Evaluating the prognostic value of cuproptosis-related genes and characterizing PDE3B’s role in gastric cancer: integrative bioinformatics analysis and experimental validation

Introduction

Due to widespread lifestyle modifications and the successful eradication of Helicobacter pylori, a consistent downward trajectory in gastric cancer incidence has been observed (1). However, recurrence and mortality rates persist as major clinical challenges (2). In China, gastric cancer contributes to 12.5% of cancer deaths (third highest), with mortality rates exceeding the global average by 110% (3). In 2022, cuproptosis was first discovered and proposed by Tsvetkov et al., which distinctly differs from previously documented mechanisms and is mediated by copper ions (4). Cu²⁺ is delivered intracellularly through specialized transport carriers such as elesclomol, reduced to Cu⁺ by FDX1. Then, copper ions directly coordinate with lipoylated proteins on mitochondrial enzymes leading to irreversible tricarboxylic acid cycle dysfunction. In addition, the decomposition of Fe-S cluster proteins is significantly inhibited in the presence of copper ions. As a result of these combined effects, cells experience toxic stress, culminating in cell death. Cuproptosis represents a novel form of cellular demise that distinctly diverges from other established modes of cell death (5). Recent studies (6-10) link cuproptosis to disease prognosis and treatment response, making cuproptosis induction a promising therapeutic strategy.

Here, we analyzed cuproptosis-related gene (CRG) expression in gastric cancer to construct a prognostic model. Through in vitro and in vivo experiments, we validated the role of a key CRG (PDE3B) in tumor progression. Our results demonstrate that targeting PDE3B potentiates elesclomol-CuCl₂ (ES-Cu)-induced cuproptosis, offering a novel therapeutic approach. We present this article in accordance with the ARRIVE and MDAR reporting checklists (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-1-0070/rc).

Methods

Patients and sources of data

Twenty-two paired gastric cancer and surrounding normal tissue were obtained from surgical specimens at The First Affiliated Hospital of Nanjing Medical University between August 2023 and August 2024. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study has been reviewed and approved by the Ethics Committee of The First Affiliated Hospital of Nanjing Medical University (No. 2020-SR-383). Informed consent was signed by all patients prior to their participation in the study. All enrolled patients were treatment-naive (no prior chemotherapy, radiotherapy, or targeted therapy) before surgery and provided written informed consent. RNA-seq data from 412 gastric adenocarcinoma (STAD) samples and 36 normal gastric tissues were downloaded from The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/projects/TCGA-STAD).

Functional profiling of differential genes and immune infiltration analysis

Functional annotation of differential genes was performed via Gene Ontology (GO) term enrichment and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway mapping. Infiltration levels of 22 immune cell types were quantitatively estimated using the CIBERSORT algorithm. The association between oncogene expression and immune cell infiltration was quantified using Pearson correlation analysis.

Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA)

In this study, gene sets were obtained from the Molecular Signatures Database (MSigDB), and the GSVA algorithm was employed to generate comprehensive scores for each gene set, enabling the evaluation of potential biological functional changes across different samples. GSEA was employed to further investigate the differences in signaling pathways between the high and low expression groups.

Nomogram model and miRNA network construction, transcriptional regulation analysis of key genes

Develop a nomogram model based on CRG expression and clinical features to predict overall survival (OS). The scores of all influencing factors were aggregated to determine the predictive value. In this study, the R package “RcisTarget” was utilized to predict potential transcription factors. Besides the motifs annotated in the source data, additional annotation files were generated based on motif similarity and gene sequence information. A nomogram model was developed the area under the receiver operating characteristic curve (AUC) for all pairwise combinations of motif sets. We retrieved the miRNAs associated with key genes from the miRcode database to further investigate whether these miRNAs regulate the transcription or degradation of certain risk genes.

Cell culture, vector construction and cell transfection and chemicals

Human gastric epithelial cell line GES-1, human gastric cancer cell line HGC-27 and human gastric cancer cells SNU-484 were obtained from Zhejiang Meisen Cell Technology Co. Ltd. (China). All cell lines were maintained in complete RPMI-1640 or DMEM, supplemented with 10% fetal bovine serum (FBS, Gibco, 10270-106, USA), 100 U/mL penicillin, and 100 µg/mL streptomycin and incubation conditions maintained at 37 ℃ with 5% CO₂. Small interfering RNA and lentiviral infection techniques were employed to knock down PDE3B in gastric cancer cells. The siRNA was synthesized and supplied by GenePharma Company (Shanghai, China). Cells were seeded into 6‑well plates at 2×10⁵ cells/well and cultured overnight to reach 60% confluence. Transfection was performed using Lipo8000™ Transfection Reagent (Beyotime, C0533, China) according to the manufacturer’s instructions. Briefly, 100 pmol siRNA was mixed with 5 µL of transfection reagent in Opti‑MEM™ medium, incubated for 15 min at room temperature, and then added to the cells. After 48 h, cells were harvested for RNA extraction and Western blotting (WB) to assess knockdown efficiency. Sequences of siRNAs used were as follows: si-PDE3B-1 forward 5'-CAGGUUAUGUAUACCUUAUTT-3', reverse 5'-AUAAGGUAUACAUAACCUGTT-3', si-PDE3B-2 forward 5'-GGGCAAUGCACCUAAUACUTT-3', reverse 5'-AGUAUUAGGUGCAUUGCCCTT-3'. For stable transfection, HGC27 cells were first seeded in 6-well plates, followed by infection with lentivirus carrying PDE3B knockdown constructs. After 48–72 hours, 1 mg/mL puromycin was added for selection. The surviving cells were continuously cultured to establish stably transfected knockdown cell lines. The efficiency of both knockdown approaches was further validated by quantitative real-time polymerase chain reaction (qRT-PCR) and WB analysis. The principal chemical reagents included Elesclomol (MedChemExpress, HY-12040, USA), Copper (II) chloride (Aladdin, C106775, China), and ammonium tetrathiomolybdate (TTM) (Macklin, A828261, China).

RNA extraction and qRT-PCR

Samples were homogenized in TRIzol reagent (Invitrogen, 15596026, USA), followed by phase separation with chloroform. RNA was precipitated with isopropanol, washed with 75% ethanol, and dissolved in RNase-free water. RNA concentration and purity were determined using a NanoDrop spectrophotometer (A260/A280 ratio between 1.8 and 2.0). RNA was reverse transcribed into cDNA using the PrimeScript RT Reagent Kit (Takara, RR037A, Japan), and the cDNA was stored at −20 ℃. qRT‑PCR was performed using a SYBR^® Green Kit (Yeasen, 11143ES, China) mix on a real‑time PCR system. The thermal cycling conditions were: initial denaturation at 95 ℃ for 5 min, followed by 40 cycles of 95 ℃ for 10 s and 60 ℃ for 30 s. A melting curve analysis was conducted to confirm amplification specificity. Each sample was run in triplicate. GAPDH was utilized as a consistent internal control across all experiments, and relative quantification (2^−ΔΔCt) was applied to compare expression fold changes between experimental groups. The primer sequences were as follows: PDE3B-forward, 5'-TCCTGGCTTACAGCAGATCCAC-3', PDE3B- reverse, 5'-GGCAGCCATAACTCTCATCAGG-3'. GAPDH-forward, 5'-TGGAGAAACCTGCCAAGTATG-3', GAPDH-reverse, 5'-GGAGACAACCTGGTCCTCAG-3'.

WB

Cells or tissues were lysed in RIPA buffer (Beyotime, P0013C). Protein concentration was determined using a BCA protein assay kit (Epizyme, ZJ101, China). Equal amounts of protein were separated by 10% SDS‑polyacrylamide gel electrophoresis (SDS‑PAGE) and then transferred onto a polyvinylidene difluoride (PVDF) membrane. The membrane was blocked with 5% bovine serum albumin (BSA) in Tris‑buffered saline containing 0.1% Tween‑20 (TBST) for 1 h at room temperature. Subsequently, the membrane was incubated overnight at 4 ℃ with primary antibodies against target proteins. After washing three times with TBST, the membrane was incubated with horseradish peroxidase (HRP)-conjugated secondary antibody for 1 h at room temperature. The strip was visualized using the ECL development method. The following antibodies were used for WB experiments: FDX1 (Abcam, ab108257, USA), HSP70 (Abmart, T55496, China), DLAT (Proteintech, 13426-1-AP, China), PDE3B (Proteintech, 25290-1-AP), GAPDH (Proteintech, 10494-1-AP), AMPK (Abmart, T55326), p-AMPK (Abmart, T55608), FOXO1(Abmart, T55376), p-FOXO1 (Abmart, TA3461).

Cell proliferation and viability assay

Depending on experimental requirements, 2,000 or 5,000 cells were seeded in 96-well plates. The cells were cultured for a duration ranging from 24 to 96 hours or treated with drugs for 48 hours. Then, 10 µL of CCK-8 solution (Yeasen, 40203ES76) was added to each well and incubated for 2 h at 37 ℃. Optical density readings were taken at 450 nm with reference measurement. Cell viability was calculated as the percentage relative to the control group after subtracting the blank.

Immunohistochemistry (IHC)

Tissue sections were deparaffinized in xylene and rehydrated through a graded ethanol series (100%, 95%, 80%, 70%) followed by washing with distilled water. Antigen retrieval was performed by heating the sections in EDTA buffer (pH 8.0) for 15–20 min. The sections were then cooled to room temperature and washed three times with phosphate‑buffered saline (PBS). Endogenous peroxidase activity was blocked by incubating the sections with 3% hydrogen peroxide (H₂O₂) in methanol for 10–15 min at room temperature in the dark. After washing, non‑specific binding was blocked with 5% normal goat serum (or 5% bovine serum albumin) in PBS for 1 h at room temperature. Then sections were immunostained with primary antibody PDE3B (Proteintech, 25290-1-AP, China) overnight at 4 ℃. After three washes with PBS (5 min each) sections were incubated with HRP-conjugated secondary antibody (Proteintech, SA00001-2, China), followed by DAB substrate for chromogenic detection and counterstained with Harris hematoxylin. Finally, comparative analysis of target protein expression in matched tumor-normal pairs.

Immunofluorescence and transmission electron microscopy (TEM)

For immunofluorescence, dispense 10⁴ cells/well in 24-well format. After overnight adhesion, cells were treated with ES-Cu for 12 h, then stained with Mitotracker Red (Thermo Fisher Scientific, M7512, USA) at 37 ℃. After removing the culture medium, cells were washed twice with PBS and fixed with 4% paraformaldehyde (PFA) for 15 min, permeabilized with 0.1% Triton X‑100 in PBS for 10–15 min at room temperature. The coverslips were then incubated overnight at 4 ℃ with primary antibody diluted in blocking buffer. After three washes with PBS (5 min each), cells were incubated with the appropriate fluorophore‑conjugated secondary antibody (Abcam, ab6717) diluted in blocking buffer for 1 h at room temperature in the dark. Nuclei were counterstained with DAPI (Beyotime, C1006) for 10 min. Finally, the coverslips were washed three times with PBS and mounted onto glass slides using an anti-fade mounting medium. Images were captured using a fluorescence microscope. For TEM analysis, cells were gently harvested from the culture dish using a cell scraper. They were subsequently fixed with 2.5% glutaraldehyde solution for 2 h at 4 ℃, then post-fixed with 1% osmium tetroxide for 1 h. Samples were embedded in Spurr’s resin and polymerized at 60 ℃ for 48 h after dehydration through a series of ethanol. After sectioning, samples were observed under electron microscopy and images were captured.

5-ethynyl-2’-deoxyuridine (EdU) staining assay

Control and transfected gastric cells were seeded in 24-well plates respectively, and treated with ES-Cu for 24 h. Appropriate concentrations of the EdU dye (Beyotime, C0075, China) were added and co-incubated with the samples for a period of 2 h under controlled conditions. After EdU removal, cells were fixed with 4% PFA for 10 min and permeabilized with 0.5% Triton X-100 for 10 min. Then, the cells were incubated with the Click Reaction Buffer in a light-protected environment. Nuclear staining procedure was conducted utilizing Hoechst. The laser confocal microscopy enables the observation and acquisition of images.

Cell cycle assay

SNU484 or HGC27 cells (5×10⁴ cells/well) were plated in 6-well culture plates and allowed to adhere for 24 h before exposure to ES-Cu for 48 h. Following this, cells were trypsinized, pelleted, and fixed in ice-cold 75% ethanol. Add 1 mL of DNA Staining Solution (Liankebio, CCS012, China) to the flow tube, vortex to mix thoroughly, and incubate at room temperature protected from light for 30 minutes. Flow cytometry data acquisition was performed according to the manufacturer’s protocol after appropriate sample preparation.

Xenograft animal model

This experiment was conducted at the Animal Experiment Center of Nanjing Medical University. All animal experiments were conducted using specific pathogen-free (SPF) BALB/c nude male mice (age: 28±2 days, weight: 18–22 g) obtained from Vital River Laboratories. Following trypsinization and viability assessment, both scramble control and PDE3B-knockdown HGC27 cells were adjusted to 2×10⁶ cells in 100 µL PBS and injected bilaterally into the subcutaneous inguinal fat pads of anesthetized mice. Upon reaching the predetermined tumor volume threshold (100±5 mm³), mice were randomized using stratified block randomization (by tumor size) into treatment (n=5) and control (n=5) groups. The experimental group received intratumoral injections of ES-Cu (10 mg/kg in 100 µL PBS), while controls received an equal volume of PBS. Treatment was administered at a frequency of once every three days. After 15 days of treatment, the nude mice were humanely euthanized to procure tumor specimens for subsequent analysis. The animals were euthanized by cervical dislocation under anesthesia induced with an intraperitoneal injection of 1% sodium pentobarbital (100 mg/kg). Experiments were performed under a project license (No. IACUC-2404033) granted by the Ethics Committee of Nanjing Medical University, in compliance with the National Research Council Guide for the Care and Use of Laboratory Animals.

Statistical analysis

All experiments were conducted with three independent replicates, and all experimental data were expressed as mean ± standard deviation (SD). Data were analyzed using R software and GraphPad Prism 9.5 Software. P<0.05 was considered to indicate statistical significance.

Results

Identification of the cuproptosis-related genes in gastric cancer

We retrieved CRGs from prior literature (4,11). Correlation analyses of CRGs were conducted separately in control (n=36) and tumor samples (n=412) (Figure 1A,1B) from the TCGA-STAD cohort. Comparative transcriptomics revealed a total of 22 up-regulated genes and 5 down-regulated genes (adjusted P<0.05, |log₂FC|>1) between two groups (Figure 1C). Functional enrichment analysis showed these genes were overrepresented in copper ion binding (GO: 0005507), mitochondrial matrix (GO: 0005759) and central carbon metabolism (KEGG: 01200), all mechanistically linked to cuproptosis (Figure 1D).

Figure 1 Differential expression and pathway enrichment analysis of CRGs in gastric cancer. (A,B) Heat maps show the correlation of CRGs in (A) normal and (B) tumor gastric tissue. (C) Distinct expression profiles of 27 CRGs in gastric tumor versus adjacent normal mucosa. (D) Functional enrichment analysis of 27 CRGs in gastric cancer. ns, not significant; *, P<0.05; **, P<0.01; ***, P<0.001. CRGs, cuproptosis-related genes; GO, Gene Ontology.

Analysis of key genes related to cuproptosis and immune infiltration

To further identify key genes among CRGs that influence gastric cancer progression, we analyzed the survival outcomes of these 27 differentially expressed CRGs (Figure 2). The results demonstrated statistically significant differences in survival between high- and low-expression groups stratified by the median value for PDE3B, MAP2K2, and CP. These three genes were thus identified as key genes for further investigation.

Figure 2 Survival analysis of 27 CRGs in gastric cancer. CRGs, cuproptosis-related genes.

The immunological landscape of the tumor microenvironment (TME) fundamentally governs both diagnostic biomarker discovery and therapeutic response. Spatial immune infiltration and the heatmap illustrating correlations among immune cells were presented in Figure 3A,3B. Gastric cancer patients exhibited elevated expression levels of naive B cells, activated CD4 memory T cells, and M0 and M1 macrophages (Figure 3C). All three key genes (PDE3B, MAP2K2, and CP) demonstrated strong correlations with specific immune cell populations (Figure 3D-3F).

Figure 3 Analysis of immune cell infiltration. (A) Analysis of immune cell infiltration in normal and tumor gastric tissues. (B) Pearson correlation matrix of tumor-infiltrating immune cell subsets. (C) Comparison of immune cells in normal and gastric cancer tissues. (D-F) Correlation analysis of key genes (D: CP; E: MAP2K2; F: PDE3B) with immune cell infiltration. ns, not significant; *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001. NK, natural killer; Tregs, regulatory T cells.

Analysis of signaling pathways, prognostic model, and gene regulation associated with key genes

We subsequently examined the signaling pathways associated with the three key genes (CP, MAP2K2, and PDE3B) to elucidate the potential molecular mechanisms influencing gastric cancer progression. GSVA analysis revealed that the high CP expression was significantly enriched in the IL6-JAK-STAT3 signaling pathway and apoptosis-related pathways (Figure 4A). MAP2K2 exhibited enrichment in the reactive oxygen species (ROS) pathway and the p53 signaling pathway (Figure 4B). Additionally, the highly expressed PDE3B gene demonstrated enrichment in UV response down (UV_RESPONSE_DN) and IL2-STAT5 signaling (Figure 4C). GSEA demonstrated that CP upregulation correlated with cAMP signaling, Foxo signaling, and Ras signaling (Figure 4D). Overexpression of MAP2K2 was linked to the enrichment of apoptosis, cytosolic DNA-sensing, and nucleotide metabolism pathways (Figure 4E). MAPK signaling, PPAR signaling, and Wnt signaling are associated with increased PDE3B expression (Figure 4F). These findings suggest that these key genes may influence gastric cancer progression through pathway modulation.

Figure 4 Analysis of three key genes signaling pathways. (A-C) GSVA analysis of CP, MAP2K2, and PDE3B. (D-F) GSEA analysis of CP, MAP2K2, and PDE3B. GSEA, gene set enrichment analysis; GSVA, gene set variation analysis; HExp, high expression; LExp, low expression.

By integrating clinical characteristics with key genetic biomarkers, we developed a clinically applicable predictive model. First, we evaluated the associations between the expression levels of CP, MAP2K2, PDE3B and the clinicopathological characteristics of gastric cancer patients (Figure 5A-5U). The results showed that the expression of all three genes was not significantly correlated with patient age, gender, or distant metastasis. However, CP expression was significantly correlated with G tumor grade, and PDE3B expression was significantly associated with N lymph node metastasis and TNM stage (all P<0.05). Multivariate Cox regression analysis demonstrated that both clinical indicators and key gene expression levels contributed differentially to the prognostic score (Figure 5V). The nomogram-predicted 3-year and 5-year OS rates demonstrated strong concordance with actual observed survival outcomes (Figure 5W), confirming the model’s robust predictive accuracy. We conducted reverse prediction on the three key genes using the miRcode database, resulting in the identification of 76 miRNAs involved in a total of 223 mRNA-miRNA interaction pairs (Figure 5X). Gene set analysis revealed coregulation of these genes through shared transcriptional mechanisms. Motif-TF analysis identified cisbp_M0779 (MAZ transcription factor) as the most significantly enriched motif (NES: 9.6) (Figure 5Y).

Figure 5 Relationship between gene expressions and clinical pathological characteristics, Nomogram model and miRNA network construction, transcriptional regulation analysis of key genes. (A-G) Association of CP with clinical pathological characteristics in GC patients. (H-N) Association of MAP2K2 with clinical pathological characteristics in GC patients. (O-U) Association of PDE3B with clinical pathological characteristics in GC patients. (V) Nomogram incorporating clinicopathological variables for the prediction of OS in gastric cancer patients. (W) Calibration of 3-year and 5-year OS predictions (X) miRNA regulatory networks of key genes. (Y) Enrichment analysis of transcription factor binding motifs. (Z) Differences in regulatory genes between normal and tumor gastric tissue. (AA) Key genes relationship with tumor progression genes. *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001. ANOVA, analysis of variance; GC, gastric cancer; miRNA, microRNA; OS, overall survival; pv, P value; SD, standard deviation; TF, transcription factor.

We analyzed the expression levels of the top 20 gastric cancer-related genes (GeneCards score ≥50) and identified significant differential expression (FDR <0.05, |log₂FC|>1) in 16 genes between tumor and normal tissues: CDH1, BRCA1, TP53, BRCA2, ATM, BRIP1, CHEK2, MSH6, MSH2, PMS2, PALB2, BARD1, POLE, KRAS, PIK3CA, and ERBB2 (Figure 5Z). Additionally, we further identified significant associations between three key genes (PDE3B, MAP2K2, CP) and established tumor progression markers. Specifically, PDE3B and ATM exhibited a significant positive correlation (r=0.429), while MAP2K2 and PIK3CA showed a significant negative correlation (r=−0.459) (Figure 5AA).

PDE3B exhibits markedly elevated expression levels in gastric cancer tissues

Through a systematic review of existing literature, we have identified that the roles of MAP2K2 and CP in gastric cancer have been extensively studied (12-14). In contrast, the functional contributions of PDE3B to gastric cancer pathogenesis remain poorly understood. Therefore, we focused on elucidating PDE3B’s oncogenic role. We initially detected the expression level of PDE3B in 30 paired gastric cancer and adjacent normal tissues using qRT-PCR. The results indicated that PDE3B expression was significantly higher in gastric cancer tissues compared to adjacent normal tissues (P<0.05) (Figure 6A). WB and immunohistochemical analyses further confirmed that the protein expression level of PDE3B was markedly upregulated in gastric cancer tissues (Figure 6B,6C).

Figure 6 PDE3B expression in gastric cancer vs. normal tissues (A) qRT-PCR analysis of PDE3B expression in gastric cancer and matched normal mucosa. (B) Representative images of the expression levels of PDE3B in tumor tissues and corresponding normal paired tissues revealed by IHC. (C) PDE3B protein expression levels were analyzed by WB in five matched tumor-normal tissue pairs. *, P<0.05. IHC, immunohistochemistry; mRNA, messenger RNA; N, normal; qRT-PCR, quantitative real-time polymerase chain reaction; T, tumor; WB, Western blotting.

PDE3B facilitates the proliferation and metastasis of gastric cancer cells

Next, we conducted further investigations to determine whether PDE3B exerts any influence on the biological functions of gastric cancer cells. We selected HGC-27 and SNU-484 cell lines with high endogenous PDE3B expression for functional experiments (Figure 7A). First, PDE3B knockdown cell models were established in HGC27 and SNU484 cell lines, and the silencing efficiency was validated by qRT-PCR and WB analysis (Figure 7B). CCK-8 assays revealed that PDE3B knockdown markedly diminished the proliferative capacity of HGC-27 and SNU-484 cells (Figure 7C). Additionally, colony formation assay corroborated that the colony-forming ability of tumor cells was significantly inhibited (Figure 7D). Wound healing assay and transwell assay demonstrated that PDE3B knockdown not only attenuated the migratory capacity of the cells but also compromised their invasive potential (Figure 7E,7F).

Figure 7 PDE3B silencing suppresses oncogenic functions in gastric cancer cells. (A) mRNA levels of PDE3B were quantified in the three cell lines using qRT-PCR. (B) The efficiency of PDE3B knockdown was confirmed by qRT-PCR and WB. (C) Cell viability of HGC27 and SNU484 cells transfected with si-PDE3B and corresponding controls. (D) Knockdown of PDE3B suppressed the colony-forming capacity of HGC27 and SNU484 cells (crystal violet staining). (E) Wound healing demonstrated that PDE3B knockdown significantly inhibited the migratory capability of HGC27 and SNU484 cells. (F) Transwell assay demonstrated a significant reduction in cell migration and invasion upon PDE3B knockdown (crystal violet staining, scale bar: 100 µm). *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001. mRNA, messenger RNA; OD, optical density; siNC, negative control small interfering RNA; siRNA, small interfering RNA; WB, Western blotting.

PDE3B knockdown promotes cuproptosis in gastric cancer cells

To further investigate the role of PDE3B in gastric cancer cells, we established a cuproptosis model using ES-Cu (elesclomol-copper) as the inducer. The CCK-8 assay was employed to assess the cell viability following drug treatment after 48 hours (Figure 8A). Dose-response analysis revealed significant suppression of HGC-27 (IC50 =320 nM) and SNU-484 (IC₅₀=160 nM) proliferation. Flow cytometry results demonstrated that the proliferation activity of gastric cancer cells was passively inhibited during the S phase following ES-Cu treatment (Figure 8B). Furthermore, the copper-induced cell death was associated with mitochondrial membrane contraction and the formation of DLAT-oligomers (Figure 8C,8D). To determine whether ES-Cu induced gastric cancer cell death was attributable to cuproptosis, we systematically verified the expression profiles of key cuproptosis-related proteins. Expression of DLAT oligomers, HSP70, and FDX1 exhibited a dose-dependent correlation with ES-Cu concentration and PDE3B was significantly down-regulated (Figure 8E). These effects were reversed by tetrathiomolybdate, confirming copper-dependent cell death (Figure 8F).

Figure 8 Cuproptosis mediated by ES-Cu in gastric cancer cells. (A) Cell viability was evaluated 48 hours post-treatment of HGC27 and SNU484 cells with ES-Cu. (B) Flow cytometry was used to assess cell cycle progression following ES-Cu treatment. (C) The SNU484 cells were subjected to varying concentrations of ES-Cu through immunofluorescence microscopy (magnification: 3000×). (D) The morphological alterations in mitochondria of SNU484 cells were examined via transmission electron microscopy following exposure to varying concentrations of ES-Cu (magnification: 3000×). (E) The expression levels of cuproptosis-related proteins were analyzed using the WB technique across varying concentrations of ES-Cu. (F) The expression levels of cuproptosis-related proteins were analyzed using the WB technique across ES-Cu with or without TTM. *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001. ES-Cu, CuCl₂ chloride; IC₅₀, half-maximal inhibitory concentration; Mito, mitochondria; NC, negative control; TEM, transmission electron microscopy; TTM, ammonium tetrathiomolybdate; WB, Western blotting.

In subsequent experiments, we employed ES-Cu to treat gastric cancer cells both before and after PDE3B knockdown. The CCK-8 assay demonstrated that PDE3B silencing significantly enhanced cuproptosis (Figure 9A). PDE3B-knockdown cells showed elevated HSP70 and DLAT oligomers versus controls, while FDX1 protein expression was significantly reduced following ES-Cu treatment (Figure 9B). The EdU assay confirmed that knockdown of PDE3B not only diminished the proliferative capacity of gastric cancer cells but also potentiated the response to ES-Cu (Figure 9C,9D).

Figure 9 Knockdown of PDE3B enhances cuproptosis in gastric cancer cells. (A) The viability of gastric cancer cells treated with ES-Cu was assessed using the CCK-8 assay both before and after Knockdown of PDE3B. (B) ES-Cu was applied to treat both control and transfected HGC27 cells, and Western blot analysis was conducted to detect cuproptosis-related protein expression levels. (C,D) EdU staining was employed to detect cellular activity in both control and transfection groups prior to and following ES-Cu exposure (magnification: 200×). ns, not significant; *, P<0.05; **, P<0.01; ***, P<0.001. ES-Cu, CuCl₂ chloride; siNC, negative control small interfering RNA; siRNA, small interfering RNA; WB, Western blotting.

Next, we assessed the combined impact of PDE3B knockdown and ES-Cu on tumor growth in vivo utilizing a nude mouse model. First, we constructed PDE3B-knockdown

HGC27 cell line (Figure 10A). In nude mice implanted with PDE3B-knockdown cells, tumor formation was notably delayed in the absence of intraperitoneal injection. Following ES-Cu treatment, a more pronounced tumor inhibition effect was observed (Figure 10B). ES-Cu treatment markedly decreased both tumor weight and volume in xenograft models (Figure 10C,10D). These findings indicate that PDE3B knockdown synergistically enhances the anti-tumor efficacy of ES-Cu in vivo.

Figure 10 Knockdown of PDE3B expression potentiates the in vivo anti-tumor efficacy of ES-Cu. (A) qRT-PCR and Western blot analysis confirmed the construction of stable PDE3B knockdown HGC27 cell lines. (B) Image of subcutaneous tumor tissue in nude mice. (C) Growth curve of subcutaneous tumors among the different groups of nude mice. (D) The weight of subcutaneous tumor tissue among the different groups of nude mice. ns, not significant; *, P<0.05; **, P<0.01. ES-Cu, CuCl₂ chloride; mRNA, messenger RNA; shNC, negative control short hairpin RNA; shRNA, short hairpin RNA; WB, Western blotting.

To elucidate the molecular mechanism by which PDE3B regulates cuproptosis in gastric cancer cells, we collected PDE3B stably knockdown HGC27 cell lines before and after ES-Cu treatment, performed RNA sequencing, and screened for signaling pathways enriched by differentially expressed genes using GSEA analysis. The results indicated that PDE3B may be involved in the activation of AMPK and FOXO signaling pathways. Subsequently, WB was used to verify key proteins in these pathways. The results showed that following ES Cu treatment, p-AMPK expression was increased in knockdown PDE3B-knockdown cells (Figure 11A). Meanwhile, the expression level of p-FOXO1, a downstream signaling molecule of AMPK, was decreased, and both the upregulation of p-AMPK and the downregulation of p-FOXO1 were suppressed by the AMPK pathway inhibitor Compound C in a dose-dependent manner (Figure 11B).

Figure 11 PDE3B regulates cuproptosis via the AMPK/FOXO1 signaling pathway. (A) p-AMPK expression increases in PDE3B-knockdown GC cells after ES-Cu treatment. (B) Changes of protein expression in normal and PDE3B-knockdown GC cells treated with ES-Cu followed by Compound C treatment. CC, Compound C; ES-Cu, CuCl₂ chloride; GC, gastric cancer; shNC, negative control short hairpin RNA.

Discussion

Gastric cancer ranks among the five most prevalent cancers globally, accounting for over 660,000 deaths worldwide in 2022 (1). The median OS for advanced gastric carcinoma is generally constrained to 12–15 months in contemporary clinical practice (15). In China, the incidence rate of new gastric cancer cases and the age-standardized mortality rate (ASMR) were higher than in the US and UK (3). Gastric cancer accounts for 37% and 39.4% of the global burden and mortality, ranks as the second leading cause of cancer-related disability-adjusted life years (DALYs) in China (16). These poor outcomes are primarily attributed to acquired resistance to current antitumor treatments (17,18). Traditional chemotherapy for gastric cancer has primarily focused on programmed cell death. Therefore, targeting alternative cell death mechanisms represents a breakthrough strategy for gastric cancer therapy.

Cuproptosis differs from other forms of programmed cell death. Copper ionophores facilitate the transport of copper ions into cells. Copper overload triggers mitochondrial membrane impairment and impaired enzyme activity in the TCA cycle. Numerous studies confirm the crucial role of cuproptosis and CRGs in various types of tumors. Li et al. (19) reported that the overexpression of DLAT stabilizes mitochondrial energy supply and promotes liver cancer growth. Upregulation of DLAT in clear cell renal cell carcinoma induces cuproptosis and represents a promising therapeutic target for its treatment (9). PDHA1 overexpression correlates with enhanced proliferative and invasive capacity in prostate cancer (20), while reduced SLC39A4 expression predicts poor prognosis in bile duct neoplasms (21). A new nanozyme targeting cuproptosis can effectively overcome chemotherapy resistance in the treatment of colorectal cancer (22). These findings establish cuproptosis as a promising therapeutic strategy, forming the core focus of our gastric cancer research.

In this study, we utilized the TCGA database to conduct a preliminary investigation into the expression profiles of CRGs in gastric cancer and identified 27 differentially expressed genes between gastric cancer and normal tissues. These findings validated the significance of CRGs in gastric cancer oncology and positioned cuproptosis as a promising therapeutic strategy. We further discovered that three genes (CP, MAP2K2, and PDE3B) were closely associated with the prognosis of gastric cancer. Previous research has demonstrated that CP and MAP2K2 promote the proliferation and growth of gastric cancer cells. However, the precise role of PDE3B in gastric carcinogenesis and cuproptosis regulation remains unknown. Therefore, we concentrated our efforts on investigating the role of PDE3B. PDE3B is one of the phosphohydrolases, which catalyzes the hydrolysis of cAMP and cGMP, plays a role in various signaling pathways, and is implicated in metabolic processes (23) and dyslipidemia (24). PDE3B acts as a critical regulator of inflammatory processes, as well as the proliferation and migration of synoviocytes in rheumatoid arthritis (25). In adipocytes, PDE3B-mediated cAMP degradation potentiates MCP-1 transcription in mature adipocytes, fostering macrophage infiltration, leading to enhanced pro-inflammatory responses (26). Post-transcriptional PDE3B repression confers protection against autoimmune diseases by maintaining immune homeostasis (27) and mitigating acute allergic reactions (28). Combined PDE3 (bronchodilation) and PDE4 (anti-inflammatory) inhibition synergistically improved spirometric outcomes in chronic obstructive pulmonary disease (COPD) (29). The PDE3B-cAMP-autophagy pathway is closely associated with supercooling liver preservation-induced liver injury, and PDE3B inhibition can effectively suppress hepatic autophagy (30). Regarding tumor-related diseases, it has been discovered that PDE3B is upregulated in gastrointestinal stromal tumors (GIST) (31). Anagrelide, a selective PDE3B inhibitor, demonstrates significant anticancer efficacy. In the pancreatic cancer cell line BxPC-3, the PDE3B-Rapgef3 complex inhibits cell metastasis and promotes apoptosis by suppressing the RAP-1 and PI3K-AKT signaling pathways (32). In our study, quantitative analysis confirmed significant PDE3B upregulation in gastric cancer tissues as evidenced by qRT-PCR, WB, and IHC. After PDE3B was knocked down, a significant impairment in clonogenic and proliferative potential was observed. Additionally, the migration and invasion capabilities were also affected. The downregulation of PDE3B expression was observed in gastric cancer cells treated with ES-Cu, and the effect was reversed by TTM. Crucially, the PDE3B silencing not only inhibited malignant phenotypes but also enhanced cuproptosis sensitivity in gastric cancer cells.

The TME orchestrates multiscale pro-tumorigenic crosstalk, driving metastatic dissemination and conferring resistance to chemo/immunotherapies through biomechanical and biochemical signaling. Immunotherapy for tumors has introduced new breakthroughs and expanded treatment options for gastric cancer patients (33,34). Our study revealed significantly elevated infiltration of activated CD4⁺ memory T cells and M1 macrophages compared to other immune populations. M1 macrophages are closely associated with the production of multiple cytokines and exhibit potent pro-inflammatory effects. M1-polarized macrophages exhibit a positive correlation with CD47 expression, and abnormal CD47 expression is indicative of poor prognosis and drug resistance in gastric cancer (35). M1 macrophages exert a key function in immune regulation through the PD-L1/PD-1 signaling axis (36). GSEA analysis revealed that PDE3B-enriched signaling pathways were significantly associated with the TME by influencing tumor differentiation, metabolic regulation, and proliferation. PDE3B expression exhibited a negative correlation with activated NK cell infiltration and positively with naive B cells and eosinophils. These findings align with clinical evidence that elevated NK cell infiltration predicts favorable prognosis in gastric cancer (37,38), suggesting PDE3B serves as both a progression biomarker and therapeutic target.

The AMPK/FOXO1 signaling axis plays an important tumor-suppressive role in various cancers. Activation of this pathway enhances gefitinib-induced apoptosis in non-small cell lung cancer (39). Suppression of the AMPK/FOXO pathway promotes metastasis of ovarian cancer (40). Our study reveals that PDE3B promotes the proliferation and migration of gastric cancer cells; conversely, inhibiting PDE3B expression enhances the cuproptosis effect induced by ES-Cu. During this process, the level of p-AMPK increases while the level of p-FOXO1 decreases, indicating that the AMPK/FOXO1 signaling pathway is activated. As a central hub of cellular energy homeostasis, AMPK not only coordinates autophagy and mitochondrial function to maintain energy metabolic balance (41), but also regulates transcriptional programs such as cell cycle arrest and apoptosis through its downstream key signaling node FOXO1 (42). This may reflect the mechanism by which knockdown of PDE3B enhances ES-Cu-induced cuproptosis.

This finding also provides a potential direction for the development of targeted therapy strategies. However, there are several limitations in this study that warrant acknowledgment. First, all omics data (whole-exome sequencing, transcriptomics) and clinical annotations originated exclusively from TCGA, limiting demographic diversity. Therefore, additional external datasets should be incorporated to robustly validate our bioinformatics findings. Second, while our experimental analyses focused on one risk marker gene, the role of CP and MAP2K2 in cuproptosis requires experimental verification. Finally, future research is essential to explore the fundamental mechanisms by which CRGs regulate cuproptosis.

Conclusions

In this study, we characterized the dysregulation landscape of CRG dysregulation in gastric adenocarcinoma. We developed a clinical prognostic model incorporating three key genes—PDE3B, CP, and MAP2K2—and elucidated the pivotal role of PDE3B in gastric cancer pathogenesis. Additionally, we verified that ES-Cu exhibited a significant cytotoxic effect on gastric cancer. Crucially, PDE3B knockdown potentiated ES-Cu’s tumoricidal activity. These findings position PDE3B-targeted cuproptosis induction as a promising therapeutic strategy for gastric cancer.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the ARRIVE and MDAR reporting checklists. Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-1-0070/rc

Data Sharing Statement: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-1-0070/dss

Peer Review File: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-1-0070/prf

Funding: This study was supported by the National Natural Science Foundation of China (Nos. 81970499 and 81770561).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-1-0070/coif). G.Z. reports funding support from the National Natural Science Foundation of China (NSFC). The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study has been reviewed and approved by the Ethics Committee of The First Affiliated Hospital of Nanjing Medical University (No. 2020-SR-383). Informed consent was obtained from all individual participants included in the study. Animal experiments were performed under a project license (No. IACUC-2404033) granted by the Ethics Committee of Nanjing Medical University, in compliance with the National Research Council Guide for the Care and Use of Laboratory Animals.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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