Skip to main content
Discover Oncology logoLink to Discover Oncology
. 2026 Feb 8;17:414. doi: 10.1007/s12672-026-04609-w

AHNAK2 exacerbates the malignant phenotype of gastric cancer through activation of the Wnt/β-catenin signaling pathway

Xiang Liu 1,#, Lei Ma 2,#, Ruixiao Wang 3, Qilun Liu 4,✉
PMCID: PMC12988110  PMID: 41655165

Abstract

Background

AHNAK2 is acknowledged to function as an oncoprotein that enhances the invasive and metastatic potential of tumor cells in multiple types of malignancy. Nevertheless, its specific role in gastric cancer (GC) remains unclear.

Methods

Immunohistochemistry (IHC) was used to examine AHNAK2 expression in matched GC tissues and paracancerous tissues, Clinical and pathological data was gathered for the purpose of investigate the association of AHNAK2 expression and prognosis in patients with GC. AHNAK2 protein expression and location was examined using Western blotting (WB) and immunofluorescence (IF). The effects of AHNAK2 knockdown on the malignant biological behavior of GC cells were evaluated. Transcriptome sequencing and WB analyses were conducted to explore the potential molecular mechanisms underlying AHNAK2-mediated regulation of GC progression.

Results

WB, IF, and IHC analyses demonstrate that AHNAK2 expression is upregulated in GC, and patients with high AHNAK2 protein expression exhibit poorer overall survival rates. Knockdown of AHNAK2 results in reduced invasive, proliferative, and migratory capacities of GC cells, along with increased apoptosis. RNA sequencing and WB analysis further confirmed that AHNAK2 exacerbates the malignant phenotypic characteristics of GC through activation of the Wnt/β-catenin pathway.

Conclusion

AHNAK2 may serve as a new prognostic biomarker and a prospective therapeutic target in GC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12672-026-04609-w.

Keywords: AHNAK2, Progression, Gastric cancer, Wnt/β-catenin

Introduction

Gastric cancer (GC) continues to represent a significant global health challenge, particularly in China [1, 2], which represented 43.9% of newly diagnosed GC cases and accounted for 48.6% of related fatalities worldwide [3]. GC is characterized by considerable complexity and biological heterogeneity [4], which substantially undermines the efficacy of personalized therapeutic approaches, thereby leading to a 5-year survival rate of less than 30% among patients with advanced GC [5]. Among patients diagnosed with GC with distant metastases, the 5-year survival rate has been reported to be below 5% [6]. Although targeted therapeutic agents such as trastuzumab have been introduced into clinical practice [7, 8], surgery combined with perioperative chemotherapy remains the standard treatment for advanced GC [9]. However, the development of chemoresistance in GC patients compromises the efficacy of therapy in controlling tumor growth and metastasis [10]. Therefore, further research into the underlying molecular mechanisms of GC is urgently needed to develop effective strategies to inhibit disease progression.

AHNAK2 is a member of the AHNAK family and is encoded by a gene situated on human chromosome 14q32 [11]. As an oncogenic protein, AHNAK2 has been correlated with the metastatic progression of multiple cancers, including lung adenocarcinoma (LUAD) [12], clear cell renal cell carcinoma (ccRCC) [13], papillary thyroid carcinoma (PTC) [14], and pancreatic ductal adenocarcinoma (PDAC) [15]. Evidence indicates that AHNAK2 exhibits elevated expression levels in lung adenocarcinoma and is closely linked to unfavorable clinical outcomes. Furthermore, mechanistic studies indicate that AHNAK2 may contribute to the invasion and metastasis of LUAD through the activation of the AKT axis [16]. These results indicate a possible role for AHNAK2 in the pathogenesis and progression of maligant tumors. However, its biological functions and the underlying regulatory mechanisms in GC remain poorly understood.

Accordingly, this research investigated the expression levels and cellular localization of AHNAK2 protein in GC cells and tissues by immunohistochemical (IHC), Western blotting (WB), and immunofluorescence (IF). The results shows that AHNAK2 protein is highly expressed in GC, and the overall survival rate of patients exhibiting high expression levels of AHNAK2 was comparatively low. In terms of biological functions, AHNAK2 enhances the proliferation and invasion of GC cells and inhibits their apoptosis. Mechanically, AHNAK2 exacerbates the malignant characteristics of GC through activate Wnt/β-catenin axis. Overall, these results identified and validated the molecular mechanisms by which AHNAK2 contributes to GC progression, highlighting its potential as a therapeutic candidate target for GC.

Materials and methods

Patients

This research enrolled 84 primary GC patients who were definitely diagnosed with primary GC in the Ningxia Medical University General Hospital from 1, January, 2017 to 31, December, 2017. The Ethics Committee of Ningxia Medical University General Hospital approved this study (Ethical Code: KYLL-2024-0023), which was conducted using anonymized data. All methodologies were implemented in compliance with applicable guidelines and regulations. It has been confirmed that all participants have obtained informed consent.

Cell culture

Human GC cell lines, including MKN-45, HGC-27, MGC-803, and AGS, along with the gastric epithelial cell line GES-1 were obtained from the Chinese Academy of Medical Sciences. The cells were cultured in RPMI-1640 medium supplemented with 10% FBS (Gibco, USA) and 1% penicillin-streptomycin (Gibco), and incubated at 37 °C in a humidified atmosphere containing 5% CO₂. AHNAK2 expression levels were assessed across GC cells, and the highest level of AHNAK2 protein expression of the GC cell line was used for further research.

Data and follow up

The clinicopathological and demographic data (including age, gender, and other relevant characteristics) of the patients were collected using the His system of General Hospital of Ningxia Medical University. Fifty-eight patients with positive expression of AHNAK2 were monitored through telephone follow-ups until December 31, 2022, with a follow-up duration ranging from 3 to 60 months and a median follow-up period of 47 months. During the follow-up, 28 patients died, 25 remained alive, and 5 patients were lost during follow-up. Patient outcomes were evaluated according to overall survival (OS) duration.

Immunohistochemistry

Formalin-fixed cancerous and neighboring non-cancerous tissue samples were processed by embedding in paraffin, followed by sectioning into 4-micrometer-thick slices. These sections were subjected to heat-induced antigen retrieval following baking and removal of paraffin through xylene and ethanol series. After rehydration, these slides were repaired with repair solution for 20 min at high temperature. Endogenous peroxidase activity was quenched using a specific blocking agent, followed by a 10-minute incubation period carried out in darkness. Incubated with a monoclonal anti-AHNAK2 antibody AHNAK2 (1:1000; Wuhan Sanying Biological Technology Co., Ltd.) at 4 °C overnight, and subsequently rinsed with PBS. The samples were then incubated with horseradish peroxidase-conjugated secondary antibody obtained from (Zhongshan Jinqiao Biotechnology Co., Ltd.) in the dark for 30 min, followed by another PBS rinse. Color development was carried out using 3,3ʹ-diaminobenzidine (DAB) as the chromogenic substrate.

Reverse transcription-quantitative PCR

Total RNA extraction follows the protocol provided by Invitrogen, and then reverse transcribed into cDNA for qRT-PCR analysis. The reaction conditions were as follow: initial denaturation for 5 min (95 °C), 40 cycles of denaturation (95 °C for 30s), annealing for 20 s (55 °C), extension for 20 s (72 °C).The specific primers used above are provided in Table S1.

Western blotting

Cells were treated with protein lysate, harvested by scraping. Proteins were extracted and quantified using BCA kit. After protein denaturation, equal amount of protein was electrophoresis in SDS-PAGE gel, transferred onto PVDF membrane, blocked with 5% BSA for 1 h, incubated over night (4 °C) with anti-AHNAK2 antibodies (OriGene, USA), TBST was used to wash three times (8 min each time), incubated with secondary antibodies for 1 h, washed again with TBST, proteins were detected utilizing an ECL detection kit.

Cell transfection

Knockdown lentiviruses (Hanheng, Shanghai, China) were transfected into corresponding GC cells according to the manufacturer’s instructions. At 48 h post-transfection, cells transfected at a multiplicity of infection (MOI) of 30 were selected for subsequent experiments based on microscopic observation. Transfection efficiency was evaluated using qRT-PCR and WB assays.

Immunofluorescence labeling of cells

Cell lines exhibiting optimal growth characteristics were cultured under standard conditions, harvested by enzymatic digestion, centrifuged, resuspended, and seeded at appropriate densities onto pre-treated culture dishes for overnight incubation. Subsequently, incubated with anti-AHNAK2 antibody at a 1:40 dilution overnight (4 °C). Next day, specimens were thoroughly washed with PBS and subsequently incubated with a fluorescently labeled secondary antibody at a 1:500 dilution for 2 h at room temperature. Following an additional wash with PBS, the samples were mounted using a DAPI-containing anti-fade mounting medium, allowed to cure, and sealed. Fluorescence signals corresponding to the secondary antibody labeling were visualized using fluorescence microscope.

Cell proliferation assay

MKN-45 cells were plated into 6-well culture plates under standard sterile conditions. When the number of cell colonies derived from cloning surpassed 50, the cells were treated with 4% paraformaldehyde for 15 min at ambient temperature and then rinsed using PBS. After fixation, the cells were exposed to 0.5 mL of a 0.05% crystal violet solution for 20 min. To eliminate residual stain, three further PBS washes were performed, followed by air-drying of the plates. The efficiency of colony formation was subsequently determined.

Cell migration and invasion assay

For the wound healing assay, MKN-45 cells were seeded into 6-well plates and cultured under standard conditions until confluence was reached prior to creating a scratch wound. Wound closure was monitored by phase-contrast microscopy at 0 h and 48 h post-scratching. For the Transwell invasion assay, Matrigel matrix was thawed and diluted 1:6 in serum-free medium. This mixture was introduced into the upper chamber of transwell inserts and incubated at 37 °C for 4 to 6 h to allow for reconstitution.The lower compartment was loaded with 500 µL of fully supplemented medium containing 10% fetal bovine serum. while 1 mL of cell suspension was added to the upper chamber and incubated for 24 h. After the incubation period, non-migrated cells were carefully wiped away to preserve the migrated cell population.The membranes were fixed using 4% paraformaldehyde and subsequently stained with 0.1% crystal violet. Visualized and counted under a microscope. Cell migration capacity, independent of extracellular matrix invasion, was evaluated in parallel without Matrigel coating.

Flow cytometry assay

Cell apoptosis was detected according to the manufacturer’s instructions provided with the detection kit. Following transfection, MKN-45 cells were harvested, resuspended and then incubated with fluorescence staining mixture: 10 µL of Annexin V-fluorescein isothiocyanate (FITC) and 5 µL of propidium iodide (PI), then incubated for 15 min at 25 °C under light-protected conditions. The apoptosis percentage was subsequently measured utilizing a flow cytometric platform (BD Biosciences, US).

RNA-seq

RNA sequencing (RNA-seq) was performed to assess transcriptomic changes after AHNAK2 knockdown. MKN-45 cells transfected with lentiviral shRNA were designated as the shRNA-NC group and the shRNA-AHNAK2 group. We identified differentially expressed genes (DEGs) between these groups and visualized the results in a volcano plot. Functional annotation of the DEGs was performed using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Gene Set Enrichment Analysis (GSEA) was also conducted to further identify significantly enriched signaling pathways.

Statistical analysis

All in vitro experiments were performed with three independent biological replicates (n = 3). Statistical analyses were conducted using GraphPad Prism 8, and data are presented as mean ± standard deviation (SD). Differences between two groups were assessed using the Student’s t-test, whereas comparisons among multiple groups were evaluated using one-way analysis of variance (ANOVA). The associations between clinicopathological characteristics and AHNAK2 expression (Table 1) were analyzed using the chi-square test, and Fisher’s exact test was applied when expected cell counts were small. Overall survival (OS) was estimated using the Kaplan–Meier method, and differences between survival curves were evaluated using the log-rank test. A P < 0.05 was considered statistically significant.

Table 1.

Relationship between AHNAK2 expression levels and clinicopathological characteristics in GC patients

Characteristic Total AHNAK2 expression P value
Low High
Gender 26 32 0.431
 Male 44 21 23
 Female 14 5 9
Age (years) 0.771
 < 60 30 14 16
 ≥ 60 28 12 16
Differentiation 0.329
 Well 8 4 4
 Moderate 24 10 14
 Poor 26 12 14
pT stage 0.051
 T1 3 3 0
 T2 10 7 3
 T3 11 4 7
 T4 34 12 22
pN stage 0.032
 N0 10 8 2
 N1 + N2+N3 48 18 30
TNM stage 0.258
 I–II 20 11 9
 III–IV 38 15 23
Vascular invasion 0.272
 Absent 33 19 14
 Present 17 7 10

Results

AHNAK2 expression is upregulated in GC and is associated with adverse prognoses

The IHC staining demonstrated that AHNAK2 expression was detected in 69.0% of GC patients, while no AHNAK2 expression was observed in the remaining 31.0% (26/84). All adjacent non-tumor tissues showed negative staining for AHNAK2. Overall, AHNAK2 protein expression was upregulated in GC tissues (Fig. 1A), as further illustrated by the statistical data presented in Fig. 1B. Among the 58 positive cases, 32 displayed high expression levels and 26 showed low expression levels. A statistically significant positive association was observed between AHNAK2 expression and lymph node metastasis (LNM) in GC patients (P < 0.05). In contrast, no significant associations were identified between AHNAK2 expression and clinicopathological parameters including age, gender, degree of tumor differentiation, pathological T stage, overall pathologic stage, and the existence of vascular tumor embolus( P > 0.05). Vascular invasion data were missing for 8 of the 58 AHNAK2-positive patients; therefore, the comparison for vascular invasion was based on the remaining 50 patients (Table 1).

Fig. 1.

Fig. 1

Expression of AHNAK2 protein was upregulated in GC and linked to adverse prognoses. A AHNAK2 expression was evaluated by IHC staining in GC and tumor-adjacent tissues. Representative IHC images of AHNAK2 staining in GC and corresponding paracancerous tissue sections are presented, including low and high expression images of AHNAK2 in GC tissues. All IHC images are presented with scale bars indicating 200 μm at 100-fold magnification or 50 μm at 400-fold magnification. B Distribution of AHNAK2 expression levels in adjacent non-tumor tissue and tumor tissue. C Using Kaplan-Meier survival analysis to assess OS in patients with GC. D WB examination of expression levels of AHNAK2 in GC cells lines relative to GES-1. As an indicator of loading, GAPDH was used. E Quantitative assessment of AHNAK2 expression levels across various cell lines as shown in C. F IF was employed to determine the subcellular localization of AHNAK2 protein in GC cells and GES-1, with DAPI used for nuclear staining, 50 μm scale bar, and corresponding to 400× magnification applies to all panels. G Quantitative assessment of AHNAK2 expression levels across various cells in E. There were three duplicates of each experiment. ***P < 0.001

The 1-, 3-, and 5-year survival probabilities in GC patients with elevated AHNAK2 expression were 82.1% (23/28), 42.9% (12/28), and 35.7% (10/28), respectively, compared to 95.7% (22/23), 69.6% (16/23), and 56.5% (13/23) in those with low AHNAK2 levels. Collectively, the results demonstrate that high AHNAK2 expression is associated with poorer survival outcomes, with a hazard ratio of 2.38 (95% confidence interval 1.09–5.17; P < 0.05; Fig. 1C). In vitro, AHNAK2 expression was upregulated in all tested GC cells lines relative to the cell line GES-1, with the most pronounced expression observed in MKN-45 cells (Fig. 1D–G). For this reason, MKN-45 cells were chosen as the model for follow-up studies. Immunolocalization analysis further revealed that AHNAK2 is primarily localized to the plasma membrane.

AHNAK2 Silencing inhibits the proliferation and promotes apoptosis of GC cells

To explore the functional significance of AHNAK2 in GC, stable AHNAK2-knockdown cell lines were generated in MKN-45 cells using lentivirus-mediated gene transduction. qRT-PCR analysis demonstrated that AHNAK2 mRNA expression level was reduced by 53% in sh-AHNAK2 cells compared to control cells (Fig. 2A). Additionally, WB analysis confirmed the successful establishment of stable AHNAK2 knockdown at the protein level (Fig. 2B, C). Subsequently, a clonogenic assay was conducted to evaluate the impact of AHNAK2 downregulation on the malignant proliferative capacity of GC cells. The findings revealed that the sh-AHNAK2 group exhibited a markedly reduced number of colonies compared to the sh-NC group, suggesting that silencing AHNAK2 effectively inhibits the proliferation of GC cells (Fig. 2D, E). Furthermore, flow cytometry analysis showed a significantly higher apoptotic rate in sh-AHNAK2-transfected cells compared to both MKN-45 and sh-NC control cells (Fig. 2F, G, P < 0.05), These findings indicate that AHNAK2 knockdown promotes apoptosis in GC cells. Furthermore, WB analysis was conducted to evaluate the expression of Bcl-2, Bax and Caspase-3. The findings revealed a significant elevation in the levels of pro-apoptotic proteins after the suppression of AHNAK2 (Fig. 2H, I).

Fig. 2.

Fig. 2

Knockdown of AHNAK2 suppresses the proliferative capacity of GC cells and induces apoptotic activation. A The relative expression levels of AHNAK2 mRNA in MKN-45 cells following shRNA transfection were assessed using real-time PCR. B Analysis of AHNAK2 protein expression by western blotting in AHNAK2-silenced MKN-45 cells. C Quantitative assessment of AHNAK2 expression levels across three groups of cells in B. D The proliferative capacity of AHNAK2-silenced MKN-45 cells was assessed via colony formation assays. E Quantification of the number of colonies from the results shown in D is presented. F Cell apoptosis in AHNAK2-depleted MKN-45 cells was analyzed using flow cytometry (FACS). G The apoptotic cell percentages derived from F were statistically evaluated and displayed. H WB analysis was used to detect the expression levels of BAX, Bcl-2, and Cleaved Caspase-3 in MKN-45 cells under control, sh-NC, and shAHNAK2 conditions. I Quantification of BAX, Bcl-2, and Cleaved Caspase-3 protein expression relative to β-actin, which served as a loading control, based on data from H. Each experiment were conducted three times. *, P < 0.05

AHNAK2 induces the Wnt/β-catenin signaling pathway in GC cells

Previous studies have showed that AHNAK2 may regulate the Wnt/β-catenin signaling pathway [17]. Based on this evidence, we hypothesized that AHNAK2 promotes the progression of GC through modulation of the same signaling pathway. Transcriptional sequencing was conducted on MKN-45 cells transfected with shRNA-NC and shRNA-AHNAK2, identified 790 upregulated and 1389 downregulated differentially expressed genes (DEGs) (Fig. 3A). Furthermore, KEGG and GSEA enrichment analyses indicated that AHNAK2 may be involved in GC progression through the Wnt/β-catenin pathway (Fig. 3B, C). Additionally, WB demonstrated that the protein expression levels of Wnt3a, β-catenin, GSK-3β, p-GSK-3β, PCNA, cyclinD2, c-Myc, nand CDK4 were significantly reduced in AHNAK2-silenced MKN-45 cells (P < 0.05) (Fig. 3D–I). These WB results collectively indicating that AHNAK2 promotes GC progression through activation of the Wnt/β-catenin signaling axis.

Fig. 3.

Fig. 3

AHNAK2 induces the Wnt/β-catenin signaling transduction in GC cells. A Volcano plots was used to show DEGs in RNA sequencing data. B KEGG enrichment analysis highlighted the top 20 signaling pathways linked to the DEGs. (C) GSEA results indicated a significant enrichment of the Wnt/β-catenin signaling pathway. D, F, H The downstream response genes protein expression of β-catenin signaling transduction was used by WB analysis. As three indicators of loading, Tublin, GAPDH and β-actin were utilized. E, G, I Quantitative analysis of protein expression of related gene in D, F, H. Every experiment was taken three duplicates. **, P < 0.01

AHNAK2 promotes GC progression through activation of the Wnt/β-catenin signaling axis

To confirm the previous results, additional rescue experiments were conducted.It was demonstrated that treatment with CHIR-99021, an activator of phosphorylated β-catenin, effectively enhanced activation of the Wnt/β-catenin signaling axis and restored the reduced migratory and invasive capabilities of AHNAK2-silenced MKN-45 cells (Fig. 4A–D). Moreover, Flow cytometric analysis revealed that CHIR-99,021 significantly attenuated the AHNAK2 silencing-induced increase in both early and late apoptotic cell populations (Fig. 4E, F). Collectively, these results show that downregulation of AHNAK2 enhances GC cell apoptosis through the inhibition of the Wnt/β-catenin signaling transduction. Furthermore, WB analysis was utilized to assess the expression of genes associated with this signaling pathway in MKN-45 cells treated with CHIR-99,021 and in MKN-45 cells with AHNAK2 silenced. The results demonstrated that in MKN-45 cells, CHIR-99,021 significantly reduced the expression level of BAX and Caspase-3, while markedly rising the expression levels of Wnt3a, GSK-3β, p-GSK-3β, β-catenin, Bcl-2, Caspase-3, PCNA, Cdk4, cyclin D2, and c-Myc (Fig. 4G–I).

Fig. 4.

Fig. 4

Knockdown of AHNAK2 suppresses GC progression through inhibition of the Wnt/β-catenin pathway. A MKN-45 cells were transfected with either AHNAK2 shRNA alone or in combination with CHIR-99021, and cell migration was assessed using wound healing assays in comparison to control cells. B The cell migration rates of A is indicated. C The cell invasive capacity was subsequently evaluated using Transwell assays. D The number of invasion cells of C that were statistically examined are presented. E The effect of cell apoptosis in MKN-45 cells transfected with AHNAK2 shRNA, either alone or in combination with CHIR-99,021, was evaluated using flow cytometry analysis. F Quantitative analysis of the apoptotic cell percentages from E is shown. G, H, I The expression of Wnt3a, GSK-3β, p-GSK-3β, β-catenin, Bax, Bcl-2, Caspase-3, PCNA, Cdk4, cyclinD2 and c-Myc in AHNAK2 shRNA or AHNAK2 shRNA plus CHIP-99,021 MKN-45 cells by Western blotting analysis. As two indicators of loading, GAPDH and Tublin were used. Each experiment was performed three times. *P < 0.05

Discussion

Tumorigenesis is a multistage and intricate process predominantly marked by uncontrolled cellular proliferation. The gradual buildup of genetic and epigenetic alterations in genetically related substances that regulate cell division is a key factor in tumorigenesis [18]. Therefore, identifying those genetically related substances that contribute to tumor advancement is crucial for exploring novel diagnostic and prognostic approaches in cancer [19]. A retrospective analysis of 178 individuals diagnosed with pancreatic ductal adenocarcinoma demonstrated that elevated AHNAK2 levels were significantly linked to unfavorable clinical outcomes [20]. Similarly, increased expression of AHNAK2 has been detected in lung adenocarcinoma cases, where higher expression was found to correlate positively with LNM, more advanced tumor stages, and decreased overall survival rates [21, 22]. AHNAK2 also demonstrated comparable and consistent results in bladder cancer [23]. The clinical significance and biological role of AHNAK2 in GC remains largely unclear. Our study indicated that AHNAK2 expression level was significantly elevated in GC, patients exhibiting elevated expression levels of AHNAK2 protein demonstrated significantly poorer prognostic outcomes, indicating that AHNAK2 serves a crucial role in GC progression. Therefore, AHNAK2 may function as a promising prognostic biomarker for unfavorable outcomes in patients with GC.

Cancer cell metastasis constitutes a multifaceted biological phenomenon characterized by processes such as invasion, migration, and proliferation [24]. Research has revealed that AHNAK2 is overexpressed in thyroid carcinoma (TC) tissues, with notably higher levels observed in metastatic cases, and suppressing AHNAK2 expression has been shown to reduce the migratory, invasive, and metastatic potential of these cells [25] and epithelial-mesenchymal transformation (EMT) of TC [17]. EMT is widely recognized as a critical process that facilitates proliferation, invasion, and metastasis, and is critically involved in the advancement of cancer. Moreover, EMT has been demonstrated to augment cancer cells resistance to both chemotherapy and immunotherapy [26–28]. Knocking down AHNAK2 exerts similar biological effects in uveal melanoma [29]. In addition, suppression of AHNAK2 expression leads to reduced synthesis of fatty acids and lipids, key processes for sustaining energy balance and cellular nutrition in cancer cells indicating that the oncogenic effects of AHNAK2 may be mediated through the modulation of tumor cellular metabolism [13]. Emerging evidence indicates that AHNAK2 exhibits elevated expression levels across multiple types of adenocarcinoma tissues, whereas it exhibits minimal expression in normal glandular tissues. Silencing AHNAK2 effectively reduces the proliferative and migratory potential of adenocarcinoma cells [30].

To investigate the impacts of AHNAK2 on GC cells proliferation, invasion, and apoptosis, as well as its role in key cellular mechanisms associated with GC development, we conducted transcriptome sequencing combined with bioinformatics analysis. Our findings demonstrate that AHNAK2 activates the Wnt/β-catenin signaling pathway, thereby promoting GC progression. Upon activation of the Wnt/β-catenin signaling cascade, the key effector protein β-catenin functions as a transcriptional co-activator to regulate related genes that govern malignant biological phenotype of tumors [31]. Inhibition of this signaling pathway is universally regarded as a critical factor in tumorigenesis and disease progression, and is strongly associated with resistance to chemotherapy and radiotherapy [32, 33]. A series of studies have consistently illustrated that the Wnt- dependent signal transduction contributes to the initiation and advancement of GC [34–36], it is approximated that 46% of GC exhibit dysregulation of the Wnt/β-catenin pathway [37]. In vitro studies have showed that endogenous β-catenin was localized in the nucleus and exhibited elevated TCF/LEF transcriptional activity, indicating dysregulated activation of the Wnt signaling pathway [38]. KEGG bioinformatics analysis has further identified Wnt pathway as the third most significantly enriched pathway in GC, with frequent mutations observed in downstream regulatory genes, including RNF43, AXIN1/2, CTNNB1, and APC [39]. It is a well-established mechanism that the suppression of the Wnt/β-catenin pathway can inhibit apoptosis to mediate tumorigenesis [40, 41]. Our findings demonstrate that AHNAK2 exacerbates the malignant phenotype of GC by enhancing the activity of the Wnt/β-catenin axis. Suggesting that AHNAK2 could function as a novel biomarker indicative of GC aggressiveness and holds promise as a therapeutic intervention target. Further investigation in larger GC cohorts is therefore warranted.

Conclusion

In conclusion, our research results highlight the critical significance of AHNAK2 in modulating the proliferation and invasive capacity of GC. Through investigation into the functional properties and underlying mechanisms of AHNAK2, this study demonstrates a strong association between AHNAK2-mediated Wnt/β-catenin pathway and the malignant progression of GC. These findings indicate that AHNAK2 may function as a prognostic biomarker for poor clinical endpoints in GC patients, as well as a novel molecular target for both diagnosis and therapeutic intervention in GC.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1. (12.2KB, docx)
Supplementary Material 2. (262.3KB, pdf)

Acknowledgements

Not applicable.

Author contributions

Xiang Liu and Lei Ma devise the experiment, Xiang Liu and Ruixiao Wang conduct the experiment, Xiang Liu analyzed the data and write the manuscript, Qilun Liu examine the manuscript. All authors have reviewed the final version of the manuscript and provided their approval for submission.

Funding

None.

Data availability

The data generated and analyzed above are openly accessible through the NCBI database repository under accession number PRJNA1214896 (https://dataview.ncbi.nlm.nih.gov/object/PRJNA1214896). The accession number PRJNA1214896 has been made publicly available and is now accessible to the general public. All data and materials referenced in this study are included in the main manuscript and the supplementary information files. Source data accompanying the paper are also provided as part of the publication.

Declarations

Ethics approval and consent to participate

The research involving human tissue samples was approved by the Ethics Committee of Ningxia Medical University General Hospital (Ethical Code: KYLL-2024-0023). All procedures were carried out in compliance with applicable guidelines and regulatory requirements. Informed consent was obtained from all participants prior to sample collection and inclusion in this study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Xiang Liu and Lei Ma contributed equally to this work.

References

  • 1.Torre L-A, Siegel R-L, Ward E-M, et al. Global cancer incidence and mortality rates and trends–an update. Cancer Epidemiol Biomarkers Prev. 2016;25(1):16–27. [DOI] [PubMed] [Google Scholar]
  • 2.The global. regional, and National burden of stomach cancer in 195 countries, 1990–2017: a systematic analysis for the global burden of disease study 2017. Lancet Gastroenterol Hepatol. 2020;5(1):42–54. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Sung H, Ferlay J, Siegel R-L, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–49. [DOI] [PubMed] [Google Scholar]
  • 4.Chia N-Y, Tan P. Molecular classification of gastric cancer. Ann Oncol. 2016;27(5):763–9. [DOI] [PubMed] [Google Scholar]
  • 5.Strong V-E. Progress in gastric cancer. Updates Surg. 2018;70(2):157–9. [DOI] [PubMed] [Google Scholar]
  • 6.Thrift A-P, El-Serag H-B. Burden of gastric cancer. Clin Gastroenterol Hepatol. 2020;18(3):534–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.M Sanford. Trastuzumab: a review of its use in HER2-positive advanced gastric cancer. Drugs. 2013;73(14):1605–15. [DOI] [PubMed] [Google Scholar]
  • 8.Gomez-Martin C, Lopez-Rios F, Aparicio J, et al. A critical review of HER2-positive gastric cancer evaluation and treatment: from trastuzumab, and beyond. Cancer Lett. 2014;351(1):30–40. [DOI] [PubMed] [Google Scholar]
  • 9.Xu W, Yang Z, Lu N. Molecular targeted therapy for the treatment of gastric cancer. J Exp Clin Cancer Res. 2016;35:1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Russi S, Verma H-K, Laurino S, et al. Adapting and surviving: intra and extra-cellular remodeling in drug-resistant gastric cancer cells. Int J Mol Sci. 2019;20(15):3736. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Zardab M, Stasinos K, Grose R-P, et al. The obscure potential of AHNAK2. Cancers (Basel). 2022;14(3):528. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Wang D-W, Zheng H-Z, Cha N et al. Down-Regulation of AHNAK2 inhibits cell Proliferation, migration and invasion through inactivating the MAPK pathway in lung adenocarcinoma. Technol Cancer Res Treat. 2020. 191079224654. [DOI] [PMC free article] [PubMed]
  • 13.Wang M, Li X, Zhang J, et al. AHNAK2 is a novel prognostic marker and oncogenic protein for clear cell renal cell carcinoma. Theranostics. 2017;7(5):1100–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Xie Z, Lun Y, Li X, et al. Bioinformatics analysis of the clinical value and potential mechanisms of AHNAK2 in papillary thyroid carcinoma. Aging. 2020;12(18):18163–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Lu D, Wang J, Shi X, et al. AHNAK2 is a potential prognostic biomarker in patients with PDAC. Oncotarget. 2017;8(19):31775–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Zhang S, Lu Y, Qi L et al. AHNAK2 is associated with poor prognosis and cell migration in lung adenocarcinoma. Biomed Res Int, 2020, 20208571932. [DOI] [PMC free article] [PubMed]
  • 17.Lin Q-Y, Qi Q-L, Hou S, et al. Silencing of AHNAK2 restricts thyroid carcinoma progression by inhibiting the Wnt/beta-catenin pathway. Neoplasma. 2021;68(5):1063–71. [DOI] [PubMed] [Google Scholar]
  • 18.Cloughesy T-F, Cavenee W-K, Mischel P-S. Glioblastoma: from molecular pathology to targeted treatment. Annu Rev Pathol. 2014;9:1–25. [DOI] [PubMed] [Google Scholar]
  • 19.Kim H, Kim T, Jeong B-C, et al. Tmem64 modulates calcium signaling during RANKL-mediated osteoclast differentiation. Cell Metab. 2013;17(2):249–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Klett H, Fuellgraf H, Levit-Zerdoun E, et al. Identification and validation of a diagnostic and prognostic multi-gene biomarker panel for pancreatic ductal adenocarcinoma. Front Genet. 2018;9:108. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Liu G, Guo Z, Zhang Q, et al. AHNAK2 promotes migration, invasion, and epithelial-mesenchymal transition in lung adenocarcinoma cells via the TGF-beta/Smad3 pathway. Onco Targets Ther. 2020;13:12893–903. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Zheng M, Liu J, Bian T, et al. Correlation between prognostic indicator AHNAK2 and immune infiltrates in lung adenocarcinoma. Int Immunopharmacol. 2021;90:107134. [DOI] [PubMed] [Google Scholar]
  • 23.Koguchi D, Matsumoto K, Shimizu Y, et al. Prognostic impact of AHNAK2 expression in patients treated with radical cystectomy. Cancers (Basel). 2021;13(8):1748. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Gerstberger S, Jiang Q, Ganesh K. Metastasis Cell. 2023;186(8):1564–79. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Ye R, Liu D, Guan H, et al. AHNAK2 promotes thyroid carcinoma progression by activating the NF-kappaB pathway. Life Sci. 2021;286:120032. [DOI] [PubMed] [Google Scholar]
  • 26.Huang Y, Hong W, Wei X. The molecular mechanisms and therapeutic strategies of EMT in tumor progression and metastasis. J Hematol Oncol. 2022;15(1):129. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Cai Y, Wang B, Li B, et al. Collection on reports of molecules linked to epithelial-mesenchymal transition in the process of treating metastasizing cancer: a narrative review. Ann Transl Med. 2021;9(11):946. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Dongre A, Weinberg R-A. New insights into the mechanisms of epithelial-mesenchymal transition and implications for cancer. Nat Rev Mol Cell Biol. 2019;20(2):69–84. [DOI] [PubMed] [Google Scholar]
  • 29.Li M, Liu Y, Meng Y, et al. AHNAK nucleoprotein 2 performs a promoting role in the proliferation and migration of uveal melanoma cells. Cancer Biother Radiopharm. 2019;34(10):626–33. [DOI] [PubMed] [Google Scholar]
  • 30.Xu M, Cheng A, Yu L, et al. AHNAK2 is a biomarker and a potential therapeutic target of adenocarcinomas. Acta Biochim Biophys Sin (Shanghai). 2022;54(11):1708–19. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Cruciat C-M. Secreted and transmembrane Wnt inhibitors and activators. Cold Spring Harb Perspect Biol. 2013;5(3):a15081. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Fesik S-W. Promoting apoptosis as a strategy for cancer drug discovery. Nat Rev Cancer. 2005;5(11):876–85. [DOI] [PubMed] [Google Scholar]
  • 33.Fromigue O, Hay E, Barbara A, et al. Essential role of nuclear factor of activated T cells (NFAT)-mediated Wnt signaling in osteoblast differentiation induced by strontium Ranelate. J Biol Chem. 2010;285(33):25251–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Koushyar S, Powell A-G, Vincan E, et al. Targeting Wnt signaling for the treatment of gastric cancer. Int J Mol Sci. 2020;21(11):3927. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Kim Y, Bae Y-J, Kim J-H, et al. Wnt/beta-catenin pathway is a key signaling pathway to trastuzumab resistance in gastric cancer cells. BMC Cancer. 2023;23(1):922. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Han R, Yang J, Zhu Y, et al. Wnt signaling in gastric cancer: current progress and future prospects. Front Oncol. 2024;14:1410513. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Ooi C-H, Ivanova T, Wu J, et al. Oncogenic pathway combinations predict clinical prognosis in gastric cancer. PLoS Genet. 2009;5(10):e1000676. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Nojima M, Suzuki H, Toyota M, et al. Frequent epigenetic inactivation of SFRP genes and constitutive activation of Wnt signaling in gastric cancer. Oncogene. 2007;26(32):4699–713. [DOI] [PubMed] [Google Scholar]
  • 39.Wang K, Yuen S-T, Xu J, et al. Whole-genome sequencing and comprehensive molecular profiling identify new driver mutations in gastric cancer. Nat Genet. 2014;46(6):573–82. [DOI] [PubMed] [Google Scholar]
  • 40.Zhang X, Wu N, Huang H, et al. Phosphorylated PTTG1 switches its subcellular distribution and promotes beta-catenin stabilization and subsequent transcription activity. Oncogene. 2023;42(32):2439–55. [DOI] [PubMed] [Google Scholar]
  • 41.Ni L, Lu J. Interferon gamma in cancer immunotherapy. Cancer Med. 2018;7(9):4509–16. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1. (12.2KB, docx)
Supplementary Material 2. (262.3KB, pdf)

Data Availability Statement

The data generated and analyzed above are openly accessible through the NCBI database repository under accession number PRJNA1214896 (https://dataview.ncbi.nlm.nih.gov/object/PRJNA1214896). The accession number PRJNA1214896 has been made publicly available and is now accessible to the general public. All data and materials referenced in this study are included in the main manuscript and the supplementary information files. Source data accompanying the paper are also provided as part of the publication.


Articles from Discover Oncology are provided here courtesy of Springer

RESOURCES