The CLIC1-PKM2 axis orchestrates glycolytic metabolism to accelerate gastric cancer progression

Abstract

Background

Metabolic reprogramming is a hallmark of malignant transformation and supports tumor proliferation and survival. Chloride intracellular channel protein 1 (CLIC1) has been implicated in multiple oncogenic processes; however, its mechanistic role in regulating glycolysis in gastric cancer (GC) remains largely unknown. This study aimed to elucidate how CLIC1 modulates PKM2-dependent glycolytic metabolism and its impact on gastric tumor progression.

Methods

Bioinformatic analyses were performed using TCGA and GEO datasets to assess correlations between CLIC1 and glycolytic pathways. Immunohistochemistry was used to assess CLIC1 and PKM2 expression and their correlation in GC. Functional assays, including Seahorse extracellular flux analysis, glucose/lactate quantification, and ATP measurement were used to evaluate glycolytic activity. Protein interactions were analyzed by co-immunoprecipitation, GST pull-down, and mass spectrometry. Cellular proliferation, migration, and invasion were assessed by CCK-8, wound healing, and Transwell assays. Xenograft mouse models were established to evaluate in vivo tumorigenic capacity and the therapeutic effects of glycolytic inhibition.

Results

CLIC1 expression was positively correlated with glycolytic pathway activity in GC. CLIC1 and PKM2 were highly expressed in gastric cancer tissues and showed a positive correlation. CLIC1 knockdown suppressed glycolysis and inhibited GC cell proliferation, migration, and invasion, whereas CLIC1 overexpression exerted the opposite effects. Mechanistically, CLIC1 directly interacted with the C-terminal domain of PKM2, stabilizing its dimeric form, thereby facilitating glycolytic flux and nuclear PKM2 accumulation. Pharmacological inhibition of PKM2 or glycolysis attenuated CLIC1-induced tumor growth both in vitro and in vivo.

Conclusions

This study identifies CLIC1 as a novel metabolic regulator that drives glycolytic reprogramming through direct interaction with PKM2 in gastric cancer. Targeting the CLIC1–PKM2 axis may provide a promising therapeutic strategy for metabolic intervention in GC and highlights a potential translational target for future clinical application.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-025-07463-6.

Introduction

Gastric cancer remains one of the most prevalent malignancies threatening human health worldwide. Recent epidemiological data from global cancer statistics rank it as the fifth most commonly diagnosed cancer and the fifth leading cause of cancer-related mortality [1]. Current management of gastric cancer centers on surgery-based multimodal therapy, with prognosis being multifactorially determined by tumor characteristics (location and nodal involvement), host genetics, and therapeutic approaches [2]. In recent years, advancements in endoscopic and surgical techniques, combined with the application of adjuvant therapies including chemotherapy, targeted therapy, and immunotherapy, have improved treatment outcomes for gastric cancer patients [3, 4]. Nevertheless, the prognosis remains dismal for most patients with advanced-stage disease, with a 5-year survival rate below 20% [5, 6]. Gastric cancer exhibits highly aggressive behavior, as approximately 60% of patients experience local recurrence or distant metastasis even after curative resection [7, 8]. These clinical challenges underscore the urgent need to elucidate the molecular mechanisms underlying gastric cancer invasion and metastasis, which would have significant implications for guiding clinical practice, prognostic prediction, and treatment evaluation.

Metabolic reprogramming represents a hallmark of cancer that is crucial for tumorigenesis and metastasis [9]. Under normoxic conditions, cancer cells preferentially undergo glycolysis with accelerated glucose uptake and lactate secretion, a phenomenon termed the “Warburg effect” or aerobic glycolysis [10]. Substantial evidence indicates that aerobic glycolysis actively participates in multiple malignant behaviors of tumor cells, including proliferation, invasion-metastasis cascades, immune evasion, and multidrug resistance [11–14]. Pyruvate kinase (PK), a key rate-limiting glycolytic enzyme, catalyzes the conversion of phosphoenolpyruvate (PEP) to pyruvate while phosphorylating ADP to generate ATP [15]. Four PK isozymes (M1, M2, L, and R) have been identified in mammals. The M1 (PKM1) and M2 (PKM2) isoforms are generated through mutually exclusive alternative splicing of PKM pre-mRNA. While PKM1 is predominantly expressed in most adult tissues, PKM2 is primarily found in fetal tissues and cancer cells [16]. Emerging studies have demonstrated aberrant PKM2 expression across various cancers, where it promotes tumor initiation and progression [17]. In cancer cells, PKM2 mainly exists in a low-activity state, and its enzymatic activity is tightly regulated by multiple factors that mediate the reversible interconversion between its dimeric and tetrameric forms [18–20]. The low-activity dimeric PKM2 redirects glucose flux from energy production to biomass synthesis, which is essential for rapidly proliferating tumor cells. Beyond its canonical enzymatic role, dimeric PKM2 can translocate to the nucleus and function as a transcriptional coactivator [21]. Recent investigations revealed that human DExD-box helicase 39B (DDX39B) enhances aerobic glycolysis-driven colorectal cancer progression by promoting PKM2 stabilization and nuclear translocation, thereby facilitating transactivation of glycolytic genes [22]. However, whether this dynamic PKM2 accumulation and nuclear transcriptional activation mechanism contributes to gastric cancer invasion and metastasis remains incompletely understood.

Chloride intracellular channel protein 1 (CLIC1), a 241-amino acid member of the glutathione S-transferase (GST) superfamily, represents the first identified human CLIC family protein that exists in both soluble and transmembrane forms [23, 24]. Emerging evidence has increasingly demonstrated the oncogenic roles of CLIC1 in various malignancies. CLIC1 was significantly overexpressed in multiple cancer types, including esophageal [25], hepatocellular carcinoma [26], gallbladder [27], pancreatic [28], and breast cancers [29], where it actively contributes in tumor immune evasion and metastatic progression. Our previous studies have established CLIC1 as a pro-oncogenic factor in gastric cancer, demonstrating its capacity to promote tumor proliferation, invasion, and metastasis through modulation of PI3K/Akt, MAPK/p38, and AMOT-p130 signaling pathways [30–32]. Furthermore, CLIC1 facilitated immune escape of gastric cancer cells by impairing CD8 + T cell function [33]. Recent investigations revealed that CLIC1 could serve as a glycolytic metabolic catalyst to drive pancreatic cancer growth [34]. However, whether CLIC1 participates in glucose metabolic reprogramming during gastric carcinogenesis and progression remains largely unknown.

In this study, we investigated the functional role of CLIC1 in regulating glycolytic metabolism in gastric cancer. We demonstrated that CLIC1 interacts with PKM2, stabilizes its dimeric form, and suppresses its enzymatic activity, thereby enhancing glycolytic flux and promoting tumor progression. Moreover, pharmacological inhibition of PKM2 attenuated CLIC1-driven tumor growth. Collectively, these findings identify the CLIC1–PKM2 axis as a critical regulator of gastric cancer metabolism and highlight its potential as a therapeutic target.

Materials and methods

Bioinformatics

The gene expression profiles of gastric cancer were obtained from The Cancer Genome Atlas database (TCGA, https://cancergenome.nih.gov/) and Gene Expression Omnibus database (GEO, https://www.ncbi.nlm.nih.gov/geo/) (GSE66229 and GSE62254). Differential expression analysis was performed using the limma package in R software (version 4.1.3), with genes showing an adjusted p-value < 0.05 and |log2 fold change| >1 considered statistically significant. Functional annotation of DEGs was conducted using clusterProfiler R package for Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Survival analysis was conducted using the survival R package with Kaplan-Meier curves. Gene-gene correlation analysis of TCGA data was performed through the Correlation Analysis module in the Expression Analysis function of GEPIA2 website (http://gepia2.cancer-pku.cn/). The glycolysis-related gene set was obtained from the GeneCards database (https://www.genecards.org/), while the CLIC1-associated gene set in gastric cancer was retrieved from the LinkedOmics database (https://www.linkedomics.org/login.php).

Clinical specimens

A total of 58 paired gastric cancer tissue samples and adjacent normal tissues were collected from patients who underwent surgical resection at the First Affiliated Hospital of Guangxi Medical University between August 2021 and October 2022. Immediately after surgical resection, a portion of each specimen was snap-frozen in liquid nitrogen and subsequently stored at − 80 °C until further analysis, while another portion was fixed in 10% neutral-buffered formalin for subsequent immunohistochemical analysis. Written informed consent was obtained from all participating patients prior to specimen collection. The First Affiliated Hospital of Guangxi Medical University medical ethics committee granted ethical approval for this study (approval number: 2025-S0119). The clinicopathological characteristics of the patients are summarized in Supplementary Table S1.

Cell culture

The human gastric cancer cell lines AGS and HGC27, along with HEK293T cells, were obtained from Procell Life Science & Technology Co., Ltd. (Wuhan, China). All cell lines were maintained at 37 °C in a humidified atmosphere with 5% CO₂. AGS cells were cultured in Ham’s F-12 medium (Gibco, USA), HGC27 cells in RPMI-1640 medium (Gibco, USA), and HEK293T cells in DMEM (MULTICELL, China). All culture media were supplemented with 10% fetal bovine serum (FBS, Wisent, Canada) and 1% penicillin-streptomycin solution (Wisent, Canada).

shRNAs, plasmids, and transfections

Lentiviruses for CLIC1 silencing and overexpression were commercially obtained from Hanbio Biotechnology Co., Ltd. (Shanghai, China). The FLAG-CLIC1 and HA-PKM2 overexpression plasmids, GST, GST-CLIC1 plasmids, along with the full-length and truncated mutant constructs of CLIC1 and PKM2, were purchased from Miaoling Biotechnology Co., Ltd. (Wuhan, China). Plasmid transfection was performed using Lipofectamine 3000 (Invitrogen, USA) according to the manufacturer’s protocol. Cell infection with lentivirus was performed in the presence of polybrene (MedChemExpress, USA), followed by puromycin selection to establish stable cell lines. Transient transfection efficiency was examined 48–72 h post-infection, and knockdown or overexpression efficiency was evaluated by quantitative RT-PCR and Western blot analysis.

Quantitative real‑time PCR (qRT-PCR)

Total RNA was extracted from cells and tissues using Nuclezol reagent (MACHEREY-NAGEL, Germany) following the manufacturer’s protocol. First-strand cDNA was synthesized using the HiScript III RT SuperMix for qPCR kit (Vazyme Biotech, China) following the manufacturer’s protocol. (qRT-PCR) was conducted using ChamQ Universal SYBR qPCR Master Mix (Vazyme Biotech, China) on a QuantStudio 7500 Fast Real-Time PCR System (Applied Biosystems, USA). Gene-specific primers were designed and synthesized by Nanning Genesil Biotechnology Co., Ltd. (Nanning, China). Relative gene expression levels were calculated using the 2-ΔΔCt method with β-actin serving as the endogenous control. Primer sequences are provided in Supplementary Table S2.

Western blot (WB)

Western blotting was performed as previously described [32]. Briefly, cells or tissues were lysed in RIPA buffer (Solarbio, China) supplemented with protease inhibitors (Solarbio, China). Nuclear and cytoplasmic proteins were extracted using the Nuclear and Cytoplasmic Protein Extraction Kit (#20126ES50; YeaSen, China) according to the manufacturer’s instructions. Protein concentrations were determined using a BCA protein assay kit (Beyotime, China). Equal amounts of protein were separated by SDS-PAGE and transferred onto polyvinylidene fluoride (PVDF) membrane (Merck Millipore, Germany). The membrane was blocked with 5% bovine serum albumin (BSA) for 1 h at room temperature, followed by overnight incubation with the primary antibodies. After washing, the membranes were incubated with horseradish peroxidase (HRP)-conjugated secondary antibodies for 1 h at room temperature. Protein bands were visualized using an enhanced chemiluminescence (ECL) detection system (Bio-Rad, USA), and band intensities were quantified using ImageJ. Primary antibodies used in this study included anti-CLIC1 (#sc-81873; Santa Cruz Biotechnology, USA), anti-PKM2 (#15822-1-AP; Proteintech, China), anti-PKM1 (#15821-1-AP; Proteintech), anti-Lamin B1 (#12987-1-AP; Proteintech), anti-β-actin (#66009-1-Ig; Proteintech), and anti-α-Tubulin (#11224-1-AP; Proteintech). HRP-conjugated goat anti-rabbit IgG (#SA00001-2) and HRP-conjugated goat anti-mouse IgG (#SA00001-1) were obtained from Proteintech (China). HA Tag and FLAG Tag antibodies were purchased from Thermo Fisher Scientific (USA).

Cell counting kit-8 (CCK-8) proliferation assay

For cell proliferation assays, 2,000 cells per well were seeded in 96-well plates with five technical replicates for each condition. 2-deoxy-D-glucose (2-DG, MCE, HY-13966, USA) and PKM2-IN-1 (MCE, HY-103617, USA) were applied to the cells to assess cell proliferation. At 24, 48, and 72 h, the medium in each well was replaced with 100 µL of fresh medium supplemented with 10% CCK-8 reagent (Vazyme, China). After incubation for 2 h at 37 °C in a humidified 5% CO₂ incubator, absorbance was measured at 450 nm using a microplate reader (BioTek Instruments, USA).

Wound healing assays

For the wound healing assay, parallel reference lines were drawn on the bottom of a 6-well plate using a marker and ruler. Gastric cancer cells were cultured in complete medium until reaching 90–100% confluence to form a uniform monolayer. A sterile 200 µL pipette tip was then used to create a straight scratch perpendicular to the reference lines. After washing twice with PBS to remove detached cells, the medium was replaced with serum-free medium. Images of the wound area were captured at 0 and 24 h using an inverted microscope to evaluate cell migration. The migration rate was quantified using ImageJ (NIH, USA) and calculated as: Wound closure (%) = [(A₀ - A₂₄)/A₀] × 100, where A₀ is the initial wound area (0 h) and A₂₄ is the remaining wound area after 24 h.

Transwell migration and invasion assays

Transwell migration and invasion assays were performed using 8-µm pore size polycarbonate membrane inserts (Corning, USA). For migration assays, 2 × 10⁵ cells in 100 µL serum-free medium were seeded into the upper chamber. For invasion assays, inserts were pre-coated with 100 µL Matrigel matrix (1:10 dilution in serum-free medium; Yisheng Biotechnology, China) and incubated at 37 °C for 30 min to allow polymerization. The lower chamber was filled with 800 µL complete medium containing 10% FBS as a chemoattractant. After 24 h incubation at 37 °C with 5% CO₂, non-migrated or non-invaded cells on the upper membrane surface were removed with cotton swabs. Cells that had migrated or invaded to the lower surface were fixed with 4% paraformaldehyde (Solarbio, China) for 15 min and stained with 0.1% crystal violet (Solarbio, China) for 15 min. Three random fields per insert were imaged under an inverted microscope, and the number of cells was quantified using ImageJ.

Immunofluorescence staining (IF)

Immunofluorescence staining was performed according to the previous method [32]. AGS and HGC27 cells were seeded onto sterile glass coverslips and cultured for 24 h at 37 °C in a humidified incubator with 5% CO₂. Cells were fixed with 4% paraformaldehyde for 20 min and permeabilized with 0.1% Triton X-100 (Sigma) for 15 min. After blocking with 5% bovine serum albumin (BSA) for 30 min, cells were incubated overnight at 4 °C with primary antibodies against CLIC1 (#sc-81873, Santa Cruz Biotechnology) and PKM2 (#15822-1-AP, Proteintech). Following PBS washes, cells were incubated with fluorophore-conjugated secondary antibodies for 1 h at room temperature and counterstained with DAPI (C1002, Beyotime) for 20 min in the dark. Coverslips were mounted using anti-fade mounting medium and imaged with a confocal laser scanning microscope (Leica Biosystems, Germany).

Immunohistochemistry (IHC)

Immunohistochemical staining was performed as previously described [35]. Briefly, tissue sections were baked at 65 °C for 1 h, deparaffinized in xylene, and rehydrated through graded ethanol solutions. Antigen retrieval was performed in citrate buffer for 10 min, followed by blocking of endogenous peroxidase activity with 3% hydrogen peroxide and nonspecific binding with 5% fetal bovine serum for 20 min. Sections were then incubated overnight at 4 °C with primary antibodies against CLIC1 and PKM2. After incubation with HRP-conjugated secondary antibodies for 20 min at room temperature, color development was achieved using DAB substrate, followed by hematoxylin counterstaining, dehydration, and sealing with neutral resin. Stained sections were visualized and photographed under a light microscope. For immunohistochemical scoring, staining intensity was classified as 0 (negative), 1 (weak), 2 (moderate), and 3 (strong). The percentage of positive cells was scored as 1 (0–25%), 2 (26–50%), 3 (51–75%), and 4 (76–100%). The final IHC score was calculated as IHC score = intensity × percentage score.

Co-immunoprecipitation (Co-IP), liquid chromatography-tandem mass spectrometry (LC-MS/MS) and GST pull-down assays

Co-IP was performed using protein A/G magnetic beads (#88805; Thermo Fisher Scientific) following the manufacturer’s instructions. Briefly, cells were lysed in lysis buffer supplemented with protease inhibitors. Protein A/G magnetic beads (25 µL) were washed with wash buffer and incubated with the appropriate antibody (5 µg/mL) in binding buffer at room temperature for 15 min. The antibody-conjugated beads were then incubated with the cell lysates on a rotating platform at room temperature for 1 h. After incubation, the protein complexes were eluted using elution buffer and subjected to Western blot analysis.

For LC-MS/MS, total protein was extracted from AGS cells, followed by Co-IP using an anti-CLIC1 antibody. The immunoprecipitated samples were analyzed using a Thermo Scientific Q Exactive HF-X mass spectrometer equipped with a Nanospray Flex™ (NSI) ion source. Peptides were separated on a C18 column using a 120-min gradient of 70–100% acetonitrile in 0.1% formic acid. MS1 scans were acquired at a resolution of 120,000 (m/z 200), and MS2 scans were performed with HCD fragmentation at 27% collision energy. The resulting data were searched against the Homo sapiens database using Sequest HT in Proteome Discoverer 2.4 with a mass tolerance of 10 ppm.

GST pull-down assays were performed using the Pierce™ GST Protein Interaction Pull-Down Kit (#21516; Thermo Fisher Scientific) following the manufacturer’s protocol. GST and GST-CLIC1 bait proteins were expressed in 293T cells and purified using glutathione agarose resin. The bait proteins were immobilized on the resin and incubated on a rotating platform at 4 °C for 30 min. The immobilized proteins were then incubated with cell lysates containing HA-PKM2 prey protein at 4 °C for 1 h with gentle rotation. After incubation, the bound complexes were eluted using glutathione elution buffer and subjected to subsequent analysis.

Protein stability assay

AGS and HGC27 cells from the CLIC1-silenced and control groups were treated with cycloheximide (CHX, 50 µg/mL) and harvested at various time points. Western blotting was performed to assess PKM2 protein stability. Band intensities were quantified using ImageJ and normalized to the 0-hour time point to calculate the relative percentage of remaining protein. The data were plotted to illustrate the protein degradation rate.

Disuccinimidyl suberate (DSS) crosslinking

Protein samples were prepared by lysing cells in ice-cold lysis buffer containing PMSF (Solarbio, China), and protein concentrations were determined using the BCA assay. For crosslinking, DSS was added at 10-fold molar excess for samples > 5 mg/mL or 20–50-fold excess for samples < 5 mg/mL, yielding final concentrations of 0.25–5 mM. Reactions were performed at room temperature for 30 min terminated by adding Tris-HCl (1 M, pH 7.5) to a final concentration of 20–50 mM for 15 min at room temperature. Samples were then mixed with 5× loading buffer and denatured at 100 °C for 10 min prior to Western blot analysis.

Glucose consumption and lactate production

Cells were seeded in 96-well plates at 1 × 10⁴ cells per well and cultured for 48 h. Culture supernatants were collected and centrifuged at 500 × g for 5 min to remove cellular debris. Glucose consumption was measured using a Glucose Assay Kit (#A154-1-1;Jiancheng Bioengineering Institute, China), following the manufacturer’s protocol. Lactate production was assessed using a Lactate Assay Kit (#A019-2-1; Nanjing Jiancheng Bioengineering Institute, China) according to the manufacturer’s instructions. Metabolic values were normalized to total cell number.

ATP measurement

Cellular ATP levels were quantified using a chemiluminescence-based ATP assay kit (Solarbio, China) according to the manufacturer’s instructions. Total protein concentration was determined using a standard protein quantification assay. ATP levels were normalized to corresponding total protein content.

Seahorse assays

The extracellular acidification rate (ECAR) of gastric cancer cells was measured in real time using a Seahorse XFe24 Extracellular Flux Analyzer (Agilent Technologies, USA) following the manufacturer’s protocol. AGS and HGC27 cells were seeded in XF24 microplates at 3 × 10⁴ cells per well and incubated overnight at 37 °C. Before the assay, the culture medium was replaced with XF assay medium (Agilent, USA). Glycolytic flux was assessed through sequential injections of 10 mM glucose, 1 µM oligomycin, and 50 mM 2-deoxy-D-glucose (2-DG) at recommended time points. All measurements were performed under standard conditions (37 °C, non-CO₂ buffered environment).

PKM2 activity detection

PKM2 activity was measured using a Pyruvate Kinase (PK) Activity Assay Kit (#BC0545; Solarbio). Cells were homogenized in the provided extraction buffer and lysed by ultrasonication on ice. After centrifugation, the supernatant was collected for analysis. PKM2 activity was quantified by monitoring absorbance at 340 nm using a TECAN SPARK microplate reader.

Xenograft tumor models

Male BALB/c nude mice (4–5 weeks old) were obtained from the Experimental Animal Center of Guangxi Medical University. For xenograft experiments, 2 × 10⁶ cells suspended in 100 µL PBS were subcutaneously injected into the left axillary region of each mouse. When tumors became palpable (~ 50 mm³), mice were treated with intraperitoneal injections of PKM2-IN-1 (3 mg/kg) or 2-DG (500 mg/kg) every other day for 15 days [36, 37]. Tumor size was measured every 3 days with digital calipers, and volume was calculated as: Volume = (length × width²)/2. All procedures were approved by the Institutional Animal Care and Use Committee of the First Affiliated Hospital of Guangxi Medical University (Approval No. 2025-S0119) and conducted according to NIH guidelines for laboratory animal welfare.

Statistical analysis

Statistical analyses were performed using Student’s t-test for comparisons between two groups and one-way ANOVA for comparisons among three or more groups. Correlation analyses were conducted using either Spearman or Pearson coefficients, depending on data distribution. A P-value < 0.05 was considered statistically significant.

Results

Silencing CLIC1 suppresses glycolysis in gastric cancer cells

CLIC1 has been reported to act as a glycolytic catalyst promoting the progression of pulmonary arterial hypertension and pancreatic cancer [34, 38]. Nonetheless, the functional mechanisms of CLIC1 in gastric cancer are not yet fully understood. To explore the potential role of CLIC1 in gastric cancer metabolism, we conducted a KEGG pathway enrichment analysis on genes associated with CLIC1. The analysis revealed a significant enrichment in carbohydrate metabolic pathways (Fig. 1A), with a significant positive correlation between CLIC1 expression and glycolytic pathway activity in the TCGA gastric cancer cohort (Fig. 1B). To functionally validate these findings, we successfully established CLIC1-silenced models in both AGS and HGC27 gastric cancer cell lines, as confirmed by qPCR and WB (Fig. 1C-E). Functional metabolic assays indicated that CLIC1 knockdown significantly impaired glycolytic activity in both cell lines. Measurements of ECAR revealed a marked reduction in both basal glycolysis and glycolytic capacity (Fig. 1F–G) following CLIC1 silencing.

Fig. 1.

Silencing CLIC1 suppresses glycolysis in gastric cancer cells. (A) KEGG pathway enrichment analysis of CLIC1-associated genes. (B) Correlation analysis between CLIC1 expression and glycolytic pathway activity. (C) qPCR validation of CLIC1 silencing in AGS and HGC27 cells. (D-E) Western blot analysis confirmed CLIC1 knockdown efficiency in AGS and HGC27 cells. (F-G) ECAR assays showed that CLIC1 silencing decreases glycolytic levels and glycolytic capacity in both cell lines. (H) Glucose consumption in CLIC1-silenced AGS and HGC27 cells. (I) Intracellular ATP production upon CLIC1 knockdown in both cell lines. (J) Lactate secretion in CLIC1-silenced gastric cancer cells. Two-sided unpaired Student’s t-test between two groups, and one-way ANOVA among three or more groups. (*p < 0.05, **p < 0.01, ***p < 0.001)

Further biochemical analyses consistently corroborated the inhibitory effect of CLIC1 knockdown on glycolytic metabolism. CLIC1 knockdown exhibited significantly decreased glucose consumption in gastric cancer cells (Fig. 1H), along with reduced intracellular ATP production (Fig. 1I). Notably, lactate secretion was also substantially attenuated in CLIC1-deficient gastric cancer cells (Fig. 1J). To validate the reproducibility and specificity of these findings, we further examined two additional CLIC1 knockdown sequences (sh-CLIC1-2 and sh-CLIC1-3). Consistently, both sh-CLIC1-2 and sh-CLIC1-3 exhibited comparable inhibitory effects on glycolytic activity, as evidenced by decreased glucose consumption (Supplementary Fig. 1A–B), reduced lactate secretion (Supplementary Fig. 1C–D), and lower intracellular ATP levels (Supplementary Fig. 1E–F). Collectively, these results demonstrated that CLIC1 plays a crucial role in regulating glycolytic metabolism in gastric cancer cells, and its silencing leads to the suppression of glycolysis.

CLIC1 promotes gastric cancer progression by enhancing glycolysis

To further explore the role of CLIC1-mediated glycolysis in gastric cancer progression, we conducted a series of functional phenotypic assays. CLIC1-overexpressing AGS and HGC27 cell lines were successfully established, as confirmed by western blotting (Fig. 2A). Functional analyses revealed that CLIC1 overexpression significantly enhanced glycolytic activity, as indicated by increased glucose consumption (Fig. 2B) and elevated lactate secretion (Fig. 2C). Notably, treatment with the glycolytic inhibitor 2-deoxyglucose (2-DG) partially reversed these pro-glycolytic effects (Fig. 2B–C), suggesting that the oncogenic function of CLIC1 is at least partly dependent on glycolytic metabolism.

Fig. 2.

CLIC1 promoted gastric cancer progression through glycolysis-dependent mechanisms. (A) WB confirmed the efficiency of CLIC1 overexpression in AGS and HGC27 gastric cancer cells. (B–C) CLIC1 overexpression increased (B) glucose consumption and (C) lactate secretion, effects that were attenuated by 2-DG. (D–G) Wound-healing assays showed that CLIC1 overexpression enhanced cell migration, which was suppressed by 2-DG. (H–I) CCK-8 assays demonstrated that CLIC1 overexpression promoted cell proliferation, an effect partially reversed by 2-DG treatment. (J–M) Transwell assays revealed that CLIC1 enhanced both migratory and invasive capacities in a glycolysis-dependent manner. (N) Representative images of xenograft tumors from each treatment group at the study endpoint. (O) Final tumor weights at sacrifice. (P) Tumor growth curves showed tumor volume changes over time. One-way ANOVA. (*p < 0.05, **p < 0.01, ***p < 0.001)

We further investigated the biological consequences of CLIC1-mediated glycolysis. Wound healing assays revealed an enhanced migratory capacity in CLIC1-overexpressing cells, which was attenuated upon treatment with 2-DG (Fig. 2D–G). Similarly, CCK-8 assays demonstrated that CLIC1 overexpression significantly promoted cell proliferation, whereas 2-DG treatment partially reversed this effect (Fig. 2H–I). Transwell invasion assays further confirmed that CLIC1 enhanced both migratory and invasive capacities in a glycolysis-dependent manner (Fig. 2J–M).

The tumor-promoting role of CLIC1 was further validated in vivo using AGS xenograft models. CLIC1 overexpression significantly accelerated tumor growth, whereas co-treatment with the 2-DG markedly attenuated this effect (Fig. 2N–P). No significant differences in body weight were observed between groups during the experiment (Supplementary Figure S2A). Collectively, these findings demonstrate that CLIC1 promotes gastric cancer progression through the activation of glycolysis, and that its oncogenic effects can be therapeutically mitigated by glycolytic inhibition.

Identification of PKM2 as a CLIC1-bound glycolytic protein

To elucidate the mechanism underlying CLIC1-mediated glycolytic regulation in gastric cancer, we extracted total protein from AGS cells and performed Co-IP using an anti-CLIC1 antibody, followed by mass spectrometry analysis. Mass spectrometry analysis identified a total of 2,043 proteins interacting with CLIC1 (Supplementary Table 3). To focus on glycolytic regulators associated with CLIC1, we retrieved glycolysis-related gene sets (Supplementary Table 4) and CLIC1-correlated gene sets (Supplementary Table 5) from the GeneCards and LinkedOmics databases. By intersecting these two gene sets with the IP-derived protein list, we identified 11 overlapping genes (Fig. 3A). Among these, PKM stood out as a key glycolytic enzyme. PKM exists in two isoforms, PKM1 and PKM2, and exhibited the highest score and coverage among the overlapping genes (Fig. 3A). Given that PKM2 emerged as the most prominent glycolytic enzyme among the CLIC1-interacting candidates, we next focused on experimentally validating the interaction between CLIC1 and PKM2 and exploring its functional relevance. To confirm their association, exogenous Co-IP assays were performed in 293T cells. Reciprocal Co-IP experiments demonstrated that CLIC1 immunoprecipitated PKM2 (Fig. 3B), and conversely, PKM2 immunoprecipitated CLIC1 (Fig. 3C), indicating a direct physical interaction between the two proteins. We further carried out endogenous Co-IP assays in AGS and HGC27 gastric cancer cells, which confirmed that CLIC1 specifically co-immunoprecipitated with PKM2 (Fig. 3D–E), but not with the PKM1 isoform (Fig. 3F–G), suggesting isoform-specific binding. Consistently, immunofluorescence analysis revealed cytoplasmic co-localization of CLIC1 and PKM2 in both AGS and HGC27 cells (Fig. 3H), further substantiating their interaction within gastric cancer cells. To further validate a direct physical interaction between CLIC1 and PKM2, we performed a glutathione S-transferase (GST) pull-down assay. The results demonstrated that GST-tagged CLIC1 successfully pulled down PKM2, whereas no binding was detected in the GST control group (Fig. 3I), confirming a specific and direct interaction between CLIC1 and PKM2.

Fig. 3.

CLIC1 interacts directly with PKM2 in gastric cancer cells. (A) Venn diagram showed the overlap among CLIC1-interacting proteins identified by mass spectrometry, glycolysis-related genes, and CLIC1-associated genes from GeneCards and LinkedOmics databases. Eleven overlapping candidates were identified. (B–C) Exogenous Co-IP assays in 293T cells demonstrated that CLIC1 immunoprecipitated PKM2 and vice versa, confirming their reciprocal interaction. (D–E) Endogenous Co-IP assays in AGS and HGC27 gastric cancer cells further verified the specific interaction between CLIC1 and PKM2. (F–G) No interaction was detected between CLIC1 and the PKM1 isoform. (H) Immunofluorescence staining showed cytoplasmic co-localization of CLIC1 and PKM2 in AGS and HGC27 cells. (I) GST pull-down assay revealed that GST-tagged CLIC1 directly bound to PKM2, whereas the GST control did not. (J) Schematic representation of CLIC1 truncation mutants. (K) Co-IP assays demonstrated that full-length CLIC1 and two truncation mutants retained PKM2-binding ability

Although our results confirmed a direct interaction between CLIC1 and PKM2, the specific binding domains responsible for this interaction remaines unclear. To delineate the interaction interface on CLIC1, a series of domain truncation mutants were constructed based on its predicted structural regions (Fig. 3J). Subsequent Co-IP assays revealed that the full-length CLIC1 and two of its truncation mutants retained the ability to bind PKM2 (Fig. 3K), indicating that multiple regions of CLIC1 may contribute to the interaction. To further identify the corresponding binding region on PKM2, we generated a set of PKM2 truncation mutants spanning distinct structural domains (Fig. 4A). Co-IP validation demonstrated that deletion of the C-terminal domain abolished the interaction between PKM2 and CLIC1 (Fig. 4B), suggesting that the C-terminal region of PKM2 is essential for its binding to CLIC1.

Fig. 4.

Mapping of the CLIC1–PKM2 interaction domain and analysis of CLIC1’s effect on PKM2 expression and stability. (A) Diagram of PKM2 truncation mutants covering different structural domains. (B) Co-IP assays showed that deletion of the C-terminal domain abolished the interaction between PKM2 and CLIC1. (C–F) Western blot analysis showing that neither CLIC1 overexpression nor knockdown altered PKM2 protein expression levels in AGS and HGC27 gastric cancer cells.(G-H) CHX chase assay revealed that CLIC1 depletion did not affect PKM2 protein stability. Two-sided unpaired Student’s t-test between two groups, and one-way ANOVA among three or more groups. (*p < 0.05, **p < 0.01, ***p < 0.001, ns. not significant)

CLIC1 does not affect PKM2 protein expression or stability in gastric cancer cells

To investigate the functional significance of the CLIC1–PKM2 interaction, we first examined whether CLIC1 regulates PKM2 protein expression or stability in gastric cancer cells. Western blot analysis revealed that neither CLIC1 overexpression nor knockdown altered PKM2 protein levels in AGS and HGC27 cells (Fig. 4C–F). We next assessed the effect of CLIC1 on PKM2 protein stability using a CHX chase assay. The results showed that CLIC1 depletion did not affect PKM2 stability, as evidenced by comparable protein half-lives between control and CLIC1-knockdown cells (Fig. 4G–H). These findings suggest that CLIC1 does not regulate PKM2 through changes in its protein expression or degradation dynamics.

CLIC1 regulates the conversion between PKM2 dimers and tetramers and promotes its nuclear localization

To further elucidate the functional significance of the interaction between CLIC1 and PKM2, we next investigated whether CLIC1 affects the oligomeric state of PKM2. It is known that PKM2 exists in monomeric, dimeric, and tetrameric forms, with the tetramer representing the catalytically active conformation. To determine whether CLIC1 regulates PKM2 oligomerization, we performed protein cross-linking assays followed by Western blot analysis. The results showed that in both AGS and HGC27 cells, overexpression of CLIC1 promoted the formation of PKM2 dimers at the expense of tetramer formation (Fig. 5A–B), whereas CLIC1 silencing exerted the opposite effect, reducing dimers and increasing tetramers (Fig. 5C–D). Consistent with the protein crosslinking results, CLIC1 silencing led to an increase in PKM2 enzymatic activity (Supplementary Figure S1G). Furthermore, subcellular fractionation and Western blot analysis revealed that overexpression of CLIC1 markedly increased the nuclear localization of PKM2 (Fig. 5E–F). Consistent with these findings, immunofluorescence staining demonstrated that CLIC1 overexpression significantly enhanced PKM2 accumulation in the nucleus compared with control cells (Fig. 5G). To further investigate the molecular mechanism by which CLIC1 regulates PKM2, molecular docking analysis was performed. Consistent with the results of the bidirectional truncation mutants, the predicted binding interface between CLIC1 and PKM2 encompassed both truncation regions of CLIC1, whereas the interaction site on PKM2 was mainly located within its C-terminal domain (Fig. 5H).

Fig. 5.

CLIC1 regulates the oligomeric state and nuclear localization of PKM2. (A–B) Protein cross-linking and Western blot analyses showed that CLIC1 overexpression promoted PKM2 dimer formation while reducing tetramer formation in AGS and HGC27 cells. (C–D) Silencing of CLIC1 led to decreasing PKM2 dimers and increasing tetramers. (E–F) Subcellular fractionation and WB analyses demonstrating that CLIC1 overexpression enhanced the nuclear localization of PKM2. (G) Immunofluorescence staining confirmed that CLIC1 overexpression promoted PKM2 accumulation in the nucleus. (H) Molecular docking analysis indicated that the binding interface between CLIC1 and PKM2 covered both truncation regions of CLIC1, whereas the interaction site on PKM2 was primarily located within its C-terminal domain

CLIC1 promotes gastric cancer progression by modulating PKM2-mediated glycolysis

To elucidate the functional significance of the CLIC1–PKM2 regulatory axis in gastric cancer progression, we conducted a series of comprehensive in vitro and in vivo phenotypic assays. Gastric cancer cells overexpressing CLIC1 were treated with the PKM2 inhibitor PKM2-IN-1. WB analysis confirmed that PKM2-IN-1 treatment markedly reduced PKM2 protein levels (Fig. 6A). We next examined whether PKM2 inhibition could modulate CLIC1-mediated glycolytic regulation. The results showed that CLIC1 overexpression significantly enhanced lactate production and glucose consumption in gastric cancer cells, whereas co-treatment with PKM2-IN-1 partially but significantly attenuated these effects (Fig. 6B–C). These findings suggest that PKM2 plays an essential role in CLIC1-driven glycolytic reprogramming in gastric cancer cells.

Fig. 6.

CLIC1 promotes gastric cancer progression by modulating PKM2-mediated glycolysis. (A) WB analysis demonstrated PKM2 protein expression following PKM2-IN-1 treatment in AGS and HGC27 cells. (B–C) Quantification of lactate production (B) and glucose consumption (C) in control and CLIC1-overexpressing AGS and HGC27 cells with or without PKM2-IN-1 treatment. (D) CCK-8 assay showed that CLIC1 overexpression enhanced gastric cancer cell proliferation, whereas PKM2-IN-1 partially reversed this effect. (E–H) Representative images and quantitative analysis of wound-healing assays. (I–L) Representative images and statistical quantification of transwell migration and invasion assays. One-way ANOVA (*p < 0.05, **p < 0.01, ***p < 0.001)

We further explored the functional consequences of this metabolic regulation. CCK-8 assays demonstrated that CLIC1 overexpression promoted cell proliferation, while PKM2 inhibition partially reversed this proliferative advantage (Fig. 6D). Similarly, wound-healing assays revealed that CLIC1 overexpression accelerated cell migration, which was markedly suppressed by PKM2-IN-1 treatment (Fig. 6E–H). Consistently, transwell migration and invasion assays confirmed these findings, showing that inhibition of PKM2 partially abrogated the enhanced migratory and invasive capacities induced by CLIC1 overexpression (Fig. 6I–L).

To further substantiate our in vitro findings, we established xenograft tumor models using gastric cancer cells. Consistent with the in vitro phenotypes, tumors derived from CLIC1-overexpressing cells exhibited markedly accelerated growth kinetics compared with controls. Notably, treatment with the PKM2-IN-1 significantly attenuated CLIC1-driven tumor growth (Fig. 7A–D). There were no significant changes in body weight among the experimental groups during the treatment period (Supplementary Figure S2B). Collectively, these data demonstrate that CLIC1 promotes glycolysis-dependent proliferation, migration, and invasion of gastric cancer cells through the regulation of PKM2 activity, and that pharmacological inhibition of PKM2 can partially abrogate the tumor-promoting effects of CLIC1.

Fig. 7.

CLIC1 promotes gastric tumor growth through PKM2-dependent glycolysis in vivo. (A) Representative xenograft tumors from each group at the endpoint. (B) Tumor weights showed that PKM2-IN-1 treatment attenuated CLIC1-induced tumor growth. (C) Tumor growth curves depicted the kinetics of tumor volume expansion over time in each experimental group. (D) Representative IHC staining of CLIC1 and PKM2 in tumor tissues. One-way ANOVA. (*p < 0.05, **p < 0.01, ***p < 0.001)

Expression pattern and clinical relevance of PKM2 and CLIC1 in gastric cancer

Our previous studies have demonstrated that CLIC1 was upregulated in gastric cancer and promotes tumor progression through multiple mechanisms [32, 33]. To further elucidate the expression patterns and clinical significance of PKM2 and CLIC1 in gastric cancer, we performed integrated bioinformatic analyses and experimental validation. Using the TCGA-STAD cohort and the GEO dataset GSE66229, we analyzed the expression and correlation of CLIC1 and PKM2 in gastric cancer. The results revealed that both CLIC1 and PKM2 were significantly upregulated in tumor tissues compared with normal controls (Fig. 8A–D). Notably, a strong positive correlation was observed between CLIC1 and PKM2 expression levels (Fig. 8E; Supplementary Figure S3). Survival analysis based on the GSE62254 cohort indicated that high expression of CLIC1 and PKM2 was associated with poorer overall survival in gastric cancer patients (Fig. 8F–G). Consistently, survival analysis using the KMplot database showed that elevated PKM2 expression correlated with worse OS, PFS, and PPS (Fig. 8H–J).

Fig. 8.

Expression pattern and clinical relevance of PKM2 and CLIC1 in gastric cancer. (A–B) Differential expression analysis of CLIC1 (A) and PKM2 (B) between tumor and adjacent normal tissues in the TCGA-STAD cohort. (C–D) Expression levels of CLIC1 (C) and PKM2 (D) in gastric cancer and normal tissues from the GSE66229 dataset. (E) Correlation analysis of CLIC1 and PKM2 expression in the TCGA-STAD cohort. (F–G) Kaplan–Meier survival curves showing that high CLIC1 (F) and PKM2 (G) expression were associated with poor overall survival in gastric cancer patients from the GSE62254 cohort. (H–J) Kaplan–Meier plots illustrated that high PKM2 expression correlated with reduced OS, PFS, and PPS. (K) RT-qPCR analysis of PKM2 mRNA expression in paired gastric cancer and adjacent normal tissues. (L) Western blot analysis of PKM2 protein expression in representative paired GC and normal tissues. (M–N) Representative IHC staining and quantification of PKM2 (M) and CLIC1 (N) in paired gastric cancer specimens. (O) Correlation analysis between CLIC1 and PKM2 protein expression levels in gastric cancer tissues. Two-sided unpaired Student’s t-test. (*p < 0.05, **p < 0.01, ***p < 0.001)

We next validated these findings using paired clinical gastric cancer specimens. Consistent with the TCGA and GEO analyses, RT-qPCR confirmed significantly higher PKM2 mRNA levels in gastric cancer tissues compared to adjacent normal tissues (Fig. 8K). Similarly, Western blot analysis of paired samples demonstrated increased PKM2 protein expression in tumor tissues (Fig. 8L). In our gastric cancer patient cohort, PKM2 expression was positively associated with advanced T stage (Supplementary Table S1). Furthermore, IHC analysis of paired clinical specimens revealed elevated protein levels of both PKM2 and CLIC1 in gastric cancer tissues, with a significant positive correlation between their expression levels (Fig. 8M–O).

Discussion

In recent years, accumulating evidence has established CLIC1 as a key oncogenic driver across multiple cancer types, where it critically regulates tumor initiation and progression. In HCC, CLIC1 has been shown to promote metastasis by recruiting PIP5K1A/C, enhancing cell–matrix adhesion [26]. Similarly, in cervical cancer, CLIC1 drives proliferation, migration, and invasion in vitro, as well as tumor growth in vivo, primarily through activation of the NF-κB and PTEN/PI3K/AKT pathways [39, 40]. In colorectal cancer, CLIC1 modulates cancer cell migration and invasion via the ROS/ERK signaling cascade [41]. Beyond its pro-tumorigenic functions, CLIC1 has also been implicated in mediating drug resistance, further underscoring its clinical relevance [42, 43]. Our previous study demonstrated that CLIC1 was significantly upregulated in gastric cancer and was closely associated with tumor progression [30]. Mechanistically, CLIC1 enhances gastric cancer cell proliferation, invasion, and migration by activating the PI3K/Akt/MAPK axis [32]. Moreover, Our previous study also revealed that circ_0008287 promoted immune evasion and metastasis in gastric cancer by sponging miR-548c-3p to upregulate CLIC1 [33]. These findings highlight the multifaceted role of CLIC1 in cancer pathogenesis. However, the precise molecular mechanisms, particularly those involving its role in metabolic reprogramming remain poorly understood.

A recent study revealed that CLIC1 promotes pancreatic cancer growth by enhancing the Warburg effect via the ROS/HIF1α signaling pathway [34]. In our study, we established CLIC1 as a novel regulator of glycolytic reprogramming in gastric cancer, thereby revealing its previously unexplored role in metabolic reprogramming during gastric cancer progression. Through integrated glycolysis analysis and functional validation in both in vitro and in vivo models, we demonstrated that CLIC1 regulates glycolytic metabolism to promote gastric cancer progression. Furthermore, through GST, Co-IP and DSS crosslinking assays we confirmed that CLIC1 could bind to the C-terminal domain of PKM2, rather PKM1, and mediated dimer stabilization of PKM2, which provided conclusive evidence that this interaction drives metabolic rewiring independent of PKM2 expression changes. Previous studies have revealed that PKM1 and PKM2 are produced from the PKM gene through mutually exclusive splicing of exons 9 and 10. Although they share a similar overall structure, PKM2 has an additional 45–amino acid sequence in its C-terminal domain near the dimer–dimer interface, endowing it with unique structural and regulatory properties [44]. Structurally, PKM2 composed of four distinct domains: the N domain (residues 1–43); the A domain (subdivided into A1: residues 44–115 and A2: residues 217–388), which contains the active site for the phosphate transfer reaction; the B domain (residues 116–217), which bridges A1 and A2; and the C domain (residues 389–531), which harbors regulatory allosteric elements [45]. In our study, we identified that CLIC1 specifically interacts with the C domain of PKM2. Given that this domain harbors key allosteric regulatory sites, we speculate that CLIC1 binding may influence the conformational equilibrium between PKM2 dimers and tetramers by modulating these allosteric elements. This potential structural regulation could represent a novel mechanism through which CLIC1 modulates PKM2 enzymatic activity and glycolytic flux, thereby contributing to metabolic reprogramming in gastric cancer cells. Further functional and structural investigations, will be necessary to validate this hypothesis and delineate the precise interface between CLIC1 and PKM2.

Our findings unveiled a paradigm-shifting aspect wherein CLIC1 directly interacts with the glycolytic enzyme PKM2, thereby reinforcing the Warburg effect. The data indicated that gastric cancer utilized a distinct mechanism wherein CLIC1 hijacked metabolic control via PKM2, underscoring a tissue-specific adaptation of oncogenic pathways. Notably, while PKM2 regulation by HIF-1α in bladder cancer [46] or DDX39B in colorectal cancer [22] involved transcriptional or stabilization mechanisms, CLIC1 represents a novel class of PKM2 regulators that manipulate oligomeric states without affecting protein abundance. This distinction became particularly significant when considering PKM2’s structural plasticity, as cancer cells typically exploit dimeric forms for biosynthetic advantage [47, 48]. Our observation that CLIC1 depletion restored tetramerization and pyruvate kinase activity implied that targeting this axis could selectively disrupt cancer-specific metabolic dependencies.

It has been well established that multiple post-translational modifications (PTMs), including acetylation, lactylation, palmitoylation, and ubiquitination, can drive the interconversion between dimeric and tetrameric PKM2 [45]. These modifications collectively promote the formation of dimers, thereby facilitating metabolic reprogramming [18, 20]. Moreover, numerous proteins that directly interact with PKM2 have been reported to regulate its oligomeric state and nuclear translocation [49, 50]. Structurally, the tetrameric form of PKM2 is stabilized by extensive inter-subunit interactions that conceal the dimerization interface located within the C-domain. In our study, we found that CLIC1 binds to the C-terminal domain of PKM2. Overexpression of CLIC1 increased the abundance of dimeric PKM2, suggesting that CLIC1 binding may sterically hinder the formation of PKM2 tetramers. Within this sophisticated regulatory framework, our study identified CLIC1 could be a novel effector that stabilizes PKM2 dimers, distinct from canonical PTM-based mechanisms. Although the precise binding interface has yet to be elucidated, the functional outcomes were clear: CLIC1 stabilizes PKM2 dimers, leading to consequently redirecting glycolytic intermediates towards anabolic pathways. This metabolic reorientation likely underlies the observed cancer cells proliferative and invasive phenotypes. The broader implications extend beyond energy production, as the role of nuclear PKM2 as a transcriptional coactivator [51] prompts intriguing inquiries regarding the potential influence of CLIC1 on its nuclear translocation, thereby amplifying glycolytic gene expression. This suggests a potential feed-forward loop that merits further investigation.

In translating these insights into clinical applications, the CLIC1-PKM2 axis offers both diagnostic and therapeutic potential. Bioinformatic analyses and examinations of clinical tissue samples have demonstrated their co-overexpression in aggressive subtypes of gastric cancer, which is associated with poor prognosis. This suggests their utility as combinatorial biomarkers for metabolic subtyping. Therapeutically, strategies aimed at disrupting this interaction could be explored. These include the development of small molecules that mimic the CLIC1 binding domain or stabilizers of the PKM2 tetramer, which may exploit this vulnerability while minimizing off-target effects due to the differential oligomerization of PKM2 in tumors versus normal tissues. Moreover, integrating metabolic targeting of the CLIC1–PKM2 axis with existing treatment modalities, such as chemotherapy or immune checkpoint blockade, may further enhance therapeutic efficacy by simultaneously disrupting tumor metabolic adaptation and immune evasion. Nonetheless, challenges remain due to the widespread expression of CLIC1; thus, conditional targeting strategies or nanoparticle-mediated delivery systems may be required to achieve tissue specificity.

Beyond intrinsic tumor signaling, external factors such as the tumor microbiota may also influence gastric cancer metabolism and therapeutic responses. Recent studies have revealed that the intratumoral microbiota can influence the initiation and progression of various cancers, including gastric cancer [52]. For instance, Zhang et al. demonstrated that Fusobacterium nucleatum within the tumor microenvironment activates NF-κB signaling to facilitate gastric cancer immune evasion by promoting tumor-associated neutrophil recruitment, thereby sensitizing tumors to immune checkpoint blockade therapy [53]. Similarly, tumor-colonizing Streptococcus mutans has been shown to metabolically reprogram the tumor microenvironment and promote the progression of oral squamous cell carcinoma [54]. Although accumulating evidence indicates that microbial metabolism plays a crucial role in tumor immunity and cancer progression, the potential connection between the CLIC1–PKM2 axis and the microbiota remains unclear and warrants further investigation. In this context, future studies exploring host–microbiota–metabolism crosstalk may provide new insights into how microbial metabolites modulate tumor glycolysis and therapeutic outcomes. Moreover, before clinical translation of CLIC1–PKM2–targeted interventions, systematic evaluation of biosafety and off-target effects will be essential to ensure therapeutic feasibility.

Our findings substantially deepen the understanding of CLIC1’s role in gastric cancer metabolism; however, several limitations should be acknowledged. Although we demonstrated that CLIC1 promotes glycolytic reprogramming by stabilizing PKM2 dimers and impeding its tetramerization, the precise molecular mechanisms governing this regulation remain to be elucidated. Structural and biochemical evidence indicated that CLIC1 interacts with the C-terminal domain of PKM2, yet the exact binding interface and interacting residues have not been identified. Further structural characterization of the CLIC1–PKM2 complex, for instance by cryo-electron microscopy or crystallography, would provide atomic-level insights to enable rational drug design. Moreover, our results suggested that CLIC1 modulates not only the oligomeric state but also the subcellular distribution of PKM2, as CLIC1 overexpression stabilized PKM2 dimers and enhanced its nuclear localization. Future studies should therefore explore how CLIC1-mediated PKM2 stabilization integrates with its transcriptional coactivator functions and whether this axis coordinates with other metabolic enzymes such as HK2 to orchestrate global metabolic reprogramming. Despite these limitations, our study identifies a previously unrecognized CLIC1–PKM2 metabolic axis in gastric cancer and establishes a conceptual framework for understanding ion channel proteins as pivotal regulators of tumor metabolism and progression.

Conclusion

In summary, our study reveals a previously unrecognized role of CLIC1 as a metabolic regulator in gastric cancer. We provide the first evidence that CLIC1 directly interacts with the C-terminal domain of PKM2, functioning as an allosteric modulator that stabilizes its dimeric form and promotes nuclear localization. This interaction drives glycolytic reprogramming and thereby facilitates gastric cancer proliferation, invasion, and tumor growth. Collectively, these findings not only expand the current understanding of metabolic dysregulation in gastric cancer but also highlight the CLIC1–PKM2 axis as a potential therapeutic target. Targeting this interaction to restore PKM2 tetramerization may represent an innovative strategy to disrupt aberrant glycolytic flux and attenuate gastric cancer progression.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

Jian Yang: Data curation, Visualization, Validation, Writing–original draft, Conceptualization. Zhu Yu: Methodology, Formal analysis, Writing–original draft. Yue Feng: Methodology, Validation. Shengyu Wang: Software, Supervision, Validation. Changhua Li: Data curation, Validation. Yuantian Mao: Data curation, Validation. Wenqian Xu: Data curation, Methodology. Junqiang Chen: Project administration, Resources, Supervision, Writing–review & editing. All authors reviewed and recommended the editing and approval of the final manuscript.

Funding

This study was supported by The Guangxi Key Research and Development Project (No.AB24010149), The Guangxi Clinical Research Center for Enhanced Recovery after Surgery, Guangxi Science and Technology Base and Talent Project (No.AD19245196), and Innovation Project of Guangxi Graduate Education (No.YCBZ2025110).

Data availability

The data used to support the findings of this study were obtained from the TCGA and GEO databases.

Declarations

Conflict of interest

The authors have no conflicts of interest to declare.