Shotgun Proteomics and Quantitative Pathway Analysis of the

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Shotgun Proteomics and Quantitative Pathway Analysis of the Mechanisms of Action of Dehydroeffusol, a Bioactive Phyto-chemical with Anti-cancer Activity from Juncus effusus I-Sheng Chang, Lai-King Sy, Bei Cao, Ching Tung Lum, WaiLun Kwong, Yi-Man Eva Fung, Chun-Nam Lok, and Chi-Ming Che J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.8b00227 • Publication Date (Web): 29 May 2018 Downloaded from http://pubs.acs.org on May 30, 2018

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Journal of Proteome Research

Shotgun Proteomics and Quantitative Pathway Analysis of the Mechanisms of Action of Dehydroeffusol, a Bioactive Phytochemical with Anti-cancer Activity from Juncus effusus I-Sheng Chang1†, Lai-King Sy1†, Bei Cao1, Ching Tung Lum1, Wai-Lun Kwong1, Yi-Man Eva Fung1*,Chun-Nam Lok1* and Chi-Ming Che1* Department of Chemistry, Chemical Biology Center and State Key Laboratory of Synthetic Chemistry, The University of Hong Kong1, Hong Kong, China ABSTRACT: Dehydroeffusol (DHE) is a phenanthrene isolated from Chinese medicine Juncus effusus. Biological evaluation of DHE reveals in vitro and in vivo anticancer effects. We performed a shotgun proteomic analysis using liquid chromatographytandem mass spectrometry to investigate the changes in the protein profiles in cancer cells upon DHE treatment. DHE affected cancer-associated signaling pathways, including NFB, β-catenin and endoplasmic reticulum stress. Through quantitative pathway and key node analysis of the proteomics data, activating transcription factor 2 (ATF-2) and c-Jun kinase (JNK) were found to be the key components in DHE’s modulated biological pathways. Based on the pathway analysis as well as chemical similarity to estradiol, DHE is proposed to be a phytoestrogen. The proteomic, bioinformatic and chemoinformatic analyses were further verified with individual cell-based experiments. Our study demonstrates a workflow for identifying the mechanisms of action of DHE through shotgun proteomic analysis. KEYWORDS: Shotgun proteomics, signaling pathway analysis, TMT-labeling, phytoestrogen. study the effect of DHE on the protein expressions in cancer cells. Quantitative pathway and key node analysis of INTRODUCTION the proteomic data were employed to identify potentially affected signaling pathways. Multiple signaling pathways, The naturally occurring phenanthrenes are a rather unmost notably those involving activating transcription faccommon class of aromatic metabolites which are likely tor 2 (ATF-2), c-Jun kinase (JNK), nuclear factor-kappa B formed by oxidative coupling of the aromatic rings of stil(NF-B), β-catenin and endoplasmic reticulum stress and 1 bene precursors . The traditional Chinese medicine Juncus estrogen receptor were found to play important roles in effuses containing considerable amount of phenanthrenes the anti-tumor activity of DHE. Selected findings from the is commonly used for treating insomnia and fidgeting2-4. proteomics analysis were further verified by means of inPhytochemical studies have shown that it contains coumadependent cell-based experiments. Our study demonric acid, flavones, cycloartanes, coumaroyl glycerides, phestrates an effective workflow for identifying the mechananthrenes, dihydrodibenzoxepins, and other possibly nisms of action of DHE through shotgun proteomic analybioactive constituents2-4. sis. Dehydroeffusol (DHE) is one of phenanthrenes isolated from J. effusus. It has been identified as an anxiolytic, sedative and antispasmodic agent5-7. Recently, evidence for an MATERIALS AND METHODS inhibitory action of DHE in gastric cancer models has emerged, indicating the involvement of vasculogenic mimExtraction and isolation of dehydroeffusol icry and endoplasmic reticulum stress8. However, the overall mechanisms of DHE’s antitumor activity remain to J. effusus (1.5 kg) was pulverized and successively sonicatbe explored. To understand the mode(s) of the biological ed (220 W) in methanol followed by filtering. Filtrates actions of DHE in an unbiased manner, we employ a syswere combined and dried in vacuo. The crude extract (31 tem biology approach involving shotgun proteomics9, g) was subject to column chromatography, started with the quantitative pathway and key node analysis10. Proteomics elution of 2% ethyl acetate/n-hexane followed by gradualanalysis performed with liquid chromatography tandem ly increasing the volume of ethyl acetate. Eluents were mass spectrometry (LC-MS/MS) techniques on LTQ Orcollected in test tubes (20 mL), monitored by TLC and bitrap MS to pooled. Each crude fraction was screened by 1H NMR. The

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fractions containing DHE was subject to further purification by normal phase semi-preparative HPLC (PREP-SIL 20 mm  25 cm column, flow rate 8 mL/min) using 15% ethyl acetate/n-hexane as mobile phase. The 1H and 13C NMR of DHE were recorded by Bruker 400 MHz. Methanol-d4 was used as solvent with TMS as internal standard (Supporting Information).

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100 µg of protein from each sample was incubated at 60°C for 10 minutes. Dithiothreitol (DTT) was added to a final concentration of 5 mM and the samples were incubated for 30 minutes at room temperature for disulfide bond reduction. Then iodoacetamide (final concentration of 25 mM) was added and kept in darkness for 30 minutes at room temperature. Subsequently, the protein extracts were precipitated with acetone at -20°C for 5 h, and then centrifuged at 15,000g for 20 minutes at 4°C. The supernatant was removed and the pellets were air dried. The dried samples were solubilized in 100 µL of 50 mM triethyl ammonium bicarbonate (TEAB) and digested by trypsin at a ratio of 1:33 (trypsin: protein) at 37°C for 16 h. The digested samples were quantified by Thermo ScientificTM PierceTM Quantitative Fluorometric Peptide Assay. Equal amount of each sample was taken for tandem mass tag (TMT) labeling (Pierce, Rockford IL, USA) as below, control 6 h (TMT-126), DHE 6 h (TMT-127), control 10 h (TMT128), DHE 10 h (TMT-129), control 24 h (TMT-130) and DHE 24 h (TMT-131). Equal amount of each labeled sample was the mixed and stored at -80°C.

Cell culture and cytotoxicity evaluation Human cancer cell lines, including HeLa, HepG2, NCl-H460, MCF7, OVCAR3, SKOV3 and CaOV3, were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and 100 U/mL penicillin-streptomycin. Cells (1 × 104 cells/well) were seeded in 96-well microplates for 24 hours and incubated with serially diluted DHE for 24 hours. Cells were fixed with 100 µL 3% formaldehyde and stained with 100 µL 0.05% naphthol blue black (NBB) overnight. The wells were washed with deionized water followed by the addition of 100 µL 50 mM NaOH. The absorbance of the solubilized NBB at 590 nm was measured using a plate reader. The IC50 values were calculated as the concentration of drug at which the cell viability was decreased by 50% (Supporting Information Figure S2).

Offline fractionations with High pH (Hp)-Reverse phase (RP)-StageTips 50 µg of mixed sixplex-TMT samples were subjected to an offline pH 10 Hp-RP-StageTip11, 12fractionations. RP chromatography was carried out on a homemade 200 𝜇L C18 StageTip11, 12. 5 mg of ReproSil-Pur C18-AQ 5 µm resin (Dr. Maisch GmbH, Germany) was first suspended in 100 mM ammonium formate (NH4HCO2, pH 10) with 50% ACN, followed by packing into a Gilson 200 μL tip with a C8 membrane frit and centrifuged at 1,500 g for 2 min. After sufficient washing and conditioning, digested TMT-labelled peptides were reconstituted with loading solution (20 mM NH4HCO2, pH 10), and loaded onto the StageTip. The peptides were eluted through an ACN gradient as described on the suggested protocol of Thermo Scientific™ Pierce™ High pH Reversed-Phase Peptide Fractionation Kit and separated into eight fractions (Supporting Information). Each fraction was desalted with a low pH (pH 2) RP-StageTip13 before applying to LC-MS/MS analysis.

In vivo anti-tumor experiments in mice The anti-tumor experiments in mice were performed with approval of Committee on the Use of Live Animals in Teaching and Research of The University of Hong Kong. The BALB/cAnN-nu (Nude) mice, 5-6 weeks old, were used in the present study. 4x106 HeLa cells were injected subcutaneously into the right back flanks of mice. When tumor volumes reached 50-100 mm3, the mice were randomly divided into two treatment groups. DHE was dissolved in 60% polyethylene glycol 400, 30% ethanol and 10% Tween 80 (PET), and diluted with phosphate-buffered saline (PBS) before injection. Mice were treated with PET solvent control or 10 mg/kg DHE by intra-tumoral injection 3 times per week until the mice were sacrificed. Tumor volumes were measured and the difference between groups was evaluated using Student’s t-test for independent samples. The significance level was set at p-value < 0.05.

Reverse phase-High Performance liquid chromatography (RP-HPLC-MS/MS) analysis

Cell treatment with DHE and protein extraction

Each fraction was separately assessed by technical triplicate runs of RP-HPLC-MS/MS. For each run, around 2.5 µg of proteins were loaded onto an analytical column with a fused silica emitter (75 µm I.D. × 12 cm, 360 µm O.D., 15 µm Tip I.D.; New Objective, Inc.) packed in-house with ReproSil-Pur C18-AQ 3 µm resin (Dr. Maisch GmbH, Germany) and connected with the HPLC (Thermo Finnigan Surveyor Plus, USA) with a split-flow setup. Then the column was connected to a NanoSpray Ionization (NSI) source (Shotgun Proteomics Inc., San Diego, CA, USA) at the orifice of the mass spectrometer. Mobile phase A was 0.1% formic acid (FA) (v/v) in H2O. Mobile phase B was 0.1% FA (v/v) in acetonitrile (ACN). The sample was load-

HeLa cells were seeded at a density of 3×105 cells/well in 6-well cell culture plates and treated with 20 µM DHE or DMSO vehicle for 6, 10 and 24 h. Cells were washed twice with cold PBS followed by the addition 100 µL lysis buffer (8 M urea, protease inhibitor cocktail in 20 mM Tris-HCl, pH 8.0) and sonicated with three 15-s pulses using a microprobe tip set at 20 W output. The resulting cell lysates from three biological replicates were collected and pooled together. The lysates were clarified by centrifugation at 15,000g for 15 minutes at 4°C. Protein concentrations were determined using the Bio-Rad protein assay. Sample preparation for proteomic analysis

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Journal of Proteome Research platform (GeneXplain GmbH, Germany) and ExPlainTM (version 3.1, BioBase, Germany), respectively.

ed onto the trap column (ZORBAX 300SB-C18, 5 µm, 5x0.3mm, Agilent Technologies, CA, USA) for 5 mins with 2% B at a 10 µL/min, and then eluted through the analytical column with a different gradient for different fractions for 120 mins at 0.28 µL/min, followed by a washing and equilibration time of 40 mins at 0.28 µL/min. (Detailed gradients described in Supporting Information) The HPLC eluate was directly electrosprayed into a linear ion trap (LTQ)-Orbitrap Velos mass spectrometer (Thermo-Scientific, MA, USA) operated in automatic datadependent acquisition mode. The instrument automatically switched between MS survey scan with Orbitrap with a m/z range from 300 to 1800 and MS/MS scans of higher energy collisionally activated dissociation (HCD) fragmentation with Orbitrap of the ten most intense ions with 30,000 resolution for MS1 and 15,000 resolution for MS/MS. The dynamic .exclusion list was set to 500 and exclusion time was 60 s. Singly-charged ions and ions with unassigned charge states were excluded. Selected ions for HCD were isolated with isolation width of 2.0 m/z, activated with collision energy of 40 (arb. units) for 0.1 ms

Immunoblot analysis Proteins (30 µg) from the cell lysates were resolved by SDS-PAGE, and then transferred to PVDF membranes. The membranes were blocked with Tris-buffered saline, containing 0.1% Tween 20 (TBST) and 5% BSA, and incubated with the primary antibodies anti-p-ATF2Thr71, -caspase 3, cleaved caspase 3, -PARP, -cleaved PARP, -β-actin, -βcatenin, -IKBα, -p-IKBαSer32, -p-NFB p652Ser536, -GAPDH, p-JNKThr183/Tyr185 or -CHOP (Cell Signaling Technology Inc.) at 4°C for 3 hours. After washing with TBST, the membranes were further incubated with an appropriate secondary antibody for an hour. The immunoreactivity was detected using an enhanced chemiluminescence detection kit (GE Healthcare). Flow cytometric assay of apoptosis HeLa cells (2×105) were treated with DHE (10 or 20 µM) or DMSO vehicle for 24 h. Cells treated with staurosporine (200 nM) were used as a positive control. Cells were collected and re-suspended in (10 mM HEPES buffer, 140 mM NaCl and 2.5 mM CaCl2 at pH 7.4), incubated with annexinV conjugated with Alexa Fluor 647 and SYTOX green (Thermo Fisher Scientific, Invitrogen) for 30 min at 37°C and analyzed by flow cytometry (BD LSR Fortessa Analyzer). The percentage of viable, apoptotic and necrotic cells were examined using FlowJo (version 7.6.1).

Data analysis Spectra were searched against the Uniprot human database (70939 entries, downloaded on May 19, 2017) with the MaxQuant search engine (version 1.6.0.1). Each search was specified to include trypsin digestion (allowed up to two missed cleavages); oxidation of methionine, deamination of asparagine and glutamine and N-terminal acetylation as a dynamic modification; the iodoacetamide derivative of cysteine and TMT reagent adducts on lysine and peptide amino termini as a static modification. The mass tolerance for monoisotopic peptide identification and fragmented ions were set to 4.5 ppm and 20 ppm, respectively. The final peptide false discovery rate (FDR) was < 1%, determined by a decoy search strategy. The raw data and search results were uploaded to PRIDE database (PXD009389). Relative protein abundance ratios between two groups were calculated from TMT reagent reporter ion intensities, obtaining from HCD spectra. The ratio of protein of DHE treatment to control was calculated and normalized by median. The normalized ratio was transform to log2 and Perseus (version 1.6.0.2) was used to perform statistical comparisons. One-sample T-test was applied to calculate significant differences in abundance among groups. The Benjamini-Hochberg FDR value < 0.05 was considered significant. Functional annotation of 24 h DHEregulated proteins was performed in the database for annotation, visualization and integrated discovery (DAVID, version 6.8). The cutoff criterion was set as a modified Fisher Exact p-value < 0.05.

In vitro angiogenesis assay 50 µL of Extracellular matrix (ECM) gel (Thermo Fisher Scientific) was added to each well of a 96-well plate and allowed to polymerize for 1 h at 37°C. MS-1 mouse pancreatic islet endothelial cells (5.0×104) were suspended in medium containing DHE (10, 20 or 40 µM) and gently added to each ECM gel coated well. The cells were incubated for 2 h at 37°C and tube formation was examined under a microscope. Cell viability was also examined by the MTT assay. Transfection and luciferase reporter assay HeLa cells were seeded at 1×105 cells/well in a 24-wellplate and transfected with 500 ng luciferase reporter using 1.5 µL Lipofectamine 2000 (Invitrogen). After 6 hours of transfection, the cells were treated with DHE or vehicle for 16 hours, followed by the respective inducers for 6 hours. The luciferase activities in the cell extracts were measured as chemiluminescence using luciferase assay reagents (Promega).

Signaling pathway and Key node analysis Quantitative pathway analysis14 and key node analysis15 were performed as previously described14, 15 with modifications. The detailed analysis method is described in Supporting Information. Quantitative pathway analysis and key node analysis were performed using the geneXplain™

Estrogen receptor binding assay The receptor binding assay was performed by Eurofins Panlab, Taiwan Ltd. Human recombinant estrogen receptor α (ERα) or estrogen receptor β (ERβ) was incubated



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ics (MM) level. The QM region was treated at the DFT level using the B3LYP method. The 6-31G* Pople basis set was employed for all the atoms. The ERs were described with the AMBER parm99 force field17. The binding structure was solvated in a cubic box with classical SPC/E water molecules. The optimization of these two regions (QM and MM) was alternated until self-consistency was reached.

with DHE at 10-9 to 10-5 µM in Tris-HCl buffer, pH 7.4, followed by incubating with 0.5 nM [3H]Estradiol for 2 hours at 25°C. The IC50 values were calculated as the concentration of DHE that inhibited 50% of the specific binding of the [3H]estradiol to the estrogen receptors. Quantum mechanics/molecular mechanics

RESULTS AND DISCUSSION

The binding between ERs and ligands was optimized using the QM/MM approach and NWChem software16. DHE and estradiol were treated as quantum parts (QM), while the

In vitro and in vivo anticancer activities of DHE

Figure 1. (A) Chemical structure of DHE and its cytotoxicity in different cancer cell lines, as determined by MTT assays. (B-D) Induction of apoptosis by DHE treatment (20 µM, 24 h) in HeLa cells as determined by immunoblot analysis of caspase 3, PARP-1. (B) Nuclear staining with Hoechst 33342 (C) and flow cytometry analysis of Annexin-V-Alexa Fluor 647/SYTOX green-stained cells (D). The apoptosis inducer staurosporine was used as a positive control. (E) In vitro anti-angiogenesis properties of DHE treatment (10, 20 and 40 µM, 24 h) as determined by tube formation assay in murine MS-1 endothelial cells. (F) Anti-tumor activities of DHE (10 mg/kg, intra-tumoral injections twice per week) on mice bearing HeLa cell xenografts. Data shown are mean ± S.E.M; *, p-value < 0.05, compared to untreated control. rest of the system was modelled at the molecular mechan-


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Journal of Proteome Research involved in the cytotoxic effects of DHE in HeLa cells, as revealed by assays of caspase-3 cleavage and poly (ADPribose) polymerase 1 (PARP-1) (Figure 1B), nuclear fragmentation and condensation (Figure 1C) and annexin-VAlexa Fluor 647/SYTOX green staining (Figure 1D). Furthermore, DHE was shown to elicit anti-angiogenic properties with respect to endothelial cell tube formation in vitro (Figure 1E). The effect of DHE on the tumor growth was examined in nude mice bearing xenografts of HeLa cancer

DHE exerted cytotoxic effects in a number of cancer cell lines, including HeLa (cervical carcinoma), HepG2 (hepatocarcinoma), NCl-H460 (non-small cell lung carcinoma), MCF7 (breast carcinoma), OVCAR3, SKOV3 and CaOV3 (ovarian carcinoma) with IC50 ranging from 5.5 to 45.6 µM (Figure 1A). The cytotoxic effect of DHE on HeLa cells was most potent with IC50 of 12 and 5.5 µM for 24 and 48 h post-treatment, respectively (Figure 1A and Supporting Information Figure S2). The induction of apoptosis was

Figure 2. Functional annotation of DHE-mediated proteins with respect to cellular components, biological processes and molecular functions. The corresponding numbers represent the percent (4%) of the number of proteins over the total identified proteins under individual GO terms.



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identified with at least 2 peptides per protein, these proteins were used for further data analysis. Upon applying stringent filtering criteria, only the data of 24 h DHE treatment gave reasonable number of regulated proteins for further data analysis. From the identified 2114 proteins, 131 proteins were found regulated (84 up-regulated and 47 down-regulated) with Benjamini-Hochberg FDR value < 0.05 and expression fold change > 1.5 fold (Supporting Information Table S1). Cellular distribution, biological process and functional classification of the proteins modulated by DHE treatment were analyzed (Supporting Information Table S2). The gene ontologies (GO) analysis of cellular components, biological processes and molecular functions of the 131 DHE-modulated proteins at 24 h treatment were showed (Figure 2). Many of the DHE regulated proteins were evenly distributed in the cell orga-

cells. DHE treatment significantly decreased the tumor size compared to solvent control without significant changes in body weight (Figure 1F). These findings provide evidence that DHE may be a potential antitumor agent. Proteomic analysis To uncover the mechanisms of action of DHE in an unbiased and comprehensive manner, proteome changes modulated by DHE treatment were accessed by shotgun proteomic analysis. HeLa cells were treated with 20 M DHE or DMSO vehicle for 6, 10 and 24 h. The proteins were extracted and digested with trypsin, followed by TMT labeling and Orbitrap LC-MS/MS analysis. In total, we have identified 2922 proteins after application of offline Hp-RPStageTip fractionations. From which, 2114 proteins were

Table 1. Significant cellular pathways affected by DHE. p-values provided for significantly affected pathways (p < 0.05).


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Journal of Proteome Research the upstream signaling molecules. The upstream key nodes were then mapped to cellular pathways with a pathway analysis method as described previously14, 18. In our study, the signaling pathways identified with p-values below 0.05 are listed in Table 1. Selected pathways, including estrogen receptor pathways, the β-catenin network, NF-κB (related to TNF-α pathway) and JNK were further examined in cell based experiments.

nelles, including nuclear, mitochondrion and cytosol. The biological processes and molecular functions of these DHEmodulated proteins were mainly involved in cell-cell adhesion, oxidation-reduction process, protein folding, apoptotic process, protein binding, RNA binding and ATP binding. Signaling pathway analysis To determine the cellular signaling pathways that are affected by DHE treatment, the regulated proteins of each sample (Supporting Information, Table S1) were automatically converted to the corresponding gene upon data uploading to geneXplain™ platform followed by a search of

Estrogen receptor Estrogens may exert mitogenic activity that is critical in the etiology and progression of human breast and other

Figure 3. Phytoestrogenic activities of DHE. (A) Effect of DHE on ERα- and ERβ-mediated transcriptional activity in HeLa cells co-transfected with the ERE luciferase reporter; ERα or ERβ were assessed separately. The anti-estrogen agent ICI 182780 was used to antagonize the ER-mediated activity. *, p-value < 0.05, compared to estradiol (10 nM). (B) Quantum Mechanics/Molecular Mechanics (QM/MM) calculations of DHE binding to estrogen receptors. (i) The superimposed structures of both DHE (light blue) and estradiol (purple) binding to ERα and ERβ. (ii) Neighboring residues of ERα and ERβ around DHE. DHE is shown in ball-and-stick with the carbon atoms in salmon. The surrounding residues around DHE are portrayed in stick display mode. Colour code: carbon (salmon, green and blue), nitrogen (dark blue), oxygen (red), sulfur (dark yellow) and hydrogen (white). (C) Estrogen receptor binding assays showing inhibition of the specific binding of estrogen to ERα and ERβ by DHE.



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gen exhibiting ER modulatory activities.

gynecological cancers19. The classical biological actions of estrogens are mediated by estrogen receptors (ERs), which act as transcription factors to regulate the expression of multiple target genes. Many estrogen-like compounds from plants (a.k.a., phytoestrogens), modulate the transcriptional response mediated by estrogen receptors in manners dependent on the receptor subtypes and tissues; in some cases, conferring therapeutic benefits in cancer, cardiovascular disease, osteoporosis and menopausal symptoms20, 21. In our study, the effects of DHE on ERα- and ERβ-mediated transcriptional activity was assessed using a luciferase reporter gene assay. DHE stimulated the transcriptional activity mediated by ectopically expressed ERs in HeLa cells in a dose-dependent manner, which is further verified by the antagonizing action of the anti-estrogen ICI182780 (Figure 3A). DHE was also subjected to Similarity Ensemble Approach (SEA) analysis to predict the potential binding target of DHE based on the chemical features it shares with those of known ligands22. The SEA calculations showed that DHE shares structural similarity to the ER ligand estradiol. A molecular simulation by Quantum Mechanics/Molecular Mechanics (QM/MM) calculations was then performed to establish a model for DHE binding to ERs (Fig. 3B). The analysis suggests that DHE can bind ERα and ERβ in a thermodynamically favorable manner. DHE can be fit into the estradiol binding pocket of both ERs via hydrophobic interactions of DHE with hydrophobic residues in the receptors (Fig. 3B). In addition, the two phenolic hydroxyl groups of DHE are predicted to form hydrogen bonds with histidine and glutamate residues in the receptors. The binding energy for DHE and ERα is calcula8ted to be -34.2 kcal/mol, and that for DHE and ERβ is -39.9 kcal/mol. Moreover, the DHE-ER interactions were further studied on the ability of increasing DHE concentrations to displace [3H]Estradiol from binding to ERα or ERβ by competitive radioligand receptor binding assays (Fig. 3C). The Ki value of DHE binding to ERβ was 30-fold lower than to ERα, indicating that DHE may preferentially bind to ERβ over ERα. Taken together, DHE could be considered as a phytoestro-

β-catenin The Wnt/β-catenin pathway plays an important role in cell growth and differentiation; aberrant activation of this pathway is associated with cancer23, 24. β-catenin is a transcriptional co-activator of the TCF/LEF transcription factor family, which controls key developmental gene expression and is degraded in the absence of Wnt. In cancer cells which often have the Wnt/β-catenin pathways activated, the otherwise degraded β-catenin accumulates in the cytoplasm and eventually translocates into the nucleus to mediate the expression of genes that favor cancer development. As shown in Figure 4A, immunoblot analysis indicates the amount of β-catenin was reduced after 24 h DHE treatment. In addition, a luciferase reporter assay was used to examine TCF/LEF transcriptional activity (Figure 4B). DHE treatment inhibited TCF/LEF activity. These results suggest that β-catenin signaling is suppressible by DHE treatment, which is consistent with our pathway analysis (Table 1).

Figure 5. Inhibition of TNF-α-stimulated Iβ-α phosphorylation, IB-α degradation and NF-B p65 phosphorylation by DHE. HeLa cells were treated with or without DHE for 16 h followed by TNF-α stimulation for 30 min, as indicated. (A) The expression of IB-α and phosphorylation of IB-α (S32) and NF-B p65 (S536) were determined by immunoblot analysis. (B) dosedependent inhibition of TNF-α-induced NF-B transcription activity by DHE.

Figure 4. (A) DHE treatment (24 h) inhibited β-catenin expression. β-actin was used as the primary antibody for detecting protein concentration. (B) Inhibition of Wnt signaling by DHE was examined by a TCF/LEF luciferase reporter assay. *, p-value < 0.05, compared to solvent control.


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Journal of Proteome Research data searching parameters were described in Supporting Information. In total, we have identified 1799 proteins. The number of identified proteins with expression fold change > 1.5 fold at 6, 10, and 24 h are 42, 91 and 201, respectively (Supporting Information Table S3). The DHE-modulated proteins of each time course were subjected to key node analysis using ExPlainTM (version 3.1, BioBase) as previously described, to identify the key molecules (proteins) in the network that are closely related to the proteome changes. Each key node was assigned a score based on its connectivity and input protein abundances. After comparing the key node scores of DHE treated samples and control, the top-scoring key nodes were identified (detailed procedure described in Supporting Information) In this study, the top-scoring key nodes from the three treatment time courses examined were PKC, MKK4, CDK1, ABL1, granzyme B and procaspase-3 (Figure 6A). The selected key nodes and the gene symbols of input regulated proteins are also listed in Figure 6A. ExPlainTM (version 3.1, BioBase) was used for further analysis with the topscoring key nodes which revealed that activating transcription factor 2 (ATF2) may be a key signaling molecule influenced by DHE (Figure 6A). The ATF2 transcription factor is a member of the ATF/CREB family of leucine zipper proteins that bind to both AP-1 (Jun) and CRE DNA response elements27. ATF-2 interacts with a variety of oncoproteins and cellular tumor suppressors and regulates growth, sur-

NF-B The identification of TNF-α pathway (Table 1) in the proteomic analysis of DHE treatment implied that the transcriptional regulator NF-B may act downstream of DHE exposure25. NF-B is activated by the phosphorylation and degradation of the inhibitory IB-α protein. The activation of NF-B usually results in the up-regulation of antiapoptotic genes, thereby promoting cell survival25. Therefore many anticancer or anti-inflammation compounds, including many natural products, act by inhibiting NF-B activity via blockage of the phosphorylation of IB-α26. In our study, we investigated the effects of DHE on the NF-B pathway. Treatment of HeLa cells with DHE was shown to inhibit TNF-α-stimulated phosphorylation and degradation of IB-α, phosphorylation of NF-B (Figure 5A) and NF-B activity (Figure 5B). Key node analysis and biological verification experiments In this study, a label free whole cell lysate shotgun proteomics approach was applied with three DHE treatments time courses of 6, 10 and 24 h for key node analysis. The detail sample preparation, LC-MS/MS data acquisition and

Figure 6. (A) Key node network analysis of proteomic data suggests that DHE acts on the ATF2/JNK pathway in HeLa cells. (B) DHE induces phosphorylation of ATF2, JNK and CHOP (C) DHE inhibits PMA-induced activator protein 1 (AP-1)driven luciferase reporter activity. Cells were transfected with the AP-1 luciferase reporter gene and treated with without or with PMA for 4 h to stimulate AP-1 activity, followed by treatment with or without DHE for 18 h (D) DHE inhibits ERstress-associated ATF4 luciferase reporter activity in cells transfected with the AP-1 luciferase reporter gene. Cells were treated with the indicated concentrations of DHE for 18 h. Thapsigargin (Tg, 100 nM) was used as a positive control to induce ER stress. *, p-value < 0.05, compared to untreated control.



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least in part via ER stress-associated signaling events which may be further connected to upstream ATF2 signaling. Our workflow of proteomic profiling and quantitative pathway/key node analysis14, 15 can lead to the identification of dominant signaling pathways and potential molecular targets of bioactive compounds. This is achieved through input of shotgun expression proteomic data obtained from drug treatment experiments to an algorithm (described in the Supporting Information) that is able to connect the drug target dynamics with the annotated signaling pathways in a bioinformatics database. The robustness of this workflow has been demonstrated previously to reconfirm or identify the key signaling pathways modulated by bioactive compounds. For example, the dominant pathways of epidermal growth factor and transforming growth factor β can be correctly identified even from limited proteomic datasets14. In another instance, topoisomerase I can be identified, as expected, as a key target of camptothecin, without containing topoisomerase I within the input data15. Recently, we have employed the same analysis on proteomic data obtained from the treatment of cancer cells with an anticancer synthetic metal complex and identified the epidermal growth factor receptor (EGFR) pathway as the dominant signaling pathway. This finding was verified by cell-based experiments that indicate an inhibition of EGFR activation by the metal complex10.

vival or apoptosis, depending on the cellular context and the composition of the dimeric complexes. Cellular stress imposed by anticancer compounds activate c-Jun kinase (JNK) that phosphorylate ATF-2, thereby mediating a tumor-suppressive effect through a transcriptional program that is frequently downregulated in human tumors28, 29. Activation of JNK and ATF2 is closely associated with induction of apoptosis. In our study, we found that phosphorylation of JNK and ATF2 were induced at 10 and 24 h in the presence of DHE (Figure 6B). Thus, the possibility exists that DHE-induced apoptosis may be linked to activation of the JNK-ATF2 pathway. Furthermore, DHE treatment also inhibited the tumor promoter, phorbol myristate acetate (PMA)-induced transcriptional activity, which is mediated through the AP-1 responsive element of a reporter gene (Figure 6C). The connections within the JNKATF2-AP1 axis are not yet fully understood but it is nonetheless a likely part of DHE’s mechanism of action. Considering that pathway analysis revealed the involvement of “stress associated pathway” and the identification of JNK/ATF2 as key node molecules in the mechanisms of action of DHE, some prominent stress associated proteins that may act as downstream effectors were examined. Endoplasmic reticulum stress, which can be either a prosurvival or pro-apoptotic cellular program, depending on cellular conditions, is induced upon treatment of cells with certain anticancer compounds30. The expression of C/EBPhomologous protein (CHOP), which is a transcription factor having a pro-apoptotic function and up-regulated upon endoplasmic reticulum (ER) stress and also inducible by phosphorylated ATF230, 31,was investigated. In this work, the expression of CHOP was markedly increased by DHE treatment, as determined by immunoblot analysis (Figure 6B). Furthermore, the translational activation of activating transcription factor 4 (ATF4), which is an ER stressstimulated protein and transcriptional activator of CHOP 31, was examined using a luciferase reporter. As shown in Figure 6D, DHE treatment (2.5 to 10 µM) stimulated ATF4 activity by 2-3 fold. Taken together, our results suggest that DHE activates apoptotic pathways in cancer cells, at

CONCLUSION In the current study, we devised a workflow integrating shotgun proteomics and bioinformatics analyses to help elucidate the actions of bioactive compounds. The proteomic analysis of shotgun protein expression profiling and the subsequent pathway and key node analysis revealed the mechanisms of action of DHE in cancer cells (Figure 7). Functional annotation of DHE-regulated proteins revealed that DHE may affect gene expression and signal transduction through exerting its effect at the RNA expression and processing levels (Fig. 2). By key node analysis at different time intervals of DHE treatment, ATF-2, which is mediated by stress-activated protein kinases, and the related JNK pathway are pivotal in the cellular actions of DHE (Fig. 6). Pathway analysis revealed that estrogen receptors (Fig. 3), β-catenin (Fig. 4), NF-B (Fig. 5) and endoplasmic reticulum stress (Fig. 6) are also involved. These findings were further examined with cell-based experiments. In particular, the direct interaction of DHE with estrogen receptors was demonstrated by a ligand binding assay and molecular simulation by QM/MM calculations, revealing that DHE acts as a phytoestrogen, preferentially binding the β form over the α form of the estrogen receptor, hence having pharmacological interest as a selective estrogen receptor modulator.

Figure 7. Scheme of the mechanisms of action of DHE.


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Journal of Proteome Research

ASSOCIATED CONTENT

(9) Zhang, Y.; Fonslow, B. R.; Shan, B.; Baek, M.-C.; Yates III, J. R., Protein analysis by shotgun/bottom-up proteomics. Chem. Rev. 2013, 113, (4), 2343. (10) Fong, T. T. H.; Lok, C. N.; Chung, C. Y. S.; Fung, Y. M. E.; Chow, P. K.; Wan, P. K.; Che, C. M., Cyclometalated Palladium (II) N‐ Heterocyclic Carbene Complexes: Anticancer Agents for Potent In Vitro Cytotoxicity and In Vivo Tumor Growth Suppression. Angew. Chem. Int. Ed. 2016, 55, (39), 11935-11939. (11) Kitata, R. B.; Dimayacyac-Esleta, B. R. T.; Choong, W.-K.; Tsai, C.F.; Lin, T.-D.; Tsou, C.-C.; Weng, S.-H.; Chen, Y.-J.; Yang, P.-C.; Arco, S. D., Mining missing membrane proteins by high-pH reverse-phase StageTip fractionation and multiple reaction monitoring mass spectrometry. J. Proteome Res. 2015, 14, (9), 3658-3669. (12) Dimayacyac-Esleta, B. R. T.; Tsai, C.-F.; Kitata, R. B.; Lin, P.-Y.; Choong, W.-K.; Lin, T.-D.; Wang, Y.-T.; Weng, S.-H.; Yang, P.-C.; Arco, S. D., Rapid high-pH reverse phase StageTip for sensitive small-scale membrane proteomic profiling. Anal. Chem. 2015, 87, (24), 12016-12023. (13) Rappsilber, J.; Mann, M.; Ishihama, Y., Protocol for micropurification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nat. Protoc. 2007, 2, (8), 1896-1906. (14) Zubarev, R. A.; Nielsen, M. L.; Fung, E. M.; Savitski, M. M.; KelMargoulis, O.; Wingender, E.; Kel, A., Identification of dominant signaling pathways from proteomics expression data. J. Proteomics 2008, 71, (1), 89-96. (15) Good, D. M.; Zubarev, R. A., Drug target identification from protein dynamics using quantitative pathway analysis. J. Proteome Res. 2011, 10, (5), 2679-83. (16) Valiev, M.; Bylaska, E. J.; Govind, N.; Kowalski, K.; Straatsma, T. P.; Van Dam, H. J.; Wang, D.; Nieplocha, J.; Apra, E.; Windus, T. L., NWChem: a comprehensive and scalable open-source solution for large scale molecular simulations. Comput. Phys. Commun. 2010, 181, (9), 1477-1489. (17) Cornell, W. D.; Cieplak, P.; Bayly, C. I.; Gould, I. R.; Merz, K. M.; Ferguson, D. M.; Spellmeyer, D. C.; Fox, T.; Caldwell, J. W.; Kollman, P. A., A second generation force field for the simulation of proteins, nucleic acids, and organic molecules. J. Am. Chem. Soc. 1995, 117, (19), 51795197. (18) Lau, S.-T.; Zhou, T.; Liu, J. A.-j.; Fung, E. Y.-M.; Che, C.-M.; Lang, B. H.-H.; Ngan, E. S.-W., Dysregulation of clathrin promotes thyroid cell growth and contributes to multinodular goiter pathogenesis. Biochim. Biophys. Acta, Mol. Basis Dis. 2015, 1852, (8), 1676-1686. (19) Liang, J.; Shang, Y., Estrogen and cancer. Annu. Rev. Physiol. 2013, 75, 225-240. (20) Cos, P.; De Bruyne, T.; Apers, S.; Berghe, D. V.; Pieters, L.; Vlietinck, A. J., Phytoestrogens: recent developments. Planta Med. 2003, 69, (07), 589-599. (21) Virk-Baker, M. K.; Nagy, T. R.; Barnes, S., Role of phytoestrogens in cancer therapy. Planta Med. 2010, 76, (11), 1132-1142. (22) Keiser, M. J.; Setola, V.; Irwin, J. J.; Laggner, C.; Abbas, A.; Hufeisen, S. J.; Jensen, N. H.; Kuijer, M. B.; Matos, R. C.; Tran, T. B., Predicting new molecular targets for known drugs. Nature 2009, 462, (7270), 175. (23) Morin, P. J., beta-catenin signaling and cancer. BioEssays : news and reviews in molecular, cellular and developmental biology 1999, 21, (12), 1021-30. (24) Yao, H.; Ashihara, E.; Maekawa, T., Targeting the Wnt/beta-catenin signaling pathway in human cancers. Expert Opin. Ther. Targets 2011, 15, (7), 873-87. (25) Luo, J. L.; Kamata, H.; Karin, M., IKK/NF-kappaB signaling: balancing life and death--a new approach to cancer therapy. J. Clin. Invest. 2005, 115, (10), 2625-32. (26) Luqman, S.; Pezzuto, J. M., NFκB: a promising target for natural products in cancer chemoprevention. Phytother. Res. 2010, 24, (7), 949963. (27) Gozdecka, M.; Breitwieser, W., The roles of ATF2 (activating transcription factor 2) in tumorigenesis. Biochem. Soc. Trans. 2012, 40, (1), 230-4. (28) Gozdecka, M.; Lyons, S.; Kondo, S.; Taylor, J.; Li, Y.; Walczynski, J.; Thiel, G.; Breitwieser, W.; Jones, N., JNK suppresses tumor formation via a gene-expression program mediated by ATF2. Cell Rep. 2014, 9, (4), 1361-74. (29) Walluscheck, D.; Poehlmann, A.; Hartig, R.; Lendeckel, U.; Schonfeld, P.; Hotz-Wagenblatt, A.; Reissig, K.; Bajbouj, K.; Roessner,

Supporting Information Table S1. Proteomic analysis of proteins whose expressions were altered by DHE treatment (24 h) - TMT labeling, RP fractionation (Excel file). Table S2. Functional annotation of cellular components, biological processes and molecular functions of DHE-modulated proteins from Table S1 (Excel file).Table S3. Proteomic analysis of proteins whose expressions were altered by DHE treatment for key node analysis (Excel file). Figure S1. NMR spectrum of DHE compound. Figure S2. Cytotoxicity of DHE and cisplatin on HeLa cancer cells. Supporting protocols of offline Hp-RP StageTip fractionation, LC gradient for Hp-RP fractions, quantitated pathway and key node analysis, label free whole cell lysate shotgun proteomics approach. This material is available free of charge via the Internet at http://pubs.acs.org.

AUTHOR INFORMATION Corresponding Authors *Email: [email protected]; [email protected]; [email protected].

Author Contributions †These

authors contributed equally.

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT We thank Ms. Juan-Yu Wang for helping on isolation and characterization of dehydroeffusol. This work is supported by Innovation and Technology Fund (ITS/345/16), the Hong Kong Jockey Club Charities Trust for the project of R&D Laboratory for Testing of Chinese Medicines, the special equipment grant (SEG HKU02) from the University Grants Committee, general research fund (17127915) from the Research Grants Council (RGC) and Chinese Medicines Information and Research Section of the Department of Health, HKSAR China.

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A.; Schneider-Stock, R., ATF2 knockdown reinforces oxidative stressinduced apoptosis in TE7 cancer cells. J. Cell. Mol. Med. 2013, 17, (8), 976-88. (30) Schönthal, A. H., Pharmacological targeting of endoplasmic reticulum stress signaling in cancer. Biochem. Pharmacol. 2013, 85, (5), 653-666. (31) Averous, J.; Bruhat, A.; Jousse, C.; Carraro, V.; Thiel, G.; Fafournoux, P., Induction of CHOP expression by amino acid limitation requires both ATF4 expression and ATF2 phosphorylation. J. Biol. Chem. 2004, 279, (7), 5288-5297.


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Shotgun Proteomics and Quantitative Pathway Analysis of the

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