Comparative Secretome Analyses Using a Hollow Fiber Culture

Article pubs.acs.org/jpr

Comparative Secretome Analyses Using a Hollow Fiber Culture System with Label-Free Quantitative Proteomics Indicates the Influence of PARK7 on Cell Proliferation and Migration/Invasion in Lung Adenocarcinoma Ying-Hua Chang,†,‡ Shu-Hui Lee,† Hua-Chien Chang,† Yau-Lin Tseng,∥ Wu-Wei Lai,∥ Chen-Chung Liao,§ Yeou-Guang Tsay,# and Pao-Chi Liao*,†,⊥ †

Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan ∥ Department of Surgery, National Cheng Kung University Hospital, Tainan, Taiwan § Proteomics Research Center, National Yang-Ming University, Taipei, Taiwan # Institute of Biochemistry and Molecular Biology, National Yang-Ming University, Taipei, Taiwan ⊥ Center for Micro/Nano Science and Technology, National Cheng Kung University, Tainan, Taiwan ‡

S Supporting Information *

ABSTRACT: As the leading cause of cancer death worldwide, lung cancer lacks effective diagnosis tools and treatments to prevent its metastasis. Fortunately, secretome has clinical usages as biomarkers and protein drugs. To discover the secretome that influences lung adenocarcinoma metastasis, the hollow fiber culture (HFC) system was used along with label-free proteomics approach to analyze cell secretomes between CL1-0 and CL1-5 cell lines, which exhibit low and high metastatic potentials. Among the 703 proteins quantified, 50 possessed different levels between CL1-0 and CL1-5. PARK7 was a primary focus because of the lack of research involving lung adenocarcinoma. The cell proliferation, migration, and invasion properties of CL1-0, CL1-5, and A549 cells were significantly diminished when the expression of their PARK7 proteins was reduced. Conversely, these functions were promoted when PARK7 was overexpressed in CL1-0. In clinical expression, PARK7 levels within tissue specimens and plasma samples were significantly higher in the cancer group. This represents the first time the HFC system has been used with label-free quantification to discern the elements of metastasis in lung adenocarcinoma cell secretomes. Likewise, PARK7 has never been researched for its role in promoting lung adenocarcinoma progression. KEYWORDS: hollow fiber culture system, label-free quantitative proteomics, PARK7, cancer metastasis

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alone.2 Non-small cell lung cancer (NSCLC) accounts for approximately 85% of all cases.3 Among the histological types of

INTRODUCTION Lung cancer is the leading cause of cancer-related deaths in the United States and worldwide.1,2 The American Cancer Society has reported an estimated 222 520 new cases of lung cancer and 157 300 lung cancer-related deaths for 2010 in the United States © 2012 American Chemical Society

Received: April 16, 2012 Published: September 17, 2012 5167

dx.doi.org/10.1021/pr300362g | J. Proteome Res. 2012, 11, 5167−5185

Journal of Proteome Research

Article

strategy, in an attempt to characterize the secretory proteins involved in lung adenocarcinoma metastasis via comparing CL1-0 (low invasive ability) and CL1-5 (high invasive ability) cell secretomes.

NSCLC, lung adenocarcinoma is the most common. Many lung cancer patients are diagnosed as having distant metastatic disease, and most cancer patients die of metastases instead of their primary tumors.4 The 5-year survival rate for all stages of lung cancer is 15.2% and only 2.8% for lung cancer patients diagnosed with distant metastases.2 Metastasis is clearly evidenced as a fatal step in the progression of cancer. Unfortunately, there is a lack of effective diagnostic and prognostic tools in the clinical field for metastasis and staging predictions. Clinical treatments that effectively control cancer progression after it has already entered more advanced stages are also lacking. To further increase patients’ survival rates, studies related to the mechanisms of metastasis are of immediate importance. Metastasis, the ultimate event in a cancer’s progression, can be described as the complex process in which cancer cells travel from a tumor site and migrate through the bloodstream or lymphatic system to other parts of the body.5 During this intricate process, numerous proteins are required to assist in the progression of the tumor cells. Secretory proteins, which are released from cells via various pathways, including the classical ER-golgi pathway, vesicle release, or a specific channel, are known as the secretome.6,7 In previous research, cell secretome was widely investigated via proteomics technologies in cancer research. There are three main aspects of this research, including clinical marker discovery, understanding mechanisms of cancer progression, such as proliferation, angiogenesis, metastasis, and so forth., and cancer treatment response/resistance (Supporting Information Table 1). Among these, 8 publications compared cell secretomes with low and high metastatic abilities to find the prediction marker of metastasis and/or metastatic mediators.8−15 It was found that secretome plays vital roles in cancer metastasis, such as promoting migration/invasion and modulation of the microenvironment to facilitate angiogenesis and metastasis.16 For instance, the proteinase MMP-9 can degrade and reconstitute the extracellular matrix to facilitate tumor cell migration and invasion.17 Fibronectin, the main component of the extracellular matrix, can promote tumor cell migration and invasion by activating MMP-9 secretion through the MEK1-MAPK and the PI3K-Akt pathways.18 The tumor cells can release VEGF, FGF, IL-8, among others, to induce tumor angiogenesis.19 During cancer metastasis, chronic changes or an abnormal secretion of secretory proteins could be an indication of the pathological conditions of metastasis. Of particular interest are those proteins released from the tumor cells and enter the bloodstream, which thereby have the potential to serve as clinical diagnostic and/or prognostic markers. Such proteins may even be used to develop cancer therapies. Currently, secretory proteins are being employed in clinical applications, for example, the clinical markers CA19-9 and CA125, which are used to monitor the recurrence of pancreatic and ovarian cancers, respectively. Additionally, a target therapy medication, Avastin, which can defend against VEGF ligands, delays the progression of colon and breast cancers.20 To effectively profile a cell’s secretome, the platform known as a hollow fiber culture (HFC) system in company with mass spectrometry was established.21−23 A HFC system not only decreases the cell lysis rate, thereby increasing the authenticity of secretory protein identification, but also provides a sample of secretory proteins at a high concentration to reduce the complexity of a sample preparation.21 In a previous study, we utilized this platform to characterize the nasopharyngeal carcinoma cell secretome and to discover plasma biomarkers.22 Here, the HFC platform was extended for not only secretome identification, but also for quantification using a label-free

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MATERIALS AND METHODS

Cell Lines

The poorly differentiated adenocarcinoma cell lines CL1-0 and CL1-5 were provided by Dr. P.-C. Yang (Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan, Republic of China)24 and cultured at 37 °C with 5% CO2 in RPMI-1640 media supplemented with 10% fetal bovine serum (FBS) (Gibco BRL, Gaithersburg, MD), 1% penicillin (Invitrogen, Carlsbad, CA), and 2 g/L NaHCO3. These two cell lines showed different invasiveness according to previous research in which the migration protein marker, vimentin, matrigel invasion assays, and lung colonization assays were used.24 The lung adenocarcinoma cell line A549 was purchased from the American Type Culture Collection (ATCC) and maintained in DMEM media supplemented with 10% FBS, 1% penicillin (Invitrogen, Carlsbad, CA), and 3.7 g/L NaHCO3. Harvesting Conditioned Media from CL1 Cancer Cell Lines Using a HFC System

The volume of serum medium was slowly reduced and replaced with serum-free medium consisting of RPMI 1640 with 15% CDM-HD serum replacement (FiberCell Systems, Inc., Frederick, MD) and 1% antibiotics. Following 2−3 passages, the cells were transferred to the HFC system, after which the cells were completely adapted to serum-free medium. CL1-0 and CL1-5 cells (∼5 × 107) were suspended in serum-free medium then inoculated into the extra-capillary space (ECS) of the hollow fiber cartridge. Secretome samples in conditioned media (CM) from the ECS of the HFC system (∼15 mL) were collected every 24 h. The media used for maintaining cell growth was refreshed every day. In addition, glucose and lactate concentrations were also measured to monitor cell growth in the HFC system daily. The kits of glucose and lactate measurement were purchased from Roche. The detailed procedure has been described in a previous study.21,22 CM harvested from the ECS of the HFC system was ultracentrifuged at 10 000g for 1 h to remove cell debris, then concentrated using Amicon Ultra-15 tubes (molecular weight cutoff 3 kDa; Millipore, Billerica, MA). The protein concentrations of the secretome samples were determined using the Bradford assay (Bio-Rad, Hercules, CA). Sample Purification and Digestion

An equal amount (50 μg) of CL1-0 and CL1-5 CM cells was purified using the stacking gel-aided purification method, which was previously established for secretome sample cleanup.25 Briefly, the CM samples were run on a self-poured stacking gel that contained 50% running gel and a 4% stacking gel. Protein samples (50 μg in a 30 μL volume) containing the sample dye and 0.5 M DTT were boiled for 10 min at 95 °C and loaded on the gel. SDS-PAGE was then performed at 55 V for 30 min. The protein samples were stacked to the border between the stacking and running gel. Coomassie Brilliant Blue R-250 was used to stain the gel. All bands were excised and digested in-gel with trypsin. The gel pieces were reduced with 0.5 M DTT (56 °C) and alkylated with saturated iodoacetamide at room temperature, with each step requiring 1 h. Twenty microliters of 0.1 μg/μL of modified trypsin was added to the gel pieces, and they were 5168



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incubated overnight at 37 °C. The digested peptide samples were cleaned with a C18 tip before mass spectrometry analyses were performed (VARIAN, Palo Alto, CA). The CL1-0 and CL1-5 CM samples were processed in technical triplicate.

IDEAL-Q uses the process of automated quantification for peptides according to the information from mzXML and XML for spectral data and identified the peptide and protein results, respectively. For LTQ-Orbitrap, the parameters used were the default values, except for the RT range for extracting the data, which was set at 1.5 min. In the recalculation of the ratio setting, the spectral data were required to pass the signal-noise ratio, charge state, and isotope pattern, which further existed in all runs. Normalized peptide abundance was used to adjust for median signal variances from run to run. The minimum distinguishable analytical signal has an abundance of a blank signal plus 3 times the standard deviation (SD), which was represented as undetectable peptide abundance. All the quantitative results for the peptides were manually validated to evaluate the overall performance of IDEAL-Q. The proteins must possess at least two quantified peptides (different m/z) for successful quantification. The presence of each protein isoform was confirmed by the identification of at least one unique peptide.

Mass Spectrometry (MS) Analyses

All MS analyses were performed using a LTQ-Orbitrap (Discovery) hybrid mass spectrometer with a nanoelectrospray ion source (ThermoElectron, San Jose, CA) coupled with a nano flow HPLC (Agilent Technologies 1200 series). The peptides were eluted using a 13.5 cm long, 75 μm inner diameter tip column (YMC-Gel, Liquid Chromatography) with mobile phases A (0.1% formic acid in water) and B (0.1% formic acid in acetonitrile). The pump flow rate was set to 0.5 μL/min, and peptide elution was achieved using a linear gradient of 5−40% B for the first 140 min followed by a rapid increase to 95% B for the next 15 min. Two blank washes were performed following each sample run. The conventional MS spectra (survey scan) were acquired at resolution (M/ΔM, 30 000 full width half-maximum) over the acquisition range of m/z 400−2000, and a series of precursor ions were selected for the MS/MS scan. The MS scan examined the accurate mass and the charge state of the selected precursor ion and the MS/MS scan acquired the spectrum (CID spectrum or MS/MS spectrum) for the fragment ions generated by the collision-induced dissociation. The data-dependent procedure that was performed alternated between one MS scan and five MS/MS scans for the five most abundant precursor ions in the MS survey scan. The m/z values selected for MS/MS were dynamically excluded for 180 s. The electrospray voltage applied was 1.8 kV.

Bioinformatics Analysis

The SignalP 4.0 program, along with the neural network-based method, was used to predict the presence of secretory signal peptide sequences.28−30 A D-value above 0.45 indicated the existence of signal peptides. The secretomeP program was performed to predict nonsignal peptide-triggered protein secretion, and an NN-score ≥0.5 indicated possible secretion.31,32 TMHMM was performed to predict transmembrane helices in proteins.33 The subcellular locations of proteins were classified according to Human Protein Reference Database and Gene Ontology.34 The available databases for the Human Plasma Database35 and ExoCarta: exosome proteome database36 were used to search for the existence of the identified proteins in human blood and exosomes released from cells, respectively.

Protein Identification and Quantification

Each cell line CM sample was performed in triplicate. The resulting MS/MS data were converted into a peak list using the noncommercial software, Raw2msm, set at the default value. The parameters were: top 6 most intense fragment ions per 100 Da were merged as a peak, tolerance of parent ions was 10 ppm, minima charge of deisotope was 2, the cutoff values of centroid was 20%, and retention time region of XIC was 1 min.26 The peak lists from each run were merged for a further Mascot search. The Mascot search engine’s database (version 2.2, Matrix Science, London, U.K.) was searched against Swiss-Prot (Version 57.7; release date, September 1, 2009; 497 293 sequences; human taxonomy) to analyze all the MS/MS spectra. The search parameters for the MS and MS/MS mass tolerances were ±0.1 and ±0.5 Da, respectively. Two missed cleavages from the trypsin digest and variable modifications of carbamidomethylation (Cys), deamidation (Asn, Gln), and oxidation (Met) were permitted during the process. When evaluating the false-discovery rate (FDR), we used identical search parameters and validation criteria to perform a decoy database search against a randomized decoy database that was created using Mascot. The FDR was required to be less than 2% for the identifications to be accepted. Identified proteins with Mascot scores above the statistically significant threshold (p < 0.05) were accepted. In addition, these proteins needed to be assigned at least two rank 1 unique peptides to be considered successfully identified. The proteins identified as common trypsin autolysis peaks as well as keratin contamination were excluded. Data quantification for the labelfree experiments with multiple LC-MS/MS runs was performed using IDEAL-Q.27 The program ReAdw, which is available at http://tools.proteomecenter.org/software.php, was used to convert the data format from .raw to a mzXML file, and the Mascot search results were reported in the XML format.

Western Blot

The antibodies and dilution titers are listed in Supporting Information Table 2. SDS-PAGE (12% gel) was used to separate the CM and cell extract samples (30−50 μg). When transferring the proteins to a PVDF membrane, iBlot (Invitrogen, Carlsbad, CA) was used in accordance with the manufacturer’s protocol. The membrane was placed in a 5% nonfat milk solution for 1 h at room temperature. Then, primary antibodies were probed on the membranes overnight (4 °C). The membranes were then washed with Tris-buffered saline and Tween-20 (TBST) three times before being incubated with horseradish peroxidase-conjugated secondary antibodies for 1 h at room temperature (SigmaAldrich, St. Louis, MO). Before the membranes were developed using enhanced chemiluminescence detection, they were washed with TBST five more times. Exosome Fraction Purification

The ExoQuick commercial kit was used to purify exosomes from the CM samples, and was performed in accordance with the manufacturer’s instructions (System Biosciences, Mountain View, CA). Briefly, the ratio between the ExoQuick solution and the concentrated CM sample was 1:1. The mixed sample was refrigerated overnight and was centrifuged at 1500g for 40 min to obtain the exosome pellet. PARK7 Knock-Down and Overexpression

The siRNA of PARK7 was purchased from Santa Cruz Biotechnology (Santa Cruz, CA). The siRNA transfection process was performed according to the manufacturer’s instructions and applied to the CL1-0, CL1-5, and A549 cell lines. Briefly, 8 μL of 10 μM siRNA was mixed with 6 μL of transfection reagent and 5169



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made available to treat 2 × 105 cells. PARK7 gene overexpression in CL1-0 cells was achieved through transfection with commercial plasmid DNA (MHS1010-57714, Thermo Openbiosystems, Huntsville, AL) using the TurboFect transfection reagent according to the manufacturer’s instructions (OriGene Technologies, Inc., Rockville, MD). Briefly, 2 μg of plasmid DNA was mixed with 8 μL of transfection reagent to treat 1 × 105 CL10 cells. When evaluating the direct effect of PARK7 protein knock-down and overexpression on cancer cell growth in vitro, 3-[4,5dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide (thiazolyl blue, MTT) proliferation analyses were performed. The cells were seeded in a 96-well plate at a concentration of 2 × 103 cells per well. The contents of the tray were incubated for 24 h and treated with the siRNA. After 24 h, 2 μL of MTT (10 mg/mL) was added to the wells before incubation for 3 h at 37 °C. The cells were then lysed with 100 μL of dimethyl sulfoxide. Microplate photometers were used to measure absorbance at 595 nm (Thermo Fisher Scientific, Inc., Waltham, MA), and cell growth within each group was monitored every 24 h for 72 h. The results were obtained by culturing the cells for each condition in 6 different wells during the three independent experiments.

specimen was sampled in replicate by sampling tumor tissue cores (1.0 mm in diameter). Immunohistochemistry (IHC) was performed on 4-μm-thick formalin-fixed paraffin-embedded sections. Rabbit anti-PARK7 (1:250 dilution, Epitomics, CA) was used as the primary antibody. The procedures were performed with the Bond-Max Automated IHC stainer (Leica Biosystems Newcastle Ltd., Australia) according to the following protocol. Tissues were deparaffinized with xylene and pretreated with the Epitope Retrieval Solution 1 (citrate buffer, pH 6.0) at 100 °C for 30 min, followed by hydroperoxide blocking for 5 min using the Bond Polymer Refine Detection Kit (Leica Biosystems Newcastle Ltd., United Kingdom). The primary antibody was incubated at room temperature for 30 min. The anti-mouse/ rabbit poly-HRP secondary antibody was incubated at room temperature (Leica Biosystems Newcastle Ltd., United Kingdom) for 8 min and developed with 3,3′- diaminobenzidine chromogen. Counterstaining was carried out with hematoxylin. Image analysis of PARK7-positive cells was further quantified by using TissueFaxs microscopy system with the HistoQuest software module (TissueGnostics, Vienna, Austria). The commercial PARK7 ELISA kit was used to measure the protein level in plasma samples (MBL International, Woburn, MA). The process was completed according to the manufacturer’s instructions.

Transwell Migration and Matrigel Invasion Assay

Statistical Analysis

BD Falcon multiwell insert systems with 8-μm pores (BD Biosciences, San Jose, CA) were applied to the migration assay to examine cell migration. The upper wells contained 1 × 105 cells seeded in a serum-free medium, while the lower chambers were filled with a complete medium supplemented with 10% FBS to induce cell migration. The cells were then incubated at 37 °C for 6 h to eliminate interference from cell proliferation, at which point the membranes were fixed with methanol. The cells were then stained with Giemsa stain, and the number of cells that migrated through the membrane on the lower side was determined. Cells that were able to cross the filter to the lower chambers were counted at 200× magnification in 6 different fields per filter via Carl Zeiss Axio Imager A1 light microscope (Carl Zeiss, Germany). The experiment was performed in triplicate. In preparation for the invasion assay, BD Falcon multiwell insert systems containing 8-μm pores were coated with 2 mg/mL BD Matrigel basement membrane matrix (BD Biosciences, San Jose, CA). The steps followed were then the same as those described for the transwell migration assay, as described above.

This study used SPSS software (SPSS 18.0, Chicago, IL) and two-tailed tests, with a statistically significant p-value of less than 0.05, which was applied to all tests. The Mann−Whitney U test, kruskal-wallis test, and t test were used to determine the differences between groups. The Kaplan−Meier curve was used to describe the 3-year survival rate and progress-free rate between groups with low (below first quartile) and high (above first quartile) PARK7 plasma levels. P-values were calculated using the log-rank test for equality of strata.

MTT Proliferation Assay

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RESULTS

Confirmation of Cell Line Migration/Invasion Properties after Serum-Free Medium (SFM) Adaptation

CL1-0 and CL1-5 are lung adenocarcinoma cell lines derived from the same parental cell line with low and high invasive abilities, respectively.24 To investigate the secretory protein profiles between the two cell lines, it is necessary to understand the mechanisms that secretory proteins regulate for cancer cell migration/invasion promotion and inhibition. The first step is to eliminate the protein contamination from serum proteins in the culture medium. Thus, the protein-free serum replacement CDM-HD was used to form the serum-free medium (SFM) for the cell secretome investigation. However, the cells’ properties were expected to be altered after SFM adaptation, that is, altered with regards to morphology, cell proliferation, migration, and invasiveness. Our results demonstrated that the CL1-0 and CL1-5 cells did not significantly alter their morphologies (Figure 1A), proliferation (Figure 1B), migration, or invasiveness (Figure 1C−E) after SFM adaptation, compared to cells grown in serum medium.

Tissue Microarray (TMA) and Sandwich ELISA

Patients were selected if lung adenocarcinoma was their primary diagnosis, they had no prior history of cancer, and received surgery as their first treatment. The testing samples were obtained from their surgery. The lung adenocarcinoma tissue and plasma samples were provided by the tissue bank of National Cheng Kung University Hospital from 2003 to 2009. The plasma samples of healthy controls with no cancer history, whose age and gender matched those of the patients, were collected from the health examination center of National Cheng Kung University Hospital in 2011. Supporting Information Tables 3 and 4 exhibit detailed clinicopathological characteristics. All of the patients and healthy controls who provided tumor tissue specimens and plasma gave written informed consent in accordance with the rules and requirements of National Cheng Kung University Hospital’s ethics committee. The TMA slides were purchased from the hospital’s tissue bank. Each tissue

CM Sample Collection and Quality Inspection

In previous studies, the HFC system platform has been established as improving the efficiency of cell secretome collection and further qualitative protein identification using tandem mass spectrometry.21−23 To ascertain the precise secretory proteins that regulate cancer cell migration and invasion in lung 5170



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Figure 1. Confirmation of cell line properties before and after serum-free medium (SFM) adaptation. (A) Micrographs (200× ) of cells’ morphology using Carl Zeiss Axiovert 40 C Inverted Microscope. (B) Cell proliferation was investigated via MTT assay from 0 to 72 h. There were no significant differences between serum medium and SFM conditions in each cell lines. (C) The protein marker, vimentin, which was used to evaluate migration abilities for each cell lines. The results showed that the CL1-0 and CL1-5 cell lines have different expression levels of vimentin and no significant differences when adapted to SFM. (D) Transwell migration assay at 100× magnification. Migration was quantified by counting cells in six random fields per membrane using Carl Zeiss Axio Imager A1 light microscope. (E) Matrigel invasion assay at 200× magnification. Invasion was quantified by counting cells in six random fields per membrane. The columns represent the average number of cells per field of at least eighteen fields from three independent experiments. The bars show standard deviation. (D and E) Both exhibited low and high migration and invasion abilities in CL1-0 and CL1-5, respectively. No significant (N.S.) influences on cell migration or invasiveness after SFM adaptation were observed. 5171



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purification. The G3PDH protein appeared in similar amounts between the CM sample (50 μg) and exosome fraction, which was purified from 50 μg of CM sample (Figure 3E). These results indicate that intracellular proteins have a high probability of being released into the extracellular space via exosome secretion.

adenocarcinoma, this analytical platform, the HFC system, was performed along with label-free quantitative technology. The overall procedures are displayed in Figure 2. The cell lines’

Characterization of Secretory Proteins Using the HFC System along with Label-Free Quantification

The CM samples from the CL1-0 and CL1-5 cell lines were processed in technical triplicate. Proteins were considered successfully identified if they possessed at least two unique peptide sequences and if both peptides were rank 1 peptides, as defined by the Mascot database search (Supporting Information Tables 5 and 6). A total of 412 and 531 proteins were identified in CL1-0 and CL1-5 cells, respectively (Supporting Information Table 5). Subsequently, identified proteins were quantified via IDEAL-Q software. After determining all peptide run abundances in the LC−MS/MS run, the median of all peptide run abundances in the LC-MS/MS run was selected as the normalization factor to eliminate systematic errors. A protein was accepted if it had at least two unique peptide sequences that could be quantified (Supporting Information Table 5. A total of 703 proteins were considered successfully quantified. Proteins can enter into the CM through various pathways. Examples include membrane protein shedding, signal peptide predominance, exosome delivery, exocytosis, or intracellular protein contamination (cell lysis). The Human Protein Reference Database and Gene Ontology Database report 29.0% (204/703) of classified proteins as extracellular and/or membrane-related proteins (Supporting Information Figure 1A and Supporting Information Table 5. Moreover, the bioinformatics program SignalP 4.0 characterizes the presence of signal peptides, SecretomeP 2.0 is a predictor of proteins secreted by a nonsignal peptide trigger, and TMHMM is a predictor of transmembrane helices in proteins.28−33 A total of 440 (309/ 703) of the identified proteins must have been released into the CM through these three pathways (Supporting Information Figure 1A and Supporting Information Table 5. When considering what percentage of the 703 identified proteins would have been secreted by the cells via exosomes, the ExoCarta database (http://exocarta.ludwig.edu.au/) was used, for which 34.1% (240/703) of the identified proteins were found to exist in the database (Supporting Information Figure 1A and Supporting Information Table 5. It is important to note that proteins present in human blood are released from cells, and it is highly probable that these proteins possess medical value as clinical biomarkers. Of the 703 identified proteins, 78.5% (552/703) were found in the plasma proteome database (http://www. plasmaproteomedatabase.org/) (Supporting Information 1A and Supporting Information Table 5. After all analyses had been considered, 90.8 (638/703) of the identified proteins were found to be released into the CM via the aforementioned mechanisms. Supporting Information Figure 1A also presents secretion evidence of individual cell lines. Simply, 90.1 (371/ 412) of CL1-0 and 92.7 (492/531) of CL1-5 were assigned different secretion possibilities via various mechanisms. The Metacore software’s FDR filter was set at 0.01 (GeneGo, Joseph, MI), and among the 703 quantified proteins, the 20 most significant processes were separated into two main aspects, including cellular component organization and cellular metabolic processes (Supporting Information Figure 1B). In addition, the 20 most significant molecular functions were related to protein binding, catalytic activity, and hydrolase activity (Supporting

Figure 2. Outline of experimental workflow for CL1 cell secretomes analyses coupled with label-free quantitative proteomics for discovery of secretory protein regulators for lung adenocarcinoma metastasis.

properties were confirmed after SFM adaptation and then transferred to the HFC system for long-term culturing in preparation for conditioned media (CM) collection. Data regarding glucose consumption, lactate production, and protein concentration were collected each day to monitor the growth of the cell lines (Figure 3A and 3B). Previous literature has pointed out that the most promising stage of the metastasis process for therapeutic targeting is the growth phase.38 CM samples in the growth phase (from day 2 to 10) were pooled in 10 μg each day for further investigation. To evaluate levels of contamination from the intracellular proteins that were released into the CM samples via cell lysis, a known lysed cell number was used to correspond with the amount of the housekeeping protein tubulin as a standard to estimate the lysed cell number in the CM samples.21 Figure 3C shows that the cell lysis rates in the CL1-0 and CL1-5 CM samples were under 0.0038%. In previous studies, evidence has revealed that intracellular proteins are released into the extracellular space via various pathways, including membrane protein shedding and secretion via exosomes.39,40 In the processes of CM sample preparation and CM protein digestion, there was a high probability that the CM sample still contained an exosome fraction according to previous studies. Exosome would be retained in CM samples unless the CM samples were ultracentrifuged at 60,000−100,000g.41,42 The stacking gel-aided purification method was also used in our research. The SDS could assist disruption of, and/or solubilize, the vesicle proteins.43,44 The exosome markers, Alix and CD9, were used to prove the existence of exosome in CM samples.45,46 Figure 3D illustrates that exosomes did indeed exist in the CM samples. Furthermore, we hypothesized that intracellular proteins would be detected in CM samples by the exosome mechanism. The housekeeping protein G3PDH might fit this hypothesis, without being released into the CM sample via cell lysis. A total of 100 μg of CM sample was equally separated into two parts. One of the CM parts was used for exosome 5172



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Figure 3. Collection of CM samples and quality inspection. (A) Daily glucose consumption and lactate concentration in HFC system. (B) Daily protein concentration in the ECS throughout the culture period. (C) Estimation of cell lysis rate in HFC system. Cytoskeleton protein levels, tubulin, were evaluated using a calibration curve plotted from cell lysate samples. The rate of cell lysis was under 0.0038% in both CL1 cell lines. (D) The presence of CD9 and Alix proteins in CL1-0 and CL1-5 CM samples confirm the existence of exosomes in the CM. Exo indicates that the exosomes were purified from CM samples via the commercial kit. (E) The expression level of known cytoplasm housekeeping protein, G3PDH, presented no significant difference between the CM (50 μg) and purified exosome fraction which was derived from the 50 μg of CM sample.

extracellular space/secreted, according to the Human Protein Reference/Gene Ontology databases, or if the prediction software and exosome/plasma databases could produce 2 pieces of evidence that the proteins were secreted, then these were considered to be high quality secreted proteins with different expression levels between the CL1-0 and CL1-5 cells. A total of 50 proteins were identified with different levels between these two cell lines (Table 1). Among these proteins, 25 and 25 proteins exhibited high levels in the CL1-0 and CL1-5 cells, respectively.

Information Figure 1C). Furthermore, after individually analyzing the processes of each cell line, it was found that the top five processes are related to metabolic processes and cellular component organization in CL1-0 and CL1-5 cells, respectively (Supporting Information Figure 1B). These findings may provide hints about the key functions of secretomes within cell lines, especially regarding the way in which different levels of invasiveness might occur within the different processes of metastasis. To determine which proteins had different activity levels between the CL1-0 and CL1-5 cell lines, the following procedures were performed. All peptides corresponding to their respective proteins in each run were calculated for their geometric mean, which provided the protein’s final abundance. After this step was performed, each protein with three protein abundances after technical triplicate analyses in the respective CL1-0 and CL1-5 cell lines was examined via t test. The p-values were then examined using a multiple hypothesis test, Benjamini and Hochberg (BH), to filter false positives.47 The p-values of quantified proteins past a level of BH 1% were considered to be significantly different between the CL1-0 and CL1-5 cell lines. Likewise, proteins with subcellular localizations described as

Selection of Protein Candidates Involved in Possible Mechanisms via Interactome analysis

To find pathways that may regulate cancer progression, protein− protein interactions were analyzed among the 50 differentially expressed proteins using the STRING 9.0 database. Supporting Information Figure 2 shows that there were 29 proteins involved in 5 possible pathways. Each pathway contains at least 4 proteins that are in direct and/or indirect association with each other via this protein−protein interaction database. Because there have only been a few studies describing their functions with regards to cancer metastasis within lung adenocarcinoma, only 7 proteins were selected based on these results. The five proteins ACTN4, 5173


Radixin

RADI_HUMAN

DNA-(apurinic or apyrimidinic site) lyase

Lysosomal protective protein

APEX1_HUMAN APEX1

PPGB_HUMAN

5174

Cadherin-23

Phosphoserine aminotransferase

CAD23_HUMAN CDH23

SERC_HUMAN

SLC1A5

AAAT_HUMAN

MYO6_HUMAN MYO6

Serine protease inhibitor Kazal-type 5

SPINK5

ISK5_HUMAN

Myosin-VI

Neutral amino acid transporter B(0)

Disintegrin and metalloproteinase domain-containing protein 7

ADAM7_HUMAN ADAM7

Ezrin

13

6.3

24.7

8.8

32.3

EZR

EZRI_HUMAN

9.6 18.1

Plasma alpha-Lfucosidase

FUCO2_HUMAN FUCA2

11.3

15.4

7.5

24.1

11.3

20.8

41.5

32.1

22.7

LDH6B_HUMAN LDHAL6B L-lactate dehydrogenase A-like 6B

Glutathione reductase, mitochondrial

GSHR_HUMAN GSR

PSAT1

Thyroid receptorinteracting protein 11

TRIPB_HUMAN TRIP11

CTSA

Ras-related protein Rab-1A

RAB1A_HUMAN RAB1A

RDX

Flotillin-1

protein name

FLOT1_HUMAN FLOT1

Swiss-Prot acc. no. gene name

28

3

35

8

17

5

6

6

10

28

61

9

6

8

19

12

no. of total coverage identified (%) peptides

4

3

4

3

6

2

3

3

2

6

9

2

3

3

8

3

21

3

30

6

15

5

6

6

10

23

48

9

6

8

18

11

0.50

0.49

0.49

0.48

0.47

0.45

0.45

0.45

0.44

0.43

0.42

0.35

0.34

0.34

0.24

0.21

1.38

0.32

0.93

1.52

0.77

1.20

1.12

0.99

1.04

2.15

1.32

0.69

1.23

1.32

1.78

0.57

0.08

0.01

0.05

0.09

0.07

0.15

0.15

0.05

0.01

0.10

0.18

0.11

0.09

0.10

0.09

0.01

0.71

0.14

0.48

0.78

0.37

0.58

0.52

0.46

0.46

0.97

0.49

0.25

0.41

0.42

0.44

0.12

0.05

0.04

0.06

0.07

0.04

0.06

0.04

0.03

0.09

0.07

0.02

0.02

0.02

0.01

0.01

0.06

N

N

N

N

N

Y

Y

Y

N

N

Y

Y

N

N

N

N

N

Y

N

N

N

Y

Y

Y

N

Y

N

Y

Y

N

N

Y

N

Y

N

N

N

N

N

N

N

N

N

N

N

N

N

N

Y

Y

N

N

Y

Y

Y

Y

Y

N

N

Y

N

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

median of SD of median of SD of normalized normalized normalized normalized abundance abundance abundance abundance plasma in CL1-0 in CL1-0 in CL1-5 in CL1-5 SignalPb SecretomePc TMHMMd exosomee databasef

Proteins with High Levels in CL1-0

no. of rank1 no. of unique quantified peptides peptides ratioa

Table 1. The 50 Quantified Protein with Different Expression between CL1-0 and CL1-5 Cell Lines

Nucleus, Cytoplasm, Membrane

Membrane

Secreted

Membrane

Membrane, Cytoplasm

unknown

Secreted

Mitochondrion

unknown

Cell membrane

Peripheral membrane protein, Cytoplasm

Lysosome

Nucleus, Cytoplasm

Golgi apparatus, Endoplasmic reticulum

Cell membrane, Cytoplasm

Cell membrane, Peripheral membrane protein

subcellular locationg

Journal of Proteome Research Article


Connective tissue growth factor

Brix domain-containing protein 1

Protein eyes shut homologue

CTGF_HUMAN CTGF

BXDC1_HUMAN RPF2

EYS_HUMAN

Vasorin

VASN_HUMAN

5175

Asparaginyl-tRNA synthetase, cytoplasmic

NARS

GOT1

GGH

FTL

SYNC_HUMAN

AATC_HUMAN

GGH_HUMAN

FRIL_HUMAN

SPB6_HUMAN

Glyoxalase domaincontaining protein 4

Ferritin light chain

Gamma-glutamyl hydrolase

SERPINB6 Serpin B6

GLOD4_HUMAN GLOD4

Endoplasmic reticulum aminopeptidase 1

ERAP1_HUMAN ERAP1

Aspartate aminotransferase, cytoplasmic

Sarcolemmal membrane-associated protein

SLMAP_HUMAN SLMAP

Kinesin-like protein KIF16B

Transmembrane and TPR repeat-containing protein 3

KIF16B

TMTC3_HUMAN TMTC3

KI16B_HUMAN

ATS17_HUMAN ADAMTS17 A disintegrin and metalloproteinase with thrombospondin motifs 17

VASN

Tripartite motifcontaining protein 6

TRIM6_HUMAN TRIM6

EYS

Probable phospholipidtransporting ATPase IIA

protein name

ATP9A_HUMAN ATP9A


Table 1. continued

20.5

36.1

51.4

37.1

49.6

9.1

15.1

22.8

18

10

13

14

20

22

6

14

25

29

34

9

6.8

21

5

4

16

13

7

31

10.1

10.5

5.8

32

22.9

18.3


3

6

6

10

14

3

6

6

5

8

5

3

3

5

5

3

4

0.62

0.60

0.60

0.55

0.54

0.54

0.53

0.52

0.50

1.94

0.93

1.31

0.39

1.07

0.71

1.28

1.30

2.05

0.03

0.04

0.03

0.03

0.09

0.01

0.12

0.18

0.04

8

10

14

19

21

6

12

22

1.82

1.74

1.61

1.60

1.59

1.49

1.40

1.35

0.62

1.14

0.93

0.41

0.45

0.94

0.53

0.80

0.02

0.16

0.04

0.05

0.03

0.11

0.11

0.08


20

28

9

3

4

13

11

6

24

1.15

2.08

1.49

0.69

0.73

1.25

0.70

1.06

1.19

0.56

0.78

0.19

0.57

0.35

0.64

0.68

1.01

0.07

0.08

0.03

0.01

0.04

0.10

0.04

0.01

0.06

0.02

0.05

0.04

0.04

0.05

0.04

0.06

0.02

N

N

N

Y

N

N

Y

N

N

Y

Y

N

Y

N

Y

Y

N

N

Y

N

Y

N

N

Y

N

Y

N

Y

N

Y

Y

N

Y

Y

N

N

N

N

N

N

N

Y

Y

N

N

Y

N

N

N

N

Y

Y

N

Y

Y

Y

Y

Y

N

N

N

N

Y

N

N

N

N

N

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

N

N

Y

Y

Y




Cytoplasm

Mitochondrion

Cytoplasm

Secreted, Lysosome, Melanosome

Cytoplasm

Cytoplasm

Endoplasmic reticulum membrane

Cell membrane, Cytoplasm

Membrane

Cytoplasm

Secreted

Membrane, Secreted

unknown

Secreted

Nucleus

Secreted

Membrane




Alpha-actinin-4

Puromycin-sensitive aminopeptidase

ACTN4_HUMAN ACTN4

PSA_HUMAN

6-phosphogluconate dehydrogenase, decarboxylating

PGD

SYT6

6PGD_HUMAN

SYT6_HUMAN

5176

15.8

Cystatin-C

Mammalian ependyminrelated protein 1

Biotinidase

CYTC_HUMAN CST3

EPDR1_HUMAN EPDR1

BTD

SERPINE1 Plasminogen activator inhibitor 1

FN1

BTD_HUMAN

PAI1_HUMAN

FINC_HUMAN

Peroxiredoxin-4

Cathepsin L1

PRDX4_HUMAN PRDX4

CATL1_HUMAN CTSL1

15.6

14.4

30.6

23.7

33.3

21.5

7

2

7

59

14

10

5

3

6

11

4

16

19

13

14

37

44

5

2

7

36

8

5

2

3

4

7

2

4

11

8

5

22

25

6

2

7

52

13

10

4

3

6

10

3

15

19

12

14

33

37

7.39

6.31

5.41

4.34

4.32

3.05

2.98

2.82

2.74

2.50

2.26

2.26

2.19

2.15

1.98

1.94

1.87

0.56

0.14

0.13

0.25

0.33

0.44

0.32

0.46

0.44

0.48

0.67

0.35

0.45

0.60

0.73

0.39

0.65

0.25

0.01

0.01

0.01

0.00

0.02

0.07

0.09

0.13

0.05

0.10

0.01

0.04

0.04

0.04

0.01

0.02

4.31

1.01

0.74

1.16

1.41

1.37

0.95

1.29

0.98

1.23

1.48

0.81

0.95

1.28

1.42

0.77

1.21

0.54

0.13

0.04

0.17

0.21

0.08

0.05

0.10

0.10

0.07

0.06

0.12

0.04

0.07

0.03

0.04

0.06

Y

Y

N

Y

Y

N

N

N

Y

N

N

N

Y

N

Y

N

Y

Y

Y

Y

Y

Y

Y

N

Y

Y

N

N

N

Y

N

N

N

N

N

N

N

N

N

N

N

Y

N

N

N

N

N

N

N

N

N

N

Y

Y

Y

Y

N

N

Y

Y

Y

N

Y

Y

Y

Y

Y

Y

b

Y

N

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y




Lysosome

Cytoplasm, Secreted

Cytoplasm, Cell membrane

Secreted

Secreted

Secreted

Secreted

Secreted

Secreted

Cytoplasm

Cytoplasmic vesicle, secretory vesicle

Cytoplasm

Endoplasmic reticulum lumen, Melanosome

Nucleus, Cytoplasm

Cytoplasm, Nucleus

Nucleus, Cytoplasm

Secreted


Protein ratio: (Geometric mean of protein abundances of CL1-5 cells in triplicate analyses)/(Geometric mean of protein abundances in CL-−0 cells in triplicate analyses). Results of SignalP software prediction. Y represented D-score >0.45, and N represented ≤0.45. cResults of SecretomeP software prediction. Y represented NN-score >0.5, and N represented ≤0.5. dResults of TMHMM software prediction. Y represented sequence number of predicted TMHs ≥ 1, and N represented 0. eHuman exosome database of ExoCarta. Y represented identified protein exists in database and N represented not. fPlasma proteome database. Y represented identified protein exists in database and N represented not. gSubcellular locations of identified proteins classified by Gene Ontology Database and Human Protein Reference Database.

a

Gamma-enolase

ENOG_HUMAN ENO2

Fibronectin

12.3

LG3BP_HUMAN LGALS3BP Galectin-3-binding protein 21

41.3

6.3

27.7

31.3

36

13.5

41.5

16.5


Phosphoglycerate mutase 1

PGAM1_HUMAN PGAM1

78 kDa glucoseregulated protein

GRP78_HUMAN HSPA5

Synaptotagmin-6

Protein DJ-1

PARK7_HUMAN PARK7

NPEPPS

Agrin

protein name

AGRIN_HUMAN AGRN


Table 1. continued




Article

Clinical Expression of PARK7 in Tissue Specimen and Plasma

FN1, PARK7, PRDX4 and GRP78 were found at high levels within the CL1-5 cells, and MYO6 and GSR were found at high levels within the CL1-0 cells. These protein levels were further confirmed for their expression levels via Western blot (Figure 4).

The tissue microarray, which included 64 cancerous tissues and 31 adjacent normal tissues, showed that the expression levels of PARK7 are significantly related to the TNM stage and lymph node metastasis (Supporting Information Figure 3 and Supporting Information Table 3). In addition, the expression levels of PARK7 in cancerous tissues were significantly higher than normal tissues (Figure 6A). A receiver operating characteristic (ROC) curve analysis was used to evaluate the separate efficacy of stage I and stage II. This method could assist doctors in choosing the appropriate treatment and indicate the spread of cancer has initiated. The area under the ROC curve (AUC) was determined to be 0.7 (95% CI, 0.52−0.92) for PARK7 (Figure 6B). When the cutoff point gray value was chosen as 119.3, sensitivity and specificity values were 67.4 and 70.3, respectively. In plasma samples, the PARK7 expression levels were significantly higher in patients than in healthy controls (Supporting Information Table 4). However, there were no significant differences between gender, age, T stage, N stage, M stage, and overall TNM stages. The 3-year survival and progression-free rates showed that when the cutoff value of PARK7’s expression level was within the first quartile (splits lowest 25% of data), patients with levels below this quartile had lower survival and progression-free rates as compared to patients with levels above the quartile (Figure 6C,D).

Figure 4. Protein samples were first separated on SDS-PAGE gels, transferred to PVDF membranes, and then probed with the necessary antibodies. There were 2 and 5 CM proteins with high expression in CL1-0 and CL1-5, respectively.

■

DISCUSSION Proliferation, migration, and invasion are cell abilities that significantly affect cancer progression and further contribute to metastasis.50 The distinct molecular mechanism underlying metastasis is the process by which tumor cells detach from the primary site and further migrate and invade into surrounding tissue. The tumor cells intravasate into blood or lymphatic vessels and survive in the circulation system. Finally, they extravasate and undergo outgrowth at a secondary site. In previous studies, secretory proteins have been shown to influence each step of this process. For instance, FLOT1 and MYO6 promote proliferation and tumorigenesis.51,52 Agrin is suspected to be a facilitator of neoangiogenesis in human hepatocellular carcinoma to promote cancer progression.53 FN1 and ACTN4 may regulate cell migration and invasion abilities.54−56 Unfortunately, the mechanisms of this complex process are still under investigation. More secreted proteins that have key roles and/or specific molecules that regulate metastasis in lung adenocarcinoma must be located. On the basis of previous studies, CL1-0 and CL1-5, lung adenocarcinoma cells derived from the same parental cell line with low and high invasive abilities, respectively,24 offer an optimal model for investigating the behavior of these cells, as they are involved in metastasis.57−60 Therefore, the HFC system along with a label-free quantitative proteomic approach was performed to identify secretory proteins that may regulate tumor cell functions and propel cells into cancer metastasis. In our previous studies, the HFC system platform was established for cell secretome identification.21−23 The HFC system supplies a high cell culture density and a circulating environment. The pores on the fiber’s membrane facilitate nutrition and waste exchange. This system provides the cells with an environment similar to in vivo and requires less serum, thereby rendering the cells more adaptable to a serum-free medium for long-tern culture.61,62 Additionally, proteins secreted from cells are trapped in a small volume of extra-capillary space, which then

The findings produced by the Western blot analysis and the mass spectrometry data indicated matching trends of protein expression. A greater focus was placed on proteins not formerly known to be involved in lung adenocarcinoma metastasis or that may have only been studied within a few other types of cancer metastases. Up-regulated proteins within highly invasive cell lines were also of particular interest because such proteins: represent drug targets for inhibiting metastasis, may be potential serum marker candidates for predicting lung adenocarcinoma metastasis, and allow for a deeper understanding of the overall mechanisms of metastasis. PARK7 was an ideal protein target based on these criteria and was examined for its functions, as they are involved in cancer metastasis. PARK7 Significantly Influences Cell Proliferation and Migration/Invasion in Lung Adenocarcinoma

To increase the confidence of examined functions in lung adenocarcinoma cells, two represented cell lines with highly metastatic ability were used, the CL1-5 and A549 cell lines.48,49 With the reduced synthesis and secretion of PARK7 in CL1-5 and A549 (Figure 5A), cell proliferation was significantly influenced between 48 and 72 h, as shown in the MTT assay (Figure 5B). Additionally, the migration and invasiveness of the two cell lines were impeded using transwell chamber migration and a matrigel invasion assay during the 6 h of incubation (Figure 5C,D). In the CL1-0 cells, whose metastatic ability is low, we saw a decrease in cell proliferation, migration and invasiveness when PARK7 expression level was reduced (Figure 5B−D). Conversely, the proliferation (Figure 5B), migration (Figure 5C), and invasiveness (Figure 5D) were enhanced when PARK7 was overexpressed in CL1-0 cell extract and CM samples (Figure 5A). 5177



Article

metastasis.63−66 However, the actual mechanism still remains to be uncovered. According to Metacore software analyses, the molecular functions among the 703 identified proteins are related to protein binding, catalytic activity, and hydrolase activity (Supporting Information Figure 1C). Some extracellular and membrane proteins transmit signals from cell-to-cell or even act as receptors. The primary function of such proteins is to bind to signaling molecules and induce biochemical responses within cells, such as CTGF. When cancer cells metastasize and invade a new organ, the cells must first produce hydrolytic enzymes, such as SERPINA1 and CST3, before they are able to activate/ deactivate the catalytic activities of proteins. This production of hydrolytic enzymes must take place to facilitate the breakdown of proteins within the extracellular matrix.67 However, these activities allow tumor cells to pass into the blood and lymphatic vessels. Therefore, catalytic and hydrolase activities play a critical role in cancer metastasis. In the biological processes analysis, the two main processes are cellular component organization and cellular metabolic processes (Supporting Information Figure 1B). Cellular component organization is comprised of the assembly, arrangement of constituent parts, or disassembly of a cellular component. This process is related to the regulation of cell migration and invasion. For instance, structural reorganization

concentrates the protein amount and further simplifies the sample preparation processes. Wu et al. demonstrated that the cell lysis rate in CM samples of equal amount was lower in the HFC system than in the culture dish/flask.21 In our study, the cell lysis rates in both cells lines were less than 0.0038% (Figure 3C). Thus, the HFC system was used not only for secretome identification, but also in conjunction with quantitative proteomics, and used to identify proteins that might regulate cancer metastasis. A total of 703 proteins with at least two unique peptide sequences and two quantified peptides were characterized between the CL1-0 and CL1-5 cells. Among these proteins, 90.8 (638/703) of the proteins provided evidence of being secreted, which was based on the prediction software and databases concerning cellular localizations, exosomes, and the human plasma proteome. Moreover, 62.2% of the proteins presented at least 2 pieces of evidence that indicated a probability for their secretion through various pathways. However, there is still the possibility that a minor portion of the proteins is released into the CM sample by cell lysis or unknown pathways. Interestingly, proteins found in the exosome database that exist in CL1-5 cells (40.8%) were more than those in CL1-0 cells (31.3%) (Supporting Information Figure 1A). This finding suggests that higher exosome activity may facilitate cancer cell

Figure 5. continued 5178



Article

Figure 5. PARK7’s effect on cell proliferation, migration, and invasiveness within lung adenocarcinoma cells. (A) Western blot analysis showed that the expression of PARK7 was reduced using siRNA in the cell extract and CM of the CL1-0, CL1-5, and A549 cell lines. In addition, the Western blot showed the overexpression of PARK7 cell extract and CM in CL1-0 cells. (B) Cell proliferation was influenced when the PARK7 levels of CL1-0, CL1-5, and A549 cell lines were knocked down and overexpressed. (C) Transwell migration assay at 100× magnification. Migration was quantified by counting cells in six random fields per membrane. (D) Matrigel invasion assay at 200× magnification. Invasion was quantified by counting cells in six random fields per membrane. Columns represent the average number of cells per field of at least eighteen fields from three independent experiments. (C) and (D) provide evidence that the migration and invasiveness of CL1-0, CL1-5, and A549 cells were reduced at 6 h after siRNA treatment was completed. Conversely, the migration and invasiveness of CL1-0 cells were promoted when PARK7 was overexpressed. 5179



Article

Figure 6. Clinical expression of PARK7. (A) The gray levels of PARK7 between adjacent normal and cancerous tissues with overall TNM stage I, II, and III. (B) ROC curve analysis of the separate efficacy of PARK7 between TNM stage I and II in tissue specimen. (C) The Kaplan−Meier illustrates the association between 3-year survival rates and plasma levels of PARK7. (D) The Kaplan−Meier illustrates the association between 3-year progressionfree survival rates and plasma levels of PARK7. P-values were calculated using the log-rank test for equality of strata.

were identified, and, among these, 32.6 (115/353) of the proteins were again identified here. The dissimilar protein profiles of the two protein lists may be accounted for in the cell culture method for CM sample collection and differing quantitative proteomics methodologies. The HFC system can provide a 3D space and a circulating environment for cell growth. It has been proven that a 3D environment would trigger different signaling pathways when compared to a 2D environment.76,77 In addition, cell lysis rates are higher in dishes than in the HFB system for the CM samples, which is as described.21 Nevertheless, the HFC system might cause randomized protein loss due to proteins sticking to the membrane of the hollow fibers.78 Even beyond this loss of protein, different mass spectrometry and quantification methods may result in different protein identifications. Patel et al. compared the iTraq and label-free quantitative approaches. Their results showed that protein components in the same sample identified via two different methodologies are not identical and that the label-free method provides superior information for identification results, including higher confidence numbers for identified proteins (at least two identified peptides corresponding to a protein) and protein coverage. Further, the label-free method has advantages in terms of fewer requirements for the sample, preparation/instrument times and a relatively lower cost.79

of the cytoskeleton is a critical function in the regulation or deregulation of cell migration, invasion, and survival.68,69 Cellular metabolic processes also play key roles during cancer metastasis. In previous studies, cancerous cells have exhibited higher cellular metabolism than normal cells due to the fact that more energy is required for the increase of proliferation, migration, invasion, etc.70−72 Cancer cells avidly consume especially large amounts of glucose and produce lactic acid under aerobic conditions.73 Furthermore, cancerous cells with more metastatic activity show enhanced mitochondrial respiratory pathways for energy production such as glycolysis and the TCA cycle.74,75 In Figure 3A, the date showed the same lemma as previous investigations in which cells with high invasiveness consumed more glucose and produced more lactate than cells with low invasiveness. In previous research (Supporting Information Table 1), 7 publications have discussed lung cancer secretome (conditioned media from culture dishes). Among these, the main goal has been biomarker discovery. This study is the first to use a threedimensional (3D) culture system to collect cell secretomes of different invasiveness and further use label-free quantitative proteomics technology to discover the metastatic regulators. In our previous lung adenocarcinoma cell secretome (the CL1-0 and CL1-5 cell lines) research, a simple gel-aided method was established to effectively purify CM samples from culture dishes along with iTRAQ quantitative technology.25 Proteins (353) 5180



Article

Figure 7. The association of PARK7, HSPA5, and PRDX4, which were revealed via the STRING protein−protein interaction database. PARK7 and PRDX4 act as HSPA5’s downstream molecules. (A) When the knock-down of PARK7 expression levels in CL1-5 and A549 cells occurred, there was no influence on HSPA5 and PRDX4 expression levels. (B) The PARK7 and PRDX4 expression levels were reduced when HSPA5 was knocked-down. (C) The potential pathway of PARK7 to mediate proliferation and migration/invasion through HSPA5 or HSPA5/PRDX4. (Protein levels were normalized to Tubulin.)

Parkinson’s disease.80 A previous study has even shown that PARK7 protects against neuronal apoptosis.81 The plasma levels of PARK7 are higher in Parkinson’s disease patients than healthy controls.82 There are several studies that describe the mechanisms or functions of PARK7 because they regulate cancer progression. Most studies discuss its ability to promote cell survival. For example, it may also be involved in leukemogenesis by regulating cell growth, proliferation, and apoptosis.83 PARK7 acts as an oncogene that drives Akt-mediated cell survival. The protein appears to protect cells against hypoxia-induced cell death and is required for adaptation to severe hypoxic stress. It has also proven to be an upstream activator of HIF1 function in cancer cells and resistance to hypoxic stress through its regulatory effects on mTOR and AMPK.84 In glioblastomas, PARK7 demonstrates a positive correlation with p53 expression and a negative correlation with epidermal growth factor receptor amplification.85 It controls cell survival and possibly tumor progression via interaction with Cezanne, which is a known deubiquitination enzyme that inhibits NF-κB activity.86 In pancreatic ductal adenocarcinoma, PARK7 regulates invasion and metastasis properties through the ERK/uPA cascade.87 In ovarian carcinoma, PARK7

The label-free quantitative strategy was performed to discover proteins with different expression levels between the CL1-0 and CL1-5 cells, which would be considered for their influence on the regulation of cancer metastasis. To eliminate false positive results when identifying differentially expressed proteins, the multiple hypotheses test, t test and Benjamini and Hochberg, was used to identify the proteins with different expression levels between the two cell lines. A total of 50 proteins were determined to fit this criterion and exhibited high confidences of secretion (Table 1). Of these 50 proteins, some are already known to have key roles in cancer and/or lung adenocarcinoma metastasis. The related literature is listed in Supporting Information Table 7 Among these proteins, PARK7 was a main focus because of its functional involvement in cancer progression and the lack of research involving PARK7 and lung adenocarcinoma. To briefly introduce Parkinson disease protein 7 (PARK7), it is known as Protein DJ-1 (DJ-1), and it belongs to the peptidase C56 family of proteins. It is a positive regulator of androgen receptor-dependent transcription and may function as a redoxsensitive chaperone, a sensor for oxidative stress, and protects neurons against oxidative stress and cell death. Defects in the protein’s gene lead to autosomal recessive early onset 5181



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other various types of cancer are so fatal. The mechanisms which mediate cancer metastasis are still unclear and a general lack of useful treatments and diagnosis tools still exists. In this complex process, secretome play vital roles as the regulators of cancer promotion and suppression. Therefore, the HFC system along with the label-free quantitative approach was utilized to discern the precise secretory proteins that regulate cancer metastasis. In previous work, the HFC system platform was established to effectively collect cell secretome samples following tandem mass spectrometry analyses for protein identification. However, this is the first time it will be used for protein identification and also supply quantitative information that will allow for the better understanding of molecule mechanisms involved in lung adenocarcinoma metastasis. Additionally, PARK7 was identified as a regulator that mediates cell proliferation, migration, and invasion. This research will also be the first time PARK7 is to be investigated for its functions as they are involved in cancer metastasis. In clinical expression, PARK7 exhibited significantly higher expression levels in cancer when compared to normal groups in tissue and plasma samples. The HFC system applied in conjunction with label-free quantitative proteomics is a viable strategy that focuses on molecule mechanisms of cancer and the secreted proteins that influence cancer metastasis.

is a negative regulator of PTEN, which is the tumor suppressor gene that promotes cancer progression.88 However, the roles of PARK7 in lung adenocarcinoma progression are unclear, and this study represents the first time PARK7 has been identified as a promoter. Our results show that when the expression levels of PARK7 were knocked-down in CL1-0, CL1-5, and A549 cell lines, this would significantly impede cell proliferation, migration, and invasion (Figure 5B−D). Likewise, the functions could be promoted when PARK7 levels were overexpressed in CL1-0 cells. In cancer research, PARK7 was found to have high levels in cancerous tissues, including lung cancer and esophageal squamous cell carcinoma, when compared to normal tissues.89−91 Our tissue microarray data also indicates that PARK7 expression levels were apparently higher in cancerous tissues. Additionally, PARK7 expression levels have a direct correlation with N stage and overall TNM stage. The different levels of PARK7 between stage I and II may indicate the spread within lymph nodes. However, the results still need to be further confirmed. In plasma samples, the ELISA results showed that the expression levels of PARK7 were significantly higher in patients than in healthy controls. Interestingly, the plasma levels had a similar trend among the expression levels in tissue specimens. The levels of PARK7 were increased during the early stage (TNM stage I and II) then decreased during the late stage (TNM stage III and IV). These results may provide hints as to PARK7’s function during a specific point in the cancer progression. This may also be applied to drug development. For instance, to reduce PARK7 during stage I may suppress cancer progress before the next stage. Indeed, the mechanisms of PARK7 still need to be further studied, but this concept provides a hopeful direction. Additionally, patients with low PARK7 levels (below first quartile) showed poor 3-years survival and progression-free rates (Figure 6C,D). The results may give way to PARK7 as a prognostic marker for lung adenocarcinoma patients. However, the sample size needs to be extended to fully understand the feasibility these prognostic markers of the future. The STRING protein−protein interaction database verifies PARK7’s association with PRDX4 and HSPA5 (Supporting Information Figure 2), which both have high levels in CL1-5 cells. From a previous study, these three proteins are known to have roles in preventing cell death.92,93 On the basis of this research, we examined the possibility that these three proteins may be involved in the same pathway. Surprisingly, PARK7 and PRDX4 act as downstream molecules for HSPA5. When HSPA5 was knocked-down in CL1-5 and A549 cells, the PARK7 and PRDX4 were thereby decreased (Figure 7B). In previous studies, HSPA5 was known as a promoter in metastasis. HSPA5 can support tumor cell proliferation, migration, and angiogenesis.94,95 PARK7 might influence these functions through HSPA5 regulation. Another possibility may be that HSPA5 regulates PRDX4, which in turn regulates PARK7 (Figure 7C). This study represents the first time secretome data has revealed their novel pathway within lung adenocarcinoma metastasis. The discovery is certainly worth pursuing for further investigation and findings. Pairing the HFC system with label-free quantitative proteomics is an advantageous strategy for the discovery of secretory proteins that influence lung adenocarcinoma in cancer progression.

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ASSOCIATED CONTENT

* Supporting Information S

Supporting Information Available: This material is available free of charge via the Internet at http://pubs.acs.org. Supplementary Figure 1 The profiles of 412 CL1−0 identified proteins, 531 CL1−5 identified proteins, and 703 quantified protein in both cell lines of secretion evidence, GO processes, and molecular functions. Supplementary Figure 2 Selection of protein candidates involved in possible mechanisms via interactome analysis. Supplementary Figure 3 Tissue array pictures of patient samples. Supplementary Figure 4 PARK7 and PRDX4 act as HSPA5′s downstream molecules. Supplementary Table 1 The review reference list of cancer cell secretome Supplementary Table 2 List of used antibodies Supplementary Table 3 The clinicopathological characteristics of 64 patients in tissue microarray Supplementary Table 4 The clinicopathological characteristics of plasma samples from 90 patients and 35 healthy controls Supplementary Table 5 List 703 quantified proteins Supplementary Table 6 Quantified peptide information Supplementary Table 7 Paper review of different expression proteins between CL1−0 and CL1−5

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AUTHOR INFORMATION

Corresponding Author

*Address: Department of Environmental and Occupational Health, National Cheng Kung University College of Medicine, 138 Sheng-Li Road, Tainan 70428, Taiwan. Tel: 886-6-2353535, ext 5566. Fax: 886-6-2743748. E-mail: [email protected].

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CONCLUSION The uncontrollable nature of cancer and its progression to metastasis is the main reason why lung adenocarcinoma and

Notes

The authors declare no competing financial interest. 5182



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ACKNOWLEDGMENTS This work was supported by the Ministry of Education, Taiwan, R.O.C. under the NCKU Project of Promoting Academic Excellence & Developing World Class Research Centers. This study was supported by Grant NSC99-2923-M-006-001-MY3, NSC101-2325-B-006-003, and Grant NSC100-2113-M-006002-MY3 from the National Science Council. The authors thank the Proteomics Research Center, National Yang-Ming University, Taipei, Taiwan for assistance in mass spectrometry analysis for protein identification and the National Cheng-Kung University Proteomics Research Core Laboratory for assistance in mass spectrometry analyses. Mr. Corbett Hart Moy from Graduate Institute of Teaching Chinese as a Second Language (at the National Taiwan Normal University) for help in English editing. Computational analyses and data mining were performed using the system provided by the Bioinformatics Core at the National Cheng Kung University, supported by the National Science Council, Taiwan. We are grateful for the support from the Tissue Bank, Research Center of Clinical Medicine, National Cheng Kung University Hospital and Dr. Kuen-Jer Tsai and Ya-Chun Hsiao for the services of image acquiring and analyzing from the FACS-like Tissue Cytometry in the Center of Clinical Medicine, National Cheng Kung University Hospital.

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