Abstract
Laryngeal carcinoma is one of the common malignancies of head and neck. However, the pathogenesis of laryngeal cancer has been not completely clear. To identify the effects of hypoxia on the invasion, metastasis, and metabolism of laryngeal carcinoma, iTRAQ-labeling-with-LC-MS/MS analysis was performed to identify differentially expressed proteins of the SCC10A cells under hypoxia and normoxia, while metabolites were examined by metabolic profiling. 155 proteins and 180 metabolites were identified and the PCK2 protein was selected for validation by Western Blotting. Immunohistochemistry (IHC) was performed to analyze the expression of PCK2 in formalin-fixed paraffin-embedded (FFPE) tissue sections, including laryngeal squamous cell carcinoma tissues from various stages. Collectively, we report that down-regulation of PCK2 inhibits the invasion, migration, and proliferation of laryngeal cancer under hypoxia and down-regulation of PCK2 may be used as a new strategy for laryngeal cancer therapy.
Keywords: Laryngeal cancer, hypoxia, PCK2, invasion, metastasis
Introduction
Laryngeal cancer is one of the frequently occurring malignancies among head and neck squamous cell carcinoma, which is common among males [1]. The incidence of laryngeal cancer has been increasing in the recent years [2]. The majority of laryngeal cancer is laryngeal squamous cell carcinoma [3,4] of which genetic and environmental factors are considered as the main cause of laryngeal cancer [5]. Although great progress has been made in the diagnosis and treatment of laryngeal cancer, 30-40% patients still die of tumor metastasis [6]. Hypoxia activates transcription factors that regulate cell survival, angiogenesis, and metastasis to promote tumor progression [7,8]. Therefore, it is highly important to understand the role of hypoxia in laryngeal cancer.
Compared with normal tissue, the unlimited proliferation of tumor cells would lead to increased oxygen consumption, for the reason that most solid tumors have hypoxia regions [9]. Thus, hypoxia is a hallmark of solid tumors [10], which promotes tumor cell invasion and metastasis [11]. Under hypoxia, glycolysis is upregulated [12] and lactate level increases in cells [13]. This glucose metabolism is an important characteristics of solid tumors that mainly initiated from GLUT-1. Aerobic glycolysis, also termed the “Warburg Effect”, is significantly accelerated in tumors [14], and glucose concentration is decreased, resulting in hypoglycemia in the tumor cells [15]. Tumor cells with limited glucose intake rely on mitochondrial oxidative phosphorylation to maintain cell proliferation [14].
To investigate the possible effects of hypoxia on laryngeal cancer, proteomic profiling was performed in this study to identify differentially expressed proteins under hypoxia and normoxia in laryngeal cancer SCC10A cells. A differentially expressed protein PCK2 was selected for further validation. Furthermore, the present study aims to dissect the effects of PCK2 in invasion, migration, and proliferation of laryngeal cancer, the relationship between PCK2 and cancer cell metabolism, and the association between PCK2 expression and clinical characteristics of laryngeal cancer patients.
Materials and methods
Reagents and antibodies
The following antibodies were used: GLUT1 (Proteintech, China, 21829-1-AP), PCK2 (Proteintech, China, 14892-1-AP), and β-actin (Biosharp, China, BL005B). Anti-mouse and anti-rabbit secondary antibodies, conjugated to horseradish peroxidase for Western blotting, were obtained from Licor.
Cell culture
Human laryngeal cancer cell line, SCC10A, was maintained in Dulbecco’s modified Eagle’s medium (DMEM, Gibco; Thermo Fisher Scientic, Inc), supplemented with 10% fetal bovine serum (Gibco; Thermo Fisher Scientic, Inc), 100 U/ml penicillin and 100 μg/ml streptomycin (Gibco; Thermo Fisher Scientic, Inc). Cells were cultured in an incubator at 37°C with 5% CO2 (Eppendorf, GER). To mimic hypoxia, cells were cultured in cobalt chloride hexahedron (CoCl2·6H2O, Aladdin) [16,17], which was dissolved in DMEM as a 2,000x concentrate and was diluted to 200 µM for experiments [18]. The cells were cultured for 12 h with CoCl2 before cells were collected.
TMT/iTRAQ labeling
After cell harvest, four volumes of lysis buffer (8M urea, 1% protease inhibitor, 3 μM TSA, 50 mM NAM and 2 mM EDTA) were added to the cells and the cells were sonicated. Cell debris were removed by centrifugation at 12,000 g at 4°C for 10 min. Then, the supernatant was transferred to a new centrifuge tube. The protein concentration was determined with a BCA kit (Bio-Rad Laboratories, Hercules, CA) according to the manufacturer’s instructions. The protein solution was added to 5 mM dithiothreitol for 30 min at 56°C and alkylated with 11 mM iodoacetamide for 15 min at room temperature in darkness. The protein samples were then diluted by adding 100 mM TEAB to urea concentration less than 2M. Finally, trypsin was added at 1:50 trypsin-to-protein mass ratio for the first digestion overnight and 1:100 trypsin-to-protein mass ratio for a second 4 h-digestion.
After trypsin digestion, peptides were desalted by Strata X C18 SPE column (Phenomenex) and vacuum-dried. Peptides were reconstituted in 0.5 M TEAB and processed according to the manufacturer’ s protocol for TMT kit/iTRAQ kit. Briefly, one unit of TMT/iTRAQ reagent was thawed and reconstituted in acetonitrile. The peptide mixtures were then incubated for 2 h at room temperature and pooled, desalted and dried by vacuum centrifugation.
LC-MS/MS analysis
The tryptic peptides were dissolved in 0.1% formic acid (solvent A), directly loaded onto a home-made reversed-phase analytical column (15-cm length, 75 μm inner diameter). The gradient was comprised of an increase from 6% to 23% solvent B (0.1% formic acid in 98% acetonitrile) over 26 min, 23% to 35% in 8 min and climbing to 80% in 3 min then holding at 80% for the last 3 min, all at a constant flow rate of 0.4 μL/min on an EASY-nLC 1000 UPLC system.
The peptides were subjected to NSI source followed by tandem mass spectrometry (MS/MS) in Q ExactiveTM Plus (Thermo) coupled online to the UPLC. The electrospray voltage applied was 2.0 kV. The m/z scan range was 350 to 1800 for full scan, and intact peptides were detected in the Orbitrap at a resolution of 70,000. Peptides were then selected for MS/MS using NCE setting as 28 and the fragments were detected in the Orbitrap at a resolution of 17,500. A data-dependent procedure that alternated between one MS scan followed by 20 MS/MS scans with 15.0s dynamic exclusion. Automatic gain control (AGC) was set at 5E4. Fixed first mass was set as 100 m/z.
Bioinformatic analysis
Gene Ontology (GO) annotation of the proteome was derived from the UniProt-GOA database (www.http://www.ebi.ac.uk/GOA/). The InterProScan software was used to annotate protein’s GO functional based on protein sequence alignment method for some proteins that were not annotated by UniProt-GOA database. KEGG online service tools KAAS (https://www.genome.jp/tools/kaas/) was used to annotate proteins’ KEGG database description and KEGG online service tools KEGG mapper was used to map the annotation results on the KEGG pathway database. The GO and the KEGG Pathway with a corrected P < 0.05 are considered significant. Hierarchical clustering was performed on the differentially expressed proteins in laryngeal cancer that was visualized by a heatmap, which used the heatmap.2 function from the plots R-package.
Cells sample preparation and analysis by gas chromatography-time-of-flight mass spectrometry (GC-TOFMS)
The sample preparation procedure was previously described by Qiu et al [19] and Wang et al [20]. Briefly, frozen cell samples were harvested and stored in an Eppendorf SafeLock microcentrifuge tube, mixed with 25 mg of pre-chilled zironium oxide beads and 10 μL of internal standard. Each aliquot of 50 μL of 50% pre-chilled methanol was added for automated homogenization (BB24, Next Advance, Inc., Averill Park, NY, USA). After centrifugation at 14,000 g and 4°C for 20 min (Microfuge 20R, Beckman Coulter, Inc, Indianapolis, IN, USA), the supernatant was carefully transferred to an autosampler vial (Agilent Technologies, Foster City, CA, USA). Each aliquot of 175 μL of pre-chilled methanol/chloroform (v/v = 3/1) was added to the residue for the second extraction. After centrifugation at 14,000 g and 4°C for 20 min, each 200 μL of the supernatant was carefully transferred to an autosampler vial. The remaining supernatant from each sample was pooled to make quality control samples. All the samples in autosampler vials were evaporated briefly to remove chloroform using a CentriVap vacuum concentrator (Labconco, Kansas City, MO, USA), and further lyophilized with a FreeZone freeze dryer equipped with a stopping tray dryer (Labconco, Kansas City, MO, USA).
The sample dericatization and injection were performed by a robotic multipurpose sample MPS2 with dual heads (Gerstel, Muehlheim, Germany). Briefly, the dried sample was derivatized with 50 μL of methoxyamine (20 mg/mL in pyridine) at 30°C for 2 h, followed by the addition of 50 μL of MSTFA (1% TMCS) containing FAMEs as retention indices at 37.5°C for another 1 h using the sample preparation head. In parallel, the derivatized samples were injected with sample injection head after dericatization.
Each 1 µL aliquot of the derivatized solution was injected in splitless mode into an Agilent 7890N gas chromatography and a Gerstel multipurpose sample MPS2 with dual heads, which were coupled with a time-of-flight mass spectrometry (GC-TOFMS) system (Pegasus HT, Leco Corporation, St. Joseph, MO, USA). The laryngeal cancer and control samples were run in the order of “control-LC-control”, alternately, to minimize systematic analytical deviations. A Rxi-5 ms capillary column (30 m × 250 µm i.d., 0.25 µm film thickness; Restek corporation, Bellefonnte, PA, USA) was used for separation. Helium was used as the carrier gas at a constant flow rate of 1.0 mL/min. The temperature of injection and transfer interface were both set to 270°C. The GC temperature programming was set to 2 min isothermal heating at 80°C, followed by 12°C/min oven temperature ramps to 300°C, 4.5 min maintenance at 300°C, 40°C/min to 320°C, and a final 1 min maintenance at 320°C. Electron impact ionization (70 eV) in the full scan mode (m/z 50-500) was used, with an acquisition rate of 25 spectra/s in the TOFMS setting.
GC-TOFMS data analysis
The raw data generated by GC were processed using Xplore for automated baseline denosing and smoothing, peak picking and deconvultion, creating reference database from the pooled QC samples, metabolite signal alignment, missing value correvtion and imputation, and QC correction. The resulting data were normalized to internal standards and the sum of cell samples before statistical analysis. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed with statistical analysis software packages in R studio (http://cran.r-project.org/). The default 7-fold cross-validation was applied to guard against overfitting. The variable importance in the projection (VIP) values (VIP > 1.0) is considered to be differentiating variables [21]. T-test is used to determine whether the two sets of data are significantly different or not. The p-value gives the amount evidence that the two sets of data are different through the t-statistic. A conservative nonparametric method, U-test, was also used to test the significance of the two sets of data. Fold change was calculated by the ratio of means or medians between the pairwise comparisons using T-test or U-test, respectively. The calculated fold change of 1.5 or p-value of 0.05 is chosen for statistical significance. The V-plot that integrated the fold change and p-values was used for depiction the (of the) significantly different metabolites.
Western blotting
Cultured cells were harvested in lysis buffer, and protein concentration was determined by a BCA protein assay kit. Proteins separated by SDS-PAGE, and transferred to PVDF membranes. Blots were blocked with 5% fat-free milk for 1 h at temperature and incubated with primary antibodies overnight at 4°C. The membranes were incubated with secondary antibody (1:1500) and the signal was visualized with ECL detection reagent. β-actin was simultaneously detected using rabbit anti-β-actin antibody as a loading control.
Transfection
For RNA interference analysis, small interfering RNA (siRNA) targeting human PCK2 (Ribobio, China) were (was) delivered into SCC10A cells using Lipofectamine 2000 reagent (Thermo Fisher Scientific) according to the manufacturer’s protocol. In addition, the non-targeting siRNA pool (Ribobio, China) was used at the same concentration of 100 nM as a control for the RNA interference assays. Four hours following transfection, the medium was replaced with DMEM containing 10% FBS and the cells were cultured for 44 hours. At the end of the transfection, cells were subjected to migration and invasion assays as described below and protein expression was determined by Western Blotting analysis.
Migration and invasion assays
In the transwell migration assay, as previously described [22,23], the upper chamber of the 24-well transwell with 8µm pore size (Corning Incorporated), 1 × 105 cells in serum-free DMEM were added. 500 µl DMEM was added in the bottom chambers and analyzed after 6 h at 37°C. The insert was fixed with 4% paraformaldehyde for 15 min and stained with 0.1% crystal violet for 30 min at 37°C. Non-migrating cells retained on the upper side were removed by wiping with a cotton swab. Cells that had migrated through the filter were counted and averaged from 3 randomly selected microscopic fields (20 × objective).
In vitro invasion assays, the upper chambers were precoated with Matrigel (BD) and maintained at 37°C and 5% CO2 for 1 h. Cells (1 × 105) in 200 μL of serum-free DMEM were added on the top of the transwell. Serum-free medium was then added to the lower chamber and incubated for 24 h at 37°C. Cells were fixed and stained with 0.1% crystal violet, Matrigel and associated cells were removed with a cotton swab. Cells that had penetrated the Matrigel and had reached the underside of the filter membrane were then counted and averaged from 3 randomly selected microscopic fields (20 × objective).
MTT assay
The proliferation capacity of three groups cells (control, empty vector and PCK2 transfected) was measured by 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyltetrazolium bromide (MTT) assay. Cells (approximately 5 × 103) were grew into 96-well plates for 24 h, 48 h, and 72 h. Then 20 μL MTT (5 mg/mL) was added to the cells for 4h at 37°C. Before measured, 150 μL DMSO was added for 20 min at room temperature on the horizontal shaker. The optical density was measured with a microplate reader (Bio-Rad) at a wavelength of 490 nm. The inhibition rate (IR) of transfected SCC10A cells was calculated as follows: IR = (1-OD treated/OD untreated) × 100%.
ATP measurement
The content of ATP was assayed using the ATP Assay Kit (Jiancheng Bio Ins, China) according to manufacturers’ manual. Briefly, the cells were digested, centrifuged, and the supernatant was discarded. 300-500 μL distilled water was added before the homogenate was centrifuged in hot water bath at 90-100°C, and heated in water bath for 10 min, then extracted and mixed for 1 min. 30 μL 1 mol/L standard solution was added to the blank tube and the standard tube, 30 μL sample solution was added to the measuring tube and the control tube, the working solution was added to the 4 tubes in a 37°C water bath for 30 min. The mixture was centrifuged at 4000 rpm for 5 min after 50 μL of precipitant was added. 300 μL supernatant was taken for measurement each tube. 500 μL coloring solution and 500 μL terminator was added in sequence, mixed and stand for 5 minutes at room temperature each time. The optical density was measured with a microplate reader (Mapada) at a wavelength of 636 nm, repeated for three times. The ATP concentration in the cells was calculated as follows: ATP concentration (μmol/gprot) = (OD measure - OD control)/(OD standard-OD blank) × standard concentration (1 × 103 μmol/L) × sample dilution factor before determination/sample protein concentration.
Glucose measurement
The glucose uptake was measured using a Glucose Assay Kit (Solarbio). The assay was performed according to manufacturers’ manual. Briefly, two groups of cells (cells in hypoxia and cells in normoxia) were digested, centrifuged, and the supernatant was discarded. 1 mL distilled water was added to 5 × 105 cells. Cells were ultrasonically disrupted, and kept in a water bath for 10 minutes at 95°C. After cooling, cells were centrifuged at 8000 rpm for 10 min at 25°C and the supernatant was collected. Working reaction mixture was prepared by mixing reagent two and reagent three at 1:1. 20 μL distilled water, 20 μL reagent one and 20 μL sample were added into blank tube, standard tube, and measuring tube respectively. The reactions were initiated by the addition of 180 µL of working reaction mixture. The optical density was measured with a microplate reader (Mapada) at a wavelength of 505 nm after incubation at 37°C for 15 minutes. The glucose concentration in the cells was calculated as follows: glucose concentration (μmol/104 cell) = 0.001 × (OD measure - OD blank)/(OD standard - OD blank).
Tissue samples
Fifty-two laryngeal cancer tissue samples were collected from patients in the Second Affiliated Hospital of University of South China from May 2012 to December 2013. The patients have not received any treatment before surgery. Fifty-two normal tissue samples were obtained from the Third Affiliated Hospital of University of South China as controls. Tumor stage was defined according to the sixth edition of Laryngeal Cancer Staging International Standards that revised by UICC in 2002. The informed consent to the study was signed by all the patients, which was approved by the University of South China Ethical Committee.
Immunohistochemistry
Immunohistochemistry (IHC) analysis of GLUT-1 and PCK2 was carried out in FFPE tissue sections using the standard immunohistochemical technique as we previously reported [24].
Statistical analysis
Statistical analysis was performed by using SPSS 17.0. Data were processed by the GraphPad Prism 5.0 software, and expressed as the mean ± standard deviation. ANOVA was used in multiple comparisons, and student’s t-test was performed between two groups. The Chi-square test was used to analyze the relationship between GLUT-1 and PCK2 expression and clinical pathological characteristics in laryngeal cancer. The relationship between GLUT-1 and PCK2 protein was analyzed by Spearman correlation test. P < 0.05 was considered as significant.
Results
Identification of differentially expressed proteins of laryngeal cancer under hypoxia
To identify differentially expressed proteins in the laryngeal cancer cells under hypoxia, proteomic profiles of SCC10A cells cultured with or without CoCl2 was compared using iTRAQ labeling and LC-MS/MS. CoCl2 treatment is well-known to be able to induce cellular hypoxic responses and thus, was used to mimic hypoxia [25]. Proteins that consistently showed an average fold change ≥ 1.5 or ≤ 0.667 in the triplicate experiments between these two conditions were considered as differentially expressed (t test, P < 0.05). As a result, 155 proteins were identified (Supplementary Table 1).
To understand the biological significance of these differentially expressed proteins of laryngeal cancer with or without CoCl2 treatment, GO and KEGG Pathway analysis was performed. Both GO and KEGG analysis results were consistent, identifying similar pathways that were changed when cells were cultured with CoCl2, especially the MAPK, AMPK, and metabolic pathways (Figure 1). Hierarchical clustering analysis was performed on significantly up-regulated or down-regulated proteins based on GO enrichment and KEGG pathway analysis. The results indicated that proteins with functions on negative regulation of cell death, gene transcription, MAPK activity, and metabolism were enriched in samples treated with CoCl2 and proteins with functions on oxidative phosphorylation and membranes were enriched in samples without CoCl2 treatment (Supplementary Figure 1). These results are consistent with what we have known for biological changes cells usually make under hypoxic stress, lending strong support to the strategy of our study.
Figure 1.
Gene Ontology and KEGG pathways analysis of 155 differentially expressed proteins. A. Enrichment of Gene Ontology analysis of the upregulated proteins. B. Enrichment of Gene Ontology analysis of the downregulated proteins. C. Significant KEGG pathways analysis of upregulated proteins. D. Significant KEGG pathways analysis of downregulated proteins. The p-value thresholds in the corresponding Gene Ontology and KEGG pathways are shown.
Metabolomics analysis of laryngeal cancer in hypoxia
In order to further understand metabolic changes that cells make under hypoxia, we compared metabolite profiles of the SCC10A cells cultured with or without CoCl2 using GC-TOFMS. The OPLSDA model was applied to the data analysis and the scores plot showed two distinct clusters (with or without CoCl2) apart from each other (Figure 2A), demonstrating a distinct metabolite profiles between these two groups of cells. A V-plot model was used to select metabolites that were differentially produced in cells with or without CoCl2 (Figure 2B). The metabolic pathway enrichment analysis results are summarized in Table 1 and Figure 2C. The top-ranked metabolites from the univariate statistical analysis are illustrated in Supplementary Figure 2.
Figure 2.
Identification of differentially produced metabolites from the SCC10A cells cultured with or without CoCl2 by GC-TOFMS. A. OPLS-DA scores plots of differentially expressed metabolites in the SCC10A cells culture without CoCl2 (representing normoxia) or with CoCl2 (representing hypoxia). B. V-plots of differentially produced metabolites in the SCC10A cells cultured with or without CoCl2. C. Summaries of the Metabolic Pathway Enrichment Analysis results.
Table 1.
Differentially regulated metabolic pathways when the SCC10A cells were cultured with CoCl2
| Pathway Name | P. hyper | Impact | Up | Down |
|---|---|---|---|---|
| Arginine biosynthesis | 3.25e-03 | 0.19 | Fumaric acid; Oxoglutaric acid; Ornithine | L-Glutamine |
| Alanine, aspartate and glutamate metabolism | 8.73e-03 | 0.26 | Gamma-Aminobutyric acid; Fumaric acid; Oxoglutaric acid; NAcetyl-L-aspartic acid | L-Glutamine |
| Phenylalanine, tyrosine and tryptophan biosynthesis | 1.25e-02 | 0.50 | 4-Hydroxyphenylpyruvic acid | L-Phenylalanine |
| D-Glutamine and D-glutamate metabolism | 2.02e-02 | 0.33 | Oxoglutaric acid | L-Glutamine |
| Galactose metabolism | 3.57e-02 | 0.09 | D-Galactose; D-Mannose; Alpha-Lactose; Sorbitol | |
| Glutathione metabolism | 4.02e-02 | 0.11 | Glycine; Ornithine; L-Cysteine; Putrescine | |
| Glycine, serine and threonine metabolism | 0.067 | 0.28 | Dimethylglycine; Glycine; Glyceric acid; L-Cysteine | |
| Pentose phosphate pathway | 0.083 | 0.10 | Glyceric acid; Gluconolactone; D-Ribose | |
| Purine metabolism | 0.093 | 0.09 | Guanine; Guanosine; Inosine; Xanthine | Adenine; L-Glutamine |
| Amino sugar and nucleotide sugar metabolism | 0.094 | 0.10 | D-Galactose; D-Mannose; D-Fructose | Fructose 6-phosphate |
The biological functions of PCK2 in laryngeal cancer
Among these differentially expressed proteins, PCK2 showed significant changes at the presence of CoCl2 (Supplementary Figure 3). Western blotting was used to validate PCK2 proteomic profiling results. Indeed, expression of PCK2 was increased in SCC10A cells when cultured with CoCl2 (Figure 3A).
Figure 3.
Characterization of PCK2 function. A. PCK2 was induced when the SCC10A cells were cultured with CoCl2. B. siRNA effectively downregulates PCK2 expression. C. Representative images of cell invasion assay following PCK2 knockdown by siRNAs. D. Quantification of the number of cells in the invasion assay that migrated through the transwell membranes by counting at least three random microscopic fields. E. Representative images of cell migration assay following PCK2 knockdown by siRNAs. F. Quantification of the number of cells in the migration assay that migrated through the transwell membranes by counting at least three random microscopic fields. Error bars indicate standard deviation. Student’s t-test was performed for statistical analysis, *P < 0.05.
To investigate the role of PCK2 function, invasion, migration, and proliferation of SCC10A cells were examined when PCK2 is down-regulated by an siRNA (Figure 3B). Invasion and migration of SCC10A cells was markedly decreased after PCK2 was knocked down (Figure 3C-F). MTT assay was performed to examine the effect of PCK2 on SCC10A cell proliferation. SCC10A cell proliferation was markedly decreased following PCK2 knockdown compared to that of control cells (Table 2). Together, these results indicated that down-regulation of PCK2 decreased the invasion, migration and proliferation of laryngeal cancer SCC10A cells.
Table 2.
OD value and IR of the SCC10A cells following PCK2 knockdown (x̅ ± s, n = 3)
| Time (h) | Control | Empty vector | PCK2-transfected | IR (%) |
|---|---|---|---|---|
| 24 | 0.724±0.141 | 0.752±0.123 | 0.611±0.018 | 23.08 |
| 48 | 1.091±0.213 | 1.066±0.218 | 0.684±0.024 | 35.83 |
| 72 | 1.254±0.341 | 1.239±0.154 | 0.772±0.025 | 36.07 |
Since metabolic pathway was significantly altered in the SCC10A cells treated with CoCl2, we examined whether cellular glucose uptake and ATP generation reflect these changes. As expected, glucose uptake and ATP content of SCC10A cells increased when cultured with CoCl2 (Figure 4A, 4B). Conversely, the glucose content and ATP generation in the SCC10A cells decreased when PCK2 is knocked down (Figure 4C, 4D), suggesting that PCK2 plays a role in glycolysis in the SCC10A cells.
Figure 4.
PCK2 regulates SCC10A cell metabolism. A. Glucose uptake of the SCC10A cells when cultured with or without CoCl2. B. ATP content in the SCC10A cells when cultured with or without CoCl2. C. Glucose uptake changes in the SCC10A cells when PCK2 is down-regulated by siRNAs. D. Cellular ATP content changes in SCC10A cells when PCK2 is down-regulated by siRNAs. Error bars indicate standard deviation. Student’s t-test was performed for statistical analysis, *P < 0.05.
GLUT-1 and PCK2 are highly expressed in laryngeal cancer
To determine whether there is a direct link between tumor hypoxia and PCK2, the expression of GLUT-1 (a well-known surrogate marker for tumor hypoxia) and PCK2 was examined by IHC in normal laryngeal squamous epithelial tissues and laryngeal squamous cell carcinoma tissues. Interestingly, expression of both GLUT-1 and PCK2 is low in normal tissues but much higher in laryngeal cancer tissues (P < 0.05) (Figure 5). Specifically, 11.53% (6/52) and 9.61% (5/52) of normal laryngeal squamous epithelial tissues were stained positive for GLUT-1 and PCK2, respectively. However, 84.61% (44/52) and 82.69% (43/52) of laryngeal squamous cell carcinoma tissues were stained positive for GLUT-1 and PCK2, respectively. Thus, a significant difference of expression was detected between normal tissues and carcinoma tissues for both proteins (P < 0.05) (Table 3).
Figure 5.
Immunohistochemistry analysis of GLUT-1 and PCK2 expression in normal laryngeal squamous epithelial tissues (Normal) and laryngeal squamous carcinoma tissues (LC). Original magnification, 10 × 40.
Table 3.
Expression of GLUT-1 and PCK2 in normal laryngeal squamous epithelial tissues and laryngeal squamous cell carcinoma tissues
| Group | n | GLUT-1 | PCK2 | ||||
|---|---|---|---|---|---|---|---|
|
|
|
||||||
| + | - | P | + | - | P | ||
| Normal | 52 | 6 | 46 | < 0.05 | 5 | 47 | < 0.05 |
| Carcinoma | 52 | 44 | 8 | 43 | 9 | ||
Expression of GLUT-1 and PCK2 in laryngeal cancer tissue is not related to sex, age, tissue type, and anatomical type of the patients (P > 0.05), but it is associated with clinical stage and lymph node metastasis (P < 0.05) (Table 4). In addition, there is a positive correlation between the expression of GLUT-1 and PCK2 in laryngeal squamous cell carcinoma by Spearman correlation (P < 0.05) (Table 5).
Table 4.
The correlation between clinical characteristics and expression of GLUT-1 and PCK2 in laryngeal squamous cell carcinoma tissues
| Factor | n | GLUT-1 | P | r | PCK2 | P | r | ||
|---|---|---|---|---|---|---|---|---|---|
|
|
|
||||||||
| + | - | + | - | ||||||
| Sex | |||||||||
| Male | 42 | 36 | 6 | 0.653 | 0.062 | 36 | 6 | 0.238 | 0.164 |
| Female | 10 | 8 | 2 | 7 | 3 | ||||
| Age | |||||||||
| ≥ 60 years | 25 | 22 | 3 | 0.515 | 0.900 | 23 | 2 | 0.088 | 0.237 |
| < 60 years | 27 | 22 | 5 | 20 | 7 | ||||
| Tissue type | |||||||||
| High-middle differentiation | 31 | 26 | 5 | 0.857 | -0.250 | 25 | 6 | 0.635 | -0.660 |
| Poor differentiation | 21 | 18 | 3 | 18 | 3 | ||||
| Anatomical type | |||||||||
| Supraglottic and subglottic | 25 | 21 | 4 | 0.906 | -0.016 | 20 | 5 | 0.621 | -0.068 |
| Glottic | 27 | 23 | 4 | 23 | 4 | ||||
| Clinical stage | |||||||||
| I | 19 | 13 | 6 | 0.014 | 0.341 | 12 | 7 | 0.005 | 0.392 |
| II-IV | 33 | 31 | 2 | 31 | 2 | ||||
| Lymph node metastasis | |||||||||
| Yes | 28 | 27 | 1 | 0.011 | 0.354 | 27 | 1 | 0.005 | 0.392 |
| No | 24 | 17 | 7 | 16 | 8 | ||||
Table 5.
The correlation between GLUT-1 and PCK2 expression in laryngeal squamous cell carcinoma
| GLUT-1 | PCK2 | |||
|---|---|---|---|---|
|
| ||||
| + | - | P | r | |
| + | 39 | 5 | 0.007 | 0.368 |
| - | 4 | 4 | ||
Discussion
Laryngeal cancer is one of most common malignancies of head and neck. The majority of laryngeal cancer patients are middle-aged or old male [26]. In recent years, the number of female patients has been increasing [1]. Therefore, it is important to diagnose and treat laryngeal cancer at early stages [27,28]. Currently, the combination of surgery and radiotherapy is the main treatment option for most laryngeal cancer patients [29]. Although the multidisciplinary treatment model has been applied in the treatment of laryngeal cancer, the effect remains far from satisfactory. Previous studies have indicated that hypoxia promotes invasion and metastasis of tumor cells, however, the role of hypoxia in laryngeal cancer remains unknown.
Our study identified 155 differentially expressed proteins and 39 differentially generated metabolites from laryngeal cancer SCC10A cells cultured with CoCl2, a molecule that mimics many aspects of hypoxia effects on cells. Among the metabolites, D-Allose is a rare sugar which showed promising anti-proliferative and pro-apoptotic activity in cancer cell [30]. Clear cell renal cell carcinoma, a unique cancer type with constitutive activation of the HIF-1α pathway due to frequent mutation of the von Hippel Lindau gene (VHL), is metabolically distinct from clear cell papillary renal cell carcinoma, primarily by high-level metabolites from the sorbitol metabolic pathway [31]. Sorbitol induces the expression of HIF-1α protein in three renal carcinoma cell lines, a new mechanism of HIF pathway activation in clear cell papillary renal cell carcinoma [31]. Many other identified metabolites have distinct functions along the hypoxia signaling pathways, such as malic acid, putrescine, xanthine oxidase-derived reactive oxygen species, and 2-oxoglutarate [32-35], but the majority of identified metabolites from this study have not been associated with the hypoxia pathway. Future study is warranted to elucidate their roles in cells under hypoxic stress.
Phosphoenolpyruvate carboxykinase (PEPCK), a key enzyme in the metabolic pathway of gluconeogenesis, converts oxaloacetate into phosphoen-olpyruvate [36]. PCK2, an isozyme of PEPCK, processes lactic acid that is continuously produced by red blood cells in the liver and kidney. PCK2 can regulate pancreatic neuroendocrine tumor cell proliferation by regulating glycolysis and mitochondrial oxidative phosphorylation, playing an important role in the adaptation of tumor cells to low glucose environments [37]. In tumor-repopulating cells of melanoma, PCK2 was down-regulated to promote the decomposition of citrate, which weakens the carbon flow in the tricarboxylic acid cycle, resulting in reduced oxidative phosphorylation [38]. PCK2 is frequently up-regulated in breast, colon, lung, prostate, thyroid, bladder, and kidney cancer cells [40-42]. However, the role of PCK2 in laryngeal cancer remains unclear.
In the current study, we have demonstrated that PCK2 is highly expressed in laryngeal cancer SCC10A cells and down-regulation of PCK2 inhibits the invasion and migration of laryngeal cancer cells, which are consistent with previous studies [29,36,43]. In the liver, there is the increased conversion of pyruvate to lactate in hypoxia, which can subsequently be converted to glucose by the gluconeogenesis, while the key enzyme of the pathway PCK2 was up-regulated in the liver [44], so the content of glucose and ATP increases with increased gluconeogenesis, which was consistent with the study that the glucose and ATP content in SCC10A cells were increased in hypoxia. PCK2 is in a unique position of cellular metabolism and plays a key role in the gluconeogenesis pathway by converting lactate to glucose in the liver [36,44]. Down-regulation of PCK2 would weaken the gluconeogenesis pathway, leading to lactic acid accumulation and reduced glucose level, just as our data demonstrated.
We have shown that PCK2 is highly expressed in laryngeal squamous cell carcinoma and is positively associated with clinical stages and lymph node metastasis. GLUT-1 is also highly expressed in laryngeal squamous cell carcinoma, consistent with a previous report [45]. Interestingly, we demonstrated a positive correlation between the expression of GLUT-1 and PCK2. Given that GLUT-1 is a marker of hypoxia [24,46], our results suggest that PCK2 may also be involved in the hypoxic pathway. However, the mechanisms of PCK2 in tumor hypoxia and laryngeal cancer tumorigenesis remain unclear and warrant further study.
In conclusion, our findings provided the evidence that down-regulation of PCK2 inhibits the invasion, migration, and proliferation of laryngeal cancer, suggesting that PCK2 plays an important role in tumorigenesis and progression of laryngeal cancer. In addition, the expression of PCK2 and GLUT-1 was positively correlated in laryngeal cancer. Given the critical role that tumor hypoxia plays in the prognosis of solid tumors, our data suggest PCK2 as a potential prognostic factor in laryngeal cancer patients. Taken together, our study provided evidence to suggest that targeting PCK2 may be a new therapeutic strategy for laryngeal cancer treatment.
Acknowledgements
This study was supported by the National Natural Science Foundation of China (no. 81272960), the Key Research Program from the Science and Technology Department of Hunan Province, China (no. 2017SK2082) and the Key Research Program from the Science and Technology Department of Ningxia Hui Autonomous Region, China (no. 2019BFH02012), the Key Research Program of Hunan Health Committee (20201909) and the program of Hengyang science and Technology Bureau (2017-1, 2020-67).
Disclosure of conflict of interest
None.
Supporting Information
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