Overexpression of FOXO1 may suppress proliferation and migration and correlate with tumor immune cells in nasopharyngeal carcinoma

Introduction

According to the latest global cancer burden survey (2022), an estimated 20 million new cancer cases and 9.7 million cancer-related deaths occurred worldwide. Among these, nasopharyngeal carcinoma (NPC) accounted for 120,416 newly diagnosed cases globally, ranking as the 23rd most common malignancy worldwide. NPC resulted in 73,476 deaths, positioning it as the 21st leading cause of cancer mortality. Notably, both incidence and mortality rates of NPC were significantly higher in males than in females (1). NPC is challenging to diagnose during the early stages due to its prolonged, subtle symptoms that frequently lead to misdiagnosis or missed diagnoses in the clinical setting (2). Radiotherapy combined with chemotherapy constitutes the current gold-standard therapeutic regimen for NPC. With advances in various diagnostic and therapeutic methods, such as intensity-modulated radiation therapy (IMRT), NPC prognosis has significantly improved over the past decades (3). However, a proportion of patients still experience locoregional recurrence and distant metastases (4,5). Consequently, it is crucial to explore the pathogenesis of NPC and identify robust prognostic biomarkers and therapeutic targets to improve patient outcomes.

According to previous studies, dysregulation of transcription factors (TFs) represents a hallmark of human malignancies. Forkhead box protein O1 (FOXO1), a key TF in the Forkhead box (FOX) subfamily, is implicated in disrupting the balance between cell proliferation and apoptosis, participating in tumorigenesis, invasion, metastasis, and other pathological processes (6-8). In various malignancies, the expression and function of FOXO1 are governed by complex, tumor-type-specific regulatory mechanisms, resulting in a significant “double-edged sword” phenotype (9,10). On the one hand, its tumor-suppressive functions can be suppressed or inactivated through multiple mechanisms, including post-translational modifications (PTMs), transcriptional regulation, and hyperactivation of oncogenic signaling pathways (11-13). On the other hand, under specific tumor microenvironment (TME) conditions or genetic contexts, FOXO1 may be aberrantly activated, exhibiting pro-tumorigenic effects (7,14). This intricate, multi-layered regulation of FOXO1 expression and activity ultimately determines its biological impact within tumors. Dysregulated FOXO1 significantly influences the malignant biological behaviors of cancer cells. Crucially, the regulatory status of FOXO1 is closely linked to clinical therapeutic outcomes (15). It participates in modulating tumor cell sensitivity or resistance to various anti-cancer treatment methods (16-18). Studies have shown that chimeric antigen receptor-T (CAR-T) cells engineered to overexpress FOXO1 exhibit enhanced persistence and tumor control capabilities in vivo. Furthermore, FOXO1 overexpression induces a T stem cell-like phenotype in CAR-T cells derived from healthy human donors or patients. This phenotype is associated with improved therapeutic effects in vivo. Taken together, these observations highlight the pivotal role of FOXO1 in tumor immunotherapy (19,20). Moreover, immunotherapy offers distinct advantages for enhancing therapeutic efficacy in NPC. The combination of nivolumab with induction chemotherapy and radiotherapy has demonstrated significant anti-tumor activity in NPC treatment, improving the complete remission rates and potentially reducing the radiotherapy dose and late toxicity (21).

Indeed, several studies have investigated FOXO-related pathways in NPC. For instance, Zhao et al. reported that miR-3188 influences NPC proliferation and sensitivity to 5-fluorouracil through a FOXO1-driven mTOR/PI3K/AKT feedback loop (22). At the same time, Li et al. described that cinobufotalin enhances cisplatin sensitivity by antagonizing myosin heavy chain 9 (MYH9), thus regulating tumor stemness and epithelial-mesenchymal transition (EMT) signaling in NPC (23). Notably, Syndecan-1 (SRGN) promotes NPC progression under regulation by the STAT3/FOXO1/CREB1 axis (24). HOXB2-FOXO1 interactions influence malignant phenotypes and radioresistance in NPC (25). Despite these findings, comprehensive investigations exploring FOXO1’s functional impact in NPC remain limited.

Therefore, exploring the regulatory network and functional roles of FOXO1 in NPC not only facilitates a deeper understanding of the molecular mechanisms underlying tumorigenesis and progression, but also provides a critical theoretical foundation and potential targets for developing novel anti-cancer strategies for NPC.

In summary, FOXO1 represents a promising therapeutic target for immunotherapy, holding substantial research potential and clinical value. This study explored FOXO1’s role and mechanisms in NPC development using bioinformatics and experimental methods, and evaluated the relationship between FOXO1 expression and the infiltration levels of immune cells. These findings bear significant implications for advancing clinical treatment strategies for NPC. We present this article in accordance with the TRIPOD and MDAR reporting checklists (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2890/rc).

Methods

Data and patient collection

The pan-cancer analyses relied on information from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression project (GTEx). The analyses were conducted utilizing online tools available through the HOME for Researchers platform. Transcriptome and clinical information were sourced from the Gene Expression Omnibus (GEO) database for the datasets GSE12452, GSE53819, GSE61218, GSE102349, GSE78220, GSE218167, and GSE171664. A combined dataset from GSE12452, GSE53819, and GSE61218 was log₂-transformed and processed with the ComBat function of the sva R package to eliminate batch effects, resulting in data comprising 59 NPC cases and 34 healthy controls. GSE102349 comprised 113 NPC samples and 88 NPC patients with disease progression data. The enrolled patients involved in the prediction of 1- and 2-year progression-free survival (PFS) were all NPC patients. The outcome data were sourced from the follow-up records of the original study. Due to the use of historical datasets, the outcome assessor was not blinded to the predictive factors. The GSE78220 dataset comprises 27 melanoma patients undergoing anti-programmed cell death protein 1 (anti-PD-1) therapy, along with their survival outcomes. GSE218167 contained data on two Epstein-Barr Virus-positive (EBV-positive) and one EBV-negative NPC43 cells. Lastly, GSE171664 included three CNE1 cells stably expressing EBV-encoded Latent Membrane Protein 1 (LMP1) and two LMP1-negative CNE1 cells. All data can be downloaded from the GEO website.

Functional enrichment analysis

The GSE102349 dataset samples were split into high and low FOXO1 expression groups based on the median value. Subsequently, the clusterProfiler R package was utilized to conduct and visualize the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) analyses.

Tumor immune infiltration assessment analysis

The IOBR2 R package (26) was utilized to assess immune cell infiltration in each NPC sample from GSE102349. We estimated the immune cell infiltration landscape of NPC using Estimating the Proportion of Immune and Cancer cells (EPIC), Microenvironment Cell Populations-counter (MCPcounter), Quantitative Transcriptome-based Tumor Immune cell Quantification (quanTIseq), and Extended Cell type Enumeration (xCell) algorithms. Immune-related scores were derived using the xCell, Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE), and Immunophenoscore (IPS) algorithms.

Cells and clinical samples

The human NPC cell lines 5-8F, CNE1 and HONE1, along with the immortalized normal nasopharyngeal epithelial cell line NP69, were provided by Guangxi Medical University, China. All cell lines were confirmed mycoplasma-negative prior to experimentation (Figure S1).

The tissue samples of untreated patients with pathologically confirmed NPC and rhinitis patients at Wuzhou Red Cross Hospital were retrospectively collected. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Wuzhou Red Cross Hospital (approval No. LL2022-49). Written informed consent was obtained from all individual participants prior to specimen collection.

Reverse transcription quantitative polymerase chain reaction (RT-qPCR)

Total RNA was isolated from cells and tissues with the RNA Easy Fast Kit (TIANGEN, Beijing, China; DP451), followed by cDNA synthesis using the Reverse Transcription Kit (ThermoFisher, Vilnius, Lithuania; M1631). The SYBR Green method was used for RT-qPCR, starting with a 10-minute initial denaturation at 95 ℃, then proceeding with 40 cycles of 95 ℃ for 10 seconds, and 60 ℃ for 1 minute. The FOXO1 primer sequences were: forward 5’-TCGTCATAATCTGTCCCTACACA-3’ and reverse 5’-CGGCTTCGGCTCTTAGCAAA-3’. GAPDH functioned as the internal standard for normalization. The 2^−ΔΔCt algorithm was used to quantify the expression levels of FOXO1. For RT-qPCR analyses, we utilized the following three cell lines: 5-8F, CNE1, and NP69. Additionally, RT-qPCR was performed using clinical biopsy specimens, including: 17 samples from patients with NPC and 15 samples from rhinitis. All experiments were replicated three times.

Western blot

A cell lysis buffer (Beyotime, Shanghai, China; P0013B) supplemented with 1% protease inhibitor was used to extract total protein. The concentration of protein was measured using a BCA quantification kit (Epizyme, ZJ101). Samples were prepared by mixing with an equal volume of 4× sample buffer (ThermoFisher, NP0007) and then denatured for 10 minutes at 70 ℃. Proteins were separated using electrophoresis on a ThermoFisher precast gel (NP0301BOX) at 200 V for 30 minutes, then transferred to a Millipore PVDF membrane (IPVH00010) at 250 mA for 1.5 hours. The membrane was blocked for 15 minutes at room temperature, followed by three washes. Then it was incubated with the primary antibody at 4 ℃ overnight. Subsequently, the membrane was washed thrice and incubated with a secondary antibody at room temperature for 1.5 hours with shaking. A chromogenic solution visualized the protein bands and gel imaging analyzer captured images. ImageJ software quantified the gray values of the protein bands. Antibody: FOXO1 (2880, CST, Danvers, USA), GAPDH (60004-1-Ig, Proteintech, Wuhan, China). Second antibody: Goat anti-Mouse IgG (H+L) Secondary Antibody, HRP (31430, Invitrogen, Waltham, USA), Goat anti-Rabbit IgG (H+L) Secondary Antibody, HRP (31460, Invitrogen). For WB analyses, we utilized the following three cell lines: 5-8F, CNE1, and NP69. All experiments were replicated three times.

Immunohistochemical (IHC) staining

Paraffin-embedded tissue sections were incubated for 3 hours at 60 ℃ and deparaffinized with xylene. The sections were rehydrated using a graded alcohol series ranging from 100% to 75%. Antigen retrieval was conducted using a high-temperature, high-pressure technique. Sections were incubated at 4 ℃ overnight with the primary antibody, then with a secondary antibody at 37 ℃ for 30 minutes. The immune response was visualized using a diaminobenzidine (DAB) substrate for color development and nuclei were counterstained with hematoxylin. Sections were differentiated using hydrochloric acid-alcohol. The intensity and distribution of staining were evaluated and scored by two independent pathologists. Antibody: FOXO1 (2880, CST), GAPDH (60004-1-Ig, Proteintech). Second antibody: Universal two-step detection kit (PV-9000, ZSGB-BIO). IHC was performed using archival formalin-fixed paraffin-embedded (FFPE) tissue specimens, including: 45 samples from patients with NPC and 26 samples from patients with rhinitis.

Cell proliferation and colony formation assay

Guangxi Medical University, Nanning, China, provided the NPC cell lines (CNE1 and 5-8F) and the immortalized nasopharyngeal epithelial cells (NP69). NPC cells were maintained in DMEM high glucose medium (Gibco, Waltham, USA; C11995500BT) with 10% fetal bovine serum (Sigma, F8318). NP69 cells were cultured in Keratinocyte-SFM medium supplemented with recombinant epidermal growth factor and bovine pituitary extract (Gibco, 17005042). PCMV6-entry-FOXO1 plasmid (RC200477) and empty vector plasmid (PS100001) were purchased from OriGene Technologies in Wuxi.

The Cell Counting Kit-8 (CCK-8) assay (Dojindo, CK04) and a colony formation assay were used to evaluate the impact of FOXO1 on cell proliferation and colony formation, respectively. In the cell proliferation assay, post-transfected NPC cells were placed in 96-well plates at 1,000 cells per well, with five replicates for each experimental and control group. Cells were incubated with CCK-8 reagent at 37 ℃ for 1.5 hours, and absorbance was detected at a wavelength of 450 nm every 24 hours over a 5-day period. In the colony formation assay, post-transfected NPC cells were seeded at 500 cells per well in 6-well plates and incubated for 14 days at 37 ℃. The samples were quantified using ImageJ software.

Migration and Transwell invasion assays

In the wound healing assay, first, transiently transfected NPC cells were seeded into 12-well plates. After the cells formed a confluent layer, scratches were made using a pipette tip, and then serum-free medium (Gibco, C11995500BT) was supplemented to each well. Wound closure was monitored under a microscope over time. The rate of scratch healing was quantified using ImageJ software. In the Transwell invasion assay, a layer of matrigel (Corning, NY, USA; REF356234) was applied to the surface of the invasion chamber. Transfected NPC cells were plated into the upper chamber, which contained serum-free medium. The lower chamber was filled with serum-containing medium. After 24 hours of incubation, a cotton swab was employed to gently clear non-invading cells from the membrane’s upper surface. Cells were washed, fixed with 4% paraformaldehyde, stained using 0.1% crystal violet, and analyzed microscopically.

Statistical analysis

The R v4.4.1 language was applied for visualization and statistical analyses. Each experimental condition was biologically replicated at least thrice to ensure reliability and reproducibility. The Wilcox or Kruskal test was employed to compare differences in FOXO1 expression among groups. The continuous variables of the predictive model were processed through log2 transformation, while categorical variables were converted into factor variables. Continuous predictive factors underwent Z-score normalization before modeling. A multivariate Cox proportional hazards regression model was employed, and predictive factors were simultaneously incorporated into the model using the full-variable forced entry method. Based on the final Cox model, a nomogram was constructed. The bias-adjusted C-index and its 95% confidence interval were calculated for internal validation. Correlations between variables were analyzed using the Spearman correlation algorithm. The prognostic significance of FOXO1 was assessed using Kaplan-Meier curve, time-dependent receiver operating characteristic (ROC) curve, and Cox regression. The prognostic model was illustrated with a forest plot and a nomogram. A P value under 0.05 was judged to be significant.

Results

FOXO1 expression in NPC based on GEO datasets

To begin, pan-cancer analysis revealed that the majority of cancers expressed lower levels of FOXO1 in tumor tissues compared to adjacent healthy tissues (Figure S2). Next, in the combined GEO datasets, FOXO1 expression was significantly reduced in NPC tissues compared to control tissues (Figure 1A). According to a cutoff value of 10.502, FOXO1 demonstrated high diagnostic accuracy for NPC, with a sensitivity of 0.706 and a specificity of 0.864, and an area under the curve of 0.842 (Figure 1B). As anticipated, early-stage NPC patients (stage I/II) exhibited significantly higher expression of FOXO1 compared with those at advanced-stage patients (stage III/IV) (Figure 1C). Compared to TME subtypes II and III, FOXO1 expression levels were significantly lower in patients with TME subtype I (Figure 1D). In contrast, there was no statistically significant difference in FOXO1 expression among patients with different tumor morphologies (Figure 1E). Interestingly, the relative expression of FOXO1 and EBV genes were negatively correlated in the GSE102349 dataset (Figure 1F). Moreover, FOXO1 was expressed at lower levels in EBV positive NPC43 cells compared to EBV negative NPC43 cells in the GSE218167 dataset (Figure 1G) and in LMP1 positive CNE1 cells compared to LMP1 negative CNE1 cells in the GSE171664 dataset (Figure 1H). We overexpressed LMP1 in CNE1 cells and observed that FOXO1 expression was downregulated upon LMP1 overexpression, which is consistent with our predicted results (Figure 1I). These findings collectively imply that FOXO1 may serve as a possible diagnostic biomarker for NPC, with its expression may be potentially regulated by EBV.

Figure 1 Association between FOXO1 expression and clinical characteristics of NPC. (A) Expression of the FOXO1 gene in NPC tissues and normal tissues in the combined dataset of GSE12452, GSE53819 and GSE61218. (B) ROC curve of FOXO1 for NPC diagnosis. (C) Expression of FOXO1 in the different clinical stages in GSE102349. (D) Expression of FOXO1 in the three TME subtypes in GSE102349. (E) Expression of FOXO1 in the three types of morphology in GSE102349. (F) Correlation between the relative expression of FOXO1 and EBV genes in GSE102349. (G) FOXO1 expression in NPC cell line EBV+ and EBV− NPC43 in GSE218167. (H) Expression of FOXO1 in NPC cell line LMP+ and LMP− CNE1 in GSE171664. (I) Expression of FOXO1 in NPC cell line LMP+ and LMP− CNE1. *, P<0.05; **, P<0.01; ***, P<0.001; ns, no statistical significance. AUC, area under the curve; EBV, Epstein-Barr Virus; FOXO1, forkhead box protein O1; NPC, nasopharyngeal carcinoma; ROC, receiver operating characteristic; TME, tumor microenvironment.

Prognostic value of FOXO1 in NPC

Furthermore, the association between FOXO1 expression and survival outcomes was investigated in the GSE102349 dataset. According to the optimal cutoff value calculated by the survminer R package, the Kaplan-Meier curve showed a significant association between elevated FOXO1 expression and longer PFS in NPC patients (Figure 2A). The areas under the time-dependent ROC curve at 1- and 2-year were 0.693 and 0.650 (Figure 2B). Multivariable Cox analysis identified FOXO1 as an independent protective factor for PFS, with a hazard ratio (HR) of 0.151 and 95% confidence interval (CI) of 0.0387 to 0.590 (Figure 2C). The concordance index of this Cox model was 0.734 (95% CI: 0.605–0.863). Thereafter, a nomogram incorporating patient morphology, clinical stage, and FOXO1 expression was constructed (Figure 2D). The calibration curves depicted satisfactory predictive accuracy for 1- and 2-year PFS (Figure 2E,2F). Altogether, these results proposed that FOXO1 could serve as a potential prognostic marker for NPC.

Figure 2 Prognostic analysis of FOXO1 for NPC in GSE102349. (A) Kaplan-Meier curve for PFS was stratified by high and low FOXO1 expression. (B) Time-dependent ROC curve of FOXO1 for predicting PFS. (C) Multivariate Cox regression analysis of morphology, clinical stage and FOXO1 expression. (D) The plot of the nomogram predicting PFS. (E,F) Calibration plot for nomogram predicting 1- and 2-year PFS. **, P<0.01. AUC, area under the curve; CI, confidence interval; FOXO1, forkhead box protein O1; NPC, nasopharyngeal carcinoma; PFS, progression-free survival; ROC, receiver operating characteristic.

Enrichment analysis of FOXO1 in NPC

GO enrichment analysis revealed that FOXO1 was predominantly associated with immune-related pathways, such as B cell receptor signaling, adaptive immune response, immune response-regulating and response-activating cell surface receptor signaling, and antigen receptor-mediated signaling (Figure 3).

Figure 3 GO enrichment analysis of FOXO1 in NPC. BP, biological process; CC, cell composition; GO, Gene Ontology; MF, molecular function; NPC, nasopharyngeal carcinoma.

On the one hand, KEGG pathway analysis combined with GSEA analysis demonstrated significant enrichment of the high FOXO1 expression group in natural killer cell-mediated cytotoxicity, T and B cell receptor signaling pathway, and programmed cell death ligand 1 (PD-L1) expression and PD-1 checkpoint pathway in cancer (Figure 4A,4B). On the other hand, the group with low FOXO1 expression showed significant enrichment in pathways associated with DNA replication, cell cycle, as well as Hippo and Wnt signaling pathways (Figure 4A,4C). We employed RT-qPCR to investigate the impact of FOXO1 overexpression on the expression levels of Hippo signaling pathway related genes (CCN2, CYR61, MST, TAZ, YAP) in CNE1 (Figure 4D). Our results demonstrated that increased FOXO1 expression markedly stimulated the transcriptional activity of Hippo pathway-related genes. Bioinformatic analysis revealed that FOXO1 downregulation activates the Hippo signaling pathway, concurrently suppressing expression of CCN2, CYR61, TAZ, and YAP. Our experimental results align with these computational findings. FOXO1 overexpression induced synchronous upregulation of CCN2, CYR61, TAZ, and YAP, indicating functional inhibition of the Hippo pathway.

Figure 4 KEGG pathway enrichment analysis of FOXO1 in NPC. (A) Dotplot of KEGG analysis. GSEA plot of KEGG pathway for FOXO1 high (B) and low (C) expression. (D) Expression of Hippo pathway-related genes in NPC cell line CNE1. *, P<0.05; **, P<0.01; ***, P<0.001; ns, no statistical significance. FOXO1, forkhead box protein O1; GSEA, Gene Set Enrichment Analysis; KEGG, Kyoto Encyclopedia of Genes and Genomes; NPC, nasopharyngeal carcinoma.

Association between FOXO1 expression and immune cell infiltration

Enrichment analysis suggested an association between elevated FOXO1 expression and immune-related pathways. Thus, the association between FOXO1 and immune cell infiltration levels was investigated using the EPIC, MCPcounter, quanTIseq, and xCell algorithms (Figure 5A-5D). The NPC patients in the GSE102349 dataset were categorized into high- and low-expression groups according to the median value of FOXO1 relative expression. The results exhibited that the high FOXO1 expression group showed significantly high infiltration levels of B cells, CD8⁺ T cells, CD4⁺ T cells, and macrophages compared to the low FOXO1 expression group.

Figure 5 The infiltration of immune cells in the high and low expression of FOXO1 groups according to the analyses of EPIC (A), MCPcounter (B), quanTIseq (C) and xCell (D) algorithms. *, P<0.05; **, P<0.01; ***, P<0.001; ns, no statistical significance. EPIC, Estimating the Proportion of Immune and Cancer cells; FOXO1, forkhead box protein O1; MCPcounter, Microenvironment Cell Populations-counter; quanTIseq, Quantitative Transcriptome-based Tumor Immune cell Quantification; xCell, Extended Cell type Enumeration.

Additionally, a robust positive association was found between FOXO1 expression and multiple immune-related scores in NPC. Specifically, the xCell algorithm demonstrated a significant association between elevated FOXO1 expression and increased immune, stromal, and microenvironment scores (Figure 6A-6C). Likewise, the ESTIMATE algorithm identified correlations between FOXO1 expression and the immune score and stromal score (Figure 6D-6F). Similarly, the IPS algorithm implied that FOXO1 expression was positively associated with the scores for effector cell, major histocompatibility complex (MHC), and immune checkpoint, while negatively correlated with the immunosuppressive cell score (Figure 6G-6J). Finally, FOXO1 expression showed a significant positive correlation with the key immune checkpoint genes like programmed cell death 1 (PDCD1), cytotoxic T-lymphocyte-associated antigen 4 (CTLA4), T cell Immunoreceptor with Ig and ITIM domains (TIGIT), and B and T lymphocyte attenuator (BTLA) (Figure 6K-6N).

Figure 6 The association between FOXO1 expression and immune scores. The immune score (A), stromal score (B) and microenvironment score (C) was calculated by the xCell algorithm. The immune score (D), stromal score (E) and ESTIMATE score (F) was calculated by the ESTIMATE algorithm. The MHC score (G), effector cell score (H), immunosuppressive cell score (I) and immune checkpoint score (J) was calculated by the IPS algorithm. The correlation between the expression of FOXO1 and immune checkpoint genes like PDCD1 (K), CTLA4 (L), TIGIT (M) and BTLA (N). (O) Kaplan-Meier curve for the overall survival of melanoma patients who was stratified by high and low expression of FOXO1 in the GSE78220 dataset. ESTIMATE, Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data; FOXO1, forkhead box protein O1; IPS, immunophenoscore; MHC, major histocompatibility complex; xCell, Extended Cell type Enumeration.

Moreover, the pan-cancer analysis indicated that FOXO1 expression was positively associated with the infiltration of T cells, B cells, and macrophages in most cancers (Figures S3-S5). Consistently, FOXO1 expression showed a positive correlation with immune checkpoint gene expression in these cancers (Figure S6).

Given the lack of publicly available immunotherapy datasets for NPC, we analyzed the GSE78220 melanoma cohort. Results exposed that melanoma patients with high FOXO1 expression levels and receiving anti-PD-1 checkpoint inhibition therapy exhibited longer overall survival than those with low FOXO1 expression (Figure 6O).

Overexpression of FOXO1 suppressed proliferation, migration, and colony formation in NPC cells

The transcriptomic and proteomic expression level of FOXO1 was assessed in NPC cell lines and biopsy tissues. FOXO1 expression, at both the mRNA and protein levels, was significantly reduced in CNE1 and 5-8F cells compared to NP69 cells, as well as in NPC tissues compared to rhinitis tissues (Figure 7A-7F).

Figure 7 FOXO1 expression in NPC cell lines and tissues compared to control samples. (A) Comparison of FOXO1 mRNA expression levels between NPC cells lines (5-8F and CNE1) and NP69. (B) Comparison of FOXO1 mRNA expression levels between NPC tissues and rhinitis tissues. (C,D) Comparison of FOXO1 protein expression level between NPC cells lines (CNE1 and 5-8F) and NP69. (E,F) Comparison of FOXO1 protein expression level between NPC tissues and rhinitis tissues. The immune response was visualized using a diaminobenzidine (DAB) substrate for color development and nuclei were counterstained with hematoxylin. *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001. FOXO1, forkhead box protein O1; IHC, immunohistochemistry; NPC, nasopharyngeal carcinoma.

The CCK-8 assay revealed that FOXO1 overexpression markedly suppressed the proliferative capacity of 5-8F and CNE1 cells (Figure 8A,8B). Additionally, the colony formation assay showed significant inhibition in colony forming ability upon FOXO1 overexpression (Figure 8C,8D). The wound healing assay demonstrated reduced cell migratory ability with FOXO1 overexpression compared to the negative control (Figure 8E-8G). The Transwell assay revealed a marked reduction in the invasive capacity of NPC cells with FOXO1 overexpression (Figure 8H,8I). Taken together, these findings support the role of FOXO1 as a tumor suppressor in NPC.

Figure 8 FOXO1 overexpression inhibited the proliferation, colony formation, migration, and invasion of NPC cell lines. (A,B) CCK-8: overexpression of FOXO1 inhibited the proliferation in 5-8F and CNE1 cells. (C,D) Colony formation assay: overexpression of FOXO1 inhibited the colony formation in 5-8F and CNE1 cells. Clones were visualized by 0.1% crystal violet staining after fixation. (E-G) Wound healing assay: overexpression of FOXO1 inhibited the migration in 5-8F and CNE1 cells. (H,I) Transwell invasion assay: overexpression of FOXO1 inhibited the invasion in 5-8F and CNE1 cells. Invaded cells were fixed and stained with 0.1% crystal violet for visualization. *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001. FOXO1, forkhead box protein O1; NPC, nasopharyngeal carcinoma.

Discussion

Preliminary investigations in recent years have explored the potential of FOXO1 as a therapeutic or diagnostic target in NPC. Concurrently, research into FOXO1’s functional significance and molecular mechanisms in NPC has gained significant momentum. Integrating findings from Zhao, Li, and colleagues reveals key insights into FOXO1 function in NPC. These studies highlight FOXO1 as a pivotal molecular hub in NPC pathogenesis. Its functional inactivation consistently promotes malignant phenotypes, including enhanced metastasis, evasion of apoptosis, and therapy resistance. FOXO1 is regulated upstream by TFs, non-coding RNAs, and protein-protein interactions. Downstream, FOXO1 exerts pleiotropic effects as a transcriptional regulator, modulating critical pathways involved in apoptosis, metastasis, DNA repair, and metabolism. This positions FOXO1 as a central node with significant therapeutic target potential in NPC (23-25,27).

Our bioinformatics analysis and experimental results demonstrated that the level of FOXO1 mRNA in EBV LMP1-positive cells was significantly reduced compared to those in LMP1-negative cells. Previous studies have established that LMP1 interacts with the regulatory subunit p85 of PI3K via its CTAR1 domain, leading to the constitutive activation of the PI3K/AKT signaling pathway (28,29). FOXO1 is a critical direct substrate of AKT; upon activation of the PI3K/AKT pathway, FOXO1 undergoes phosphorylation, resulting in its translocation from the nucleus to the cytoplasm and subsequent degradation through the ubiquitin-proteasome pathway (30,31). Furthermore, existing literature suggests that LMP1 can downregulate FOXO1 expression (32). These findings imply that in NPC, LMP1 may facilitate the downregulation of FOXO1 expression via the PI3K/AKT signaling pathway. We validated this conclusion in CNE1 cells using RT-qPCR. Moreover, given that LMP1 protein is expressed in only approximately 50% of NPC cases (33), it is likely that additional factors, such as DNA methylation or m6A RNA modification, are involved in the upstream regulation of FOXO1. The dysregulation of FOXO1 inevitably involves other upstream mechanisms, a finding that is consistent with the complexity of FOXO1 regulation observed in other cancers (8,34).

Functional enrichment analysis and RT-qPCR validation revealed that the downregulation of FOXO1 in NPC is closely associated with cell cycle dysregulation and the abnormal activation of the Wnt/β-catenin and Hippo signaling pathways. We hypothesize that the inactivation of FOXO1 releases its inhibitory effect on key pro-proliferative and pro-metastatic signaling pathways. Furthermore, the upregulation of FOXO1 can significantly suppress the expression of cell cycle-related genes. Previous studies have demonstrated that activated FOXO1 promotes expression of cyclin-dependent kinase inhibitors p21Cip1 and p27Kip1, inducing G1/S phase arrest in non-small cell lung cancer (8,35). In NPC, the deficiency of FOXO1 may directly facilitate cell cycle progression, thereby driving cell proliferation. Furthermore, FOXO1 inhibits cell proliferation and migration in osteosarcoma, pancreatic cancer, and other malignancies by suppressing the Wnt/β-catenin pathway (35-37). Recent studies have demonstrated that FOXO1 overexpression suppresses tumor invasion and migration in multiple malignancies, including bladder cancer and small-cell lung carcinoma (38-40). In clear cell renal cell carcinoma, ACE loss drives malignant tumor progression via aberrant AKT hyperphosphorylation and subsequent inhibition of the transcriptional activity and tumor-suppressive function of downstream FOXO1 (41). Our findings in NPC suggested that the inactivation of FOXO1 may activate this pathway, thereby enhancing the invasive and metastatic potential of tumor cells. Our experiment has preliminarily confirmed this viewpoint. Additionally, Hippo signaling pathway activation leads to YAP inactivation, consequently inhibiting FOXO1 activity and antioxidant gene expression (42). However, further investigation is required to elucidate how the downregulation of FOXO1 impacts Hippo signaling and its role in tumor progression within the context of NPC. Additionally, the transcriptional inhibition of FOXO1 mediated by Homeobox B2 (HOXB2) results in defects in DNA damage repair, which serves as a direct example of how FOXO1 inactivation can promote therapeutic resistance (25). FOXO1, as a key transcriptional regulatory hub, its inactivation leads to widespread disruption of downstream target gene networks and is a common driving factor for malignant phenotypes in various cancers, such as prostate cancer and gastric cancer (43,44). This study systematically correlated FOXO1 inactivation with key pathways in NPC, thereby providing a more solid experimental basis for its role as a “molecular switch”.

In addition, this study uncovered a significant correlation between FOXO1 expression and the TIME in NPC. Specifically, tumors with high FOXO1 expression exhibited stronger infiltration of B cells, CD8⁺ T cells, CD4⁺ T cells, and macrophages. These tumors also demonstrated higher immune scores and increased expression of key immune checkpoint receptors, such as PD-1 and CTLA-4. FOXO1 plays a crucial role in the differentiation, function, and survival of immune cells, including CD8⁺ T cells and macrophages (45-47). It can regulate the expression of chemokines, antigen-presenting molecules, and immune regulatory molecules in tumor cells (34,48). Therefore, the expression level of FOXO1 in tumor cells may profoundly influence the composition and activity of the TIME. Our observations in melanoma patients provided preliminary but crucial clinical clues, consistent with other studies reporting that FOXO1 activity affected the response to immune therapy (19,49). Based on these findings, we propose a key hypothesis: the expression level of FOXO1 in NPC tumor cells may serve as a biomarker for predicting the responsiveness to immune checkpoint inhibitor (ICI) treatment. Low FOXO1 expression may indicate an immunosuppressive microenvironment and poor response to monotherapy with ICIs, while high FOXO1 expression may suggest more active immune infiltration and a potentially better response to ICIs.

The absence of FOXO1 severely curtailed the development of Foxp3(+) regulatory T (Treg) cells, and those that developed were nonfunctional in vivo. Moreover, it was found that FOXO1 regulated PD-L1 transcription in a β-catenin-independent or -dependent manner (36,50). Our analysis indicated that FOXO1 held substantial potential for clinical applications in NPC. Assessment of FOXO1 expression levels in tumor tissues or through circulating biomarkers could aid in identifying NPC patients who were more likely to benefit from ICI therapies-such as anti-PD-1 or anti-CTLA-4, thereby serving as a predictive biomarker. Moreover, targeting mechanisms underlying FOXO1 inactivation—such as inhibiting of the PI3K/AKT pathway or blockade of LMP1 function—might restore FOXO1 activity. This restoration potentially reshaped the TIME and enhance NPC sensitivity to ICI therapies. Additionally, directly activating of FOXO1 or its downstream anti-cancer pathways could uncover novel therapeutic targets and pave the way for developing innovative treatment strategies.

This study integrated bioinformatics and cellular experiments to further confirm the tumor suppressive function of FOXO1 in NPC and FOXO1 expression could serve as a potential independent or combinatorial biomarker to develop more precise prognostic prediction models. Integrating FOXO1 status assessment with other clinicopathological features and molecular markers would facilitate the identification of patient subgroups at high risk of recurrence or metastasis. This enables more refined risk stratification, allowing for tailored management strategies such as intensified surveillance or more aggressive adjuvant therapy for high-risk individuals. More importantly, we propose the important role of the LMP1-PI3K/AKT-FOXO1 inhibition axis in NPC and extend the function of FOXO1 to the field of tumor immune regulation. We propose a new paradigm of “FOXO1 as a key hub connecting EBV infection, tumor cell malignant behavior, and immune microenvironment regulation.” Future research should explore incorporating FOXO1 status into therapeutic algorithms to guide personalized treatment selection. The ultimate goal is to optimize the clinical management of NPC patients and improve their survival outcomes.

Nevertheless, some limitations of this study merit acknowledgment. Firstly, the diagnostic and prognostic significance of FOXO1 in NPC was assessed using retrospective GEO data, and thus, prospective cohort studies are warranted to validate its clinical applicability. Secondly, additional in vivo and in vitro experiments are necessitated to verify the link between FOXO1 and immune infiltration. Finally, mechanistic research is necessary to determine FOXO1’s role and function in NPC.

Future research should focus on elucidating the regulatory mechanisms of the LMP1-PI3K/AKT-FOXO1 axis on downstream pathways, including the cell cycle, Wnt, and Hippo signaling pathways, as well as specific immune regulatory targets, using both in vitro and in vivo models. Additionally, further investigation into the mechanisms by which FOXO1 modulates tumor immunity in NPC is warranted. Strengthen clinical translation, validate the value of FOXO1 expression as a predictive biomarker for immune therapy response in a larger cohort of NPC patients, evaluate the synergistic anti-tumor effect of targeting the FOXO1 inactivation pathway in combination with ICI, and explore treatment strategies that directly activate FOXO1 or its key downstream effector molecules.

Conclusions

In NPC, FOXO1 exerts a tumor suppressive function and holds potential as a diagnostic and prognostic biomarker, as well as a predictor of immune therapy response. Restoring FOXO1 function or leveraging its expression level to guide immunotherapy represents a highly promising new direction for the precision treatment of NPC. The comprehensive framework and specific hypotheses proposed in this study have laid a solid foundation for further exploration of the underlying mechanisms and for clinical translation research.

Acknowledgments

We would like to thank the Guangxi Health Commission Key Laboratory of Molecular Epidemiology of Nasopharyngeal Carcinoma for providing us with the experimental site, laboratory equipment, and technical support.

Footnote

Reporting Checklist: The authors have completed the TRIPOD and MDAR reporting checklists. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2890/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2890/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2890/prf

Funding: This work was supported by grants from National Natural Science Foundation of China (No. 82360618), Guangxi Natural Science Foundation (Nos. 2024GXNSFAA010417 and 2020GXNSFAA297105), and Liuzhou Science and Technology Project (No. 2024YB0103A021).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2890/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 Wuzhou Red Cross Hospital (Approval No. LL2022-49). Written informed consent was obtained from all individual participants prior to specimen collection.

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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