Differential Proteomic Profiling Identifies Novel Molecular Targets of Paclitaxel and Phytoagent Deoxyelephantopin against Mammary Adenocarcinoma Cells Wai-Leng Lee,†,‡,§ Tuan-Nan Wen,¶ Jeng-Yuan Shiau,‡ and Lie-Fen Shyur*,‡,§ Molecular and Biological Agricultural Sciences Program, Taiwan International Graduate Program, Taiwan, ROC, Agricultural Biotechnology Research Center, Academia Sinica, Taipei 115, Taiwan, ROC, Graduate Institute of Biotechnology, National Chung-Hsing University, Taichung 402, Taiwan, ROC, and Institute of Plant and Microbial Biology, Academia Sinica, Taipei 115, Taiwan, ROC Received June 22, 2009
A major germacranolide sesquiterpene lactone, deoxyelephantopin, identified from Elephantopus scaber L. (known as “Didancao” in Chinese medicine) showed significant antitumor growth and antimetastatic effect on murine mammary adenocarcinoma TS/A cells in vitro and in vivo in mice. Deoxyelephantopin exhibited a superior effect to that of the paclitaxel in prolonging median survival time of tumor-bearing animals in our recent study. To investigate the molecular mechanisms underlying the difference in efficacy between deoxyelephantopin and paclitaxel, we used 2-D DIGE and LC-ESI-MS/MS to profile proteins differentially expressed in the nucleus and cytoplasm of TS/A cells and used the MetaCore database to determine the functional protein networks affected by both treatments. Deoxyelephantopin and paclitaxel treatment produced regulation of molecules involved in proteolysis and calcium ion transport, suggesting the possible effects of both drugs on proteasome and endoplasmic reticulum machinery in TS/A cells. Western blot analysis of marker proteins (e.g., PDI, GRP78, TXND5, caspase12, caspase-3 and PARP) further verified that induction of endoplasmic reticulum stress was associated with apoptosis induced by both deoxyelephantopin and paclitaxel, but only deoxyelephantopin inhibited proteasomal proteolysis in TS/A cells. The novel effects on targeting ER machinery and suppressing proteasome activity suggest the great potential of deoxyelephantopin for mammary cancer therapy. Keywords: Deoxyelephantopin • paclitaxel • mammary adenocarcinoma • DIGE 2-D electrophoresis • endoplasmic reticulum stress • apoptosis • proteasome inhibitor • therapeutic agents • TS/A cells
Introduction Breast cancer, by far the most common cancer among women, was responsible for 548 000 deaths worldwide in 2007.1,2 Following the introduction of modern strategies of early diagnosis with mammographic screening and postoperative adjuvant therapies, the survival rate among patients has improved greatly in recent years,3 but recurrent and metastatic breast tumor is still the leading cause of death among breast cancer patients. In management of metastatic breast cancer, hormonal therapy is effective in one-third (∼30%) of patients, but for those refractory to hormone treatment, cytotoxic chemotherapy is the treatment of choice. Among different established chemotherapeutic agents, taxanes are now considered the most active agents for the treatment.4 Paclitaxel (PTX), a diterpene alkaloid initially isolated from Taxus brevifolia, was the first taxane to show activity in breast cancer, where it targets β-tubulin to stabilize microtubule dynamics, * To whom correspondence should be addressed. Telephone (Fax): +8862-2651-5028. E-mail:
[email protected]. † Taiwan International Graduate Program. ‡ Agricultural Biotechnology Research Center, Academia Sinica. § National Chung-Hsing University. ¶ Institute of Plant and Microbial Biology, Academia Sinica. 10.1021/pr900543e
2010 American Chemical Society
subsequently inducing apoptosis of cancer cells.4,5 Nevertheless, emerging clinical resistance to taxanes following their extensive use in chemotherapy worldwide has attenuated the effectiveness of many of these agents, including PTX, in the treatment of breast cancer.6 The use of cancer preventative agents in combination with chemotherapy or radiotherapy has been suggested to provide more effective treatment of cancer. As a result, the potential chemopreventive or chemotherapeutic properties of various plant-derived phytocompounds have attracted a great deal of interest, including the characterization of their underlying molecular mechanisms.7 One such potent antitumor phytocompound, the major germacranolide sesquiterpene lactone, deoxyelephantopin (DET) from the traditional medicinal herb Elephantopus scaber L.8,9 was reported to repress nuclear factor-κB (NF-κB) activation10 and to be a partial agonist of the gamma isotype of the peroxisome proliferator-activated receptor, PPARγ.11 However, the anticancer effect of DET in HeLa cells was shown to be independent of the PPARγ pathway.11 Beside inhibition of tumor growth, DET was also found in our laboratory to suppress mammary carcinoma metastasis in vitro and in vivo.12 A comprehensive investigation Journal of Proteome Research 2010, 9, 237–253 237 Published on Web 11/09/2009
research articles
Lee et al.
Figure 1. Effect of DET and PTX on TS/A cell viability. (A) The chemical structure of deoxyelephantopin (DET) and paclitaxel (PTX). (B) TS/A and M10 cells were treated with indicated concentrations of DET and PTX for 24 and 48 h, and cell viability was determined by MTT assay. For TS/A cells, cell viability was also determined with 6- and 12-h treatment. (C) Morphological change in 24 h vehicle (0.05% DMSO), DET (5 µM) and PTX (2 µM) treated TS/A cells (×400 magnification). Representative results of three independent experiments are shown.
of the molecular regulation of DET in cancer cells was needed to shed light on these novel anticancer and antimetastatic functions. Two-dimensional (2-D) gel electrophoresis, a powerful tool in proteomics used for protein separation and abundance analysis is one of the core technologies used in proteomics to dissect the mechanisms of drug actions that modulate signal transduction pathways.13 In the present study, we investigated the comparative proteome of DET- and PTX-treated TS/A cells, a highly metastatic mouse mammary adenocarcinoma cell line14 used for bioefficacy studies in our laboratory by using mainly Ettan 2-D differential in-gel electrophoresis (DIGE) system for protein 2-D electrophoresis13 and LC-ESI-MS/MS for protein identification. The possible interactions between the identified proteins and the functional protein networks that were affected by treatments were analyzed using a Web-based database, MetaCore.15 DET was shown to suppress proteasome activity and induce ER stress in TS/A cancer cells, giving its great potential as a novel therapeutic agent for mammary cancer. With this study, a comprehensive and in-depth investigation of DET- and PTX-induced spatial or temporal cellular regulations at protein level in mammary cancer cells was presented. 238
Journal of Proteome Research • Vol. 9, No. 1, 2010
Materials and Methods Isolation and Structure Elucidation of DET. Approximately 5.0 kg of dried whole E. scaber L. (voucher specimen ES001 deposited in the Agricultural Biotechnology Research Center, Academia Sinica, Taiwan) was extracted with boiling water for 2 h, and the crude extract partitioned with ethyl acetate (EtOAc). The EtOAc extract was chromatographed on a silica gel column using CHCl3/EtOAc eluting solvents to give 11 fractions. Fraction 5 obtained by eluting with CHCl3/EtOAc (6: 1, v/v), which exhibited anticancer cell proliferative activity, was then purified on a RP-C18 silica gel column eluted with 50% methanol to obtain pure white crystals of deoxyelephantopin (DET, Figure 1A). The structure of DET was elucidated by electrospray ionization mass spectrometry (ESI-MS) and 1H and 13C NMR spectrometry and confirmed by comparison of the data with previously published results.161H and 13C NMR spectra were recorded on a Bru ¨ ker ADVANCE 500 AV spectrometer, and ESI-MS data was recorded using a ThermoFinnigan LCQ in positive ion mode. Chemicals. PTX, carbobenzoxyl-L-leucyl-L-leucyl-L-leucinal (MG132), thapsigargin (TG), 3-(4,5-dimethylthiazol-2-yl)-2,5diphenyltetrazolium bromide (MTT), and proteasome fluorogenic substrates were purchased from Sigma-Aldrich. Cell
Novel Molecular Targets of Mammary Carcinoma Treatments compartment kit for nuclear and cytoplasmic protein extraction was supplied by QIAGEN. Silica gel (230-400 mesh) and silica gel 60 F254 TLC and RP-18 F254 TLC plates were purchased from Merck (Germany). RP-18 silica gel (75C18-OPN) was from Cosmosil. All other chemicals and solvents were of reagent or HPLC grade. Primary antibodies against actin (Chemicon, Millipore), PSMG1 (Abgent), TXND5 (Abcam), poly(ADP-ribose) polymerase (PARP), cleaved caspase-3, caspase-12, phosphoPERK, phospho-GCN2, phospho-eIF2R, PDI, TERA, and PSA6 (Cell Signaling Technology) were used. All other antibodies were from Santa Cruz Biotechnology. All reagents used in 2-DE were purchased from Bio-Rad and GE Healthcare as listed. Cell Culture. TS/A cells, a murine mammary adenocarcinoma cell line, and H184B5F5/M10, a noncancerous human mammary epithelial cell line (ATCC), were grown in Dulbecco’s modified Eagle medium (DMEM, Life Technologies) and in Minimum Essential Medium, respectively, supplemented with 10% fetal bovine serum, 100 U/mL penicillin, and 100 µg/mL streptomycin (Invitrogen), in a humidified 5% CO2 incubator at 37 °C. Cytotoxicity Assay. TS/A cells were cultured in 96-well plates at a density of 1 × 104 cells/well and allowed to adhere overnight, and then treated for 6, 12, 24, and 48 h with vehicle (0.05% DMSO), DET or PTX at indicated concentrations. Cell growth was measured using the MTT-based colorimetric assay according to Chiang et al.17 Nuclear and Cytoplasmic Protein Extraction. TS/A cells (5 × 106 cells) were treated with 0.05% DMSO (vehicle, control), 5 µM DET and 2 µM PTX, respectively, for 6, 12, 24, and 48 h. After treatment, cells were trypsinized from culture flask, collected by centrifugation at 20 °C, and then washed with icecold PBS (50 mM NaH2PO4, 150 mM NaCl, pH 7.2). Nuclear and cytoplasmic protein extractions were done using Cell Compartment Kit (Qproteome, QIAGEN) according to the manufacturer’s protocol. Prior to 2-D DIGE, collected protein fractions were precipitated by the addition of 4 vol of ice-cold acetone on ice for 15 min and centrifugation at 12 000g for 10 min at 4 °C. Protein pellets were redissolved in CyDye labeling compatible lysis buffer (30 mM Tris, 7 M urea, 2 M thiourea, 4% CHAPS, pH 8.5) and protein concentrations were then determined using reducing agent compatible (RC) and detergent compatible (DC) colorimetric protein assay (Bio-Rad). DIGE Experimental Design. In this study, nuclear and cytoplasmic proteins of 12 individual lysate samples were obtained from 6, 12, 24, and 48 h DET-treated, PTX-treated and control TS/A cells, with three biological replicates to ensure the reproducibility of protein changes. Protein profile comparisons within these samples were performed across six DIGE gels in each electrophoresis. An internal standard pool with equal amounts of each protein sample was used to reduce intergel variation. Proteins in each sample were fluorescentlabeled according to the manufacturer’s protocol for minimal labeling (CyDye DIGE Fluor minimal dyes, GE Healthcare). To minimize dye-specific labeling artifacts, Cy3 and Cy5-labeling patterns were swapped between experimental replicates. The pooled internal standards were all Cy2-labeled. Fifty micrograms of protein of each sample was labeled with 400 pmol of dye on ice in the dark for 30 min. Reaction was quenched with 1 µg of 10 mM L-lysine for 10 min under the same conditions. DIGE 2-DE. Pair of Cy3 and Cy5-labeled samples (each containing 50 µg of protein) and 50 µg of the Cy2-labeled pooled standard were mixed and diluted with rehydration buffer (7 M urea, 2 M thiourea, 4% CHAPS, 0.18% ampholytes
research articles
pH 5-8, 0.02% ampholytes pH 8-10, 1% DTT and 0.005% bromophenol blue) to reach a final volume of 300 µL. The IPG strips (17 cm, pH 5-8 NL, Bio-Rad) were rehydrated passively in rehydration buffer for at least 11 h and then subjected to isoelectric focusing at 15 °C using a PROTEAN IEF system (BioRad), under the following conditions: 1 h at 150 V, 3 h at 300 V, gradient to 1500 V in 2 h, 3 h at 1500 V, gradient to 4000 V in 2 h, 3 h at 4000 V, gradient to 8000 V in 2 h and finally 3 h at 8000 V, for a total of 60 kVh. In preparation for the seconddimension electrophoresis run, the strips were equilibrated for 20 min in equilibration buffer (50 mM Tris-HCl pH 8.8, 6 M urea, 30% glycerol, 2% SDS and 0.002% BPB) with 1% DTT, then another 20 min in the same buffer supplemented with 2.5% iodoacetamide. Polyacrylamide gels (10-14% gradient) were cast in low fluorescence glass plates and proteins in equilibrated strips were resolved by Ettan Daltsix electrophoresis system (GE Healthcare) for approximately 4 h at 20 °C at 17 W/gel. Using a Typhoon 9400 laser scanner (GE Healthcare), images of differential labeled coresolved proteins were scanned (excitation/emission: 488/520 nm for Cy2-labeled images, 523/ 580 nm for Cy3-labeled images, 633/670 for Cy5-labeled images) directly from gels within the glass plates, and the acquired images were exported in XML format for the following data analysis. DIGE Image Analysis. DeCyder differential analysis software version 5.0 (GE Healthcare) was used in this study. For individual gel analysis, spots were detected, quantified and normalized according to the volume ratio of corresponding spots detected in the Cy2 image of the pooled-sample internal standard using the differential in-gel analysis (DIA) module. All normalized DIA data sets from 18 nuclear sample gels and 18 cytoplasmic sample gels were collectively analyzed employing the biological variation analysis (BVA) module, which enables matching of multiple images from different gels to provide statistical data on average abundance for each protein spot among the DIGE gels in the study. Student’s t-test and ANOVA analysis were used to assess the statistical significance of each calculation of abundance change. On the basis of a standardized average spot volume ratio, spots whose abundance showed a relative change of 1.5 times or greater (either increase or decrease) between control and treatment at 95% confidence level (p < 0.05) were considered to be significant. Those protein spots with significant relative change across 2 or more treatment time points were selected for further protein identification. In-Gel Trypsin Digestion. The protocol used for in-gel trypsin digestion of proteins was adapted from a method previously described.18 Briefly, the protein spots from 2-D gel were manually excised, cut into small pieces (∼0.5 mm3) and placed in Eppendorf tubes. The gel pieces were washed several times with solution containing 50% methanol and 5% acetic acid for 2-3 h, twice with a solution of 25 mM NH4HCO3 in 50% acetonitrile for 10 min each, and then dried in a vacuum centrifuge. Proteins in gel pieces were reduced with DTT and alkylated with iodoacetamide and digested with sequencing grade modified trypsin (Promega) for 12-16 h at 37 °C. The recovered tryptic peptides from gel pieces were redissolved in 10-20 µL of 0.1% formic acid for LC-ESI-MS/MS analysis. MS Analysis and Protein Identification. MS and protein identification were carried out in the Proteomics Core Facility of Institute of Plant and Microbial Biology, Academia Sinica, Taiwan. An LTQ linear ion trap mass spectrometer coupled with an online capillary liquid chromatography (LC) system from Journal of Proteome Research • Vol. 9, No. 1, 2010 239
research articles Thermo Fisher Scientific (San Jose, CA) was utilized for protein identification and analysis. The capillary LC system equipped with an autosampler and Surveyor pumps (Thermo Scientific), a C18 trap cartridge (Zobax 300SB-C18, 5 µm, 5 × 0.3 mm; Agilent Technologies, Santa Clara, CA) and a C18 reverse phase column (BioBasic C18, 75 µm × 10 cm, PicoFrit column; New Objective, Inc. Woburn, MA) was used to deliver solvent and tryptic peptides with a linear gradient from 5% to 40% of acetonitrile in 0.1% (v/v) formic acid for 40 min (or 60 min) at nanoflow (∼300 nL/min) rate. A total of 5-10 µL of the sample was loaded on the column. The PicoFrit column was coupled to a nanoelectrospray ionization source and MS data was acquired with a full MS scan followed by four MS/MS scans of the top four precursor ions from the MS scan. The MS scan was performed over the mass-to-charge (m/z) range of 300-2000 using the data-dependent data acquisition mode with a 180 s-dynamic exclusion enabled. Database Search. The acquired MS/MS data were analyzed using a SEQUEST search program (v. 28. BioWorks Browser 3.3, Thermo Fisher Scientific) against the M. musculus (mouse) genomic protein database (34 966 entries) downloaded from National Center for Biotechnology Information (NCBI database, Mouse Build 37, updated on April 5, 2007). Peak list data (DTA) used for database searching were generated from MS/MS spectra using an ion intensity threshold of 1000, a group scan of 1, a minimum group count of 1, a minimum ion threshold of 10, and a precursor tolerance of 1.4 atomic mass units (u) (extract_msn ver. 4.0, Thermo Fisher Scientific). The protein sequences in the database were indexed with trypsin digestion at both ends with 2 missed cleavages, 400-4000 molecular weight range, a variable modification of Met by oxidation and a static modification of Cys by carboxyamidomethylation. The DTA data were searched with 3.0 u (monoisotopic) of precursor peptide mass tolerance and 1.0 u (monoisotopic) of fragment mass tolerance. Matched peptides were accepted when they passed multiple filters, Xcorr g 1.5 for singly charged ions (z ) 1), 2.0 for doubly charged ions (z ) 2), 2.5 for triply charged ions (z ) 3), deltaCN g 0.1, and peptide probability e1 × 10-3. Matched proteins were accepted only when they had at least 2 distinct peptide hits. Peptide false discovery rates, < 0.001%, for all protein searches were calculated using Proteome Discoverer 1.0 (Thermo Fisher Scientific) with the decoy database search. Bioinformatics Analysis. The identified proteins and their respective biological functions or relationships were determined using the Entrez protein database (www.ncbi.nlm.nih.gov/ sites/entrez?db)protein) from NCBI. Protein-protein interaction networks were analyzed using MetaCore, a Webbased integrative software suite enabling data mining for protein interactions and associations.15 Protein networks for drug-responsive nuclear and cytoplasmic proteins in TS/A cells were built by the Analyze Network tool. The GI numbers of 18 DET- and 20 PTX-responsive nuclear proteins and 27 DET- and 14 PTX-responsive cytoplasmic proteins were uploaded to the MetaCore data manager. From the input list, a master global network was created, and then, the functionally focused subnetworks were further built from the master network. In parallel, the distribution of protein networks derived from timecourse data according to GeneGo processes (MetaCore database) was generated by use of the Compare Experiments Workflow tool. The GI numbers of DET- and PTX-responsive proteins with up- or downregulation on treatment at 6, 12, 24, and 24 h were accordingly uploaded to the MetaCore data 240
Journal of Proteome Research • Vol. 9, No. 1, 2010
Lee et al. manager. With use of Compare Experiments Workflow, input protein lists from these experiments were normalized, and the most significant GeneGo processes associated with compoundresponsive protein networks were obtained. Western Blotting. Proteins were resolved by 10-15% gradient SDS-PAGE, and electrophoretically transferred to PVDF membranes (Millipore) which were then soaked in blocking solution (TBS containing 0.1% Tween 20 and 3% w/v skimmed milk). The soaked membranes were incubated for at least 16 h with specific primary antibody, then washed and incubated with appropriate horseradish peroxidase (HRP)-conjugated secondary antibodies for 3 h at room temperature. Reacted protein bands were visualized using ECL detection reagents (Thermo Scientific). Reproducibility was confirmed in three independent experiments. Assay for Proteasome Activities. TS/A cells were treated with 0.05% DMSO (vehicle, control), 5 µM DET, 2 µM PTX or 1 µM MG132 for 0, 1, 3, 6, 12, 24, and 48 h. For the dose-dependent experiment, proteasome activities of cells treated at 6, 12, 24, and 48 h were examined by different DET concentrations ranging from 0 to 10 µM. Total cellular proteins of each treated sample were extracted according to Chiang et al.17 Protein aliquots (10 µg) were incubated at 37 °C for 90 min with 20 µM of fluorogenic peptide substrate, Suc-Leu-Leu-Val-Tyr-AMC for chymotrypsin-like, Z-Leu-Leu-Glu-AMC for peptidylglutamylpeptide hydrolyzing (PGPH), Z-Ala-Arg-Arg-AMC (Sigma) for trypsin-like activities, in 200 µL of assay buffer (20 mM TrisHCl, pH 8.0). After incubation, the reaction mixture was diluted with 200 µL of assay buffer followed by a measurement of the hydrolyzed 7-amido-4-methyl-coumarin (AMC) groups using a fluorometer (Wallac 1420 VICTOR3, Perkin-Elmer Life Science) with an excitation filter at 380 nm and an emission filter at 460 nm. Immunofluorescence and Microscopy. TS/A cells were seeded on 12-mm glass slips in 24-well plates for 24 h and then treated with vehicle (0.05% DMSO), DET (5 µM), PTX (2 µM) and TG (5 nM), respectively, for 12 h. Cells were fixed by 4% paraformaldehyde and then permeabilized with PBS containing 0.2% Triton X-100. After rinsing twice with PBS, the cells were blocked with PBS containing 3% bovine serum albumin and then stained with primary antibody (rabbit anti-PDI) at a dilution of 1:100 and secondary antibody (Cy3 conjugated goat anti-rabbit, Jackson ImmunoResearch Laboratories) at a dilution of 1:200. Nuclei were stained by DAPI. Fluorescence imaging was performed and captured on a Nikon Eclipse E800 microscope equipped with 40×/0.75 objective lens (Nikon) and an Olympus DP70 CCD camera. Images were processed with DP Controller software (Olympus, Japan). Statistical Analysis. All data were expressed as means ( standard deviations. Statistical significance of differences between treatments was determined by ANOVA. P < 0.05 was considered to be statistically significant.
Results Cytotoxic Effects of DET and PTX in Mammary Carcinoma Cells. The cytotoxicity of DET and PTX were examined by MTT assay. Different effects of DET and PTX on cell viability of M10 and TS/A cells were observed. As shown in Figure 1B, cell viability of treated TS/A cells was reduced in a concentrationdependent manner. The IC50 of DET was 3.04 µM for 48 h treatment, while PTX at 0.5-5 µM reduced cell viability by 30-40% over 24-48 h, relative to vehicle control (100%). At 5 µM, DET can confer a significant and differentiated effect on
Novel Molecular Targets of Mammary Carcinoma Treatments TS/A cell proliferation; therefore, we chose the dose and treatment times for the following proteomics study. For PTX treatment, no significant difference was observed in cell viability with PTX between 0.5 and 5 µM; therefore, we chose 2 µM as the median dose of PTX for the following experiment. Typical apoptotic cell features of rounded cell shape, shrunk size and blebbing were observed in TS/A cells treated with 5 µM DET or 2 µM PTX (Figure 1C). 2-DE Analysis of Vehicle Control, DET and PTX Treated Mammary Carcinoma Cells. Protein profiles of vehicle control (0.05% DMSO), DET- and PTX-treated TS/A cells were analyzed by 2-DE to examine drug-induced changes in different subcellular compartments (nucleus and cytoplasm) of cancer cells at various time points (6, 12, 24, 48 h). The procedure of DIGE used here is summarized in Supplementary Figure 1. Three rounds of six-plex 2-D DIGE were carried out for three biological replicates of nuclear and cytoplasmic fractions, respectively. As three individual images (Cy2-, Cy3-, and Cy5labeled samples) were obtained from each gel, 54 gel images in total were analyzed in each experiment using DeCyder software. With the DIA module, an average of 1800 protein spots were detected on each image of nuclear samples and 1929 from cytosolic samples. The number of detected spots in different gels was similar, with coefficient of variation (CV) of only 2.4% and 1.5% among images of nuclear and cytosolic samples, respectively. Gel images with DIA detected spots were then processed by BVA module for gel-to-gel spot matching. For each experiment, images from each time course treatment were matched to a single master image and common protein spots were identified. In nuclear samples, 1471, 1511, 1448, and 1494 spots were matched across images from 6, 12, 24, and 48 h treatment, and 1664, 1661, 1646, and 1605 spots were matched across images from 6, 12, 24, and 48 h treatments in cytosolic samples. The spot matching across images was consistent within repeated experiments, with CV of 13-15% and 11-12% for nuclear and cytosolic samples, respectively. The average abundances of identified common protein spots were quantified and those with relative changes in abundance greater than 1.5 times between control and treatment (up or down) at 95% confidence level (p < 0.05) were considered. The numbers of proteins with significantly and reproducibly increased or decreased abundance at different time point treatments of DET and PTX in TS/A cells are summarized (Supplementary Data 1). Identification of the Differentially Expressed Proteins. Protein spots with significant relative change across two or more treatment time points were selected for protein identification (ID) by tryptic in-gel digestion and LC-ESI-MS/MS analysis. Following a SEQUEST database search using MS/MS DTA, 46 proteins were identified as proteins responding to DET treatment (19 proteins in nucleus; 27 proteins in cytoplasm) and 35 (21 proteins in nucleus; 14 proteins in cytoplasm) to PTX treatment. The locations of these spots with protein ID are depicted in Supplemental Figure 2. Most spots showed a one spot to one protein ID, with the exception of enolase (ENO) and proliferation-associated protein 2G4 (PA2G4) which were identified with identical protein score (90) from the same protein spot in cytoplasmic fraction, both with increased level in response to both DET and PTX treatments, while several protein spots were identified as isoforms of tubulin (TB) in PTXtreated TS/A cells. In the nuclear proteome, a number of contiguous spots were identified as lamin A (LMNA), probably
research articles
due to post-translational modification of this protein. Details of the sequence identifier (GI) number, protein score, sequence coverage, theoretical and experimental pI value and molecular weight as well as average relative change at each treatment time point for all identified proteins are summarized in Table 1 for DET treatment and Table 2 for PTX treatment. In addition, identified proteins were categorized according to their involvement in different biological processes. Protein Database Search and Classification. The molecular function of each identified protein in TS/A cells treated with DET or PTX were classified on the basis of Gene Ontology search (http://amigo.geneontology.org; Figure 2). Regardless of the specific treatment, nearly one-third of the responsive proteins in the nucleus fraction (DET, 38%; PTX, 32%) were nucleic acid binding proteins. As the most abundant protein group in cells, it was not surprising that structural molecules were another category of proteins that responded to both DET and PTX treatment, in the nucleus as well as in cytoplasm. In PTX treatment, as much as 58% of affected cytoplasmic proteins were structural molecules. Other proteins in the cytoplasm of TS/A cells that responded to DET were of more diverse types, including various enzymes (transferases, ligases, peptidases and isomerases) and those involved in protein metabolism and homeostasis (proteasomal proteins, translation initiation factor, Golgi proteins and chaperones). Bioinformatic Analysis of Subcellular Treatment Responsive Protein Networks. MetaCore, a Web-based integrative software suite, was employed to mine the possible protein-protein interaction networks derived from 2-D DIGE experimentations. Using the Analyze Network tool, we analyzed the functional subnetworks derived from the original input list of 46 DET- and 35 PTX-responsive proteins as root nodes (summarized in Tables 3 and 4, respectively). The key domain of the subnetwork and the top related Gene Ontology (GO) processes are shown in these tables, and a Z-score was assigned to each network to indicate the saturation of the analyzed network by the original input protein list. In this analysis, the p-value indicates significance of the assigned GO process on the basis of assembly size as compared with the subnetworks derived from the input protein list. Proteins analyzed as key domains (hubs) of each protein network are proposed to be the prominent regulatory components in various cellular processes influenced by DET- and PTXtreatments. Eight DET-responsive nuclear proteins were found to form the most significant protein network (z-score ) 56.55; p e 1.13 × 10-7) with p53, RelA (p65 NF-κB subunit), estrogen receptor 1 and c-src as network hubs. This network may be associated with cellular stress responses, regulation of apoptosis and nucleocytoplasmic transport. The RelA(NFκB) protein likely plays an important role in these key domains of the network topology because we have demonstrated previously that DET can block the binding activity of RelA(NF-κB) to a cis-acting DNA element by directly hydrogen bounding with RelA protein.12 For DET-responsive cytosolic proteins, the most significant protein network (z-score ) 45.36; p e 2.86 × 10-7) with hsp90 (R and β) and c-myc as network hubs is probably involved in protein metabolic process and positive regulation of IL-2 production (Table 3). In PTX treatment, five nuclear proteins formed the highest ranked network (z-score ) 40.28) with a number of important proteins (RelA, iNOS, CTGF, p67-phox and R5β3-integrin) known to regulate cell proliferation (p ) 1.91 × 10-8) and calcium ion transport (p ) 9.35 × 10-9), as Journal of Proteome Research • Vol. 9, No. 1, 2010 241
research articles
Lee et al.
Table 1. Identification of Differentially Expressed Proteins in DET-Treated TS/A Cells relative fold changec ID
protein name
GI number
score
SC (%)a
matched peptideb
unique peptide
theoretical pI/MW (kDa)
experimental pI/MW (kDa)
6h
12 h
24 h
48 h
Up-Regulated Proteins in Nucleus Cell Cycle RFA2 Replication protein A 32 kDa subunit CDC2 Cell division control protein 2 homologue
110625961
60
23
6
6
5.4/29.4
5.8/30.0
nsd
ns
+1.85 +2.93
31542366
190
53
15
14
8.8/34.1
6.8/30.0
ns
ns
+1.67 +1.85
21704096
120
34
12
2
6.3/44.5
6.8/45.0
ns
ns
-1.83 +2.47
33667042
210
40
16
15
6.7/60.1
7.8/70.0
ns
ns
-1.82 +4.36
120
55
12
12
6.4/27.4
6.8/27.5
+2.03 +1.87 ns
266
48
26
1
5.0/89.3
5.5/100.0
+1.95 +2.61 +2.01 ns
110 160
16 40
9 16
7 12
5.3/67.3 4.9/53.7
5.8/77.5 5.3/57.5
ns ns +1.54 +1.96 +1.82 +2.03 ns +1.97
320
63
30
19
5.2/70.8
5.8/77.5
ns
ns
+1.71 +1.93
150 330
22 17
14 32
14 29
4.5/76.7 5.4/226.2
6.8/80.0 5.8/100.0
ns ns
ns ns
+1.55 +2.98 +4.56 +5.62
13384620
260
50
23
18
5.3/50.9
5.8/65.0
-2.25 -3.17 -1.79 ns
19527048
100
39
10
8
5.2/45.7
5.8/47.5
-2.55 -1.95 ns
ns
10946928
140
38
12
6
5.9/49.2
6.8/45.0
-1.92 -2.42 ns
ns
33667042
210
40
16
15
6.7/60.1
7.8/70.0
ns
Protein Catalytic Process/Proteolysis AMPM1 Methionyl 28202007 aminopeptidase 1
190
55
16
16
6.8/43.2
7.5/45.0
-2.25 -1.89 ns
360 150 470
49 54 22
32 13 46
6 0 45
6.6/74.3 5.2/41.7 5.1/285.2
6.8/70.0 5.5/50.0 5.8/135.0
-2.31 -1.73 -1.53 ns -1.68 -1.74 ns ns ns ns -2.48 -2.15
21281687
50
48
5
5
5.7/17.4
5.8/17.5
+4.21 +3.68 +2.67 +2.72
12963491
90
37
9
0
6.4/47.1
6.8/47.5
+1.71 +1.53 nsd
ns
90
27
9
9
6.4/43.7
6.8/47.5
+1.71 +1.53 ns
ns
Regulation of Transcription TADBP TAR DNA-binding protein 43 RNA Processing HNRPL Heterogeneous nuclear ribonucleoprotein L
Protein Catabolic Process/Proteolysis PSA6 Proteasome subunit 6755198 alpha type 6 TERA Transitional 30023842 endoplasmic reticulum ATPase Cytoskeleton/Membrane Organization LMNB2 Lamin-B2 113195686 VIME Vimentin 31982755 Stress Response HSP7C Heat shock cognate 71 31981690 kDa protein Angiogenesis NUCL Nucleolin MYH9 Myosin-9
84875537 114326446
ns
Down-Regulated Proteins in Nucleus RNA Processing HNRPK Heterogeneous nuclear ribonucleoprotein K HNRPF Heterogeneous nuclear ribonucleoprotein F HNRH1 Heterogeneous nuclear ribonucleoprotein H1 HNRPL Heterogeneous nuclear ribonucleoprotein L
Cytoskeleton/Membrane Organization LMNA Lamin A 50355692 Actin Actin 6671509 SPTA2 Spectrin alpha 2 115496850
ns
-1.82 +4.36
ns
Up-Regulated Proteins in Cytoplasm Cellular Metabolism DUT Deoxyuridine triphosphatase ENO Enolase protein
Protein Catalytic Process/Proteolysis PA2G4 Proliferation-associated 6755100 protein 2G4 242
Journal of Proteome Research • Vol. 9, No. 1, 2010
research articles
Novel Molecular Targets of Mammary Carcinoma Treatments Table 1. Continued
ID
protein name
GI number score SC (%)a
matched unique theoretical experimental peptideb peptide pI/MW (kDa) pI/MW (kDa)
relative fold changec 6h
12 h
24 h
48 h
Cytoskeleton/Membrane Organization TBCB Tubulin folding cofactor B NSF1C NSFL1 cofactor p47
13384976 38198665
100 130
39 52
10 13
10 8
4.9/27.3 5.0/40.9
5.4/30.0 5.1/47.5
+3.00 ns ns ns
ns +1.73 +1.63 +1.56
83921612
60
20
6
6
5.4/46.4
5.3/50.0
ns
+2.01 ns
31981086
80
34
8
0
4.9/26.8
5.1/32.5
+1.71 +2.00 +1.96 +1.67
31981722
370
54
35
33
4.9/72.4
5.1/77.5
ns
22122515
160
54
15
15
5.3/38.1
5.8/42.5
+1.50 ns
9845236
110
49
10
8
5.3/26.5
5.6/32.5
ns
6678794
120
38
12
10
6.2/43.4
7.1/45.0
-2.06 -2.03 ns
51492007
120
28
11
11
7.3/56.9
7.4/92.5
-1.53 ns
6754994
178
71
15
13
6.7/37.5
7.5/40.0
-1.97 -2.10 ns
ns
210 88 180
48 45 50
18 8 16
14 0 16
6.5/54.3 4.7/32.9 5.6/35.6
7.3/52.5 6.1/28.5 6.4/45.0
-1.72 -1.65 ns -1.53 -1.61 ns -2.13 -1.91 ns
ns ns ns
9506555
140
42
10
10
6.0/33.1
6.8/30.0
-2.01 -2.15 ns
ns
6755212
120
40
12
12
5.7/28.7
6.1/28.5
-1.53 -1.61 ns
ns
21312888
70
51
7
7
7.2/19.6
7.4/17.5
-2.13 -2.06 ns
ns
31981147
140
38
14
14
7.2/56.1
7.1/55.0
-1.59 -1.86 -2.12 -1.54
6679741 30519911 83921618
50 100 140
6 52 26
5 9 13
5 9 0
6.2/119.1 8.4/22.4 5.8/69.4
6.3/30.0 6.0/17.5 7.1/55.0
nsd -1.82 -2.47 -1.77 -2.06 -1.91 -2.03 ns -1.59 -1.86 -2.12 -1.54
125347376 458
20
41
40
5.6/280.3
6.8/110.0
-1.58 ns
21313080
130
53
13
13
5.2/33.3
5.5/30.0
-1.64 -1.51 ns
124248572 50 124517663 280
34 67
5 26
5 26
6.0/22.4 7.2/38.7
6.3/22.5 7.4/37.5
-1.82 -2.07 ns ns ns -1.67 -1.62 -1.65
Stress Responses TXND5 Thioredoxin domaincontaining protein 5 EFHD EF-hand domain-containing protein GRP78 78 kDa glucose-regulated protein AHSA1 Activator of HSP90 ATPase homologue 1
ns
ns
+2.30 +1.66 +1.60 ns
Down-Regulated Proteins in Cytoplasm Cell Cycle/Proliferation ARD1A N-acetyltransferase complex ARD1 subunit homologue A MP2K1 Mitogen-activated protein kinase kinase 1
-1.62 -1.65 ns ns
RNA Processing FUBP2 Far upstream element-binding protein 2 PCBP1 Poly(rC) binding protein 1
-1.55 ns
Translation SYWC RPS EIF3G
Tryptophanyl-tRNA synthetase 34328206 40S ribosomal protein 31560560 Eukaryotic translation initiation 31980808 factor 3, subunit G
Protein Catalytic Process/Proteolysis PSMG1 Proteasome assembly chaperone 1 PSME1 Proteasome activator complex subunit 1 UBE2C Ubiquitin-conjugating enzyme E2C AMPL Cytosol aminopeptidase Down-Regulated Proteins in Cytoplasm Cytoskeleton/Membrane Organization FAK1 Focal adhesion kinase 1 TAGL2 Transgelin-2 ERM Ezrin/Radixin/Moesin domain-containing protein FLNA Filamin-A
-2.66 ns
Stress Responses GLOD4 Glyoxalase domain-containing protein 4 PFD3 Prefoldin subunit 3 ANXA1 Annexin A1
ns
a Sequence coverage. b Number of peptides used in protein identification. c Spot abundance is expressed as the average ratio of intensities of up-regulated (positive values) or down-regulated (negative values) proteins between control and DET treatment at 6, 12, 24, and 24 h, respectively. Relative fold changes with p-values 1.5) in DET- and PTX-treated TS/A cells. List of proteins identified and and MS/MS spectra of the highlighted peptides in the proteins. This material is available free of charge via the Internet at http://pubs.acs.org. References (1) World Health Organization. Fact sheet No. 297: Cancer, July; 2008. (2) Stewart, B. W.; Kleihues, P. World cancer report; IARCPress: Lyon, 2003. (3) American Cancer Society. Breast Cancer Facts & Figures 20072008; American Cancer Society, Inc.: Atlanta, GA, 2007. (4) Mariani, G. New developments in the treatment of metastatic breast cancer: from chemotherapy to biological therapy. Ann. Oncol. 2005, 16 (Suppl. 2), ii191–4. (5) Wang, T. H.; Wang, H. S.; Soong, Y. K. Paclitaxel-induced cell death: where the cell cycle and apoptosis come together. Cancer 2000, 88 (11), 2619–28. (6) Orr, G. A.; Verdier-Pinard, P.; McDaid, H.; Horwitz, S. B. Mechanisms of Taxol resistance related to microtubules. Oncogene 2003, 22 (47), 7280–95. (7) Sarkar, F. H.; Li, Y. Using chemopreventive agents to enhance the efficacy of cancer therapy. Cancer Res. 2006, 66 (7), 3347–50. (8) Xu, G.; Liang, Q.; Gong, Z.; Yu, W.; He, S.; Xi, L. Antitumor activities of the four sesquiterpene lactones from Elephantopus scaber L. Exp. Oncol. 2006, 28 (2), 106–9.
research articles
Novel Molecular Targets of Mammary Carcinoma Treatments (9) Lee, K. H.; Cowherd, C. M.; Wolo, M. T. Antitumor agents. XV: Deoxyelephantopin, an antitumor principle from Elephantopus carolinianus Willd. J. Pharm. Sci. 1975, 64 (9), 1572–3. (10) Ichikawa, H.; Nair, M. S.; Takada, Y.; Sheeja, D. B.; Kumar, M. A.; Oommen, O. V.; Aggarwal, B. B. Isodeoxyelephantopin, a novel sesquiterpene lactone, potentiates apoptosis, inhibits invasion, and abolishes osteoclastogenesis through suppression of nuclear factor-kappaB (NF-kappaB) activation and NF-kappaB-regulated gene expression. Clin. Cancer Res. 2006, 12 (19), 5910–8. (11) Zou, G.; Gao, Z.; Wang, J.; Zhang, Y.; Ding, H.; Huang, J.; Chen, L.; Guo, Y.; Jiang, H.; Shen, X. Deoxyelephantopin inhibits cancer cell proliferation and functions as a selective partial agonist against PPARγ. Biochem. Pharmacol. 2008, 75 (6), 1381–92. (12) Huang, C. C.; Lo, C. P.; Chiu, C. Y.; Shyur, L. F. Deoxyelephantopin, a novel multifunctional agent, suppresses mammary tumor growth and lung metastasis and doubles survival time in mice Br. J. Pharmacol. 2009, DOI: 10.1111/j.1476-5381.2009.00581.x. (13) Marouga, R.; David, S.; Hawkins, E. The development of the DIGE system: 2D fluorescence difference gel analysis technology. Anal. Bioanal. Chem. 2005, 382, 669–78. (14) Lollini, P. L.; de Giovanni, C.; Eusebi, V.; Nicoletti, G.; Prodi, G.; Nanni, P. High-metastatic clones selected in vitro from a recent spontaneous BALB/c mammary adenocarcinoma cell line. Clin. Exp. Metastasis 1984, 2 (3), 251–9. (15) Ekins, S.; Nikolsky, Y.; Bugrim, A.; Kirillov, E.; Nikolskaya, T. Pathway mapping tools for analysis of high content data. Methods Mol. Biol. 2007, 356, 319–50. (16) But, P. P. H.; Hon, P. M.; Cao, H.; Chan, T. W. D.; Wu, B. M.; Mak, T. C. W.; Che, C. T. Sesquiterpene lactones from Elephantopus scaber. Phytochemistry 1997, 44 (1), 113–6. (17) Chiang, Y. M.; Lo, C. P.; Chen, Y. P.; Wang, S. Y.; Yang, N. S.; Kuo, Y. H.; Shyur, L. F. Ethyl caffeate suppresses NF-kappaB activation and its downstream inflammatory mediators, iNOS, COX-2, and PGE2 in vitro or in mouse skin. Br. J. Pharmacol. 2005, 146 (3), 352–63. (18) hevchenko, A.; Wilm, M.; Vorm, O.; Mann, M. Mass spectrometric sequencing of proteins from silver-stained polyacrylamide gels. Anal. Chem. 1996, 68 (5), 850–8. (19) Adams, J. The proteasome: structure, function, and role in the cell. Cancer Treat. Rev. 2003, 29 (Suppl. 1), 3–9. (20) Wu, J.; Kaufman, R. From acute ER stress to physiological roles of the unfolded protein response. Cell Death Differ. 2006, 13, 374– 84. (21) Jiang, H. Y.; Wek, R. C. Phosphorylation of the alpha-subunit of the eukaryotic initiation factor-2 (eIF2R) reduces protein synthesis and enhances apoptosis in response to proteasome inhibition. J. Biol. Chem. 2005, 280 (14), 14189–202. (22) Nakagawa, T.; Zhu, H.; Morishima, N.; Li, E.; Xu, J.; Yankner, B. A.; Yuan, J. Caspase-12 mediates endoplasmic reticulum-specific apoptosis and cytotoxicity by amyloid-b. Nature 2000, 403, 98– 103. (23) Nanni, P.; de Giovanni, C.; Lollini, P. L.; Nicoletti, G.; Prodi, G. TS/A: a new metastasizing cell line from a BALB/c spontaneous mammary adenocarcinoma. Clin. Exp. Metastasis 1983, 1 (4), 373– 80. (24) Rosato, A.; Dalla Santa, S.; Zoso, A.; Giacomelli, S.; Milan, G.; Macino, B.; Tosello, V.; Dellabona, P.; Lollini, P. L.; De Giovanni, C.; Zanovello, P. The cytotoxic T-lymphocyte response against a poorly immunogenic mammary adenocarcinoma is focused on a single immunodominant class I epitope derived from the gp70 Env product of an endogenous retrovirus. Cancer Res. 2003, 63 (9), 2158–63. (25) Oshikawa, K.; Shi, F.; Rakhmilevich, A. L.; Sondel, P. M.; Mahvi, D. M.; Yang, N. S. Synergistic inhibition of tumor growth in a murine mammary adenocarcinoma model by combinational gene therapy using IL-12, pro-IL-18, and IL-1beta converting enzyme cDNA. Proc. Natl. Acad. Sci. U.S.A. 1999, 96 (23), 13351–6. (26) Mollinedo, F.; Gajate, C. Microtubules, microtubule-interfering agents and apoptosis. Apoptosis 2003, 8, 413–50. (27) Lessor, T. J.; Yoo, J. Y.; Xia, X.; Woodford, N.; Hamburger, A. W. Ectopic expression of the ErbB-3 binding protein Ebp1 inhibits growth and induces differentiation of human breast cancer cell lines. J. Cell. Physiol. 2000, 183, 321–9. (28) Cicchillitti, L.; Michele, M. D.; Urbani, A.; Ferlini, C.; Donati, M. B.; Scambia, G.; Rotilio, D. Comparative proteomic analysis of paclitaxel sensitive A2780 epithelial ovarian cancer cell line and its
(29)
(30) (31) (32)
(33) (34)
(35)
(36) (37)
(38) (39) (40)
(41)
(42) (43) (44)
(45) (46) (47)
resistant counterpart A2780TC1 by 2D-DIGE: The role of ERp57. J. Proteome Res. 2009, 8, 1902–12. Dowling, P.; Meleady, P.; Dowd, A.; Henry, M.; Glynn, S.; Clynes, M. Proteomic analysis of isolated membrane fractions from superinvasive cancer cells. Biochim. Biophys. Acta 2007, 1774, 93– 101. Alli, E.; Bash-Babula, J.; Yang, J. M.; Hait, W. N. Effect of stathmin on the sensitivity to antimicrotubule drugs in human breast cancer. Cancer Res. 2002, 62, 6864–9. Belmont, L. D.; Mitchison, T. J. Identification of a protein that interacts with tubulin dimers and increases the catastrophe rate of microtubules. Cell 1996, 84, 623–31. Elliott, B. E.; Meens, J. A.; SenGupta, S. K.; Louvard, D.; Arpin, M. The membrane cytoskeletal crosslinker ezrin is required for metastasis of breast carcinoma cells. Breast Cancer Res. 2005, 7, R365–73. Kersten, S.; Desvergne, B.; Wahli, W. Roles of PPARs in health and disease. Nature 2000, 405, 421–4. To´th, J.; Varga, B.; Kova´cs, M.; Ma´lna´si-Csizmadia, A.; Ve´rtessy, B. G. Kinetic mechanism of human dUTPase, an essential nucleotide pyrophosphatase enzyme. J. Biol. Chem. 2007, 282 (46), 33572–82. Rual, J. F.; Venkatesan, K.; Hao, T.; Hirozane-Kishikawa, T.; Dricot, A.; Li, N.; Berriz, G. F.; Gibbons, F. D.; Dreze, M.; Ayivi-Guedehoussou, N.; Klitgord, N.; Simon, C.; Boxem, M.; Milstein, S.; Rosenberg, J.; Goldberg, D. S.; Zhang, L. V.; Wong, S. L.; Franklin, G.; Li, S.; Albala, J. S.; Lim, J.; Fraughton, C.; Llamosas, E.; Cevik, S.; Bex, C.; Lamesch, P.; Sikorski, R. S.; Vandenhaute, J.; Zoghbi, H. Y.; Smolyar, A.; Bosak, S.; Sequerra, R.; Doucette-Stamm, L.; Cusick, M. E.; Hill, D. E.; Roth, F. P.; Vidal, M. Towards a proteomescale map of the human protein-protein interaction network. Nature 2005, 437 (7062), 1173–8. Martinez-Contreras, R.; Cloutier, P.; Shkreta, L.; Fisette, J.; Revil, T.; Chabot, B. hnRNP proteins and splicing control. Adv. Exp. Med. Biol. 2007, 623, 123–47. Inoue, A.; Sawata, S. Y.; Taira, K.; Wadhwa, R. Loss-of-function screening by randomized intracellular antibodies: Identification of hnRNP-K as a potential target for metastasis. Proc. Natl. Acad. Sci. U.S.A. 2007, 104 (21), 8983–8. Nagaoka, K.; Tanaka, T.; Imakawa, K.; Sakai, S. Involvement of RNA binding proteins AUF1 in mammary gland differentiation. Exp. Cell Res. 2007, 313, 2937–45. Shcherbik, N.; Haines, D. S. Ub on the move. J. Cell. Biochem. 2004, 93 (1), 11–9. Hirano, Y.; Hendil, K. B.; Yashiroda, H.; Iemura, S.; Nagane, R.; Hioki, Y.; Natsume, T.; Tanaka, K.; Murata, S. A heterodimeric complex that promotes the assembly of mammalian 20S proteasomes. Nature 2005, 437 (7063), 1381–5. Sullivan, D. C.; Huminiecki, L.; Moore, J. W.; Boyle, J. J.; Poulsom, R.; Creamer, D.; Barker, J.; Bicknell, R. EndoPDI, a novel proteindisulfide isomerase-like protein that is preferentially expressed in endothelial cells acts as a stress survival factor. J. Biol. Chem. 2003, 278, 47079–88. Fribley, A.; Wang, C. Y. Proteasome inhibitor induces apoptosis through induction of endoplasmic reticulum stress. Cancer Biol. Ther. 2006, 5 (7), 745–8. Liao, P. C.; Tan, S. K.; Lieu, C. H.; Jung, H. K. Involvement of endoplasmic reticulum in paclitaxel-induced apoptosis. J. Cell. Biochem. 2008, 104, 1509–23. Kardosh, A.; Golden, E. B.; Pyrko, P.; Uddin, J.; Hofman, F. M.; Chen, T. C.; Louie, S. G.; Petasis, N. A.; Scho¨nthal, A. H. Aggravated endoplasmic reticulum stress as a basis for enhanced glioblastoma cell killing by bortezomib in combination with celecoxib or its noncoxib analogue, 2,5-dimethyl-celecoxib. Cancer Res. 2008, 68 (3), 843–51. Tishler, R.; Schiff, P.; Geard, C.; Hall, E. Taxol: a novel radiation sensitizer. Int. J. Radiat. Oncol. Biol. Phys. 1992, 22, 613–7. Adams, J. The proteasome: a suitable antineoplastic target. Nat. Rev. Cancer 2004, 4, 349–60. Landis-Piwowar, K. R.; Milacic, V.; Chen, D.; Yang, H.; Zhao, Y.; Chan, T. H.; Yan, B.; Dou, Q. P. The proteasome as a potential target for novel anticancer drugs and chemosensitizers. Drug Resist. Update 2006, 9 (6), 263–73.
PR900543E
Journal of Proteome Research • Vol. 9, No. 1, 2010 253
