In total, 50 pairs of GC and adjacent normal tissues were resected from patients at the First Hospital of Hebei Medical University. None of the patients underwent chemotherapy/radiation before surgery. Isolated specimens were snap-frozen in liquid nitrogen and stored at Hebei Medical University First Hospital Biobank. In this study, histologically confirmed gastric adenocarcinoma, including signet-ring cell carcinoma subtypes, was utilized for tumor tissue analysis. The study protocol, including patients and samples, was approved by the Ethics Committee of Hebei Medical University First Hospital and followed the principles of the Declaration of Helsinki (Approval No. S00826). The studies were conducted in accordance with the local legislation and institutional requirements. The ethics Committee review board waived the requirement of written informed consent for participation from the participants or the participants’ legal guardians/next of kin because the use of these specimens falls under the “exemption category” defined by the National Health Commission and the institutional ethics guidelines, as the research involves no intervention, no additional risk to patients, and no impact on their treatment or privacy. The specimens were originally retained for potential future research purposes with prior generic consent obtained during hospitalization.

GC cells (NUGC-3, Hs746T) were obtained from Shanghai iCell Bioscience Inc., and human gastric mucosa cells (GES-1) and GC cells (HGC-27, AGS), which were confirmed by STR analysis, from Wuhan Pricella Biotechnology Co., Ltd. The cells were cultured in RPMI 1640 or DMEM (Gibco, Carlsbad, CA, USA) supplemented with 10% fetal bovine serum (Gibco) and 1% penicillin–streptomycin solution (Solarbio Science and Technology Co., Ltd., Beijing, China). Cells were cultured in a 37°C incubator with 5% CO₂. Monthly mycoplasma screening was performed via PCR, and the number of cell passages was strictly limited to no more than 30.

Transfections were performed using Lipofectamine 3000 (Invitrogen; Carlsbad, CA, USA; Catalog number: L3000008) once the cells reached 60%–70% confluence. NUGC-3/Hs746T and HGC-27/AGS cells were transfected with four INHBA-targeting siRNA sequences (si281, si382, si499, si822) or overexpressed pcDNA3.1-INHBA plasmids (with negative controls; GenePharma Co., Ltd., Shanghai, China). To identify the most effective siRNA against ITGA6, we screened four candidates (si614, si1293, si1595, si2679) in AGS cells. This screening revealed siITGA6-614 as the most effective, demonstrating superior silencing efficiency. In rescue experiments, NUGC-3 received ITGA6 overexpression (pcDNA3.1-ITGA6) and INHBA silencing (siRNA-INHBA), whereas AGS underwent ITGA6 silencing (siRNA-ITGA6) and INHBA overexpression (pcDNA3.1-INHBA). Functional assays were conducted 48 h after transfection. For a stable clone selection, neomycin (600 μg/mL) was introduced into HGC-27 cultures 48 h after transfection of the INHBA overexpressed plasmid to generate oe-Vector and oe-INHBA isogenic cell lines (antibiotic-free background). G418 is an antibiotic that inhibits protein synthesis by blocking the extension steps in prokaryotic and eukaryotic cells. Once a monoclonal colony was established, the cells were cultured in medium supplemented with 300 μg/mL G418 (Solarbio Science and Technology Co., Ltd., Beijing, China) for 10 consecutive days to stabilize transgenic expression.

Total RNA was isolated from cells (GES-1, HGC-27, AGS, NUGC-3 and Hs746T) and tissue samples using RNA-Easy Isolation Reagent (Vazyme Biotech Co., Ltd., Nanjing, China; Catalog number: R701-01). Reverse transcription was performed using the PrimeScript RT Reagent Kit (Takara Bio, Beijing, China; Catalog number: RR037A) to synthesize complementary DNA (cDNA). For quantitative reverse transcription–polymerase chain reaction (qRT–PCR), reactions were performed using AceQ Universal SYBR qPCR Master Mix (Vazyme). β-Actin mRNA was used as the endogenous reference for normalization. All experiments included three technical replicates per sample. Supplementary Table S1 presents the primers used. To calculate relative mRNA expression levels, cycle threshold values were analyzed using the 2^−∆∆CT method.

Protein extraction was performed from cells (GES-1, HGC-27, AGS, NUGC-3 and Hs746T) using RIPA lysis buffer (Solarbio, Beijing, China; Catalog number: R0010) mixed with protease/phosphatase inhibitor (Boster, Wuhan, China; Catalog number: AR1182) at a 100:1 ratio. The animal tumor tissues (INHBA over-expression and vector group) were washed with PBS buffer and cut into pieces and then the protein extraction process was the same of the cells. After shaking at 4°C for 30 min, the protein mixtures were centrifuged at 12,000× g for 10 min at 4°C. The supernatant was collected to detect protein concentrations using a protein assay kit (Solarbio, Beijing, China; Catalog number: PC0020) and the protein concentration was adjusted to an equivalent loading of total protein. 30 μg of total protein was loaded in each lane. Proteins were separated via electrophoresis on 10% SDS-polyacrylamide gels (Bio-Rad Laboratories Inc., Hercules, CA, USA) and then transferred to a polyvinylidene fluoride membrane (Merck Millipore, Billerica, MA, USA). After blocking with milk for 2 h, samples were incubated with diluted antibodies. The antibodies used were as follows: GAPDH (diluted 1:500; Goodhere-Bio, Hangzhou, China; Catalog number: AB-P-R001), INHBA (diluted 1:500; Proteintech, Wuhan, China; Catalog number: 17524-1-AP), ITGA6 (diluted 1:500; Proteintech, Catalog number: 27189-1-AP), MEK1/2 (diluted 1:1000; Proteintech; Catalog number: 11049-1-AP), phospho-MEK1 (diluted 1:1000; Proteintech; Catalog number: 28930-1-AP), ERK1/2 (diluted 1:1000; Proteintech; Catalog number: 66192-1-Ig), and phospho-ERK1/2 (diluted 1:100; Proteintech; Catalog number: 28733-1-AP). The Odyssey scanning system (LI-COR Biosciences, Lincoln, NE, USA) was used to identify immunoreactive protein bands. All experiments were performed in independent replicates.

For the CCK-8 assay, cells (HGC-27, AGS, NUGC-3 and Hs746T) from each group were evenly seeded in 96-well plates at a density of 2 × 10³ cells per well and cultured in complete medium. At 24, 48, 72, and 96 h post-seeding, 10 μL of a Cell Counting Kit-8 reagent (CCK-8; Dojindo, Tokyo, Japan; Catalog number: CK04) was added to each well. After a 2-h incubation, absorbance was measured at 450 nm using a Promega GloMax luminescence detector (Promega, Madison, WI, USA).

In the colony formation assay, cells (AGS and NUGC-3) were plated at a density of 1000 cells per well in 6-well plates and cultured in complete medium, replaced every 3 days. After 7–14 days, the cells were washed twice with 1× PBS (pH 7.2–7.4), fixed with 4% PFA for 30 min, and then stained with 0.1% crystal violet for 20 min. The cells were again washed twice with 1× PBS (pH 7.2–7.4) followed by dehydration in the air. Finally, the stained cell colonies were counted using the ImageJ software (ImageJ 1.53e, National Institutes of Health, Bethesda, MD, USA).

In the wound-healing assay, cells (HGC-27, AGS, NUGC-3 and Hs746T) from each group were seeded in six-well plates (3 × 10⁵ cells per well). Once the cells reached 100% confluence, a 200-μL pipette tip was used to draw two straight lines in each well to mimic wounds. After washing twice with 1× PBS (pH 7.2–7.4), the cells were cultured in serum-free medium. Wound images were obtained by a microscope (TE2000-U, Nikon, Tokyo, Japan) at 0 and 48 h, and the migration rate was calculated as the ratio of the gap width at 0 h to that at 48 h.

For the Transwell migration assay, 4 × 10⁴ (HGC-27, AGS) or 6 × 10⁴ (NUGC-3, Hs746T) cells in 200-μL serum-free medium were added to the upper chamber (Corning Incorporated, Corning, NY, USA), whereas 700 μL of complete medium was added to the lower chamber to induce cell migration. After a 48-h incubation, cells on the upper side of the polycarbonate membrane were removed using a cotton swab. The membrane was washed twice with 1× PBS (pH 7.2–7.4), fixed with 4% PFA for 30 min, and then stained with 0.1% crystal violet for 20 min. Excess stain was removed through PBS washing. Images of five randomly selected fields were obtained, and the stained cells were counted using the ImageJ software (ImageJ 1.53e, National Institutes of Health, Bethesda, MD, USA).

To facilitate downward invasion, GC cells (HGC-27, AGS, NUGC-3 and Hs746T) were resuspended in 100-μL serum-free medium and seeded into the upper chamber, whereas 600-μL complete medium was added to the lower chamber for the Transwell invasion assay. All the other experimental procedures were performed according to the same protocol used in the Transwell migration assay.

After 48 h of transfection, the cells (HGC-27, AGS, NUGC-3 and Hs746T) were collected from each group and stained with Annexin V-FITC/PI apoptosis assay kit (NeoBioscience, Shenzhen, China; Catalog number: FAK015.50). Every tube of cells was added to 300 μL buffer, followed by 5 μL Annexin-V-FITC and 10 μL PI stain, which was then shaken. The reaction was carried out in the dark at room temperature for 20 min. A total of 1 × 10⁵ cells were analyzed for apoptosis via flow cytometry (BD Biosciences, San Jose, CA, USA; number: 342976). HGC-27cells were transfected with INHBA over-expressed plasmid or empty plasmid as negative control. The flow cytometry Annexin-FITC/PI double staining method utilizes Annexin-V to specifically bind to phosphatidylserine that was efflorescated in the early stage of apoptosis, while PI only passes through the damaged cell membrane to mark nucleic acids. Lower left quadrant (Annexin-FITC-/PI-): indicating a living cell. Right lower quadrant (Annexin-FitC+/PI-): indicating early apoptotic cells. Upper right quadrant (Annexin-FITC+/PI+): corresponding to late apoptosis or necrotic cells. Upper left quadrant (Annexin-FITC-/PI+): mostly due to mechanical injury, cell fragments or necrotic cells. The apoptosis experimental design of other cell lines is similar to that of HGC27. The apoptotic rate was calculated using the FlowJo software (FlowJo 10.9.0, BD Biosciences, Portland, USA).

A total of 10 male BALB/c nude mice weighing between 12 and 16 g and aged 4–5 weeks were obtained from Beijing Sibeifu Biotechnology Co., Ltd. They were randomly divided into two groups, each consisting of five animals, and housed in a pathogen-free environment with ad libitum access to food and water. The environment was maintained at a temperature of approximately 22°C and a 12-h light/dark cycle. After the skin of the left hind limb flank of the nude mice was disinfected, the mice were subcutaneously inoculated with stable overexpression of INHBA and negative control HGC-27 cells (6 × 10⁶ cells per mouse) using a two-sterile syringe. Starting on day 4 post-injection, tumor size was measured every 2 days, and the volume was measured by the following equation: 0.5 × long diameter × short diameter². The mice were humanely euthanized on the day 18 post-injection. Subsequently, the tumor tissues were sectioned, paraffin-embedded, and then subjected to HE staining and immunohistochemistry (IHC). The study protocols were approved by the Experimental Animal Care and Ethics Committee of Hebei Medical University First Hospital (Approval No. S00825).

Tissue samples from patients and nude mice were fixed in 4% paraformaldehyde (PFA) solution and paraffin-embedded using standard histological procedures (Shanghai YiYang Instrument Co., Ltd., China). Subsequently, 4-μm-thick sections were prepared and stained. For immunohistochemical analysis, the sections were processed using a Rabbit two-step detection kit (ZSGB-Bio, Beijing, China; Catalog number: PV-6001) in accordance with the manufacturer’s protocol. The following primary antibodies obtained from Proteintech (Wuhan, China) were used: INHBA (diluted 1:200; Proteintech; Catalog number: 17524-1-AP), Ki67 (diluted 1:100; Proteintech; Catalog number: 27309-1-AP), and ITGA6 (diluted 1:500; Proteintech; Catalog number: 27189-1-AP).

The IHC staining score included the proportion of positively stained tumor cells and staining intensity. The proportion of positively stained tumor cells was scored as follows: 0 (no tumor cells stained), 1 (<25% tumor cells stained), 2 (25%–50% tumor cells stained), 3 (50%–75% tumor cells stained), and 4 (75%–100% tumor cells stained). Staining intensity was graded using the following criteria: 3 (brown, strong staining), 2 (yellow brown, moderate staining), 1 (light yellow, weak staining), and 0 (no staining). The total staining score was calculated by multiplying the proportion of stained tumor cells by the staining intensity score. A score of ≤3 indicated negative expression, while a score of >3 indicated positive expression. Pathological diagnosis was made in accordance with the histological classification of tumors developed by the World Health Organization.

After 24-h transfection with siRNA-NC and siRNA-INHBA, total RNA was extracted from NUGC-3 cells. Beijing Novogene Technology Co., Ltd., performed RNA library preparation and sequencing analysis. Briefly, six samples (triplicates of siRNA negative control [siNC] and INHBA-targeting siRNA [siINHBA]) were sequenced on an Illumina NovaSeq 6000 platform. Raw sequencing data were subjected to quality control and filtering to obtain high-quality reads, which were then aligned with reference genomes using the HISAT2 (HISAT2 2.2.1) software for gene expression quantification. Differentially expressed genes (DEGs) were identified using the DESeq2 (DESeq2 v2.1) software with the threshold criteria of log2 |FoldChange| ≥ 0 and p-value < 0.05. INHBA silencing induced widespread transcriptome dysregulation, comprising 1112 and 846 up- and down-regulated genes, as shown in the gene expression heatmap and volcano plot. Through the analysis of RNA-seq-identified downregulated genes (log2Fold Change > 1, p < 0.05), along with the 3742 genes that are highly expressed in GC within the GEPIA2 database, several genes were identified as potential candidates for binding to the INHBA protein.

NUGC-3 cells were evenly seeded onto coverslips placed in six-well plates (7 × 10⁵ cells/well). At 20%–30% confluence, the cells were gently washed three times with 1× PBS (pH 7.2–7.4). Subsequently, the cells were sequentially processed as follows: blocked with 2% bovine serum albumin (BSA-V; Solarbio; Catalog number: A8020), fixed with 4% PFA, and penetrated with 0.2% Triton X-10 (Solarbio; Catalog number: T8200). Primary INHBA antibody (diluted 1:50; Proteintech; Catalog number: 17524-1-AP) and ITGA6 antibody (diluted 1:50; Santa Cruz Biotechnology, Dallas, TX, USA; Catalog number: sc-374057) were added to the cells and incubated overnight at 4°C. After incubation of the primary antibody, the cells were incubated with fluorescently labeled secondary antibodies (1:500 dilution; Cy3 Anti-Rabbit IgG, FITC Anti-Mouse IgG; Beyotime Biotechnology Co., Shanghai, China; Catalog numbers: A0516 and A0568) for 1 h at room temperature in the dark. Finally, nuclei were stained with 4^′6^′-diamino-2-phenylindole dihydrochloride (1 ug/mL) (Beyotime Biotechnology Co., Shanghai, China). Representative images were then acquired using a fluorescence microscope (Eclipse Boi, Nikon, Tokyo, Japan).

NUGC-3 cells were washed twice with 1× PBS (pH 7.2–7.4) under gentle conditions. Cell lysis was performed using the Pierce™ Classic Magnetic IP/Co-IP Kit (Thermo Scientific, Waltham, MA, USA; Cat# 88804) according to the manufacturer’s protocol. Then, the lysate was mixed with 10 μg of the INHBA, ITGA6, and IgG control antibodies obtained from Proteintech. Next, the mixture was incubated at room temperature for 2 h with gentle rotation. After the addition of magnetic beads to the lysate, the mixture was continuously rotated at room temperature for 1 h. After magnetic bead separation, proteins were eluted with an elution buffer. The pH was neutralized using a neutralization buffer. The resulting samples were analyzed via Western blot (WB).

The expression levels of INHBA mRNA in GC tissues and adjacent normal tissues were analyzed using the Gene Expression Omnibus database (GEO) (https://www.aclbi.com/static/index.html#/geo). Gene expression levels and survival analysis in GC were analyzed using Gene Expression Profiling Interactive Analysis 2 (GEPIA2) (http://gepia2.cancer-pku.cn/#index), whereas subcellular localization was analyzed using GeneCards (https://www.genecards.org/). Specific primers were designed and validated using PrimerBank (https://pga.mgh.harvard.edu/primerbank/) in combination with an advanced primer design tool (https://www.nc/bi.nlm.nih.gov/tools/primer-blast/). KEGG enrichment analysis was conducted on the DAVID (Database for Annotation, Visualization, and Integrated Discovery) (https://davidbioinformatics.nih.gov/). Several candidate genes regulated by INHBA are screened through the Venn diagram (https://bioinfogp.cnb.csic.es/tools/venny/).

Three independent experiments were conducted for each group to ensure the reliability of the results, in accordance with established guidelines within the field. Normally distributed data were expressed as mean ± standard deviation, whereas non-normally distributed data were expressed as median and interquartile distance. All statistical analyses were conducted using SPSS 26.0 (IBM, Armonk, NY, USA) and GraphPad Prism 9.5 (GraphPad Software, La Jolla, CA, USA) software. Student’s t-test was employed for pairwise comparisons, one-way analysis of variance (ANOVA) for single-factor group comparisons, and two-way ANOVA for assessing interactions between two independent variables. p < 0.05 was considered statistically significant.

Data supporting the findings of this study are available from the corresponding author upon request. Gene Expression Profiling Interactive Analysis (GEPIA2) and Gene Expression Omnibus (GEO) at GSE63089 and GSE66229 provided the data used in this analysis.

To elucidate the role of INHBA in the GC pathophysiology, we initially assessed its expression in GC tissues and adjacent normal tissues using data from the GEO database, specifically the GSE63089 and GSE66229 datasets. Our analysis revealed substantial upregulation of INHBA expression in GC tissues relative to adjacent normal tissues, as presented in Fig. 1A. This finding was further corroborated by the significant upregulation of INHBA in stomach adenocarcinoma (STAD) tissues, as shown by analysis conducted using the GEPIA2 online tool (Fig. 1B). Survival analysis using GEPIA2 revealed that patients with GC demonstrating high INHBA expression had significantly poorer OS than those with low INHBA expression (Fig. 1C). Based on existing knowledge of the functional role of INHBA in GC, we used it as the target gene for further investigation. We verified INHBA mRNA expression in 34 pairs of GC tissues and their adjacent normal tissues via qRT–PCR. The results indicated a statistically significant upregulation of INHBA mRNA in GC tissues compared with normal tissues (p < 0.05) (Fig. 1D). To confirm these findings at the protein level, IHC was conducted on GC tissues and adjacent normal tissues, which revealed that INHBA protein was localized in the cytoplasm of GC cells and significantly overexpressed in GC tissues (p < 0.001, χ² = 19.485) (Fig. 1E, Table 1). Furthermore, the correlation between INHBA expression and the clinical characteristics of patients with GC was investigated. Our analysis revealed that the INHBA expression was not associated with gender, age, tumor size, and tumor differentiation. However, it was found to be significantly associated with tumor lesion, lymph node metastasis, and TNM stage (*p < 0.05, **p < 0.01, ***p < 0.001) (Table 2). These findings suggest that INHBA overexpression is closely related to poor prognosis in patients with GC, indicating its potential as a prognostic biomarker and a therapeutic target in GC. Finally, the mRNA and protein expression levels of INHBA in different GC cell lines and GES-1 cells were evaluated via qRT-PCR and WB (Supplementary Fig. S1A,B).

To explore the functional role of INHBA in GC, we first downregulated INHBA expression in NUGC-3 and Hs746T cell lines and evaluated its impact on various cellular processes. After transfection with siINHBA, considerable reductions in INHBA mRNA (Fig. 2A,B) and protein (Fig. 2C,D) levels were observed compared with the siNC. Among the four siRNA sequences of INHBA (si281, si382, si499, si822), the si382 decline elicited the most evident effect; thus, it was selected for subsequent cell function knockdown experiments. The CCK-8 assay revealed that the viability of NUGC-3 and Hs746T cells was markedly reduced after INHBA knockdown compared with the control group (Fig. 2E,F). The wound healing assay revealed that the migratory capacity of INHBA knockdown cells was significantly impaired compared with that of the control group in NUGC-3 and Hs746T cells after 48 h (Fig. 2G,H). Flow cytometry analysis revealed a considerable increase in the number of apoptotic cells in NUGC-3 and Hs746T cell lines after INHBA silencing compared with that in the control group (Fig. 2I,J). The Transwell assay results indicated a significant reduction in the migratory and invasive capacities of NUGC-3 and Hs746T cell lines in the INHBA-KO group (Fig. 2K–N). These findings suggest that INHBA downregulation promotes apoptosis while inhibiting the invasion, migration, and proliferation of GC cells.

To further investigate the function of INHBA in cellular biological processes, we upregulated its expression in HGC-27 and AGS cell lines. pcDNA3.1-INHBA transfection considerably increased the INHBA mRNA (Fig. 3A,B) and protein (Fig. 3C,D) levels compared with pcDNA3.1-vector control transfection. The CCK-8 assay demonstrated that INHBA overexpression significantly increased HGC-27 and AGS cell viability compared with the control group (Fig. 3E,F). The wound-healing assay revealed that INHBA upregulation significantly enhanced cell migration in HGC-27 and AGS cells after 48 h (Fig. 3G,H). Meanwhile, flow cytometry analysis showed that INHBA upregulation significantly alleviated apoptosis in HGC-27 and AGS cells (Fig. 3I,J). Moreover, the Transwell assay demonstrated that INHBA upregulation significantly enhanced the migratory and invasive capacities of HGC-27 and AGS cells (Fig. 3K–N). In summary, our findings suggest that INHBA acts as a pro-oncogene in GC, promoting invasion, migration, and proliferation while inhibiting apoptosis.

To better investigate the role of INHBA in vivo, we created a subcutaneous xenograft model in BALB/C nude mice using HGC-27 cells transfected with INHBA-overexpressing or control vectors. Through qRT-PCR and WB, we first confirmed INHBA overexpression in stably transfected cell lines (Fig. 4A,B), validating the successful construction. HGC-27 cells stably transfected with INHBA-overexpressing or empty vectors were subcutaneously injected into BALB/C nude mice to construct a subcutaneous xenograft model. Fig. 4C–F demonstrate that INHBA-overexpressing tumors displayed significantly higher growth rates, volumes, and weights than the vector group in subcutaneous xenograft models. Histopathological analysis of subcutaneous xenograft model tissues via HE staining revealed that the cellular architecture and morphological features closely resembled those of human GC tissues (Fig. 4G). IHC for Ki67 revealed a considerable increase in the cell proliferative capacity of the INHBA-overexpressing group than the vector group (Fig. 4H). These findings indicate that INHBA overexpression promotes GC progression in vivo.

To elucidate the pathophysiological role of INHBA in GC, we performed transcriptome RNA-seq on NUGC-3 cells transfected with either nontargeting siRNA (siNC) or siINHBA. The results indicated that INHBA silencing induced widespread transcriptome dysregulation, with 1958 differentially expressed genes identified, comprising 1112 and 846 up- and down-regulated genes, respectively, as shown in the gene expression heatmap and volcano plot (Fig. 5A,B). Through the analysis of RNA-seq-identified downregulated genes (log2Fold Change > 1, p < 0.05), along with the 3742 genes that are highly expressed in GC within the GEPIA2 database, 10 genes were identified as potential candidates for binding to the INHBA protein (Fig. 5C). As INHBA is localized extracellularly and cytoplasmic, we selected membrane proteins from the candidate genes as potential targets for INHBA regulation. Among the 10 candidate genes, ITGA6 was the only membrane protein that exhibited broad distribution across multiple cellular compartments in GC cells. Bioinformatics analysis using the GEPIA2 database revealed that ITGA6 showed a constitutive overexpression in gastric adenocarcinoma specimens (Fig. 5D), with multicompartment localization patterns demonstrating predominant distribution in the cytomembrane, cytoplasm, and nucleus domains (Fig. 5E). Therefore, we speculated that ITGA6 is a potential downstream target gene. Subsequently, Co-IF and Co-IP assays were conducted to demonstrate the interaction between INHBA and ITGA6. Immunofluorescence co-localization analysis revealed that co-localization of INHBA and ITGA6 is mainly observed in the cytoplasm and cytomembrane of GC cells (Fig. 5F). Co-IP assay confirmed direct interaction between INHBA and ITGA6 in GC cells (Fig. 5G). To confirm the INHBA-mediated regulation of ITGA6 expression, we performed bidirectional INHBA modulation (knockdown and overexpression) in GC cells. INHBA knockdown decreased ITGA6 mRNA and protein expressions in NUGC-3 cells (Fig. 5H,I). Conversely, INHBA upregulation increased the ITGA6 mRNA and protein expression levels in AGS cells (Fig. 5J,K). These results suggest that INHBA regulates downstream gene expression at the transcriptional and translational levels. In summary, these results indicated a functional interaction between INHBA and ITGA6 in GC and that ITGA6 may act as a potential modification target of INHBA in GC.

Next, we evaluated ITGA6 expression in GC cell lines and clinical specimens.

Quantitative analysis revealed that the majority of GC cell lines exhibited a significant increase in ITGA6 mRNA expression compared with normal gastric mucosa cells (Fig. 6A). WB analysis revealed that NUGC-3 exhibited the highest ITGA6 protein expression among all the tested cell lines (Fig. 6B). IHC analysis of 30 paired clinical specimens revealed that the GC tissues exhibited higher ITGA6 expression (positive rate 80%) than the adjacent normal tissues (positive rate 40%) (Fig. 6C). These results suggest that ITGA6 is highly expressed in GC tissues and various GC cell lines. Further studies are warranted to determine how the INHBA–ITGA6 interaction contributes to gastric carcinogenesis. The cell lines were selected based on the baseline ITGA6/INHBA expression level. Functional screening of four ITGA6-targeting siRNAs in AGS cells with the highest ITGA6 mRNA expression revealed that siITGA6-614 showed superior silencing efficiency and was thus prioritized for further analyses (Fig. 6D,E). Subsequently, we applied reciprocal modulation strategies in GC cell models: NUGC-3 received ITGA6 overexpression (pcDNA3.1-ITGA6) and depletion with INHBA (siRNA-INHBA), whereas AGS underwent ITGA6 silencing (siRNA-ITGA6) and INHBA overexpression (pcDNA3.1-INHBA). qRT–PCR and WB were employed to identify variations in INHBA expression between the groups. The results indicated that ITGA6 overexpression could inhibit the INHBA knockdown effect in NUGC-3 cells (Fig. 6F,G). Similarly, ITGA6 silencing mitigated the effect of INHBA overexpression in AGS cells (Fig. 6H,I). These results indicate that ITGA6 can influence INHBA expression in GC cells.

To further explore the molecular mechanism of INHBA and ITGA6, we selected the top 1000 genes co-expressed with INHBA and ITGA6 in GC from the GEPIA2 database and analyzed the signaling pathways these genes controlled. KEGG pathway enrichment analysis using the DAVID revealed that gene clusters were markedly enriched in the MAPK signaling pathways (Fig. 7A). Therefore, we speculated that INHBA activates ITGA6 via the MAPK signaling pathway to promote GC progression. Subsequently, we examined the ability of ITGA6 to rescue the suppression of the MAPK signaling pathway induced by INHBA knockdown. WB analysis revealed that INHBA silencing induced concomitant downregulation of MAPK cascade components (p-MEK, p-ERK1/2) in NUGC-3 cells. Simultaneously, ITGA6 overexpression rescued the suppression of MAPK phosphoproteins, such as p-MEK and p-ERK1/2, induced by INHBA knockdown (Fig. 7B). These results suggest that INHBA regulates the activation of the MAPK signaling pathway via ITGA6. Functional interaction studies demonstrated that ITGA6 modulates INHBA-induced oncogenic phenotypes. Functional rescue assays revealed that ITGA6 overexpression rescued the attenuation of cell proliferation, migration, and invasion in NUGC-3 cells induced by INHBA silencing (Fig. 7C,E,G,I,J). Similarly, downregulation of the ITGA6 expression reduced the enhancement of proliferation, migration, and invasion in AGS cells caused by INHBA overexpression (Fig. 7D,F,H,K,L). In conclusion, the INHBA/ITGA6 axis promotes gastric carcinogenesis by activating the MAPK signaling pathway, with ITGA6 acting as the indispensable mediator of INHBA oncogenic activity. In summary, elevated INHBA levels increased the expression of ITGA6 mRNA and protein, which further activated the MAPK signaling pathway and eventually contributed to GC progression.