ANKRD1 Facilitates Tumor Progression and Immune Evasion in Stomach Adenocarcinoma through STAT3 Activation and Remodeling of the Tumor Microenvironment

ANKRD1 Facilitates Tumor Progression and Immune Evasion in Stomach Adenocarcinoma through STAT3 Activation and Remodeling of the Tumor Microenvironment | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article ANKRD1 Facilitates Tumor Progression and Immune Evasion in Stomach Adenocarcinoma through STAT3 Activation and Remodeling of the Tumor Microenvironment Lu Nie, Yu Nie, Ruiyang Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7782118/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: ANKRD1 is implicated in various cancers, but its role in Stomach adenocarcinoma (STAD) remains unclear. Methods: ANKRD1 expression and its prognostic value in STAD were analyzed using TIMER, UALCAN, GEPIA, and Kaplan-Meier plotter. Immune cell infiltration was evaluated via CIBERSORT and Single-sample Gene Set Enrichment Analysis (ssGSEA). Somatic mutations were analyzed from TCGA data. Functional enrichment analysis (GO, KEGG, GSEA(Gene Set Enrichment Analysis)) was performed on ANKRD1-associated genes. Subsequently, in vitro experiments were conducted. ANKRD1 protein levels were examined in STAD cell lines by Western blot. Stable knockdown and overexpression models were created. Functional assays (CCK-8, Transwell, wound healing) assessed proliferation, migration, and invasion. Western blot measured STAT3 pathway activity. Results: ANKRD1 was significantly overexpressed in STAD tissues and high expression correlated with poorer overall, first progression, and post-progression survival. ANKRD1 expression positively correlated with M0 macrophage and activated mast cell infiltration, and negatively with resting memory CD4+ T cells and naive B cells. Although ANKRD1 itself was not mutated, associated genes were enriched in pathways like Wnt signaling. In vitro, ANKRD1 knockdown inhibited cell proliferation, migration, and invasion, while its overexpression promoted these effects. ANKRD1 was found to modulate STAT3 phosphorylation. Conclusions: ANKRD1 is overexpressed in STAD and predicts poor prognosis. It promotes tumor cell proliferation, migration, and invasion, likely through activating the STAT3 signaling pathway, and correlates with an altered immune microenvironment. ANKRD1 represents a potential prognostic biomarker and therapeutic target for STAD. Stomach Adenocarcinoma Tumor immune microenvironment ANKRD1(Ankyrin Repeat Domain 1) Cell Invasion Western blot STAT3 signaling Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1. INTRODUCTION Gastric cancer (GC) remains a significant global health challenge, ranking fifth in incidence and fourth in mortality worldwide 1 . Although its incidence has declined in some regions, its marked geographic heterogeneity (with the highest burden in East Asia and Eastern Europe) reveals complex interactions between genetic, environmental, and socioeconomic factors. Histologically, the majority of cases are adenocarcinomas, which can be classified into intestinal and diffuse types according to the Lauren classification, each with distinct epidemiological, pathological, and molecular characteristics 2 . Stomach adenocarcinoma (STAD) is the predominant histological form and the primary focus of oncological research 3 . The development of STAD is a multi-step process, primarily triggered by chronic infection with Helicobacter pylori (H. pylori), which is associated with approximately 90% of non-cardia gastric cancers 4,5 . Other significant risk factors include dietary carcinogens (such as smoked and pickled foods), smoking, alcohol consumption, obesity, and Epstein-Barr virus (EBV) infection 6 . Importantly, genetic susceptibility also plays a critical role, with hereditary syndromes like hereditary diffuse gastric cancer (HDGC) caused by CDH1 gene mutations accounting for a small but significant proportion of patients 7 . Molecular subtyping studies, particularly those by The Cancer Genome Atlas (TCGA) network, have revolutionized our understanding of STAD heterogeneity by proposing a four-tier classification system: 1) EBV-positive tumors, characterized by PIK3CA mutations and PD-L1 amplification; 2) microsatellite instability-high (MSI-H) tumors, which exhibit high mutational burden and a more favorable prognosis; 3) genomically stable (GS) tumors, often of the diffuse subtype; and 4) chromosomally unstable (CIN) tumors, marked by aneuploidy and receptor tyrosine kinase amplifications 8,9 . This taxonomy provides a crucial framework for developing personalized treatment strategies 10,11 . For localized disease, curative treatment is based on surgical resection combined with perioperative or adjuvant chemotherapy and radiotherapy. However, a significant proportion of patients are diagnosed at advanced or metastatic stages, for whom systemic therapy is the mainstay of treatment 12,13 . Although the emergence of HER2-targeted therapies, ramucirumab targeting VEGFR2 14 , and immune checkpoint inhibitors for MSI-H/dMMR or PD-L1-positive tumors has improved outcomes, the overall prognosis for advanced STAD remains poor, with a 5-year survival rate below 10%. Intrinsic and acquired resistance, coupled with a robust tumor immunosuppressive microenvironment (TME), are major obstacles to achieving durable treatment responses 15,16 . Therefore, there is an urgent need to stratify patients and improve therapeutic efficacy by identifying novel and reliable prognostic biomarkers and therapeutic targets. Ankyrin repeat domain 1 (ANKRD1), also known as Cardiac Ankyrin Repeat Protein (CARP), was initially identified as a striated muscle-specific structural protein but has now been redefined as a ubiquitously expressed, context-dependent signaling hub and transcriptional coregulator across diverse tissues 17 . Its expression is highly sensitive to various stressors, including biomechanical stress, oxidative damage, and inflammatory signals, a characteristic that underlies its complex and often paradoxical roles in human pathophysiology 18 . In the field of oncology, ANKRD1 exhibits a remarkable duality: it can function either as a tumor suppressor or an oncogene, depending on the cellular microenvironment 19 . In cancers such as breast cancer, it acts as a potent protector by inhibiting key pro-tumorigenic pathways such as NF-κB (via cytoplasmic sequestration of its subunits) and TGF-β, thereby suppressing inflammation, epithelial-mesenchymal transition (EMT), and metastasis 20,21 . The functional paradox of ANKRD1 also extends to various systemic diseases, where it consistently serves as a sentinel of cellular stress. In cardiovascular pathophysiology, its sharp upregulation following heart failure and myocardial infarction is part of a pathological reactivation of the fetal gene program; while initially compensatory, sustained ANKRD1 expression contributes to pathological cardiac hypertrophy and systolic dysfunction by translocating to the nucleus and corepressing contractile protein genes 22 . Similarly, in muscular dystrophies such as Duchenne muscular dystrophy (DMD), its persistent expression in regenerating fibers reflects failed repair attempts, where it acts as a mechanical stress sensor modulating the balance between muscle degeneration and regeneration 23 . Its pathophysiological influence is also evident in pulmonary arterial hypertension, where it drives excessive vascular smooth muscle cell proliferation, and in rheumatoid arthritis, where it may synergize with NF-κB to exacerbate joint inflammation 24,25 . Thus, ANKRD1 can be regarded as a molecular "Janus face," whose pleiotropic functions are mediated through complex network of pathways and cellular interactions. Elucidating the precise mechanisms that determine its dual nature is of paramount importance for exploiting its potential as a biomarker and novel therapeutic target across the spectrum of human diseases, from oncology to cardiology. Our existing understanding of ANKRD1 expression, regulation, and functionality in STAD remains rudimentary. The objective of our investigation was to delve into the expression, prognostic implications, roles, and underlying mechanisms of ANKRD1 in STAD. Through a comprehensive multi-database analysis, we uncovered that ANKRD1 is markedly overexpressed in STAD, exhibiting a strong correlation with diminished overall survival rates, initial progression, and survival following progression in patients. While ANKRD1 expression showed a relationship with the infiltration of tumor immune cells, it did not correlate with the tumor mutation burden. Functional enrichment assessments indicated that ANKRD1 plays a pivotal role in various essential biological processes and signaling pathways. Experimental findings in vitro revealed that ANKRD1 facilitates the proliferation, migration, and invasion of stomach adenocarcinoma cells. Mechanistically, it appears that ANKRD1 may exert its oncogenic influence via the activation of the STAT3 signaling pathway. 2. METHODS 2.1 Data sources The Cancer Genome Atlas (TCGA) 26 database ( https://portal.gdc.cancer.gov/ ) offers comprehensive molecular and clinical data for patients with Stomach adenocarcinoma (STAD), such as downloadable mRNA expression profiles, summaries of genetic mutations, and anonymized patient histories. In this study, we utilized a dataset containing transcriptomic information from 445 samples, which included 35 normal tissue specimens and 409 tumor tissue specimens. To identify differentially expressed genes between these normal and cancerous tissues, we performed an analysis using the Limma package (version 3.64.3) in R. 2.2 Analysis of Gene Expression Data via the UALCAN Database A comprehensive online analysis investigating differential gene expression between cancerous and non-cancerous tissues was conducted utilizing the UALCAN database ( http://ualcan.path.uab.edu/ ) 27 , leveraging data sourced from The Cancer Genome Atlas (TCGA). This database facilitated the categorization of patients according to their gene expression profiles, enabling a comparative assessment of the survival outcomes among various expression cohorts. 2.3 Analysis of the TIMER database To investigate the differential expression of genes between tumor and precancerous tissues, we utilized TIMER ( http://timer.cistrome.org/ ) 28 , a user-friendly web application designed for the analysis of large-scale cancer genomics data from The Cancer Genome Atlas (TCGA). This tool enabled a systematic comparison of gene expression profiles between tumor samples and matched precancerous samples from the same patients. 2.4 Analysis of the KM plotter database Based on the survival data of Stomach adenocarcinoma (STAD) patients, we conducted survival analysis using the Kaplan-Meier survival curve in the online database ( https://www.kmplot.com/analysis/ ) 29 . Patients with ANKRD1 expression levels above the median were defined as the high expression group, while those below the median were defined as the low expression group. Survival curves were plotted, hazard ratios were calculated, and confidence intervals were estimated to evaluate the impact of ANKRD1 on the prognosis of STAD patients. 2.5 Profiling of the Immune Landscape via Bioinformatics Analysis The composition of 22 distinct human immune cell types was determined through the LM22 gene signature 30 in conjunction with the CIBERSORTx algorithm 31 . By employing single-sample gene enrichment analysis (ssGSEA) 32 within the R package GSVA (version 2.2.0), we assessed the degree of infiltration of 28 immune cell types 33 . 2.6 Landscape of somatic mutations in STAD Tumor mutational burden (TMB) is defined as the quantity of somatic mutations per megabase of DNA (Mut/Mb), encompassing various genetic alterations such as insertions, deletions, single-base substitutions, and chromosomal translocations 34 . 2.7 Functional enrichment analysis Based on ANKRD1 expression levels, TCGA patients were categorized into high-expression (top 50%) and low-expression (bottom 50%) groups. Differentially expressed genes (DEGs) between these two groups were identified using the “DESeq2” 35 , with a significance threshold set at adjusted P 1. To further explore the functional implications of ANKRD1 in Stomach Adenocarcinoma (STAD), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the “ClusterProfiler” 36 R package (v4.16.0), with terms considered significantly enriched at P < 0.05. The TCGA patients were divided into low (0–50%) and high (50–100%) groups based on ANKRD1 expression levels. The R package DESeq2 (version 1.48.1) was used to identify differentially expressed genes (DEGs) between the high-ANKRD1 and low-ANKRD1 expression groups. The threshold for significance was set to an adjusted P-value 1. To further investigate the role of ANKRD1 in STAD, we used the ClusterProfiler R package (version 4.16.0) to identify enriched Gene Ontology (GO) terms and KEGG pathways. and GSEA(Gene Set Enrichment Analysis) with P < 0.05. 2.8 Cell Culture and Transfection The cell lines selected for this study include the human Stomach Adenocarcinoma cell lines AGS, SGC-7901, BGC-803, MKN45, and the normal gastric mucosal epithelial cell line NGEC, all of which were purchased from the Shanghai Cell Bank of the Chinese Academy of Sciences. The cells were cultured in RPMI-1640 medium (Gibco, Cat. No. C11875500BT) supplemented with 10% fetal bovine serum (FBS, Gibco, Cat. No. 10099-141) and 1% penicillin-streptomycin solution (Solarbio, Cat. No. P1400). They were maintained in a humidified incubator (Thermo Scientific, Model Forma 3111) at 37°C with 5% CO₂ and 95% humidity. The culture medium was replaced every 2–3 days. When the cells reached 80%-90% confluence, they were passaged using 0.25% trypsin-EDTA (Gibco, Cat. No. 25200072), and cells in the logarithmic growth phase were used for subsequent experiments. The overexpression plasmid OE-ANKRD1 was constructed using the pcDNA3.1 (+) vector (Invitrogen, Cat. No. V79020), with the full-length CDS sequence of ANKRD1 (NM_001130086.2) inserted. The negative control plasmid (NC) was the empty pcDNA3.1 (+) vector. Three small interfering RNA (siRNA) sequences targeting the ANKRD1 gene (si-ANKRD1 #1, #2) were designed, with a non-targeting scramble RNA used as the negative control (si-NC). All oligonucleotides were synthesized by Shanghai GenePharma Co., Ltd. AGS or MKN-45 cells in the logarithmic growth phase were seeded into 6-well plates at a density of 5×10⁵ cells per well. Transfection was performed when cell confluence reached 60%-70%. The transfection was carried out using Lipofectamine 3000 reagent (Invitrogen, Cat. No. L3000015) according to the manufacturer's instructions. Briefly, 2 µg of plasmid (or 100 pmol siRNA) was mixed with 5 µL of P3000™ reagent. Simultaneously, 5 µL of Lipofectamine 3000 was mixed with 250 µL of Opti-MEM reduced-serum medium (Gibco, Cat. No. 31985070). After incubating separately at room temperature for 5 minutes, the two mixtures were combined and incubated for an additional 20 minutes at room temperature. The resulting complex was then added to each well. After 6 hours, the medium was replaced with complete culture medium. Transfection efficiency was assessed by PCR and Western blot (WB) 48 to 72 hours post-transfection. Cells exhibiting the highest knockdown or overexpression efficiency were selected for subsequent experiments. 2.9 PCR Using a high-fidelity DNA polymerase (such as Phusion High-Fidelity DNA Polymerase), cDNA from stomach adenocarcinoma cancer cells was used as the template, and PCR amplification was performed with specific primers. Primer sequences were as follows: STAT3 forward primer (5'-AGGAGTCTAACAACGGCAGCCT-3') and STAT3 reverse primer (5'- GTGGTACACCTCAGTCTCGAAG-3'), ANKRD1 forward primer (5'-CCAGACGAAGACCTGAAGGA-3') and ANKRD1 reverse primer (5'-GGTGGTGATGCTGATGTTGA − 3'), GAPDH forward primer (5'-TGCAACCGGGAAGGAAATGA-3') and GAPDH reverse primer (5'-GCCCAATACGACCAAATCAGA-3'). The PCR reaction system included template DNA, primers, dNTPs, buffer, and DNA polymerase. The reaction conditions were set as follows: initial denaturation at 95°C for 3 minutes, followed by 30–35 cycles (denaturation at 95°C for 30 seconds, annealing at a temperature set based on the primer Tm, and extension at 72°C for a duration determined by the product length), and a final extension at 72°C for 5–10 minutes. The PCR products were verified for size by agarose gel electrophoresis, purified, and recovered for subsequent experiments. 2.10 CCK-8 Assay After transfection, AGS and MKN-45 cells were digested with trypsin and resuspended in complete medium. The cell concentration was adjusted to 5×10³ cells per 100µL. The cell suspension was seeded into a 96-well plate (Corning, Cat. No. 3599) at 100µL per well. Each experimental group was set up with 5 replicate wells, and blank control wells (containing medium only) were also established. At 0, 1, 2, 3, and 4 days after seeding, 10µL of CCK-8 solution (Dojindo, Cat. No. CK04) was added to each well, followed by incubation at 37°C for 2 hours. The optical density (OD) at 450nm was then measured using a microplate reader (Bio-Tek, Model ELx808), with the blank control wells used for zero adjustment. A cell proliferation curve was plotted with the culture time as the x-axis and the average OD value as the y-axis. A higher OD value indicates stronger cell proliferative capacity. 2.11 Transwell Migration and Invasion Experiment The experimental procedure for the invasion assay was essentially the same as that for the migration assay. Transfected cells were resuspended in serum-free medium and adjusted to a concentration of 1×10⁵ cells in 200 µL. The lower chamber of the Transwell chamber (8 µm pore size, Corning, Cat# 3422) was filled with 600 µL of complete medium containing 20% FBS. The upper chamber was loaded with the 200 µL cell suspension. The chamber was incubated at 37°C for 24 hours. After incubation, the chamber was washed twice with PBS. Cells were fixed with 4% paraformaldehyde for 15 minutes and then stained with 0.1% crystal violet staining solution (Solarbio, Cat# G1063) for 10 minutes. Non-migrated cells on the upper surface of the membrane were gently removed with a cotton swab, followed by three washes with PBS.The membrane was imaged using an inverted microscope (Olympus, Model IX73). Five random fields of view (200× magnification) were captured per membrane, and the number of cells that migrated to the lower surface was counted. Matrigel matrix (BD, Cat# 356234) was diluted 1:8 with serum-free medium. Then, 50 µL of the diluted Matrigel was added to the upper chamber of the Transwell chamber (8 µm pore size, Corning, Cat# 3422) and allowed to solidify at 37°C for 4 hours.The subsequent steps were identical to the migration assay, except the incubation time was extended to 48 hours. Cell migration and invasion abilities were quantified by the mean number of cells that traversed the membrane. All results are presented as mean ± standard deviation. 2.12 Cell Scratch Test After transfection, cells were seeded into a 6-well plate (Corning, Cat# 3516). When the cells reached a confluent monolayer (fusion degree > 90%), a 200µL sterile pipette tip was used to gently create a scratch perpendicular to the bottom of the well. The cells were washed three times with PBS to remove detached cells. A medium containing 1% FBS was then added. The same location of the scratch was photographed at 0 hours and 24 hours using an inverted microscope (Olympus, Model IX73) at 100× magnification. The scratch width was measured using ImageJ software. The cell migration rate was calculated as follows: Migration rate = (scratch width at 0 hours – scratch width at 24 hours) / scratch width at 0 hours × 100%. A higher migration rate indicates stronger cell migration ability. 2.13 Western Blot Western blot was performed to detect the expression level of ANKRD1 protein in stomach adenocarcinoma cancer cells. Stomach Adenocarcinoma cells in the logarithmic growth phase were collected, and total protein was extracted by lysis followed by quantification using the BCA method. Equal amounts of protein samples were separated by SDS-PAGE and subsequently transferred to a PVDF membrane. After blocking, the membranes were incubated with anti-ANKRD1 primary antibody and the internal reference antibody β-actin at 4°C overnight. The next day, after incubation with HRP-labeled secondary antibody, protein bands were visualized using ECL chemiluminescence and recorded with an image acquisition system. 2.14 Statistical Analysis All statistical analyses were conducted using R software (version 4.5.0), GraphPad Prism 9, and ImageJ. Experimental data are presented as mean ± standard deviation (mean ± SD). Statistical comparisons were performed with GraphPad Prism 9, using independent samples t-test for comparisons between two groups and one-way ANOVA for multi-group comparisons. A P-value of < 0.05 was considered statistically significant.. 3. RESULTS 3.1 Elevated ANKRD1 Expression in Stomach Adenocarcinoma Analysis of the TIMER database revealed markedly increased ANKRD1 expression across multiple cancer types, with Stomach Adenocarcinoma (STAD) showing particularly high levels (Fig. 1 A). This finding was further validated using the UALCAN database, which also indicated significant upregulation of ANKRD1 in STAD samples (Fig. 1 B). 3.2 High Expression of ANKRD1 is Associated with Poor Prognosis in STAD Through analysis of the Kaplan-Meier plotter database, it was observed that patients exhibiting high expression levels of the ANKRD1 gene demonstrated significantly inferior overall survival (OS) (HR = 1.39, 95% CI: 1.17–1.65 p < 0.001; Fig. 2 A), first progression survival (FPS) (HR = 1.46, 95%CI: 1.19–1.78. p < 0.001; Fig. 2 B), and post-progression survival (PPS) (HR = 1.58, 95% CI: 1.26–1.97 p < 0.001; Fig. 2 C) when compared to patients with low expression levels. 3.3 ANKRD1 expression and the Immune Microenvironment of STAD To evaluate the relationship between ANKRD1 expression and immune cell infiltration, correlation analyses were performed. A matrix representing the relative abundance of 22 distinct tumor-infiltrating cell types was generated for 409 samples using CIBERSORT software locally ( Fig. 3 A). Patients with Stomach adenocarcinoma (STAD) were then stratified into high and low ANKRD1 expression groups based on the median expression level. Using CIBERSORTx analysis, we investigated the tumor immune microenvironment characteristics across these groups. The results indicated a statistically significant positive correlation (P < 0.05) between ANKRD1 expression and the frequencies of NK cells resting, Macrophages M0, and Macrophages M1. In contrast, ANKRD1 expression showed a statistically significant negative correlation (P < 0.05) with the proportions of B cells memory, T cells CD4 memory resting, and NK cells activated (Fig. 3 B). Additionally, based on single-sample Gene Set Enrichment Analysis (ssGSEA), ANKRD1 expression demonstrated positive correlations (P < 0.05) with several immune cell types, including Gamma delta T cell, Immature dendritic cell, Natural killer T cell, Regulatory T cell, and T follicular helper cell (Fig. 3 C). 3.4 The Genomic Landscape of Somatic Mutations in Stomach Adenocarcinoma Somatic mutation data from Stomach Adenocarcinoma (STAD) patients were acquired from the TCGA database and visualized using the "maftools" R package (v2.24.0). The resulting mutation landscape illustrates distinct mutation types using color codes, with a corresponding annotation provided below. The ten most frequently mutated genes were identified as follows: TTN (53%), TP53 (46%), MUC16 (32%), ARID1A (27%), LRP1B (27%), SYNE1 (25%), CSMD3 (24%), FAT4 (21%), FLG (20%), and PCLO (19%) (Fig. 4 A). Further analysis revealed that missense mutations represent the predominant variant category, and single nucleotide polymorphisms (SNPs) were more abundant than insertions or deletions. Among single nucleotide variants (SNVs), C-to-T transitions were the most prevalent type observed in STAD samples (Fig. 4 B). Additionally, the total number of mutations per sample was quantified, and the distribution of mutation types is summarized in a box plot, where each category is color-coded for clarity (Fig. 4 B). Notably, no somatic mutations were detected in ANKRD1 (mutation frequency: 0%), suggesting that its role in STAD prognosis is unlikely to be mediated through tumor mutational burden (TMB). 3.5 Functional Enrichment Analysis of DEGs Related to ANKRD1 In this study, we evaluated the potential role of ANKRD1 in Stomach Adenocarcinoma (STAD) through differential expression analysis. Based on the median expression value of ANKRD1, STAD patients were divided into high and low expression groups, with 204 patients in each group. The R package "DESeq2" was then used to screen for differentially expressed genes (DEGs) associated with ANKRD1. A total of 1868 differentially expressed genes were identified, including 64 up-regulated and 1804 down-regulated genes. The results are shown in the volcano plot (Fig. 5 A), with the threshold set at |logFC| > 1.0 and P < 0.05. GO enrichment analysis indicated that DEGs associated with ANKRD1 are involved in several BPs, including intermediate filament organization. In addition, it is also implicated in CC and MF. The CCs included the GABA − A receptor complex, muscle myosin complex, chloride channel complex, acrosomal vesicle, and intermediate filament cytoskeleton. The MFs included cysteine − type endopeptidase inhibitor activity, neurotransmitter receptor activity, hormone activity, endopeptidase regulator and inhibitor activity, and peptidase inhibitor activity (Fig. 5 B). In addition, KEGG analysis (Fig. 5 C) revealed the involvement of ANKRD1 in various pathways, such as Neuroactive ligand signaling, Cornified envelope formation, and Hormone signaling. The GSEA results indicate that ANKRD1 is involved in the following functions: Signaling by GPCR, Cytokine-mediated signaling pathway, Apoptotic signaling pathway, JAK-STAT signaling pathway, Signaling by interleukins, and Regulation of Wnt signaling pathway (Fig. 5 D–I). 3.6 ANKRD1 is Significantly Highly Expressed in Stomach Adenocarcinoma Cells To clarify the association between ANKRD1 and Stomach Adenocarcinoma, this study examined the expression levels of ANKRD1 protein in four Stomach Adenocarcinoma cell lines (SGC-901, BGC-803, AGS, MKN45) and the normal gastric mucosal epithelial cell line NGEC using Western blot (WB). The results (Fig. 6 ) showed that compared to the normal cell line NGEC, ANKRD1 protein was significantly overexpressed in all tested Stomach Adenocarcinoma cell lines (P < 0.05). Among these, the expression of ANKRD1 was highest in AGS and MKN45 cells, suggesting that ANKRD1 may be involved in regulating the malignant phenotype of Stomach Adenocarcinoma cells. Based on these findings, subsequent experiments selected AGS and MKN45 cells as the research subjects to more precisely elucidate the function of ANKRD1. 3.7 Verification of ANKRD1 Knockdown and Overexpression Efficiency With the aim of elucidating the biological functions of ANKRD1, we initiated the study by creating isogenic cell models featuring either knockdown or overexpression of ANKRD1.In this study, si-ANKRD1 (small interfering RNA) and OE-ANKRD1 (overexpression plasmid) were transfected into AGS and MKN45 cells, and the efficiency of knockdown and overexpression was validated by Western blot (WB) and PCR. The results (Fig. 7 A-B) showed that in AGS cells, compared with the si-NC group (negative control), the expression level of ANKRD1 was significantly reduced in the si-ANKRD1 group (P < 0.05). Compared with the NC group (empty vector control), the ANKRD1 expression was significantly increased in the OE-ANKRD1 group (P < 0.05). Similarly, in MKN45 cells (Fig. 7 C-D), the expression of ANKRD1 in the si-ANKRD1 group decreased by approximately 60% compared to the si-NC group (P < 0.05), while it increased approximately 1.9-fold in the OE-ANKRD1 group compared to the NC group (P < 0.05). These results indicate the successful establishment of the ANKRD1 knockdown and overexpression cell models. 3.8 ANKRD1 Effect on Stomach Adenocarcinoma Cell Proliferation CCK-8 Assay Based on the high expression of ANKRD1 in Stomach Adenocarcinoma cells, this study investigated its impact on the proliferative capacity of these cells using the CCK-8 assay. Cell viability (represented by OD450 values) was measured in AGS and MKN45 cells across the si-ANKRD1, si-NC, OE-ANKRD1, and NC groups at 0, 1, 2, 3, and 4 days of culture. The results showed that: In AGS cells (Fig. 8A-B), compared to the si-NC group, the OD values in the si-ANKRD1 group were significantly reduced starting from day 2 of culture (P < 0.05). Conversely, the OD values in the OE-ANKRD1 group were significantly higher than those in the NC group from day 2 onwards (P < 0.05).In MKN45 cells (Fig. 8C-D), the trend was consistent with that in AGS cells: the OD value in the si-ANKRD1 group was lower than that in the si-NC group on day 4 (P < 0.05), while the OD value in the OE-ANKRD1 group was higher than that in the NC group (P < 0.05). These results indicate that ANKRD1 significantly promotes the proliferation of Stomach Adenocarcinoma cells, as knocking down ANKRD1 inhibited cell proliferation, while its overexpression enhanced it. 3.9 ANKRD1 Effect on Stomach Adenocarcinoma Cell Migration Transwell Assay The migratory and invasive capacities of cells are critical hallmarks of Stomach Adenocarcinoma metastasis. We further investigated the impact of ANKRD1 on these capabilities using Transwell assays. Migration assay (Fig. 9 A-B): In AGS cells, the number of migrating cells in the si-ANKRD1 group was significantly lower than that in the si-NC group (P < 0.001), whereas the OE-ANKRD1 group showed a significantly higher number of migrating cells compared to the NC group (P < 0.05). In MKN45 cells, the number of migrating cells in the si-ANKRD1 group decreased by 64% compared to the si-NC group (P < 0.001), while the OE-ANKRD1 group exhibited an increase compared to the NC group (P < 0.05). Invasion assay (Fig. 9 C-D): The results were consistent with the migration assay. In AGS cells, the number of invading cells was significantly reduced in the si-ANKRD1 group compared to the si-NC group (P < 0.001) and significantly increased in the OE-ANKRD1 group compared to the NC group (P < 0.05). Similarly, in MKN45 cells, the si-ANKRD1 group showed a significant reduction in invading cells compared to the si-NC group (P < 0.001), and the OE-ANKRD1 group showed a significant increase compared to the NC group (P < 0.05). These findings suggest that ANKRD1 significantly enhances the migratory and invasive abilities of Stomach Adenocarcinoma cells. 3.10 Investigating the Role of ANKRD1 in the Motility of Stomach Adenocarcinoma cells Using a Wound Healing Assay To further validate the impact of ANKRD1 on the migration ability of stomach adenocarcinoma cells, we assessed the scratch healing capacity of the cells through a wound healing assay. The results showed that in AGS cells, the 24-hour wound healing rate in the si-ANKRD1 group was significantly lower than that in the si-NC group (P < 0.05) (Fig. 10 A), while the healing rate in the OE-ANKRD1 group was significantly higher than that in the NC group (P < 0.05) (Fig. 10 C). In MKN45 cells, the healing rate in the si-ANKRD1 group decreased by 55% compared to the si-NC group (P < 0.05) (Fig. 10 B), whereas the healing rate in the OE-ANKRD1 group increased compared to the NC group (P < 0.05) (Fig. 10 D). These results are consistent with the Transwell migration assay, further confirming that ANKRD1 promotes the migration ability of stomach adenocarcinoma cells. 3.11 ANKRD1 Affects the Functions of Stomach Adenocarcinoma cells by Modulating the STAT3 Signaling Pathway To explore the potential molecular mechanism by which ANKRD1 exerts its cancer-promoting effects, we examined the protein levels of ANKRD1, total STAT3, and phosphorylated STAT3 (p-STAT3) in stomach adenocarcinoma cells following ANKRD1 knockdown or overexpression, using Western blot (WB). In AGS cells (Fig. 11 A), compared to the si-NC group, ANKRD1 expression was significantly reduced in the si-ANKRD1 #2 group (P < 0.05), and the level of p-STAT3 was also significantly downregulated (P < 0.05). Conversely, in the OE-ANKRD1 #2 group, ANKRD1 expression was significantly increased compared to the NC group (P < 0.05), which was accompanied by a significant upregulation of p-STAT3 levels (P < 0.05). In MKN-45 cells (Fig. 11 B), a consistent trend was observed: in the si-ANKRD1 #2 group, the expression of ANKRD1 and p-STAT3 decreased compared to the si-NC group (both P < 0.05), while total STAT3 showed no significant change. In the OE-ANKRD1 #2 group, the expression of ANKRD1 and p-STAT3 was significantly increased compared to the NC group (P < 0.05), while the level of total STAT3 remained unchanged. These results indicate that ANKRD1 expression is closely associated with the phosphorylation and activation of STAT3, suggesting that ANKRD1 promotes the malignant phenotype of stomach adenocarcinoma cells, at least in part, by activating the STAT3 signaling pathway. This provides important insights into the mechanism of ANKRD1 in the progression of stomach adenocarcinoma. 4. DISCUSSION Stomach adenocarcinoma remains a significant global health challenge, with ongoing difficulties in understanding its pathogenesis and developing clinical treatments 37–39 .Epidemiologically, stomach adenocarcinoma shows remarkable geographical variation, with a particularly high disease burden in East Asia and Eastern Europe. This distribution pattern reflects the complex interplay of genetic background, environmental exposures, and socioeconomic factors 40 .The development of stomach adenocarcinoma is a multi-stage process, with Helicobacter pylori infection being the primary causative factor, responsible for approximately 90% of non-cardia gastric cancers 41 .Notably, genetic susceptibility plays a crucial role in the pathogenesis of stomach adenocarcinoma 42,43 .For example, hereditary diffuse gastric cancer caused by CDH1 gene mutations, although accounting for a small proportion of cases, is clinically significant 44 . The most distinctive feature of its encoded protein is the presence of N-terminal ankyrin repeat (ANK) domains, which mediate extremely diverse protein-protein interactions 45 .ANKRD1 expression is strictly regulated in both time and space 46 .It is highly active during embryonic heart development, decreases in adulthood, but is rapidly and strongly re-induced in response to various stresses such as biomechanical stress, hypoxia, oxidative stress, hormonal stimulation, and tissue damage 47 .This suggests it plays a central role in maintaining internal homeostasis 48 .In terms of molecular function, ANKRD1 is considered a "molecular scaffold" with significantly context-dependent functionality. Firstly, as a transcriptional co-regulator, although it does not directly bind to DNA, it can interact with transcription factors such as p53 and YB-1 through its ANK domains, shuttling between the cytoplasm and nucleus, thereby significantly enhancing or suppressing the transcriptional activity of target genes. For instance, its interaction with p53 can amplify the DNA damage response 49 .Secondly, in skeletal and cardiac muscle, ANKRD1 localizes to the I-band of the sarcomere, interacting with the N2A region of titin and calpain, making it a key molecule in sensing and transmitting mechanical signals and maintaining sarcomere structural integrity 50 .Furthermore, ANKRD1 is involved in regulating apoptosis and autophagy 51 .In some contexts, it promotes cell survival by inhibiting apoptotic proteins or modulating autophagy flux, while in others, it may cooperate with p53 to promote apoptosis, reflecting its dual functionality 52 . Given these multifaceted roles of ANKRD1 in cellular stress response and transcriptional regulation, we sought to investigate its specific function in the context of STAD. Our findings reveal that Stomach adenocarcinoma (STAD) remains a formidable global health challenge with a high incidence and poor prognosis, underscoring the urgent need to identify reliable prognostic biomarkers and therapeutic targets. In this study, we systematically demonstrated that ANKRD1 is significantly overexpressed in STAD tissues and cell lines. This elevated expression was strongly associated with unfavorable patient survival outcomes, including overall survival, first progression survival, and post-progression survival, establishing ANKRD1 as a potent prognostic indicator. Notably, our analysis of the somatic mutation landscape revealed that ANKRD1 itself is not mutated in STAD, suggesting that its oncogenic role is driven by transcriptional upregulation rather than genetic alteration. To decipher the biological functions of ANKRD1, we performed functional enrichment analyses. Intriguingly, while GO and KEGG analyses highlighted enrichment in pathways like olfactory transduction, GSEA provided more direct oncogenic insights, linking ANKRD1 to crucial cancer-related pathways such as GPCR signaling and the JAK-STAT pathway. A key aspect of tumor progression is the tumor immune microenvironment. Our study revealed that ANKRD1 expression correlates with a distinct immune cell infiltration pattern, characterized by suppressive features such as reduced activated NK cells and enriched pro-tumoral macrophages. This suggests that ANKRD1 may contribute to an immunosuppressive milieu, potentially explaining the poorer prognosis observed in patients with high ANKRD1 expression. The central finding of our study is the functional role of ANKRD1 as a bona fide oncogene. Through comprehensive in vitro experiments, we conclusively demonstrated that ANKRD1 knockdown significantly inhibited, while its overexpression enhanced, the proliferation, migration, and invasion capabilities of STAD cells. These results unequivocally position ANKRD1 as an active driver of STAD malignancy. Mechanistically, we bridged these phenotypic observations to a specific signaling pathway. Our data indicate that ANKRD1's oncogenic effects are likely mediated through the activation of the STAT3 signaling pathway, as evidenced by concomitant changes in STAT3 phosphorylation upon ANKRD1 manipulation. The STAT3 pathway is a well-known master regulator of oncogenesis, controlling cell survival, proliferation, and immune evasion. Therefore, we propose a plausible model wherein ANKRD1, positioned as an upstream regulator, enhances STAT3 phosphorylation, thereby orchestrating a transcriptional program that fuels the aggressive phenotype of STAD cells. In conclusion, our integrative multi-omics and experimental approach unveils ANKRD1 as a critical player in STAD pathogenesis and progression. It functions as a non-mutated oncogene that promotes malignant behaviors, likely by fostering an immunosuppressive microenvironment and activating the STAT3 signaling pathway. These findings nominate ANKRD1 as a promising prognostic biomarker and a potential therapeutic target for STAD. Our study employed a comprehensive and multi-faceted methodological approach to investigate the role of ANKRD1 in STAD. A key strength lies in the integration of extensive bioinformatics analyses from multiple public databases (TCGA, UALCAN, TIMER, KM plotter) with robust in vitro experimental validation. The bioinformatics component not only provided a high-level, clinically correlated overview of ANKRD1's expression, prognostic value, and association with the immune microenvironment but also guided our subsequent functional experiments by highlighting potential mechanisms, such as the JAK-STAT pathway identified through GSEA. This hypothesis-generating approach ensured that our wet-lab experiments were targeted and biologically relevant. Furthermore, the in vitro models were rigorously established using both gain-of-function and loss-of-function strategies in two distinct STAD cell lines, which consistently corroborated the pro-tumorigenic functions of ANKRD1, thereby strengthening the reliability of our conclusions regarding its role in promoting proliferation, migration, and invasion. However, several limitations of our study should be acknowledged. Firstly, while our in vitro findings are compelling, they lack validation in an in vivo setting. The use of animal models, such as xenograft mice, would be essential to confirm the tumor-promoting effects of ANKRD1 within a complex tumor microenvironment and to substantiate its potential as a therapeutic target. Secondly, although we identified a correlation between ANKRD1 expression and the phosphorylation of STAT3, the precise molecular mechanism by which ANKRD1 activates the STAT3 signaling pathway remains unclear. It is uncertain whether this interaction is direct or indirect, and further investigations, such as co-immunoprecipitation assays, are required to delineate the exact molecular intermediaries or binding partners involved. Lastly, the immune cell infiltration analysis, while insightful, was derived from computational algorithms based on transcriptomic data. These findings warrant confirmation through more direct methods like flow cytometry or immunohistochemistry on clinical tissue samples to accurately quantify the infiltrating immune cell populations. 5. CONCLUSIONS In summary, our study comprehensively demonstrates that ANKRD1 is significantly overexpressed in Stomach Adenocarcinoma (STAD) and is associated with poor patient prognosis. Through multi-database bioinformatics analysis and experimental validation, we established that high ANKRD1 expression promotes the proliferation, migration, and invasion of STAD cells. Mechanistically, ANKRD1 likely exerts its oncogenic functions by activating the STAT3 signaling pathway, as evidenced by correlated phosphorylation levels of STAT3 upon modulation of ANKRD1 expression. Furthermore, ANKRD1 expression is linked to specific immune cell infiltration patterns in the tumor microenvironment, although it does not contribute to tumor mutation burden .These findings highlight ANKRD1 as a potential prognostic biomarker and therapeutic target in Stomach Adenocarcinoma, providing new insights into the molecular mechanisms driving STAD progression. Declarations Ethics Approval Not applicable Consent to publish Not applicabl Consent to participate Not applicable Competing interests The authors hereby declare that there are no competing financial interests or personal relationships that could be construed as influencing the work presented in this paper. Author contributions Lu Nie participated in research design, statistical analysis, and manuscript drafting; Nie Yu, Nie Lu, and Wang Ruiyang were responsible for PCR, WB, and all cell experiments.; Lu Nie and Ruiyang Wang contributed to study design and guided manuscript drafting. All authors reviewed the manuscript. Funding This research received no external funding. Data availability The TCGA dataset for 445 samples was sourced from https://portal.gdc.cancer.gov (Project IDs: TCGA-STAD). UALCAN database (http://ualcan.path.uab.edu/) TIMER database (http://timer.cistrome.org/) KM plotter database (https://www.kmplot.com/analysis/) References Goetze, O.T., Al-Batran, S.E., Chevallay, M. & Mönig, S.P. Multimodal treatment in locally advanced gastric cancer. Updates Surg 70 , 173-179 (2018). Ma, J., Shen, H., Kapesa, L. & Zeng, S. Lauren classification and individualized chemotherapy in gastric cancer. Oncol Lett 11 , 2959-2964 (2016). Milano, A.F. 20-Year Comparative Survival and Mortality of Cancer of the Stomach by Age, Sex, Race, Stage, Grade, Cohort Entry Time-Period, Disease Duration & Selected ICD-O-3 Oncologic Phenotypes: A Systematic Review of 157,258 Cases for Diagnosis Years 1973-2014: (SEER*Stat 8.3.4). J Insur Med 48 , 5-23 (2019). Posselt, G., Crabtree, J.E. & Wessler, S. Proteolysis in Helicobacter pylori-Induced Gastric Cancer. Toxins (Basel) 9 (2017). Debowski, A.W. , et al. Helicobacter pylori gene silencing in vivo demonstrates urease is essential for chronic infection. PLoS Pathog 13 , e1006464 (2017). Liu, J. , et al. Prognostic value of the Epstein-Barr virus and tumor suppressor gene p53 gene in nasopharyngeal squamous cell carcinoma. J Cancer Res Ther 15 , 426-436 (2019). Côme, P., Rochefort, P., De Crignis, L. & Dupré, A. [Prophylactic gastrectomy]. Bull Cancer 112 , 259-262 (2025). Wang, V.G., Kim, H. & Chuang, J.H. Whole-exome sequencing capture kit biases yield false negative mutation calls in TCGA cohorts. PLoS One 13 , e0204912 (2018). Usui, G. , et al. DNA Methylation and Genetic Aberrations in Gastric Cancer. Digestion 102 , 25-32 (2021). Torres, C. & Grippo, P.J. Pancreatic cancer subtypes: a roadmap for precision medicine. Ann Med 50 , 277-287 (2018). Aziz, H. , et al. Hepatic adenoma: evolution of a more individualized treatment approach. J Gastrointest Surg 28 , 975-982 (2024). Leowattana, W., Leowattana, P. & Leowattana, T. Systemic treatment for advanced pancreatic cancer. World J Gastrointest Oncol 15 , 1691-1705 (2023). Yu, J. , et al. Unleashing the efficacy of immune checkpoint inhibitors for advanced hepatocellular carcinoma: factors, strategies, and ongoing trials. Front Pharmacol 14 , 1261575 (2023). Fuchs, C.S. , et al. Safety and Efficacy of Pembrolizumab Monotherapy in Patients With Previously Treated Advanced Gastric and Gastroesophageal Junction Cancer: Phase 2 Clinical KEYNOTE-059 Trial. JAMA Oncol 4 , e180013 (2018). Akter, Z., Salamat, N., Ali, M.Y. & Zhang, L. The promise of targeting heme and mitochondrial respiration in normalizing tumor microenvironment and potentiating immunotherapy. Front Oncol 12 , 1072739 (2022). Saleh, R. & Elkord, E. Acquired resistance to cancer immunotherapy: Role of tumor-mediated immunosuppression. Semin Cancer Biol 65 , 13-27 (2020). Shen, L. , et al. Overexpression of ankyrin repeat domain 1 enhances cardiomyocyte apoptosis by promoting p53 activation and mitochondrial dysfunction in rodents. Clin Sci (Lond) 128 , 665-678 (2015). Wen, D. , et al. The impact of METTL3 on bladder cancer through m(6)A modification: a potential therapeutic target and prognostic biomarker. Front Oncol 15 , 1622117 (2025). Jiménez, A.P. , et al. The tumor suppressor RASSF1A induces the YAP1 target gene ANKRD1 that is epigenetically inactivated in human cancers and inhibits tumor growth. Oncotarget 8 , 88437-88452 (2017). Yadegar, N. , et al. The Prominent Role of miR-942 in Carcinogenesis of Tumors. Adv Biomed Res 11 , 63 (2022). Irshad, N. , et al. Mangiferin: An effective agent against human malignancies. Food Sci Nutr 12 , 7137-7157 (2024). Radke, M.H. , et al. Deleting Full Length Titin Versus the Titin M-Band Region Leads to Differential Mechanosignaling and Cardiac Phenotypes. Circulation 139 , 1813-1827 (2019). Wallace, G.Q. & McNally, E.M. Mechanisms of muscle degeneration, regeneration, and repair in the muscular dystrophies. Annu Rev Physiol 71 , 37-57 (2009). Griffiths, K. , et al. Fluorinated perhexiline derivative attenuates vascular proliferation in pulmonary arterial hypertension smooth muscle cells. Vascul Pharmacol 156 , 107399 (2024). Wang, Q. , et al. Targeting NF-kB signaling with polymeric hybrid micelles that co-deliver siRNA and dexamethasone for arthritis therapy. Biomaterials 122 , 10-22 (2017). Shen, X. , et al. ALDH2 as an immunological and prognostic biomarker: Insights from pan-cancer analysis. Medicine (Baltimore) 103 , e37820 (2024). He, X. , et al. Clinical significance for diagnosis and prognosis of POP1 and its potential role in breast cancer: a comprehensive analysis based on multiple databases. Aging (Albany NY) 14 , 6936-6956 (2022). Zhao, C. , et al. NEIL3 may act as a potential prognostic biomarker for lung adenocarcinoma. Cancer Cell Int 21 , 228 (2021). Li, X. , et al. Regulation of P53 signaling in breast cancer by the E3 ubiquitin ligase RNF187. Cell Death Dis 13 , 149 (2022). Newman, A.M. , et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods 12 , 453-457 (2015). Han, S. , et al. A Prognostic Signature Constructed by CTHRC1 and LRFN4 in Stomach Adenocarcinoma. Front Genet 12 , 646818 (2021). Jin, H. , et al. Integrative Genomic and Transcriptomic Analysis of Primary Malignant Gliomas Revealed Different Patterns Between Grades and Somatic Mutations Related to Glioblastoma Prognosis. Front Mol Biosci 9 , 873042 (2022). Yan, G. , et al. Potential Impact of ALKBH5 and YTHDF1 on Tumor Immunity in Colon Adenocarcinoma. Front Oncol 11 , 670490 (2021). Cui, S. , et al. The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients. Eur J Med Res 28 , 90 (2023). Jiang, Y. , et al. Insights into potential mechanisms of asthma patients with COVID-19: A study based on the gene expression profiling of bronchoalveolar lavage fluid. Comput Biol Med 146 , 105601 (2022). Yang, Y. , et al. Prognostic value of a hypoxia-related microRNA signature in patients with colorectal cancer. Aging (Albany NY) 12 , 35-52 (2020). Huang, H. , et al. An integrated analysis of DNA promoter methylation, microRNA regulation, and gene expression in gastric adenocarcinoma. Ann Transl Med 9 , 1414 (2021). Ajani, J.A. , et al. Gastric adenocarcinoma. Nat Rev Dis Primers 3 , 17036 (2017). Sutton, P. & Boag, J.M. Status of vaccine research and development for Helicobacter pylori. Vaccine 37 , 7295-7299 (2019). Marrie, R.A. Demographic, genetic, and environmental factors that modify disease course. Neurol Clin 29 , 323-341 (2011). Bornschein, J. & Malfertheiner, P. Gastric carcinogenesis. Langenbecks Arch Surg 396 , 729-742 (2011). Chmiela, M., Karwowska, Z., Gonciarz, W., Allushi, B. & Stączek, P. Host pathogen interactions in Helicobacter pylori related gastric cancer. World J Gastroenterol 23 , 1521-1540 (2017). Mocellin, S., Verdi, D., Pooley, K.A. & Nitti, D. Genetic variation and gastric cancer risk: a field synopsis and meta-analysis. Gut 64 , 1209-1219 (2015). Jakubowska, A. , et al. CDH1 gene mutations do not contribute in hereditary diffuse gastric cancer in Poland. Fam Cancer 9 , 605-608 (2010). Tyrkalska, S.D. , et al. Identification of an Evolutionarily Conserved Ankyrin Domain-Containing Protein, Caiap, Which Regulates Inflammasome-Dependent Resistance to Bacterial Infection. Front Immunol 8 , 1375 (2017). Badi, I. , et al. Intracellular ANKRD1 protein levels are regulated by 26S proteasome-mediated degradation. FEBS Lett 583 , 2486-2492 (2009). Clunie-O'Connor, C. , et al. The Derivation of Primary Human Epicardium-Derived Cells. Curr Protoc Stem Cell Biol 35 , 2c.5.1-2c.5.12 (2015). Cui, Y. , et al. Molecular mechanisms by which casein glycomacropeptide maintains internal homeostasis in mice with experimental ulcerative colitis. PLoS One 12 , e0181075 (2017). Kciuk, M., Gielecińska, A., Mujwar, S., Mojzych, M. & Kontek, R. Cyclin-Dependent Kinase Synthetic Lethality Partners in DNA Damage Response. Int J Mol Sci 23 (2022). Belgrano, A. , et al. Multi-tasking role of the mechanosensing protein Ankrd2 in the signaling network of striated muscle. PLoS One 6 , e25519 (2011). Xu, X. , et al. Pan-cancer integrated analysis of ANKRD1 expression, prognostic value, and potential implications in cancer. Sci Rep 14 , 5268 (2024). Pellegrini, F.R. , et al. Blockage of autophagosome-lysosome fusion through SNAP29 O-GlcNAcylation promotes apoptosis via ROS production. Autophagy 19 , 2078-2093 (2023). Additional Declarations No competing interests reported. Supplementary Files TableS1.docx SupplementaryWesternBlotfullmembranescan.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7782118","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":561105714,"identity":"e659e680-ad53-4cb5-ac39-82e9b505e4e0","order_by":0,"name":"Lu Nie","email":"","orcid":"","institution":"Shandong Cancer Hospital and Institute Shandong First Medical University, Shandong Academy of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Lu","middleName":"","lastName":"Nie","suffix":""},{"id":561105718,"identity":"8191e580-aa1c-47a6-afcb-6d4701322805","order_by":1,"name":"Yu Nie","email":"","orcid":"","institution":"Shandong Second Provincial General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Nie","suffix":""},{"id":561105719,"identity":"adfe6741-c101-4f84-8fc6-69ca62f3e62b","order_by":2,"name":"Ruiyang Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvUlEQVRIiWNgGAWjYJCCAyCCn5n54APStEi2syUbkGaVwXkeMwHiVN4+Y3iYp+aO3ebDDGYMDDU20YS1nMsxOMxz7FnytsMMaQ8YjqXlNhDSYnaGB6iF7XCy2WGG4waMDYeJ1fLvcLJxM2ObBPFaeNsO2xkwM7MRp8X+DFvBwbl9hxMkDrMxGyQQ4xfJHubNH958O2zP33/+44MPNTaEtYAAEw8DQyJYZQIxykGA8QfQgcQqHgWjYBSMghEIAD5xQQ6vhAWHAAAAAElFTkSuQmCC","orcid":"","institution":"University of Traditional Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Ruiyang","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-10-04 23:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7782118/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7782118/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98606403,"identity":"9b724eef-ff19-4986-af71-f2a3d1af57a1","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3803463,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/b249d0a1db1f2c782797eb17.docx"},{"id":98606401,"identity":"2ea8c6e3-18dc-4c22-9934-ed08bb4c0c1b","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":19901,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/1cc29ec85ec4bc3f43071313.docx"},{"id":98628894,"identity":"2369f936-3d28-4226-88be-42e796b24128","added_by":"auto","created_at":"2025-12-19 17:12:44","extension":"json","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5559,"visible":true,"origin":"","legend":"","description":"","filename":"21f0557b14a948a08c3072a45520e01c.json","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/bf51aaa74ef30f1f82789aec.json"},{"id":98628013,"identity":"b6b55c99-5b67-41e5-a558-d1cee0382025","added_by":"auto","created_at":"2025-12-19 17:10:52","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8516962,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryWesternBlotfullmembranescan.docx","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/037de1efe8fe6bcaf5bbcc7b.docx"},{"id":98606410,"identity":"47c95332-1fb1-428f-bce0-9ce4d31f7f78","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":70084,"visible":true,"origin":"","legend":"","description":"","filename":"21f0557b14a948a08c3072a45520e01c1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/39d9c2e8197b6427e34fb0ea.xml"},{"id":98629447,"identity":"dc4ad1ae-ac09-4014-9eda-3f17694b4d93","added_by":"auto","created_at":"2025-12-19 17:13:59","extension":"zip","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1919662,"visible":true,"origin":"","legend":"","description":"","filename":"FigPDF.zip","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/33b03f8a0ca5b95e20aee404.zip"},{"id":98606414,"identity":"b6081e6b-b3be-44f5-88ae-1d3b51f98ee4","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":267195,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/2cc6813aa05516c898c0d220.png"},{"id":98606412,"identity":"91be7cff-996a-432d-8c76-21deaeddf66b","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"jpeg","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":544818,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage10.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/ef6e66553bb6b6e47438564e.jpeg"},{"id":98628760,"identity":"444bd0f8-fb90-42f9-8e74-c5aa9dfab150","added_by":"auto","created_at":"2025-12-19 17:12:22","extension":"jpeg","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":277324,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage11.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/fa707a6d5557cebcf0e4c923.jpeg"},{"id":98628975,"identity":"4cac8031-f7ec-405c-81e3-143651af972b","added_by":"auto","created_at":"2025-12-19 17:12:58","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":147327,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/3ccd79ed6f9f9a8e5a75a30c.png"},{"id":98606419,"identity":"a615fbb4-fd2a-4c36-9e86-47b99d12ddb5","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"jpeg","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":780490,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/4418dc36270c75629dd8cccc.jpeg"},{"id":98627951,"identity":"5c78f145-99b8-47d2-9ebc-dee0f38e72bb","added_by":"auto","created_at":"2025-12-19 17:10:48","extension":"jpeg","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":481918,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/1249c58b4b16f318e8309ce4.jpeg"},{"id":98606426,"identity":"9ce28269-6f74-4ba5-82d2-387dc8ff7183","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"jpeg","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":378315,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/0db0bac5ce514a41862ca157.jpeg"},{"id":98628831,"identity":"521c6215-92b2-496c-b534-0b1396a99235","added_by":"auto","created_at":"2025-12-19 17:12:37","extension":"jpeg","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":92438,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/28b2d3e8ceca2909a222a699.jpeg"},{"id":98606430,"identity":"0e78efe1-37b2-4cfc-ba20-622d51f3b549","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"jpeg","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":231568,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/435c3a3b9f05e69dae69d674.jpeg"},{"id":98629011,"identity":"81b6478b-f9bf-43fe-a2bc-9a7c4203af49","added_by":"auto","created_at":"2025-12-19 17:13:05","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":82516,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/8fe3222d30be60089b6edfec.png"},{"id":98606433,"identity":"54fafe20-e7b9-4f1b-8d4e-78a099ed6c54","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"jpeg","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":692344,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/ce394fba216a37da367cba03.jpeg"},{"id":98628110,"identity":"f800add2-249f-4b3a-a190-f68ade7cb7b8","added_by":"auto","created_at":"2025-12-19 17:10:59","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":42402,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/fb6049cc3c377b77bcde072c.png"},{"id":98606424,"identity":"c3b8719c-d2f5-4412-b197-49dfc5da1691","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":99315,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/d5f2c258c8dc45225d5c515d.png"},{"id":98606429,"identity":"605c12e8-9e86-4a01-b51e-f54f92d62c0e","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":29445,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/62bcd20679748e0dd352f4f0.png"},{"id":98628746,"identity":"d4d3adf6-5af0-4657-aa97-73f22a746bec","added_by":"auto","created_at":"2025-12-19 17:12:21","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":29890,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/a510c93094dc67ff8140a586.png"},{"id":98629106,"identity":"0eabb810-d610-4bb3-80ae-52f1e89c309c","added_by":"auto","created_at":"2025-12-19 17:13:15","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":61763,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/40a7521db1b5555c3403f50e.png"},{"id":98606432,"identity":"9b7b02f9-955e-4f6b-b528-525663e47ed5","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"png","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":38300,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/2fc7488d392d8242402a3e2f.png"},{"id":98606431,"identity":"bc930650-cd49-4e50-9e8b-14b671d56b2e","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"png","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":63482,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/4073f0ba67b4e1159a263b37.png"},{"id":98606439,"identity":"7baadb1f-a2bf-48b3-869e-9dd9abaf3821","added_by":"auto","created_at":"2025-12-19 13:40:10","extension":"png","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":19942,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/884c8470cfdd335cde18c501.png"},{"id":98606436,"identity":"35cc06c5-61f6-4599-8018-e475e5756f86","added_by":"auto","created_at":"2025-12-19 13:40:10","extension":"png","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":28096,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/ac083932e862c4e20234b2ba.png"},{"id":98629075,"identity":"e8700adb-9073-4f26-88cd-7f2f66e9eb71","added_by":"auto","created_at":"2025-12-19 17:13:12","extension":"png","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":23504,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/a65c967a70fa43a2f353743e.png"},{"id":98606435,"identity":"ad3b6f97-feae-4cd5-8e1d-24a8874e8d90","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"png","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":92882,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/1223c2c3b6605bae3c8d8a00.png"},{"id":98628394,"identity":"8a86a5ea-6e63-41cd-b8d2-2071354cecdf","added_by":"auto","created_at":"2025-12-19 17:11:26","extension":"xml","order_by":29,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":83378,"visible":true,"origin":"","legend":"","description":"","filename":"21f0557b14a948a08c3072a45520e01c1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/30baf132b9d86bc40c73d2b1.xml"},{"id":98606440,"identity":"52005300-89a3-4c87-ada6-f0f102630ed9","added_by":"auto","created_at":"2025-12-19 13:40:10","extension":"html","order_by":30,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":75178,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/3069d0c1426e238a67901883.html"},{"id":98628923,"identity":"6a04105d-bc38-483b-ab72-a3b0c2389bff","added_by":"auto","created_at":"2025-12-19 17:12:48","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":85538,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of ANKRD1 expression in multiple databases. (A) Expression levels of ANKRD1 in different cancer types according toTIMER. ***P\u0026lt; 0.001, **P \u0026lt; 0.01, *P\u0026lt; 0.05. (B) Box plot comparing ANKRD1 expression in STAD derived from UALCAN.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/8c85684c03dd55445f1cdaf7.jpg"},{"id":98606397,"identity":"d41b050b-4922-4fde-a54c-8b15c62ba8f8","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":61595,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier survival curve of STAD patients with ANKRD1 expression. (A) High ANKRD1 expression showed a significantly poorer Overall Survival (OS) rate. (B) First Progression Survival (FPS). (C) Post Progression Survival (PPS).\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/8194394c7284495e96fc0258.jpg"},{"id":98606399,"identity":"0cf37936-867a-4657-9a25-bc880c951dbe","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":119312,"visible":true,"origin":"","legend":"\u003cp\u003eComprehensive evaluation of ANKRD1 expression in tumor-infiltrating immune cells (TIICs). (A) Composition of TIICs across samples. (B) Comparative abundances of 22 TIIC subtypes between STAD patients with high versus low ANKRD1 expression. (C) Single-sample GSEA (ssGSEA) scores for immune-related pathways stratified by ANKRD1 expression (ns: not significant; *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/3b6f808b77d9fff5925f28e5.jpg"},{"id":98628928,"identity":"50aea59e-5cf8-41ff-97f7-4fb4c14e3892","added_by":"auto","created_at":"2025-12-19 17:12:50","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":76793,"visible":true,"origin":"","legend":"\u003cp\u003eSomatic mutation landscape in STAD. (A) Mutation spectrum showing the top mutated genes ranked by mutation frequency (left) and the distribution of mutation types (bottom). (B) Profiles of variant classifications, single nucleotide variant (SNV) categories, and mutation types in the STAD cohort.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/5d2de3f32f3188d780b422bf.jpg"},{"id":98628192,"identity":"d3148c95-1758-4e74-8323-466a532454d4","added_by":"auto","created_at":"2025-12-19 17:11:07","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":107792,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional enrichment analysis of ANKRD1-associated differentially expressed genes (DEGs). (A) Volcano plot visualizing DEGs between high and low ANKRD1 expression groups. (B) Gene Ontology (GO) terms enriched among the DEGs. (C) Significantly enriched KEGG pathways. (D–I) Gene Set Enrichment Analysis (GSEA) of the DEG sets.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/c33afc2efdbb691d81124f0d.jpg"},{"id":98628781,"identity":"64b3acbd-e4a6-4f1d-ab6f-fa0ba3e93df4","added_by":"auto","created_at":"2025-12-19 17:12:28","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":18227,"visible":true,"origin":"","legend":"\u003cp\u003eANKRD1 is upregulated in Stomach Adenocarcinoma cell lines.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/6a8d133a83638b5749dbdf8f.jpg"},{"id":98606407,"identity":"a2ef58ca-38be-472e-9af1-f20188bc7665","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":73637,"visible":true,"origin":"","legend":"\u003cp\u003eEfficient knockdown and overexpression of ANKRD1 in AGS and MKN45 cells. (A-B) Western blot (WB) and Polymerase Chain Reaction (PCR) analysis of ANKRD1 expression in AGS cells transfected with si-ANKRD1 or OE-ANKRD1 plasmid. (C-D) WB and PCR analysis of ANKRD1 expression in MKN45 cells transfected with si-ANKRD1 or OE-ANKRD1 plasmid. Data are presented as mean ± SD (P \u0026lt; 0.05 vs. respective control group).\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/fe37150a862eab4a406412b7.jpg"},{"id":98628931,"identity":"f746187e-5041-4082-93c8-2855ecc67bde","added_by":"auto","created_at":"2025-12-19 17:12:50","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":70709,"visible":true,"origin":"","legend":"\u003cp\u003eANKRD1 promotes the proliferation of Stomach Adenocarcinoma cell. (A-B) Proliferation of AGS cells assessed by CCK-8 assay after ANKRD1 knockdown or overexpression. OD450 values were measured at 0, 1, 2, 3, and 4 days. (C-D) Proliferation of MKN45 cells assessed by CCK-8 assay after ANKRD1 knockdown or overexpression. OD450 values were measured at 0, 1, 2, 3, and 4 days.\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/602ed9349023d60c376d0e63.jpg"},{"id":98629631,"identity":"a827e026-3642-4ac0-a8e0-694108132e4f","added_by":"auto","created_at":"2025-12-19 17:14:22","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":112057,"visible":true,"origin":"","legend":"\u003cp\u003eANKRD1 regulates the migratory and invasive capabilities of Stomach Adenocarcinomacells.\u003c/p\u003e\n\u003cp\u003e(A, B) Migration assays performed using Transwell chambers without Matrigel coating.(C, D) Invasion assays performed using Transwell chambers pre-coated with Matrigel. Statistical significance is indicated as *P \u0026lt; 0.05 and ***P \u0026lt; 0.001 compared to their respective control groups.\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/5b89b91b6da6f78515085ea4.jpg"},{"id":98628976,"identity":"5f1820a1-1a98-45af-9f71-69564a6b207f","added_by":"auto","created_at":"2025-12-19 17:12:58","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":99738,"visible":true,"origin":"","legend":"\u003cp\u003eANKRD1 promotes the migration of stomach adenocarcinoma cells in a scratch wound healing assay. (A) Effect of si-ANKRD1 on migration in AGS cells. (B) Effect of si-ANKRD1 on migration in MKN45 cells. (C) Effect of OE-ANKRD1 on migration in AGS cells. (D) Effect of OE-ANKRD1 on migration in MKN45 cells. Statistical significance is indicated as *P \u0026lt; 0.05 compared to their respective control groups.\u003c/p\u003e","description":"","filename":"10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/af7f558e136da22dd3018267.jpg"},{"id":98629471,"identity":"f1e2b127-18da-4f14-ada3-38c34ab5730a","added_by":"auto","created_at":"2025-12-19 17:14:01","extension":"jpg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":78466,"visible":true,"origin":"","legend":"\u003cp\u003eANKRD1 regulates the phosphorylation of STAT3 in stomach adenocarcinoma cells.Modulation of ANKRD1 expression alters the phosphorylation level of STAT3 without affecting total STAT3 protein. (A) Western blot (WB) analysis of AGS cells transfected with siRNA targeting ANKRD1 (si-ANKRD1 #2), ANKRD1 overexpression plasmid (OE-ANKRD1 #2), or their corresponding negative controls (si-NC and NC). (B) WB analysis of MKN-45 cells subjected to the same transfection and treatment conditions. ** P \u0026lt; 0.05 vs. the respective control group (si-NC or NC).\u003c/p\u003e","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/25e19aaf851b06e30ec60785.jpg"},{"id":102415537,"identity":"97b7bd3b-d1e2-4db6-b477-0d76322bea5f","added_by":"auto","created_at":"2026-02-11 12:44:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2123914,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/e3f812b2-3cdc-418d-ad15-e180739790a6.pdf"},{"id":98628111,"identity":"bebab1ad-9174-45fd-af97-5a0e721b60df","added_by":"auto","created_at":"2025-12-19 17:10:59","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":19901,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/f5b9fb18edb09c2fff70c97b.docx"},{"id":98606416,"identity":"703d9392-9a8c-4c72-a4fa-6b23a848ee8c","added_by":"auto","created_at":"2025-12-19 13:40:09","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":8516962,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryWesternBlotfullmembranescan.docx","url":"https://assets-eu.researchsquare.com/files/rs-7782118/v1/35ec606832b099dd5a0c5a69.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"ANKRD1 Facilitates Tumor Progression and Immune Evasion in Stomach Adenocarcinoma through STAT3 Activation and Remodeling of the Tumor Microenvironment","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eGastric cancer (GC) remains a significant global health challenge, ranking fifth in incidence and fourth in mortality worldwide\u003csup\u003e1\u003c/sup\u003e. Although its incidence has declined in some regions, its marked geographic heterogeneity (with the highest burden in East Asia and Eastern Europe) reveals complex interactions between genetic, environmental, and socioeconomic factors. Histologically, the majority of cases are adenocarcinomas, which can be classified into intestinal and diffuse types according to the Lauren classification, each with distinct epidemiological, pathological, and molecular characteristics\u003csup\u003e2\u003c/sup\u003e. Stomach adenocarcinoma (STAD) is the predominant histological form and the primary focus of oncological research\u003csup\u003e3\u003c/sup\u003e. The development of STAD is a multi-step process, primarily triggered by chronic infection with Helicobacter pylori (H. pylori), which is associated with approximately 90% of non-cardia gastric cancers\u003csup\u003e4,5\u003c/sup\u003e. Other significant risk factors include dietary carcinogens (such as smoked and pickled foods), smoking, alcohol consumption, obesity, and Epstein-Barr virus (EBV) infection\u003csup\u003e6\u003c/sup\u003e. Importantly, genetic susceptibility also plays a critical role, with hereditary syndromes like hereditary diffuse gastric cancer (HDGC) caused by CDH1 gene mutations accounting for a small but significant proportion of patients\u003csup\u003e7\u003c/sup\u003e. Molecular subtyping studies, particularly those by The Cancer Genome Atlas (TCGA) network, have revolutionized our understanding of STAD heterogeneity by proposing a four-tier classification system: 1) EBV-positive tumors, characterized by PIK3CA mutations and PD-L1 amplification; 2) microsatellite instability-high (MSI-H) tumors, which exhibit high mutational burden and a more favorable prognosis; 3) genomically stable (GS) tumors, often of the diffuse subtype; and 4) chromosomally unstable (CIN) tumors, marked by aneuploidy and receptor tyrosine kinase amplifications\u003csup\u003e8,9\u003c/sup\u003e. This taxonomy provides a crucial framework for developing personalized treatment strategies\u003csup\u003e10,11\u003c/sup\u003e. For localized disease, curative treatment is based on surgical resection combined with perioperative or adjuvant chemotherapy and radiotherapy. However, a significant proportion of patients are diagnosed at advanced or metastatic stages, for whom systemic therapy is the mainstay of treatment\u003csup\u003e12,13\u003c/sup\u003e. Although the emergence of HER2-targeted therapies, ramucirumab targeting VEGFR2\u003csup\u003e14\u003c/sup\u003e, and immune checkpoint inhibitors for MSI-H/dMMR or PD-L1-positive tumors has improved outcomes, the overall prognosis for advanced STAD remains poor, with a 5-year survival rate below 10%. Intrinsic and acquired resistance, coupled with a robust tumor immunosuppressive microenvironment (TME), are major obstacles to achieving durable treatment responses\u003csup\u003e15,16\u003c/sup\u003e. Therefore, there is an urgent need to stratify patients and improve therapeutic efficacy by identifying novel and reliable prognostic biomarkers and therapeutic targets.\u003c/p\u003e \u003cp\u003eAnkyrin repeat domain 1 (ANKRD1), also known as Cardiac Ankyrin Repeat Protein (CARP), was initially identified as a striated muscle-specific structural protein but has now been redefined as a ubiquitously expressed, context-dependent signaling hub and transcriptional coregulator across diverse tissues\u003csup\u003e17\u003c/sup\u003e. Its expression is highly sensitive to various stressors, including biomechanical stress, oxidative damage, and inflammatory signals, a characteristic that underlies its complex and often paradoxical roles in human pathophysiology\u003csup\u003e18\u003c/sup\u003e. In the field of oncology, ANKRD1 exhibits a remarkable duality: it can function either as a tumor suppressor or an oncogene, depending on the cellular microenvironment\u003csup\u003e19\u003c/sup\u003e. In cancers such as breast cancer, it acts as a potent protector by inhibiting key pro-tumorigenic pathways such as NF-κB (via cytoplasmic sequestration of its subunits) and TGF-β, thereby suppressing inflammation, epithelial-mesenchymal transition (EMT), and metastasis\u003csup\u003e20,21\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe functional paradox of ANKRD1 also extends to various systemic diseases, where it consistently serves as a sentinel of cellular stress. In cardiovascular pathophysiology, its sharp upregulation following heart failure and myocardial infarction is part of a pathological reactivation of the fetal gene program; while initially compensatory, sustained ANKRD1 expression contributes to pathological cardiac hypertrophy and systolic dysfunction by translocating to the nucleus and corepressing contractile protein genes\u003csup\u003e22\u003c/sup\u003e. Similarly, in muscular dystrophies such as Duchenne muscular dystrophy (DMD), its persistent expression in regenerating fibers reflects failed repair attempts, where it acts as a mechanical stress sensor modulating the balance between muscle degeneration and regeneration\u003csup\u003e23\u003c/sup\u003e. Its pathophysiological influence is also evident in pulmonary arterial hypertension, where it drives excessive vascular smooth muscle cell proliferation, and in rheumatoid arthritis, where it may synergize with NF-κB to exacerbate joint inflammation\u003csup\u003e24,25\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThus, ANKRD1 can be regarded as a molecular \"Janus face,\" whose pleiotropic functions are mediated through complex network of pathways and cellular interactions. Elucidating the precise mechanisms that determine its dual nature is of paramount importance for exploiting its potential as a biomarker and novel therapeutic target across the spectrum of human diseases, from oncology to cardiology.\u003c/p\u003e \u003cp\u003eOur existing understanding of ANKRD1 expression, regulation, and functionality in STAD remains rudimentary. The objective of our investigation was to delve into the expression, prognostic implications, roles, and underlying mechanisms of ANKRD1 in STAD. Through a comprehensive multi-database analysis, we uncovered that ANKRD1 is markedly overexpressed in STAD, exhibiting a strong correlation with diminished overall survival rates, initial progression, and survival following progression in patients. While ANKRD1 expression showed a relationship with the infiltration of tumor immune cells, it did not correlate with the tumor mutation burden. Functional enrichment assessments indicated that ANKRD1 plays a pivotal role in various essential biological processes and signaling pathways. Experimental findings in vitro revealed that ANKRD1 facilitates the proliferation, migration, and invasion of stomach adenocarcinoma cells. Mechanistically, it appears that ANKRD1 may exert its oncogenic influence via the activation of the STAT3 signaling pathway.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data sources\u003c/h2\u003e \u003cp\u003eThe Cancer Genome Atlas (TCGA)\u003csup\u003e26\u003c/sup\u003e database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://portal.gdc.cancer.gov/\u003c/span\u003e\u003cspan address=\"https://portal.gdc.cancer.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) offers comprehensive molecular and clinical data for patients with Stomach adenocarcinoma (STAD), such as downloadable mRNA expression profiles, summaries of genetic mutations, and anonymized patient histories. In this study, we utilized a dataset containing transcriptomic information from 445 samples, which included 35 normal tissue specimens and 409 tumor tissue specimens. To identify differentially expressed genes between these normal and cancerous tissues, we performed an analysis using the Limma package (version 3.64.3) in R.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Analysis of Gene Expression Data via the UALCAN Database\u003c/h2\u003e \u003cp\u003eA comprehensive online analysis investigating differential gene expression between cancerous and non-cancerous tissues was conducted utilizing the UALCAN database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ualcan.path.uab.edu/\u003c/span\u003e\u003cspan address=\"http://ualcan.path.uab.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e27\u003c/sup\u003e, leveraging data sourced from The Cancer Genome Atlas (TCGA). This database facilitated the categorization of patients according to their gene expression profiles, enabling a comparative assessment of the survival outcomes among various expression cohorts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Analysis of the TIMER database\u003c/h2\u003e \u003cp\u003eTo investigate the differential expression of genes between tumor and precancerous tissues, we utilized TIMER (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://timer.cistrome.org/\u003c/span\u003e\u003cspan address=\"http://timer.cistrome.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e28\u003c/sup\u003e, a user-friendly web application designed for the analysis of large-scale cancer genomics data from The Cancer Genome Atlas (TCGA). This tool enabled a systematic comparison of gene expression profiles between tumor samples and matched precancerous samples from the same patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Analysis of the KM plotter database\u003c/h2\u003e \u003cp\u003eBased on the survival data of Stomach adenocarcinoma (STAD) patients, we conducted survival analysis using the Kaplan-Meier survival curve in the online database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.kmplot.com/analysis/\u003c/span\u003e\u003cspan address=\"https://www.kmplot.com/analysis/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e29\u003c/sup\u003e. Patients with ANKRD1 expression levels above the median were defined as the high expression group, while those below the median were defined as the low expression group. Survival curves were plotted, hazard ratios were calculated, and confidence intervals were estimated to evaluate the impact of ANKRD1 on the prognosis of STAD patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Profiling of the Immune Landscape via Bioinformatics Analysis\u003c/h2\u003e \u003cp\u003eThe composition of 22 distinct human immune cell types was determined through the LM22 gene signature\u003csup\u003e30\u003c/sup\u003e in conjunction with the CIBERSORTx algorithm\u003csup\u003e31\u003c/sup\u003e. By employing single-sample gene enrichment analysis (ssGSEA) \u003csup\u003e32\u003c/sup\u003ewithin the R package GSVA (version 2.2.0), we assessed the degree of infiltration of 28 immune cell types\u003csup\u003e33\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Landscape of somatic mutations in STAD\u003c/h2\u003e \u003cp\u003eTumor mutational burden (TMB) is defined as the quantity of somatic mutations per megabase of DNA (Mut/Mb), encompassing various genetic alterations such as insertions, deletions, single-base substitutions, and chromosomal translocations\u003csup\u003e34\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Functional enrichment analysis\u003c/h2\u003e \u003cp\u003eBased on ANKRD1 expression levels, TCGA patients were categorized into high-expression (top 50%) and low-expression (bottom 50%) groups. Differentially expressed genes (DEGs) between these two groups were identified using the \u0026ldquo;DESeq2\u0026rdquo;\u003csup\u003e35\u003c/sup\u003e, with a significance threshold set at adjusted P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log₂FC| \u0026gt; 1. To further explore the functional implications of ANKRD1 in Stomach Adenocarcinoma (STAD), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the \u0026ldquo;ClusterProfiler\u0026rdquo; \u003csup\u003e36\u003c/sup\u003eR package (v4.16.0), with terms considered significantly enriched at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eThe TCGA patients were divided into low (0\u0026ndash;50%) and high (50\u0026ndash;100%) groups based on ANKRD1 expression levels. The R package DESeq2 (version 1.48.1) was used to identify differentially expressed genes (DEGs) between the high-ANKRD1 and low-ANKRD1 expression groups. The threshold for significance was set to an adjusted P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log2 fold change| \u0026gt; 1. To further investigate the role of ANKRD1 in STAD, we used the ClusterProfiler R package (version 4.16.0) to identify enriched Gene Ontology (GO) terms and KEGG pathways. and GSEA(Gene Set Enrichment Analysis) with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Cell Culture and Transfection\u003c/h2\u003e \u003cp\u003eThe cell lines selected for this study include the human Stomach Adenocarcinoma cell lines AGS, SGC-7901, BGC-803, MKN45, and the normal gastric mucosal epithelial cell line NGEC, all of which were purchased from the Shanghai Cell Bank of the Chinese Academy of Sciences. The cells were cultured in RPMI-1640 medium (Gibco, Cat. No. C11875500BT) supplemented with 10% fetal bovine serum (FBS, Gibco, Cat. No. 10099-141) and 1% penicillin-streptomycin solution (Solarbio, Cat. No. P1400). They were maintained in a humidified incubator (Thermo Scientific, Model Forma 3111) at 37\u0026deg;C with 5% CO₂ and 95% humidity. The culture medium was replaced every 2\u0026ndash;3 days. When the cells reached 80%-90% confluence, they were passaged using 0.25% trypsin-EDTA (Gibco, Cat. No. 25200072), and cells in the logarithmic growth phase were used for subsequent experiments.\u003c/p\u003e \u003cp\u003eThe overexpression plasmid OE-ANKRD1 was constructed using the pcDNA3.1 (+) vector (Invitrogen, Cat. No. V79020), with the full-length CDS sequence of ANKRD1 (NM_001130086.2) inserted. The negative control plasmid (NC) was the empty pcDNA3.1 (+) vector. Three small interfering RNA (siRNA) sequences targeting the ANKRD1 gene (si-ANKRD1 #1, #2) were designed, with a non-targeting scramble RNA used as the negative control (si-NC). All oligonucleotides were synthesized by Shanghai GenePharma Co., Ltd.\u003c/p\u003e \u003cp\u003eAGS or MKN-45 cells in the logarithmic growth phase were seeded into 6-well plates at a density of 5\u0026times;10⁵ cells per well. Transfection was performed when cell confluence reached 60%-70%. The transfection was carried out using Lipofectamine 3000 reagent (Invitrogen, Cat. No. L3000015) according to the manufacturer's instructions. Briefly, 2 \u0026micro;g of plasmid (or 100 pmol siRNA) was mixed with 5 \u0026micro;L of P3000\u0026trade; reagent. Simultaneously, 5 \u0026micro;L of Lipofectamine 3000 was mixed with 250 \u0026micro;L of Opti-MEM reduced-serum medium (Gibco, Cat. No. 31985070). After incubating separately at room temperature for 5 minutes, the two mixtures were combined and incubated for an additional 20 minutes at room temperature. The resulting complex was then added to each well. After 6 hours, the medium was replaced with complete culture medium. Transfection efficiency was assessed by PCR and Western blot (WB) 48 to 72 hours post-transfection. Cells exhibiting the highest knockdown or overexpression efficiency were selected for subsequent experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9 PCR\u003c/h2\u003e \u003cp\u003eUsing a high-fidelity DNA polymerase (such as Phusion High-Fidelity DNA Polymerase), cDNA from stomach adenocarcinoma cancer cells was used as the template, and PCR amplification was performed with specific primers. Primer sequences were as follows: STAT3 forward primer (5'-AGGAGTCTAACAACGGCAGCCT-3') and STAT3 reverse primer (5'- GTGGTACACCTCAGTCTCGAAG-3'), ANKRD1 forward primer (5'-CCAGACGAAGACCTGAAGGA-3') and ANKRD1 reverse primer (5'-GGTGGTGATGCTGATGTTGA \u0026minus;\u0026thinsp;3'), GAPDH forward primer (5'-TGCAACCGGGAAGGAAATGA-3') and GAPDH reverse primer (5'-GCCCAATACGACCAAATCAGA-3'). The PCR reaction system included template DNA, primers, dNTPs, buffer, and DNA polymerase. The reaction conditions were set as follows: initial denaturation at 95\u0026deg;C for 3 minutes, followed by 30\u0026ndash;35 cycles (denaturation at 95\u0026deg;C for 30 seconds, annealing at a temperature set based on the primer Tm, and extension at 72\u0026deg;C for a duration determined by the product length), and a final extension at 72\u0026deg;C for 5\u0026ndash;10 minutes. The PCR products were verified for size by agarose gel electrophoresis, purified, and recovered for subsequent experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.10 CCK-8 Assay\u003c/h2\u003e \u003cp\u003eAfter transfection, AGS and MKN-45 cells were digested with trypsin and resuspended in complete medium. The cell concentration was adjusted to 5\u0026times;10\u0026sup3; cells per 100\u0026micro;L. The cell suspension was seeded into a 96-well plate (Corning, Cat. No. 3599) at 100\u0026micro;L per well. Each experimental group was set up with 5 replicate wells, and blank control wells (containing medium only) were also established. At 0, 1, 2, 3, and 4 days after seeding, 10\u0026micro;L of CCK-8 solution (Dojindo, Cat. No. CK04) was added to each well, followed by incubation at 37\u0026deg;C for 2 hours. The optical density (OD) at 450nm was then measured using a microplate reader (Bio-Tek, Model ELx808), with the blank control wells used for zero adjustment. A cell proliferation curve was plotted with the culture time as the x-axis and the average OD value as the y-axis. A higher OD value indicates stronger cell proliferative capacity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.11 Transwell Migration and Invasion Experiment\u003c/h2\u003e \u003cp\u003eThe experimental procedure for the invasion assay was essentially the same as that for the migration assay. Transfected cells were resuspended in serum-free medium and adjusted to a concentration of 1\u0026times;10⁵ cells in 200 \u0026micro;L. The lower chamber of the Transwell chamber (8 \u0026micro;m pore size, Corning, Cat# 3422) was filled with 600 \u0026micro;L of complete medium containing 20% FBS. The upper chamber was loaded with the 200 \u0026micro;L cell suspension. The chamber was incubated at 37\u0026deg;C for 24 hours. After incubation, the chamber was washed twice with PBS. Cells were fixed with 4% paraformaldehyde for 15 minutes and then stained with 0.1% crystal violet staining solution (Solarbio, Cat# G1063) for 10 minutes. Non-migrated cells on the upper surface of the membrane were gently removed with a cotton swab, followed by three washes with PBS.The membrane was imaged using an inverted microscope (Olympus, Model IX73). Five random fields of view (200\u0026times; magnification) were captured per membrane, and the number of cells that migrated to the lower surface was counted. Matrigel matrix (BD, Cat# 356234) was diluted 1:8 with serum-free medium. Then, 50 \u0026micro;L of the diluted Matrigel was added to the upper chamber of the Transwell chamber (8 \u0026micro;m pore size, Corning, Cat# 3422) and allowed to solidify at 37\u0026deg;C for 4 hours.The subsequent steps were identical to the migration assay, except the incubation time was extended to 48 hours.\u003c/p\u003e \u003cp\u003eCell migration and invasion abilities were quantified by the mean number of cells that traversed the membrane. All results are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.12 Cell Scratch Test\u003c/h2\u003e \u003cp\u003eAfter transfection, cells were seeded into a 6-well plate (Corning, Cat# 3516). When the cells reached a confluent monolayer (fusion degree\u0026thinsp;\u0026gt;\u0026thinsp;90%), a 200\u0026micro;L sterile pipette tip was used to gently create a scratch perpendicular to the bottom of the well. The cells were washed three times with PBS to remove detached cells. A medium containing 1% FBS was then added. The same location of the scratch was photographed at 0 hours and 24 hours using an inverted microscope (Olympus, Model IX73) at 100\u0026times; magnification. The scratch width was measured using ImageJ software. The cell migration rate was calculated as follows: Migration rate = (scratch width at 0 hours \u0026ndash; scratch width at 24 hours) / scratch width at 0 hours \u0026times; 100%. A higher migration rate indicates stronger cell migration ability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e2.13 Western Blot\u003c/h2\u003e \u003cp\u003eWestern blot was performed to detect the expression level of ANKRD1 protein in stomach adenocarcinoma cancer cells. Stomach Adenocarcinoma cells in the logarithmic growth phase were collected, and total protein was extracted by lysis followed by quantification using the BCA method. Equal amounts of protein samples were separated by SDS-PAGE and subsequently transferred to a PVDF membrane. After blocking, the membranes were incubated with anti-ANKRD1 primary antibody and the internal reference antibody β-actin at 4\u0026deg;C overnight. The next day, after incubation with HRP-labeled secondary antibody, protein bands were visualized using ECL chemiluminescence and recorded with an image acquisition system.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e2.14 Statistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were conducted using R software (version 4.5.0), GraphPad Prism 9, and ImageJ. Experimental data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD). Statistical comparisons were performed with GraphPad Prism 9, using independent samples t-test for comparisons between two groups and one-way ANOVA for multi-group comparisons. A P-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant..\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Elevated ANKRD1 Expression in Stomach Adenocarcinoma\u003c/h2\u003e \u003cp\u003eAnalysis of the TIMER database revealed markedly increased ANKRD1 expression across multiple cancer types, with Stomach Adenocarcinoma (STAD) showing particularly high levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). This finding was further validated using the UALCAN database, which also indicated significant upregulation of ANKRD1 in STAD samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.2 High Expression of ANKRD1 is Associated with Poor Prognosis in STAD\u003c/h2\u003e \u003cp\u003eThrough analysis of the Kaplan-Meier plotter database, it was observed that patients exhibiting high expression levels of the ANKRD1 gene demonstrated significantly inferior overall survival (OS) (HR\u0026thinsp;=\u0026thinsp;1.39, 95% CI: 1.17\u0026ndash;1.65 p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), first progression survival (FPS) (HR\u0026thinsp;=\u0026thinsp;1.46, 95%CI: 1.19\u0026ndash;1.78. p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), and post-progression survival (PPS) (HR\u0026thinsp;=\u0026thinsp;1.58, 95% CI: 1.26\u0026ndash;1.97 p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC) when compared to patients with low expression levels.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.3 ANKRD1 expression and the Immune Microenvironment of STAD\u003c/h2\u003e \u003cp\u003eTo evaluate the relationship between ANKRD1 expression and immune cell infiltration, correlation analyses were performed. A matrix representing the relative abundance of 22 distinct tumor-infiltrating cell types was generated for 409 samples using CIBERSORT software locally ( Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Patients with Stomach adenocarcinoma (STAD) were then stratified into high and low ANKRD1 expression groups based on the median expression level. Using CIBERSORTx analysis, we investigated the tumor immune microenvironment characteristics across these groups. The results indicated a statistically significant positive correlation (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between ANKRD1 expression and the frequencies of NK cells resting, Macrophages M0, and Macrophages M1. In contrast, ANKRD1 expression showed a statistically significant negative correlation (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) with the proportions of B cells memory, T cells CD4 memory resting, and NK cells activated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Additionally, based on single-sample Gene Set Enrichment Analysis (ssGSEA), ANKRD1 expression demonstrated positive correlations (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) with several immune cell types, including Gamma delta T cell, Immature dendritic cell, Natural killer T cell, Regulatory T cell, and T follicular helper cell (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.4 The Genomic Landscape of Somatic Mutations in Stomach Adenocarcinoma\u003c/h2\u003e \u003cp\u003eSomatic mutation data from Stomach Adenocarcinoma (STAD) patients were acquired from the TCGA database and visualized using the \"maftools\" R package (v2.24.0). The resulting mutation landscape illustrates distinct mutation types using color codes, with a corresponding annotation provided below. The ten most frequently mutated genes were identified as follows: TTN (53%), TP53 (46%), MUC16 (32%), ARID1A (27%), LRP1B (27%), SYNE1 (25%), CSMD3 (24%), FAT4 (21%), FLG (20%), and PCLO (19%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eFurther analysis revealed that missense mutations represent the predominant variant category, and single nucleotide polymorphisms (SNPs) were more abundant than insertions or deletions. Among single nucleotide variants (SNVs), C-to-T transitions were the most prevalent type observed in STAD samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Additionally, the total number of mutations per sample was quantified, and the distribution of mutation types is summarized in a box plot, where each category is color-coded for clarity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eNotably, no somatic mutations were detected in ANKRD1 (mutation frequency: 0%), suggesting that its role in STAD prognosis is unlikely to be mediated through tumor mutational burden (TMB).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Functional Enrichment Analysis of DEGs Related to ANKRD1\u003c/h2\u003e \u003cp\u003eIn this study, we evaluated the potential role of ANKRD1 in Stomach Adenocarcinoma (STAD) through differential expression analysis. Based on the median expression value of ANKRD1, STAD patients were divided into high and low expression groups, with 204 patients in each group. The R package \"DESeq2\" was then used to screen for differentially expressed genes (DEGs) associated with ANKRD1. A total of 1868 differentially expressed genes were identified, including 64 up-regulated and 1804 down-regulated genes. The results are shown in the volcano plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), with the threshold set at |logFC| \u0026gt; 1.0 and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eGO enrichment analysis indicated that DEGs associated with ANKRD1 are involved in several BPs, including intermediate filament organization. In addition, it is also implicated in CC and MF. The CCs included the GABA\u0026thinsp;\u0026minus;\u0026thinsp;A receptor complex, muscle myosin complex, chloride channel complex, acrosomal vesicle, and intermediate filament cytoskeleton. The MFs included cysteine\u0026thinsp;\u0026minus;\u0026thinsp;type endopeptidase inhibitor activity, neurotransmitter receptor activity, hormone activity, endopeptidase regulator and inhibitor activity, and peptidase inhibitor activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eIn addition, KEGG analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC) revealed the involvement of ANKRD1 in various pathways, such as Neuroactive ligand signaling, Cornified envelope formation, and Hormone signaling.\u003c/p\u003e \u003cp\u003eThe GSEA results indicate that ANKRD1 is involved in the following functions: Signaling by GPCR, Cytokine-mediated signaling pathway, Apoptotic signaling pathway, JAK-STAT signaling pathway, Signaling by interleukins, and Regulation of Wnt signaling pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD\u0026ndash;I).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e3.6 ANKRD1 is Significantly Highly Expressed in Stomach Adenocarcinoma Cells\u003c/h2\u003e \u003cp\u003eTo clarify the association between ANKRD1 and Stomach Adenocarcinoma, this study examined the expression levels of ANKRD1 protein in four Stomach Adenocarcinoma cell lines (SGC-901, BGC-803, AGS, MKN45) and the normal gastric mucosal epithelial cell line NGEC using Western blot (WB). The results (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) showed that compared to the normal cell line NGEC, ANKRD1 protein was significantly overexpressed in all tested Stomach Adenocarcinoma cell lines (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Among these, the expression of ANKRD1 was highest in AGS and MKN45 cells, suggesting that ANKRD1 may be involved in regulating the malignant phenotype of Stomach Adenocarcinoma cells. Based on these findings, subsequent experiments selected AGS and MKN45 cells as the research subjects to more precisely elucidate the function of ANKRD1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Verification of ANKRD1 Knockdown and Overexpression Efficiency\u003c/h2\u003e \u003cp\u003eWith the aim of elucidating the biological functions of ANKRD1, we initiated the study by creating isogenic cell models featuring either knockdown or overexpression of ANKRD1.In this study, si-ANKRD1 (small interfering RNA) and OE-ANKRD1 (overexpression plasmid) were transfected into AGS and MKN45 cells, and the efficiency of knockdown and overexpression was validated by Western blot (WB) and PCR. The results (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-B) showed that in AGS cells, compared with the si-NC group (negative control), the expression level of ANKRD1 was significantly reduced in the si-ANKRD1 group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Compared with the NC group (empty vector control), the ANKRD1 expression was significantly increased in the OE-ANKRD1 group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Similarly, in MKN45 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC-D), the expression of ANKRD1 in the si-ANKRD1 group decreased by approximately 60% compared to the si-NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while it increased approximately 1.9-fold in the OE-ANKRD1 group compared to the NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These results indicate the successful establishment of the ANKRD1 knockdown and overexpression cell models.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e3.8 ANKRD1 Effect on Stomach Adenocarcinoma Cell Proliferation CCK-8 Assay\u003c/h2\u003e \u003cp\u003eBased on the high expression of ANKRD1 in Stomach Adenocarcinoma cells, this study investigated its impact on the proliferative capacity of these cells using the CCK-8 assay. Cell viability (represented by OD450 values) was measured in AGS and MKN45 cells across the si-ANKRD1, si-NC, OE-ANKRD1, and NC groups at 0, 1, 2, 3, and 4 days of culture. The results showed that: In AGS cells (Fig.\u0026nbsp;8A-B), compared to the si-NC group, the OD values in the si-ANKRD1 group were significantly reduced starting from day 2 of culture (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Conversely, the OD values in the OE-ANKRD1 group were significantly higher than those in the NC group from day 2 onwards (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).In MKN45 cells (Fig.\u0026nbsp;8C-D), the trend was consistent with that in AGS cells: the OD value in the si-ANKRD1 group was lower than that in the si-NC group on day 4 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while the OD value in the OE-ANKRD1 group was higher than that in the NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These results indicate that ANKRD1 significantly promotes the proliferation of Stomach Adenocarcinoma cells, as knocking down ANKRD1 inhibited cell proliferation, while its overexpression enhanced it.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e3.9 ANKRD1 Effect on Stomach Adenocarcinoma Cell Migration Transwell Assay\u003c/h2\u003e \u003cp\u003eThe migratory and invasive capacities of cells are critical hallmarks of Stomach Adenocarcinoma metastasis. We further investigated the impact of ANKRD1 on these capabilities using Transwell assays.\u003c/p\u003e \u003cp\u003eMigration assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003eA-B): In AGS cells, the number of migrating cells in the si-ANKRD1 group was significantly lower than that in the si-NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas the OE-ANKRD1 group showed a significantly higher number of migrating cells compared to the NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In MKN45 cells, the number of migrating cells in the si-ANKRD1 group decreased by 64% compared to the si-NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while the OE-ANKRD1 group exhibited an increase compared to the NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eInvasion assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003eC-D): The results were consistent with the migration assay. In AGS cells, the number of invading cells was significantly reduced in the si-ANKRD1 group compared to the si-NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and significantly increased in the OE-ANKRD1 group compared to the NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Similarly, in MKN45 cells, the si-ANKRD1 group showed a significant reduction in invading cells compared to the si-NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the OE-ANKRD1 group showed a significant increase compared to the NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eThese findings suggest that ANKRD1 significantly enhances the migratory and invasive abilities of Stomach Adenocarcinoma cells.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.10 Investigating the Role of ANKRD1 in the Motility of Stomach Adenocarcinoma cells Using a Wound Healing Assay\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo further validate the impact of ANKRD1 on the migration ability of stomach adenocarcinoma cells, we assessed the scratch healing capacity of the cells through a wound healing assay. The results showed that in AGS cells, the 24-hour wound healing rate in the si-ANKRD1 group was significantly lower than that in the si-NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003eA), while the healing rate in the OE-ANKRD1 group was significantly higher than that in the NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003eC). In MKN45 cells, the healing rate in the si-ANKRD1 group decreased by 55% compared to the si-NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003eB), whereas the healing rate in the OE-ANKRD1 group increased compared to the NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003eD). These results are consistent with the Transwell migration assay, further confirming that ANKRD1 promotes the migration ability of stomach adenocarcinoma cells.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e3.11 ANKRD1 Affects the Functions of Stomach Adenocarcinoma cells by Modulating the STAT3 Signaling Pathway\u003c/h2\u003e \u003cp\u003eTo explore the potential molecular mechanism by which ANKRD1 exerts its cancer-promoting effects, we examined the protein levels of ANKRD1, total STAT3, and phosphorylated STAT3 (p-STAT3) in stomach adenocarcinoma cells following ANKRD1 knockdown or overexpression, using Western blot (WB). In AGS cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e11\u003c/span\u003eA), compared to the si-NC group, ANKRD1 expression was significantly reduced in the si-ANKRD1 #2 group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and the level of p-STAT3 was also significantly downregulated (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Conversely, in the OE-ANKRD1 #2 group, ANKRD1 expression was significantly increased compared to the NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), which was accompanied by a significant upregulation of p-STAT3 levels (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In MKN-45 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e11\u003c/span\u003eB), a consistent trend was observed: in the si-ANKRD1 #2 group, the expression of ANKRD1 and p-STAT3 decreased compared to the si-NC group (both P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while total STAT3 showed no significant change. In the OE-ANKRD1 #2 group, the expression of ANKRD1 and p-STAT3 was significantly increased compared to the NC group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while the level of total STAT3 remained unchanged. These results indicate that ANKRD1 expression is closely associated with the phosphorylation and activation of STAT3, suggesting that ANKRD1 promotes the malignant phenotype of stomach adenocarcinoma cells, at least in part, by activating the STAT3 signaling pathway. This provides important insights into the mechanism of ANKRD1 in the progression of stomach adenocarcinoma.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eStomach adenocarcinoma remains a significant global health challenge, with ongoing difficulties in understanding its pathogenesis and developing clinical treatments\u003csup\u003e37\u0026ndash;39\u003c/sup\u003e.Epidemiologically, stomach adenocarcinoma shows remarkable geographical variation, with a particularly high disease burden in East Asia and Eastern Europe. This distribution pattern reflects the complex interplay of genetic background, environmental exposures, and socioeconomic factors\u003csup\u003e40\u003c/sup\u003e.The development of stomach adenocarcinoma is a multi-stage process, with Helicobacter pylori infection being the primary causative factor, responsible for approximately 90% of non-cardia gastric cancers\u003csup\u003e41\u003c/sup\u003e.Notably, genetic susceptibility plays a crucial role in the pathogenesis of stomach adenocarcinoma\u003csup\u003e42,43\u003c/sup\u003e.For example, hereditary diffuse gastric cancer caused by CDH1 gene mutations, although accounting for a small proportion of cases, is clinically significant\u003csup\u003e44\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe most distinctive feature of its encoded protein is the presence of N-terminal ankyrin repeat (ANK) domains, which mediate extremely diverse protein-protein interactions\u003csup\u003e45\u003c/sup\u003e.ANKRD1 expression is strictly regulated in both time and space\u003csup\u003e46\u003c/sup\u003e.It is highly active during embryonic heart development, decreases in adulthood, but is rapidly and strongly re-induced in response to various stresses such as biomechanical stress, hypoxia, oxidative stress, hormonal stimulation, and tissue damage\u003csup\u003e47\u003c/sup\u003e.This suggests it plays a central role in maintaining internal homeostasis\u003csup\u003e48\u003c/sup\u003e.In terms of molecular function, ANKRD1 is considered a \"molecular scaffold\" with significantly context-dependent functionality. Firstly, as a transcriptional co-regulator, although it does not directly bind to DNA, it can interact with transcription factors such as p53 and YB-1 through its ANK domains, shuttling between the cytoplasm and nucleus, thereby significantly enhancing or suppressing the transcriptional activity of target genes. For instance, its interaction with p53 can amplify the DNA damage response\u003csup\u003e49\u003c/sup\u003e.Secondly, in skeletal and cardiac muscle, ANKRD1 localizes to the I-band of the sarcomere, interacting with the N2A region of titin and calpain, making it a key molecule in sensing and transmitting mechanical signals and maintaining sarcomere structural integrity\u003csup\u003e50\u003c/sup\u003e.Furthermore, ANKRD1 is involved in regulating apoptosis and autophagy\u003csup\u003e51\u003c/sup\u003e.In some contexts, it promotes cell survival by inhibiting apoptotic proteins or modulating autophagy flux, while in others, it may cooperate with p53 to promote apoptosis, reflecting its dual functionality\u003csup\u003e52\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGiven these multifaceted roles of ANKRD1 in cellular stress response and transcriptional regulation, we sought to investigate its specific function in the context of STAD. Our findings reveal that Stomach adenocarcinoma (STAD) remains a formidable global health challenge with a high incidence and poor prognosis, underscoring the urgent need to identify reliable prognostic biomarkers and therapeutic targets. In this study, we systematically demonstrated that ANKRD1 is significantly overexpressed in STAD tissues and cell lines. This elevated expression was strongly associated with unfavorable patient survival outcomes, including overall survival, first progression survival, and post-progression survival, establishing ANKRD1 as a potent prognostic indicator.\u003c/p\u003e \u003cp\u003eNotably, our analysis of the somatic mutation landscape revealed that ANKRD1 itself is not mutated in STAD, suggesting that its oncogenic role is driven by transcriptional upregulation rather than genetic alteration. To decipher the biological functions of ANKRD1, we performed functional enrichment analyses. Intriguingly, while GO and KEGG analyses highlighted enrichment in pathways like olfactory transduction, GSEA provided more direct oncogenic insights, linking ANKRD1 to crucial cancer-related pathways such as GPCR signaling and the JAK-STAT pathway.\u003c/p\u003e \u003cp\u003eA key aspect of tumor progression is the tumor immune microenvironment. Our study revealed that ANKRD1 expression correlates with a distinct immune cell infiltration pattern, characterized by suppressive features such as reduced activated NK cells and enriched pro-tumoral macrophages. This suggests that ANKRD1 may contribute to an immunosuppressive milieu, potentially explaining the poorer prognosis observed in patients with high ANKRD1 expression.\u003c/p\u003e \u003cp\u003eThe central finding of our study is the functional role of ANKRD1 as a bona fide oncogene. Through comprehensive in vitro experiments, we conclusively demonstrated that ANKRD1 knockdown significantly inhibited, while its overexpression enhanced, the proliferation, migration, and invasion capabilities of STAD cells. These results unequivocally position ANKRD1 as an active driver of STAD malignancy.\u003c/p\u003e \u003cp\u003eMechanistically, we bridged these phenotypic observations to a specific signaling pathway. Our data indicate that ANKRD1's oncogenic effects are likely mediated through the activation of the STAT3 signaling pathway, as evidenced by concomitant changes in STAT3 phosphorylation upon ANKRD1 manipulation. The STAT3 pathway is a well-known master regulator of oncogenesis, controlling cell survival, proliferation, and immune evasion. Therefore, we propose a plausible model wherein ANKRD1, positioned as an upstream regulator, enhances STAT3 phosphorylation, thereby orchestrating a transcriptional program that fuels the aggressive phenotype of STAD cells.\u003c/p\u003e \u003cp\u003eIn conclusion, our integrative multi-omics and experimental approach unveils ANKRD1 as a critical player in STAD pathogenesis and progression. It functions as a non-mutated oncogene that promotes malignant behaviors, likely by fostering an immunosuppressive microenvironment and activating the STAT3 signaling pathway. These findings nominate ANKRD1 as a promising prognostic biomarker and a potential therapeutic target for STAD.\u003c/p\u003e \u003cp\u003eOur study employed a comprehensive and multi-faceted methodological approach to investigate the role of ANKRD1 in STAD. A key strength lies in the integration of extensive bioinformatics analyses from multiple public databases (TCGA, UALCAN, TIMER, KM plotter) with robust in vitro experimental validation. The bioinformatics component not only provided a high-level, clinically correlated overview of ANKRD1's expression, prognostic value, and association with the immune microenvironment but also guided our subsequent functional experiments by highlighting potential mechanisms, such as the JAK-STAT pathway identified through GSEA. This hypothesis-generating approach ensured that our wet-lab experiments were targeted and biologically relevant. Furthermore, the in vitro models were rigorously established using both gain-of-function and loss-of-function strategies in two distinct STAD cell lines, which consistently corroborated the pro-tumorigenic functions of ANKRD1, thereby strengthening the reliability of our conclusions regarding its role in promoting proliferation, migration, and invasion.\u003c/p\u003e \u003cp\u003eHowever, several limitations of our study should be acknowledged. Firstly, while our in vitro findings are compelling, they lack validation in an in vivo setting. The use of animal models, such as xenograft mice, would be essential to confirm the tumor-promoting effects of ANKRD1 within a complex tumor microenvironment and to substantiate its potential as a therapeutic target. Secondly, although we identified a correlation between ANKRD1 expression and the phosphorylation of STAT3, the precise molecular mechanism by which ANKRD1 activates the STAT3 signaling pathway remains unclear. It is uncertain whether this interaction is direct or indirect, and further investigations, such as co-immunoprecipitation assays, are required to delineate the exact molecular intermediaries or binding partners involved. Lastly, the immune cell infiltration analysis, while insightful, was derived from computational algorithms based on transcriptomic data. These findings warrant confirmation through more direct methods like flow cytometry or immunohistochemistry on clinical tissue samples to accurately quantify the infiltrating immune cell populations.\u003c/p\u003e"},{"header":"5. CONCLUSIONS","content":"\u003cp\u003eIn summary, our study comprehensively demonstrates that ANKRD1 is significantly overexpressed in Stomach Adenocarcinoma (STAD) and is associated with poor patient prognosis. Through multi-database bioinformatics analysis and experimental validation, we established that high ANKRD1 expression promotes the proliferation, migration, and invasion of STAD cells. Mechanistically, ANKRD1 likely exerts its oncogenic functions by activating the STAT3 signaling pathway, as evidenced by correlated phosphorylation levels of STAT3 upon modulation of ANKRD1 expression. Furthermore, ANKRD1 expression is linked to specific immune cell infiltration patterns in the tumor microenvironment, although it does not contribute to tumor mutation burden .These findings highlight ANKRD1 as a potential prognostic biomarker and therapeutic target in Stomach Adenocarcinoma, providing new insights into the molecular mechanisms driving STAD progression.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicabl\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors hereby declare that there are no competing financial interests or personal relationships that could be construed as influencing the work presented in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLu Nie participated in research design, statistical analysis, and manuscript drafting; Nie Yu, Nie Lu, and Wang Ruiyang were responsible for PCR, WB, and all cell experiments.; Lu Nie and Ruiyang Wang contributed to study design and guided manuscript drafting. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe TCGA dataset for 445 samples was sourced from\u0026nbsp;https://portal.gdc.cancer.gov\u0026nbsp;(Project IDs: TCGA-STAD).\u003c/p\u003e\n\u003cp\u003eUALCAN database (http://ualcan.path.uab.edu/)\u003c/p\u003e\n\u003cp\u003eTIMER database (http://timer.cistrome.org/)\u003c/p\u003e\n\u003cp\u003eKM plotter database (https://www.kmplot.com/analysis/)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGoetze, O.T., Al-Batran, S.E., Chevallay, M. \u0026amp; M\u0026ouml;nig, S.P. Multimodal treatment in locally advanced gastric cancer. \u003cem\u003eUpdates Surg\u003c/em\u003e \u003cstrong\u003e70\u003c/strong\u003e, 173-179 (2018).\u003c/li\u003e\n\u003cli\u003eMa, J., Shen, H., Kapesa, L. \u0026amp; Zeng, S. Lauren classification and individualized chemotherapy in gastric cancer. \u003cem\u003eOncol Lett\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 2959-2964 (2016).\u003c/li\u003e\n\u003cli\u003eMilano, A.F. 20-Year Comparative Survival and Mortality of Cancer of the Stomach by Age, Sex, Race, Stage, Grade, Cohort Entry Time-Period, Disease Duration \u0026amp; Selected ICD-O-3 Oncologic Phenotypes: A Systematic Review of 157,258 Cases for Diagnosis Years 1973-2014: (SEER*Stat 8.3.4). \u003cem\u003eJ Insur Med\u003c/em\u003e \u003cstrong\u003e48\u003c/strong\u003e, 5-23 (2019).\u003c/li\u003e\n\u003cli\u003ePosselt, G., Crabtree, J.E. \u0026amp; Wessler, S. Proteolysis in Helicobacter pylori-Induced Gastric Cancer. \u003cem\u003eToxins (Basel)\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e(2017).\u003c/li\u003e\n\u003cli\u003eDebowski, A.W.\u003cem\u003e, et al.\u003c/em\u003e Helicobacter pylori gene silencing in vivo demonstrates urease is essential for chronic infection. \u003cem\u003ePLoS Pathog\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, e1006464 (2017).\u003c/li\u003e\n\u003cli\u003eLiu, J.\u003cem\u003e, et al.\u003c/em\u003e Prognostic value of the Epstein-Barr virus and tumor suppressor gene p53 gene in nasopharyngeal squamous cell carcinoma. \u003cem\u003eJ Cancer Res Ther\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 426-436 (2019).\u003c/li\u003e\n\u003cli\u003eC\u0026ocirc;me, P., Rochefort, P., De Crignis, L. \u0026amp; Dupr\u0026eacute;, A. [Prophylactic gastrectomy]. \u003cem\u003eBull Cancer\u003c/em\u003e \u003cstrong\u003e112\u003c/strong\u003e, 259-262 (2025).\u003c/li\u003e\n\u003cli\u003eWang, V.G., Kim, H. \u0026amp; Chuang, J.H. Whole-exome sequencing capture kit biases yield false negative mutation calls in TCGA cohorts. \u003cem\u003ePLoS One\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, e0204912 (2018).\u003c/li\u003e\n\u003cli\u003eUsui, G.\u003cem\u003e, et al.\u003c/em\u003e DNA Methylation and Genetic Aberrations in Gastric Cancer. \u003cem\u003eDigestion\u003c/em\u003e \u003cstrong\u003e102\u003c/strong\u003e, 25-32 (2021).\u003c/li\u003e\n\u003cli\u003eTorres, C. \u0026amp; Grippo, P.J. Pancreatic cancer subtypes: a roadmap for precision medicine. \u003cem\u003eAnn Med\u003c/em\u003e \u003cstrong\u003e50\u003c/strong\u003e, 277-287 (2018).\u003c/li\u003e\n\u003cli\u003eAziz, H.\u003cem\u003e, et al.\u003c/em\u003e Hepatic adenoma: evolution of a more individualized treatment approach. \u003cem\u003eJ Gastrointest Surg\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 975-982 (2024).\u003c/li\u003e\n\u003cli\u003eLeowattana, W., Leowattana, P. \u0026amp; Leowattana, T. Systemic treatment for advanced pancreatic cancer. \u003cem\u003eWorld J Gastrointest Oncol\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 1691-1705 (2023).\u003c/li\u003e\n\u003cli\u003eYu, J.\u003cem\u003e, et al.\u003c/em\u003e Unleashing the efficacy of immune checkpoint inhibitors for advanced hepatocellular carcinoma: factors, strategies, and ongoing trials. \u003cem\u003eFront Pharmacol\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 1261575 (2023).\u003c/li\u003e\n\u003cli\u003eFuchs, C.S.\u003cem\u003e, et al.\u003c/em\u003e Safety and Efficacy of Pembrolizumab Monotherapy in Patients With Previously Treated Advanced Gastric and Gastroesophageal Junction Cancer: Phase 2 Clinical KEYNOTE-059 Trial. \u003cem\u003eJAMA Oncol\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, e180013 (2018).\u003c/li\u003e\n\u003cli\u003eAkter, Z., Salamat, N., Ali, M.Y. \u0026amp; Zhang, L. The promise of targeting heme and mitochondrial respiration in normalizing tumor microenvironment and potentiating immunotherapy. \u003cem\u003eFront Oncol\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 1072739 (2022).\u003c/li\u003e\n\u003cli\u003eSaleh, R. \u0026amp; Elkord, E. Acquired resistance to cancer immunotherapy: Role of tumor-mediated immunosuppression. \u003cem\u003eSemin Cancer Biol\u003c/em\u003e \u003cstrong\u003e65\u003c/strong\u003e, 13-27 (2020).\u003c/li\u003e\n\u003cli\u003eShen, L.\u003cem\u003e, et al.\u003c/em\u003e Overexpression of ankyrin repeat domain 1 enhances cardiomyocyte apoptosis by promoting p53 activation and mitochondrial dysfunction in rodents. \u003cem\u003eClin Sci (Lond)\u003c/em\u003e \u003cstrong\u003e128\u003c/strong\u003e, 665-678 (2015).\u003c/li\u003e\n\u003cli\u003eWen, D.\u003cem\u003e, et al.\u003c/em\u003e The impact of METTL3 on bladder cancer through m(6)A modification: a potential therapeutic target and prognostic biomarker. \u003cem\u003eFront Oncol\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 1622117 (2025).\u003c/li\u003e\n\u003cli\u003eJim\u0026eacute;nez, A.P.\u003cem\u003e, et al.\u003c/em\u003e The tumor suppressor RASSF1A induces the YAP1 target gene ANKRD1 that is epigenetically inactivated in human cancers and inhibits tumor growth. \u003cem\u003eOncotarget\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 88437-88452 (2017).\u003c/li\u003e\n\u003cli\u003eYadegar, N.\u003cem\u003e, et al.\u003c/em\u003e The Prominent Role of miR-942 in Carcinogenesis of Tumors. \u003cem\u003eAdv Biomed Res\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 63 (2022).\u003c/li\u003e\n\u003cli\u003eIrshad, N.\u003cem\u003e, et al.\u003c/em\u003e Mangiferin: An effective agent against human malignancies. \u003cem\u003eFood Sci Nutr\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 7137-7157 (2024).\u003c/li\u003e\n\u003cli\u003eRadke, M.H.\u003cem\u003e, et al.\u003c/em\u003e Deleting Full Length Titin Versus the Titin M-Band Region Leads to Differential Mechanosignaling and Cardiac Phenotypes. \u003cem\u003eCirculation\u003c/em\u003e \u003cstrong\u003e139\u003c/strong\u003e, 1813-1827 (2019).\u003c/li\u003e\n\u003cli\u003eWallace, G.Q. \u0026amp; McNally, E.M. Mechanisms of muscle degeneration, regeneration, and repair in the muscular dystrophies. \u003cem\u003eAnnu Rev Physiol\u003c/em\u003e \u003cstrong\u003e71\u003c/strong\u003e, 37-57 (2009).\u003c/li\u003e\n\u003cli\u003eGriffiths, K.\u003cem\u003e, et al.\u003c/em\u003e Fluorinated perhexiline derivative attenuates vascular proliferation in pulmonary arterial hypertension smooth muscle cells. \u003cem\u003eVascul Pharmacol\u003c/em\u003e \u003cstrong\u003e156\u003c/strong\u003e, 107399 (2024).\u003c/li\u003e\n\u003cli\u003eWang, Q.\u003cem\u003e, et al.\u003c/em\u003e Targeting NF-kB signaling with polymeric hybrid micelles that co-deliver siRNA and dexamethasone for arthritis therapy. \u003cem\u003eBiomaterials\u003c/em\u003e \u003cstrong\u003e122\u003c/strong\u003e, 10-22 (2017).\u003c/li\u003e\n\u003cli\u003eShen, X.\u003cem\u003e, et al.\u003c/em\u003e ALDH2 as an immunological and prognostic biomarker: Insights from pan-cancer analysis. \u003cem\u003eMedicine (Baltimore)\u003c/em\u003e \u003cstrong\u003e103\u003c/strong\u003e, e37820 (2024).\u003c/li\u003e\n\u003cli\u003eHe, X.\u003cem\u003e, et al.\u003c/em\u003e Clinical significance for diagnosis and prognosis of POP1 and its potential role in breast cancer: a comprehensive analysis based on multiple databases. \u003cem\u003eAging (Albany NY)\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 6936-6956 (2022).\u003c/li\u003e\n\u003cli\u003eZhao, C.\u003cem\u003e, et al.\u003c/em\u003e NEIL3 may act as a potential prognostic biomarker for lung adenocarcinoma. \u003cem\u003eCancer Cell Int\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 228 (2021).\u003c/li\u003e\n\u003cli\u003eLi, X.\u003cem\u003e, et al.\u003c/em\u003e Regulation of P53 signaling in breast cancer by the E3 ubiquitin ligase RNF187. \u003cem\u003eCell Death Dis\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 149 (2022).\u003c/li\u003e\n\u003cli\u003eNewman, A.M.\u003cem\u003e, et al.\u003c/em\u003e Robust enumeration of cell subsets from tissue expression profiles. \u003cem\u003eNat Methods\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 453-457 (2015).\u003c/li\u003e\n\u003cli\u003eHan, S.\u003cem\u003e, et al.\u003c/em\u003e A Prognostic Signature Constructed by CTHRC1 and LRFN4 in Stomach Adenocarcinoma. \u003cem\u003eFront Genet\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 646818 (2021).\u003c/li\u003e\n\u003cli\u003eJin, H.\u003cem\u003e, et al.\u003c/em\u003e Integrative Genomic and Transcriptomic Analysis of Primary Malignant Gliomas Revealed Different Patterns Between Grades and Somatic Mutations Related to Glioblastoma Prognosis. \u003cem\u003eFront Mol Biosci\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 873042 (2022).\u003c/li\u003e\n\u003cli\u003eYan, G.\u003cem\u003e, et al.\u003c/em\u003e Potential Impact of ALKBH5 and YTHDF1 on Tumor Immunity in Colon Adenocarcinoma. \u003cem\u003eFront Oncol\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 670490 (2021).\u003c/li\u003e\n\u003cli\u003eCui, S.\u003cem\u003e, et al.\u003c/em\u003e The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients. \u003cem\u003eEur J Med Res\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 90 (2023).\u003c/li\u003e\n\u003cli\u003eJiang, Y.\u003cem\u003e, et al.\u003c/em\u003e Insights into potential mechanisms of asthma patients with COVID-19: A study based on the gene expression profiling of bronchoalveolar lavage fluid. \u003cem\u003eComput Biol Med\u003c/em\u003e \u003cstrong\u003e146\u003c/strong\u003e, 105601 (2022).\u003c/li\u003e\n\u003cli\u003eYang, Y.\u003cem\u003e, et al.\u003c/em\u003e Prognostic value of a hypoxia-related microRNA signature in patients with colorectal cancer. \u003cem\u003eAging (Albany NY)\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 35-52 (2020).\u003c/li\u003e\n\u003cli\u003eHuang, H.\u003cem\u003e, et al.\u003c/em\u003e An integrated analysis of DNA promoter methylation, microRNA regulation, and gene expression in gastric adenocarcinoma. \u003cem\u003eAnn Transl Med\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 1414 (2021).\u003c/li\u003e\n\u003cli\u003eAjani, J.A.\u003cem\u003e, et al.\u003c/em\u003e Gastric adenocarcinoma. \u003cem\u003eNat Rev Dis Primers\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, 17036 (2017).\u003c/li\u003e\n\u003cli\u003eSutton, P. \u0026amp; Boag, J.M. Status of vaccine research and development for Helicobacter pylori. \u003cem\u003eVaccine\u003c/em\u003e \u003cstrong\u003e37\u003c/strong\u003e, 7295-7299 (2019).\u003c/li\u003e\n\u003cli\u003eMarrie, R.A. Demographic, genetic, and environmental factors that modify disease course. \u003cem\u003eNeurol Clin\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, 323-341 (2011).\u003c/li\u003e\n\u003cli\u003eBornschein, J. \u0026amp; Malfertheiner, P. Gastric carcinogenesis. \u003cem\u003eLangenbecks Arch Surg\u003c/em\u003e \u003cstrong\u003e396\u003c/strong\u003e, 729-742 (2011).\u003c/li\u003e\n\u003cli\u003eChmiela, M., Karwowska, Z., Gonciarz, W., Allushi, B. \u0026amp; Stączek, P. Host pathogen interactions in Helicobacter pylori related gastric cancer. \u003cem\u003eWorld J Gastroenterol\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e, 1521-1540 (2017).\u003c/li\u003e\n\u003cli\u003eMocellin, S., Verdi, D., Pooley, K.A. \u0026amp; Nitti, D. Genetic variation and gastric cancer risk: a field synopsis and meta-analysis. \u003cem\u003eGut\u003c/em\u003e \u003cstrong\u003e64\u003c/strong\u003e, 1209-1219 (2015).\u003c/li\u003e\n\u003cli\u003eJakubowska, A.\u003cem\u003e, et al.\u003c/em\u003e CDH1 gene mutations do not contribute in hereditary diffuse gastric cancer in Poland. \u003cem\u003eFam Cancer\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 605-608 (2010).\u003c/li\u003e\n\u003cli\u003eTyrkalska, S.D.\u003cem\u003e, et al.\u003c/em\u003e Identification of an Evolutionarily Conserved Ankyrin Domain-Containing Protein, Caiap, Which Regulates Inflammasome-Dependent Resistance to Bacterial Infection. \u003cem\u003eFront Immunol\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 1375 (2017).\u003c/li\u003e\n\u003cli\u003eBadi, I.\u003cem\u003e, et al.\u003c/em\u003e Intracellular ANKRD1 protein levels are regulated by 26S proteasome-mediated degradation. \u003cem\u003eFEBS Lett\u003c/em\u003e \u003cstrong\u003e583\u003c/strong\u003e, 2486-2492 (2009).\u003c/li\u003e\n\u003cli\u003eClunie-O\u0026apos;Connor, C.\u003cem\u003e, et al.\u003c/em\u003e The Derivation of Primary Human Epicardium-Derived Cells. \u003cem\u003eCurr Protoc Stem Cell Biol\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 2c.5.1-2c.5.12 (2015).\u003c/li\u003e\n\u003cli\u003eCui, Y.\u003cem\u003e, et al.\u003c/em\u003e Molecular mechanisms by which casein glycomacropeptide maintains internal homeostasis in mice with experimental ulcerative colitis. \u003cem\u003ePLoS One\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, e0181075 (2017).\u003c/li\u003e\n\u003cli\u003eKciuk, M., Gielecińska, A., Mujwar, S., Mojzych, M. \u0026amp; Kontek, R. Cyclin-Dependent Kinase Synthetic Lethality Partners in DNA Damage Response. \u003cem\u003eInt J Mol Sci\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e(2022).\u003c/li\u003e\n\u003cli\u003eBelgrano, A.\u003cem\u003e, et al.\u003c/em\u003e Multi-tasking role of the mechanosensing protein Ankrd2 in the signaling network of striated muscle. \u003cem\u003ePLoS One\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, e25519 (2011).\u003c/li\u003e\n\u003cli\u003eXu, X.\u003cem\u003e, et al.\u003c/em\u003e Pan-cancer integrated analysis of ANKRD1 expression, prognostic value, and potential implications in cancer. \u003cem\u003eSci Rep\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 5268 (2024).\u003c/li\u003e\n\u003cli\u003ePellegrini, F.R.\u003cem\u003e, et al.\u003c/em\u003e Blockage of autophagosome-lysosome fusion through SNAP29 O-GlcNAcylation promotes apoptosis via ROS production. \u003cem\u003eAutophagy\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 2078-2093 (2023).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Stomach Adenocarcinoma, Tumor immune microenvironment, ANKRD1(Ankyrin Repeat Domain 1), Cell Invasion, Western blot, STAT3 signaling","lastPublishedDoi":"10.21203/rs.3.rs-7782118/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7782118/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e ANKRD1 is implicated in various cancers, but its role in Stomach adenocarcinoma (STAD) remains unclear.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e ANKRD1 expression and its prognostic value in STAD were analyzed using TIMER, UALCAN, GEPIA, and Kaplan-Meier plotter. Immune cell infiltration was evaluated via CIBERSORT and Single-sample Gene Set Enrichment Analysis (ssGSEA). Somatic mutations were analyzed from TCGA data. Functional enrichment analysis (GO, KEGG, GSEA(Gene Set Enrichment Analysis)) was performed on ANKRD1-associated genes. Subsequently, in vitro experiments were conducted. ANKRD1 protein levels were examined in STAD cell lines by Western blot. Stable knockdown and overexpression models were created. Functional assays (CCK-8, Transwell, wound healing) assessed proliferation, migration, and invasion. Western blot measured STAT3 pathway activity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e ANKRD1 was significantly overexpressed in STAD tissues and high expression correlated with poorer overall, first progression, and post-progression survival. ANKRD1 expression positively correlated with M0 macrophage and activated mast cell infiltration, and negatively with resting memory CD4+ T cells and naive B cells. Although ANKRD1 itself was not mutated, associated genes were enriched in pathways like Wnt signaling. In vitro, ANKRD1 knockdown inhibited cell proliferation, migration, and invasion, while its overexpression promoted these effects. ANKRD1 was found to modulate STAT3 phosphorylation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e ANKRD1 is overexpressed in STAD and predicts poor prognosis. It promotes tumor cell proliferation, migration, and invasion, likely through activating the STAT3 signaling pathway, and correlates with an altered immune microenvironment. ANKRD1 represents a potential prognostic biomarker and therapeutic target for STAD.\u003c/p\u003e","manuscriptTitle":"ANKRD1 Facilitates Tumor Progression and Immune Evasion in Stomach Adenocarcinoma through STAT3 Activation and Remodeling of the Tumor Microenvironment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-19 13:40:04","doi":"10.21203/rs.3.rs-7782118/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"90917606-b247-4998-b55f-b5c153be71ff","owner":[],"postedDate":"December 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-11T12:43:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-19 13:40:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7782118","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7782118","identity":"rs-7782118","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}