We opted for the GSE54129 dataset in the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/gds/) database, which comprised 111 human GC tissue samples and 21 non-cancerous gastric tissue samples. Furthermore, from the stomach adenocarcinoma (STAD) dataset in The Cancer Genome Atlas (TCGA) database (https://tcga-data.nci.nih.gov/tcga/), we extracted 32 adjacent non-tumor tissue samples and 375 STAD samples. The “Limma” program (version 3.6.0) in R software (version 3.6.0, R Foundation for Statistical Computing, Vienna, Austria) was used to carry out the differential expression analysis. The selection of genes was done using fold change (FC), with FC $>$1.3 regarded upregulated and FC 0.7 considered downregulated. a degree of significance of p 0.05 was applied to establish statistical significance.

To evaluate the expression levels of SLC30A2 in the GSE54129 dataset and the TCGA-STAD dataset, the Wilcoxon test was employed. Visualization of the expression data was facilitated utilizing the “ggplot2” library (version 3.2.1) within the R software. The subsequent assessment involved the application of the “survival” package (version 3.6.3) in R for conducting Kaplan-Meier (KM) survival curve analysis. This analysis aimed to assess the effects of SLC30A2 expression levels at high and low on the Progression-free Survival (PFS) probability among STAD patients, including the calculation of the log-rank p-value. Additionally, the University of Alabama at Birmingham Cancer data analysis portal (UALCAN) database (http://ualcan.path.uab.edu/index.html) was used to study the correlation between the level of SLC30A2 and various clinical factors in TCGA-STAD samples. The clinical factors analyzed encompassed individual cancer stages, patient’s gender, patient’s race, tumor grade, patient’s age, and lymph node metastasis status. Statistical significance threshold was specified as a p 0.05.

The Type Culture Collection of the Chinese Academy of Sciences (Shanghai, China) supplied the normal gastric mucosal cells (GES1) and the GC cell lines (AGS, HGC27, MGC803, and SNU-1). RPMI 1640 medium (Bioss, Beijing, China) was used to culture the cells. 10% fetal bovine serum (Gibco, Carlsbad, CA, USA), 100 mg/mL streptomycin (Solarbio, Beijing, China), and 100 units/mL penicillin (Gibco, Carlsbad, CA, USA) were added as supplements. All cell lines were validated by short tandem repeat (STR) profiling and tested negative for mycoplasma. Cells were all cultured in a humidified incubator at 37 °C and 5% CO₂.

AGS and HGC27, two GC cell lines, were plated on a 24-well plate at the concentration of 2 $\times$ 10⁵ cells each, and they were grown in full growth media for the whole night until reaching approximately 70–80% confluence. Transfection procedures followed the manufacturer’s guidelines using Lipofectamine 2000 transfection reagent (Invitrogen, Shanghai, China). Specifically, specific small interfering RNA (siRNA) targeting SLC30A2 (si-SLC30A2-1 and si-SLC30A2-2) or negative control siRNA (si-NC), as well as SLC30A2 overexpression plasmid or control vector, were transfected into GC cells. Following standardization protocols, transfections were performed in 24-well plates. Further experiments were conducted 48 hours post-transfection. To examine the impact of zinc sulfate (ZnSO₄) on GC cells, different concentrations of ZnSO₄ (10, 50, 100, 150 µM) were administered for 24 hours post-transfection, along with saline treatment, setting the stage for subsequent analyses.

Total RNA extraction from GC cells was performed utilizing the RNeasy kit (Qiagen, Beijing, China). complementary DNA (cDNA) synthesis was completed utilizing the QuantiTect SYBR Green PCR kit (Qiagen). Subsequently, the StepOnePlus real-time PCR machine (Applied Biosystems, Foster City, CA, USA) was employed to carry out qRT-PCR using the SYBR Green PCR Master Mix. For data normalization, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was utilized as an internal reference. The following primer sequences were used for amplification in Supplementary Table 1. Gene expression analysis was conducted using the 2^{-Δ⁢Δ⁢CT} method.

Protease and phosphatase inhibitors were included in RIPA lysis buffer (pH 8.0) (Thermo Fisher Scientific, Waltham, MA, USA) that was employed to make cell protein extracts. The bicinchoninic acid (BCA) Protein Assay Kit (Beyotime, Jiangsu, China) was employed to calculate the concentration of protein. SDS-PAGE was employed to divide equal quantities of protein, which were then deposited onto polyvinylidene fluoride (PVDF) membranes (BSA-coated, Beyotime, Jiangsu, China). Wuhan Sanying Biotechnology (Wuhan, China) provided all of the antibodies used. Primary antibodies against SLC30A2 (1:2000), Cyclin D1 (1:5000), P21 (1:1000), P27 (1:1000), Cleaved-caspase-3 (1:1000), Cleaved-caspase-9 (1:1000), Wnt-3a (1:1000), and anti-$\beta$-catenin (1:5000) were used to probe the membranes. After incubation with primary antibodies, Affinipure Donkey Anti-Goat IgG (1:3000) conjugated with horseradish peroxidase (HRP) was incubated on the membranes at room temperature for 1.5 hours, followed by visualization using the enhanced chemiluminescence (ECL) chemiluminescence detection kit (Beyotime, Jiangsu, China).

Cell proliferation and viability were evaluated utilizing CCK-8 assay (CK04, Dojindo, China). In a 96-well plate, AGS and HGC27 cells were added at a cell count of 5 $\times$ 10³ cells per well. Next, each well received the addition of 10 µL of CCK-8 reagent. After that, the plate was placed for four hours at 37 °C and 5% CO₂. Following the incubation period, a microplate reader (Thermo Fisher Scientific, USA) was employed to measure absorbance at 450 nm. Absorbance readings were obtained at one to four days post-incubation with the CCK-8 reagent to monitor cell proliferation and generate growth curves.

Following transfection for 24 hours, cells were harvested and re-suspended at a concentration of 5 $\times$ 10⁴ cells/well. Subsequently, these cells were inserted into the upper chambers of Transwell inserts (6-well format) covered with 10 µL of 1:9 diluted Matrigel (BD Biosciences, Shanghai, China) containing serum-free media. 600 µL of culture media with 20% fetal bovine serum (FBS, Procell, Wuhan, China) was added to the bottom chambers. The cells were then cultured for ten hours at 37 °C. The cells were fixed for 20 minutes with 4% paraformaldehyde and dyed for 30 minutes with 4’,6-diamidino-2-phenylindole (DAPI). Cotton swabs were used to remove non-invaded cells from the upper surface of the membrane. The invaded cells on the lower surface were then counted and examined under a microscope. To assess cell migratory capacity, the same inserts were used without the Matrigel coating in a separate migration assay.

To evaluate cell apoptosis and cell cycle distribution in AGS and HGC27 cells, flow cytometry analysis was performed. Initially, AGS and HGC27 cells were cultivated for 24 hours after being planted at a density of 1 $\times$ 10⁴ cells per well in 24-well plates. Following dissociation with trypsin-Ethylenediaminetetraacetic Acid (EDTA) and washing with Phosphate Buffered Saline (PBS), cells were cultured with 5 µL of propidium iodide (PI) and 5 µL Annexin V-FITC of solution at ambient temperature for a duration of 15 minutes for apoptosis analysis. Subsequently, a flow cytometer (Jiyuan, Guangzhou, China) was used to assess the staining of PI and Annexin V, and FlowJo software version 10.4.2 (FlowJo, Ashland, OR, USA) was used to analyze the results. For cell cycle analysis, AGS and HGC27 cells were preserved for four hours at 4 °C in 75% ethanol, and thereafter stained at 37 °C for an hour with 50 µg/mL PI containing 10 mg/L RNase A. A flow cytometer (Jiyuan, Guangzhou, China) was used to assess the cell cycle distribution, and FlowJo software was applied to analyze the information.

In 96-well plates, AGS and HGC27 cells were planted at a density of 1 $\times$ 10⁴ cells per well. Following cell adherence, the monolayers were washed twice with PBS and subsequently lysed. After that, the resulting lysates were centrifuged for five minutes at 10,000 $\times$g to separate the supernatants. These were sonicated and utilized for the assessment of malondialdehyde (MDA), glutathione (GSH), and total oxidative stress (TOS). MDA levels, reflecting lipid peroxidation, were quantified through spectrophotometric detection of the MDA-thiobarbituric acid complex at 532 nm. The absorbance of GSH, a vital antioxidant molecule, was measured at 412 nm by its interaction with 5,5^′-dithiobis (2-nitrobenzoic acid). TOS was evaluated based on oxidant-mediated conversion of ferrous to ferric ions, with the resultant color change measured at 530 nm. These assays were performed using kits from Nanjing Jiancheng Bioengineering Institute and Rel Assay (Mega Medical Co., Gaziantep, Turkey), Ensuring precise and replicable measurements of oxidative stress indicators by adhering to manufacturer protocols.

In this study, the secretion of Caspase-3, Cytochrome C (CYC), Tumor necrosis factor (TNF)-$\alpha$, and interleukin (IL)-6 in the culture supernatants of AGS and HGC27 cells, either treated or untreated with ZnSO₄ (50 and 150 µM, for 24 hours), was determined using ELISA kit (CUSABIO, Wuhan, China). An ELISA reader was employed to detect absorbance at 450 nm. The obtained values were compared with standard curves established using standard titration. The bicinchoninic acid (BCA) test was utilized to ascertain the protein content in each culture bottle. All concentrations were standardized to the respective cellular protein content and expressed as pg/mL (cellular protein).

The dataset underwent statistical analysis using the R programming language. The student’s t-test was utilized to analyze variations between groups and mean values along with their standard deviations (SD) were reported. An analysis of variance (ANOVA) was employed in conjunction with Tukey’s post-hoc test to assess variations between several groups. p 0.05 significance level was used.

The “limma” package was employed in this work to conduct differential expression analysis on the GSE54129 dataset and TCGA-STAD samples. Specifically, 3199 upregulated DEGs and 3465 downregulated DEGs were identified from the GSE54129 dataset, while 9424 upregulated DEGs and 1274 downregulated DEGs were selected from the TCGA-STAD samples (Fig. 1A,B). Notably, SLC30A2 was identified as an upregulated gene in both the GSE54129 dataset and TCGA-STAD samples, exhibiting significant overexpression in tumor samples (Fig. 1C,D). Moreover, KM survival analysis indicated that higher expression levels of SLC30A2 were associated with a markedly reduced PFS in patients, in contrast to those exhibiting lower levels of SLC30A2 expression (p 0.05, as shown in Fig. 1E).

Fig. 1.

Differential expression of SLC30A2 in gastric cancer (GC) and its prognostic analysis. (A,B) Volcano plot depicting the distribution of differentially expressed genes (DEGs) in the GSE54129 dataset and TCGA-STAD samples. The x-axis (Log₂ Fold Change) represents the log₂ fold change in gene expression between tumor and normal samples. The y-axis (–log₁₀ p-value) indicates the statistical significance of differential expression. Up-regulated DEGs are depicted in red, and down-regulated DEGs are depicted in blue. (C,D) Box plot showing the differential expression of SLC30A2 between tumor and normal samples in the GSE54129 dataset and TCGA-STAD samples. (E) Kaplan-Meier (KM) curve demonstrating the association between SLC30A2 expression levels and Progression-free Survival (PFS) in GC patients. The abscissa represents time in months, and the ordinate is PFS probability. TCGA, The Cancer Genome Atlas; STAD, stomach adenocarcinoma. ***p 0.001, ****p 0.0001.

In the TCGA-STAD dataset, we examined the relationship between SLC30A2 expression levels and different clinical-pathological factors using the UALCAN database. Our analysis indicated that SLC30A2 expression levels were not associated with the stage of cancer (Fig. 2A), patient race (Fig. 2B), or gender (Fig. 2C). However, a significant variation in SLC30A2 expression was observed across age groups, with the most pronounced differences being between the groups of 21–40 years and those of 41–60 years, 81–100 years, and 61–80 years (Fig. 2D). Furthermore, a clear differential expression of SLC30A2 was noted when comparing tumor grades, with substantial variations between Grade 2 and Grade 3 tumors as well as between Grade 1 and Grade 3 tumors found (Fig. 2E). Regarding nodal metastasis status, there was a noteworthy difference in SLC30A2 expression between cases classified as N2 and N3 (Fig. 2F).

Fig. 2.

Expression analysis of SLC30A2 in UALCAN database. (A–F) Box plot illustrating the association between SLC30A2 expression levels and individual cancer stages (A), patient’s race (B), patient’s gender (C), patient’s age (D), tumor grades (E), and nodal metastasis statuses (F) in TCGA-STAD samples. TCGA, The Cancer Genome Atlas; STAD, stomach adenocarcinoma; UALCAN, the University of Alabama at Birmingham Cancer data analysis portal.

We examined the level of SLC30A2 in GC cell lines (AGS, HGC27, MGC803, and SNU-1) and normal gastric mucosal cells (GES1). The findings demonstrated that SLC30A2 was substantially expressed in all GC cell lines compared to normal tissues, with significant upregulation observed particularly in the AGS and HGC27 cell lines (Fig. 3A–C). Therefore, these two cell lines were selected for further exploration of the functional significance of SLC30A2 in GC. Subsequently, we evaluated the transfection efficiency of SLC30A2 knockdown plasmids in AGS and HGC27 cells employing WB and qRT-PCR (Fig. 3D–G). The invasion, migration, and proliferation abilities of AGS and HGC27 cells following SLC30A2 knockdown were assessed using CCK-8 and Transwell assays (Fig. 3H–K). In comparison to the control group, the outcomes demonstrated that SLC30A2 knockdown suppressed the growth, invasion, and migration of AGS and HGC27 cells.

Fig. 3.

Effects of SLC30A2 knockdown on GC proliferation, invasion and migration. (A–C) qRT-PCR and WB analysis depicting the mRNA and protein expression levels of SLC30A2 in normal gastric mucosal cells (GES1) and GC cell lines (AGS, HGC27, MGC803, and SNU-1). (D–G) Assessment of the transfection efficiency of SLC30A2 knockdown plasmids in AGS and HGC27 cells using qRT-PCR and WB analysis. (H,I) CCK-8 results show the proliferation abilities of AGS and HGC27 cells following SLC30A2 knockdown. (J,K) Evaluation of the invasion and migration abilities of AGS and HGC27 cells following SLC30A2 knockdown using Transwell assays. Representative images of the underside of the membrane stained with DAPI illustrate the invasion and migration of cells (left). Quantification of cell invasion and migration represented as a percentage of cell count (right). Magnification: 200$\times$, scale bar = 50 µm. qRT-PCR, Quantitative real-time polymerase chain reaction; WB, Western blotting; mRNA, messenger RNA; CCK-8, cell counting kit-8; NC, negative control. *p 0.05.

After SLC30A2 knockdown, flow cytometry analysis evaluated apoptosis and cell cycle distribution in AGS and HGC27 cells. Our findings showed that SLC30A2 knockdown enhanced apoptosis in AGS and HGC27 cells relative to the control group, along with a reduce in the proportion of cells in the S phase, indicating cell cycle arrest during the G1 to S transition (Fig. 4A–C). Subsequently, qRT-PCR and WB assays were conducted to evaluate the gene and levels of cell cycle proteins (Cyclin D1, P21, and P27) in AGS and HGC27 cells after SLC30A2 knockdown. Our findings revealed that SLC30A2 knockdown resulted in a decline in Cyclin D1 expression and increased P27 and P21 expression in contrast to the control group (Fig. 4D–I). Those findings indicated that in vitro cell cycle arrest and apoptosis are enhanced by SLC30A2 knockdown.

Fig. 4.

Impact of SLC30A2 knockdown on apoptosis and cell cycle progression in GC cells. (A–C) Flow cytometry analysis illustrating the effects of SLC30A2 knockdown on apoptosis and cell cycle distribution in AGS and HGC27 cells. (D–I) qRT-PCR and WB analysis of the mRNA and protein expression levels of cell cycle proteins (Cyclin D1, P27, and P21) in AGS and HGC27 cells following SLC30A2 knockdown. qRT-PCR, Quantitative real-time polymerase chain reaction; WB, Western blotting; mRNA, messenger RNA. *p 0.05.

The CCK-8 test was showed that at a concentration of 150 µM, ZnSO₄ considerably decreased the viability of AGS and HGC27 cells (Fig. 5A,B). To further investigate the impact of zinc on oxidative stress in GC cells, the level of MDA, GSH, and TOS were evaluated utilizing respective assay kits in AGS and HGC27 cells subjected to 50 and 150 µM concentrations of ZnSO₄. The findings indicated that in contrast to the group under control, MDA and TOS levels exhibited concentration-dependent increases, while GSH levels showed concentration-dependent decreases in response to ZnSO₄ treatment (Fig. 5C–H). These results suggested that ZnSO₄ exerts cytotoxic effects and induces oxidative stress in GC cells, underscoring its potential impact on the cellular redox state and viability.

Fig. 5.

Effects of ZnSO₄ on cytotoxicity and oxidative stress in GC cells. (A,B) The viability of AGS and HGC27 cells treated with different concentrations of ZnSO₄ (0, 10, 50, 100, 150 µM) was assessed using the CCK-8 assay. The Y-axis represents cell viability, and the X-axis represents different concentrations of ZnSO₄ treatment conditions. (C–H) Measurement of MDA, GSH, and TOS levels in AGS and HGC27 cells treated with 50 and 150 µM concentrations of ZnSO₄ using respective assay kits; CCK-8, cell counting kit-8; MDA, malondialdehyde; GSH, glutathione; TOS, total oxidant status; ZnSO₄, zinc sulfate. *p 0.05, **p 0.01.

ELISA analysis results showed that exposure to ZnSO₄ significantly affected apoptosis and inflammatory biomarkers in AGS and HGC27 cell lines. After treatment with different concentrations of ZnSO₄ (50, 150 µM), a dose-dependent rise in the levels of Caspase-3 was observed in AGS (Fig. 6A) and HGC27 cells (Fig. 6B), indicating enhanced apoptotic activity. Similarly, CYC levels in AGS (Fig. 6C) and HGC27 cells (Fig. 6D) also increased with increasing ZnSO₄ concentration, further confirming the induction of apoptosis. In addition to these apoptotic markers, proinflammatory cytokines were also assessed. In GC cells, compared to the control group, TNF-$\alpha$ and IL-6 levels rose in a concentration-dependent way in response to ZnSO4 (Fig. 6E–H). These findings highlighted that ZnSO₄ treatment not only causes GC cells to undergo apoptosis but also promotes a pro-inflammatory environment.

Fig. 6.

ZnSO₄ modulates apoptotic and inflammatory markers in GC cells. (A–H) Expression levels of apoptotic markers Caspase3 (A,B) and CYC (C,D), as well as inflammatory cytokines Tumor necrosis factor (TNF)-$\alpha$ (E,F) and interleukin (IL)-6 (G,H), were evaluated by ELISA in AGS and HGC27 cells treated with 50 and 150 µM concentrations of ZnSO₄. The Y-axis represents the expression level of each marker, and the X-axis represents different treatment conditions with ZnSO₄. CYC, cytochrome C; ZnSO₄, zinc sulfate; ELISA, Enzyme-Linked Immunosorbent Assay. *p 0.05, **p 0.01.

The assays of qRT-PCR and WB were employed to evaluate the effectiveness of SLC30A2 overexpression in AGS and HGC27 cells (Fig. 7A–C). Proliferation, invasion, and migration of AGS and HGC27 cells under five different treatment conditions (control, saline, saline + ZnSO₄, saline + ZnSO₄ + Vector, and saline + ZnSO₄ + over-SLC30A2) were assessed using CCK-8 and Transwell assays (Fig. 7D–G). The control and saline groups did not significantly vary from one another, according to the results. Following the addition of ZnSO₄ to the saline group, a reduction in cell proliferation, invasion, and migration was observed. However, this inhibitory effect was partially reversed when ZnSO₄ and overexpression of SLC30A2 were combined in the saline medium. These results indicated that SLC30A2 is vital not only in mediating the cytotoxic response of ZnSO₄ but also in encouraging the invasion and migration properties of GC cells.

Fig. 7.

Overexpression of SLC30A2 rescues ZnSO₄-induced inhibition of proliferation, invasion, and migration in GC cells. (A–C) The efficiency of SLC30A2 overexpression in AGS and HGC27 cells was assessed by qRT-PCR and WB assays. (D–G) Proliferation, invasion, and migration of AGS and HGC27 cells under different treatment conditions (control, saline, saline + ZnSO₄, saline + ZnSO₄ + Vector, and saline + ZnSO₄ + over-SLC30A2) evaluated by CCK-8 (D,E) along with Transwell assays (F,G). Representative images of the underside of the membrane stained with DAPI illustrate the invasion and migration of cells (left). Quantification of cell invasion and migration represented as a percentage of cell count (right). Magnification: 200$\times$, scale bar = 50 µm. qRT-PCR, Quantitative real-time polymerase chain reaction; WB, Western blotting; CCK-8, cell counting kit-8; ZnSO₄, zinc sulfate. *p 0.05.

To further elucidate the impacts of ZnSO₄ treatment and SLC30A2 overexpression on GC cell apoptosis and the Wnt/$\beta$-catenin signaling pathway. Wnt-3a, $\beta$-catenin, cleaved caspase-3, and cleaved caspase-9 expression levels were evaluated using qRT-PCR and WB assays (Fig. 8A–L). Between the GC cell control and saline groups, there was no discernible difference in the outcomes. However, after adding ZnSO₄ to the saline group, the amounts of Cleaved caspase-3 and Cleaved caspase-9 rose, indicating that the apoptosis pathway was enhanced. Similarly, Wnt/3a and $\beta$-catenin expression levels rose, indicating that the Wnt/$\beta$-catenin signaling pathway was triggered. Contrary to these effects, overexpression of SLC30A2 markedly mitigated the ZnSO₄-induced upregulation, leading to decreased production of Wnt-3a, $\beta$-catenin, cleaved caspase-3, and cleaved caspase-9. These findings indicated that zinc promoted GC cell apoptosis and initiates the Wnt/$\beta$-catenin signaling pathway, and SLC30A2 overexpression can prevent this effect.

Fig. 8.

Regulation of GC cell apoptosis and Wnt/$\beta$-catenin signaling activation by ZnSO₄ and SLC30A2 overexpression. (A–F) Expression levels of Cleaved caspase-3, Cleaved caspase-9, Wnt-3a, and $\beta$-catenin in AGS cells were assessed by qRT-PCR and WB assays under different treatment conditions (control, saline, saline + ZnSO₄, saline + ZnSO₄ + Vector, and saline + ZnSO₄ + over-SLC30A2). (G–L) Expression levels of Cleaved caspase-3, Cleaved caspase-9, Wnt-3a, and $\beta$-catenin in HGC27 cells under the same treatment conditions. qRT-PCR, Quantitative real-time polymerase chain reaction; WB, Western blotting; ZnSO₄, zinc sulfate. *p 0.05.