Suppressive role of SCN4B in the epithelial‑mesenchymal transition of lung adenocarcinoma

Introduction

Lung cancer, a malignancy that poses a major threat to human health, is generally classified into two main subtypes: i) Small cell lung cancer; and ii) non-small cell lung cancer (NSCLC) (1), with the latter accounting for ~85% of all cases (2). Although notable progress has been achieved in the treatment of lung cancer, through advances in surgical techniques, refinement of chemoradiotherapy regimens, and the introduction of targeted and immune-based therapies (3), overall survival (OS) remains unsatisfactory, particularly among patients with advanced disease (4). Metastasis is a principal cause of therapeutic failure and mortality in lung cancer (5). Epithelial-mesenchymal transition (EMT) refers to a process in which epithelial cells, under specific physiological or pathological conditions, lose their epithelial characteristics and acquire the phenotype and functional properties of mesenchymal cells (6). During EMT, the expression of epithelial markers, such as E-cadherin, is markedly reduced, whereas mesenchymal markers, including N-cadherin and Vimentin, are upregulated, thereby enhancing cellular migratory and invasive capacities (7,8). Increasing evidence indicates that EMT serves a pivotal role in the initiation, progression, invasion and metastasis of lung cancer. Multiple signaling pathways have been implicated in regulating EMT in lung cancer cells, including the TGF-β pathway (9), Notch pathway (10) and Wnt pathway (11,12). EMT-related transcription factors, such as Snail (13), Twist (14) and zinc-finger E homeobox-binding family members (15), are frequently upregulated in lung cancer tissues (16). These factors directly repress E-cadherin expression while inducing the expression of mesenchymal markers such as N-cadherin and Vimentin, thereby driving EMT (17). Despite advances in the understanding of the relationship between lung cancer and EMT, numerous mechanistic questions remain to be addressed.

The sodium channel β4 subunit (SCN4B) gene encodes a crucial subunit of the voltage-gated sodium channel, serving a key role in cellular electrophysiological functions (18,19). Previous studies have primarily concentrated on its involvement in the nervous system, particularly in relation to neuromuscular disorders (20,21). However, emerging evidence indicates that SCN4B may also contribute to pathologies beyond the nervous system, notably in cancer, a major threat to human health. For instance, alterations in SCN4B expression have been implicated in modulating tumor cell proliferation and metastasis in colorectal cancer (22). In lung cancer, SCN4B expression levels have been reported to be closely associated with tumor aggressiveness and patient prognosis, underscoring its potential influence on disease progression (23). In summary, SCN4B was proposed to act as a tumor suppressor by restraining the excessive activation of tumor cell migration.

In the present study, the differential expression of SCN4B in lung adenocarcinoma (LUAD) was analyzed and its prognostic significance was evaluated. Based on these findings, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on SCN4B-associated differentially expressed genes, alongside immune infiltration profiling. To further elucidate the role of SCN4B in suppressing LUAD cell migration and invasion, SCN4B-overexpressing cell lines were established. The effect of SCN4B on tumor progression was assessed by examining changes in cell viability, migration and invasion. Finally, the effect of SCN4B on the EMT process was investigated through the evaluation of EMT-related marker protein expression levels. Based on previous reports (24,25), we hypothesized that SCN4B may be involved in EMT regulation in LUAD, and the working hypothesis is summarized in Fig. 1.

Figure 1. Proposed mechanism of SCN4B in the regulation of EMT in lung adenocarcinoma. All activating signaling pathways are indicated by blue solid arrows, while all inhibitory pathways are represented by red T-shaped termination lines. SCN4B, sodium channel β4 subunit; EMT, epithelial-mesenchymal transition; CDH2, N-cadherin; HDAC, histone deacetylase.

Materials and methods

Data acquisition and preprocessing

Transcriptomic data for The Cancer Genome Atlas (TCGA)-LUAD cohort were obtained from TCGA portal (https://portal.gdc.cancer.gov) using the Spliced Transcripts Alignment to a Reference processing pipeline. Expression profiles were extracted in the transcripts per million format, and paired tumor-adjacent and tumor tissue samples were identified based on matched patient identifiers. In total, 598 samples were included in the analysis, comprising 59 normal lung tissues and 539 LUAD specimens.

Differential expression analysis of SCN4B

Bioinformatics and statistical analyses were performed in R (v4.5.2; R Core Team; http://www.R-project.org/) (26). The expression levels of SCN4B in LUAD and adjacent normal tissues were compared using the ‘limma’ R package (v3.66.0; http://bioconductor.org/packages/release/bioc/html/limma.html). The log2 fold change (log2FC) and adjusted P-value (adj. P.Val) were calculated for all genes, and those with |log2FC|>1 and adj. P.Val <0.05 were considered significantly differentially expressed. Receiver operating characteristic (ROC) curve analysis was performed using the ‘pROC’ package (v1.19.0.1; http://cran.r-project.org/package=pROC), and the results were visualized with ‘ggplot2’ (v4.0.1; http://cran.r-project.org/package=ggplot2) (27).

Visualization of gene expression and correlation analysis

Boxplots were generated using the ‘ggplot2’ package to display SCN4B expression differences between tumor and normal lung tissues. Volcano plots were generated using the ‘ggplot2’ package to visualize SCN4B-associated differentially expressed genes between the SCN4B high- and low-expression groups within the TCGA-LUAD tumor cohort. Correlation heatmaps illustrating the relationships between SCN4B and selected lung cancer-associated marker genes were created to facilitate visualization of co-expression patterns (28).

GO and KEGG functional enrichment analysis

SCN4B-associated differentially expressed genes identified between the SCN4B high- and low-expression groups within the TCGA-LUAD tumor cohort (|log2FC|>1; adj. P.Val <0.05) were selected for enrichment analysis. GO annotation and KEGG pathway enrichment analysis were performed using the R package ‘clusterProfiler’ (v4.4.4; http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html) package (29), running under R (v4.5.2; R Core Team; http://www.R-project.org/). Bubble plots generated with the R package ‘ggplot2’ were used to present the enrichment results.

Prognostic evaluation

OS data for patients with LUAD were obtained from the Gene Expression Profiling Interactive Analysis 2 platform (v2.0; http://gepia2.cancer-pku.cn/#index), while disease-specific survival (DSS) and progression-free interval (PFI) information were sourced from TCGA. Kaplan-Meier survival analysis was conducted, and statistical differences were assessed using the log-rank test. Corresponding P-values were calculated and displayed on the survival plots (30).

Expression validation and prognostic analysis in the Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/) dataset

The present study used the GSE31210 (31) (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31210; Affymetrix GPL570; Thermo Fisher Scientific, Inc.) series matrix (robust multi-array average log2-transformed). SCN4B was mapped to probe 236359_at. Samples were grouped as tumor vs. normal (unpaired), and group differences were tested using Welch's t-test; genome-wide analysis employed the linear modeling framework implemented in the limma R/Bioconductor package (version 4.4.4; http://bioconductor.org/packages/release/bioc/html/limma.html) with Benjamini-Hochberg false discovery rate correction.

Prognostic analysis

In GSE31210 (GPL570), OS was used as the endpoint. SCN4B expression was extracted using probe 236359_at and patients were dichotomized at the cohort median to generate Kaplan-Meier curves and the number at risk table. Groups were compared using the two-sided log-rank test.

Clinical association analysis

Clinical information for patients with LUAD, including age, sex, tumor stage and metastatic status, was retrieved from TCGA. The association between SCN4B expression and clinical characteristics (such as tumor stage and metastasis) was evaluated using either the χ2 test or Fisher's exact test (32) (Table I). Bar plots illustrating the relationship between SCN4B expression and clinical features were generated with the ‘ggplot2’ package (33).

Table I. Baseline clinical characteristics of patients with lung adenocarcinoma with high and low SCN4B expression.

Table I.

Baseline clinical characteristics of patients with lung adenocarcinoma with high and low SCN4B expression.

Characteristics	Low SCN4B expression, n (%) (n=269)	High SCN4B expression, n (%) (n=270)	P-value
Pathologic T stage			0.003
T1	69 (12.9)	107 (20.0)
T2	166 (31.0)	126 (23.5)
T3	24 (4.5)	25 (4.7)
T4	9 (1.7)	10 (1.9)
Pathologic N stage			0.658
N0	172 (32.9)	178 (34.0)
N1	54 (10.3)	43 (8.2)
N2	40 (7.6)	34 (6.5)
N3	1 (0.2)	1 (0.2)
Pathologic M stage			0.734
M0	188 (48.2)	177 (45.4)
M1	12 (3.1)	13 (3.3)
Pathologic stage			0.164
Stage I	137 (25.8)	159 (29.9)
Stage II	72 (13.6)	53 (10.0)
Stage III	45 (8.5)	39 (7.3)
Stage IV	12 (2.3)	14 (2.6)
Sex			<0.001
Female	124 (23.0)	165 (30.6)
Male	145 (26.9)	105 (19.5)
Age, years			0.005
≤65	144 (27.7)	113 (21.7)
>65	115 (22.1)	148 (28.5)
Smoker			0.005
No	27 (5.1)	50 (9.5)
Yes	235 (44.8)	213 (40.6)
Anatomic neoplasm subdivision			0.628
Left	100 (19.1)	107 (20.4)
Right	160 (30.5)	157 (30.0)

[i] Due to missing or unknown information for certain clinicopathological variables in The Cancer Genome Atlas clinical annotations, the totals for some categories may not sum to the overall cohort size. Percentages were calculated based on the available data for each variable. P-values were calculated using the Pearson χ² test or Fisher's exact test, as appropriate. SCN4B, sodium channel β4 subunit.

Immune infiltration analysis

Correlations between SCN4B expression levels and immune cell infiltration scores were assessed, and the results were visualized using lollipop plots generated with the ‘ggplot2’ package.

Differential expression of SCN4B in tissues

The immunohistochemical expression patterns of SCN4B in adjacent non-tumor and LUAD tissues were obtained from the Human Protein Atlas (HPA) database (https://www.proteinatlas.org/). The analysis was conducted within the ‘Tissue’ section to explore potential biological implications of SCN4B in LUAD.

Cell culture, passaging and cryopreservation

The human LUAD cell lines A549, NCI-H1299, NCI-H1975, PC-9 and HCC827, and the normal human bronchial epithelial cell line BEAS-2B (all from Wuhan Servicebio Technology Co., Ltd.), were maintained in a humidified incubator at 37°C with 5% CO2. A549, NCI-H1299 and BEAS-2B cells were cultured in DMEM (Wuhan Servicebio Technology Co., Ltd.), whereas NCI-H1975, PC-9 and HCC827 cells were cultured in RPMI-1640 medium (Wuhan Servicebio Technology Co., Ltd.). All media were supplemented with 10% FBS (Wuhan Servicebio Technology Co., Ltd.) and 1% penicillin-streptomycin (Wuhan Servicebio Technology Co., Ltd.; final concentration 100 U/ml penicillin and 100 µg/ml streptomycin, 100X stock solution). The culture medium was refreshed every 48 h, and cells were passaged at 80–90% confluence (typically every 2–3 days). Cells were cryopreserved at −80°C overnight and then transferred to liquid nitrogen for long-term storage following standard procedures.

Plasmid transfection and experimental grouping

SCN4B overexpression plasmid DNA was transiently transfected into A549 and NCI-H1299 cells using Lipofectamine® 3000 (Invitrogen; Thermo Fisher Scientific, Inc.). The SCN4B coding sequence was cloned into the pcDNA3.1(+) backbone at the BamHI/EcoRI sites (Sangon Biotech Co., Ltd.). Cells were seeded in 6-well plates (0.3–1×105 cells/well) 1 day before transfection. On the day of transfection, 0.5 µg plasmid DNA and 1.5–2.5 µl Lipofectamine 3000 were prepared in serum-free DMEM (Wuhan Servicebio Technology Co., Ltd.) to form transfection complexes according to the manufacturer's instructions, which were then added to the cells. Cells were incubated at 37°C with 5% CO2 for 18–24 h (without antibiotics). The transfection efficiency was validated by reverse transcription-quantitative PCR (RT-qPCR) to assess SCN4B mRNA expression. Cells were divided into two groups: Vector (empty plasmid) and oe-SCN4B (SCN4B overexpression). Subsequent experiments were initiated at 48 h post-transfection, unless otherwise stated.

Cell Counting Kit-8 (CCK-8) viability assay

Cells were seeded into 96-well plates at a density of 5×103 cells/well and incubated at 37°C with 5% CO2 to allow attachment. At 48 h post-transfection (defined as 0 h for the CCK-8 assay), and at 24, 48 and 72 h thereafter, 10 µl CCK-8 reagent (Wuhan Servicebio Technology Co., Ltd.) was added to each well containing 100 µl culture medium, and plates were incubated for 1–4 h. Absorbance was measured at 450 nm using a microplate reader to quantify the formazan product, which reflects cell viability.

Transwell invasion assays

For the invasion assay, Transwell inserts were precoated with Matrigel (Wuhan Servicebio Technology Co., Ltd.) at 37°C for 30 min prior to cell seeding. Cells were harvested and resuspended in serum-free DMEM, and a total of 5×105 cells in 50 µl were seeded into the upper chamber of each Transwell insert, with the lower chamber filled with DMEM supplemented with 20% FBS (Wuhan Servicebio Technology Co., Ltd.). Each group was prepared in triplicate and cells were incubated at 37°C with 5% CO2 for 48 h. Non-invaded cells on the upper surface were gently removed with cotton swabs. The inserts were fixed with 4% paraformaldehyde (Beyotime Biotechnology) for 15 min at room temperature (20–25°C), stained with crystal violet for 10 min at room temperature and washed three times with PBS. Invaded cells in five random fields (magnification, ×100) were imaged using an inverted light microscope and counted using ImageJ software (v1.52a; National Institutes of Health).

Wound healing assay

A549 and H1299 cells were seeded at 5×105 cells/well in 6-well plates. Upon reaching ~97% confluence, a scratch was made using a 200-µl pipette tip guided by a ruler to maintain uniform width. Detached cells were removed by PBS washing, followed by incubation in low-serum medium (1% FBS). Images were captured at 0 and 48 h (34) at the same wound site using an inverted light microscope (magnification, ×100). The wound closure rate (%) was calculated as: Wound closure rate (%)=[(area at 0 h-area at 48 h)/area at 0 h] ×100. The wound area was quantified using ImageJ software (v1.52a; National Institutes of Health). All assays were repeated three times.

RNA extraction and RT-qPCR

Total RNA was extracted from cells using TRIzol® reagent (Beyotime Biotechnology) following the manufacturer's instructions. Briefly, cells at 70–80% confluence (~1×106 cells per sample) were lysed in 1 ml TRIzol for RNA extraction. First-strand cDNA was synthesized from 1 µg total RNA using a first-strand cDNA synthesis kit (Beyotime Biotechnology) according to the manufacturer's protocol. qPCR was performed on a Rotor-Gene 3000 real-time PCR system (Gene Company, Ltd.) using SYBR® Green qPCR Master Mix (Beyotime Biotechnology; the fluorophore was SYBR Green I dye provided in the master mix). Each reaction was carried out in a 20 µl volume, and amplification was performed with the following thermocycling conditions: 95°C for 30 sec, followed by 40 cycles of 95°C for 5 sec and 60°C for 30 sec; melt-curve analysis was performed to verify specificity. GAPDH served as the internal control, and relative expression levels were calculated using the 2−ΔΔCq method (35). All qPCR reactions were performed in triplicate (technical replicates). The primer sequences for the target genes were as follows: SCN4B forward, 5′-TCTTCCTGCTCCCCGTAAC-3′ and reverse, 5′-AATGCGTCACTGCTGTTGTAG-3′; and GAPDH forward, 5′-CTGGGCTACACTGAGCACC-3′ and reverse, 5′-AAGTGGTCGTTGAGGGCAATG-3′.

Western blotting

Total cellular proteins were extracted from the collected cell pellets using pre-chilled RIPA lysis buffer (Beijing Solarbio Science & Technology Co., Ltd.) supplemented with protease and phosphatase inhibitors. Protein concentrations were determined via a BCA assay. A total of 30 µg protein was loaded per lane. Equal amounts of protein samples were separated on 10% SDS-PAGE gels and subsequently transferred onto PVDF membranes. After blocking with 5% non-fat milk at room temperature for 1 h, the membranes were incubated overnight at 4°C with primary antibodies against SCN4B (cat. no. DF4512; 1:1,000), E-cadherin (cat. no. BF0219; 1:1,000), N-cadherin (cat. no. AF5239; 1:1,000), Vimentin (cat. no. BF8006; 1:1,000), Snail (cat. no. AF6032; 1:1,000) and GAPDH (cat. no. AF7021; 1:1,000). Subsequently, the membranes were incubated for 2 h at room temperature with horseradish peroxidase-conjugated secondary antibodies corresponding to the species of the primary antibodies: Anti-rabbit IgG (cat. no. S0001; 1:10,000) or anti-mouse IgG (cat. no. S0002; 1:10,000). All primary and secondary antibodies were purchased from Affinity Biosciences. Protein bands were visualized using a SuperECL Plus chemiluminescent detection kit (LI-COR Biosciences) and imaged with the Bio-Rad ChemiDoc MP system (Bio-Rad Laboratories, Inc.). Band intensities were semi-quantified using ImageJ software (v1.5.2a; National Institutes of Health).

Flow cytometry

Cells were harvested, washed twice with cold PBS and resuspended in 1X Annexin V binding buffer (10 mM HEPES, 140 mM NaCl, 2.5 mM CaCl2, pH 7.4) at ~1×106 cells/ml. For each sample, 100 µl of cell suspension was incubated with 5 µl annexin V-FITC and 5 µl PI (Annexin V-FITC Apoptosis Detection Kit; cat. no. C1062; Beyotime Biotechnology) for 15 min at room temperature in the dark. After adding 400 µl binding buffer, samples were analyzed within 1 h on a CytoFLEX flow cytometer (Beckman Coulter, Inc.) using the FITC and PI channels. Data acquisition was performed with CytExpert software (v2.4; Beckman Coulter, Inc.), and data were analyzed with FlowJo (v10.10.0; BD Biosciences). Single-stained and unstained controls were used for compensation. Events were gated to exclude debris and doublets [forward scatter (FSC)/side scatter; FSC-area vs. FSC-height]. No fixation was performed prior to acquisition. Cells were classified as viable (annexin V−/PI−), early apoptotic (annexin V+/PI−), late apoptotic (annexin V+/PI+) or necrotic (annexin V−/PI+). The apoptosis rate (%) was calculated as early + late apoptosis.

Statistical analysis

Unless otherwise stated, all experiments were performed in triplicate. Data are presented as the mean ± SD from three independent experiments (n=3), unless otherwise indicated. For non-normally distributed continuous variables, data are presented as the median (interquartile range). Statistical analyses were conducted using GraphPad Prism 8.0 (Dotmatics) and SPSS 26.0 (IBM Corp.). Categorical clinicopathological variables were compared between high and low SCN4B expression groups using χ2 tests or Fisher's exact tests. Survival was analyzed using the Kaplan-Meier method, and differences were evaluated using the log-rank test. For expression analyses based on transcriptomic data, paired data were analyzed using a paired Student's t-test, and unpaired comparisons with unequal variances were analyzed using Welch's t-test. Comparisons among multiple groups were performed using the Kruskal-Wallis test followed by Dunn's multiple comparisons test when data were not normally distributed, whereas two-group comparisons were performed using the Wilcoxon rank-sum test under the same conditions. Spearman's rank correlation was used to assess correlations between SCN4B expression and the expression of selected genes. A two-tailed unpaired Student's t-test was used to analyze the wound healing, Transwell and flow cytometry apoptosis assay data, as well as RT-qPCR (ΔCq values) and western blot densitometric semi-quantification data, comparing between the vector and oe-SCN4B groups. Baseline SCN4B expression across multiple lung adenocarcinoma cell lines was compared using one-way ANOVA with Dunnett's post hoc test. The CCK-8 assay data were analyzed using two-way ANOVA with Bonferroni's post hoc test. Correlations between SCN4B expression and immune cell infiltration scores were evaluated using Spearman correlation analysis, and the corresponding correlation coefficients and P-values are shown in the figures. ROC curves were generated to assess the diagnostic performance of SCN4B. P<0.05 was considered to indicate a statistically significant difference.

Results

Differential expression of SCN4B in LUAD

In TCGA-LUAD dataset, 539 tumor samples and 59 adjacent normal tissue samples were analyzed, and 58 matched tumor-normal pairs were available for paired analysis (Fig. 2A). The baseline clinical characteristics of patients with LUAD with high and low SCN4B expression are summarized in Table I. Elevated SCN4B expression was markedly associated with earlier T stage, sex, age and smoking status, whereas no significant differences were observed in N stage, M stage, overall pathological stage or anatomic neoplasm subdivision.

Figure 2. Differential expression analysis of SCN4B in LUAD. (A) Differential expression analysis of SCN4B in LUAD and adjacent non-tumorous tissue. A paired Student's t-test was used. (B) Gene Expression Omnibus cohort (GSE31210; Affymetrix GPL570): Comparison of SCN4B microarray intensity between tumor and normal lung tissues. Welch's t-test was used. (C) Diagnostic receiver operating characteristic curve analysis of SCN4B. ***P<0.001, ****P<0.0001. AUC, area under the curve; SCN4B, sodium channel β4 subunit; LUAD, lung adenocarcinoma; TPM, transcripts per million; TPR, true positive rate; FPR, false positive rate.

Expression profiling revealed that SCN4B was markedly downregulated in LUAD tissues compared with adjacent normal tissues (Fig. 2A). The external GEO cohort (GSE31210) exhibited significant downregulation of SCN4B in tumor vs. normal lung tissues (Fig. 2B). ROC curve analysis (Fig. 2C) indicated that SCN4B possessed strong diagnostic potential, with an area under the curve of 0.979 (95% CI, 0.969–0.990).

Differential analysis of SCN4B and related genes

The volcano plot of SCN4B-associated differentially expressed genes between the SCN4B high- and low-expression groups is shown in Fig. 3A. Spearman's rank correlation analysis was performed to assess the correlation between SCN4B and several genes, including ADAMTS8, ADH1B, INMT, FHL1, C1QTNF7, MAMDC2, ATP1A2, TBX4, SCN7A, TCF21 and ITGA8 (Fig. 3B). These associations suggest that SCN4B and the identified genes may participate in common biological processes (BPs) or signaling pathways, potentially exerting cooperative or reciprocal regulatory effects.

Figure 3. Differentially expressed genes associated with SCN4B in lung adenocarcinoma. (A) Volcano plot illustrating SCN4B-associated differentially expressed genes in the dataset. Red dots represent upregulated genes, blue dots indicate downregulated genes and gray dots denote non-significant genes. (B) Spearman's rank correlation analysis between SCN4B and selected genes. P.adj, adjusted P-value; SCN4B, sodium channel β4 subunit; TPM, transcripts per million.

GO and KEGG functional enrichment analysis

GO functional enrichment analysis indicated that the SCN4B-associated differentially expressed genes were significantly enriched in BP terms including ‘cell-substrate adhesion’, ‘extracellular structure organization’, ‘extracellular matrix organization’ and ‘heart morphogenesis’. At the cellular component level, the SCN4B-associated differentially expressed genes were mainly associated with ‘collagen-containing extracellular matrix’, ‘cell-cell junction’, ‘caveola’ and ‘platelet alpha granule’. In terms of molecular functions (MFs), the SCN4B-associated differentially expressed genes were primarily enriched in ‘sulfur compound binding’, ‘glycosaminoglycan binding’, ‘heparin binding’ and ‘extracellular matrix structural constituent’ (Fig. 4A). In addition, KEGG pathway enrichment analysis showed that the SCN4B-associated differentially expressed genes were enriched in pathways such as ‘cell adhesion molecules’ (CAMs), ‘vascular smooth muscle contraction’, ‘dilated cardiomyopathy’, ‘hypertrophic cardiomyopathy’ and ‘arrhythmogenic right ventricular cardiomyopathy’ (Fig. 4B).

Figure 4. Functional enrichment analysis of SCN4B-associated differentially expressed genes. (A) Gene Ontology functional enrichment analysis based on differences. (B) KEGG functional enrichment analysis. KEGG, Kyoto Encyclopedia of Genes and Genomes; BP, biological process; CC, cellular component; MF, molecular function; P adj, adjusted P-value.

Immune infiltration analysis of SCN4B

SCN4B expression was positively associated with mast cells, eosinophils and immature dendritic cells (iDCs). By contrast, SCN4B expression showed a negative correlation with type 2 helper T cells (Th2 cells), natural killer (NK) CD56dim cells, γδ T cells (Tgds) and regulatory T cells (Tregs) (Fig. 5A).

Figure 5. Analysis of immune infiltration related to SCN4B. (A) Bubble plot of immune infiltration analysis. (B) Correlation analysis of SCN4B expression with tumor purity, M2 macrophage infiltration (quanTIseq) and NK cell infiltration (quanTIseq). Spearman correlation analysis was performed; Ρ-values and P-values are shown. SCN4B, sodium channel β4 subunit; NK, natural killer; quanTIseq, quantification of the tumor immune contexture from RNA sequencing; TPM, transcripts per million.

As shown in Fig. 5B, SCN4B expression was negatively associated with tumor purity, and weak positive correlations were observed with M2 macrophage and NK cell infiltration levels estimated by quantification of the tumor immune contexture from RNA sequencing.

SCN4B expression in LUAD and adjacent normal tissues

Analysis using the HPA database revealed that SCN4B expression was nearly absent in tumor tissues, whereas detectable expression was observed in adjacent non-tumor tissues (Fig. 6).

Figure 6. SCN4B expression in lung cancer tissues and normal tissues. Immunohistochemical staining images of SCN4B expression in normal lung tissue and lung adenocarcinoma tumor tissue were obtained from the online Human Protein Atlas database (https://www.proteinatlas.org/). The magnification of the first row of images is ×100; scale bar, 200 µm; the magnification of the second row of images is ×400; scale bar, 50 µm. SCN4B, sodium channel β4 subunit.

Prognostic and clinicopathological association analysis of SCN4B

Patients with high SCN4B expression exhibited longer OS and DSS than those with low expression (Fig. 7A and B). High SCN4B expression was associated with a longer PFI (Fig. 7C).

Figure 7. Prognostic analysis and clinical association analysis of SCN4B. (A) Kaplan-Meier survival curve for overall survival stratified by SCN4B expression. (B) Kaplan-Meier survival curve for disease-specific survival based on SCN4B expression levels. (C) Kaplan-Meier survival curve for the progression-free interval in patients with high vs. low SCN4B expression. (D) Comparison of SCN4B expression across T stages (T1-T4). (E) SCN4B expression in patients with or without lymph node metastasis. (F) SCN4B expression in patients with or without distant metastasis. (G) SCN4B expression across different tumor stages. (D and E) Kruskal-Wallis test. (F and G) Wilcoxon rank-sum test. ***P<0.001. HR, hazard ratio; ns, not significant (P>0.05); SCN4B, sodium channel β4 subunit; TPM, transcripts per million.

In the analysis of SCN4B expression across TNM stages, a significant difference was observed between T1 and T2 stages, with markedly reduced expression in T2 tumors. SCN4B expression differed between stages T1 and T2. However, no statistically significant differences were observed in stage T3-T4 compared with stages T1 or T2 (Fig. 7D). Furthermore, SCN4B expression was not markedly associated with lymph node metastasis, distant metastasis or overall tumor stage (Fig. 7E-G).

External prognostic validation

In the external LUAD cohort GSE31210, high SCN4B expression was associated with improved survival. After median dichotomization, Kaplan-Meier curves and the ‘number at risk’ table displayed below the plot showed a significant difference between groups (Fig. 8).

Figure 8. Prognostic association of SCN4B in the GSE31210 cohort. Kaplan-Meier curves were generated by stratifying patients into high and low SCN4B expression groups using the median expression value as the cutoff. The ‘number at risk’ table below the plot indicates the counts remaining at risk at each time point. Groups were compared using the two-sided log-rank test (P=0.0042). SCN4B, sodium channel β4 subunit.

Baseline SCN4B profiling and model selection

First, SCN4B protein and mRNA levels were screened by western blotting and RT-qPCR in a normal lung-derived cell line and multiple lung cancer cell lines. Using the normal cell line as the reference and normalizing to GAPDH, most cancer cell lines exhibited a marked reduction in SCN4B signal. The decrease was most consistent and pronounced in A549 and H1299 cells, which were therefore selected for subsequent functional assays (Fig. 9).

Figure 9. Basal expression of SCN4B across lung cell lines. (A) Representative western blot images: Lane 1, normal lung cells; lanes 2–6, lung cancer cell lines. GAPDH served as the loading control. For densitometric quantification, SCN4B was normalized to GAPDH and further normalized to the normal cells (=1). (B) Reverse transcription-quantitative PCR validation in the same panel of distinct cell lines as in (A) (normalized to GAPDH; 2−ΔΔCq). One-way ANOVA with Dunnett's post hoc test was used for statistical analysis. N=3 independent experiments. *P<0.05, **P<0.01, ****P<0.0001. ns, not significant (P>0.05); SCN4B, sodium channel β4 subunit.

Construction of SCN4B overexpression cell models

SCN4B overexpression cell lines were established in A549 and H1299 cells by transfection with an overexpression plasmid. The results showed that the mRNA expression levels of SCN4B were markedly increased in the oe-SCN4B group compared with the vector group (Fig. 10).

Figure 10. Construction of SCN4B overexpression models in A549 and H1299 lung adenocarcinoma cell lines. After transfection with overexpression plasmids for 48 h in A549 and H1299 cells, the relative mRNA expression level changes of SCN4B in the cells were detected by reverse transcription-quantitative PCR. Data were analyzed using a two-tailed unpaired Student's t-test. N=3 independent experiments. **P<0.01. SCN4B, sodium channel β4 subunit; oe, overexpression.

SCN4B reduces lung cancer cell viability and induces apoptosis in LUAD cells

The CCK-8 assay results demonstrated that SCN4B overexpression markedly reduced the viability of A549 and H1299 cells in a time-dependent manner, with prolonged exposure leading to stronger inhibitory effects (Fig. 11A).

Figure 11. SCN4B induces apoptosis and inhibits cell viability. (A) Changes in the viability of A549 and H1299 cells at different time points after transfection (0, 24, 48 and 72 h) were detected using a Cell Counting Kit-8 assay. Data were analyzed using two-way ANOVA with Bonferroni's post hoc test. Changes in the proportion of apoptotic cells after 48 h of transfection in (B) A549 and (C) H1299 cells labeled with PI/annexin V-FITC double staining were detected by flow cytometry. Data were analyzes using a two-tailed unpaired Student's t-test. N=3 independent experiments. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001. ns, not significant (P>0.05); SCN4B, sodium channel β4 subunit; oe, overexpression; OD, optical density.

Flow cytometry analysis using annexin V-FITC/PI double staining revealed that SCN4B overexpression markedly increased the proportion of apoptotic cells (early apoptosis + late apoptosis) in A549 and H1299 LUAD cells (Fig. 11B and C).

SCN4B suppresses invasion and migration of LUAD cells

Transwell assay results showed that the number of invasive cells was significantly decreased following SCN4B overexpression (Fig. 12A). In addition, wound healing assay results indicated that SCN4B overexpression markedly slowed the wound closure rate and markedly reduced the healing area compared with the vector group (Fig. 12B).

Figure 12. SCN4B can inhibit the invasion and migration of lung cancer cells. (A) Changes in the invasion of A549 and H1299 LUAD cells 48 h after transfection with SCN4B overexpression plasmid were detected using a Transwell assay (magnification, ×100; scale bar, 100 µm). (B) Changes in the migration of A549 and H1299 LUAD cells 48 h after transfection with SCN4B overexpression plasmid were detected using a cell scratch assay (magnification, ×100; scale bar, 200 µm). Data were analyzed using a two-tailed unpaired Student's t-test. N=3 independent experiments. *P<0.05, **P<0.01, ***P<0.001. SCN4B, sodium channel β4 subunit; oe, overexpression; LUAD, lung adenocarcinoma.

Effect of SCN4B on EMT-related marker proteins

Western blot analysis revealed that SCN4B overexpression markedly increased the relative expression levels of E-cadherin, while suppressing the relative expression levels of N-cadherin, Vimentin and Snail (Fig. 13).

Figure 13. SCN4B can inhibit the epithelial-mesenchymal transition process of LUAD cells. The relative protein expression levels of SCN4B, E-cadherin, N-cadherin, Vimentin and Snail in A549 and H1299 LUAD cells 48 h after transfection with SCN4B overexpression plasmid were detected by western blotting. Data were analyzed using a two-tailed unpaired Student's t-test for each protein. N=3 independent experiments. ****P<0.0001. SCN4B, sodium channel β4 subunit; oe, overexpression; LUAD, lung adenocarcinoma.

Discussion

LUAD is one of the leading causes of tumor-related mortality worldwide, with its high lethality primarily attributed to late-stage diagnosis and highly aggressive biological behavior (36). Among the various mechanisms driving LUAD progression, EMT has been shown to be a central process underlying metastasis and recurrence (37). Therefore, an improved understanding of the molecular regulation of EMT in LUAD is of considerable clinical value.

The present bioinformatics analysis revealed marked downregulation of SCN4B expression in LUAD tissues, with low expression markedly associated with unfavorable prognosis. This observation aligns with a previous large-scale analysis reporting a prognostic link between reduced SCN4B levels and poor lung cancer outcomes (38).

Kaplan-Meier survival analysis demonstrated that patients with low SCN4B expression had a substantially shorter median survival time, while ROC curve analysis indicated that SCN4B possessed promising diagnostic value in LUAD. Furthermore, analysis by pathological T stage showed that SCN4B expression was significantly lower in stage T2 than in stage T1, whereas no statistically significant differences were observed between stage T3-T4 and either stage T1 or stage T2. This trend may indicate that changes in SCN4B expression are closely related to local tumor expansion or primary tumor burden. However, SCN4B expression did not significantly differ between groups based on other staging parameters (such as N stage, M stage or pathological stage), which may be due to the limited sample size or may indicate that SCN4B primarily participates in early-stage local invasion and proliferation (39). To the best of our knowledge, to date, the biological basis for this stage-specific pattern remains unexplored.

Dysregulated cell proliferation and inhibition of apoptosis are considered key molecular events driving tumor initiation and progression (40,41). Under normal conditions, cell growth is tightly regulated by extracellular cues. However, cancer cells frequently acquire autocrine growth signaling, bypass cell-cycle checkpoints and maintain uncontrolled proliferation (42,43). In the present study, SCN4B overexpression in LUAD cell lines (A549 and H1299) markedly reduced the proliferative capacity in a time-dependent manner, as determined by CCK-8 assays. The results showed that SCN4B overexpression markedly decreased cell viability in both cell lines, with a time-dependent inhibitory effect. Furthermore, considering that apoptosis evasion is an important mechanism for tumor survival and immune escape (44), annexin V/PI dual-staining flow cytometry was performed to evaluate apoptosis. The results demonstrated that SCN4B overexpression markedly induced both early and late apoptosis in LUAD cells. These results suggested that SCN4B exerts a tumor-suppressive effect through simultaneous inhibition of proliferation and promotion of apoptosis.

In LUAD, EMT not only drives metastasis but also contributes to chemoresistance and stemness acquisition (45). The Snail family of transcription factors, including Snail1 and Snail2, are key EMT regulators (46). By binding to the E-box elements within the E-cadherin promoter region, they suppress E-cadherin expression, thereby promoting EMT (47). N-cadherin, a mesenchymal cell marker, is upregulated during EMT and is associated with enhanced invasive and migratory abilities (48,49). Vimentin, an intermediate filament protein, is another mesenchymal marker whose increased expression during EMT is associated with enhanced motility and invasiveness (50).

The functional assays in the present study demonstrated that SCN4B overexpression markedly impaired LUAD cell migration and invasion. Western blot analysis showed that SCN4B elevated E-cadherin expression, while reducing N-cadherin, Vimentin and Snail levels, suggesting a suppressive effect on EMT, potentially via the Snail/E-cadherin axis. Previous work has shown that Snail recruits histone deacetylases to the E-cadherin promoter, modulating H3/H4 acetylation and silencing transcription, providing a plausible mechanism for SCN4B-mediated EMT inhibition (41). Taken together, the present results and previous reports (24,25) supported the proposed schematic model whereby SCN4B may regulate EMT in LUAD (Fig. 1).

In the LUAD cell models used in the present study, SCN4B overexpression attenuated EMT and invasive behavior, suggesting that its downstream effects may involve several key signaling pathways. Among the classical EMT-inducing cascades, the TGF-β/Smad axis is a major driver of epithelial plasticity, invasive growth and treatment resistance in NSCLC. TGF-β receptor signaling promotes the disassembly of tight junctions, reorganization of the actin cytoskeleton and induction of EMT-related transcription factors such as Snail (51). Previous studies have indicated that SCN4B participates in the regulation of cell adhesion and cytoskeletal dynamics (52,53). In the present study, SCN4B overexpression increased E-cadherin expression, while reducing N-cadherin, Vimentin and Snail expression. These findings support the hypothesis that SCN4B may dampen TGF-β-induced EMT in LUAD cells. Biologically, such an effect would be expected to reduce EMT plasticity and local invasiveness of tumor cells and to alleviate the development of an immunosuppressive, therapy-resistant tumor microenvironment driven by chronic TGF-β signaling, thereby collectively constraining tumor progression.

The Wnt/β-catenin pathway represents another critical signaling cascade that promotes EMT, maintenance of stem-like properties and metastatic spread in lung cancer. Under physiological conditions, β-catenin is sequestered at adherens junctions through binding to E-cadherin. When E-cadherin is lost, β-catenin accumulates in the nucleus and activates Wnt target genes (54). In TCGA-LUAD, enrichment analysis of SCN4B-associated differentially expressed genes highlighted adhesion-related processes, including the KEGG ‘cell adhesion molecules’ pathway, and in the in vitro experiments, SCN4B overexpression increased E-cadherin expression, suggesting that SCN4B may indirectly limit sustained activation of canonical Wnt/β-catenin signaling by stabilizing the membrane E-cadherin/β-catenin complex. Integrating these observations, a unified and testable working model in which SCN4B functions as a membrane-associated ‘brake’ was proposed. On the one hand, it attenuates TGF-β/Smad signaling by restricting TGF-β1-induced Smad2/3 phosphorylation and the upregulation of EMT transcription factors (52). On the other hand, it suppresses canonical Wnt/β-catenin signaling by stabilizing epithelial cell-cell junctions, reducing nuclear β-catenin accumulation and lowering T-cell factor/lymphoid enhancer factor reporter activity (55). This integrated model can be evaluated by combining TGF-β1 stimulation and pharmacologic modulation of the Wnt pathway in SCN4B-manipulated LUAD cells, together with TCF/LEF-dependent luciferase reporter assays using the TOPflash reporter (containing wild-type TCF/LEF-binding sites) and the FOPflash (containing mutated TCF/LEF-binding sites) mutant control, and analyses of Smad2/3, EMT markers and β-catenin expression and subcellular localization (56). Given that both TGF-β and Wnt/β-catenin pathways are tightly linked to EMT plasticity, stem-like tumor cell subpopulations, metastatic colonization and resistance to systemic therapy, the regulation of these pathways by SCN4B may have important implications for the biological aggressiveness and clinical behavior of LUAD (56,57).

GO and KEGG enrichment analyses of SCN4B-associated differentially expressed genes between SCN4B-high and SCN4B-low LUAD samples were performed to investigate the potential role of SCN4B in post-transcriptional regulation and in modulating cellular structure and function during the EMT process. In TCGA-LUAD dataset, GO enrichment analysis revealed that SCN4B-associated differentially expressed genes were markedly enriched in BP terms including ‘cell-substrate adhesion’, ‘extracellular structure organization’ and ‘extracellular matrix organization’. KEGG pathway analysis further demonstrated that these genes were markedly enriched in the ‘cell adhesion molecules’ pathway. The dynamic balance between microtubule polymerization and depolymerization is a crucial mechanism for maintaining cytoskeletal stability and regulating the migratory capacity of cancer cells (58). The enrichment of SCN4B-associated differentially expressed genes in the ‘cell adhesion molecules’ pathway, involving key adhesion molecules such as E-cadherin and integrins, suggests that SCN4B may interfere with the EMT process by modulating intercellular junction structures (such as adherens junctions and desmosomes), thereby inhibiting the invasion and metastasis of LUAD cells (59,60).

In addition, marked enrichment of ‘glycosaminoglycan binding’ in the MF category was observed in the present study. Glycosaminoglycans, covalently linked to proteins to form proteoglycans, are ubiquitous across mammalian cells, and are present on membranes, in the intracellular space and within the extracellular matrix (ECM). By interacting with a wide range of ligands, they participate in multiple physiological and pathological events, including cancer (61). In the present study, the MF term ‘glycosaminoglycan binding’ was markedly enriched, suggesting that SCN4B may influence the remodeling of the tumor microenvironment and regulate pro-tumorigenic signaling pathways by modulating ECM components.

Immune profiling revealed a positive association between SCN4B expression and mast cells, eosinophils and iDCs, but an inverse correlation with Th2 cells, NK CD56dim cells and Tgds. Such patterns suggest that SCN4B may act as an immune microenvironment regulator by shaping immune cell infiltration profiles. Given that the tumor microenvironment is integral to cancer initiation, progression, metastasis and therapeutic response, the infiltration landscape of immune cells has direct implications for prognosis (62,63).

Despite the promising findings, the present study has several limitations that must be acknowledged. First, most conclusions were drawn from association analyses based on publicly available transcriptomic datasets, which may introduce selection bias and cannot fully reflect protein-level regulation. Second, the in vitro validation was limited to a small number of LUAD cell lines, and thus, may not capture the heterogeneity of the disease. Third, in vivo evidence from animal models is still lacking, which restricts the translational interpretation of SCN4B function in lung tumor progression. Future research should therefore include validation in larger independent clinical cohorts, incorporate proteomic and in vivo functional assays, and explore the underlying molecular mechanisms by which SCN4B regulates EMT and tumor metastasis. Addressing these aspects will provide a more comprehensive understanding of SCN4B and strengthen its potential as a prognostic biomarker and therapeutic target in LUAD.

In conclusion, low SCN4B expression was closely associated with poor prognosis, whereas its high expression may suppress LUAD cell proliferation, migration and invasion by negatively regulating the EMT process.

Acknowledgements

Not applicable.

Funding

Funding: No funding was received.

Availability of data and materials

The data generated in the present study are included in the figures and/or tables of this article.

Authors' contributions

MG performed the experiments, collected the data and drafted the manuscript. HL contributed to preliminary research and data analysis. ZZ and YW contributed to the conception and methodology of the study, provided technical input for experimental design and troubleshooting, and critically revised the manuscript for important intellectual content. JT and BZ participated in experimental implementation. YZ conceived and designed the study, and was responsible for overall supervision. MG and HL confirm the authenticity of all the raw data. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Not applicable.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

References