FDX1 expression promotes DSF/Cu-induced cuproptosis in gastric cancer cells

Cell culture and DSF/Cu treatment

Epithelial cells of the human stomach (GES1), as well as two types of cells found in human GC (MKN45 and AGS) were incubated in RPMI-1640 medium containing 10% fetal bovine serum [FBS] (Gibco, Grand Island, New York, USA) at 37°C in 5% CO₂. A combination of DSF/Cu at a 1:1 ratio was administered to the GES1, MKN45, and AGS cell lines upon reaching a cell growth density of 80%–90% and allowed to incubate for 24–48 h. All human cell lines have been authenticated using STR profiling all experiments were performed with mycoplasma-free cells.

RNA extraction and gene expression analysis

GC cells were treated with DSF/Cu for 24 h, after which the cells were collected and total RNA was extracted. Conversion of RNA into cDNA was performed using the first strand cDNA synthesis kit (Tiangen, Beijing, China). Real-time quantitative polymerase chain reaction (qPCR) was used to assess the levels of FDX1, DLAT, LIAS, and WDR43 expression. The qPCR conditions included the following: an initial heating at 94°C for 3 min; followed by 35 cycles of denaturation at 94°C for 10 s, annealing at 59°C for 15 s, and extension at 72°C for 30 s. β-actin was used as the control gene. The primer sequences are provided in Table S1.

Western blot

Total proteins were extracted from GC cells with Beyotime extraction buffer using the BCA protein assay kit (Tiangen) for quantification. The subsequent process included separating the proteins through SDS-PAGE, transferring the proteins onto a PVDF membrane, and combining the membrane with primary antibodies against FDX1, DLAT, WDR43, cyclin dependent-kinase 2 (CDK2), cyclinD-1, and β-actin (Proteintech, Wuhan, China). These primary antibodies were allowed to incubate overnight at 4°C. Subsequently, secondary antibodies (goat anti-rabbit) were introduced, diluted to 1:10,000, and left to incubate at 37°C for 1 h. The resulting bands were then subjected to analysis using ECL Super Signal (Pierce, Rockford, Illinois, USA).

Proteomic analysis

Total proteins of DSF/Cu-treated GC cells were extracted for protein sequencing and peptides were separated by reverse-phase high-performance liquid chromatography (RPLC). After peptide enrichment, liquid chromatography-mass spectrometry tandem analysis was performed for MS data processing and analysis. After obtaining the results of quantitative and qualitative analysis of proteins, bioinformatics analysis was performed using omics data analysis tools. The target proteins with FDX1 regulatory effects were screened and verified.

Knockout and overexpression of FDX1 gene and knockdown of WDR43

The vector for FDX1 overexpression was built utilizing pcDNA3.1 (GenePharma, Suzhou, China). Concurrently, the FDX1 knockout (KO) vector was formulated using the CRISPR/Cas9 framework (px459; (Addgene, Watertown, Massachusetts, USA). GC cells were transfected separately for 48 h with the FDX1 overexpression (pcDNA3.1) and FDX1-KO vectors. Cells transfected with non-specific pcDNA3.1-CON were used as controls. siWDR43 was obtained from RiboBio (Guangzhou, China). GC cells were transfected with siWDR43 for 48 h and control cells were transfected with non-specific siRNA.

Protein-protein interaction

The crystal structures corresponding to the two proteins were obtained from the AlphaFold database. Protein pretreatment, natural ligand state regeneration, hydrogen bond allocation optimization, protein energy minimization, and water removal treatment were performed on the obtained protein structures. Protein-protein interaction simulations of the processed proteins using a protein-protein docking module were used to determine the specific part of the FDX1 binding to WDR43. The different chains of the protein-protein interaction complex and the lowest interaction fraction are labeled with different colors.

Protein stability testing

To determine whether the protein half-life of WDR43 is altered upon FDX1 overexpression, transfected cells were treated with 50 μg/mL cycloheximide (CHX) at designated time points (0, 6, 12, and 24 h), followed by western blot analysis. FDX1-overexpressing cells were treated with 20 μM MG132 or 50 μM chloroquine (CQ) to determine whether the FDX1-mediated downregulation of WDR43 protein is associated with the ubiquitin-proteasome degradation pathway and subsequent western blot analysis was performed.

NK cell identification

NK cells (Jilin Zhongke, Changchun, China) were harvested and rinsed two times using PBS. The cell count was reduced to 10⁶/100 μL with a 0.1% bovine serum albumin (BSA) solution. Subsequently, 5–10 μL of CD3, CD16, and CD56 antibodies (Invitrogen, Carlsbad, California, USA) were included and incubated at ambient temperature for 30 min. Finally, the cells were spun down and rinsed two times with PBS before being examined using flow cytometry (BD Biosciences, San Jose, California, USA).

Acquisition of Cu-EXO

NK cells were maintained in NK cell culture medium containing 10% FBS at 37°C in 5% CO₂. The cell culture supernatants were harvested after 72 h. Exosomes were isolated using a series of ultra-fast centrifugation steps at 4°C, including spins at 300 g for 30 min, 2,000 g for 30 min, 12,000 g for 45 min, and finally at 110,000 g for 70 min post-filtration through a 0.22-μm membrane. After discarding the supernatant, the pellet was resuspended in PBS and underwent an additional spin at 110,000 g for 70 min. Subsequently, the NK cell exosomes were suspended in PBS and loaded with DSF/Cu using a freeze-thaw technique before being stored at −80°C. The quantity of exosomal proteins was assessed using a BCA protein analysis kit to determine the exosome concentration from NK cells. The Cu ion level within the exosomes was measured with a Copper Ion Content Analysis Kit (Elabscience, Wuhan, China).

Characterization of Cu-EXO

Cu-EXO was fixed with 2% PFA for 5 min. Then, the exosome suspension was placed in the grid and incubated for 10 min. The EM mesh surface was stained with 1% uranyl acetate (UA) solution for 2 min. The surplus UA solution is subsequently blotted from the mesh using filter paper and dried at room temperature. The morphology of exosomes was examined using transmission electron microscopy.

The particle size and concentration of exosomes were measured by nanoparticle tracking analysis (NTA) using an NanoFCM instrument (Flow NanoAnalyzer, Xiamen, China). The exosomes isolated by ultracentrifugation were diluted with 1 × PBS, then samples were sent for detection. After the instrument performance test with standard products was qualified, the exosome sample was loaded, and the sample gradient was diluted to avoid blocking the injection needle.

Total NK cell exosomal proteins were extracted and the expression of exosomal surface markers [TSG101 and CD9] (Abcam, Waltham, Massachusetts, USA) was detected by western blot analysis using the extracted NK cell culture medium as the control.

Cell migration, invasion, proliferation, cycle analysis, and clonal formation

GC cells were treated or transfected with DSF/Cu, overexpressed vector, FDX1-KO vector, siWDR43, or Cu-EXO. The cells were cultured after being scratched in a serum-free medium. Images were taken after 0, 24, 48, and 72 h of culture, and the scratch area was used to express the cell migration rate.

Matrigel (BD Biosciences, San Jose, California, USA) and serum-free RPMI-1640 were diluted at a 1:8 ratio and added to a Transwell chamber (Corning Life Sciences, Tewksbury, Massachusetts, USA) until Matrigel solidified. Cells treated or transfected with DSF/Cu, overexpressed vector, FDX1-KO vector, siWDR43, or CU-EXO for 24–48 h were added to the cell at 10⁵ per 100 μL, filled with 0.5 mL medium containing 10% FBS outside the cell, incubated for 24 h, and fixed with 4% paraformaldehyde. Photographs were taken after staining with 0.1% crystal violet.

The proliferation activity of GC cells was measured after treatment or transfection with DSF/Cu, overexpressed vector, FDX1-KO vector, siWDR43, or Cu-EXO. The treated and the control cells were placed in 96-well plates and cultured in medium. After 24 h, CCK-8 reagent (Meilunbio, Dalian, China) was added and incubated for 0.5–4 h. OD values were obtained at 450 nm using an enzymoleter (Tecan, Männedorf, Switzerland).

GC cell samples treated or transfected with DSF/Cu, overexpressed vector, FDX1-KO, siWDR43, or Cu-EXO were selected with a Cell Cycle Detection Kit (Meilunbio, Dalian, China). After the cells were collected, the cells were fixed with 75% alcohol and the dyeing solution was mixed according to the ratio of dyeing buffer, as follows: propyl iodide (PI) dyeing solution:RNase A = 100:5:2. Each cell sample was added to 500 μL of staining solution, the cell precipitation was suspended, and the temperature bath was protected from light at 37°C for 30 min. BD flow cytometry was used to analyze whether the cell cycle was affected.

The 1,000 treated cells were cultured in a 6-cm dish. The fluid was changed every 3–5 d. The culture was completed after 2 weeks, fixed with 95% ethanol, and stained with 0.1% crystal violet. The stained cultures were allowed to dry and photographed, and the cell colonies were counted.

Cell live/dead staining

Cell viability was analyzed using the Live/Dead Assay Kit (Abbkine, Wuhan, China). The treated cells were incubated in a dark environment with 0.5 mL of staining solution. Green fluorescence (live cells) and red fluorescence (dead cells) images were captured using a fluorescence microscope (Olympus, Hachioji, Japan).

Immunofluorescence staining

After treatment, cells were fixed with 4% paraformaldehyde and washed with PBS. The cells were subsequently permeated with 1% BSA for 1 h, washed with PBS, and antibodies were added and incubated overnight at 4°C. The cells were washed three times, then the corresponding secondary antibody was added and incubated for 1 h. DAPI working solution was added and incubated in the dark for 15 min. Finally, the sample images were captured using a fluorescence microscope.

In vitro tracking of exosomes

A DiO Kit (Meilunbio) was used to label exosomes and track the in vitro uptake of EVs, according to the manufacturer’s procedures. Cells were cultured to 70%–80% fusion in a 6-well plate to determine whether EVs could be internalized by cells. Then, exosome-labeled exosomes were added and incubated with the cells for 8 h. Direct observation was performed with laser scanning confocal microscopy [LSCM] (Olympus).

Small animal in vivo imaging

Exosomes were labeled to track the release of exosomes in vivo using a PKH-26 Kit (Beyotime, Shanghai, China) according to the manufacturer’s protocol. The exosomes were incubated with 500 μL of diluted C solution and 4 μL of PKH-26 dye solution in a dark environment at room temperature for 5 min. Then, 500 μL of 1% bovine serum albumin was added to stop the staining. The labeled exosomes were obtained by super-centrifugation of 100,000 g for 70 min and suspension with 200 μL of PBS. After bearing tumor, nude mice were injected with PKH-26 labeled Cu-EXO. An equal amount of PBS was used as a control. Nude mice were anesthetized by inhalation with 2% isoflurane. Anesthetized mice were imaged using a Bioluminescence Imaging System (λ_ex = 530 nm, λ_em = 600 nm; Biolight Biotechnology, Guangzhou, China) within 2 h after injection.

GC mouse model construction

Forty female nude mice (6–8 weeks old; Vital River, Beijing, China) were utilized for in vivo tests. Forty mice were randomly divided into 5 groups without bias. Mice were injected under the left ribcage with 8 × 10⁶–1 × 10⁷ AGS cells or AGS cells overexpressing FDX1. The mice were administered DSF/Cu or Cu-EXO 7 d after the injection for a duration of 2 weeks. Mice weights were measured and documented. The control group was given a solution of solvent (DSMO) and PBS. The mice were euthanized on the 14th d of treatment, the tumor tissue was excised, the tumor dimensions were evaluated, and a histopathologic analysis was performed. The Cu ion content in the heart, liver, spleen, lungs, and kidney tissues was detected using a Tissue Copper Ion Detection kit (Elabscience). Mice were euthanized by cervical dislocation. Another five groups of mice were treated as described above after tumor loading and the survival conditions were continuously observed and recorded for 160 days. The mice used in the experiment were obtained from the Laboratory Animal Center at Jilin University (Changchun, China) and were housed under SPF conditions. The mice were provided a standard rodent diet and water ad libitum within their cages. The study underwent review and approval by an Institutional Ethics Committee prior to start. The study protocol involving animals was sanctioned by the Institutional Animal Care and Use Committee of Jilin University (SY202306044). All procedures were carried out following the guidelines outlined in GB/T 35892-2018 for Laboratory Animals – Ethical Review Protocol and adhered to the ARRIVE guidelines.

Hematoxylin and eosin (HE) staining

The tumor and organ tissues underwent fixation in 4% paraformaldehyde for a duration of 48 h, followed by a 24 h wash in PBS at 4°C. The sample was subsequently embedded in paraffin wax and sectioned into 5-mm thick slices. These sections were stained with HE, allowing for the observation of cancer cell infiltration under a microscope.

Statistical analysis

An unpaired Student t-test and one-way ANOVA (Tukey’s multiple comparisons test) were utilized in this study. SPSS 16.0 software was used for statistical analysis. Data are presented as the mean ± standard deviation. A P value < 0.05 was regarded as statistically significant.

DSF/Cu inhibited the growth of GC cells

A DSF/Cu compound was synthesized for cellular experiments. After the synthesis of the DSF/Cu complex, energy dispersive spectroscopy (EDS) elemental tests, Fourier transform infrared spectroscopy (FTIR) detection, and X-ray photoelectron spectroscopy (XPS) detection were performed to analyze the surface elemental composition, chemical composition, and molecular structure of the DSF/Cu complex (Figure S1A–C). Initially, GC cells were exposed to various concentrations of DSF/Cu and proliferation was assessed using the CCK-8 assay. Subsequent experiments utilized concentrations that exhibited a 50% inhibition rate (Figure 1A). GES1 cells were also treated with DSF/Cu; CCK-8 detection proved that DSF/Cu produced a killing effect on normal cells at a concentration of 3 μM (Figure S2A). Moreover, the clonogenic potential of GC cells post-DSF/Cu treatment was evaluated, showing a significant inhibition of GC cell clonogenesis (Figure 1B). The immunofluorescence results showed that the degree of DLAT aggregation increased after DSF/Cu treatment of GC cells (Figure 1C). These findings indicated that DSF/Cu effectively hinders GC cell proliferation and promotes the occurrence of cuproptosis. By investigating the expression of cuproptosis-related genes, elevated levels of FDX1 and DLAT proteins were demonstrated in GC cells compared to GES1, as confirmed by western blot analysis (Figure 1D, E). qPCR results also revealed increased FDX1 and DLAT gene expression in AGS cells compared to GES1, while LIAS gene expression was decreased (Figure 1F). The above results demonstrated the patterns of key gene expression for cuproptosis in different GC cells. To distinguish DSF/Cu-induced cuproptosis from other cell death mechanisms, gene expression profiles associated with autophagy, ferroptosis, and apoptosis in GC cells post-treatment were analyzed. The qPCR data revealed no significant changes in the expression of these genes following DSF/Cu treatment (Figure 1G–I). After treating GC cells with the Cu chelator, TTM, the necrosis inhibitor, Nec-1, the ferroptosis inhibitor, Fer-1, the ROS inhibitor, NAC, and the apoptosis inhibitor, Z-VAD-FMK, the cells were subsequently treated with DSF/Cu. The CCK-8 assay revealed that only TTM treatment reversed inhibition of GC cell proliferation (Figure S2B). Western blot results indicated that TTM was the sole treatment altering the expression of cuproptosis-related genes (Figure S2C). Cell live/death experiments demonstrated that TTM effectively rescued cuproptosis induced by DSF/Cu (Figure S2D). Therefore, the results suggested that DSF/Cu induces cuproptosis in GC cells by modulating the expression of the cuproptosis-related gene, FDX1.

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Figure 1

Expression patterns of genes associated with cuproptosis in GC cells. (A) Cell proliferation after DSF/Cu treatment was detected by CCK-8 (n = 3). (B) The clonogenesis ability of 1 μM DSF/Cu-treated cells for 24 h was detected by a plate cloning experiment (n = 3) and statistical analysis of plate cloning results (scale bar, 10 mm). (C) Immunofluorescence assay (n = 3) was used to detect oligomerization of DLAT in cells treated with 1 μM DSF/Cu for 24 h (scale bar, 50 μm). (D) Western blot detection of FDX1 and DLAT gene expression levels in GES1, AGS, and MKN45 cells (n = 3). (E) Statistical analysis of western blot. (F) qPCR was used to detect the levels of FDX1, DLAT, and LIAS gene expression in GES1, AGS, and MKN45 cells (n = 3). (G) The levels of LC3A, LC3B, PINK1, P62, BECLIN, and PARKIN gene expression in GC-and DSF/Cu-treated GC cells were detected by qPCR (n = 3). (H) The levels of GPX4, ACSL4, SLC7A11, NOX1, ALOX15, and FTH1 gene expression in GC-and DSF/Cu-treated GC cells were detected by qPCR (n = 3). (I) qPCR was used to detect the levels of P53, BAX, BCL2, and CASPASE3 gene expression in GC-and DSF/Cu-treated GC cells (n = 3). Data are expressed as the mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001, indicating statistically significant differences.

Protein sequencing after DSF/Cu treatment of GC cells

Protein sequencing was performed on GC cells treated with DSF/Cu to determine the regulatory role of DSF/Cu-induced cuproptosis in GC cells. A total of 21 significantly differentially expressed proteins (DEPs) were identified with 4 proteins upregulated and 17 downregulated. Volcano plots and heatmaps visually represented the differentially expressed genes [DEGs] (Figures 2A and S3A). Figure S3B shows the sub-localization of DEGs in cells. Enrichment analysis of these proteins highlighted the involvement in cell surface signaling and cytokine-related pathways (Figure 2B, C). Gene Ontology (GO) and Cluster of Orthologous Groups (COG) analyses indicated that these genes were primarily associated with cellular processes and biological regulation (Figure 2D, E). Bioinformatic analysis revealed that the WDR43 protein was linked to the regulation of cellular component biogenesis and metabolic processes. WDR43 also had a significant correlation with the prognosis of GC patients (Figure 2F). Moreover, bioinformatics analysis showed that WDR43 was highly expressed in GC tissues (Figure 2G). The mass spectrum of WDR43 is presented in Figure S3C. Alphafold was utilized to predict the structure of the FDX1 protein with protein binding predictions indicating interaction sites between FDX1 and WDR43 proteins (Figure S3D, E). Point mutations were performed on the predicted binding sites (Figure S4A–C). The western blot results showed that when FDX1 was overexpressed, the expression of WDR43 rebounded after simultaneous point mutations at all three sites (Figure S4D). The levels of WDR43 expression in GC cells were assessed using qPCR and western blot techniques. The qPCR results revealed increased WDR43 expression in GC cells compared to GES1 cells (Figure 2H), while DSF/Cu treatment resulted in increased WDR43 expression in cancer cells (Figure 2I). Western blot analysis also confirmed high WDR43 expression in GC cells (Figure 2J, K). These findings suggested a potential role for WDR43 in the DSF/Cu-induced cuproptosis pathway in GC cells.

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Figure 2

Protein sequencing analysis of GC cells treated with DSF/Cu. (A) Volcano map analysis of differentially expressed proteins. (B) Protein domain enrichment analysis of biological process. (C) Protein domain enrichment analysis of cellular component. (D) GO annotation analysis. (E) COG/KOG functional classification analysis. (F) Prediction of the prognostic correlation between FDX1 and WDR43 in patients with GC. (G) Bioinformatics analysis predicts the expression of differentially expressed genes in GC tissues. (H) The level of WDR43 expression in GES1, AGS, and MKN45 cells was detected by qPCR (n = 3). (I) qPCR was used to detect the expression of WDR43 in GC cells and 1 μM DSF/Cu-treated GC cells (n = 3). (J) Western blot analysis of WDR43 expression in GES1, AGS, and MKN45 cells (n = 3). (K) Statistical analysis of western blot. Data are expressed as the mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 indicated statistically significant differences.

Verifying the regulation of FDX1 on cuproptosis sensitivity of GC cells

Studies have shown that the level of cuproptosis-related genes may affect the occurrence of cuproptosis in cancer cells^22,23. This study aimed to determine the impact of altering FDX1 gene expression on the sensitivity of GC cells to DSF/Cu treatment and investigate the relationship between FDX1 and WDR43. Overexpression and knockout vectors for FDX1 were generated using the CRISPR/Cas9 system. qPCR analysis post-FDX1 overexpression showed a significant increase in FDX1 expression (Figure 3A). The CCK-8 assay revealed that DSF/Cu treatment after FDX1 overexpression led to a notable inhibition of GC cell growth compared to DSF/Cu treatment alone (Figure 3B). Western blot analysis showed that FDX1 expression increased, WDR43 expression decreased, and the level of DLAT oligomerization increased after FDX1 overexpression (Figures 3C and S5A). The protein half-life assay revealed that FDX1 overexpression reduced the stability of WDR43 protein and shortened the half-life (Figure S6A, B). After treatment of FDX1-overexpressing GC cells with MG132, FDX1-mediated downregulation of WDR43 protein was shown to be related to the proteasome degradation pathway (Figure S6C, D). Moreover, DSF/Cu treatment after FDX1 overexpression reduced the migratory and invasive capabilities of GC cells (Figure 3D–G). In addition, FDX1 overexpression induced G1 phase cell cycle arrest, while DSF/Cu treatment caused S phase cell cycle arrest (Figure 3H, I).

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Figure 3

Effects of FDX1 overexpression on GC cells. (A) qPCR was used to detect the level of FDX1 gene expression in overexpressed FDX1 GC cells (n = 3). (B) CCK-8 detected the proliferation of non-treated GC cells (CON), GC cells overexpressing FDX1 (+FDX1), GC cells treated with 1 μM DSF/Cu for 24 h, and GC cells overexpressing FDX1 and treated with DSF/Cu [Cu + FDX1] (n = 3). (C) Western blot analysis of the levels of FDX1, WDR43, and DLAT in FDX1 overexpressed GC cells (n = 3). (D) Scratch healing assay to detect cell migration (n = 3) (scale bar, 500 μm). (E) Statistical analysis of the results of scratch healing experiments (n = 3). (F) Invasion assay to detect the invasion ability of cells (n = 3) (scale bar, 100 μm). (G) Statistical analysis of the results of invasion experiments (n = 3). (H) Cell cycle was measured by flow cytometry (n = 3). (I) Statistical analysis of cell cycle test results (n = 3). Data are expressed as the mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001, indicating statistically significant differences.

A CRISPR/Cas9 system was used to knock out FDX1, as shown in Figure S7A, B. Subsequent qPCR analysis confirmed the reduction in FDX1 expression upon knockout, as depicted in Figure 4A. Interestingly, CCK-8 results revealed that the proliferation capacity of GC cells remained unaffected when FDX1 was knocked out and DSF/Cu was added compared to DSF/Cu treatment alone (Figure 4B). Western blot experiments further demonstrated a decrease in FDX1 expression, an increase in WDR43 expression after FDX1 knockout, and the level of DLAT oligomerization decreased (Figures 4C,S5B and S7C). Notably, the migration and invasion abilities of GC cells were enhanced upon treatment with DSF/Cu following FDX1 knockout (Figure 4D–G). Moreover, while DSF/Cu treatment led to cell cycle arrest in the S phase, knocking out FDX1 did not significantly alter this effect (Figure 4H, I). These findings suggested that FDX1 influences WDR43 gene expression, the increase in FDX1 expression leads to a decrease in WDR43 expression in GC cells, and upregulation of FDX1 can enhance the sensitivity of GC cells to DSF/Cu treatment.

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Figure 4

Effect of FDX1 knockout on GC cells. (A) qPCR was used to detect the level of FDX1 gene in GC expression cells with FDX1 knockout (n = 3). (B) CCK-8 detected the proliferation of normal GC cells (CON), GC cells knocked out FDX1 (KOFDX1), GC cells treated with 1 μM DSF/Cu for 24 h, and GC cells knocked out FDX1, then treated with DSF/Cu [Cu + KOFDX1] (n = 3). (C) Western blot detection of the levels of WDR43 and DLAT in GC cells after FDX1 knockout (n = 3). (D) Scratch healing assay to detect cell migration (n = 3) (scale bar, 500 μm). (E) Statistical analysis of the results of scratch healing experiments (n = 3). (F) Invasion assay to detect the invasion ability of cells (n = 3) (scale bar, 100 μm). (G) Statistical analysis of the results of invasion experiments (n = 3). (H) Cell cycle was measured by flow cytometry (n = 3). (I) Statistical analysis of cell cycle test results (n = 3). Data are expressed as the mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001 and ****P < 0.0001, indicating statistically significant differences.

Effects of decreased expression of WDR43 on GC cells

The current study aimed to determine the impact of changes in WDR43 expression on GC cells because WDR45 is a downstream gene of FDX1 known to have an inverse relationship with FDX1 expression. Following the synthesis of siWDR43 and knockdown of WDR43, western blot analysis confirmed a decrease in WDR43 expression (Figure 5A, B). Subsequent CCK-8 assay results showed a reduction in the proliferation capacity of GC cells post-WDR43 knockdown (Figure 5C). Moreover, decreased WDR43 expression led to inhibition of invasion and migration abilities in GC cells (Figure 5D–G) and induced G1 phase cell cycle arrest (Figure 5H, I). Western blot analysis also revealed an upregulation of cell cycle-related proteins (CDK2 and cyclinD-1) with reduced WDR43 expression (Figure 5J, K). In addition, the results of immunofluorescence and western blot indicated that the changes in WDR43 expression did not affect the level of DLAT oligopolization (Figure S8A, B). Therefore, WDR43 may not directly regulate the occurrence of cuproptosis in GC. These results indicated that downregulation of WDR43 affects the growth of GC cells and suggested that the FDX1/WDR43 axis has a crucial role in regulating cell cycle, migration, and invasion in these cells.

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Figure 5

Effect of WDR43 knockdown on GC cells. (A) Western blot detection of WDR43 protein expression in GC cells with WDR43 knockdown (n = 3). (B) Statistical analysis of western blot. (C) CCK-8 detected the proliferation of non-treated GC (CON) and GC cells (siWDR43) after knocking down WDR43 (n = 3). (D) Invasion assay to detect the invasion ability of cells (n = 3) (scale bar, 100 μm). (E) Statistical analysis of the results of the invasion experiment (n = 3). (F) Scratch healing assay to detect cell migration (n = 3) (scale bar, 500 μm). (G) Statistical analysis of the results of scratch healing experiments (n = 3). (H) Cell cycle was measured by flow cytometry (n = 3). (I) Statistical analysis of cell cycle test results (n = 3). (J) Western blot analysis was performed to detect the levels of CDK2, cyclinD-1, and DLAT gene expression in GC cells with FDX1 knockout (n = 3). (K) Statistical analysis of western blot. Data are expressed as the mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001, indicating statistically significant differences.

DSF/Cu was loaded into NK cell exosomes to treat GC cells

DSF/Cu was encapsulated into NK cell exosomes, which are known for high biosafety, cellular uptake efficiency, and specific targeting abilities to further investigate enhancing the therapeutic potential of DSF/Cu. The efficacy of NK cell exosomes loaded with DSF/Cu (Cu-EXO) was evaluated in vivo and in vitro. Human NK cells were cultured (Figure S9A) and characterized by NK cell surface markers (Figure S9B). The exosomes were isolated and loaded with DSF/Cu. The morphology of Cu-EXO was examined using transmission electron microscopy (Figure 6A), while particle size analysis was performed to determine the size of Cu-EXO (Figure 6B). Exosome surface markers were identified through western blot analysis (Figure 6C). The concentration of Cu²⁺ ion in Cu-EXO was quantified using a kit method (Figure S10A) and the treatment dosage of Cu-EXO was determined based on this ion concentration. The accuracy of the Cu²⁺ ion content analysis kit method was verified through the spiking recovery experiment (Figure S10B) and it was confirmed by HPLC that DSF was also successfully loaded into exosomes (Figure S10C). Given the pivotal role of NK cells in immune regulation, the pro-inflammatory impact of Cu-EXO on GC cells was assessed using qPCR. The results indicated a reduction in the levels of inflammatory factor (TNF, IL-6, and IL-8) expression in GC cells following Cu-EXO treatment (Figure S11A). Subsequent experiments involving GC cells revealed that Cu-EXO significantly suppressed the proliferation of GC cells, supported by CCK-8 results (Figure 6D). Further analysis after Cu-EXO treatment showed a notable increase in FDX1 expression and an increase in the level of DLAT oligomerization, as evidenced by qPCR and western blot results (Figures 6E, F, and S11B). In addition, treatment of GES1 and AGS cells with NK exosomes labeled with DiO dye demonstrated a higher affinity of NK exosomes towards GC cells, which led to internalization (Figure S12A, B). In addition, Cu-EXO treatment led to a reduction in migration ability, invasion rate, and induced cell cycle arrest among GC cells in the S phase (Figure 6G–L). These findings collectively suggested that Cu-EXO exhibits promising efficacy in inhibiting GC cell proliferation and inducing cuproptosis in vitro.

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Figure 6

DSF/Cu loaded into NK cell exosomes for the treatment of GC cells. (A) The morphology of NK cell exosomes was observed under transmission electron microscopy (scale bar, 200 nm). (B) Exosome particle size analysis of Cu-EXO. (C) Western blot detection of Cu-EXO exosome surface markers (TSG101 and CD9). (D) The proliferation of normal GC cells (CON), GC cells treated with 4 mg/mL of NK cell exosomes (EXO) for 24 h and GC cells treated with 4 mg/ml of DSF/Cu-loaded exosomes (Cu-EXO) for 24 h was detected by CCK-8 (n = 3). (E) qPCR was used to detect the levels of FDX1 and DLAT gene expression in Cu-EXO treated GC cells (n = 3). (F) Western blot analysis of FDX1, DLAT, and WDR43 gene expression in Cu-EXO treated GC cells (n = 3). (G) Scratch healing assay to detect cell migration (n = 3) (scale bar, 500 μm). (H) Statistical analysis of the results of scratch healing experiments (n = 3). (I) Invasion assay to detect the invasion ability of cells (n = 3) (scale bar, 100 μm). (J) Statistical analysis of the results of invasion experiments (n = 3). (K) Cell cycle was measured by flow cytometry (n = 3). (L) Statistical analysis of cell cycle test results (n = 3). Data are expressed as the mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001, indicating statistically significant differences.

Cu-EXO can inhibit GC in vivo

The therapeutic effects of DSF/Cu and Cu-EXO in GC mouse models were further investigated by dividing the mice into five groups. These groups were constructed with AGS cells and overexpressing FDX1 of AGS cells, then treated with DSF/Cu or Cu-EXO (Figure 7A). In vivo imaging results showed that Cu-EXO labeled with DiR dye injected into the subcutaneous skin of mice with GC led to consistent fluorescence intensity at the tumor site within 1 h, indicating sustained drug retention and release at the tumor site over time (Figure 7B). After injecting Cu-EXO into the tail veins of mice, fluorescence at the tumor site was shown to increase over time within 24 h, proving that Cu-EXO can accumulate at the tumor site (Figure S13A, B). After 3 weeks of treatment, mouse tumors were removed, which revealed that overexpression of FDX1 and treatment with DSF/Cu and Cu-EXO effectively inhibited the growth of GC tumors (Figure 7C, D). In addition, mice treated with DSF/Cu and Cu-EXO exhibited less weight change compared to controls (Figure 7E). Analysis of mouse tumors by western blot demonstrated that DSF/Cu and Cu-EXO treatment following FDX1 overexpression significantly increased the expression of FDX1 and decreased the expression of WDR43 (Figure 7F–H). HE staining of mouse tumors and organs confirmed that Cu-EXO effectively inhibited tumors with no apparent adverse effects on mouse organs, demonstrating good biosafety (Figure S14A, B). The Cu content in the main organs of the mice in the treatment group was not significantly higher than the control group, proving that DSF/Cu and Cu-Exo treatment did not cause destruction of Cu homeostasis and obvious systemic toxicity (Figure S15A). In addition, long-term feeding and monitoring of GC mice treated with the same treatment were performed and it was found that the long-term survival rate of mice in the Cu-EXO treatment group was higher compared to the control group (Figure S15B). The above experimental results proved that DSF/Cu and Cu-EXO have a good inhibitory effect on tumor growth in mice and better biocompatibility compared to Cu-EXO.

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Figure 7

DSF/Cu and Cu-EXO inhibit tumor growth in vivo. (A) Schematic diagram of experimental procedures in mice. The naked mice were divided into 5 groups (n = 8), which were treated with PBS and DMSO after AGS tumor bearing (CON), 10 mg/kg of DSF/Cu after AGS tumor bearing (Cu), and 100 mg/kg of Cu-EXO after AGS tumor bearing (Cu-EXO). AGS cells overexpressing FDX1 were treated with 10 mg/kg of DSF/Cu (Cu+FDX1) and 100 mg/kg Cu-EXO (EXO+FDX1). (B) In situ injection of DiR-labeled exosomes in nude mice and in vivo imaging detection. (C) Tumor volume in tumor-bearing mice (n = 8). (D) Tumor volume analysis (n = 8). (E) Weight changes in tumor-bearing mice after initiation of treatment (n = 8). (F) The levels of FDX1 and WDR43 gene expression in mouse tumor tissues were detected by qPCR (n = 3). (G) Western blot analysis of FDX1, DLAT, and WDR43 protein expression in mouse tumor tissues (n = 3). (H) Statistical analysis of western blot. Data are expressed as the mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001, indicating statistically significant differences.