Introduction
Lung cancer is one of the most prevalent malignancies in humans, and its incidence and mortality are increasing worldwide [1]. Approximately 80% of lung cancers are non-small cell lung cancers (NSCLCs). Although diagnostic and treatment methods have recently improved markedly, no significant improvements in the prognosis of patients with NSCLC have been achieved, as the 5-year survival rates for all patients diagnosed with lung cancer remain at approximately 15% [2, 3]. Currently, the major methods for lung cancer treatment include surgery, chemotherapy and radiotherapy. Among these methods, chemotherapy can significantly relieve symptoms and improve patient quality of life. However, the efficacy and safety of this treatment remain a primary concern. Chemotherapy drugs have some serious side effects, and the toxicity of these drugs has always been an obstacle to clinical applications [4]. Therefore, the development of new therapeutic drugs for lung cancer that have high efficacy and low toxicity is clinically important.
Triptolide (TP), originally extracted from the traditional Chinese medicinal plant Tripterygium wilfordii [5], has been confirmed to have myriad biological properties, including immunosuppression and anti-inflammatory effects, and has been applied for the treatment of autoimmune diseases, such as nephritis and rheumatoid arthritis [6-8]. Recently, numerous studies have demonstrated that TP possesses prominent anti-tumor activities in diverse tumor cell types in vitro, such as breast [9], pancreatic [10], ovarian [11], lung [12], and prostate cancers [13]. TP can also prevent tumor growth in vivo via cell proliferation inhibition and apoptosis induction [14]. Moreover, studies have reported that TP sensitizes human cancer cells to cisplatin, 5-fluorouracil (5-FU) and TNF-alpha-induced apoptosis in vivo and in vitro [15, 16]. In a previous study, we observed that TP induces apoptosis in human lung cancer cells through PP2A-regulated ERK, p38, MAPK and Akt signaling pathways [17]. Until recently, the activity of TP in inducing tumor cell death has been well documented, but the complex molecular targets of TP anti-tumor activity have not been well characterized. Thus, a powerful tool to accurately monitor and quantitatively detect changes in protein expression in response to TP treatment is needed.
Proteomics approaches, enabling relatively comprehensive global analyses, have been widely used to examine complex biological functions [18-20]. The isobaric tags for the relative and absolute quantitation (iTRAQ) method combined with nano liquid chromatography-mass spectrometry (NanoLC-MS/MS), developed for protein quantitation, represent a high-throughput quantitative technique with high sensitivity and reproducibility. Currently, iTRAQ-based proteomics has been widely used to investigate the mechanistic effects of chemicals on cancer [21-24].
In the present study, we employed a strategy combining iTRAQ with NanoLC-MS/MS to analyze alterations in the protein profile of the A549 lung adenosquamous carcinoma cell line following TP treatment. Differential protein expression data may provide a valuable resource to reveal potential molecular targets underlying the anticancer activity of TP and to improve the understanding of the anti-tumor effects of TP on lung cancer.
Materials and Methods
Cell culture and treatment
Human lung cancer A549 cells (American Type Culture Collection; ATCC CCL185) were maintained in monolayer culture at 37°C in a humidified atmosphere with 5% CO2 in RPMI-1640 medium (Gibco-BRL, USA) supplemented with 10% fetal bovine serum (FBS) (Sijiqin Biotechnology Co. Ltd., China) and 1% penicillin/streptomycin solution (100 U/ml penicillin and 100 µg/ml streptomycin). A total of 20 mg of TP (purity≥98%, Beijing Fan-China Biotechnology Co., Ltd.) was dissolved in 0.5 ml dimethylsulfoxide (DMSO) to obtain a 100% stock solution, which was subsequently stored at -20°C and diluted with medium prior to use in experiments. The final DMSO concentration did not exceed 0.1% (v/v) throughout the study. For exposure experiments, A549 cells at approximately 80% confluency were transferred to medium containing 12.5, 50, and 200 ng/ml of TP and were cultured for 36 h (24-h 50% inhibitory concentration [IC50]=273.0 ng/ml) [17]. Cells treated with an equal amount of DMSO were employed as a control, and all of the treatments were performed in triplicate. Three replicate proteomics analyses were performed for each test concentration and the control group. The iTRAQ experimental results described herein are only for the 200 ng/ml TP concentration, as cells represented more acute TP cytotoxicity at this concentration.
Flow cytometric cell cycle and cell apoptosis analysis
The effects of TP on cell cycle progression were measured using flow cytometry. The fixed cells were stained with propidium iodide (PI, ComWin Biotech Co. Ltd., China) solution (50 µg/ml PI and 100 µg/ml RNase A in PBS) and were subsequently subjected to cell cycle analysis. Cell apoptosis was measured using Annexin V/PI double staining (ComWin Biotech Co. Ltd., China). Briefly, 100 µl of binding buffer containing 2.5 µl of Annexin V-fluorescein isothiocyanate (FITC) and 1 µl of PI was added to the cell suspension, followed by incubation for 30 min in the dark. The samples were assayed using a Beckman-Coulter Flow Cytometer with excitation at 488 nm and emission at 525 nm for FITC and 575 nm for PI. The data were analyzed using FlowJo software.
Protein preparation
The harvested cells were washed five times using ice-cold PBS and disrupted using enhanced RIPA lysis buffer (Beyotime Co., China) containing protease and phosphatase inhibitors for 30 min on ice, followed by ten cycles of 5-second bursts of sonication with 30-second intervals. The cell debris was removed by centrifugation at 12, 000×g for 30 min at 4°C, and the supernatants were collected. Protein concentrations were assayed using a bicinchoninic acid (BCA) protein assay kit according to the manufacturer’s instructions (Beyotime Co., China). Bovine serum albumin (BSA) was used as the standard.
iTRAQ labeling and high-pH RPLC fractionation
The iTRAQ Reagent 4-Plex kit (AB Sciex, USA) was used according to the manufacturer’s instructions to label peptides. Equal amounts of protein (100 µg per sample) obtained from TP-treated and control cells were labeled using iTRAQ labeling reagents. The TP-treated samples were labeled using 117, while the control samples were labeled using 114. Briefly, the proteins in each sample were reduced with dithiothreitol (DTT) and were subsequently alkylated with iodoacetamide. The samples were digested overnight at 37°C using trypsin (AB Sciex, USA) at a trypsin:protein ratio of 1: 20 (W/W). The tryptic peptides were labeled using iTRAQ reagents. The labeled samples were combined and lyophilized. The peptide mixtures were dissolved in high-pH reverse phase (HP-RP) solvent A (20 mM ammonium formate, pH 10.0). The peptides were fractionated using the Shimadzu LC-30A system with a Durashell-C18 column (4.6 mm×250 mm, 5 µm 100 Å, Agela, China) for high-pH RP chromatography. A total of 40 RP fractions were collected and subsequently dried and reconstituted using 30 µl of 0.1% FA for NanoLC-MS/MS analysis.
NanoLC-MS/MS analysis
Separation was performed using the Eksigent nanoLC-UltraTM 2D System combined with the cHiPLCTM-Nanoflex system in Trap-Elute mode connected to a Triple TOF 4600 mass spectrometer (AB Sciex, USA). Briefly, 8 µl of each fraction was loaded onto the cHiPLC trap (200 µm × 500 µm ChromXP C18-CL 3 µm 300 Å) and washed for 15 min at 2 µl/min. Subsequently, an elution gradient of 10-43% acetonitrile (0.1% formic acid) in an 85-min gradient at 300 nl/min was used on a nano cHiPLC column (75 µm × 15 cm ChromXP C18-CL 3 µm 300 Å). The MS analysis was performed using a nano ion spray voltage maintained at 2.3 kV and a scan range of 350 to 1500 (m/z) in the positive-ion mode. Full-scan MS spectra were acquired from 40 precursors selected for MS/MS from an m/z 100-1500 range using a dynamic exclusion setting of 30 s. The IDA CE parameter script, which selected up to 40 precursors with charge states of 2+ to 4+, automatically controlled the collision energy (CE). The mass spectrometer was calibrated using the tryptic peptides of beta-galactosidase.
Protein identification and quantitation
Peptide identification and quantification were conducted using ProteinPilot 4.2 software (AB Sciex, USA). The following search parameters were used: (1) sample type, iTRAQ 4-plex (Peptide Labeled); (2) cysteine alkylation, iodoacetamide; (3) digestion, trypsin; (4) instrument, Triple TOF 4600; (5) special factors, none; (6) species, Homo sapiens; (7) ID Focus, biological modifications; (8) database, UniProtKB/Swiss-Prot FASTA; and (9) search effort, Thorough ID. In the iTRAQ quantitation, the Pro Group algorithm was automatically selected to calculate the reporter-peak areas. To estimate the false discovery rate (FDR) for peptide identification, a decoy database search strategy was adopted. For this study, a strict unused confidence score of >1.3 was used as the qualification criterion, corresponding to a peptide confidence level of 95%. If the iTRAQ ratios were >2.0 or <0.5 in the samples obtained from the TP-treated A549 cells relative to those of the control group, then the proteins were considered differentially expressed.
Bioinformatics analysis of proteomics data
The identified proteins were classified according to annotations from the UniProt knowledge base (Swissprot/TrEMBL, http://www.uniprot.org/).The multi-omics data analysis tool, OmicsBean, was used to analyze the obtained proteomics data (http://www.omicsbean.com), in which distributions in biological process (BP), cellular components (CCs) and molecular functions (MF) were assigned to each protein based on Gene Ontology (GO) categories. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis (http://www.genome.ad.jpkegg/pathway.html) was performed to enrich high-level functions in the defined biological systems. Protein-protein interaction (PPI) analysis was performed using Cytoscape software, with a confidence cutoff of 400; interactions with larger confident scores are indicated with solid lines between genes/proteins, or otherwise shown as dashed lines.
Western blotting
The A549 cells were washed twice with cold PBS and lysed in 200 µl RIPA lysis buffer (50 mM Tris-HCl, 150 mM NaCl, 1% Triton X-100, 1% sodium deoxycholate, and 0.1% sodium dodecyl sulfate; Beyotime Co., China) containing 100 mM phenylmethanesulfonyl fluoride (PMSF; Beyotime Co., China) for 30 min on ice. The lysates were centrifuged at 14, 000×g for 10 min at 4°C, and the supernatants were collected. Twenty micrograms of protein/well was loaded onto 10% gels for separation using sodium dodecyl sulfate-polyacrylamide gels electrophoresis (SDS-PAGE). The gels were electrophoretically transferred onto polyvinylidene fluoride (PVDF) membranes (0.45 or 0.20 µm pore size; Millipore, Billerica, MA, USA). The blotted membranes were blocked with 5% nonfat dry milk in a Tris-buffered saline solution (25 mM Tris, pH 7.5, and 150 mM NaCl) containing 0.05% Tween 20 (TBST) for 2 h at room temperature, followed by incubation with the diluted primary antibody against target protein for 4 h at room temperature. After washing for 10 min in TBST solution, the membranes were incubated with properly diluted secondary antibody conjugated with horseradish peroxidase for 2 h at room temperature. Western signals were developed using ECL chemiluminescent reagents from Thermo Scientific (Waltham, MA, USA). The β-actin levels were used as loading controls.
Statistical analysis
Western blotting and flow cytometry results are presented as the means ± standard deviations (SD) from three independent experiments. Statistical analysis of the quantitative data for multiple group comparisons was performed using one-way ANOVA. Duncan’s test (two sided) was used to determine the statistical significance levels (P<0.05 and P<0.01) between control and TP-treated groups.
Results
TP-induced apoptosis of A549 cells
To investigate the effects of TP on apoptosis in A549 cells, Annexin V/PI staining-based FACS analysis was performed to detect the externalization of phosphatidylserine on the cell membrane, a hallmark of early apoptosis. Cells undergoing early-stage apoptosis were stained with Annexin V-FITC+/PI-, and late apoptotic cells were stained with Annexin V+/PI+. Fig. 1A quantifies the increase in early apoptotic cells labeled with Annexin V+/PI-, showing increases from 3.2% in the control group to 14.8, 20.4% and 27.3% in the TP-treated groups, respectively. In addition, the overall apoptotic rates were significantly increased in the TP groups. These findings revealed that various TP treatments induced significantly higher percentages of apoptotic cells than the control group (Fig. 1B), indicating that TP can promote apoptosis.
Fig. 1.
Apoptotic effects of TP on human lung cancer A549 cells. (A) After 36 h of TP treatment (12.5, 50, and 200 ng/ml), A549 cells were stained with Annexin V-FITC and PI and analyzed using flow cytometry. Early apoptotic cells were Annexin V+/ PI–, and late apoptotic cells were Annexin V+/PI+. (B) The overall apoptotic rates were significantly increased after TP treatment. **P<0.01 compared with the control group. Data are presented as the means ± SD of three independent experiments.
Effects of TP on cell cycle arrest
The effects of TP on the cell cycle are shown in Fig. 2. Compared with the control group, the percentage of cells in the G0/G1 phase decreased from 63.84% to 13.75%, whereas the percentage of cells in the G2/M phase increased from 14.66% to 64.56%. These results indicated that TP blocks A549 cells at the G2/M phase.
Fig. 2.
Effects of TP on cell cycle distribution in human lung cancer A549 cells. (A) Representative histograms depicting cell cycle distributions in A549 cells treated with TP. After 36 h of TP exposure (0, 12.5, 50 and 200 ng/ml), A549 cells were stained with PI and analyzed using flow cytometry. (B) The percentage of the total cell population in each phase of the cell cycle is represented as a bar diagram. **P<0.01 compared with the control group. Data are presented as the means ± SD of three independent experiments.
Comparative proteomics of TP-treated A549 cells versus control A549 Cells
The proteins were extracted from cells treated in parallel. The samples were digested using trypsin and were labeled using 114 and 117 iTRAQ tags, and the labeled digests were utilized for MS analysis (Fig. 3A). The database we searched contains 376809 entries. Using ProteinPilot 4.5, we identified totals of 4977/5102/4762 proteins in these two cell lines in the three runs (Local FDR of <5%). Using filters with an unused protein score of >1.3 and a number of peptides of ≥2, 4561/4446/4302 proteins were identified (Table 1). In total, we identified 141 up-regulated (with 117: 114 iTRAQ ratios of >2.0) and 171 down-regulated proteins (with 117: 114 iTRAQ ratios of <0.5) in TP-treated A549 cells compared with the control cells (Fig. 3C, Tables 2 and 3). Among those 312 dysregulated proteins, 50 proteins related to cell apoptosis were enriched (Table 4). Afterward, we performed a cluster analysis to get the heatmap which contains the data obtained for the 312 dysregulated proteins. The three horizontal clusters represent the technical replicates (Fig. 4).
Fig. 3.
Experimental quantitative proteomics analysis workflow and results. (A) Experimental design for the quantitative proteomics analysis. The proteins from A549 cells treated with different concentrations of TP were digested with trypsin and labeled using 114/117/iTRAQ tags. The labeled digests were analyzed using Nano LC-MS/MS. The differentially expressed proteins were evaluated using western blotting and analyzed through database searches. (B) The enriched counts for Biological Process, Cellular Component, Molecule Function, and KEGG Pathway. The counts for each category represent the total number of terms in the database associated with the query gene/protein list. Terms with P-values<0.05 are statistically significant. (C) In total, 312 proteins were identified, including 141 up-regulated proteins and 171 down-regulated proteins.
Fig. 4.
Heatmap of the expression levels of 312 dysregulated proteins. The red-colored clusters represent up-regulated proteins, and the greencolored clusters represent down-regulated proteins.
Functional enrichment of the TP-regulated proteins
The obtained protein data were analyzed using bioinformatics approaches to extract information relevant to the involved pathways. Enrichments of TP-related proteins in BP, CC, and MF categories based on GO analysis are shown in Fig. 3B. In the BP analysis, the majority of identified proteins were classified into metabolic processes, particularly nitrogen compound metabolism and cellular nitrogen compound metabolism. The CC analysis showed that most of the identified proteins belonged to organelles and membrane-bounded organelles. The molecular functional classification revealed that most of these proteins were involved in binding, heterocyclic compound binding, and protein binding (Fig. 5.). GO analysis indicated that these TP-induced differentially expressed proteins exhibited a wide variety of cellular distributions and functions, consistent with the fact that TP has broad-spectrum anti-tumor effects.
Fig. 5.
GO enrichment analysis. An overview of the GO annotations of the 312 dys-regulated proteins with up to 10 significantly enriched terms in three categories: biological process (BP), cellular component (CC) and molecular function (MF). The cutoff of P-value was set to 0.05. Terms in the same category were ordered based on the P-values. Information for the percentages and numbers of involved genes/proteins in a term is provided on the left and right y-axes.
KEGG pathway analysis
KEGG analysis revealed 30 significant pathways with P<0.05 (Fig. 3B.). The top ten pathways, including Ribosome biogenesis in eukaryotes (hsa03008), Spliceosome (hsa03040), mRNA surveillance pathway (hsa03015), Carbon metabolism (hsa01200), Steroid biosynthesis (hsa00100), Cysteine and methionine metabolism (hsa00270), Propanoate metabolism (hsa00640), Glycolysis/Gluconeogenesis (hsa00010), Biosynthesis of amino acids (hsa01230), and Cardiac muscle contraction (hsa04260), were displayed. Ribosome biogenesis in eukaryotes and spliceosome were the most significantly enriched pathways (Fig. 6).
Fig. 6.
Distribution of enriched KEGG pathways. Columns refer to related pathways, colored with gradient colors from midnight blue (smaller P-value) to lighter blue (larger P-value).
Protein-protein interaction network analysis
To further examine the comprehensive information obtained from the identified protein data, the PPI network was analyzed. The network model was generated using the Cytoscape web application based on information gained in up to 4 levels of functional analysis: fold-change of gene/protein expression, protein-protein interactions, KEGG pathway enrichment and biological process enrichment. A merged network is shown in Fig. 7. Again, PPI analysis identified ribo-some biogenesis in eukaryotes and the spliceosome as the most significantly enriched pathways. In the network, the proteins indicated with red circle nodes were up-regulated, and the proteins indicated with green circle nodes were down-regulated. These data clearly show that most of the proteins were down-regulated in Ribo-some biogenesis in eukaryotes, Spliceosome, and mRNA surveillance pathways, while the dysregulated proteins in Cysteine and methionine metabolism, Propanoate metabolism and Glycolysis/Gluconeogenesis were up-regulated.
Fig. 7.
Protein-protein interaction (PPI) network. The PPI analysis was based on fold changes of protein expression, PPIs, and KEGG pathway and biological process enrichments. Circle nodes refer to genes/proteins. The rectangles refer to KEGG pathways or biological processes, colored with gradient colors from yellow (smaller P-value) to blue (larger P-value). Genes/proteins are colored in red (up-regulation) and green (down-regulation). A default confidence cutoff of 400 was used: interactions with higher confidence scores are shown as solid lines between genes/proteins or are otherwise indicated as dashed lines.
Evaluation of iTRAQ results using western blotting
Based on the results of the MS analysis, the expression levels of five dysregulated proteins were validated using western blotting in TP-treated or negative control cells. The expression levels of two proteins (MTA2 and EIF4A3) were significantly down-regulated (Fig. 8A), while the expression levels of the remaining three proteins (PHB, CDH1 and AIFM1) were markedly increased in TP-treated cells compared with the corresponding control (Fig. 8B), consistent with the results from the MS analysis. Therefore, the altered expression levels of 312 proteins were considered induced by TP.
Fig. 8.
Expression levels of the representative dysregulated proteins were verified using western blot analysis. (A) CDH1, AIFM1 and PHB are down-regulated proteins. (B) EIF4A3 and MTA2 are up-regulated proteins. β-actin was used as the loading control. Data are expressed as the means ± SD (n=3). *P<0.05 and **P<0.01 compared with the control group.
Discussion
TP has been widely investigated for its broad-spectrum anticancer activity. Many studies have shown that TP inhibits cell growth and induces apoptosis in various cancers, primarily through multiple mechanisms, including the suppression of various signaling pathways and proliferative and antiapoptotic factors in a given cell type and under specific conditions. TP has been reported to strongly inhibit the transcription of numerous pro-inflammatory mediators [25] and was also implicated as a potent inhibitor of NF-kappa B and a promoter of transcriptional arrest [26-30]. Recent studies have shown that TP inhibits RNA polymerase-mediated transcription by targeting transcription factors, leading to the down-regulation of certain mRNA molecules [31-33]. However, to our knowledge, there are no studies reporting the anti-proliferative and pro-apoptotic effects of TP against NSCLC cells at the proteomics level. In the present study, we attempted to investigate the potential protein targets of TP in a human NSCLC A549 lung adenocarcinoma cell line in vitro. First, we investigated the cytotoxicity of TP on A549 cells. TP strongly inhibited cell proliferation and induced cell apoptosis and cell cycle arrest in dose-dependent manners. Second, an iTRAQ-based proteomics method was employed to analyze the molecular targets of A549 cancer cells after TP treatment, and pathway and network analyses were performed. Proteomics analysis is a powerful tool for the identification of biological markers and estimation of biological networks [34]. A global view of the inter-connectivity of signaling proteins and their actions is critically important for successful lung cancer therapy [35] and should provide a comprehensive perspective for elucidating the roles of TP as a potential agent for treatment of NSCLC. We observed 312 differentially expressed proteins in A549 cells after TP treatment. Moreover, bioinformatics analysis revealed that these proteins were involved in many BPs, including ribosome biogenesis, RNA processing, ribonucleoprotein complex biogenesis, rRNA metabolic process, rRNA processing, ncRNA processing, cellular component biogenesis, and others. These proteins were implicated in 226 different KEGG pathways and associated with each other to form a network. The anticancer activity of TP against A549 cancer cells is mediated through its effects on multiple BPs and pathways, including ribosome biogenesis in eukaryotes, the spliceosome, mRNA surveillance pathway, PARP1/AIF pathway, metabolic pathway and other important molecular targets.
Ribosome biogenesis in eukaryotes and spliceosome and mRNA surveillance pathways are central processes for gene expression and protein synthesis, which are inextricably associated with cell growth and division. After TP treatment, most of the differentially expressed proteins involved in RNA metabolism pathways were significantly down-regulated. Among these down-regulated proteins, SNW1, HNRPM, EFTUD2, and SNRNP200 are components of the spliceosome. Many drugs have recently been demonstrated as inhibitors of RNA splicing, with cytotoxic effects on tumor cell lines [36]. SNW1 depletion induced apoptosis in breast cancer cells, and EFTUD2 knockdown also significantly promoted cellular apoptosis [37]. Previous studies have demonstrated that through the inhibition of the Akt signaling pathway, TP induces Bax- and Bcl-2-mediated mitochondrial apoptotic pathways, resulting in caspase-9- and caspase-3-triggered cell apoptosis [17, 38, 39]. In the present study, we identified key nuclear proteins and other mitochondrial proteins as down- or upstream targets of the Akt signaling pathway, such as REF1/Aly, GTPBP4, EIF4A3 and PHB. REF1/Aly, GTPBP4 and EIF4A3 are involved in RNA metabolism-related pathways. EIF4A3 (DDX48) is a core component of the exon junction complex (EJC) and plays a critical role in multiple posttranscriptional events, including RNA subcellular localization, nonsense-mediated decay (NMD), and translation [40]. The AKT signaling pathway regulates the assembly of the core EJC proteins eIF4A3, MAGOH, and Y14 into complexes at speckled domains, which is essential for mRNA export. AKT inhibition results in the disorder of mRNA export and gene expression [41]. REF1/Aly is a nuclear speckle protein implicated in mRNA export and is a physiological target of the nuclear Akt signaling cascade [42, 43]. The depletion of Aly markedly blocks cell cycle progression and reduces cell growth and mRNA export, and these processes are regulated by Akt phosphorylation [43, 44]. GTPBP4, located in the nucleus, is involved in the biosynthesis of the 60S subunit of the ribosome [45] and can be used as a molecular switch to control signal transduction pathways, protein synthesis and other biological processes. GTPBP4 down-regulation in colorectal cancer cell lines significantly inhibited cell proliferation [46]. GTPBP4 is closely associated with the MAPK signaling pathway and participates in the regulation of MAPK and Akt signaling pathways through interactions with AKT [47, 48]. It has also been reported that GTPBP4 binds to P53, and low GTPBP4 expression leads to the aggregation and activation of P53 proteins, which regulate the downstream apoptosis-related factors caspase-3, caspase-9, and PARP [49]. Prohibitin belongs to the Band-7 protein family and is widely present in different cellular compartments. Several studies using different organism models have provided strong evidence for critical biological roles of PHB in mitochondrial function, cell proliferation, and development. The contribution of PHB to cancer cell apoptosis may depend on the stimuli and cell type [50]. Recent studies have characterized PHB as a multifunctional protein involved in the PI3K/Akt and Ras/MAPK/ERK signaling pathways. A recent study in cancer cells showed that Akt phosphorylates PHB at Thr258. PHB could also indirectly facilitate crosstalk between the PI3K/Akt and Ras/MAPK/ERK pathways through interactions with their signaling intermediates. The emerging roles of PHB in the PI3K/Akt and Ras/ERK pathways highlight the importance of PHB in the crosstalk between signaling pathways. In the present study, PHB was up-regulated in the TP-induced apoptosis of NSCLC cells. We speculate that PHB may play an important role in the TP-induced apoptosis of A549 cells. Targeting PHB may have inspiring prospects in the future research of TP anti-tumor activity.
As described above, we speculated that TP-induced toxicities in lung cancer cells may be associated with the inhibition of RNA metabolism-related pathways, regulated by the Akt signaling pathway via important molecular target proteins. TP inhibits global ribosome biogenesis and splicing in cancer cells, which may explain the high potency of TP in killing lung cancer. Further studies are required to determine the potential link between the target proteins induced by TP and lung cancer and to provide a new strategy for cancer therapy.
Apoptosis-inducing factor 1 (AIFM1) is a mitochondrial flavoprotein with a critical role in programmed cell death. AIFM1 is a cell death executioner alternative to caspases [51]. Distinguishing from classic caspase-dependent apoptosis, the PARP1/AIF death cascade is a highly orchestrated and caspase-independent programmed cell death process termed parthanatos [52, 53]. In the present study, both AIF and PARP1 were up-regulated in NSCLC A549 cells after TP treatment, indicating that in addition to the classic caspase-dependent apoptosis pathway [17], the PARP1/AIF pathway may be another mechanism for TP to induce lung cancer cell apoptosis.
Unlike normal human cells, cancer cells display metabolic reprogramming to meet cell growth and proliferation needs [54]. Altered metabolic pathways in cancer cells may be attractive targets for anticancer therapy [55]. In the present study, some proteins related to metabolic pathways were dysregulated after TP treatment. The dysregulated proteins ECHS1, HADHA, PKM, AHCY and GOT2 are located in the mitochondria, and these enzymes are involved in apoptosis initiation and development. The mitochondrion is an important organelle with multiple functions, including ATP production, lipid metabolism, developmental processes and apoptosis regulation [56]. The expression levels of these proteins were enhanced during TP-induced apoptosis, suggesting that apoptosis is an active and energy-consuming procedure. These results demonstrated that energy metabolism is important in TP-induced apoptosis. Further research is required to determine the potential link between the altered mitochondrial enzymes induced by TP and NSCLC and to provide a new strategy for NSCLC therapy.
Metastasis is the ultimate cause of death for most cancer patients. TP has been reported as an inhibitor of lung cancer cell migration and metastasis, but its mechanism is not clearly defined [12, 57, 58]. We observed some other differentially expressed proteins, such as MTA2 and E-cadherin (CDH1), implicated in cancer cell migration. MTA2 is a member of the metastasis tumor-associated family of transcriptional regulators and acts as a central regulator of key gene expression pathways central to metastatic dissemination [59]. MTA2 knockdown in human cancer cells significantly inhibited migration and invasion [60]. E-cadherin is the core protein of the epithelial adherens junction. The loss of E-cadherin expression is a crucial step in the epithelial-mesenchymal transition (EMT) and is involved in cancer invasion and metastasis [61]. In human tumors, E-cadherin down-regulation is frequently associated with poor prognosis [62, 63]. Interestingly, MTA2 promotes NSCLC metastasis through E-cadherin inhibition [64]. In the present study, we observed that TP not only up-regulates E-cadherin but also down-regulates MTA2, which might be a new target of the TP-mediated inhibition of A549 cell migration.
In conclusion, TP showed significant cytotoxicity in human A549 lung cancer cells, induced cell apoptosis and blocked cell cycle arrest. Potential cytotoxicity mechanisms were explored using an iTRAQ-based proteomics approach. The results provided the first evidence that the broad-spectrum anti-tumor activity of TP in lung cancer cells may be associated with inhibition of RNA metabolism and protein synthesis. Among the large number of differentially expressed proteins identified, some proteins, which may be potential targets for lung cancer treatment in the future, were validated. The present study provides an effective platform for the anticancer activity of TP. However, the present study has several limitations. First, there is a lack of the same experiments on normal lung cells. Second, protein profile changes in normal lung cells in response to TP may better reveal the specificity of TP effects on cancer cells. Moreover, the in vivo activity, clinical application, and other mechanisms of TP against NSCLC require further investigation.
Abbreviations
TP (triptolide); PNCA-1 (pancreatic cancer cells); NSCLC (non-small cell lung cancer); iTRAQ (isobaric tags for relative and absolute quantitation); NanoLC-MS/MS (nano liquid chromatography-mass spectrometry); FBS (fetal bovine serum); DMSO (dimethylsulfoxide); BCA (bicinchoninic acid); PI (propidium iodide); PMSF (phenylmethanesulfonyl fluoride); BP (biological process); CC (cellular component); KEGG (Kyoto Encyclopedia of Genes and Genomes); MF (molecular function); SDS-PAGE (sodium dodecyl sulfate-polyacrylamide gel electrophoresis); PVDF (polyvinylidene fluoride); GO (Gene Ontology); HP-RP (high-pH reverse phase); CE (collision energy); FDR (false discovery rate).
Acknowledgements
This study was financially supported by grants from the Science Foundation from the Science and Technology Project of Zhejiang Province (2014F10014) and the Natural Science Foundation of Zhejiang Province (Q17H290005). This study was also supported by National Science Foundation of China (No. 81774026).
Disclosure Statement
No conflicts of interest exist in the submission of this manuscript, and this manuscript was approved by all authors for publication.
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