1. Introduction
Gastric cancer (GC) is the fifth most frequently diagnosed cancer and the third leading cause of cancer-related deaths worldwide, with over 1,000,000 new gastric cancer cases in 2018 and an estimated 783,000 related deaths [
1,
2]. Radical surgery and chemotherapy remain the main treatments. Although screening for early GC has improved overall survival rates, the prognosis of GC remains poor compared to that of other solid tumors [
3] because most GC patients are still diagnosed at an advanced stage with either regional, distant or both, metastasis [
2], which undermines treatment effectiveness. Hence, it is necessary to reveal the molecular mechanisms underlying the carcinogenesis and progression of GC and find suitable metastasis predictors or therapeutic targets to improve its prognosis.
The A Disintegrin and Metalloproteinase with Thrombospondin motifs (ADAMTS) family comprises 19 members [
4]. Aberrant expression or function of ADAMTS family members has been associated with tumor biology [
4,
5,
6,
7]. Members of the ADAMTS family, such as ADAMTS2, ADAMTS5, ADAMTS12, and ADAMTS15, can act as cancer suppressors or promoters [
8,
9,
10,
11]. Hypermethylation of the ADAMTS19 gene has been observed in gastrointestinal cancers, and epigenetic inactivation of ADAMTS19 can promote metastatic spread in colorectal cancer [
12]. However, the role and function of ADAMTS19 in GC remains undocumented.
S100 calcium-binding protein A16 (S100A16) is a member of the EF-hand Ca2 +-binding proteins and participates in tumorigenesis [
13,
14]. In breast cancer, S100A16 promotes epithelial-mesenchymal transition (EMT) via the Notch1 pathway and correlates with poor prognosis [
15]. In pancreatic cancer, it promotes metastasis and progression through the FGF19-mediated AKT and ERK1/2 pathways [
16]. In GC, it also acts as a target gene regulating proliferation, invasion, and EMT [
17]. However, no studies have investigated the correlation of S100A16 with clinicopathological characteristics and prognosis in GC.
In this study, we focused on the correlation of ADAMTS19 expression with clinicopathological characteristics and overall survival (OS); meanwhile, the mechanisms of ADAMTS19 in GC progression were studied at the molecular level by in vitro assays.
2. Materials and Methods
2.1. Patients and Cancer Tissue Samples
In our previous study [
10], we obtained 176 primary cancer tissue samples collected in the Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China, from December 2007 to March 2012. Tissue specimens were constructed using tissue microarrays (TMAs) for immunohistochemistry (IHC), the correlations between ADAMTS19 and S100A16 and clinicopathological characteristics were analyzed based on IHC. The patients were followed up until death or until December 31, 2018. Patients lost to follow-up were excluded from the analysis. The interval between the date of surgery and the date of death or last follow-up visit was considered OS. The American Joint Committee on Cancer Staging System (7th edition) was used for GC staging. A group comprising 53 pairs of primary gastric cancerous and adjacent normal mucous tissues (collected in the Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China, from August 2018 to December 2018) was analyzed immunohistochemically to evaluate the differential expression of ADAMTS19. Another group comprising 24 pairs of primary gastric cancerous and adjacent normal mucous tissues (collected in the Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China, from March 2019 to August 2018) was used to evaluate the differential expression of S100A16. Informed consent was obtained from all patients. The study was approved by the Research Ethics Committee of Sun Yat-Sen University and complied with the principles of the Declaration of Helsinki.
2.2. Immunohistochemistry
We used a biotin-streptavidin horseradish peroxidase (HRP) detection system (ZSGB Bio, Beijin, China) for IHC staining as previously described [
10]. In brief, primary rabbit antibodies against ADAMTS19 (ab190073, Abcam, Cambridge, UK, 1:1000) and S100A16 (11456-1-AP, Proteintech, Wuhan, China, 1:1200) were incubated with specimens at 4 °C overnight. The specimens were then incubated with secondary antibodies. Finally, the specimens (TMAs) were developed with diaminobenzidine and counterstained with hematoxylin. A primary antibody diluent was used as a negative control. The ADAMTS19 and S100A16 expression scores were assigned by two pathologists independently. We subsequently used X-tile (Version 3.6.1, Rimm Lab, Connecticut, New Haven, CT, USA) software to select the best cutoff score (5.5 for ADAMTS19 and 6.0 for S100A16) based on a previous study [
18]. A group comprising 53 pairs of primary gastric cancerous and adjacent normal mucous tissues was analyzed immunohistochemically to evaluate the differential expression of ADAMTS19. Another group comprising 24 pairs of primary gastric cancerous and adjacent normal mucous tissues was used to evaluate the differential expression of S100A16. The TMAs that contained the 176 primary cancer tissue specimens were used to evaluate the expression of ADAMTS19 and S100A16 and their correlations with clinicopathological characteristics and prognosis in GC. Meanwhile, according to the cutoff scores of ADAMTS19 and S100A16, we divided 176 patients into four groups: ADAMTS19
high-S100A16
low (ADAMTS19 score ≥ 5.5 and S100A16 score < 6.0), ADAMTS19
high-S100A16
high (ADAMTS19 score ≥ 5.5 and S100A16 score ≥ 6.0), ADAMTS19
low-S100A16
low (ADAMTS19 score < 5.5 and S100A16 score < 6.0) and ADAMTS19
low-S100A16
high (ADAMTS19 score < 5.5 and S100A16 score ≥ 6.0); and the OS of the four groups was also evaluated.
2.3. Public Online Databases and Related Analyses
The public database Oncomine (
https://www.oncomine.org/resource/main.html, access date: 25 September 2018) was used to search for the differential expression of ADAMTS19 in GC and normal tissues. The correlation analysis between S100A16 and P65 was based on GEPIA 2 (
http://gepia2.cancer-pku.cn/#index, access date: 12 June 2020). The MEXPRESS database (
http://mexpress.be, access date: 24 March 2020) was used to analyze the correlation between ADAMTS19 expression and promoter methylation.
2.4. Cell Lines and Culture
Seven human GC cell lines (MKN1, MKN45, MGC803, BGC803, HGC27, SGC7901, and AGS) and one human normal gastric mucosal cell (GES1) were obtained from the Type Culture Collection Cell Bank of the Chinese Academy of Sciences Committee (Shanghai, China). AGS was cultured in DMEM/F12, whereas the other cell lines were cultured in an RPMI 1640 medium. All media were supplemented with 10% fetal bovine serum. The cells were cultured at 37 °C in a humidified atmosphere containing 5% CO2.
2.5. Plasmid Construction and Transfection
Full-length cDNA encoding ADAMTS19 was amplified using polymerase chain reaction (PCR) from the complete open reading frame (ORF) of ADAMTS19 (NM_133638.4). Then, it was cloned into a pCDH-CMV-MCS-EF1-CopGFP-T2A-Puro (PCHD) vector between the NheI and EcoRI sites. Additionally, two oligonucleotides (5-GGAATTCTCACTTGTCATCGTCGTCCTTGTAGTCACTCTTCTGCTGCAG-3 and 5-CGGCTAGCATGCGCCTGACTCACATC-3) were used to introduce a FLAG epitope at the EcoRI site. Finally, a PCDH-ADAMTS19 plasmid was constructed successfully. Another plasmid, pCDNA3.1-ADAMTS19-3xFlag, was constructed using the same method. The recombinant vectors were transformed into competent Escherichia coli DH5α cells (Takara, Kyoto, Japan) for amplification. The identity of the recombinant vectors was confirmed by sequencing. Virus packaging was performed in human embryonic kidney epithelial cell line 293T cells using a Lipofectamine 3000 reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. Briefly, PCDH-ADAMTS19 were co-transfected with pCMV-Δ8.91 and pCMV-VSVG plasmids into the 293T cells. Virus supernatants were harvested 48 and 72 h after co-transfection, and the virus titers were determined. For infection, a lentiviral suspension containing approximately 4 × 106 lentiviral particles (multiplicity of infection = 10) and polybrene (5 µg/mL) were added to MGC803 and MKN45 cells. The infected cells were screened by puromycin (Sangon Biotech, Shanghai, China). Puromycin-resistant single-cell clones stably expressing ADAMTS19 were established and verified by quantitative real-time PCR (qRT-PCR) and Western blotting. For ADAMTS19 knockdown, ADAMTS19-shRNA lentiviral and control shRNA vectors were purchased from Genechem (Shanghai, China). The targeting sequence of ADAMTS19-shRNA was 5-GGATGCAGCTATACTTATA-3. BGC823 and SGC7901 cells were also infected using the abovementioned packaged lentiviral vector.
To construct the plasmid of S100A16 and P65, full-length cDNA was amplified from the complete ORF of S100A16 (NM_080388.3) and P65 (NC_000011.10) using PCR. Then, it was cloned into pCDNA3.1 vector, and the recombinant vectors were confirmed by sequencing. Transient transfection was completed using a Lipofectamine 3000 reagent according to the manufacturer’s instructions. Small interfering RNA (siRNA) of S100A16 (RiboBio, Guangzhou, China) was transfected into cells using a Lipofectamine RNAiMAX reagent (Invitrogen, Carlsbad, USA). The siRNA-targeted sequences were as follows: siS100A16-1, 5-GCGAGATGCTCCAGAAAGA-3 (forward); siS100A16-2, 5-GAACCTGGATGCCAATCAT-3 (forward).
2.6. RNA Extraction and qRT-PCR
A TRIzol reagent (Invitrogen, Carlsbad, USA) was used to extract total RNA from tissues according to the manufacturer’s instructions, and an RNA-Quick Purification Kit (ES-RN001; Yishan Biotechnology, Shanghai, China) was used to extract total RNA from cells according to the manufacturer’s instructions. Reverse transcription PCR and qRT-PCR were performed as previously described [
18]. For the assessment of ADAMTS19, the messenger RNA (mRNA) levels in GC were evaluated using 45 pairs of fresh-frozen primary cancerous and adjacent normal tissues. For the assessment of S100A16, the mRNA levels in GC were evaluated using 80 pairs of fresh-frozen primary cancerous and adjacent normal tissues.
The qRT-PCR primer sequences were as follows: ADAMTS19, 5-AGGCCAGTAACTGCTTGCTAC-3 (forward) and 5-GTCTAGCTTGGTTCTGCATTCTT-3 (reverse); GAPDH, 5-GACAGTCAGCCGCATCTTCTT-3 (forward) and 5-AATCCGTTGACTCCGACCTTC-3 (reverse); S100A16, 5-GCTGTCGGACACAGGGAAC-3 (forward) and 5-TGATGCCGCCTATCAAGGTC-3 (reverse).
2.7. Western Blot Analysis
Cell protein was extracted using a T-PER Tissue Protein Extraction Reagent (Thermo Fisher Scientific, Massachusetts, MA, USA) and supplemented with protease and phosphatase inhibitors (ApexBio, Houston, TX, USA) according to the manufacturer’s instructions. The protein concentration was measured using a BCA protein assay kit (Beyotime, Shanghai, China) according to the manufacturer’s instructions. Briefly, lysates containing 40 μg of protein were separated by SDS-PAGE and then transferred to polyvinylidene fluoride membranes (Millipore, Massachusetts, MA, USA). The membranes were then blocked with 5% skimmed milk or 5% bovine serum albumin (BSA) at room temperature for 1 h and incubated with primary antibodies at 4 °C overnight. They were subsequently incubated with corresponding HRP-conjugated secondary antibodies (goat anti-mouse IgG: SA00001-1, 100 μL, Proteintech, 1:10,000; mouse anti-rabbit IgG light chain specific: SA00001-7L, 100 μL, Proteintech; 1:10,000) at room temperature for 1 h. The bands were then detected with an enhanced chemiluminescence reagent and were observed using a ChemiDoc Touch Imaging System (Bio-Rad, California, CA, USA). The bands were quantified using ImageJ (version 1.52v, National Institutes of Health, Bethesda, MD, USA) and normalized with glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Membranes were incubated with the following primary antibodies: ADAMTS19 (ab190073, Abcam, Cambridge, UK, 1:1000), S100A16 (11456-1-AP, Proteintech, Wuhan, China, 1:1000), P65 (#8242, Cell Signaling Technology, Massachusetts, MA, USA, 1:1000), Phospho-P65 (#3033, Cell Signaling Technology, Massachusetts, USA, 1:1000), E-cadherin (20874-1-AP, Proteintech, Wuhan, China, 1:1000), β-catenin (17565-1-AP, Proteintech, Wuhan, China, 1:1000), GAPDH (60004-1-Ig, Proteintech, Wuhan, China, 1:10,000), and PCNA (10205-2-AP, Proteintech, Wuhan, China, 1:2000).
2.8. Migration and Invasion Assay
Transwell chambers (#353097, Falcon, New York, NY, USA) with and without Matrigel (#356234, Corning, New York, NY, USA) were used to assess GC cell migration and invasion. In brief, 4 × 104 cells were transferred into the upper chamber with 100 μL of serum-free RMPI-1640, whereas the lower chamber was filled with 700 μL of 10% serum RMPI-1640 to generate a chemoattractant. The cells in the lower chamber were fixed using 4% paraformaldehyde after adequate culturing, and crystal violet was used to stain the cells on the lower membrane surface. Five random fields of the lower membrane surface were photographed using a microscope (Olympus, Tokyo, Japan), and the numbers of migration and invasion cells were calculated using ImageJ. The assays were performed at least in triplicate.
2.9. Wound Healing Assay
A sterile tip of a 200-μL pipette was used to make a wound after seeding 1 × 106 cells in a 12-well plate. The cells were then cultured with 1% serum RMPI-1640 for up to six days. An IncuCyte ZOOM system (Essen BioScience, Michigan, MI, USA) was used to capture images of the wound area every 2 h during culturing. Finally, the initial wound area was defined 100%, and ImageJ was used to calculate the percentage of wound closure at the end of the culturing process. The assays were performed at least in triplicate.
2.10. RNA Sequencing Array and Bioinformatics Analysis
Whole-transcript deep sequencing (RNAseq) was performed on a BGISEQ-500 platform (BGI, Shenzhen, China). The analysis was designed with two groups of paired MGC803-Vector/ADAMTS19 cells. Heat map analysis of the altered genes was performed using OmicShare Heatmap tools (
http://www.omicshare.com/tools, access date: 3 July 2020). The data were also analyzed using the Gene Ontology (GO) method with the free online analysis tool, Database for Annotation, Visualization and Integrated Discovery (DAVID;
https://david.ncifcrf.gov/, access date: 3 July 2020) [
19,
20]. The results of the GO analysis were displayed using the online analysis tool, SangerBox (
http://sangerbox.com/Index, access date: 23 December 2020). Gene set enrichment analysis (GSEA) was performed using a GSEA preranked tool, R (version 4.0.3, The R Foundation, New York, NY, USA), and RStudio (1.4.1103, RStudio, Boston, MA, USA).
2.11. Dual-Luciferase Reporter Assay
After constructing a pGL4-S100A16 plasmid that contained 1000 bp upstream of the S100A16 promoter region, the identity of the recombinant vector was confirmed by sequencing. The pGL4-S100A16, pRL-TK, pCDNA3.1-ADAMTS19-3xFlag, and pCDNA3.1-P65 plasmids were co-transfected into MGC803 and BGC823 cells using Lipofectamine 3000 according to the manufacturer’s instructions. After culturing for 24–48 h, luciferase activity was measured using a Dual-Luciferase Reporter Gene Assay System (Promega, Wisconsin, WI, USA) according to the manufacturer’s instructions. The assays were performed in triplicate.
2.12. Immunofluorescence Assay
MKN45 and MGC803 cells were fixed in 4% paraformaldehyde solution after being transfected with pCDNA3.1-ADAMTS19-3xFlag using a Lipofectamine 3000 reagent and cultured for 48–72 h. The cell membranes were penetrated with a 0.25% Triton X100 (meilunbio, Dalian, China) solution. After 15 min, 1% BSA was transferred to block the cells at room temperature for 30 min. Primary antibodies (Flag-tag: 390002, ZenBio, Sicuan, China, 1:1000; P65: 10745-1-AP, Proteintech, Wuhan, China, 1:200) were incubated at 4 °C for 12–16 h. Primary antibody binding and nuclei were observed using fluorescence secondary antibodies (anti-rabbit: A11034, Invitrogen, 1:200; anti-mouse IgG: A11003, Invitrogen, 1:200) and DAPI (4’,6-diamidino-2-phenylindole; #C1002, Beyotime, Shanghai, China, 1:1000) staining, respectively. Finally, the transfected MKN45 and MGC803 cells were observed and photographed using a confocal microscope (Leica, Weztlar, Germany).
2.13. Nuclear and Cytoplasmic Protein Extraction Assay
A nuclear and cytoplasmic protein extraction assay was performed using a NE-PER Nuclear and Cytoplasmic Extraction Reagent Kit (#78833, Thermo Fisher Scientific, Massachusetts, USA) according to the manufacturer’s instructions. In brief, after protein extraction, 20 μg of protein was added into each well of 8% SDS-PAGE. Subsequently, Western blotting was performed as described above.
2.14. Co-Immunoprecipitation Assay
Stably overexpressed ADAMTS19 and control MGC803 cells were lysed using Pierce IP Lysis Buffer (#87788, Thermo Fisher Scientific, Massachusetts, USA) according to the manufacturer’s instructions. Cell supernatants were centrifuged at 4 °C, and then 50 μL of a protein A/G agarose bead solution was added to every 100 μL of cell supernatant. ADAMTS19 (ab190073, Abcam, Cambridge, UK) and P65 (#8242, Cell Signaling Technology, Massachusetts, USA) primary antibodies were used to pull down the proteins interacting with ADAMTS19 and P65 at 4 °C overnight. Immunoglobulin G protein was used as a positive control. After protein extraction, detections were performed by Western blotting as described above.
2.15. Statistical Analysis
Statistical analysis was performed using IBM SPSS Statistics version 21.0 (IBM, New York, NY, USA). Continuous variables were presented as the means ± standard deviations and analyzed by Student’s t test. Categorical variables were assessed using the chi-squared test, or the Wilcoxon signed-rank test as appropriate. Overall survival was calculated using the Kaplan–Meier method, and comparisons were performed using the log-rank test. Potential prognostic factors for survival were assessed in multivariate analysis using Cox proportional hazards regression following a backward elimination process. The correlation with ADAMTS19 with promoter methylation were assessed using Pearson’s correlation coefficient. A p-value of less than 0.05 was considered statistically significant.
4. Discussion
Members of the ADAMTS family are involved in the progress of solid tumors [
5,
6]. Members such as ADAMTS2, ADAMTS5, ADAMTS12, and ADAMTS15 act as cancer suppressors or promoters [
8,
9,
10,
11]. Moreover, ADAMTS19 is downregulated and correlates with prognosis in colorectal cancer [
12]. However, its role in GC has hitherto been unknown. This is the first study to explore its exact role in GC. Using qRT-PCR and IHC, we found that ADAMTS19 is downregulated in cancer tissues compared to adjacent normal tissues. The results were consistent with our Oncomine analysis.
DNA methylation is frequently described as a “silencing” epigenetic marker. Methylation blocks the start of transcription, not elongation [
21]. We used the MEXPRESS database to analyze the correlation between ADAMTS19 expression and promoter methylation [
22]. In line with a previous study on colorectal cancer [
12]. Pearson’s correlation coefficient showed that ADAMTS19 expression negatively correlates with promoter methylation (
Figure S1). This result indicates that promoter hypermethylation leads to downregulated ADAMTS19 expression in GC. Hence, we speculate that ADAMTS19 is a tumor inhibitor and plays a crucial role in the pathogenesis of GC.
We also found that ADAMTS19 protein significantly correlates with distant metastasis, Lauren’s classification, differentiation and perineural invasion in GC. Survival analysis revealed that patients with low ADAMTS19 expression have worse OS than high ADAMTS19 patients, which is consistent with the findings of a study on colorectal cancer [
12]. Subsequent cell functional assays showed that ADAMTS19 suppresses GC cell migration and invasion. We further performed mechanistic experiments and rescue assays and demonstrated that S100A16 is the downstream of ADAMTS19, acting as a tumor promoter involved in carcinogenesis. This finding is consistent with previous studies on S100A16 [
15,
23]. In contrast, ADAMTS19 and S100A16 were not associated with EMT significantly, but they tended to affect the levels of E-cadherin and β-catenin measured by Western blot (
Figure S2).
Although previous studies have reported that S100A16 tends to act as a tumor promoter [
16,
23,
24], none examined the correlation between S100A16 expression and clinicopathological characteristics of GC. This is the first study to show that high S100A16 expression tends to result in poor differentiation and that patients with high S100A16 expression have worse OS than low S100A16 patients. We also showed that S100A16 is an independent predictor of GC prognosis, with ADAMTS19
high-S100A16
low patients having the best OS and ADAMTS19
low-S100A16
high patients having the worst OS. In addition, our study reveals that both ADAMTS19 and S100A16 were correlated with Lauren’s classification, but not WHO classification (
Table 1). WHO classification and Lauren’s classification are the two main classifications of histologic type of gastric cancer. WHO classification includes not only the common types of gastric cancer, but also the rare and special types. However, WHO classification is not suitable for prognosis analysis of gastric cancer due to its relatively fine classification and great differences in biological behaviors between different types of gastric cancer. The advantages of Lauren’s classification are simplicity, ease of grasping, and high repeatability between different observers. However, the disadvantage of Lauren’s typing is that it is too general to distinguish gastric cancer with different biological behaviors. In our study, there were no significant differences in the WHO classification (
Figure S4A) and Lauren’s classification (
Figure S4B) of 176 patients. The intestinal type has a trend to obtain better OS than diffuse type and mixed type, the non-significant difference between the groups may be caused by small sample size.
We further explored the regulatory ADAMTS19-S100A16 mechanism. The NF-κB pathway, especially its important member P65, has a complicated relationship with cancer [
25,
26,
27,
28]. Shan et al. demonstrated that P65 binds to the mortalin promoter and promotes ovarian cancer cell proliferation and migration via regulating mortalin [
26]. Zhang et al. showed that it can directly bind to the promoter of cyclin D1, mediating an increase in the protein’s expression [
28]. In this study, we found that ADAMTS19 can bind to cytoplasm P65 and inhibit the nuclear translocation of P65, decreasing nucleus phospho-P65. We also found that P65 can regulate the transcription of S100A16 and positively correlates with S100A16 expression. We thus demonstrated that ADAMTS19 inhibits cell migration and invasion via the NF-κB/S100A16 axis.
To our knowledge, our study is not only the first to reveal the correlation between ADAMTS19 and S100A16 in GC but also the first to explore the correlation of the differential co-expression of ADAMTS19 and S100A16 with the prognosis of GC. Moreover, it is the first study to elucidate the regulatory ADAMTS19-S100A16 mechanism. The role of ADAMTS19 and S100A16 warrants further research. Studies on animal models should be conducted to further explore the role of ADAMTS19 in GC cell migration and invasion. Moreover, future studies should further investigate the specific methylation mechanism of ADAMTS19. Finally, further research is needed to clarify the exact transcriptional mechanism of S100A16 regulated by P65.