Proteomics analysis demonstrating rosmarinic acid suppresses cell growth by blocking the glycolytic pathway in human HepG2 cells

Biomedicine & Pharmacotherapy 105 (2018) 334–349

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Proteomics analysis demonstrating rosmarinic acid suppresses cell growth by blocking the glycolytic pathway in human HepG2 cells

T

Zhan-Jun Maa,1, Yan Hub,1, Ya-Jiao Wangc, Yang Yanga, Xiao-Bin Lib, An-Cheng Shia, ⁎ ⁎ Jing-Wen Xub, Yu-Bao Lua, Li Lub,d, , Xue-Xi Wangb,d, a

The Second Clinical School, Lanzhou University, Lanzhou, Gansu, 730000, China School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu, 730000, China c Clinical College of Hebei Medical University, Shijiazhuang, Hebei, 050031, China d Key Laboratory of Preclinical Study for New Drugs of Gansu Province, Lanzhou University, Lanzhou, 730000, China b

A R T I C LE I N FO

A B S T R A C T

Keywords: Rosmarinic acid Apoptosis HepG2 cells Proteomics Glycolytic pathway

Rosmarinic acid (RA), isolated from herbal balm mint plants, has demonstrated potent anti-tumor properties against liver cancer. However, the precise underlying mechanisms remain unclear. This study aimed to investigate the molecular mechanisms of RA in HepG2 cells. RA anti-tumor activity was assessed using 3-(4,5dimethylthiazol-2-yl)2,5-diphenyl-tetrazolium bromide (MTT) and lactate dehydrogenase (LDH) assays, and Hoechst 33258 staining. Apoptosis and the cell cycle distribution were evaluated by flow cytometry. A proteomics approach was used to identify differentially expressed proteins following RA treatment in HepG2 cells, and quantitative reverse transcription–quantitative polymerase chain reaction was used to validate the results. Bioinformatics analysis was also implemented to further understand the identified proteins, and western blotting was used to analyze the associated proteins. Our results suggested that RA treatment significantly inhibits the viability of HepG2 cells. The MTT and LDH assays indicated dose-dependent decreases in cell proliferation following RA treatment. Hoechst 33258 staining and flow cytometry analysis showed that RA exhibits an apoptosis-inducing effect and induces cell cycle arrest in G1. The proteomics analysis successfully identified 16 differentially expressed proteins. Bioinformatics analysis indicated that the identified proteins participated in several biological processes and exhibited various molecular functions, mainly related to inactivation of the glycolytic pathway. Further western blotting analysis showed that RA could downregulate the expression of glucose transporter-1 and hexokinase-2, leading to the suppression of glucose consumption and generation of lactate and ATP. Taken together, our study found that RA exhibits significant cytotoxic effects by inhibiting cell proliferation and inducing apoptosis and cell cycle arrest, possibly by blocking the glycolytic pathway in human HepG2 cells.

1. Introduction Hepatocellular carcinoma (HCC) is currently one of the most common potentially aggressive human malignant cancers and the third cause of tumor-related deaths worldwide, accounting for more than 800,000 mortalities every year [1]. At early stages, tumors can be curable by surgical therapy, liver transplantation, or ablation, and 5year survival rates greater than 50% can be attained [2]. At advanced stages, systemic chemotherapy is the primary treatment, although the existing chemotherapy regimens suffer from a number of issues, including poor therapeutic effect, drug resistance, and adverse reactions [3]. Thus, the search for novel efficient targeted agents or new

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therapeutic strategies are urgently necessary for the treatment of HCC. Thus, increasing attention has been focused on traditional Chinese medicine (TCM) to explore new cancer approaches that are promising and effective for patients with HCC [4]. TCMs from medicinal plants have been shown to be an excellent source of chemotherapeutic agents with various biological activities and great potential therapeutic value [5], and research in the field of TCM is in high demand to help humans overcome many diseases, particularly cancers [6,7]. TCM, which is comprised mainly of natural products, has attracted increasing public attention recently, and many researchers have explored novel therapeutic targets against HCC [8]. Rosmarinic acid (RA; Fig. 1) is a water-soluble polyphenol hydroxyl

Corresponding authors at: School of Basic Medical Sciences of Lanzhou University, School of Medicine, 205 Tianshui Rd South Lanzhou, Gansu, 730000, China. E-mail address: [email protected] (X.-X. Wang). These authors contributed equally to this study and share first authroship.

https://doi.org/10.1016/j.biopha.2018.05.129 Received 13 January 2018; Received in revised form 12 May 2018; Accepted 24 May 2018 0753-3322/ © 2018 Elsevier Masson SAS. All rights reserved.

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demonstrated numerous biological activities, including antioxidant, anti-inflammation, anti-virus, anti-mutagenic, and anti-cancer properties [10]. Some studies have shown that RA exhibits anti-tumor effects in vitro and can be applied for the treatment of colon cancer, breast cancer, prostate cancer, ovarian carcinoma, and gastric carcinoma [11,12]. In addition, treatment of liver cancer HepG2 cells with RA caused an increase in apoptosis and a decrease in Bcl-2 mRNA levels [13]. However, the specific mechanisms of action underlying the anticancer effects of RA in HepG2 cells remain elusive. TCM has been widely applied for thousands of years in China and other Asian countries to prevent, diagnose, and cure many diseases. However, TCM is a typical complex material system, comprising raw materials of various origins and leading to various chemical constituents in TCM. In addition, TCM diversity, in turn, leads to expression in multiple effector organs, with multiple roles and multiple targets; thus, studying their mechanisms of action is difficult [14]. The application of systems biology to the study of TCM has provided new ideas and methods for the study of complex systems and has become a focus in the study of the modernization of TCM [15]. Proteomics technology, an important component of systems biology, has gained considerable attention in studying the mechanism of action of TCM, identifying effective drug targets, and developing new drugs [16]. Proteomics approaches mainly consist of two-dimensional electrophoresis (2-DE), mass spectrometry, and bioinformatics [17]. In addition, genomics and proteomics are considered other effective tools to study biological systems [18]. It is also a powerful approach to identify the molecular targets of TCM and investigate the underlying mechanisms of diseases. In the present study, the cytotoxic effects of RA on HepG2 cells were examined using 3-(4,5-dimethylthiazol-2-yl)2,5-diphenyl-tetrazolium bromide (MTT) and lactate dehydrogenase (LDH) assays, Hoechst 33258 staining, and flow cytometry. Proteomics, bioinformatics, western blotting, and enzyme-linked immunosorbent assays were carried out to investigate and confirm the mechanism of action in HepG2 cells following RA treatment. The data in this study provide many theoretical bases to understand the molecular mechanisms of the cytotoxic effects of RA in HepG2 cells and will help to develop tools for the diagnosis and prognosis of cancers.

Fig. 1. Chemical structure of RA. Table 1 Primer sequences for qRT-PCR. GENE

Forward primer sequence

Reverse primer sequence

PHB DLST EEF1A1 LDHA

GCGTGGTGAACTCTGCTCTA CTGTCACACGGAAGCTAGCG CTCCACTTGGTCGTTTTGCTG GTCAGCAAGAGGGAGAAAGC

TGTACCCAGGGGATGAGGAA ATCCCCAGGATGGCAGACTGA GCAGACTTGGTGACTTTGCC TCCAAGCCACGTAGGTCAAG

2. Materials and methods 2.1. Reagents and chemicals RA was purchased from Sigma-Aldrich (St. Louis, MO, USA) and its purity was determined by high-performance liquid chromatography to be ≥ 98%. RA was split into 100 μg per tube and dissolved in 1 ml of culture medium before use, a condition that maintained the stability of RA. The structure of RA is shown in Fig. 1. RPMI-1640 medium, fetal bovine serum (FBS), and antibiotics were obtained from Hyclone (Thermo Fisher Scientific, Waltham, MA, USA). All reagents used in 2DE were obtained from Bio-Rad Laboratories (Milan, Italy), and the silver staining chemicals were purchased from CWBIO (Beijing, China). The annexin V-FITC/propidium iodide (PI), LDH release assay, and ATP assay kits were obtained from Beyotime Co. (Hangzhou, China). Glucose and lactate assay kits were obtained from Nanjing Jiancheng Bioengineering Institute (Nanjing, China). Antibodies against β-actin, glucose transporter-1 (Glut-1), and hexokinase-2 (HK-2) were obtained from Cell Signaling Technology (Danvers, MA, USA). Other chemical reagents, unless otherwise indicated, were obtained from Sigma-Aldrich.

Fig. 2. The cytotoxicity of RA on HepG2 cells. A. HepG2 cells were treated with different concentrations of RA for different time points (24, 48, and 72 h), and then cell viability was measured using the MTT assay. The results showed RA could inhibit HepG2 cells proliferation in a time- and dose-dependent manner with respect to control cells (*P < 0.05). B. Cytotoxicity was measured using the LDH release assay kit. LDH release was significantly increased compared to untreated cells (*P < 0.05, **P < 0.01). The data were represented by mean ± SD of three experiments, and each experiment was conducted in triplicate.

2.2. Cell culture and treatment HepG2 cells were purchased from the cell bank of the Chinese Academy of Sciences (Shanghai, China) and cultured in RPMI-1640 medium supplemented with 10% FBS and 1% antibiotics at 37 °C in 5% CO2 and 95% air for all cell culture experiments. When the cells

acid that exists in many Chinese traditional herb drugs, especially in labiatae, boraginaceae, and umbelliferae, with the structure of the ester of caffeic acid and 3-(3,4-dihydroxyphenyl) lactic acid [9]. RA has

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Fig. 3. The Hoechst 33,258 staining of HepG2 cells. Morphological change of HepG2 cells in response to various concentrations RA treatment for 48 h under a fluorescence microscope at magnification of 200 × (Scale bar = 50 μm). The arrows indicate several apoptotic cells with typical condensation of chromatin, cell shrinkage and nuclear fragmentation.

2.5. Hoechst 33258 staining

reached 80% confluence, they were harvested for subsequent experiments. The cells incubated in normal medium without RA were considered the control group.

HepG2 cells (1 × 105/well) were seeded in six-well plates and incubated overnight before exposure to different concentrations of RA (6.25, 12.5, 25, 50, and 100 μg/ml) for 48 h. After incubation, the cells were incubated in 100% methanol for 15 min at room temperature and washed twice with phosphate-buffered saline (PBS). The cell nucleus was stained with 5 μg/ml Hoechst 33258 for 20 min at room temperature in the dark and washed twice with PBS. To observe nuclear damage, dhanges in nuclear morphology, including the formation of apoptotic bodies or chromatin condensation and edge sets, were observed by fluorescence microscopy (Olympus, Japan).

2.3. Cell viability assays Cell number and viability were quantified using the MTT assay. HepG2 cells (5 × 103/well) were seeded in 96-well plates for 24 h at 37 °C. Next, fresh RPMI-1640 medium containing different concentrations of RA (6.25, 12.5, 25, 50, and 100 μg/ml) was added at 100 μl per well, and five replicate wells were used for each concentration. After incubation for 24, 48, and 72 h, the MTT solution (10 μl, 5 mg/ml) was added to each well and incubated for 4 h at 37 °C, followed by the addition of 150 μl of dimethyl sulfoxide to solubilize the formazan and gentle shaking for 10 min in the dark. The absorbance of the samples was measured at 570 nm using a microplate reader (Bio-Rad Laboratories, Hercules, CA, USA). The cytotoxicity of RA was assessed as the percent values compared with that of the untreated control group. The IC50 (concentration required to induce growth inhibition of 50% of the cells) value was determined by interpolation from doseresponse curves using Graphpad Prism 5. All data were obtained from three independent experiments.

2.6. Cell apoptosis assays Cell apoptosis levels were measured using an annexin V-FITC double-staining apoptosis detection kit according to the manufacturer’s instructions. HepG2 cells (1 × 106/well) were seeded in 25-cm2 culture dishes and incubated for 24 h at 37 °C. After 40–50% confluency was reached, the cells were exposed to different concentrations of RA (6.25, 12.5, 25, 50, and 100 μg/ml) for 48 h. The cells were obtained, resuspended in 195 μl of 1× binding buffer containing annexin V-FITC (5 μl) and PI (10 μl), and incubated in the dark for 15 min. Apoptotic cells were evaluated immediately by flow cytometry (BD FACSCanto; BD Biosciences, Piscataway, NJ, USA). For each sample, 10,000 events were collected. All the data were obtained from three independent experiments.

2.4. LDH release assay The cytotoxicity of RA in HepG2 cells was analyzed using the LDH release assay kit. HepG2 cells (1 × 104/well) were seeded in 96-well plates for 24 h at 37 °C. Next, fresh RPMI-1640 medium containing different concentrations of RA (6.25, 12.5, 25, 50, and 100 μg/ml) was added at 100 μl per well for 48 h. The level of LDH released into the cell culture supernatant was measured using the LDH assay kit according to the manufacturer’s instructions. The absorbance was immediately determined at 450 nm using a microplate reader (Bio-Rad Laboratories). The cell death rate was determined by the following equation: cell death rate = 100 × (experimental release − spontaneous release) / (maximum release − spontaneous release).

2.7. Cell cycle analysis Synchronization of HepG2 cells was performed by double thymidine block. Briefly, cells were treated with 2 mM thymidine in RPMI-1640 medium with 10% FBS for 16 h and washed twice with PBS and then cultured in fresh medium with 10% FBS for 9 h. The cells were treated again with RPMI-1640 medium with 10% FBS containing 2 mM thymidine for 16 h. After washing cells with PBS, the block was released by the incubation of cells in fresh medium with 10% FBS, and cells were 336

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Fig. 4. RA induces apoptosis in HepG2 cells. A. HepG2 cells were treated with different concentrations of RA for 48 h. Flow cytometric analysis of RA-induced apoptosis in HepG2 cells using Annexin V-FITC/PI staining. B. Data from three independent experiments are shown, and the percentage of apoptotic cells is presented as the mean ± SD. Significant differences from the control are indicated by *P < 0.05.

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Fig. 5. Cell cycle analysis of HepG2 cells after exposed with RA. Synchronization of HepG2 cells was performed by double thymidine block. Then, the cells were released in the absence (upper panel) or presence of 25 μg/ml RA (lower panel) for 24, 48, and 72 h. Data are representative of two independent experiments.

flow cytometry (BD FACSCanto; BD Biosciences).

Table 2 Effect of RA on cell cycle progression. Time

Group

G1(%)

24 h

control RA(25 μg/ml) control RA(25 μg/ml) control RA(25 μg/ml)

55.03 62.60 58.51 74.52 55.12 81.26

48 h 72 h

S(%) ± ± ± ± ± ±

2.08 1.09* 0.88 1.52* 2.13 1.36*

37.95 21.72 33.86 12.97 35.35 15.38

± ± ± ± ± ±

1.24 1.32 1.59 2.37 3.28 1.64

G2/M(%)

2.8. Protein extraction

7.02 ± 1.04 15.68 ± 2.52 7.63 ± 1.51 12.51 ± 1.88 9.53 ± 1.52 3.36 ± 0.59

HepG2 cells (1 × 106/well) were seeded in 25-cm2 culture dishes overnight and incubated in the absence or presence (30 μg/ml) of RA for 48 h. Next, the cells were rinsed with PBS and solubilized in 300 μl of lysis buffer [7 M urea, 2 M thiourea, 4% CHAPS, 40 mM Tris, 60 mM dithiothreitol (DTT), and 1% protease inhibitor cocktail]. The lysates were recovered following centrifugation at 15,000 × g at 4 °C for 30 min, and the supernatants were carefully obtained. Finally, protein concentration was determined using the Bradford assay prior to 2-DE analysis.

Data are presented as the mean ± standard deviation. *P < 0.05 vs. control group.

harvested at 0, 24, 48, and 72 h. The cell cycle progression was detected by flow cytometric analysis. After the treatment of cells with 25 μg/ml RA for the indicated times, the HepG2 cells were collected and washed twice with PBS, and fixed in 70% ice-cold ethanol overnight. The fixed cells were then centrifuged and washed twice with PBS. The cells were treated with 250 μl of PBS containing 100 μg/ml RNase A at 37 °C for 30 min. After incubation, cells were stained with 50 μg/ml PI for 30 min in the dark at room temperature. Finally, the cell cycle was analyzed by

2.9. 2-DE and protein identification by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS) Following protein extraction, the protein samples (70 μg) were resuspended with rehydration solution using immobilized pH gradient strips (Bio-Rad Laboratories; 17 cm, pH 3–10, nonlinear) to a final volume of 300 μl at 20 °C and 30 V for 10 h. After rehydration, isoelectric Fig. 6. Comparison of 2-DE image of control HepG2 cells with that of RA-treated HepG2 cells. 80 μg protein were rehydrated in rehydration buffer and separated by 2-DE-PAGE, then the gels were stained with silver nitrate and the synthetic gel images were generated using PDQUEST program. The red circle marked on behalf of differentially expressed proteins. A. The representative 2-DE image of cells treated with 30 μg/ml RA for 48 h. B. The representative 2-DE image of control cells for 48 h.

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Table 3 MALDI-TOF-MS/MS identification results of differentially expressed protein spots in RA treated HepG2 cells. Spot No.

Protein name

Accession No.

MW (KD)

pI

score

Sequence coverage(%)

matches

Expression change

Quantitative changes (%)

1 2 3 4 5 6 7 8 9 10 11

Destrin Proteasome subunit beta type-3 Alcohol dehydrogenase [NADP(+)] Triosephosphate isomerase (TPI1) Nucleoside diphosphate kinase A (NME1) Flavin reductase (NADPH) Isocitrate dehydrogenase [NAD] subunit alpha, mitochondrial Prohibitin (PHB) 40S ribosomal protein S12 (RPS12) Alpha-S1-casein Dihydrolipoyllysine-residue succinyltransferase component of 2oxoglutarate dehydrogenase complex, mitochondrial (DLST) ATP synthase subunit alpha, mitochondrion Eukaryotic translation elongation factor 1 Alpha 1 Fructose-bisphosphate aldolase A L-lactate dehydrogenase A chain (LDHA) Beta-casein

P60981 P49720 P14550 P60174 P15531 P30043 P50213 P35232 P25398 P47710 P36957

18.950 23.219 36.892 26.938 17.309 22.297 40.022 29.843 14.905 24.484 49.067

8.06 6.14 6.32 6.45 5.83 6.49 6.47 5.57 6.81 5.04 9.11

117 287 214 335 248 324 436 638 139 329 160

13 23 15 26 30 28 22 34 25 26 5

6(4) 3(3) 4(3) 6(5) 5(4) 5(4) 5(5) 7(6) 3(2) 5(3) 7(5)

Decrease Decrease Decrease Decrease Increase Increase Decrease Increase Decrease Increase Increase

124 ± 9.34 87 ± 7.12 62 ± 8.05 67 ± 6.63 42 ± 8.69 21 ± 4.82 58 ± 5.89 36 ± 7.36 32 ± 8.74 28 ± 8.58 43 ± 7.04

P25705 P68104

59.828 50.433

9.16 9.10

707 52

17 2

6(5) 5(4)

Decrease Decrease

45 ± 9.64 68 ± 9.51

P04075 P00338 P05814

39.851 34.903 25.147

8.30 6.93 5.26

297 200 138

15 11 8

3(3) 2(1) 6(5)

Decrease Decrease Decrease

42 ± 7.43 57 ± 8.49 47 ± 6.83

12 13 14 15 16

phosphate dehydrogenase (GAPDH) was used as an internal reference. Fold-change values were calculated using the 2−ΔΔCt method. All PCR amplifications were carried out in triplicate and were repeated in three independent experiments.

focusing was conducted based on the following: 250 V for 30 min; 1000 V for 60 min; and 500 V for 10 h. After the first focusing, the strips were reduced and alkylated in the equilibration buffer [10 mg/ml DTT and 25 mg/ml iodoacetamide in 6 M urea, 0.375 M Tris−HCl at pH 8.8, 20% (w/v) glycerol, and 2% (w/v) sodium dodecyl sulfate (SDS)]. Subsequently, the second dimension gels were separated by 12% SDSpolyacrylamide gel electrophoresis (PAGE) in two steps at 10 °C: 80 V/ gel for 30 min and 300 mA/gel when the bromophenol blue reached the end of the gel with running buffer (25 mM Tris−HCl, 192 mM glycine, 0.1% SDS). Following electrophoresis, the gels were visualized using a silver staining kit and analyzed using a GS-800 calibrated densitometer (Bio-Rad Laboratories). Next, we analyzed the images using the PDQuest™ 2-DE Program (ver. 8.0.1; Bio-Rad Laboratories). The means and standard deviation (SD) were calculated from three independent experiments, and a paired Student’s t-test was used to assess differences in the average protein abundance between gels. Only spots that changed significantly by more than two-fold (P < 0.05) were chosen for further MALDI-TOF/TOF-MS analysis and identification. The different protein spots were dislodged from the stained gels to analyze MS fingerprinting. Following excision of the protein spots of interest, the spots were destained and subjected to tryptic in-gel digestion as described previously [19]. Protein identification and analysis were conducted by Shanghai Sangon Biological Technology Co., Ltd. (Shanghai, China) using an Applied Biosystems 4700 Proteomics Analyzer (Applied Biosystems, Framingham, CA, USA). MASCOT (http://www.matrixscience. co.uk) was used in the NCBI database to search for proteins by MS data. The UniProt Knowledgebase was also used. The results with peptide scores greater than 30 were significant for the Swiss-Prot database (P < 0.05).

2.11. Bioinformatics analysis 2.11.1. Interaction network Protein–protein interactions were analyzed using STRING software, version 9.1 (http://string-db.org), which is a system that searches for the interaction between known and predicted proteins. This system not only identifies direct physical interactions among proteins but also indirect interactions related to the functional relationships among proteins. 2.11.2. Gene ontology (GO) analysis GO primarily analyzes the functions of genes and proteins. The three hierarchical parts of GO are ‘Biological Process’ (BP), ‘Cellular Component’ (CC), and ‘Molecular Function’ (MF). We analyzed the functional distribution of differential gene expression and protein production using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) tool (http://david.abcc.ncifcrf.gov). Additionally, we used the DAVID tool to map differential gene expression and protein production into the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways database to search for the associated biological interpretation and signaling pathways following RA treatment of HepG2 cells. Fisher's exact test was used, and P < 0.05 was considered to indicate statistical significance. 2.12. Western blotting analysis

2.10. Quantitative reverse transcription–quantitative polymerase chain reaction (RT–qPCR)

To explore glycolytic pathway-related protein changes, HepG2 cells were harvested and lysed with radioimmunoprecipitation lysis buffer (Beyotime) for 30 min at 4 °C, and the cell lysate supernatants were harvested by centrifugation at 15,000 × g for 15 min at 4 °C. The protein concentration was determined using a BCA protein assay kit according to the manufacturer’s instructions (Beyotime). Subsequently, the treated and control protein samples (15 μg of protein/lane) were separated by 12% SDS-PAGE and transferred to polyvinylidene difluoride membranes. Following transfer, the membranes were blocked with 5% nonfat milk and incubated with primary antibodies at 4 °C overnight. After washing with Tris-buffered saline with Tween-20 three times, the membranes were incubated with the corresponding secondary antibodies for 1 h. Finally, the signals were detected using the

Total RNA was extracted from HepG2 cells following RA treatment using TRIzol reagent (Invitrogen, Carlsbad, CA, USA). Complementary DNA (cDNA) was then synthesized from 1 μg of total RNA through a high-capacity cDNA reverse transcription kit (TaKaRA, Dalian, China) according to the manufacturer’s instructions and PHB, DLST, EEF1A1, and LDHA mRNA levels were assessed by RT–qPCR. The sequences of the primers are listed in Table 1. PCR was performed according to the standard protocol using a Roche LightCycler (Roche, Pleasanton, CA, USA) using SYBR green detection (TaKaRa SYBR Green Supermix). PCR amplification was performed by denaturation at 95 °C for 5 s, and annealing and extension at 60 °C for 40 s for 40 cycles. Glyceraldehyde 3339

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Fig. 7. Identification of protein spot #8 from Fig. 6. A. Mass spectrum of tryptic peptide from spot #8. B. Protein sequence of prohibitin is shown. The matched peptides are in bold red. C. Output of the database searching by the MASCOT program using MS/MS data resulted in the identification of prohibitin.

concentrations of RA (12.5, 25, and 50 μg/ml) for 48 h. Next, the supernatants and cells were collected, and the glucose and lactate levels in the incubation media were assayed using glucose and lactate assay kits (Nanjing Jiancheng Bioengineering Institute) according to the manufacturer’s instructions. To measure ATP, HepG2 cells from the different groups were lysed and the cell lysates were clarified by centrifugation at 15,000 rpm and 4 °C for 10 min. The concentration of ATP in the supernatants from different samples was calculated using the ATP assay kit (Beyotime) using an automated microplate reader (Bio-Rad Laboratories). Each assay was performed in triplicate.

enhanced chemiluminescence substrate kit (Thermo Fisher Scientific) and visualized using the Gel Imaging System (Bio-Rad Laboratories). The target protein amounts were normalized with GAPDH as a reference protein. ImageJ software was used to analyze the western blotting data.

2.13. Measurement of glucose consumption and lactate and ATP production HepG2 cells (2 × 105 cells/well) were seeded in 24-well plates with 200 μl of media in each well. After 24 h, the culture medium was removed and replaced with fresh medium containing different 340

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Fig. 8. Identification of protein spot #15 from Fig. 6. A. Mass spectrum of tryptic peptide from spot #15. B. Protein sequence of L-lactate dehydrogenase A chain is shown. The matched peptides are in bold red. C. Output of the database searching by the MASCOT program using MS/MS data resulted in the identification of Llactate dehydrogenase A chain.

2.14. Statistical analysis

3. Results

All experiments were performed in triplicate. The data were presented as means ± SD and analyzed by one-way analysis of variance using SPSS 22.0 software (IBM, Armonk, NY, USA). Statistical significance was deemed at a P-value < 0.05.

3.1. RA exhibits cytotoxicity in HepG2 cells To evaluate whether RA influences the cytotoxicity of HepG2 cells, the cells were treated with different concentrations of RA (6.25, 12.5, 25, 50, and 100 μg/ml) and subjected to MTT and LDH assays at 24, 48, and 72 h. The results clearly indicated that cell viability decreased gradually as the RA concentration increased. RA could significantly 341

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Fig. 9. The mRNA expression levels of identified proteins were validated by RT-qPCR in HepG2 cells after RA treatment for 48 h. The differential expression of PHB and DLST mRNA expression were upregulated, EEF1A1 and LDHA mRNA expression were decreased after treatment with RA (*P < 0.05, **P < 0.01).

annexin V-FITC/PI double staining assay was applied to verify that RA induces apoptosis. Following treatment with RA (6.25, 12.5, 25, 50, and 100 μg/ml) for 48 h, the ratios of cells in early and late apoptosis were significantly increased, whereas the percentage of viable cells was decreased (Fig. 4A). The percentage of apoptotic cells increased from 0.35% to 28.61%. These results demonstrated that RA dose-dependently increased apoptosis (Fig. 4B), resulting in the cytotoxic activity of RA in HepG2 cells.

reduce the viability of HepG2 cells in a time- and dose-dependent manner (Fig. 2A). The RA IC50 value for HepG2 cells was 33 ± 0.74 μg/ml after 48 h of incubation. Thus, 30 μg/ml RA was chosen for subsequent proteomic experiments. Destruction of the cell membrane structure caused by apoptosis or necrosis results in the release of enzymes from the cytoplasm into the culture fluid, including LDH. Thus, by testing the activity of LDH released from the plasma membrane by ruptured cells into the medium, quantitative analysis of cytotoxicity can be achieved [20]. When HepG2 cells were exposed to different concentrations (6.25, 12.5, 25, 50, and 100 μg/ml) of RA for 48 h, LDH release was significantly increased compared with that of untreated cells (Fig. 2B), further supporting the role of RA-mediated cytotoxicity in HepG2 cells.

3.4. Effect of RA on the cell cycle of HepG2 cells

The nucleus was stained with Hoechst 33258 to determine the morphological effects of apoptosis. Typical microphotographs showed that the morphological changes in apoptosis, including chromatin condensation, cell shrinkage, and nuclear fragmentation, were evident in HepG2 cells treated with the different concentrations of RA. These results showed a significant increase in apoptosis compared with that of the control group (Fig. 3). Therefore, RA could increase the rates of apoptosis.

Cell growth inhibition is usually related to cell cycle arrest at a specific stage. We performed flow cytometric analysis of cellular DNA to evaluate the cell cycle distribution of HepG2 cells treated with 25 μg/ ml RA for 24, 48, and 72 h. To detect the cell cycle progression, HepG2 cells were synchronized at G1/S phase by using double thymidine block. Upon release from the block, the percentage of HepG2 cells was increased in the G1 phase of the cell cycle compared with that of controls, suggesting that more HepG2 cells were arrested at the G1 phase of the cell cycle in the presence of RA (Fig. 5). RA increased the proportion of cells in G1 from 55.03% in control cells to 62.60% for 24 h, 58.51% in control cells to 74.52% for 48 h, and 55.12% in control cells to 81.26% for 72 h following exposure of HepG2 cells to the 25 μg/ ml RA (Table. 2).

3.3. Apoptosis induction following RA treatment in HepG2 cells

3.5. 2-DE and image analyses

3.2. RA induces apoptosis in HepG2 cells

To further investigate the underlying mechanisms of RA-induced

Apoptosis is usually dysregulated during cancer progression. The 342

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Fig. 10. Protein interaction network and functional analysis. A. Protein-protein interaction networks built on STRING for the identified proteins. (B-D). Gene ontology (GO) classification of the proteins affected by RA. The y-axis shows significantly enriched gene ontology (GO) terms relative to the genome, and the x-axis shows the enrichment scores of these terms. B. Molecular Function (MF) categories in GO. C. Biological Process (BP) categories in GO. D. Cellular Component (CC) categories in GO. E. KEGG analysis of differentiall expressed proteins associated signal pthways. F. KEGG pathway enrichment analysis maps of the Glycolysis / Gluconeogenesis signal pathway.

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Fig. 10. (continued)

their MASCOT scores, MS/MS matched sequences, theoretical molecular weights, pI, coverage, and changes in expression levels are revealed in Table 3. Among them, five proteins (nucleoside diphosphate kinase A, flavin reductase [NADPH], prohibitin, alpha-S1-casein, and dihydrolipoyllysine-residue succinyltransferase component of 2-oxoglutarate dehydrogenase complex, mitochondrial) were upregulated, and 11 (destrin, proteasome subunit beta type-3, alcohol dehydrogenase, triosephosphate isomerase, isocitrate dehydrogenase subunit alpha, 40S ribosomal protein S12, ATP synthase subunit alpha, eukaryotic translation elongation factor 1 alpha 1, fructose-bisphosphate aldolase A, L-lactate dehydrogenase A chain, and beta-casein) were decreased. Characteristic MS/MS search results for spots 8 and 15 are shown in Figs. 7 and 8.

cytotoxicity in HepG2 cells, proteomic profiling of control and RAtreated cells was conducted via comparative proteomic analysis. HepG2 cells were exposed to 30 μg/ml RA for 48 h and collected. Cell lysates were centrifuged and the supernatants were obtained. The 2-DE protein maps were applied to observe the underlying mechanisms of action of RA in HepG2 cells. Proteins (70 μg; pI 3–10) were separated by 2-DEPAGE, and a typical pair of silver-stained images was obtained (Fig. 6). PDQuest software was used to detect any variations in protein spots, defined as those essentially representing a two-fold or greater intensity difference (P < 0.05) from three replicate gels. Our results revealed that 364 proteins were differentially expressed following RA treatment, and we successfully identified 16 proteins that showed significant changes between the RA-treated and control groups through MS analysis. These identified proteins are labeled with arrows.

3.7. Confirmation of differentially expressed proteins by RT-qPCR 3.6. Identification of differentially expressed proteins To further verify whether the protein changes determined by proteomic analysis are related to alterations of mRNA at the transcriptional level, we demonstrated the corresponding mRNA expression by specific primers through RT–qPCR. Therefore, we further verified the differential expression of PHB, DLST, EEF1A1, and LDHA in HepG2 cells with or without RA treatment by RT–qPCR. Compared with the control

All 16 protein spots were identified successfully by comparing the two images, according to the MALDI-TOF/TOF-MS analysis and the NCBI database search. Among them, five proteins were upregulated and 11 proteins were downregulated. The 16 differentially expressed proteins are marked in spots 1–16. A list of the identified proteins with 344

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Fig. 10. (continued)

expressed proteins (P < 0.05). Fig. 10B–D lists the top 10 significantly enriched GO terms. Additionally, the differentially expressed proteins were allocated to forecast KEGG pathways, with the identified differentially accumulated proteins enriched in pathways related to the biosynthesis of antibiotics, glycolysis/gluconeogenesis, carbon metabolism, metabolic pathways, biosynthesis of amino acids, tricarboxylic acid (TCA) cycle, and fructose and mannose metabolism (Fig. 10E). The KEGG maps of glycolysis/gluconeogenesis signaling pathways are shown in Fig. 10F. The STRING and GO analysis results demonstrated that the identified proteins participated in several biological processes and exhibited various molecular functions, mainly related to inactivation of the glycolysis/gluconeogenesis signaling pathway and other metabolic pathways.

group, PHB and DLST mRNA expression levels were increased following treatment with RA (Fig. 9). Similarly, RA also resulted in downregulation of the mRNA level of EEF1A1 and LDHA in HepG2 cells (Fig. 9). The RT–qPCR results agreed with those of the 2-DE analysis. 3.8. Analysis of the signaling network using bioinformatics To analyze the protein–protein interactions among the proteins identified by MADLI-TOF/MS, we subjected the differentially expressed proteins to the web-tool STRING database. Fig. 10A shows the protein–protein interaction networks generated by the database and web tool STRING. The proteins EEF1A1, LDHA, TPI1, and RPS12 represented important nodes and modulators within the network maps. Next, the differentially expressed proteins were classified according to their GO function using the DAVID analysis tool. Sixteen function annotations of MF, 109 function annotations of BP, and 16 function annotations of CC were significantly enriched among the differentially

3.9. RA suppresses the glycolytic pathway of HepG2 cells Changes in cellular metabolism are important features of tumors, 345

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Fig. 11. RA suppresses the activation of glycolytic pathway in HepG2 cells. A. The level Glut-1 and HK-2 expression was detected using western blotting analysis. βactin was used as a control. B-D. Relative glucose consumption, lactate, and ATP levels after 48 h of treatment with RA. The results were presented as mean ± SD of three independent experiments. *P < 0.05 vs the control.

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Fig. 12. RA exhibits significant cytotoxic effects by inhibiting cell proliferation, inducing apoptosis, possibly through blocking glycolytic pathway in human HepG2 cells.

proliferation by RA. Flow cytometry also showed an increase in the rate of apoptosis in response to RA treatment. Similarly, RA significantly increased LDH leakage in HepG2 cells with increasing concentration. Destruction of the cell membrane structure caused by apoptosis or necrosis will result in the release of enzymes from the cytoplasm into the culture fluid, including LDH with relatively stable enzymatic activity. Quantitative analysis of cytotoxicity can be achieved by detecting the activity of LDH released from plasma membrane-disrupted cells into the culture fluid. LDH release is an important indicator of cell membrane integrity and is widely used to test cytotoxicity. Thus, these data suggested that RA could induce cytotoxicity in HepG2 cells, and the data are similar to previous reports that RA treatment increased the rates of apoptosis and necrosis of glioblastoma cells [25]. The cell cycle represents a sequence of events that impact cell growth and proliferation. In recent years, these cell cycle phases have been targets for cancer therapy. For example, many anti-cancer agents arrest the cell cycle at the G1, S, or G2/M phases and induce apoptotic cell death. Accordingly, the effect of RA on the cell cycle distribution of HepG2 cells was studied to verify the mechanism by which the anticancer effect was achieved. These data suggested that RA could inhibit cell growth and induce apoptosis of HepG2 cells associated with cell cycle arrest in G1, and the data are similar to those of previous reports that RA induced cell cycle arrest in G1 in colorectal cells [26]. Additionally, we performed proteomic analysis to identify target molecules of RA in HepG2 cells. Sixteen differentially expressed proteins were identified by MALDI-TOF/TOF-MS analysis followed by an NCBI database search. Among them, five proteins (nucleoside diphosphate kinase A, NADPH, prohibitin, alpha-S1-casein, and dihydrolipoyllysine-residue succinyltransferase component of 2-oxoglutarate dehydrogenase complex, mitochondrial) were upregulated and 11 (destrin, proteasome subunit beta type-3, alcohol dehydrogenase, triosephosphate isomerase, isocitrate dehydrogenase subunit alpha, 40S ribosomal protein S12, ATP synthase subunit alpha, eukaryotic translation elongation factor 1 alpha 1, fructose-bisphosphate aldolase A, L-lactate dehydrogenase A chain, and beta-casein) were decreased. The qRT–PCR results for the PHB, DLST, EEF1A1, and LDHA mRNA levels agreed with those of the 2-DE analysis. The functional effects of the key proteins are discussed briefly below. PHB is a multi-organelle-localized protein with high homology that

with reciprocal causation concerning the occurrence and development of tumors. Aerobic glycolysis is an important feature of tumors, providing survival advantages for tumor cells. According to the results of the above bioinformatics analysis, therefore, we investigated the effects of RA on the glycolytic pathway in HepG2 cells. The protein expression levels of Glut-1 and HK-2 were significantly downregulated with the increase in RA concentration, and the ratio of protein expression was decreased (Fig. 11A). We further studied the effect of RA on glycolysis in HepG2 cells. RA significantly suppressed the rate of glucose consumption, and lactate and ATP production with increasing doses of RA (Fig. 11B–D). These data indicated that RA could inhibit growth and induce apoptosis by blocking the glycolytic pathway in HepG2 cells. 4. Discussion The incidence and fatality rates of malignant tumors have increased annually, and malignancies are ranked first among all causes of death, seriously endangering human health. HCC is a common malignant gastrointestinal cancer with high mortality and morbidity and is ranked third in cancer incidence worldwide, with an increasing trend annually [21]. China has a high incidence of HCC, accounting for approximately half of the world's total number of cases, and its mortality rate ranks first in the world. Currently, the preferred treatment for HCC is surgical resection. However, the recurrence rate of HCC is as high as 80% after 5 years, seriously affecting the prognosis of patients [22]. Therefore, it is of great significance to identify and develop anti−HCC drugs with high efficiency and low toxicity. TCM has been widely applied to prevent, diagnose, and cure many diseases for over 3000 years and has a unique advantage in the treatment of cancer [23]. Many anti-cancer agents arrest the cell cycle at the G0/G1, S, and G2/M phases and directly induce apoptosis or necrosis to kill cancer cells [23,24]. In the present study, human HepG2 cells were used as a model, and a 2-DE-based proteomics method was used to identify the proteins altered by treatment with RA. Following RA treatment, the proliferation of HepG2 cells was significantly inhibited and typical morphological changes related to apoptosis were observed. For several decades, apoptosis has been considered the principal mechanism of programmed cell death in mammalian cells [24]. The present study furthers our understanding of the inhibitory effects of 347

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nutrients such as glucose and increased glycolysis often appear. Despite the low productivity of glycolysis, it provides rapid ATP supply to tumor cells and many macromolecules that meet the energy and substance requirements of rapidly proliferating tumor cells [40]. Presently, some good results have been achieved by targeting tumor energy metabolism in tumorigenesis and clinical treatment. For example, targeted inhibition of GLUTs, HK, PK, LDHA, and MCTs could reduce the tumor cell glycolytic capacity and inhibit tumor growth and proliferation [41,42]. These results have demonstrated that the treatment program of targeting cancer cell energy metabolism will be important in the field of cancer treatment. To ascertain whether the glycolytic pathway contributes to the effect induced by RA treatment, western blotting analysis was carried out. RA treatment could increase the levels of Glut-1 and HK-2, leading to the suppression of glucose consumption as well as the generation of lactate and ATP, indicating that RA could inhibit the glucose metabolism of HepG2 cells. GLUTs can transport glucose into the interior of cells and provide the energy they need to grow and proliferate through glycolysis or aerobic oxidation in cancer cells [43]. Studies have shown that the inhibition of GLUT1 could attenuate glycolysis and significantly reduce cancer cell viability and ATP levels [44]. Therefore, GLUT1 is expected to be a target of anti-tumor therapy. Additionally, HKs are the first rate-limiting enzymes in glycolysis, and the four isoforms usually exhibit low expression in normal cells and are highly expressed in many cancer cells [45]. Targeting HK-2 can effectively inhibit the growth of cancer cells [46]. These results indicated that RA might suppress cell growth by blocking the glycolytic pathway in HepG2 cells. The data are similar to those of previous reports that RA might be a therapeutic agent to suppress the Warburg effect in gastric carcinoma [47]. Taken together, the data in the present study demonstrated that RA possessed cytotoxic activity by inducing apoptosis and cell cycle arrest in HepG2 cells in vitro. Proteomics analysis of the differentially expressed protein profiles and western blot analysis indicate that glycolysis proteins are associated with RA-induced cytotoxicity. Our data demonstrated that RA could suppress cell growth and induce apoptosis and cell cycle arrest via blocking the glycolytic pathway in HepG2 cells (Fig. 12). These findings could contribute to our understanding of the molecular toxicity of RA and provide valuable data for the reasonable use of this drug.

is mainly distributed in the mitochondrial inner membrane, plasma membrane, and cytoplasm and plays a corresponding physiological function as a molecular chaperone in mitochondria, maintaining the structure and function of mitochondria and is involved in cell adhesion in the quality membrane and transmission of cellular signals [27]. Several studies have shown that the overexpression of PHB in the nucleus may reveal failed movement of mitochondria, leading to the dysfunction of mitochondria and regulation of the cell cycle and playing important roles in inhibiting proliferation and inducing apoptosis [28]. Therefore, PHB may act as a tumor suppressor and its increased expression may contribute to the anti-cancer activity of RA in HepG2 cells. RPS12, a highly conserved protein at the functional center of the 30S subunit of the ribosome, participates in protein synthesis [29]. Many studies have indicated that RPS12 is overexpressed in human cervical carcinoma, breast cancer, and gastric cancer [30]. In addition, RPS12, as the determinant of the various streptomycin phenotypes, might promote multi-drug resistance by inhibiting drug-induced apoptosis [31]. We observed that RA could decrease the expression of RPS12, indicating that RPS12 may be a common therapeutic biomarker for tumors and a new target of RA in reversing drug resistance. LDHA is a tetrameric enzyme polymerized from four subunits and can catalyze the conversion of pyruvate into lactic acid in the terminal glycolytic process. LDH has five isozymes, among which LDHA is the most closely associated with tumor occurrence but is also associated with tumor metabolism, invasion, and prognosis [32]. Studies have shown that LDHA is overexpressed to varying degrees in many tumors and functions like oncogenes [33]. c-Myc upregulates expression of the LDHA gene, making the tumor cells show high aerobic glycolysis and promoting tumor growth [34]. In vivo experimental results showed that the inhibition of LDHA expression by short interfering RNA or drugs could hinder tumor development [35]. The small molecule inhibitor FX11 and sodium oxalate of LDHA could delay glycolysis, increase mitochondrial metabolic flux, and inhibit tumor growth and invasion, further demonstrating the important role of LDHA in tumors [36]. These data show that LDHA may be a valid target in cancer treatment. In the present study, the expression of LDHA was decreased in RAtreated HepG2 cells, as confirmed by qRT − PCR results, thereby potentially blocking tumor glycolytic metabolism to inhibit HepG2 cell proliferation. To obtain comprehensive insight and the possible interactions of the identified proteins, bioinformatics of the identified 16 proteins, including protein network, GO, and pathway analyses, were analyzed. STRING analysis was applied to identify the interacting networks involving the proteins. In the interaction network, the proteins clustered in a tight interaction network centered on EEF1A1, LDHA, TPI1, and RPS12, which were mainly connected with cancer metabolic pathways. The identified proteins were then queried against the KEGG pathway database, and the main pathways were related to signaling pathways, including the biosynthesis of antibiotics, glycolysis/gluconeogenesis, carbon metabolism, metabolic pathways, biosynthesis of amino acids, the TCA cycle, and fructose and mannose metabolism, indicating that these signaling proteins played a significant role in the effect of RA treatment in HepG2 cells. These data demonstrated that the identified proteins participated in several biological processes and exhibited diverse molecular functions mainly related to the activation of glycolysis/ gluconeogenesis and metabolic pathways. Energy metabolism refers to the process of energy production, release, conversion, and utilization of organisms in the process of material metabolism. The energy of the cell comes mainly from the conversion of glucose [37]. Normal cells are mainly powered by the aerobic oxidation of glucose, while the energy metabolism of tumor cells differs significantly from normal cells. Even in the case of adequate oxygen, tumor cells still use glycolysis as the major energy source, a phenomenon called the Warburg effect [38,39]. The energy metabolism of tumor cells mainly depends on glycolytic activity. Due to the rapid growth of tumor cells, the increased uptake of

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