TRAF4 promotes nasopharyngeal carcinoma progression by stabilizing SETDB1 to suppress mitochondrial apoptosis

Abstract

Nasopharyngeal carcinoma (NPC) is a malignant tumor with high metastatic potential. Tumor necrosis factor receptor-associated factor 4 (TRAF4) has been identified as an oncogene in various cancers; however, its specific role and molecular mechanism in NPC progression, particularly regarding oxidative stress regulation, remain largely unexplored. In this study, TRAF4 and SETDB1 expression levels were analyzed in NPC cell lines using RT-qPCR and Western blotting. Loss-of-function and gain-of-function assays were performed to evaluate cell proliferation and apoptosis in vitro. The regulatory interaction between TRAF4 and SETDB1 was investigated via co-immunoprecipitation and ubiquitination assays. Mitochondrial function was assessed using MitoSOX, JC-1, and MitoTracker staining to monitor reactive oxygen species (ROS) generation and membrane potential. TRAF4 was significantly upregulated in NPC cell lines compared to immortalized nasopharyngeal epithelial cells. Silencing TRAF4 markedly inhibited NPC cell proliferation and induced apoptosis. Mechanistically, TRAF4 functioned as a critical stabilizer of SETDB1; TRAF4 depletion reduced SETDB1 protein levels by altering its ubiquitination status. Furthermore, SETDB1 knockdown triggered mitochondrial dysfunction, characterized by ROS accumulation, membrane potential collapse, and Cytochrome c release, which could be reversed by the ROS scavenger N-acetyl-L-cysteine (NAC). Importantly, overexpression of SETDB1 rescued the proliferation inhibition and mitochondrial apoptosis induced by TRAF4 silencing. Our findings demonstrate that TRAF4 promotes NPC progression by stabilizing SETDB1 to suppress ROS-dependent mitochondrial apoptosis, highlighting the TRAF4/SETDB1 axis as a promising therapeutic target for NPC treatment.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1007/s11010-026-05651-6.

Introduction

Nasopharyngeal carcinoma (NPC) is a prevalent malignant tumor of the head and neck, with a distinct geographical distribution characterized by high incidence rates in Southern China, North Africa, and Alaska [1]. Although NPC is radiosensitive and chemosensitive, the efficacy of current treatments is often compromised by locoregional recurrence and distant metastasis, resulting in a 5-year overall survival rate of approximately 50–60% for advanced cases [2]. Therefore, elucidating the underlying molecular mechanisms of NPC pathogenesis is critical for identifying novel therapeutic targets and improving clinical outcomes.

Reactive oxygen species (ROS) are metabolic byproducts of cellular respiration that play a dual role in biological systems. Low to moderate levels of ROS act as signaling molecules that support cell proliferation and survival. However, excessive ROS accumulation induces oxidative stress, which causes irreversible damage to lipids, proteins, and DNA. Compared to normal cells, cancer cells exhibit elevated basal ROS levels due to metabolic reprogramming, oncogene activation, and hypoxia [3]. Consequently, cancer cells rely heavily on antioxidant pathways to maintain redox homeostasis [4]. This elevated basal state renders cancer cells more vulnerable to further ROS induction; pushing ROS levels beyond a critical threshold can trigger cytotoxicity and apoptosis [5]. In the context of NPC, several agents have been shown to exert anti-tumor effects via ROS-dependent pathways. For instance, lucialdehyde B inhibits CNE2 cell proliferation by inducing mitochondria-dependent apoptosis [6]; Oridonin promotes apoptosis via ROS generation [7]; and 8-formylophiopogonanone B induces apoptosis in CNE-1 cells through an ROS-mediated mechanism [8]. These findings suggest that disrupting redox homeostasis to trigger the mitochondrial apoptotic pathway represents a promising therapeutic strategy against NPC.

Tumor necrosis factor receptor-associated factor 4 (TRAF4), a member of the TRAF protein family, functions as a key signal transducer in various physiological and pathological processes. There is growing evidence that TRAF4 acts as an oncogene. For example, TRAF4 stabilizes CAV1 via ubiquitination to activate AKT/ERK1/2 signaling in glioma [9], and promotes invasion and metastasis in prostate cancer by ubiquitinating TrkA [10]. Conversely, TRAF4 silencing sensitizes neuroblastoma cells to retinoic acid by inducing apoptosis [11]. In NPC, TRAF4 is significantly upregulated in tumor tissues, and knocking it down notably enhances radiosensitivity [12]. Although these studies suggest that TRAF4 is involved in NPC cell survival and therapeutic resistance, the role of TRAF4 in regulating NPC progression through ROS-mediated mitochondrial pathways remains largely unknown.

TRAF4 possesses E3 ubiquitin ligase activity. Previous studies have demonstrated that TRAF4 interacts with the Tudor domain of SET domain bifurcated 1 (SETDB1), promoting SETDB1 stability and function via non-canonical ubiquitination, thereby driving glioblastoma proliferation [13]. Interestingly, SETDB1 depletion has been reported to induce intracellular ROS accumulation [14]. Given that SETDB1 is upregulated in NPC and its inhibition suppresses cell proliferation and migration [15], we hypothesize a novel regulatory axis. TRAF4 promotes NPC progression and inhibits apoptosis by stabilizing SETDB1, which suppresses ROS-dependent mitochondrial apoptotic pathways. The aim of this study is to validate this hypothesis and provide new insights into the potential of targeting the TRAF4/SETDB1/ROS axis for NPC therapy.

Materials and methods

Cell lines and cell culture

Human NPC cell lines (C666-1, NPC/HK-1, and 5–8F) and the immortalized human nasopharyngeal epithelial cell line NP69 were purchased from iCell Bioscience Inc. (Shanghai, China). NP69 cells were cultured in a specialized medium (iCell-h431-001b; iCell Bioscience), whereas C666-1, NPC/HK-1, and 5–8F cells were maintained in RPMI-1640 medium (Procell, China) supplemented with 10% fetal bovine serum (FBS; TransGen Biotech, China) and 1% penicillin–streptomycin (KeyGen Biotech, China).

All cells were cultured in a humidified incubator (Thermo Fisher Scientific) at 37 °C and 5% CO₂. Cells were passaged when reaching approximately 80% confluence. Briefly, cells were washed with phosphate-buffered saline (PBS) and digested with 0.25% trypsin (Crondabio). Digestion was terminated with complete medium, followed by centrifugation at 1000 rpm for 5 min, and cells were subcultured at a ratio of 1:2.

Cell transfection

Cell transfection was performed using Lipofectamine™ 2000 (11668-019, Invitrogen, USA) according to the manufacturer’s instructions. When cells reached 70–80% confluence, they were washed with PBS and cultured in serum-free Opti-MEM medium (31985-070, Gibco, USA). Plasmid DNA (1 µg) and Lipofectamine™ 2000 were separately diluted in Opti-MEM at a ratio of 1:2–1:3 and incubated for 5 min at room temperature before mixing. The mixture was further incubated for 20 min and then added to the cells. After 4–6 h of incubation, the medium was replaced with fresh complete medium without antibiotics, and cells were cultured for subsequent experiments. Subsequently, the cells were treated with 10 µM G132 (HY-13259, MCE, Shanghai, China) for 4 h. HK-1 cells were transfected for 24 h and then incubated with 10 mmol/L N-acetyl-L-cysteine (NAC, S20137-25g, Yuanye) for 1 h prior to subsequent assays.

Quantitative real-time PCR (qRT-PCR)

Total RNA was extracted from cells using TRIzol reagent (Vazyme, China) following the manufacturer’s protocol. RNA was isolated by chloroform extraction. For reverse transcription, 2 µg of total RNA was used to synthesize cDNA with the Hifair^® AdvanceFast 1st Strand cDNA Synthesis SuperMix (Yeasen, China). qRT-PCR was performed using Hieff UNICON^® ColorGPS qPCR SYBR Green Master Mix (Yeasen) on a Roche LightCycler^® 480 II system. Relative gene expression levels were calculated using the 2^{−ΔΔ𝐶𝑡} method with β-actin as the internal control. The primer sequences are provided in the Table S1.

Western blot analysis

Cells were lysed in RIPA buffer containing 1 mM PMSF (Beyotime, China) on ice. Lysates were centrifuged at 12,000 rpm for 20 min at 4℃ and the supernatants were collected. Protein concentrations were determined using a BCA Protein Assay Kit (Biosharp, China). Equal amounts of protein were separated by SDS-PAGE and transferred onto PVDF membranes (Millipore, USA). Membranes were blocked with 5% non-fat milk for 1 h at room temperature and incubated overnight at 4℃ with primary antibodies against TRAF4, SETDB1, RIPK3, COX IV, Cytochrome c (Cytc), BCL2, Bax, cleaved caspase3 and β-actin (Proteintech, USA). After washing with TBST, membranes were incubated with HRP-conjugated secondary antibodies (1:10,000) for 30 min at room temperature. Protein signals were detected using enhanced chemiluminescence (ECL; Tanon, China) and visualized with a Tanon 5200 imaging system. The relative protein expression levels were quantified by densitometry using ImageJ.

Co-immunoprecipitation (Co-IP)

Co-immunoprecipitation was conducted using a commercial IP/Co-IP kit (Absin, China). Cells were washed with pre-chilled PBS and lysed in lysis buffer on ice for 5 min. Cell lysates were sonicated on ice (35–40% power, three cycles) and centrifuged at 14,000 × g for 10 min at 4 ℃.

Approximately 500 µL of supernatant was incubated with 1–5 µg of specific antibody or control IgG overnight at 4 ℃. Protein A/G magnetic beads were then added and incubated for 1–3 h. The immunoprecipitates were washed three times with wash buffer, resuspended in SDS loading buffer, boiled at 95–100 °C for 5 min, and subjected to Western blot analysis.

Cell functional assays

Cell viability assay

Cell viability was assessed using a CCK-8 kit (Beyotime, China). Cells were seeded into 96-well plates (100 µL/well) and allowed to adhere overnight. After drug treatment, 10 µL of CCK-8 solution was added to each well and incubated at 37 ℃ for 1–4 h. Absorbance at 450 nm was measured using a microplate reader (Thermo MK3).

Colony formation assay

Exponentially growing cells were seeded at a density of 1200 cells per dish and cultured for 10–14 days, with medium replaced every 2–3 days. Colonies were fixed with paraformaldehyde, stained with 0.1% crystal violet (Solarbio, China), photographed, and counted.

Apoptosis analysis

Cell apoptosis was evaluated using an Annexin V-FITC/PI Apoptosis Detection Kit (Vazyme, China). Cells were harvested using EDTA-free trypsin, washed with PBS, and resuspended in 300 µL binding buffer. Annexin V-FITC (10 µL) and PI (5 µL) were added, followed by incubation for 15 min in the dark at room temperature. Apoptotic cells were analyzed by flow cytometry (Beckman CytoFLEX).

Mitochondrial function assays

Mitochondrial membrane potential (ΔΨm)

ΔΨm was assessed using an enhanced JC-1 staining kit (C2003S, Beyotime). Cells were incubated with JC-1 working solution at 37℃ for 30 min, washed with PBS, and observed under a fluorescence microscope (Olympus CKX53). ΔΨm depolarization was evaluated by quantifying the transition from red (J-aggregates, polarized) to green (JC-1 monomers, depolarized) fluorescence. The collapse of ΔΨm was quantified by calculating the ratio of green to red fluorescence intensity (Green/Red) using ImageJ.

Mitochondrial superoxide detection

Mitochondrial ROS were detected using MitoSOX™ Red (Beyotime). Cells were incubated with the staining solution at 37 ℃ for 30 min, washed with PBS, and examined under a fluorescence microscope.

Mitochondrial tracking

Mitochondria were labeled using MitoTracker Red CMXRos (Beyotime). Cells were incubated with 200 nM MitoTracker working solution at 37℃ for 15–30 min, followed by replacement with fresh medium and fluorescence microscopy observation.

scRNA-seq data analysis

Data from GSE120926 were downloaded from the GEO database. This data encompasses primary tumors or lymph node metastases from 19 EBV + NPC patients and 7 non-cancerous nasopharyngeal samples from normal subjects. The R package Seurat (v5.0.1) was utilized for quality control and downstream analysis. Cells expressing fewer than 200 genes, genes expressed in fewer than 3 cells, and cells with > 20% mitochondrial gene expression were excluded. Gene expression maps for different groups were plotted using the “VlnPlot” function.

Statistical analysis

All statistical analyses were performed using GraphPad Prism software (version 9.0; GraphPad Software, USA) or R (version 4.3.3). Data are presented as the mean ± standard deviation (SD) from at least three independent experiments unless otherwise stated. Comparisons between two groups were conducted using the two-tailed Student’s t-test. For comparisons among multiple groups, one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test was applied. For experiments involving two independent variables, two-way ANOVA was used where appropriate. For the MitoSOX™ Red and MitoTracker assays, representative images were captured, and the relative mitochondrial ROS levels and mitochondrial mass were quantified by calculating the mean fluorescence intensity (MFI) using ImageJ software (NIH, USA). A P value < 0.05 was considered statistically significant.

Results

TRAF4 is significantly upregulated in NPC cell lines

To characterize the expression profile of TRAF4 in NPC, we assessed its mRNA and protein levels in the immortalized nasopharyngeal epithelial cell line NP69 and three NPC cell lines (C666-1, NPC/HK-1 and 5–8F) using RT-qPCR and Western blot analyses. The results demonstrated that TRAF4 mRNA expression was significantly upregulated in all three NPC cell lines compared to NP69 cells. However, at the protein level, while TRAF4 was markedly upregulated in C666-1 and NPC/HK-1 cells, it showed a decrease in 5–8F cells. Notably, the upregulation was most pronounced in HK-1 cells (Fig. 1A, B). These results imply that the abnormal overexpression of TRAF4 may contribute to the development and progression of NPC.

Fig. 1.

TRAF4 expression in NPC cell lines. A The mRNA expression levels of TRAF4 in the immortalized nasopharyngeal epithelial cell line (NP69) and three NPC cell lines (C666-1, NPC/HK-1 and 5–8F) were determined by RT-qPCR. B The protein expression levels of TRAF4 in NP69, C666-1, NPC/HK-1, and 5–8F cell lines were analyzed by Western blot analysis (left panel) and quantitatively analyzed (right panel). β-actin was used as an internal loading control. Data are presented as mean ± SD. **P < 0.01, ***P < 0.001 vs. NP69 group

Knockdown of TRAF4 suppresses NPC HK-1 cell proliferation and induces apoptosis

To investigate the biological function of TRAF4, we constructed TRAF4-specific small interfering RNAs (siRNAs) and evaluated their knockdown efficiency. In HK-1 cells, RT-qPCR and Western blot analyses identified siRNA-TRAF4-2 as the most effective sequence (Fig. 2A, B), which was selected for subsequent experiments. Functional assays revealed that, compared with the negative control (siRNA-NC) group, TRAF4 silencing significantly impaired cell viability, as determined by the CCK-8 assay (Fig. 2C), and markedly reduced colony-forming ability (Fig. 2D). Furthermore, flow cytometric analysis indicated a significant increase in the apoptotic rate following TRAF4 knockdown (Fig. 2E). These phenomena were consistently observed in C666-1 cells (Fig. S1). Taken together, these data suggest that TRAF4 plays a role in promoting the proliferation and inhibiting the apoptosis of NPC cells.

Fig. 2.

Knockdown of TRAF4 inhibits proliferation and induces apoptosis in HK-1 cells. A, B HK-1 cells were transfected with negative control siRNA (si-NC) or TRAF4-specific siRNA. The knockdown efficiency was verified by RT-qPCR (A) and Western blotting (B). (C) Cell viability was assessed using the CCK-8 assay. D Colony formation assays were performed to evaluate long-term proliferative capacity. Representative images (left) and quantification (right) are shown. E Apoptosis rates were determined by Annexin V-FITC/PI staining and flow cytometry. Data are presented as mean ± SD. **P < 0.01, ***P < 0.001 vs. siRNA-NC group

TRAF4 maintains SETDB1 stability via a proteasome-dependent mechanism

To elucidate the molecular mechanism underlying TRAF4-mediated oncogenesis, we examined its regulatory effect on SETDB1 in HK-1 cells. RIPK3 (Receptor-interacting serine/threonine-protein kinase 3) is essential for the cell death pathway called necroptosis [16]. Western blot analysis showed that TRAF4 knockdown led to a substantial decrease in SETDB1 protein levels, accompanied by a significant upregulation of RIPK3 (Fig. 3A). To explore whether this regulation occurs at the post-translational level, we performed a ubiquitination assay. As shown in Fig. 3B, co-transfection of HA-Ub with siRNA-TRAF4 resulted in a marked reduction in global ubiquitination levels compared to the HA-Ub control group. Treatment with the proteasome inhibitor MG132 successfully rescued the degradation of SETDB1 induced by TRAF4 silencing (Fig. 3C). Together, these results indicate that SETDB1 degradation induced by TRAF4 depletion is proteasome-dependent, implying that TRAF4 may be involved in maintaining SETDB1 stability through the ubiquitin-proteasome pathway, although the specific direct ubiquitination requires further investigation.

Fig. 3.

TRAF4 regulates SETDB1 stability through ubiquitination. A Western blot analysis of SETDB1 and RIPK3 protein levels in HK-1 cells following TRAF4 knockdown. B Ubiquitination assay. Cells were co-transfected with HA-Ub plasmids and si-TRAF4. Cell lysates were immunoprecipitated (IP) with anti-SETDB1 antibody, followed by immunoblotting (IB) with anti-HA antibody to detect ubiquitinated SETDB1 levels. IgG was used as a negative control. C Western blot analysis and quantification of SETDB1 protein levels in HK-1 cells following TRAF4 knockdown, in the presence or absence of MG132 treatment. ***P < 0.001 vs. siRNA-NC group

Silencing SETDB1 inhibits proliferation and promotes apoptosis in HK-1 cells

To validate the functional role of SETDB1 in HK-1 cells, we silenced SETDB1 expression using specific siRNAs. Among the candidates, siRNA-SETDB1-2 exhibited the highest knockdown efficiency and was used for further studies (Fig. 4A, B). Similar to the phenotype observed with TRAF4 knockdown, SETDB1 silencing significantly decreased cell viability (Fig. 4C), suppressed colony formation (Fig. 4D), and markedly increased the percentage of apoptotic cells compared to the control group (Fig. 4E). These findings confirm that SETDB1 functions as an oncogene in HK-1 cells.

Fig. 4.

Silencing SETDB1 suppresses HK-1 cells growth and promotes apoptosis. A, B The efficiency of SETDB1 knockdown in HK-1 cells was confirmed by RT-qPCR (A) and Western blotting (B). C The effect of SETDB1 knockdown on cell viability was measured by CCK-8 assay. D Representative images and statistical analysis of colony formation assays. E Flow cytometry analysis of cell apoptosis in si-NC and si-SETDB1 groups. Data are presented as mean ± SD. **P < 0.01, ***P < 0.001 vs. siRNA-NC group

SETDB1 knockdown triggers the mitochondrial apoptotic pathway

To determine the mechanism of apoptosis induced by SETDB1 depletion, we focused on mitochondrial function in HK-1 cells. Staining with MitoSOX™ Red revealed that SETDB1 knockdown significantly elevated mitochondrial ROS levels (Fig. 5A). JC-1 staining assays demonstrated a significant collapse of the ΔΨm in SETDB1-silenced cells (Fig. 5B). Additionally, MitoTracker staining indicated an increase in mitochondrial staining intensity (Fig. 5C). Consistent with these findings, Western blot analysis showed that SETDB1 knockdown increased the expression of RIPK3 and cytosolic Cytc, while decreasing mitochondrial Cytc levels (Fig. 5D). These data suggest that SETDB1 silencing promotes Cytc release from the mitochondria to the cytosol, thereby activating the mitochondria-dependent apoptotic pathway in HK-1 cells.

Fig. 5.

SETDB1 knockdown activates the mitochondrial apoptotic pathway in HK-1 cells. A Mitochondrial ROS levels were detected using MitoSOX™ Red staining. Representative fluorescence images (left) and relative fluorescence intensity quantification (right) are shown. Scale bar = 50 μm. B Mitochondrial membrane potential (ΔΨm) was assessed by JC-1 staining. An increase in the green/red fluorescence ratio indicates mitochondrial depolarization. Scale bar = 50 μm. C Mitochondrial mass/activity was visualized using MitoTracker Red CMXRos staining. Representative images and fluorescence intensity quantification are shown. Scale bar = 20 μm. D Western blot analysis of RIPK3 expression and the distribution of Cytc in the mitochondrial and cytosolic fractions. COX IV and β-actin were used as loading controls for mitochondrial and cytosolic proteins, respectively. The fluorescence intensity (MitoSOX and MitoTracker), the green/red fluorescence ratio (JC-1), and relative protein expression levels were all quantified using ImageJ software. Data are presented as mean ± SD. **P < 0.01, ***P < 0.001 vs. siRNA-NC group

The ROS scavenger NAC reverses the anti-tumor effects induced by SETDB1 silencing

To verify whether ROS accumulation is critical for SETDB1 knockdown-induced apoptosis, we treated HK-1 cells with the ROS scavenger NAC. CCK-8 assays showed that the reduced cell viability caused by siRNA-SETDB1 was partially restored by NAC treatment (Fig. 6A). Consistent results were observed in colony formation assays (Fig. 6B). Furthermore, flow cytometry analysis demonstrated that NAC treatment significantly attenuated the apoptosis induced by SETDB1 silencing (Fig. 6C). These results suggest that the pro-apoptotic effect of SETDB1 knockdown is mediated, at least in part, by ROS accumulation.

Fig. 6.

The ROS scavenger NAC reverses SETDB1 knockdown-induced apoptosis. HK-1 cells were transfected with si-SETDB1 and treated with or without N-acetyl-L-cysteine (NAC). A Cell viability was measured by CCK-8 assay. B Colony formation capacity was assessed. C Apoptosis rates were analyzed by flow cytometry. Data are presented as mean ± SD (n = 3). **P < 0.01, ***P < 0.001 vs. Control group; ##P < 0.01 vs. siRNA-SETDB1 group

TRAF4 modulates the mitochondrial apoptotic pathway via SETDB1

Furthermore, to validate the clinical relevance of our findings, we incorporated additional analyses using the publicly available GSE120926 dataset. Consistent with our in vitro experimental results, this analysis revealed that the expression levels of both TRAF4 (p < 0.001) and SETDB1 (p = 0.016) were significantly upregulated in NPC tumor tissues compared to non-malignant nasopharyngeal tissues (Fig. S2).

To confirm the causal relationship between TRAF4 and SETDB1, we performed rescue experiments by overexpressing SETDB1 in TRAF4-silenced HK-1 cells. The overexpression efficiency was verified by RT-qPCR and Western blot (Fig. 7A, B). Functional analysis showed that TRAF4 knockdown significantly increased mitochondrial ROS levels, decreased ΔΨm, and altered mitochondrial activity. However, these mitochondrial dysfunctions were significantly reversed by SETDB1 overexpression (Fig. 7C–E). Moreover, Western blot analysis confirmed that re-introduction of SETDB1 reversed the TRAF4 knockdown-induced upregulation of RIPK3, Bax, Bcl-2, cleaved-Caspase 9 and the cytosolic release of Cytc (Fig. 7F, G).

Fig. 7.

TRAF4 regulates mitochondrial dysfunction via the SETDB1 axis in HK-1 cells. A, B Validation of SETDB1 overexpression efficiency by RT-qPCR (A) and Western blotting (B). C–E Cells were co-transfected with si-TRAF4 and SETDB1 overexpression plasmids. Mitochondrial function was evaluated by MitoSOX Red staining for ROS (C, Scale bar = 50 μm), JC-1 staining for membrane potential (D, Scale bar = 50 μm), and MitoTracker staining (E, Scale bar = 20 μm). F Western blot analysis of RIPK3 and subcellular Cytc levels in the indicated groups. G Western blot analysis of Bax, Bcl-2 and cleaved-Caspase 9 levels in the indicated groups. Data are presented as mean ± SD. **P < 0.01, ***P < 0.001 vs. Control group; ##P < 0.01 vs. siRNA-TRAF4 group

Overexpression of SETDB1 rescues TRAF4 knockdown-mediated proliferation inhibition and apoptosis

Finally, we validated the biological significance of the TRAF4-SETDB1 axis in HK-1 cells. CCK-8, colony formation, and flow cytometry assays demonstrated that TRAF4 knockdown significantly inhibited cell proliferation and promoted apoptosis compared to the control group. Importantly, these effects were substantially rescued by the overexpression of SETDB1 (Fig. 8A–C). These data provide compelling evidence that TRAF4 promotes NPC HK-1 cells progression and inhibits apoptosis through the stabilization of SETDB1.

Fig. 8.

Overexpression of SETDB1 rescues the phenotype caused by TRAF4 depletion. HK-1 cells were transfected with si-NC, si-TRAF4, or co-transfected with si-TRAF4 and SETDB1 overexpression vector. A Cell viability was determined by CCK-8 assay. B Colony formation assays were performed to assess proliferation. C The percentage of apoptotic cells was analyzed by flow cytometry. Data are presented as mean ± SD (n = 3). **P < 0.01, ***P < 0.001 vs. Control group; ##P < 0.01 vs. siRNA-TRAF4 group

Discussion

NPC persists as a formidable clinical challenge due to its high recurrence and metastatic rates [17]. Despite the efficacy of radiotherapy, radioresistance and chemotherapy failure frequently occur [18, 19], underscoring the need to identify novel molecular targets that drive NPC progression. In the present study, we identified a novel regulatory axis involving TRAF4 and SETDB1 that orchestrates mitochondrial apoptosis in NPC. The present findings demonstrate that TRAF4 is upregulated in NPC cells and functions as a critical stabilizer of the oncoprotein SETDB1. The present study provides evidence that the TRAF4-SETDB1 axis suppresses ROS generation and maintains mitochondrial integrity, thereby preventing apoptosis and promoting tumor cell proliferation.

TRAF4 has been implicated in various malignancies, acting primarily as an oncogene that potentiates AKT, ERK, and NF-κB signaling pathways [20, 21]. In accordance with these observations, we detected markedly elevated levels of TRAF4 in NPC cell lines in comparison to immortalized nasopharyngeal epithelial cells. A series of functional assays were conducted, revealing that depletion of TRAF4 severely impaired the viability and clonogenicity of NPC cells while concomitantly triggering apoptosis. This finding is consistent with the conclusions of earlier reports, which indicated that TRAF4 overexpression plays a role in the development of radioresistance and a poor prognosis in NPC [12]. However, while prior studies have focused on classical signaling cascades, our study uncovers a novel mechanism linking TRAF4 directly to epigenetic regulation and metabolic stress responses.

Previous studies have identified SETDB1 as a critical downstream effector of TRAF4. SETDB1 is a histone methyltransferase known to repress tumor suppressor genes and maintain genome stability [22]. Gu et al. demonstrated that TRAF4 promotes glioblastoma cell proliferation by stabilizing SETDB1 and activating the AKT signaling pathway [13]. Mechanistically, TRAF4 knockdown markedly reduced SETDB1 protein levels and global ubiquitination, indicating that TRAF4-mediated ubiquitination is required for SETDB1 stability rather than its proteasomal degradation. This regulatory pattern bears resemblance to non-canonical ubiquitination, such as K63-linked polyubiquitination, which predominantly modulates protein stability and interactions [23]. Moreover, ectopic expression of SETDB1 effectively rescued the apoptosis induction and proliferation arrest caused by TRAF4 silencing, highlighting SETDB1 as a key mediator of TRAF4-driven oncogenic effects [13].

Significantly, the present study builds upon previous research by establishing a link between SETDB1 stabilization and redox homeostasis, as well as mitochondrial function, in NPC. A mounting body of evidence suggests a role for SETDB1 in the regulation of oxidative stress. Depletion of SETDB1 has been observed to result in an accumulation of intracellular ROS [14, 24]. In accordance with these observations, our findings indicate that SETDB1 knockdown significantly increases mitochondrial ROS levels, disrupts ΔΨm, and promotes Cytc release into the cytosol, thereby activating the mitochondrial apoptotic pathway. These mitochondrial alterations were accompanied by increased expression of RIPK3, suggesting a convergence of oxidative stress and programmed cell death signaling [25]. The functional importance of ROS in this process was further confirmed by pharmacological intervention. Treatment with the ROS scavenger NAC led to a partial reversal of the proliferation inhibition and apoptosis induced by SETDB1 silencing, indicating that excessive ROS accumulation plays a pivotal role in SETDB1 loss-induced cellular toxicity. These findings are consistent with the concept that cancer cells rely on antioxidant mechanisms to maintain redox balance and that disruption of this balance can selectively trigger tumor cell death [26]. Crucially, our rescue experiments provide strong causal evidence supporting the TRAF4–SETDB1 axis. Re-expression of SETDB1 in TRAF4-silenced cells effectively restored mitochondrial function, reduced ROS accumulation, suppressed Cytc release, and reversed apoptosis and proliferation arrest. These results demonstrate that SETDB1 is a principal mediator of TRAF4-driven oncogenic effects in NPC and place SETDB1 downstream of TRAF4 in the regulation of mitochondrial apoptosis.

From a clinical perspective, our findings carry significant therapeutic implications. Given the reliance of NPC cells on TRAF4-mediated SETDB1 stabilization to maintain redox homeostasis and mitochondrial integrity, targeting this axis may represent a promising strategy to sensitize NPC cells to apoptosis. In particular, pharmacological inhibition of SETDB1 or disruption of TRAF4-mediated ubiquitination could enhance oxidative stress beyond tolerable thresholds in tumor cells, thereby augmenting the efficacy of existing therapies such as radiotherapy and chemotherapy.

Despite these promising findings, our study has several limitations. First, our experiments were conducted exclusively in vitro; confirming the therapeutic potential of targeting the TRAF4-SETDB1 axis in in vivo xenograft models is a necessary next step. Second, the precise ubiquitin linkage type involved in TRAF4-mediated SETDB1 stabilization was not determined and warrants further investigation. Elucidating whether K63-linked or other non-canonical ubiquitination is involved may provide additional mechanistic insight and identify more specific druggable targets. Future structural biology studies are warranted to clarify these molecular details.

In summary, the present study delineates a mechanistic pathway in which TRAF4 stabilizes SETDB1, thereby inhibiting ROS-dependent mitochondrial apoptosis in NPC. These findings contribute to our expanding understanding of the non-canonical functions of TRAF4 and propose the TRAF4-SETDB1 axis as a potential therapeutic target. Strategies aimed at disrupting this axis could sensitize NPC cells to oxidative stress-inducing therapies, offering a new avenue for clinical intervention.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

NPC

Nasopharyngeal carcinoma

TRAF4

Tumor necrosis factor receptor-associated factor 4

SETDB1

SET domain bifurcated 1

ROS

Reactive oxygen species

NAC

N-acetyl-L-cysteine

Cytc

Cytochrome c

RIPK3

Receptor-interacting serine/threonine-protein kinase 3

ΔΨm

Mitochondrial membrane potential

RT-qPCR

Quantitative real-time polymerase chain reaction

Co-IP

Co-immunoprecipitatio

WB

Western blot

SDS-PAGE

Sodium dodecyl sulfate-polyacrylamide gel electrophoresis

PVDF

Polyvinylidene difluoride

FBS

Fetal bovine serum

PBS

Phosphate-buffered saline

OD

Optical density

SD

Standard deviation

siRNA

Small interfering RNA

NC

Negative control

Author contributions

Author Contributions Jing-Yuan Wang and Qiang-Wei Zhang contributed to the study conception and design. Material preparation, data collection and analysis were performed by Jing-Yuan Wang, Kai-Xue Wen, Shu-Xin Wen, Yu-Hao Zhang, Li-Xia Zhang and Tian Wang. The first draft of the manuscript was written by Jing-Yuan Wang and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Funding

This work was supported by the Fundamental Research Program of Shanxi Province (Grant No. 202403021222382).

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.

Ethical approval

Not applicable.