Abstract

Ginsenoside F₂ (F₂), a protopanaxdiol type of saponin, was reported to inhibit human gastric cancer cells SGC7901. To better understand the molecular mechanisms of F₂, an iTRAQ-based proteomics approach was applied to define protein expression profiles in SGC7901 cells in response to lower dose (20 μM) and shorter duration (12 hour) of F₂ treatment, compared with previous study. 205 proteins were screened in terms of the change in their expression level which met our predefined criteria. Further bioinformatics and experiments demonstrated that F₂ treatment downregulated PRR5 and RPS15 and upregulated RPL26, which are implicated in ribosomal protein-p53 signaling pathway. F₂ also inhibited CISD2, Bcl-xl, and NLRX1, which are associated with autophagic pathway. Furthermore, it was demonstrated that F₂ treatment increased Atg5, Atg7, Atg10, and PUMA, the critical downstream effectors of ribosomal protein-p53 signaling pathway, and Beclin-1, UVRAG, and AMBRA-1, the important molecules in Bcl-xl/Beclin-1 pathway. The 6 differentially abundant proteins, PRR5, CISD2, Bcl-xl, NLRX1, RPS15, and RPL26, were confirmed by western blot. Taken together, ribosomal protein-p53 signaling pathway and Bcl-xl/Beclin-1 pathway might be the most significantly regulated biological process by F₂ treatment in SGC7901 cells, which provided valuable insights into the deep understanding of the molecular mechanisms of F₂ for gastric cancer treatment.

1. Introduction

Gastric cancer is the fifth most common cancer and the third leading cause of cancer-related death worldwide. Annually it results in approximately 700,000 deaths [1]. Currently, chemotherapy has proved to decrease the rate of recurrence and improve overall survival; however, the drug resistance and serious toxic side effects largely reduce therapeutic efficacy and quality of life in patients [2, 3]. In recent years, compounds of natural products have caught wide attention due to their promising anticancer effects and minimal side effects [4–7]. Therefore, it is very necessary to develop new optimal anticancer agent from natural resource [3].

Ginsenosides, the major bioactive constituents in ginseng, have been demonstrated to exert potential anticancer ability [4, 5]. Exploration of ginsenoside as a new anticarcinogenic agent is of much interest [4–7]. Structural-function studies showed that the increased antitumor effect is implicated with the decrease of its sugar number [5]. Sugar moiety at C-6 significantly reduces the anticancer activities of ginsenosides. Ginsenoside F₂ (see structure in Figure 1), a protopanaxdiol type ginsenoside with one sugar molecular at C-3 and one sugar molecule at C-20, has been shown to be potent in inhibiting tumorigenesis in several different cancers including gastric tumor and glioblastoma multiforme [6, 7]. Recently, our in vitro and in vivo studies demonstrated that ginsenoside F₂ possesses anticancer effects in human gastric carcinoma cells SGC7901 [6]. However, the involved exact mechanisms of ginsenoside F₂ on SGC7901 cancer cells at proteome level have not been systemically investigated.

Figure 1 

Structure of ginsenoside F₂.

Advancements in the field of proteomics have made it possible to accurately monitor and quantitatively detect the changes of protein expression in response to drug treatment. The achieved data provide valuable insights into the molecular mechanisms of disease and help to identify therapeutic targets [8]. Isobaric tag for relative and absolute quantification (iTRAQ) is a robust mass spectrometry technique that allows quantitative comparison of protein abundance by measuring peak intensities of reporter ions released from iTRAQ-tagged peptides by fragmentation. iTRAQ with multiplexing capability up to eight distinct samples in a single experiment and relatively higher sensitivity has gained significant interest in the field of quantitative proteomics. In the present study, SGC7901 cells treated by lower dose and a shorter duration than that in previous report were analyzed by iTRAQ-based proteomics integrated with bioinformatics using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Cluster of Orthologous Groups (COG) of proteins database. And network analysis was applied to identify critical molecules which are involved in anticancer mechanisms of ginsenoside F₂ in gastric SGC7901 cells. General molecular biological techniques such as western blot were utilized for validation.

2. Materials and Methods

2.1. Reagents and Antibodies

Ginsenoside F₂ was isolated previously from leaves of Panax ginseng by a series of chromatographic procedures [9]. Ginsenoside F₂ has a molecular mass of 784 Da and was isolated with 98% purity. Primary antibodies of PRR5, CISD2, Bcl-2L, NLRX1, RPS15, RPL26, p53, PUMA, Beclin-1, UVRAG, AMBRA-1, mTOR, LC3-II, LC3-I, and β-actin together with all secondary antibodies were purchased from Cell Signaling Technology (Danvers, MA, USA). The Atg5, Atg7, and Atg10 antibodies were obtained from Santa Cruz Biotechnology (Santa Cruz, CA, USA).

2.2. Cell Culture and Treatment

SGC7901 cells were purchased from American Type Culture Collection and maintained in Dulbecco’s modified Eagle’s medium (Hyclone) supplemented with 10% fetal bovine serum (FBS), 100 μg/mL streptomycin, and 100 μg/mL penicillin and grown at 37°C in 5% carbon dioxide.

2.3. Protein Preparation

In one of our recent reports [6], we have shown that the IC₅₀ of ginsenoside F₂ is in <50 μM in 24 hours. In order to characterize ginsenoside F₂-related mechanism it is imperative to use samples that are at the early stages of ginsenoside F₂ treatment. So, a lower dose than the IC₅₀ (20 μM) and a shorter duration (12 hours in the study) were chosen in the study. The treated (20 μM) and untreated SGC7901 cells were suspended in the lysis buffer and sonicated in ice. The proteins were reduced with 10 μM DTT (final concentration) at 56°C for 1 h and then alkylated by 55 mM iodoacetamide (IAM) (final concentration) in the darkroom for 1 h. The reduced and alkylated protein mixtures were precipitated by adding 4x volume of chilled acetone at −20°C overnight. After centrifugation at 4°C, 30 000 ×g, the pellet was dissolved in 0.5 M triethylammonium bicarbonate (TEAB) (Applied Biosystems, Milan, Italy) and sonicated in ice. After centrifuging at 30000 ×g at 4°C, the supernatants were collected, and the total protein concentration was determined using a Bradford protein assay kit (BioRad, Hercules, CA, USA). The proteins in the supernatant were kept at −80°C for further analysis.

2.4. iTRAQ Labeling and SCX Fractionation

Total protein (100 μg) was taken out of each sample solution and then the protein was digested with Trypsin Gold (Promega, Madison, WI, USA) with the ratio of protein : trypsin = 30 : 1 at 37°C for 16 hours. iTRAQ labeling was performed according to the iTRAQ Reagents-8plex labeling manual (AB SCIEX, Madrid, Spain). Briefly, one unit of iTRAQ reagent was thawed and reconstituted in 24 μL isopropanol. iTRAQ labels 113 were used to label control sample separately, and 115 and 117 were used to label twice F₂-treated samples for duplicated experiment. The peptides were labeled with the isobaric tags, incubated at room temperature for 2 h. The labeled peptide mixtures were then pooled and dried by vacuum centrifugation.

The mixed peptides were fractionated by strong cation exchange (SCX) chromatography on a LC-20AB HPLC Pump system (Shimadzu, Kyoto, Japan). The iTRAQ labeled peptide mixtures were reconstituted with 4 mL buffer A (25 mM NaH₂PO₄ in 25% acetonitrile, pH 2.7) and loaded onto a 4.6 × 250 mm Ul tremex SCX column containing 5 μm particles (Phenomenex). The peptides were eluted at a flow rate of 1 mL/min with a gradient of buffer A for 10 min, 5–60% buffer B (25 mM NaH₂PO₄, 1 M KCl in 25% acetonitrile, pH 2.7) for 27 min, and 60–100% buffer B for 1 min. The system was then maintained at 100% buffer B for 1 min before equilibrating with buffer A for 10 min prior to the next injection. Elution was monitored by measuring the absorbance at 214 nm, and fractions were collected at 1-minute intervals. The eluted peptides were pooled into 20 fractions, desalted with a Strata X C18 column (Phenomenex), and vacuum-dried. The cleaned fractions were then lyophilized again and stored at −20°C until analyzed by mass spectrometry.

2.5. LC-ESI-MS/MS Analysis Based on Q EXACTIVE

Each fraction was resuspended in buffer A (2% acetonitrile, 0.1% FA) and centrifuged at 20 000 ×g for 10 min. In each fraction, the final concentration of peptide was about 0.5 μg/μL. 10 μL supernatant was loaded on a LC-20AD nano-HPLC (Shimadzu, Kyoto, Japan) by the autosampler onto a 2 cm C18 trap column. Then, the peptides were eluted onto a 10 cm analytical C18 column (inner diameter 75 μm) packed in-house. The samples were loaded at 8 μL/min for 4 min; then the 44 min gradient was run at 300 nL/min starting from 2 to 35% B (98% acetonitrile, 0.1% FA), followed by 2-minute linear gradient to 80%, maintenance at 80% B for 4 min. Initial chromatographic conditions were restored in 1 min.

Data acquisition was performed with tandem mass spectrometry (MS/MS) in a Q EXACTIVE (Thermo Fisher Scientific, San Jose, CA) coupled online to the HPLC. Intact peptides were detected in the Orbitrap at a resolution of 70 000. Peptides were selected for MS/MS using high-energy collision dissociation (HCD) operating mode with a normalized collision energy setting of 27.0; ion fragments were detected in the Orbitrap at a resolution of 17500. In the octopole collision cell, the ten most intense peptide ions (charge states 2) were sequentially isolated to a maximum target value of 5 × 10⁵ by pAGC and fragmented HCD. A data-dependent procedure that alternated between one MS scan and 15 MS/MS scans was applied for the 15 most abundant precursor ions above a threshold ion count of 20000 in the MS survey scan with a following Dynamic Exclusion duration of 15 s. The electrospray voltage applied was 1.6 kV. Automatic gain control (AGC) was used to optimize the spectra generated by the Orbitrap. A sweeping collision energy setting of  eV was applied to all precursor ions for collision-induced dissociation. The AGC target for full MS was 3e⁶ and 1e⁵ for MS². For MS scans, the m/z scan range was 350 to 2000 Da. For MS² scans, the m/z scan range was 100–1800 Da. The iTRAQ experiments were performed as three technical replicates to gather reliable quantitative information.

2.6. Data Analysis

Raw data files acquired from the Orbitrap were converted into MGF files using Proteome Discoverer 1.2 (PD 1.2, Thermo) [5600 msconverter] and the MGF files were searched. Protein identifications were performed by using Mascot search engine (Matrix Science, London, UK; version 2.3.02) against database containing 143397 sequences.

For protein identification and quantification, a peptide mass tolerance of 20 ppm was allowed for intact peptide masses and 0.05 Da for fragmented ions, with allowance for one missed cleavage in the trypsin digests. Carbamidomethylation of cysteine was considered a fixed modification, and the conversion of N-terminal glutamine to pyroglutamic acid and methionine oxidation were considered variable modifications. All identified peptides had an ion score above the Mascot peptide identity threshold, and a protein was considered identified if at least one such unique peptide match was apparent for the protein. To reduce the probability of false peptide identification, only peptides at the 95% confidence interval by a Mascot probability analysis greater than “identity” were counted as identified. The quantitative protein ratios were weighted and normalized by the median ratio in Mascot. We set a 1.2-fold change as the threshold and a value must be below 0.05 to identify significant changes.

2.7. Function Method Description

Functional annotations of the proteins were conducted using Blast2 GO program against the nonredundant protein database (NR; NCBI). The KEGG database (http://www.genome.jp/kegg/) and the COG database (http://www.ncbi.nlm.nih.gov/COG/) were used to classify and group these identified proteins.

GO is an international standardization of gene function classification system. It provides a set of dynamic updating controlled vocabulary to describe genes and gene products attributes in the organism. GO has 3 ontologies which can describe molecular function, cellular component, and biological process, respectively.

COG is the database for protein orthologous classification. Every protein in COG is supposed to derive from a same protein ancestor.

KEGG PATHWAY is a collection of manually drawn pathway maps representing our knowledge on the molecular interaction and reaction networks. Molecules are represented as nodes, and the biological relationship between two nodes is represented as an edge (line).

2.8. Western Blot

Western blot analyses were performed to confirm the presence of differentially expressed proteins. After the treatment of the indicated concentration of ginsenoside F₂ (10, 20, and 40 μM) for 12 h, cells were harvested, washed with cold PBS (pH 7.4), and lysed with ice-cold lysis buffer (50 μM Tris-HCl, 150 μM NaCl, 1 μM EGTA, 1 μM EDTA, 20 μM NaF, 100 μM Na₃VO₄, 1%NP40, 1 μM PMSF, 10 μg/mL aprotinin, and 10 μg/mL leupeptin, pH 7.4) for 30 min and centrifuged at 12 000 ×g for 30 min at 4°C. The protein concentration of the clear supernatant was quantified using Bio-Rad Protein Assay Kit.

Approximately 30 μg of protein was loaded into a 10–15% sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS–PAGE). Thereafter, proteins were electrophoretically transferred to nitrocellulose membrane and nonspecific sites were blocked with 5% skimmed milk in 1% Tween-20 (Sigma-Aldrich) in 20 μM TBS (pH 7.5) and reacted with a primary polyclonal antibody, PRR5, CISD2, Bcl-2L, NLRX1, RPS15, RPL26, p53, Atg5, Atg7, Atg10, LC3-II, LC3-I PUMA, Beclin-1, UVRAG, and mTOR and β-actin for 4 h at room temperature. After washing with TBS three times (5 min each), the membrane was then incubated with alkaline phosphatase-conjugated goat anti-rabbit secondary antibody. The signal was observed and developed with Kodak film by exposure to enhanced chemiluminescence (ECL) plus western Blotting Detection Reagents (Amersham Biosciences, Piscataway, NJ, USA).

2.9. Statistical Analysis

For cell-based assay, experiments were performed in duplicate and three independent experiments were performed. Western blot analyses of differential protein expressions were validated on cell lysates from three biological replicates. Statistical significance was analyzed using Student’s t-test or ANOVA test by using GraphPad Prism v4.0 software (GraphPad Software, San Diego, CA, USA). Statistical significance is expressed as ; ; .

3. Results

3.1. Proteome Analysis

Human gastric carcinoma cells (SGC7901) are treated with ginsenoside F₂ at a dose of 20 μM for 12 hours. The harvested proteins are used to perform iTRAQ for quantifying the difference of total 31853 peptides and 5411 proteins in SGC7901 cells with or without treatment. Finally, 205 proteins were screened out in terms of the change in their expression level which meet our predefined criteria of with relative expression levels at least >1.2-fold (Table 1) or <0.83-fold (Table 2) (both 113/115 and 113/117) in ginsenoside F₂-treated group compared with the control group. The protein properties, including pI, molecular weight (MW), and number of residues were calculated by Mascot. The results are highly reproducible in two individual experiments.

3.2. Classification of Differentially Expressed Proteins

Firstly, screened proteins were functionally catalogued with GO and WEGO to three different groups (Figures 2 and 3(a)): biological process (BP), cellular component (CC), and molecular function (MF). As shown in Figure 2, the proteins are involved in BP including cellular process (13.44%), metabolic process (11.16%), single-organism process (10.36%), biological regulation (8.06%), and regulation of biological process (7.59%). The identified proteins separated according to CC include cell (19.40%), cell part (19.40%), organelle (16.68%), organelle part (12.46%), membrane (7.97%), and macromolecular complex (7.94%). MF of the proteins was classified and large groups were found to be binding (50.59%), catalytic activity (27.97%), enzyme regulator activity (3.94%), transporter activity (3.84%), and structural molecular activity (3.43%).

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Figure 2 

Classification of identified proteins. (a) The biological processes (BPs), (b) cellular components (CCs), and (c) molecular functions (MFs) of the total identified proteins classified by GO database.

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Figure 3 

WEGO (a) and COG (b) assay of the 205 differentially expressed proteins.

Further COG function classification revealed that posttranslational modification, protein turnover, and ribosomal structure biogenesis were major function of the screened 205 proteins (Figure 3(b)). In each category of BP, CC, and MF, top twenty proteins which generated bigger difference in response to ginsenoside F₂ treatment are listed in Figure 4.

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Figure 4 

GO annotation of the final selected differentially expressed proteins. The top 20 components for BP (a), CC (b), and MF (c) of the selected differentially expressed proteins are shown along with their enrichment score, represented as a value.

KEGG is a publicly available pathway database and could provide biologists excellent resources to attain a deeper understanding of biological mechanisms in response to different treatments. Protein analysis through KEGG indicated that 205 differentially expressed proteins were involved in 128 different pathways (data not shown). The connection degree between proteins is calculated by protein-protein interaction network analysis and the results are shown in Figure 5. Among these proteins, PRR5, RPS15, and RPL26 were found in ribosomal protein signaling pathway; CISD2, Bcl-xl, and NLRX1 were found in Beclin-1/Bcl-xL pathway. Therefore, PRR5, RPS15, RPL26, CISD2, Bcl-xl, and NLRX1 were selected for further validation and study in order to provide a comprehensive perspective for elucidating underlying molecular mechanisms of ginsenoside F₂.

Figure 5 

The protein-protein interaction network of the differentially expressed proteins identified. Red triangle denotes upregulated proteins; green triangle denotes downregulated protein.

3.3. Western Blot Analysis

3.3.1. For Verification

To validate the information obtained from the iTRAQ-based quantitative proteomics study and bioinformatics analysis, the screened proteins with strong response to ginsenoside F₂ treatment were further confirmed by western blot. As shown in Figure 6, ginsenoside F₂ significantly reduced protein expressions of PRR5, CISD2, Bcl-xl, NLRX1, and RPS15 () and enhanced the expression of the RPL26 () in SGC7901 cells in comparison with the treatment with vehicle control.

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Figure 6 

Western blot validations of RPS15, RPL26, PRR5, CISD2, NLRX1, p53, PUMA, mTOR, and Bcl-xl in SGC7901 cells with different concentrations of ginsenoside F₂. 1 × 10⁶ SGC7901 cells are seeded in 6-well plate for overnight. On day 2, the cultured cells are treated with different concentration ginsenoside F₂. 12 hours after treatment, the protein is prepared by lysating cells with RIPA buffer for performing western blot analysis. Left panel: the representative western blot analysis. β-actin was used as the loading control. Right panel: accumulated results show the relative protein density. Error bars represent means ± SEMs. Significant difference is expressed as , .

3.3.2. For Determining the Expression of Apoptosis and Autophagic Proteins

As shown in Figure 6, ginsenoside F₂ suppressed the expression of mTOR and upregulated the expression of p53 in a dose-dependent manner. Atg5, Atg7, Atg10, PUMA, Beclin-1, UVRAG, and AMBRA-1 are known to be modulated by p53 or Bcl-xl signaling, which may trigger apoptosis or autophagy. Therefore, we proceeded to check the expressions of Atg5, Atg7, Atg10, PUMA, Beclin-1, UVRAG, and AMBRA-1. As shown in Figure 7, ginsenoside F₂ upregulated the expressions of these proteins in a dose-dependent manner. LC3 is now widely used to monitor autophagy. During autophagy, the cytoplasmic form LC3-I is processed and recruited to phagophores, where LC3-II is generated by site-specific proteolysis and lipidation at the C-terminus. Thus, the amount of LC3-II positively correlates with the number of autophagosomes [10]. We examined the effect of F₂ on LC3 conversion in SGC7901 cells. Western blot analysis showed that F₂ treatment resulted in dose-dependent accumulation of LC3-II and reduction of LC3-I (Figure 7). The conversion of LC3-I to LC3-II suggested F₂ treatment induces autophagy.

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Figure 7 

Effect of ginsenoside F₂ on the expression of Beclin-1, UVRAG, AMBRA-1, Atg5, Atg7, Atg10, LC3 I, and LC3-II. 1 × 10⁶ SGC7901 cells are seeded in 6-well plate for overnight. On day 2, the cultured cells are treated with different concentration ginsenoside F₂. 12 hours after treatment, the protein is prepared by lysating cells with RIPA buffer for performing western blot analysis. Left panel: the representative western blot analysis. β-actin was used as the loading control. Right panel: accumulated results show the relative protein density. Error bars represent means ± SEMs. Significant difference is expressed as , .

In the present study, combination of iTRAQ-based proteomics method with bioinformatics was used to identify critical molecules in SGC7901 cancer cells in response to ginsenoside F₂ treatment. Ginsenoside F₂ generated significant change of protein profile in SGC7901 cells. Some of them have been demonstrated to participate in either apoptosis or autophagy responses, suggesting that the antitumor mechanisms of ginsenoside F₂ in SGC7901 cells are involved in both apoptosis and autophagy.

The current findings demonstrate that ginsenoside F₂ impacts distinct signaling pathways and induces broad change in the protein profile of SGC7901 cells. Overall, 205 differentially expressed proteins were identified with ≥95% confidence in ginsenoside F₂ treated group. Application of a ratio of 1.2-fold change as criteria resulted in 44 and 161 differentially abundant proteins in SGC7901 cells.

In our study, some proteins that were significantly altered by ginsenoside F₂ show close relationship of protein-protein interaction (Figure 5). Ribosomal proteins, such as RPS15 and RPL26, exert critical roles in MDM2-p53 signal pathway [11, 12]. PRR5 [13], CISD2 [14], Bcl-xl [15], and NLRX1 [16, 17] have been reported to play a key role in the regulation of autophagy or apoptosis. The changes of these six potential proteins were verified by western blot analysis.

Ribosomal proteins (RPs) are considered to have diverse extra ribosomal functions, ranging from cell cycle progression to cell death and to malignant transformation and cellular metabolism [11]. Relevantly, a number of RPs have been shown to bind to MDM2, the inhibitor of p53 (murine double minute 2, and also HDM2 for its human ortholog), and inhibit MDM2 E3 ligase activity, leading to p53 stabilization and activation, then triggering apoptosis or autophagy [11]. Following the treatment of ginsenoside F₂ in SGC7901 cells, the levels of RPL28, RPL34, RPL35, RPS16, RPL17, RPL14, RPL24, RPL7A, and RPL26 were increased, whereas that of RPS15 reduced. Although the functions of RPL28, RPL34, RPL35, RPS16, RPL17, RPL14, RPL24, and RPL7A have not been well studied, RPL26, a positive regulator of p53, was found to increase the translational rate of p53 mRNA by binding to its 50 untranslated region [12] and, in this case, MDM2 acts as an ubiquitin E3 ligase for ubiquitylation and degradation of RPL26 [18]. Thus, under the treatment of ginsenoside F₂, the increased level of RPL26 indicated that RPL26 may inhibit MDM2 and subsequently activate p53. RPS15, identified as a direct p53 transcriptional target, was thought to activate p53 by repressing MDM2 activity [19]. Interestingly, in our study, the level of RPS15 reduced in SGC7901 followed by ginsenoside F₂ treatment, suggesting that the roles of RPS15 and RPL26 involved in the anticancer mechanism of ginsenoside F₂ are different, which warrant further investigation.

mTOR, existing in two multiprotein complexes, mTORC1 and mTORC2, regulates cell growth in response to a variety of cellular signals derived from growth factors and environmental stress [20]. mTORC2 is a kinase complex comprised of mTOR, PRR5, Rictor, mSin1, and mLST8/GbL. The expression level of PRR5 is correlated with that of mTORC2. Recent study showed that mTORC2 is implicated in actin cytoskeleton regulation, as well as phosphorylation of Akt [13]. Although TOR kinase has been largely attributed as a negative regulator of autophagy through TORC1, resent study indicated that mTORC2 was an independent positive regulator of autophagy during amino acid starvation [21]. In the present study, ginsenoside F₂ decreased level of PPR5, indicated that ginsenoside F₂ may inhibit the expression of PRR5, and consequently inhibited mTORC2.

Recent study indicated that p53 can be a positive or negative regulator of autophagy. In the nucleus, p53 may activate the AMPK pathway and inhibit the mTOR pathway, subsequently triggering autophagy. p53 may also transactivate multiple genes with proautophagic roles, including proapoptotic Bcl-2 proteins (Bax, PUMA) [22, 23]. In this network, PUMA induces the noncanonical autophagy pathway regulated via Atg5, Atg7, and Atg10. PUMA’s initiation of autophagy promotes cytochrome c release, which then leads to apoptosis [22]. Interestingly, in our previous work, increasing level of cytochrome c and decreased mitochondrial transmembrane potential (MTP) were observed [6]. In present study, decreased expressions of PRR5 and RPL26 were found, which implied that ginsenoside F₂ might trigger p53 signal pathway. It was reported that western blot analyses tended to show greater differential abundance compared with iTRAQ analyses [24]. Thus, the expressions of p53, Atg5, Atg7, Atg10, and PUMA were validated by western blot analyses. The increased level of Atg5 Atg7, Atg10, and PUMA and reduced level of P53 and mTORC2 suggested that ginsenoside F₂ may initiate autophagy by ribosomal protein-p53 signaling pathway.

CISD2, also known as NAF-1, Miner1, Eris, and Noxp70, is a member of the 2Fe-2S cluster NEET family [25]. Our results showed that CISD2 was significantly decreased in ginsenoside F₂ treated group, confirmed by western blot analysis. Recent work identified CISD2 as a Bcl-xl binding partner at a branch point between autophagy and apoptosis, life and death, under nutrient-deprived and oxidative stress conditions in vivo cells [25, 26]. Bcl-xl, also called Bcl-2L, is known to function through inhibition of the autophagy effector and tumor suppressor Beclin-1 [15]. CISD2 is required in this pathway for Bcl-xl to functionally antagonize Beclin-1-dependent autophagy. In our study, the expression of Bcl-xl decreased, confirmed by western blot analysis. Thus, CISD2 may be a Bcl-xl-associated cofactor that targets Bcl-2 for the autophagy pathway.

During initiation of autophagosome formation, after release from Bcl-xl, Beclin-1 functions as a platform by binding to class III PI3K/vacuolar protein sorting-34 (Vps34), UV-resistance-associated gene (UVRAG), activating molecule in Beclin-1-regulated autophagy (AMBRA-1) [15, 26, 27]. Previous studies have shown that binding of Beclin-1 to Bcl-2/Bcl-xl inhibits the autophagic function of Beclin-1, suggesting that Beclin-1 might have a role in the convergence between autophagy and apoptotic cell death [22]. For confirming the Beclin-1/Bcl-xl pathway, western blot was employed. The expressions of Beclin-1, UVRAG, and AMBRA-1 were increased, while Bcl-xl was decreased, which suggested that ginsenoside F₂ may induce autophagy via Bcl-xl/Beclin-1 pathway.

NLRX1, a mitochondrial NOD-like receptor that amplifies apoptosis by inducing reactive oxygen species production, is an important component of TLR mediated inflammatory pathways [13, 16]. Recent evidence suggested that upregulated expression of NLRX1 may synergistically regulate metabolism and autophagy for highly invasive growth of the autophagy addicted MDA-MB-231 breast cancer cells [16]. And it acted as tumor suppressor by regulating TNF-α induced apoptosis and metabolism in cancer cells. In our iTRAQ results, expression of NLRX1 was significantly decreased in SGC7901 cells treated with ginsenoside F₂. The phenomenon suggested different role of NLRX1 involved in the ginsenoside F₂ treatment that may be different from that of published reports [16, 17], though the mechanism needs further research.

Mai et al. reported that F₂ induces apoptotic cell death accompanied by protective autophagy in breast cancer stem cells [28]. In one of our previous studies, we found that F₂ induces apoptosis by causing an accumulation of ROS and activating the apoptosis signaling pathway [6]. However, there was no report systemically comparing differently regulated proteins and building a network of F₂-treated cancer cells at proteome level. In the current study, by the close look at cellular mechanisms at proteome level, we clearly identified the distinct pattern of cellular responses for the F₂-treated cells, and 6 differentially regulated proteins were identified, which provide useful information on elucidating the anticancer mechanism of F₂ to SGC7901 cells. Moreover, the integration of networks and pathway with the proteomic data enhanced our understanding of the functional relationship of proteome changes caused by the compound.

4. Conclusions

In conclusion, 44 upregulated proteins and 161 downregulated proteins were discovered by iTRAQ analysis in SGC7901 cells treated with lower dose and shorter duration of ginsenoside F₂, compared with our previous study. 6 differentially abundant common proteins, PRR5, CISD2, Bcl-xl, NLRX1, RPS15, and RPL26, were confirmed by western blot analysis. Ribosomal protein-p53 signaling pathway and Bcl-xl/Beclin-1 pathway might be significantly regulated biological process by ginsenoside F₂ treatment in SGC7901 cells. Although more work is required to find out the precise role of targeted proteins, our data lead to a better understanding of the molecular mechanisms of ginsenoside F₂ for gastric cancer treatment.

Abbreviations

Competing Interests

The authors declare that there is no conflict of interests.

Acknowledgments

This work was supported by the Natural Science Foundation of China (nos. 81573596, 81503191, 81274018, 81373946, and 81303221) and National High Technology Research and Development Plan of China (863 Plan) (2014AA022204).