Overexpression of ACTL6A is associated with poor prognosis in gastric cancer, and nuclear level is an independent predictor

Introduction

Gastric cancer (GC) remains a major global health challenge, with the latest statistics indicating that in 2022, it ranked fifth worldwide in both incidence and mortality (1). Its clinical management is profoundly complicated by substantial molecular heterogeneity. This diversity is captured by classification systems such as the Lauren classification, which distinguishes diffuse and intestinal types, and The Cancer Genome Atlas (TCGA) molecular taxonomy, which includes subtypes like microsatellite instability (MSI) and Epstein-Barr virus (EBV) positive tumors (2,3). Although multimodal therapy for GC has made considerable progress, significant limitations such as prevalent late-stage diagnosis and heterogeneous treatment responses persist (4,5); therefore, the discovery and validation of novel molecular biomarkers represents a critical and urgent need to enable precise patient stratification and advance more effective individualized treatment strategies.

The actin-related protein (ARP) family, including important members such as ARP1, ARP2, ARP3, etc., is present in both the nucleus and cytoplasm and plays multiple roles in cellular processes ranging from cytoskeletal dynamics to nuclear regulation (6,7). Among them, ACTL6A (actin-like 6A, also known as ARP4) has a typical actin folding structure and is an indispensable core subunit of ATP-dependent chromatin remodeling complexes, especially the SWI/SNF complex (8). ACTL6A directly controls chromatin accessibility and the epigenetic landscape by promoting nucleosome localization. This core role enables ACTL6A to coordinate transcriptional programs that form the basis of cell migration, invasion and proliferation, making ACTL6A a key node in cell homeostasis (9,10). And its dysregulation is associated with tumorigenesis (11,12).

Accumulating evidence has firmly established ACTL6A as a potent oncoprotein, with its overexpression being a common feature across a wide spectrum of human malignancies (13). Its tumor-promoting functions are mediated through the dysregulation of multiple critical signaling pathways and cellular processes. Mechanistically, ACTL6A has been shown to co-activate transcriptional effectors like YAP/TAZ, thereby driving proliferation and invasion in cancers such as glioma and head and neck squamous cell carcinoma (14-16). It also regulates the AKT signaling pathway to affect glioma cell migration and sensitivity to temozolomide (17). In addition, ACTL6A also regulates the SOX2/Notch1 signaling pathway in acute promyelocytic leukemia (18) and hepatocellular carcinoma (19); stabilizing or enhancing MYC activity in hepatocellular carcinoma (20), triple-negative breast cancer (21), and cervical cancer (22). Importantly, ACTL6A is highly expressed in GC and promotes tumor cell survival by inhibiting ferroptosis through upregulation of the expression of the catalytic subunit of glutamate-cysteine ligase (GCLC) (23). Crucially, this multifaceted oncogenic activity is consistently linked to adverse clinical outcomes. A recent systematic review and meta-analysis robustly confirmed that high ACTL6A expression significantly correlates with worse overall survival (OS), advanced tumor stage, and higher histological grade across multiple cancer types, highlighting its emerging role as a conserved prognostic biomarker (24).

While only one study has reported an association between ACTL6A overexpression and progression in GC, it did not examine the correlation between its subcellular localization (nuclear vs. cytoplasmic) and the clinicopathological characteristics or survival outcomes of GC patients—a critical consideration, as differential localization often reflects distinct biological functions. This study aims to systematically elucidate the expression pattern and clinical relevance of ACTL6A in GC, with a focus on its subcellular distribution, to evaluate its potential as a novel prognostic indicator for patient stratification. We present this article in accordance with the REMARK reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0033/rc).

Methods

Tissue microarray (TMA) cohort

This retrospective cohort study utilized a TMA constructed from archived GC specimens. The TMA and associated de-identified clinicopathological data were provided by Shanghai Outdo Biotech Company Ltd. The study cohort consisted of 96 patients with gastric adenocarcinoma who underwent curative surgery between April and November 2009. Formalin-fixed, paraffin-embedded tissue samples were used to construct the TMA, which included 96 cores of tumor tissue and 84 cores of matched adjacent non-neoplastic mucosa. Patients who had received preoperative neoadjuvant therapy or presented with distant metastases at diagnosis were excluded. Comprehensive clinicopathological information was retrieved, including demographic characteristics, tumor histology, differentiation grade, TNM stage (AJCC 7th edition), depth of invasion, lymph node metastasis status, and tumor dimensions. All patients were followed until July 2015, yielding a median follow-up duration of 1.8 years (range, 0.2–6.2 years). OS was defined as the interval from the date of surgery to the date of death from any cause. Histopathological evaluation and classification were performed according to World Health Organization criteria. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Committee of Shanghai Outdo Biotech Company Ltd. (No. SHYJS-CP-1804014). Informed consent was waived in this retrospective study.

Immunohistochemistry (IHC) and score assessment

The expression of ACTL6A was evaluated in the GC TMA cohort described above using standard IHC. Formalin-fixed, paraffin-embedded tissue sections (4-µm thick) were dewaxed in xylene and rehydrated through a graded ethanol series. Antigen retrieval was performed by heating the sections in citrate buffer (pH 6.0). Endogenous peroxidase activity was quenched with 3% hydrogen peroxide. After blocking with normal serum, the sections were incubated overnight at 4 ℃ with a primary antibody against ACTL6A (1:100; 10341-1-AP; Proteintech, Wuhan, China). Following washes with PBS, the sections were incubated with an appropriate horseradish peroxidase-conjugated secondary antibody. Immunoreactivity was visualized using 3,3'-diaminobenzidine (DAB) as the chromogen, followed by counterstaining with hematoxylin. IHC staining was assessed by an experienced pathologist who was blinded to the clinical data.

For ACTL6A, which exhibited both cytoplasmic and nuclear localization, the staining intensity and the percentage of positive tumor cells were evaluated separately for each subcellular compartment. The staining intensity was scored as 0 (negative), 1+ (weak), 2+ (moderate), or 3+ (strong). The proportion of positive cells was scored as 0 (0%), 1 (1–25%), 2 (26–50%), 3 (51–75%), or 4 (76–100%). A final composite score was calculated by multiplying the intensity and percentage scores. Based on the distribution of composite scores within the cohort, cases were categorized into low- and high-expression groups using an optimal cut-off value (a composite score of <8 for cytoplasmic expression and <9 for nuclear expression).

Bioinformatic analysis

To systematically investigate the oncogenic role of ACTL6A, multi-platform bioinformatics analyses were conducted using established public databases. The pan-cancer expression profile of ACTL6A was first interrogated using the TIMER 3 database (http://timer.cistrome.org/), which analyzes RNA-seq data from TCGA. This analysis was validated and extended using the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) portal (http://gepia2.cancer-pku.cn/), which integrates expression data from both TCGA and the Genotype-Tissue Expression (GTEx) project. The UALCAN web resource (http://ualcan.path.uab.edu/) was employed for a dual purpose: firstly, to analyze the expression of other members within the ACTL6A protein family in GC, and secondly, to correlate ACTL6A transcript levels with clinicopathological variables such as tumor stage and histological grade in stomach adenocarcinoma (STAD). Genomic alterations, including mutations and copy number variations of ACTL6A in STAD, were explored via the cBioPortal for Cancer Genomics (https://www.cbioportal.org/) using the TCGA PanCancer Atlas dataset. Patient survival analysis was performed using the Kaplan-Meier plotter platform (https://kmplot.com/analysis/) to assess the prognostic value of ACTL6A mRNA expression. Furthermore, to infer the gene’s functional essentiality for cancer cell proliferation, gene dependency scores (Chronos scores) derived from genome-wide CRISPR-Cas9 knockout screens across hundreds of cancer cell lines were obtained from the DepMap portal (https://depmap.org/portal/). Finally, to explore the potential molecular context and interacting partners of ACTL6A, known and predicted protein-protein interaction (PPI) networks were constructed and analyzed using the STRING database (https://string-db.org/) and the GeneMANIA platform (https://genemania.org/).

Cell culture and transfection

Cells AGS, MKN28, MGC803 and SGC7901 were purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA). The GES-1 was purchased from Wuhan Sunncell Biotechnology Co., Ltd. (Wuhan, China). All cultured in RPMI 1640 (Cat. 11875500BT, Gibco, Thermo Fisher Scientific, Waltham, MA, USA) containing 1% penicillin-streptomycin (Cat. 15070063, Gibco) and 10% fetal bovine serum (FBS, Cat. 10099141C, Gibco), cultured in the incubator containing 5% carbon dioxide at 37 ℃. They were passaged once every 3 days.

The transfection experiment was carried out according to the manufacturer’s instructions. Lipofectamine™ 2000 Transfection Reagent (Cat. 11668019, Invitrogen, Thermo Fisher Scientific) was mixed with siRNA or plasmid DNA in Opti-MEM medium at ratios of 3:1 or 4:1, respectively. After incubation at room temperature for 10 minutes, the transfection mixture was added to the cells in the medium that had been replaced with fresh serum-free medium. The targeted siRNA sequences for ACTL6A are as follows:

siACTL6A-01: GCACATTAATGGAAATAGA
siACTL6A-02: GCTCCATTCTAGCCTCTTT
siACTL6A-03: GTATGCGGTTGAAATTGAT

Protein extraction and Western blot

Cells were lysed on ice using RIPA buffer (P0013, Beyotime, Shanghai, China) supplemented with protease and phosphatase inhibitors. Following a 20-minute incubation, lysates were centrifuged at 12,000 rpm for 15 min at 4 ℃. The supernatants were collected, mixed with 4× SDS-PAGE loading buffer (P0015L, Beyotime), and denatured by boiling at 100 ℃ for 10 min. Samples were stored at −20 ℃.

Proteins were separated by SDS-PAGE using 10% precast gels (LK304, Epizyme Biotech, Shanghai, China) and transferred to methanol-activated PVDF membranes. After blocking with 5% non-fat milk for 1 hour, membranes were incubated overnight at 4 ℃ with primary antibodies: anti-ACTL6A (1:1,000, 10341-1-AP, Proteintech) and anti-GAPDH (1:1,000, D16H11, Cell Signaling Technology, Danvers, MA, USA). Following TBST washes, membranes were incubated with an HRP-conjugated secondary antibody (1:1,000, 7074S, Cell Signaling Technology) for 1 hour at room temperature. Protein bands were visualized using an enhanced chemiluminescence (ECL) detection kit and imaged. All experiments were repeated at least three times.

Quantitative real-time PCR analysis

Total RNA was extracted using RNAsimple Total RNA Kit (DP419, TIANGEN Biotech, Beijing, China), reverse transcribed into cDNA using the PrimeScript™ RT Master Mix (RR036A, Takara Bio, Shiga, Japan). Then the qPCR system was prepared according to the instructions and amplified using StepOnePlus Real-Time PCR System (Thermo Fisher Scientific). b2m expression was used for standardization, and the relative mRNA expression was calculated according to the 2^-ΔΔCt method. The primer sequences used were as follows: b2m (beta-2-microglobulin): 5'-ACTCTCTCTTTCTGGCCTGG-3' and 5'-ATGTCGGATGGATGAAACCC-3'; ACTL6A: 5'-AGGACTGCCCCAAGGTGGAT-3' and 5'-AGGTGGGACCGCCTTGTTTG-3'.

Migration and invasion

Cell migration and invasion assays were performed using Transwell chambers (8.0 µm, 24-well plates; Cat. 3422, Corning, Corning, NY, USA). For the migration assay, 2 × 10⁴ cells resuspended in 100 µL serum-free RPMI 1640 medium were seeded into the upper chamber. The lower chamber was filled with RPMI 1640 medium containing 10% FBS as a chemoattractant. After 24 h of incubation at 37 ℃, non-migrated cells on the upper membrane surface were gently removed with cotton swabs. Migrated cells attached to the lower surface were fixed with 4% paraformaldehyde for 10 min, stained with 0.1% crystal violet for 15 min, and rinsed thoroughly with distilled water. Residual cells in the upper chamber were carefully wiped again with cotton. Migrated cells were visualized and photographed under an inverted microscope.

For the invasion assay, the upper chamber was pre-coated with 30 µL Matrigel (Cat. 354230, Corning) and allowed to polymerize for 30 min at 37 ℃. The subsequent procedure was consistent with the migration experiment.

Statistical analysis

Statistical analyses were conducted using IBM SPSS Statistics (Version 26.0, Armonk, NY, USA). Survival curves were plotted and the log-rank test was performed using GraphPad Prism (Version 9.0, GraphPad Software, San Diego, CA, USA). Categorical data were presented as frequencies and percentages. The associations between ACTL6A expression (categorized into high- and low-expression groups based on pre-defined cut-off scores) and clinicopathological characteristics were analyzed using the Chi-square test, with Fisher’s exact test applied where expected cell counts were less than 5. OS was analyzed using the Kaplan-Meier method, and differences between groups were compared with the log-rank test. Variables with a P value <0.05 in the univariate analysis were subsequently entered into a multivariate Cox proportional hazards regression model to identify independent prognostic factors. Hazard ratios (HRs) with 95% confidence intervals (CIs) were reported. All statistical tests were two-sided, and a P value of <0.05 was considered statistically significant.

Results

ACTL6A is upregulated in GC

To investigate the expression profile of ACTL6A across different cancers, we analyzed public database data. Analysis of TCGA data via the TIMER 3 database revealed that ACTL6A mRNA was significantly upregulated in 13 cancer types, including bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), and STAD, while it was downregulated in kidney chromophobe (KICH) and kidney renal clear cell carcinoma (KIRC) (Figure 1A). This finding was validated using the GEPIA2 database, which integrates TCGA and GTEx normal tissue data, confirming significantly higher ACTL6A expression in COAD, esophageal carcinoma (ESCA), head and neck squamous cell carcinoma (HNSC), lung squamous cell carcinoma (LUSC), rectum adenocarcinoma (READ), and STAD (Figure 1B). Examination of the ACTL6A family in STAD showed that most ARP members, including ACTL6A, were highly expressed (Figure 1C). Genomic alteration analysis from cBioPortal indicated that the ACTL6A gene was altered in 54% (238/440) of queried gastric adenocarcinoma patients/samples, with “mRNA High” being the predominant alteration type (Figure 1D). Further stratification across seven histological subtypes of gastric adenocarcinoma revealed varying frequencies of high ACTL6A mRNA expression: 62.5% in papillary, 59.49% in tubular, 50.62% in intestinal type, 47.88% in not otherwise specified (NOS) subtype, 31.82% in mucinous, 33.33% in diffuse type, and 30.77% in signet ring cell carcinomas (Figure 1E). In addition, at the cellular level, the ACTL6A protein was significantly more highly expressed in GC cells AGS, MKN28, MGC803, and SGC7901 than in normal gastric cell GES1 (Figure 1F). In summary, ACTL6A was aberrantly overexpressed in GC, suggesting it may have important clinical significance.

Figure 1 ACTL6A is overexpressed in GC. (A) Differential expression of ACTL6A mRNA across various cancer types from the TCGA project, analyzed via TIMER. Red bars represent tumor tissues, blue bars represent normal tissues. (B) Validation of ACTL6A mRNA expression in selected cancer types using GEPIA2 (TCGA tumor vs. TCGA normal + GTEx normal). (C) Expression levels of ACTL6A (ARP4) and related ARP family members in STAD (TCGA). (D) OncoPrint summarizing genomic alterations of the ACTL6A gene in STAD (TCGA, PanCancer Atlas; 440 samples/patients) from cBioPortal. (E) Bar graph depicting the proportion of various alteration types of the ACTL6A gene across seven histological subtypes of gastric adenocarcinoma. (F) The protein expression of ACTL6A in normal human gastric mucosal cell (GES1) and GC cell lines (AGS, MKN28, MGC803, SGC7901) was presented by Western blot. *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001. CNA, copy number alteration; GC, gastric cancer; GTEx, Genotype-Tissue Expression; mRNA, messenger RNA; STAD, stomach adenocarcinoma; TCGA, The Cancer Genome Atlas; TIMER, Tumor Immune Estimation Resource; TPM, transcripts per million.

Overexpression of ACTL6A and its association with clinicopathological characteristics in GC

Next, we employed a TMA for experimental verification to validate our bioinformatic findings. Quantitative analysis of the staining scores confirmed that ACTL6A expression was significantly higher in tumor tissues compared to the matched adjacent normal tissues, for both cytoplasmic (Figure 2A) and nuclear (Figure 2B) localization. Representative IHC images clearly demonstrate that ACTL6A protein was expressed in both the cytoplasm and nucleus of gastric cells, and both the staining intensity and positive rate were markedly greater in tumor samples than in adjacent normal tissues (Figure 2C,2D).

Figure 2 Overexpression of ACTL6A in GC tissues and its correlation with clinicopathological parameters. (A,B) Quantitative comparison of cytoplasmic (A) and nuclear (B) ACTL6A immunohistochemistry scores between gastric tumor tissues and adjacent normal tissues. Data are presented as mean ± SEM; the Wilcoxon test was used, and P<0.05 was considered statistically significant. (C,D) Representative immunohistochemical images of ACTL6A expression in adjacent normal gastric tissue and gastric tumor tissue (magnifications). Brown staining indicates positive signals for the ACTL6A antibody. (E-G) Analysis of ACTL6A mRNA expression in the TCGA-STAD cohort across different N stages (E), pathological grades (F), and pathological stages (G). Expression values are shown as log₂ (TPM + 1). **, P<0.01; ***, P<0.001; ****, P<0.0001. GC, gastric cancer; IHC, immunohistochemistry; mRNA, messenger RNA; SEM, standard error of the mean; STAD, stomach adenocarcinoma; TCGA, The Cancer Genome Atlas; TPM, transcripts per million.

Subsequently, we analyzed the correlation between ACTL6A expression and clinicopathological characteristics. As shown in Table 1, high cytoplasmic expression of ACTL6A was significantly associated with the N stage (P=0.02) in GC patients, but not with other parameters such as age, sex, or histological grade. Similarly, high nuclear expression of ACTL6A was also specifically correlated with advanced N stage (Table 2, P=0.03). The N stage, which reflects the extent of regional lymph node involvement, is a critical indicator of tumor aggressiveness and is strongly associated with poorer prognosis in GC.

Analysis of the TCGA-STAD database further corroborated these findings (Figure 2E-2G). ACTL6A mRNA expression was significantly elevated in tumor tissues across different N stages, pathological stages, and grades compared to normal gastric tissues. Notably, ACTL6A expression seems to increase progressively with disease severity. For instance, the median expression values in pathological stages I through IV were 47.347, 48.54, 51.199, and 52.646, respectively (Figure 2G). Collectively, our tissue-based validation and bioinformatic analysis consistently demonstrate that ACTL6A is significantly overexpressed in GC and its expression level is clinically associated with lymph node metastasis, suggesting its potential role in cancer progression.

High expression of ACTL6A is correlated with a poor prognosis in GC patients

To evaluate the prognostic significance of ACTL6A, survival analyses were performed based on our TMA cohort. Using the Kaplan-Meier method and log-rank test, we analyzed the correlation between ACTL6A expression and OS. For cytoplasmic ACTL6A expression, no significant association with patient survival was observed (P=0.77, Figure 3A). In contrast, high nuclear expression of ACTL6A was significantly associated with shorter OS (P<0.001, Figure 3B), indicating that nuclear-localized ACTL6A serves as a potent prognostic biomarker for unfavorable outcomes in GC.

Figure 3 Prognostic value of ACTL6A expression in GC. (A,B) Kaplan-Meier survival curves depicting OS of GC patients in our tissue microarray cohort, stratified by low vs. high expression of cytoplasmic (A) or nuclear (B) ACTL6A protein. P values were determined by the log-rank test. (C-E) Kaplan-Meier survival curves generated from the Kaplan-Meier Plotter database, showing the association between high ACTL6A expression and poor OS (C), FP (D), and PPS (E) in GC patients (probe 202666_s_at). FP, first progression; GC, gastric cancer; HR, hazard ratio; OS, overall survival; PPS, post-progression survival.

Kaplan-Meier Plotter database was used to validate these findings in an independent and larger cohort. Consistent with our tissue-based results, high expression of ACTL6A (probe 202666_s_at) was significantly correlated with worse OS (P<0.001, Figure 3C), first progression (FP, P<0.001, Figure 3D), and post-progression survival (PPS, P<0.001, Figure 3E) in GC patients. These consistent results from both our cohort and a public database robustly demonstrate that elevated ACTL6A expression, particularly within the nuclear compartment of gastric tumor tissues, is a reliable indicator of poor prognosis in GC.

Nuclear expression of ACTL6A is an independent adverse prognostic factor in GC

Publicly available CRISPR-Cas9 knockout screening data from the Achilles and SCORE projects were analyzed to assess the functional role of ACTL6A. The derived gene effect scores demonstrated that ACTL6A knockout consistently suppressed cell growth across multiple GC cell lines, as indicated by negative scores (Figure 4A). This suggests ACTL6A is essential for promoting GC cell proliferation and survival. Analysis of ACTL6A expression across molecular subtypes revealed its highest level in the epithelial-mesenchymal transition (EMT) subtype (Figure 4B), which correlates with the poorest clinical outcome among all subtypes (Figure 4C). This expression pattern further associates elevated ACTL6A with aggressive tumor behavior.

Figure 4 Functional impact of ACTL6A on GC cell growth and its expression across molecular subtypes. (A) Gene effect scores for ACTL6A derived from CRISPR-Cas9 knockout screens (Achilles and SCORE projects) in a panel of GC cell lines. Negative scores indicate that gene knockout inhibits cell growth/viability. (B) Expression levels of ACTL6A across different molecular subtypes of GC, including EMT, MSI, MSS, MSS/TP53⁻, and MSS/TP53⁺. (C) Overall survival curves for patients belonging to different molecular subtypes of GC. EMT, epithelial-mesenchymal transition; GC, gastric cancer; MSI, microsatellite instability; MSS, microsatellite stable.

Multivariate Cox regression analysis was performed to determine the independent prognostic value of ACTL6A in nucleus, incorporating clinicopathological variables from our TMA cohort (Table 3). While cytoplasmic ACTL6A expression was not significant in univariate analysis, high nuclear expression of ACTL6A emerged as an independent predictor of poor OS (HR =3.052, 95% CI: 1.643–5.670, P<0.001), confirming its role as a significant risk factor beyond traditional parameters.

Knockdown of ACTL6A suppresses the migration and invasion of GC cells

Given the significant correlation between nuclear ACTL6A expression and advanced N stage (Table 2), we sought to determine whether ACTL6A functionally regulates the migration and invasion of GC cells. We first validated the knockdown efficiency of three independent siRNAs targeting ACTL6A in four GC cell lines (AGS, MKN28, MGC803, and SGC7901). qPCR analysis revealed that siACTL6A-01 and siACTL6A-03 reduced ACTL6A mRNA levels by over 90% across all cell lines, whereas siACTL6A-02 achieved approximately 50% knockdown (Figure 5A). Consistently, Western blot analysis confirmed corresponding reductions in ACTL6A protein expression (Figure 5B).

Figure 5 ACTL6A knockdown inhibits gastric cancer cell migration and invasion. (A) qPCR analysis of ACTL6A mRNA expression in AGS, MKN28, MGC803, and SGC7901 cells following transfection with control siRNA (NC) or three independent ACTL6A-targeting siRNAs (siACTL6A-01, -02, -03). (B) Western blot analysis of ACTL6A protein levels under the same knockdown conditions as in (A). (C,D) Representative images (200×, 0.1% crystal violet) of Transwell assays showing the migration (C) and invasion (D) capabilities of AGS and MKN28 cells after ACTL6A knockdown. (E,F) Representative images (200×, 0.1% crystal violet) showing the migration (E) and invasion (F) capabilities of GES1 cell following overexpression of ACTL6A (ACTL6A OE) or empty vector control (NC). Data are presented as the mean ± SD of three independent experiments. ****, P<0.0001. mRNA, messenger RNA; NC, negative control; OE, overexpression; SD, standard deviation; siRNA, small interfering RNA.

We then performed Transwell assays using AGS and MKN28 cells following ACTL6A knockdown. Compared with control groups, knockdown of ACTL6A in GC cells significantly reduced the number of migrated (Figure 5C) and invaded (Figure 5D) cells. Conversely, ectopic overexpression (OE) of ACTL6A in normal gastric epithelial GES1 cells markedly enhanced their migratory (Figure 5E) and invasive (Figure 5F) capacities. The above results indicate that ACTL6A affects the migration and invasion of GC cells, supporting its role in promoting the progression of GC.

Protein interaction networks and functional enrichment of ACTL6A

To elucidate the potential molecular mechanisms of ACTL6A in GC, we constructed PPI networks using STRING and GeneMANIA. STRING analysis indicated that ACTL6A is functionally linked to SWI/SNF complex components (ARID1A, SMARCA2, etc.). GeneMANIA identified additional partners from histone acetyltransferase complexes (TRRAP, KAT5, etc.) (Figure 6A,6B). These findings suggest that ACTL6A may be involved in two epigenetic regulatory systems, offering a potential link to its role in GC progression.

Figure 6 Bioinformatic analysis of ACTL6A interaction networks. (A) Protein-protein interaction network of ACTL6A generated using the STRING database. Each node represents a protein, with a schematic of its structural domain shown within the circle. Lines connecting the nodes represent interactions. (B) Extended functional interaction network of ACTL6A generated using the GeneMANIA platform. Lines of different colors represent different types of functional associations. The distinct colors of the nodes indicate their different functional roles within the network.

Discussion

Our study systematically demonstrates that ACTL6A is a significant oncoprotein in GC, which is consistent with the results of existing research (23). We confirmed its significant overexpression at both transcriptional and protein levels in GC tissues compared to adjacent normal mucosa. Crucially, through meticulous subcellular localization analysis, we identified that high nuclear, but not cytoplasmic, ACTL6A protein expression serves as a powerful and independent prognosticator for worse OS (HR =3.052), strongly associating with advanced lymph node metastasis (N stage). Knocking down ACTL6A in GC cells resulted in reduced cell migration and invasion, thereby validating the hypothesis that ACTL6A promotes GC metastasis. Functional enrichment analysis positioned nuclear ACTL6A within the core of chromatin regulatory machineries, specifically the SWI/SNF remodeling and histone acetyltransferase complexes, providing a mechanistic scaffold for its role. Collectively, our work elevates ACTL6A from a general overexpressed gene to a compartmentalized, nuclear-localized driver and biomarker in GC.

The strength of this work lies in its multi-level validation strategy, bridging in-silico data from large-scale databases (TCGA, DepMap) with protein-level evidence from our own clinically annotated cohort. A pivotal methodological strength was the separate scoring and analysis of cytoplasmic and nuclear staining, which directly yielded the critical finding of nuclear specificity. However, several limitations of this study should be acknowledged. Firstly, although the validation cohort of 96 cases yielded preliminary results, its relatively small sample size may limit the robustness of the prognostic model and the generalizability of our findings. Larger-scale, multi-center prospective studies are therefore essential to validate the compartment-specific prognostic value of nuclear ACTL6A before any clinical consideration. Secondly, preliminary immunofluorescence staining of GES-1 and GC cell lines (AGS, MKN28, MGC-803, SGC-7901) showed weak nuclear and diffuse cytoplasmic ACTL6A signals in GES-1 cells, but marked nuclear enrichment in cancer cells—confirming enhanced nuclear localization as a shared feature of gastric malignancy (Figure S1). However, ACTL6A subcellular localization requires further validation and replication at the cellular level to enhance the reliability of tissue-level findings. Moreover, while we inferred the potential role of ACTL6A in chromatin remodeling through bioinformatic analysis, the precise molecular mechanism by which nuclear ACTL6A drives metastasis and poor prognosis in GC remains to be elucidated. Addressing these limitations in future studies will be critical for translating our findings into clinically actionable insights.

The oncogenic role of ACTL6A in GC has only recently begun to be elucidated, with only one report to date. The study by Yang et al. (2023) in Nature Communications first established a concrete mechanistic link, demonstrating that ACTL6A, as a subunit of the SWI/SNF chromatin remodeling complex, functions as a co-transcription factor with NRF2 to upregulate GCLC expression (23). This axis promotes glutathione synthesis and confers resistance to ferroptosis, thereby driving GC progression. While this seminal work provided a crucial molecular mechanism centered on redox homeostasis, it did not establish the independent prognostic value of ACTL6A protein at the subcellular level in clinical cohorts. Our study builds upon established evidence of ACTL6A overexpression in GC and advances the investigation to the functionally relevant subcellular localization level. While existing literature has predominantly focused on ACTL6A expression levels (total protein or mRNA), our work specifically demonstrates ACTL6A nuclear expression as an independent prognostic biomarker in GC.

When viewed in the broader context of oncological research, the prognostic significance of ACTL6A overexpression is not unique to GC but aligns with a consistent pattern observed across diverse malignancies. For instance, in colon cancer (25) and triple-negative breast cancer (26), it promotes cancer progression by regulating invasion, metastasis, and EMT. The correlation between high ACTL6A expression and poor prognosis has been verified in tumors such as squamous cell carcinoma (14) and oral squamous cell carcinoma (27,28). Furthermore, other studies have revealed that in uveal melanoma (29) and non-small cell lung cancer (NSCLC) (11), ACTL6A promotes cancer progression by influencing the immune environment. This cross-cancer consistency underscores ACTL6A’s fundamental role in driving tumor dissemination (28). Therefore, our study positions GC within this established paradigm while adding the novel and critical layer of nuclear-specific prognostic stratification, a refinement not commonly reported in studies of other cancers.

The implications of this study are twofold. Clinically, standardized assessment of the nuclear site ACTL6A based on IHC is expected to develop into a practical prognostic biomarker. Scientifically, the important role of ACTL6A for cell viability and its nuclear-specific function underscores its biological significance in GC progression. Although these findings are encouraging, the retrospective design and relatively small sample size necessitate validation in large-scale prospective studies, as well as further investigation into the molecular mechanisms by which nuclear ACTL6A drives GC progression. Given its role in other cancers, such as coordinating with oncogenic transcription factors (like p63, YAP) and regulating key pathways (such as SOX2/Notch1 signaling) (14,15,19), determining whether a similar network functions in GC may offer new treatment opportunities for cancer patients.

Conclusions

In summary, this study demonstrates that ACTL6A is a significant oncoprotein in GC. Crucially, our findings reveal that the prognostic power of ACTL6A is dictated by its subcellular localization. Specifically, high nuclear ACTL6A expression, but not its cytoplasmic counterpart, serves as a strong and independent prognostic biomarker, significantly associated with advanced lymph node metastasis and poor OS. These results position nuclear ACTL6A as a novel, compartment-specific biomarker for risk stratification.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0033/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0033/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0033/prf

Funding: This work was supported by National Natural Science Foundation of China (No. 82002974), Shenzhen Hospital of Southern Medical University, Research Promotion Funds for the Key Discipline Construction Program (No. ZDXKKYTS006), Wu Jieping Medical Foundation (No. 320-6750-2020.06.63), and Basic Research Fund of Shenzhen Science and Technology Innovation Commission (No. JCYJ20220530154003007).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0033/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Committee of Shanghai Outdo Biotech Company Ltd. (No. SHYJS-CP-1804014). Informed consent was waived in this retrospective study.

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

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