DNA topoisomerases were found in the enriched functional classes (Figure 4). More specifically, TOP2A displayed increased expression (8-fold) in TIMP-1 high expressing cells (Table 2A) and the proteomics data was validated by Western blotting (Figure 5B). Proteomics data also showed that TOP1 was 1.8 fold higher expressed (Table 2A) in the TIMP-1 high expressing cells, however this slight fold up-regulation is lower than the statistically determined cutoff value of 2.3 and higher expression of TOP1 is not detectable in the Western blot (Figure 5B). There was no differential expression of TOP2B between TIMP-1 low and high expressing cells (Table 2A), also validated by the Western blotting (Figure 5B). Many phosphorylation sites on the topoisomerases were found to be up-regulated in the TIMP-1 high expressing cells (Table 2B). TOP1 had three phosphorylation sites (Ser 2, 10 and 112), where phosphorylation was up-regulated in TIMP-1 high expressing cells (Figure 5A, left and Table 2B). The phosphorylation at Ser 2 was only detected in the first replicate with a fold-change of about 3. Phosphorylation at Ser 10 and 4142



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Figure 4. Functional class distribution of protein−protein interaction network of the identified proteins up-regulated at expression and/or phosphorylation levels in TIMP-1 high expressing cells. The nodes in the STRING network are sectored by different colors for functional annotations. Circular nodes originate from the proteome data set (median normalized ratio ≥ 2.3), triangular nodes originate from the phosphoproteome data set (median normalized ratio ≥ 3.0), whereas the octagon represents the proteins detected in both data sets. TOP1, TOP2A, TOP2B, TIMP-1, CD44, and CLU are highlighted.

immunoblots + phosphatase) showed substantially fewer modified forms as compared with the untreated samples, indicating that the majority of the more acidic forms are due to phosphorylations, which supports our MS-based analysis. The most heavily phosphorylated topoisomerase enzyme was TOP2B, in which several Ser sites were phosphorylated in the TIMP-1 high expressing cells: Ser 1336, 1340, 1342, 1344, 1400, 1413, 1461, 1466, 1522, 1524, and 1526 (Figure 5A, right and Table 2B). The phosphorylations on Ser 1461 and 1466 were only detected in the first experiment, but were found to have an 11-fold increase. All other phosphorylation sites were found to be 2−5-fold up-regulated in TIMP-1 high expressing cells. Since TOP2B is similarly expressed between TIMP-1 low and high expressing cells (Figure 5B and Table 2A), the SILAC ratios for the phosphorylations indicate true up-regulation of several phosphorylations at a post-translational level.

112 were detected in both replicates with up-regulations of about two and three folds respectively in the TIMP-1 high expressing cells. TOP2A had one identified phosphorylation site at Ser 1328 which was about 13-fold more phosphorylated in the TIMP-1 high expressing cells although this was only detected in replicate one. The fact that SILAC ratios for the phosphorylations of TOP1 and TOP2A are generally higher than the SILAC ratios for their expressions (Table 2), between TIMP-1 low and high expressing cells, indicates some upregulation of phosphorylation at a post-translational level. To confirm these differences in the phosphorylation states of TOP1 between low and high TIMP-1 expressing cells, we exploited the fact that phosphorylated protein will almost always have a more acidic pI than its corresponding unphosphorylated form. IEF followed by immunoblotting allows detecting more acidic forms of a protein and the PTM state of a protein. Indeed, 2D gel-based comparative analysis of TOP1 in low TIMP-1 and high TIMP-1 cells showed that TOP1 exists in a state of at least four modified forms in low TIMP-1 expressing cells, and that TIMP-1 overexpression affects TOP1 gain of additional modifications, with a clear shift toward multiple modification states (Figure 5C, TOP1 immunoblots). Since PTMs other than phosphorylation can cause changes in the pI, we treated cell lysates with lambda phosphatase prior to gel analysis to show that the multiple forms identified were mainly due to phosphorylation events. The TOP1 patterns obtained in this manner (Figure 5C, TOP1

Kinase Motif Analysis of Upregulated Phosphorylation Sites in TIMP-1 High Expressing Cells

In order to visualize the kinase motifs over-represented in the up-regulated phophorylation sites compared to the unregulated phophorylation sites, the sequence windows aligned around all class I up-regulated phosphorylation sites with median normalized ratios equal to or higher than the statistical cutoff of 3.0 were compared to those of unregulated class I sites and demonstrated a bias against arginine in several minus and plus subsites (especially −1 to −4) and against proline in +1 subsite (Figure 6A). This indicates an under-representation of the 4143


4144

high TIMP-1/low TIMP-1b

3f 2±2 2.8 ± 0.4 13f 2±1 2±1 4±2 4±2 4±2 11f 11f 5±2 5±2

high TIMP-1/low TIMP-1e

CK2_group ATM_ATR_group CDK2_CDK3_CDK1_CDK5_group CDK2_CDK3_CDK1_CDK5_group CK2_group PLK_group (all three sites) CDK2_CDK3_CDK1_CDK5 group CDK2_CDK3_CDK1_CDK5_group CK2_group PKC_group PLK_group CK2_group PLK_group

NetPhorest group

CK2alpha ATM CDK1 CDK1 CK2alpha PLK1 (all three sites) CDK1 CDK1 CK2alpha PKCdelta PLK1 CK2alpha PLK1

kinase

TIMP1_HUMAN 10 ± 1 TOP1_HUMAN 1.8 ± 0.2 TOP2A_HUMAN 8c TOP2B_HUMAN 1±2 CD44_HUMAN 2.7 ± 0.6 CD63_HUMAN 2.1 ± 0.2 CLUS_HUMAN 4±1 JUNB_HUMAN 3.0 ± 0.5 FOSL2_HUMAN 2.6 ± 0.8 topoisomerases: Marker phospho-peptides identified by quantitative phospho-proteomics

UniProt name

0.5 0.5 0.3 0.6 0.2 0.2 0.3 0.3 0.1 0.3 0.2 0.2 0.2

NetworKIN score

(A) Median protein SILAC ratios from quantitative proteomics. (B) Marker phospho-peptides from topoisomerases identified by quantitative phospho-proteomics. Median phospho-peptide SILAC ratios are reported. Potential protein kinases responsible for the up-regulated phosphorylation sites (NetworKIN) in topoisomerases are reported along with their respective scores. bAll protein ratios (total peptide counts ≥ 2) are medians of the normalized SILAC ratios from experimental replicates 1 and 2. cOnly identified in experimental replicate 1. dA site localization probability cutoff of 0.80 was used. e All ratios are medians of the normalized SILAC ratios from experimental replicates 1 and 2. fOnly identified in experimental replicate 1.

a

_VVEAVNS(ph)DS(ph)DS(ph)EFGIPKK_

_SEDDS(ph)AKFDS(ph)NEEDSASVFSPSFGLK_f

_VKAS(ph)PITNDGEDEFVPSDGLDKDEYTFSPGK_ _VKAS(ph)PITNDGEDEFVPS(ph)DGLDK_

2 10 112 1328 1336, 1340, 1342, 1344 1400 1400, 1413 1461, 1466 1522, 1524, 1526

_(ac)S(ph)GDHLHNDSQIEADFR_f _(ac)SGDHLHNDS(ph)QIEADFR_ _ENGFSS(ph)PPQIKDEPEDDGYFVPPK_ _IKNENTEGS(ph)PQEDGVELEGLK_f _RNPWS(ph)DDES(ph)KS(ph)ES(ph)DLEETEPVVIPR_

TOP 1

TOP 2A TOP 2B

P-sited

sequence

protein name

metalloproteinase inhibitor 1 DNA topoisomerase 1 DNA topoisomerase 2-alpha DNA topoisomerase 2-beta CD44 antigen CD63 antigen clusterin transcription factor jun-B Fos-related antigen 2 (B) Effect of TIMP-1 expression levels on the phosphorylation levels of

protein name

(A) Effect of TIMP-1 expression levels on those of topoisomerases and others: Median protein ratios from quantitative proteomics

Table 2. Regulated Proteins and Phospho-Proteins with Known Biological Relation to TIMP-1a

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Figure 5. Effect of TIMP-1 overexpression on the expression and phosphorylation levels of topoisomerases. (A) A representative phosphorylated peptide from pTOP1 (left) and a phosphorylated peptide from pTOP2B (right). All peptides are in SILAC triplets. Different colors correspond to the colors in Figure 1, representing the SILAC L/M/H labels. (B) Western blot analysis of TOP1, TOP2A, and TOP2B with β-actin as a loading control. The expression for TIMP-1 is also shown. (C) Two-dimensional immunoblot analysis of TOP1 expression and PTMs patterns in low TIMP-1 A (upper panel) and high TIMP-1 B (lower panel) cell line clones. The IEF gels were either silver stained (left-hand panels) or immunoblotted for TOP1 (right-hand panels). Arrowheads indicate multiple forms of TOP1. Treatment of lysates with lambda protein phosphatase prior to gel analysis is shown (right-hand panel, TOP1 immunoblot + phosphatase). 4145



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Figure 6. Effect of TIMP-1 overexpression on the global phosphorylation patterns and cell growth. (A) Phospho-peptides were aligned around the class I phosphorylation sites, thereby comparing up-regulated phospho-peptides (median normalized ratios ≥ 3.0) with reference phospho-peptides (0.8 ≤ median normalized ratios ≤ 1.2). Observed sequence bias was visualized with the IceLogo software tool. Over-represented, unbiased, and under-represented known kinase substrate motifs are also shown. (B) Growth curves for the cell lines low TIMP-1 A, low TIMP-1 B, high TIMP-1 A, and high TIMP-1 B. Cells were counted in triplicates with 24 h intervals and the best-fitted exponential lines were layered on top of the data. Three independent experiments were performed and a representative experiment is shown. Error bars represent SE. Doubling times were calculated from the curves and the differences between the low TIMP-1A/B and the high TIMP-1A/B cells were statistically significant (P = 0.0003).

TIMP-1 High Expressing Cells Are More Resistant toward Topoisomerase Inhibitors but Not toward Cisplatin

baseophilic kinases such as PKA and PKC, as well as the proline-directed cyclin-dependent kinases and MAP kinases,57 which are of particular interest since TIMP-1 high expressing cells showed a significantly longer doubling time (25 h) compared to the TIMP-1 low expressing cells (22 h) (P = 0.0003) (Figure 6B). A preference was seen for glutamic acids in the minus subsites (−4 to −1) and for serine in the distal minus subsites (−6 to −3) (Figure 6A) in TIMP-1 high cells, which indicates an over-representation of kinases such as PLK, PLK1, and CK1. There is no bias for or against kinases such as CK2 and ATM/ATR (Figure 6A). In order to combine the sequence bias information with the protein association network information, a NetworKIN analysis was used to identify candidate kinases involved in the hyperphosphorylation of topoisomerases (Table 2B). Five highscoring kinases were identified: ATM, CDK1, CK2 alpha, PKC delta and PLK1. PLK1 was the only kinase, which was expressed at a slightly higher level in the TIMP-1 high expressing cells (1.4-fold induction, Supporting Information Table 1).

To test whether the increased protein levels and/or phosphorylation status of the topoisomerase enzymes in TIMP-1 high expressing cells were associated with a changed sensitivity to targeted inhibition of the topoisomerases, we performed cell viability assays of the high and low TIMP-1 expressing clones treated with different topoisomerase inhibitors. Each cell line was exposed to increasing concentrations of specific topoisomerase inhibitors to analyze the cell viability response (Figure 7A−C). The relationship between cellular TIMP-1 protein levels and sensitivity to the TOP1 inhibitor SN-38 was statistically highly significant as determined by mixed model analysis (P < 0.0001), with TIMP-1 high expressing cells being significantly less sensitive to SN-38 compared to TIMP-1 low expressing cells (Figure 7A). TIMP-1 high expressing cells were also significantly (P = 0.035) less sensitive to epirubicin (general TOP2 inhibitor) induced reduction of cell viability as compared to TIMP-1 low expressing cells (Figure 7B). This was confirmed by exposure of the cells to etoposide, another TOP2 inhibitor. In full agreement with the epirubicin data, TIMP-1 high expressing 4146



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Figure 7. Cell viability of cells treated with chemotherapy for 48 h. (A) Cells treated with the TOP1 inhibitor SN-38 (0, 0.256, 1.28, 6.4, 32, 160, 800 nM). (B) Cells treated with the TOP2 inhibitor Epirubicin (0, 0.061, 2.4, 9.8, 39, 156, 625 nM). (C) Cells treated with the TOP2B inhibitor XK 469 (0, 25, 50, 75, 100, 200, 300, 500 μM). (D) Cells treated with cisplatin (0, 3.13, 6.25, 12.50, 25, 50, 100 μM). Data is presented as percent of untreated cells, and the concentrations of drugs are indicated in the figures.

observed following cisplatin treatment (Figure 7D). The IC50 values are shown in Table 3.

cells were less sensitive (P < 0.0001) to etoposide induced cell death as compared to TIMP-1 low expressing cells (Supporting Information Figure 3A). As an important extension, we applied murine fibrosarcoma cell lines to generalize our findings. These data demonstrated that SN-38 and epirubicin caused significantly more cell death in mouse fibroblast cells established from a TIMP-1 genetically knock out mouse compared to wild type mouse fibroblasts28 (Supporting Information Figure 3B). To test if high TIMP-1 also influenced sensitivity to a specific TOP2B inhibitor, we exposed the cells to the TOP2B inhibitor XK 469. We showed, that the TIMP-1 high expressing cells were significantly less sensitive to this TOP2B inhibitor (P = 0.023) as compared to TIMP-1 low expressing cells (Figure 7C). The observed differences in sensitivity to chemotherapeutic drugs could be associated to TIMP-1 mediated differences in cellular growth. Therefore, we compared the growth of the 4 MCF-7 sublines and found that the TIMP-1 overexpressing cells had a small but significantly longer doubling time (25 h) compared to the TIMP-1 low expressing cells (22 h) (P = 0.0003) (Figure 6B). To exclude the possibility that overexpression of TIMP-1 in MCF-7S1 cells led to a more general chemoresistant phenotype, perhaps related to the observed differences in growth rate, we tested the cell viability response to the chemotherapeutic drug cisplatin that has a different mode of action. This drug does not target any of the topoisomerases, but cross-links DNA thereby preventing normal cell cycle regulation which eventually triggers apoptosis.58 No significant differences in cell viability (P = 0.13) between TIMP-1 low and high expressing cells were

Table 3. IC50 Values of TOP Inhibitors and Cisplatin for the Four Low and High TIMP-1 Cell Clonesa IC50 values for the four cell clones low TIMP-1 A SN-38 Epirubicin XK 469 Cisplatin

70 30 65 57

nM nM μM μM

low TIMP-1 B 70 50 90 50

nM nM μM μM

high TIMP-1 A

high TIMP-1 B

230 nM 150 nM 460 μM 52 μM

150 nM 130 nM 450 μM 44 μM

a

The half maximal inhibitory concentration (IC50) is read from the dose−response curves for each cell line exposed to either SN-38, epirubicin, XK 469, or cisplatin.

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DISCUSSION In this study, we employed SILAC based quantitative MS to analyze global proteome and phosphoproteome differences of MCF-7 breast cancer cells genetically manipulated to express high or low levels of TIMP-1. We prioritized to investigate proteins being potentially biologically associated with our preclinical findings and our clinical observations that high levels of TIMP-1 in cancer cells significantly associate with resistance to treatment with topoisomerase inhibitors.12,22 We confirmed the previous findings that high cellular expression of TIMP-1 is associated with increased resistance to topoisomerase inhibitors, and we also observed that murine TIMP-1 wild-type 4147



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fibrosarcoma cells are more resistant to topoisomerase inhibitors than their gene deficient counterparts. Moreover, our data showed that cells expressing high levels of TIMP-1 have increased expression and/or phosphorylation of the topoisomerases, which may explain the resistance phenotype observed in cells with high TIMP-1 levels. The proteomic and phosphoproteomic data revealed regulation of hundreds of proteins and hundreds of phosphorylation sites in cells with high TIMP-1 levels compared to those with low levels. We mapped the most upregulated proteins and phospho-proteins to functional classes using IPA and found enrichment for processes that TIMP-1 is believed to be involved in, for example, apoptosis, cell cycle, transcription factors, DNA repair, drug transport, and drug resistance/sensitivity.7−11,28,59 It is particularly interesting that all the identified topoisomerases were either hyper-phosphorylated or overexpressed since this may explain why previous studies found high TIMP-1 levels in tumor or plasma to be associated with decreased benefit from topoisomerase inhibitor containing chemotherapy,12−15 as both topoisomerase 1 and 2 activity is positively dependent on phosphorylation.60−62 It is therefore intriguing to speculate that increased expression levels and phosphorylation status of topoisomerases may cause the chemotherapy resistance phenotype. To investigate the functional relevance of the increased protein expression and/or phosphorylation of topoisomerases found in the two TIMP-1 high-expressing cell lines, we exposed all cell lines to TOP1 and TOP2 inhibitors and found significantly decreased sensitivity to both inhibitors in TIMP-1 high expressing cells. Although there is abundant evidence that high TIMP-1 levels are associated with topoisomerase inhibitor resistance, the underlying mode of action is to date not clear. TIMP-1 may bind to the cell surface and be transported into the nucleus as shown in a previous study in MCF-7 human breast cancer cells.63 As such, TIMP-1 has also been shown to bind to the cell surface proteins CD63 and CD44. The binding of TIMP-1 to these proteins initiates intracellular signal transduction that leads to an antiapoptotic phenotype.9,12−15,20,21,51 We found both CD63 and CD44 to be up-regulated at the expression level, which suggests a positive feedback mechanism. This opens new doors in developing anticancer therapeutic interventions, as disruption of the TIMP-1 complex with plasma membrane proteins could potentially reduce the antiapoptotic signaling from the complex. TIMP-1 has been suggested to initiate many different intracellular signaling pathways, which could explain the chemotherapy resistance phenotype seen in TIMP-1 high expressing cells and tumors. To determine which kinases, and hence pathways, may be hyperactivated in TIMP-1 high expressing cells, we analyzed the kinase motifs for all the upregulated phosphorylation sites against unchanged phosphorylation sites (reference) from the same data set and found a bias against proline-directed kinases. This is interesting because the proline-directed kinases, Akt and ERK, play a role in TIMP1 overexpressing cells, and have been related to resistance to breast cancer treatment.7−9,11,19,59,64,65 Second, although contradictory to earlier studies, we found TIMP-1 high expressing cells to grow slightly but significantly slower than TIMP-1 low expressing cells. This could be explained by the underrepresentation of the proline-directed kinases that promote proliferation.66−68 Consistent with this we have recently reported an inverse relationship between TIMP-1

protein levels and the proliferation marker Ki67 in clinical breast cancer samples.69 The motif analysis showed that the recognition motif for polo-like kinases was overrepresented. Moreover, polo-like kinase 1 (PLK1) phosphorylates TOP2A70 and NetworKIN predicted PLK1 also to be responsible for the phosphorylation of six up-regulated phosphorylation sites in TOP2B. PLK1 also phosphorylates numerous other cell-cycle proteins, including PKMYT1 and CCNB1, both of which we found to be upregulated in cells with high TIMP-1 levels. These phosphorylations lead to inhibition of PKMYT171 and promoted nuclear import of CCNB,72 promoting progression through M-phase. This is consistent with the slower growth of TIMP-1 high expressing cells and the observed increase in expression and phosphorylation of the topoisomerases. Our data set revealed increased expression of hundreds of proteins in the TIMP-1 high expressing cells compared to TIMP-1 low expressing, and it is possible that the mere regulation of protein expression plays a role. As such, we observed an up-regulation of several transcription factors in TIMP-1 high expressing cells, which may explain the massive amounts of proteins being up-regulated in these cells. Two transcription factors belonging to the activator protein-1 (AP1) complex family, namely, JunB and FosL2, were found to be up-regulated in TIMP-1 high expressing cells and are present in the STRING TIMP-1 interaction network. A previous 293 AP1 reporter cell line study showed that exposure to recombinant TIMP-1 resulted in elevated level of AP-1 activity, suggesting that TIMP-1 can activate this transcription factor complex either directly or indirectly.19 While the PI3K/Akt/NF-kβ signaling pathway has also been proposed as a candidate in another TIMP-1 high related TOP2 inhibitor resistant model,11 we did not observe a differential expression of NF-kβ in TIMP1 low and high expressing cells. This does not exclude that the protein could possess different activity in different cell lines.

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CONCLUSIONS

This study is the first global, unbiased, and quantitative proteomic investigation of low and high TIMP-1 expressing breast cancer cells, and it shows for the first time that overexpression of TIMP-1 results in up-regulation and hyperphosphorylation of a number of proteins being either directly or indirectly associated with drug resistance mechanisms. Of particular interest is the observed association between high TIMP-1 protein expression and resistance to topoisomerase inhibitors, which is likely due to the observed up-regulation and/or hyper-phosphorylation of the three major DNA topoisomerases, TOP1, TOP2A, and TOP2B. However, the exact relationship between topoisomrase phosphorylation and sensitivity to topoisomerase inhibitors remains to be elucidated. In particular, it should be tested whether phosphorylated topoisomerases are likely candidates as biomarkers for topoisomerase inhibitor resistance in TIMP-1 high expressing tumors. Importantly, our data from the experimental model system recapitulates fundamental aspects of increased resistance to topoisomerase inhibitors observed in vivo for TIMP-1 overexpressing cells. 4148



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Di, L. A.; Albain, K.; Swain, S.; Piccart, M.; Pritchard, K. Comparisons between different polychemotherapy regimens for early breast cancer: meta-analyses of long-term outcome among 100,000 women in 123 randomised trials. Lancet 2012, 379 (9814), 432−444. (3) Egeblad, M.; Werb, Z. New functions for the matrix metalloproteinases in cancer progression. Nat. Rev. Cancer 2002, 2 (3), 161−174. (4) Stetler-Stevenson, W. G. Tissue inhibitors of metalloproteinases in cell signaling: metalloproteinase-independent biological activities. Sci. Signaling 2008, 1 (27), re6. (5) Wurtz, S. O.; Schrohl, A. S.; Sorensen, N. M.; Lademann, U.; Christensen, I. J.; Mouridsen, H.; Brunner, N. Tissue inhibitor of metalloproteinases-1 in breast cancer. Endocr.-Relat. Cancer 2005, 12 (2), 215−227. (6) Airola, K.; Karonen, T.; Vaalamo, M.; Lehti, K.; Lohi, J.; Kariniemi, A. L.; Keski-Oja, J.; Saarialho-Kere, U. K. Expression of collagenases-1 and −3 and their inhibitors TIMP-1 and −3 correlates with the level of invasion in malignant melanomas. Br. J. Cancer 1999, 80 (5−6), 733−743. (7) Liu, X. W.; Bernardo, M. M.; Fridman, R.; Kim, H. R. Tissue inhibitor of metalloproteinase-1 protects human breast epithelial cells against intrinsic apoptotic cell death via the focal adhesion kinase/ phosphatidylinositol 3-kinase and MAPK signaling pathway. J. Biol. Chem. 2003, 278 (41), 40364−40372. (8) Liu, X. W.; Taube, M. E.; Jung, K. K.; Dong, Z.; Lee, Y. J.; Roshy, S.; Sloane, B. F.; Fridman, R.; Kim, H. R. Tissue inhibitor of metalloproteinase-1 protects human breast epithelial cells from extrinsic cell death: a potential oncogenic activity of tissue inhibitor of metalloproteinase-1. Cancer Res. 2005, 65 (3), 898−906. (9) Jung, K. K.; Liu, X. W.; Chirco, R.; Fridman, R.; Kim, H. R. Identification of CD63 as a tissue inhibitor of metalloproteinase-1 interacting cell surface protein. EMBO J. 2006, 25 (17), 3934−3942. (10) Wang, T.; Lv, J. H.; Zhang, X. F.; Li, C. J.; Han, X.; Sun, Y. J. Tissue inhibitor of metalloproteinase-1 protects MCF-7 breast cancer cells from paclitaxel-induced apoptosis by decreasing the stability of cyclin B1. Int. J. Cancer 2010, 126 (2), 362−370. (11) Fu, Z. Y.; Lv, J. H.; Ma, C. Y.; Yang, D. P.; Wang, T. Tissue inhibitor of metalloproteinase-1 decreased chemosensitivity of MDA435 breast cancer cells to chemotherapeutic drugs through the PI3K/ AKT/NF-small ka, CyrillicB pathway. Biomed. Pharmacother. 2011, 65 (3), 163−167. (12) Willemoe, G. L.; Hertel, P. B.; Bartels, A.; Jensen, M. B.; Balslev, E.; Rasmussen, B. B.; Mouridsen, H.; Ejlertsen, B.; Brunner, N. Lack of TIMP-1 tumour cell immunoreactivity predicts effect of adjuvant anthracycline-based chemotherapy in patients (n = 647) with primary breast cancer. A Danish Breast Cancer Cooperative Group Study. Eur. J. Cancer 2009, 45 (14), 2528−2536. (13) Ejlertsen, B.; Jensen, M. B.; Nielsen, K. V.; Balslev, E.; Rasmussen, B. B.; Willemoe, G. L.; Hertel, P. B.; Knoop, A. S.; Mouridsen, H. T.; Brunner, N. HER2, TOP2A, and TIMP-1 and responsiveness to adjuvant anthracycline-containing chemotherapy in high-risk breast cancer patients. J. Clin. Oncol. 2010, 28 (6), 984−990. (14) Sorensen, N. M.; Bystrom, P.; Christensen, I. J.; Berglund, A.; Nielsen, H. J.; Brunner, N.; Glimelius, B. TIMP-1 is significantly associated with objective response and survival in metastatic colorectal cancer patients receiving combination of irinotecan, 5-fluorouracil, and folinic acid. Clin. Cancer Res. 2007, 13 (14), 4117−4122. (15) Frederiksen, C.; Qvortrup, C.; Christensen, I. J.; Glimelius, B.; Berglund, A.; Jensen, B. V.; Nielsen, S. E.; Keldsen, N.; Nielsen, H. J.; Brunner, N.; Pfeiffer, P. Plasma TIMP-1 levels and treatment outcome in patients treated with XELOX for metastatic colorectal cancer. Ann. Oncol. 2011, 22 (2), 369−375. (16) Schrohl, A. S.; Christensen, I. J.; Pedersen, A. N.; Jensen, V.; Mouridsen, H.; Murphy, G.; Foekens, J. A.; Brunner, N.; HoltenAndersen, M. N. Tumor tissue concentrations of the proteinase inhibitors tissue inhibitor of metalloproteinases-1 (TIMP-1) and plasminogen activator inhibitor type 1 (PAI-1) are complementary in determining prognosis in primary breast cancer. Mol. Cell. Proteomics 2003, 2 (3), 164−172.

ASSOCIATED CONTENT

S Supporting Information *

Additonal experimental details as described in the text. This material is available free of charge via the Internet at http:// pubs.acs.org. Accession Codes

All the MS raw data associated with this manuscript can be found at http://cpr1.sund.ku.dk/datasets/proteomics. The name of the zipfile containing all the raw files is “TIMP1_in_relation_to_drug_resistance_in_breast_cancer_cells”. The password is pTOP_2b.

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AUTHOR INFORMATION

Corresponding Author

*(J.V.O.) E-mail: [email protected]. Telephone: +45 35 32 50 22. Fax: +45 35 32 50 01. (J.S.) E-mail: Stenvang@sund. ku.dk. Telephone: +45 35 33 37 53. Fax: +45 35 33 27 55. Author Contributions #

O.H., S.M., L.F., N.B., J.V.O., and J.S.: Shared authorship.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors would like to thank Mr. Anatoliy Dmytriyev for uploading the raw data, and Dr. Christian D. Kelstrup and Dr. Sebastian A. Wagner for helpful discussions. Ms. Vibeke Jensen is acknowledged for technical assistance on cell culture and TIMP-1 analysis. We thank the Danish Natural Research Foundation, The Danish Strategic Research Council (TIPCAT), The Medical Research Council, The Danish Cancer Society, The Danish Center for Translational Breast Cancer Research, and A Race Against Breast Cancer for financial support. Work at the Center for Protein Research is supported by a generous donation from the Novo Nordisk Foundation. Part of this work has been funded by PRIME-XS a seventh Framework Programme of the European Union (Contract No. 262067- PRIME-XS). C.F. is supported by Marie Curie and EMBO postdoctoral fellowships.

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ABBREVIATIONS TIMP, tissue inhibitor of metalloproteinase; SILAC, stable isotope labeling by amino acids in cell culture; TOP, topoisomerase; FAK, focal adhesion kinase; ERK, extracellular signal-regulated kinase; PTM, post-translational modifications; TWT-III, TIMP-1 wild type murine fibrosarcoma cell lines; TKO-III, TIMP-1 knock out murine fibrosarcoma cell lines; CAA, chloroacetamide; 2,5-DHB, 2,5-dihydroxybenzoic acid; HCD, higher energy collisional dissociation; IPI, International Protein Index; LDH, lactate dehydrogenase; 2D PAGE, twodimensional PAGE; lambda PP, lambda protein phosphatase; hsp74, Heat shock 70 kDa protein 4; CLU, clusterin; mTOR, mammalian target of rapamycin; AP-1, activator protein-1; PLK1, polo-like kinase 1

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REFERENCES

(1) Early Breast Cancer Trialists’ Collaborative Group (EBCTCG). Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet 2005, 365 (9472), 1687−1717. (2) Peto, R.; Davies, C.; Godwin, J.; Gray, R.; Pan, H. C.; Clarke, M.; Cutter, D.; Darby, S.; McGale, P.; Taylor, C.; Wang, Y. C.; Bergh, J.; 4149



Article

(17) Wurtz, S. O.; Christensen, I. J.; Schrohl, A. S.; Mouridsen, H.; Lademann, U.; Jensen, V.; Brunner, N. Measurement of the uncomplexed fraction of tissue inhibitor of metalloproteinases-1 in the prognostic evaluation of primary breast cancer patients. Mol. Cell. Proteomics 2005, 4 (4), 483−491. (18) Birgisson, H.; Nielsen, H. J.; Christensen, I. J.; Glimelius, B.; Brunner, N. Preoperative plasma TIMP-1 is an independent prognostic indicator in patients with primary colorectal cancer: a prospective validation study. Eur. J. Cancer 2010, 46 (18), 3323−3331. (19) Bigelow, R. L.; Williams, B. J.; Carroll, J. L.; Daves, L. K.; Cardelli, J. A. TIMP-1 overexpression promotes tumorigenesis of MDA-MB-231 breast cancer cells and alters expression of a subset of cancer promoting genes in vivo distinct from those observed in vitro. Breast Cancer Res. Treat. 2009, 117 (1), 31−44. (20) Stilley, J. A.; Sharpe-Timms, K. L. TIMP1 contributes to ovarian anomalies in both an MMP-dependent and -independent manner in a rat model. Biol. Reprod. 2012, 86 (2), 47. (21) Egea, V.; Zahler, S.; Rieth, N.; Neth, P.; Popp, T.; Kehe, K.; Jochum, M.; Ries, C. Tissue inhibitor of metalloproteinase-1 (TIMP1) regulates mesenchymal stem cells through let-7f microRNA and Wnt/beta-catenin signaling. Proc. Natl. Acad. Sci. U.S.A. 2012, 109 (6), E309−E316. (22) Schrohl, A. S.; Meijer-van Gelder, M. E.; Holten-Andersen, M. N.; Christensen, I. J.; Look, M. P.; Mouridsen, H. T.; Brunner, N.; Foekens, J. A. Primary tumor levels of tissue inhibitor of metalloproteinases-1 are predictive of resistance to chemotherapy in patients with metastatic breast cancer. Clin. Cancer Res. 2006, 12 (23), 7054− 7058. (23) Sorensen, N. M.; Schrohl, A. S.; Jensen, V.; Christensen, I. J.; Nielsen, H. J.; Brunner, N. Comparative studies of tissue inhibitor of metalloproteinases-1 in plasma, serum and tumour tissue extracts from patients with primary colorectal cancer. Scand. J. Gastroenterol. 2008, 43 (2), 186−191. (24) Cox, J.; Mann, M. Quantitative, high-resolution proteomics for data-driven systems biology. Annu. Rev. Biochem. 2011, 80, 273−299. (25) Ong, S. E.; Blagoev, B.; Kratchmarova, I.; Kristensen, D. B.; Steen, H.; Pandey, A.; Mann, M. Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell. Proteomics 2002, 1 (5), 376−386. (26) Jaattela, M.; Benedict, M.; Tewari, M.; Shayman, J. A.; Dixit, V. M. Bcl-x and Bcl-2 inhibit TNF and Fas-induced apoptosis and activation of phospholipase A2 in breast carcinoma cells. Oncogene 1995, 10 (12), 2297−2305. (27) Cox, J.; Matic, I.; Hilger, M.; Nagaraj, N.; Selbach, M.; Olsen, J. V.; Mann, M. A practical guide to the MaxQuant computational platform for SILAC-based quantitative proteomics. Nat. Protoc. 2009, 4 (5), 698−705. (28) Davidsen, M. L.; Wurtz, S. O.; Romer, M. U.; Sorensen, N. M.; Johansen, S. K.; Christensen, I. J.; Larsen, J. K.; Offenberg, H.; Brunner, N.; Lademann, U. TIMP-1 gene deficiency increases tumour cell sensitivity to chemotherapy-induced apoptosis. Br. J. Cancer 2006, 95 (8), 1114−1120. (29) Macek, B.; Mann, M.; Olsen, J. V. Global and site-specific quantitative phosphoproteomics: principles and applications. Annu. Rev. Pharmacol. Toxicol. 2009, 49, 199−221. (30) Olsen, J. V.; Macek, B. High accuracy mass spectrometry in large-scale analysis of protein phosphorylation. Methods Mol. Biol. 2009, 492, 131−142. (31) Olsen, J. V.; Schwartz, J. C.; Griep-Raming, J.; Nielsen, M. L.; Damoc, E.; Denisov, E.; Lange, O.; Remes, P.; Taylor, D.; Splendore, M.; Wouters, E. R.; Senko, M.; Makarov, A.; Mann, M.; Horning, S. A dual pressure linear ion trap Orbitrap instrument with very high sequencing speed. Mol. Cell. Proteomics 2009, 8 (12), 2759−2769. (32) 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.

(33) Olsen, J. V.; Macek, B.; Lange, O.; Makarov, A.; Horning, S.; Mann, M. Higher-energy C-trap dissociation for peptide modification analysis. Nat. Methods 2007, 4 (9), 709−712. (34) Cox, J.; Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 2008, 26 (12), 1367−1372. (35) Olsen, J. V.; Blagoev, B.; Gnad, F.; Macek, B.; Kumar, C.; Mortensen, P.; Mann, M. Global, in vivo, and site-specific phosphorylation dynamics in signaling networks. Cell 2006, 127 (3), 635−648. (36) Szklarczyk, D.; Franceschini, A.; Kuhn, M.; Simonovic, M.; Roth, A.; Minguez, P.; Doerks, T.; Stark, M.; Muller, J.; Bork, P.; Jensen, L. J.; von, M. C. The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Res. 2011, 39 (Database issue), D561−D568. (37) von, M. C.; Jensen, L. J.; Snel, B.; Hooper, S. D.; Krupp, M.; Foglierini, M.; Jouffre, N.; Huynen, M. A.; Bork, P. STRING: known and predicted protein-protein associations, integrated and transferred across organisms. Nucleic Acids Res. 2005, 33 (Database issue), D433− D437. (38) Taboureau, O.; Nielsen, S. K.; Audouze, K.; Weinhold, N.; Edsgard, D.; Roque, F. S.; Kouskoumvekaki, I.; Bora, A.; Curpan, R.; Jensen, T. S.; Brunak, S.; Oprea, T. I. ChemProt: a disease chemical biology database. Nucleic Acids Res. 2011, 39 (Database issue), D367− D372. (39) Knox, C.; Law, V.; Jewison, T.; Liu, P.; Ly, S.; Frolkis, A.; Pon, A.; Banco, K.; Mak, C.; Neveu, V.; Djoumbou, Y.; Eisner, R.; Guo, A. C.; Wishart, D. S. DrugBank 3.0: a comprehensive resource for ’omics’ research on drugs. Nucleic Acids Res. 2011, 39 (Database issue), D1035−D1041. (40) Smoot, M. E.; Ono, K.; Ruscheinski, J.; Wang, P. L.; Ideker, T. Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 2011, 27 (3), 431−432. (41) Warsow, G.; Greber, B.; Falk, S. S.; Harder, C.; Siatkowski, M.; Schordan, S.; Som, A.; Endlich, N.; Scholer, H.; Repsilber, D.; Endlich, K.; Fuellen, G. ExprEssence–revealing the essence of differential experimental data in the context of an interaction/regulation net-work. BMC Syst. Biol. 2010, 4, 164. (42) Colaert, N.; Helsens, K.; Martens, L.; Vandekerckhove, J.; Gevaert, K. Improved visualization of protein consensus sequences by iceLogo. Nat. Methods 2009, 6 (11), 786−787. (43) Linding, R.; Jensen, L. J.; Ostheimer, G. J.; van Vugt, M. A.; Jorgensen, C.; Miron, I. M.; Diella, F.; Colwill, K.; Taylor, L.; Elder, K.; Metalnikov, P.; Nguyen, V.; Pasculescu, A.; Jin, J.; Park, J. G.; Samson, L. D.; Woodgett, J. R.; Russell, R. B.; Bork, P.; Yaffe, M. B.; Pawson, T. Systematic discovery of in vivo phosphorylation networks. Cell 2007, 129 (7), 1415−1426. (44) Miller, M. L.; Jensen, L. J.; Diella, F.; Jorgensen, C.; Tinti, M.; Li, L.; Hsiung, M.; Parker, S. A.; Bordeaux, J.; Sicheritz-Ponten, T.; Olhovsky, M.; Pasculescu, A.; Alexander, J.; Knapp, S.; Blom, N.; Bork, P.; Li, S.; Cesareni, G.; Pawson, T.; Turk, B. E.; Yaffe, M. B.; Brunak, S.; Linding, R. Linear motif atlas for phosphorylation-dependent signaling. Sci. Signaling 2008, 1 (35), ra2. (45) Moller, S. N.; Dowell, B. L.; Stewart, K. D.; Jensen, V.; Larsen, L.; Lademann, U.; Murphy, G.; Nielsen, H. J.; Brunner, N.; Davis, G. J. Establishment and characterization of 7 new monoclonal antibodies to tissue inhibitor of metalloproteinases-1. Tumour Biol. 2005, 26 (2), 71−80. (46) Holten-Andersen, M. N.; Murphy, G.; Nielsen, H. J.; Pedersen, A. N.; Christensen, I. J.; Hoyer-Hansen, G.; Brunner, N.; Stephens, R. W. Quantitation of TIMP-1 in plasma of healthy blood donors and patients with advanced cancer. Br. J. Cancer 1999, 80 (3−4), 495−503. (47) Cabezon, T.; Gromova, I.; Gromov, P.; Serizawa, R.; Timmermans, W., V; Kroman, N.; Celis, J. E.; Moreira, J. M. Proteomic Profiling of Triple-negative Breast Carcinomas in Combination With a Three-tier Orthogonal Technology Approach Identifies Mage-A4 as Potential Therapeutic Target in Estrogen Receptor Negative Breast Cancer. Mol. Cell. Proteomics 2013, 12 (2), 381−394. 4150



Article

(48) Pines, A.; Kelstrup, C. D.; Vrouwe, M. G.; Puigvert, J. C.; Typas, D.; Misovic, B.; de, G. A.; von, S. L.; van de Water, B.; Danen, E. H.; Vrieling, H.; Mullenders, L. H.; Olsen, J. V. Global phosphoproteome profiling reveals unanticipated networks responsive to cisplatin treatment of embryonic stem cells. Mol. Cell. Biol. 2011, 31 (24), 4964−4977. (49) de Godoy, L. M.; Olsen, J. V.; Cox, J.; Nielsen, M. L.; Hubner, N. C.; Frohlich, F.; Walther, T. C.; Mann, M. Comprehensive massspectrometry-based proteome quantification of haploid versus diploid yeast. Nature 2008, 455 (7217), 1251−1254. (50) Selbach, M.; Schwanhausser, B.; Thierfelder, N.; Fang, Z.; Khanin, R.; Rajewsky, N. Widespread changes in protein synthesis induced by microRNAs. Nature 2008, 455 (7209), 58−63. (51) Lambert, E.; Bridoux, L.; Devy, J.; Dasse, E.; Sowa, M. L.; Duca, L.; Hornebeck, W.; Martiny, L.; Petitfrere-Charpentier, E. TIMP-1 binding to proMMP-9/CD44 complex localized at the cell surface promotes erythroid cell survival. Int. J. Biochem. Cell Biol. 2009, 41 (5), 1102−1115. (52) Lourda, M.; Trougakos, I. P.; Gonos, E. S. Development of resistance to chemotherapeutic drugs in human osteosarcoma cell lines largely depends on up-regulation of Clusterin/Apolipoprotein J. Int. J. Cancer 2007, 120 (3), 611−622. (53) Mizutani, K.; Matsumoto, K.; Hasegawa, N.; Deguchi, T.; Nozawa, Y. Expression of clusterin, XIAP and survivin, and their changes by camptothecin (CPT) treatment in CPT-resistant PC-3 and CPT-sensitive LNCaP cells. Exp. Oncol. 2006, 28 (3), 209−215. (54) Wang, Y. H.; Huang, M. L. Organogenesis and tumorigenesis: insight from the JAK/STAT pathway in the Drosophila eye. Dev. Dyn. 2010, 239 (10), 2522−2533. (55) Bucher, N.; Britten, C. D. G2 checkpoint abrogation and checkpoint kinase-1 targeting in the treatment of cancer. Br. J. Cancer 2008, 98 (3), 523−528. (56) Gaur, S.; Chen, L.; Yang, L.; Wu, X.; Un, F.; Yen, Y. Inhibitors of mTOR overcome drug resistance from topoisomerase II inhibitors in solid tumors. Cancer Lett. 2011, 311 (1), 20−28. (57) Ubersax, J. A.; Ferrell, J. E., Jr. Mechanisms of specificity in protein phosphorylation. Nat. Rev. Mol. Cell Biol. 2007, 8 (7), 530− 541. (58) Alborzinia, H.; Can, S.; Holenya, P.; Scholl, C.; Lederer, E.; Kitanovic, I.; Wolfl, S. Real-time monitoring of cisplatin-induced cell death. PLoS One 2011, 6 (5), e19714. (59) Li, G.; Fridman, R.; Kim, H. R. Tissue inhibitor of metalloproteinase-1 inhibits apoptosis of human breast epithelial cells. Cancer Res. 1999, 59 (24), 6267−6275. (60) Ackerman, P.; Glover, C. V.; Osheroff, N. Phosphorylation of DNA topoisomerase II by casein kinase II: modulation of eukaryotic topoisomerase II activity in vitro. Proc. Natl. Acad. Sci. U.S.A. 1985, 82 (10), 3164−3168. (61) Bandyopadhyay, K.; Gjerset, R. A. Protein kinase CK2 is a central regulator of topoisomerase I hyperphosphorylation and camptothecin sensitivity in cancer cell lines. Biochemistry 2011, 50 (5), 704−714. (62) Hackbarth, J. S.; Galvez-Peralta, M.; Dai, N. T.; Loegering, D. A.; Peterson, K. L.; Meng, X. W.; Karnitz, L. M.; Kaufmann, S. H. Mitotic phosphorylation stimulates DNA relaxation activity of human topoisomerase I. J. Biol. Chem. 2008, 283 (24), 16711−16722. (63) Ritter, L. M.; Garfield, S. H.; Thorgeirsson, U. P. Tissue inhibitor of metalloproteinases-1 (TIMP-1) binds to the cell surface and translocates to the nucleus of human MCF-7 breast carcinoma cells. Biochem. Biophys. Res. Commun. 1999, 257 (2), 494−499. (64) Baselga, J. Targeting the phosphoinositide-3 (PI3) kinase pathway in breast cancer. Oncologist 2011, 16 (Suppl 1), 12−19. (65) McCubrey, J. A.; Steelman, L. S.; Chappell, W. H.; Abrams, S. L.; Wong, E. W.; Chang, F.; Lehmann, B.; Terrian, D. M.; Milella, M.; Tafuri, A.; Stivala, F.; Libra, M.; Basecke, J.; Evangelisti, C.; Martelli, A. M.; Franklin, R. A. Roles of the Raf/MEK/ERK pathway in cell growth, malignant transformation and drug resistance. Biochim. Biophys. Acta 2007, 1773 (8), 1263−1284.

(66) Hayakawa, T.; Yamashita, K.; Tanzawa, K.; Uchijima, E.; Iwata, K. Growth-promoting activity of tissue inhibitor of metalloproteinases1 (TIMP-1) for a wide range of cells. A possible new growth factor in serum. FEBS Lett. 1992, 298 (1), 29−32. (67) Luparello, C.; Avanzato, G.; Carella, C.; Pucci-Minafra, I. Tissue inhibitor of metalloprotease (TIMP)-1 and proliferative behaviour of clonal breast cancer cells. Breast Cancer Res. Treat. 1999, 54 (3), 235− 244. (68) Peng, L.; Yanjiao, M.; Ai-guo, W.; Pengtao, G.; Jianhua, L.; Ju, Y.; Hongsheng, O.; Xichen, Z. A fine balance between CCNL1 and TIMP1 contributes to the development of breast cancer cells. Biochem. Biophys. Res. Commun. 2011, 409 (2), 344−349. (69) Bjerre, C.; Knoop, A.; Bjerre, K.; Larsen, M. S.; Henriksen, K. L.; Lyng, M. B.; Ditzel, H. J.; Rasmussen, B. B.; Brunner, N.; Ejlertsen, B.; Laenkholm, A. V. Association of tissue inhibitor of metalloproteinases1 and Ki67 in estrogen receptor positive breast cancer. Acta Oncol. 2013, 52 (1), 82−90. (70) Li, H.; Wang, Y.; Liu, X. Plk1-dependent phosphorylation regulates functions of DNA topoisomerase IIalpha in cell cycle progression. J. Biol. Chem. 2008, 283 (10), 6209−6221. (71) Nakajima, H.; Toyoshima-Morimoto, F.; Taniguchi, E.; Nishida, E. Identification of a consensus motif for Plk (Polo-like kinase) phosphorylation reveals Myt1 as a Plk1 substrate. J. Biol. Chem. 2003, 278 (28), 25277−25280. (72) Toyoshima-Morimoto, F.; Taniguchi, E.; Shinya, N.; Iwamatsu, A.; Nishida, E. Polo-like kinase 1 phosphorylates cyclin B1 and targets it to the nucleus during prophase. Nature 2001, 410 (6825), 215−220.

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