FOS regulation of T-cell activation and the mechanism of inflammatory injury of coronary endothelium in Kawasaki disease

Introduction

Kawasaki disease (KD), also referred to as mucocutaneous lymph node syndrome, is primarily characterized as a systemic immune-mediated vasculitis affecting small-to-medium-sized vessels, with a particular predilection for the coronary arteries. Approximately 25–30% of untreated patients develop coronary artery lesions (CALs) (1). Even following administration of intravenous immunoglobulin (IVIG), nearly 4% of pediatric patients continue to develop coronary artery aneurysms (2). KD has emerged as the leading cause of acquired heart disease in developed countries (3). The precise pathogenesis of KD remains elusive. However, research indicates that it may be precipitated by the invasion of one or more known or unknown microorganisms in genetically susceptible individuals. This invasion prompts macrophages to enter the bloodstream and target small-to-medium-sized vessels, particularly the coronary arteries, thereby initiating immune activation involving T and B lymphocytes. This process culminates in immune dysregulation and subsequent inflammatory injury to the vascular endothelium (4). T-cell hyperactivation is recognized as a pivotal step in this process, driving aberrant immune activity that culminates in vascular immune damage (5,6). During KD onset, T helper 17 (Th17) and Th1 responses are enhanced, characterized by increased levels of interleukin (IL)-6, IL-10, IL-17A, and interferon-γ (IFN-γ) (7). In contrast, Th2 and regulatory T cell (Treg) responses are diminished, with decreased expression of IL-4, IL-5, FoxP3, and transforming growth factor-β (TGF-β) (8,9). Additionally, a decrease in the ratio of CD8 and natural killer (NK) cells is observed (10). Research using a Candida albicans water-soluble fraction (CAWS)-induced KD mouse model has demonstrated reductions in subsets of CD3+, CD4+, CD8+, CD8+CD45+, Foxp3+, CD25+, and Foxp3+CD25+ T lymphocytes, along with an increase in the CD45+T lymphocyte subset. Furthermore, pro-inflammatory cytokines (IL-1β, IL-6, TNF-α), chemokines (RANTES), and adhesion molecules (MCP-1, VCAM-1, ICAM-1, E-selectin) are elevated, while anti-inflammatory cytokines (IL-10, G-CSF) are reduced (11). These findings highlight the critical involvement of T cells in the vasculitic injury model of KD.

The Fos proto-oncogene family comprises four members: FOS, FOSB, FOSL1, and FOSL2. These genes encode leucine zipper proteins that heterodimerize with JUN family proteins to assemble the activator protein-1 (AP-1) transcription factor complex, a critical regulator of cell growth, differentiation, and stress responses (12). Mutations within the basic regions of FOS and JUN can exert dominant-negative effects, thereby disrupting normal cellular function (13). Consequently, FOS protein is recognized as a regulator of cell proliferation, differentiation, and transformation (14). In the immune system, FOS expression is rapidly induced following antigen or cytokine stimulation, regulating the proliferation, differentiation, and effector functions of various immune cell subsets (15). During acute infection, the activated T-cell nuclear factor NFAT/FOS complex acts downstream of the T-cell receptor (TCR) and CD28 co-stimulatory receptor, inducing the expression of effector cytokines (16). Conversely, FOS inhibition has been shown to attenuate the production of inflammatory cytokines and chemokines (17). FOS also functions as a transcriptional activator of IL-2, enhancing T-cell proliferation and survival (18). Furthermore, FOS plays a key role in IL-4 gene expression, thereby influencing T-cell differentiation and function (19). Given that extensive research has established the critical role of T-cell activation in KD, we hypothesize that FOS contributes to the pathogenesis and progression of KD-associated vasculitis by modulating T-cell activation. To validate this hypothesis, we used clinical blood samples and in vivo and in vitro experiments to investigate the correlation between FOS expression and coronary artery inflammatory injury. Additionally, we examined the impact of FOS on endothelial cell damage and inflammatory expression, thereby further elucidating the potential molecular mechanisms of FOS in KD vasculitis. We present this article in accordance with the MDAR and ARRIVE reporting checklists (available at https://tp.amegroups.com/article/view/10.21037/tp-2026-1-0149/rc).

Methods

Patient sample collection and ethical considerations

Peripheral blood samples were prospectively collected at the Children’s Hospital of Soochow University from February 2024 to February 2025. Patients with acute KD and subacute KD were enrolled upon admission, and age-matched febrile children with upper respiratory tract infection served as controls. For RNA sequencing, three samples were included in each group (acute KD, subacute KD, and febrile control). For RT-qPCR validation, eight samples were included in each group. Inclusion criteria followed the 2017 American Heart Association (AHA) guidelines for KD (17). Acute KD was defined as illness days 1–10/11 with persistent fever and typical mucocutaneous manifestations; subacute KD was defined as illness days 11–21 with improvement of fever and typical desquamation/platelet elevation. Exclusion criteria included prior IVIG use, incomplete/atypical KD, admission time ≥7 days for the acute-phase sampling group, or other major comorbidities. Demographic and clinical variables, including age, sex, fever duration, white blood cell count, neutrophil percentage, platelet count, C-reactive protein, erythrocyte sedimentation rate, IVIG response, and coronary artery status, were collected from medical records. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Children’s Hospital of Soochow University (No. 2025CS251) and informed consent was obtained from the children’s legal guardians.

Peripheral blood T-cell isolation

Peripheral blood (2 mL) was collected in EDTA anticoagulant tubes and processed within 30 minutes. After centrifugation at 2,500 rpm for 5 minutes at 2–8 ℃, plasma was aliquoted and stored at −80 ℃, and the cell pellet was kept on ice for T-cell isolation. T cells were isolated using a human whole-blood T-cell isolation kit (Catalog #19661, STEMCELL Technologies, Vancouver, Canada) according to the manufacturer’s instructions. Briefly, the cell pellet was resuspended in 2 mL buffer, and the cell concentration was adjusted to 1×10⁸ cells/mL. Cells were incubated sequentially with 10 µL biotinylated antibody cocktail and 10 µL streptavidin-coated magnetic nanobeads on ice for 15 minutes each, with gentle mixing during incubation. After adding 2.5 mL buffer, the tube was placed in a magnet for 5 minutes, and magnetic separation was repeated twice. The isolated T-cell pellet was resuspended in 1 mL TRIzol for subsequent RNA extraction.

Peripheral blood T-Cell RNA extraction and reverse transcription

Trizol-extracted T cells were vortexed with chloroform, centrifuged, and the aqueous phase was mixed with isopropanol. After centrifugation, the RNA pellet was washed with 75% ethanol, air-dried, and dissolved in RNase-free water. RNA concentration was measured using a NanoDrop-2000 spectrophotometer, ensuring an A260/280 ratio of 1.8–2.2. Reverse transcription was performed using a PE9600PCR instrument.

Real-time quantitative PCR (RT-qPCR)

Primers were designed based on gene IDs retrieved from NCBI and synthesized by Beijing Tsingke Biotechnology Co., Ltd. RT-qPCR was performed on a LightCycler 480 real-time PCR system (Roche, Basel, Switzerland) using LightCycler^® 480 SYBR Green I Master (Cat. No. 04707516001, Roche, Basel, Switzerland). Samples were loaded onto a 384-well PCR plate in triplicate. GAPDH was used as the internal control, and relative gene expression was calculated using the 2^−ΔΔCt method.

CAWS-induced vasculitis mouse model establishment

The sample size was determined based on previous experience with the CAWS-induced vasculitis model and pilot experiments, which indicated that this number provides sufficient statistical power to detect significant differences in coronary inflammatory scores and cytokine levels. Four-week-old SPF grade C57BL/6J male mice were purchased from Hangzhou Ziyuan Experimental Animal Technology Co., Ltd. (License: SCXK (Zhe) 2019-0004). CAWS was prepared according to established protocols (20). Mice were randomly assigned to CAWS (experimental) and PBS (control) groups (5 mice per group) using a computer-generated random number sequence to ensure unbiased allocation. The CAWS group received daily intraperitoneal (i.p.) injections of 4 mg CAWS for 5 days, repeated every 4 weeks. The control group received an equal volume of PBS. Mice were sacrificed 4 to 14 days post-CAWS injection under chloral hydrate anesthesia, and peripheral blood and cardiac tissues were collected. To minimize potential confounders, all animal injections and tissue collections were performed at the same time of day (between 9:00 AM and 11:00 AM). Cage locations were also rotated weekly to account for potential environmental variations within the animal facility. All animal experiments were performed under a project license (No. SUDA20220906A01) granted by the Ethics Committee of Soochow University, in compliance with the institutional guidelines for the care and use of laboratory animals.

Mouse heart tissue paraffin embedding and sectioning

Fresh mouse heart tissue was transversely cut near the coronary arteries. The basal portion containing the aortic root/coronary ostia was fixed in 4% paraformaldehyde at room temperature for at least 24 hours, dehydrated through graded ethanol, cleared in xylene, infiltrated with paraffin, and embedded. Sections were cut at 4 µm thickness using a microtome, dried on slides, and stored at room temperature.

Hematoxylin and eosin (H&E) staining and vasculitis scoring

Sections were dewaxed, rehydrated, stained with H&E, differentiated, blued, counterstained with eosin, dehydrated, cleared, and mounted. Observations focused on the coronary arteries, aorta, and myocardium. The vasculitis scoring system was adapted from previously published CAWS vasculitis studies (21). Coronary Artery/Aorta Scoring: 0: no inflammation; 1: occasional inflammation; 2: scattered inflammation; 3: diffuse inflammatory infiltration; 4: dense inflammatory infiltration. Myocardial Scoring: 0: no myocardial fibrosis; 1: occasional focal subepicardial interstitial fibrosis; 2: mild subepicardial interstitial fibrosis with partial infiltration into the subepicardial layer; 3: focal subepicardial interstitial fibrosis; 4: complete myocardial tissue replacement by fibrosis. Histological scoring and immunohistochemical analysis were performed by two independent investigators who were blinded to the experimental group assignments to minimize observer bias.

Immunohistochemistry (IHC)

IHC was performed on heart sections. Following dewaxing and rehydration, antigen retrieval was performed using Sodium Citrate Antigen Retrieval Buffer (pH 6.0, Cat# C1032, Beyotime, Shanghai, China). Endogenous peroxidase activity was quenched with 3% hydrogen peroxide and sections were blocked with goat serum for 30 minutes. Sections were incubated overnight at 4 ℃ with anti-FOS antibody (Cat# 31254S, Cell Signaling Technology, Danvers, MA, USA; 1:200 dilution), followed by HRP-conjugated anti-rabbit secondary antibody (Cat# 7074S, Cell Signaling Technology; 1:500 dilution) and DAB substrate. Sections were counterstained with hematoxylin before mounting.

Immunofluorescence staining

After dewaxing and antigen retrieval, sections were blocked with 5% goat serum at 37 ℃ for 30 minutes. Primary antibody diluted in TBS were incubated overnight at 4 ℃. The antibody panel included anti-FOS (Cat# 31254S, Cell Signaling Technology, 1:200) and anti-CD3 (Cat# ab16669, Abcam, 1:200). The next day, sections were incubated with corresponding fluorescent secondary antibodies (Goat Anti-Rabbit IgG H&L, Alexa Fluor 488, Cat# ab150077, Abcam, 1:500) for 1 hour at 37 ℃ in the dark. After washing, the DAPI working solution was added and incubated for 10 minutes in the dark. Slides were mounted with anti-fade mounting medium and imaged using a fluorescence microscope.

Western blotting

Total protein was extracted from mouse cardiac tissue by homogenization in RIPA lysis buffer supplemented with PMSF. Protein concentration was were quantified using the BCA assay. Equal amounts of protein were separated by SDS-PAGE and transferred onto polyvinylidene fluoride (PVDF) membranes. Membranes were blocked with 5% skim milk for 2 hours and incubated overnight at 4 ℃ with primary antibodies: anti FOS (Cat# 31254S, Cell Signaling Technology, 1:1,000), anti-IL-6 (Cat# ab208113, Abcam, 1:1,000), and anti GAPDH (Cat# 2118, Cell Signaling Technology, 1:5,000). Membranes were then incubated with HRP conjugated secondary antibodies for 1 hour. Immunoreactive bands were detected using an enhanced chemiluminescence (ECL) system, and densitometric analysis was performed using ImageJ software.

ELISA

ELISA kits for IL-6, TNF-α, and IL-1β (Cat# EK206HS, EK282HS, EK201HS, Biosensis, Adelaide, Australia) were used according to the manufacturer’s instructions. Briefly, 100 µL of diluted cytokine standard or plasma sample was added to each well. Biotinylated antibody working solution was prepared at 1:100 in Dilution Buffer R and incubated for 90 minutes at 37 ℃. After washing, streptavidin HRP was prepared at 1:100 and incubated for 30 minutes at 37 ℃. TMB substrate was added for color development, and the reaction was stopped with stop solution. Absorbance was measured at 450 nm using a microplate reader. Each sample was assayed in duplicate or triplicate, and cytokine concentrations were calculated against the standard curve.

Flow cytometry

Following T-cell activation, JURKAT cells were washed twice with PBS and stained for flow cytometry. The antibody panel used to define the activation phenotype included anti-human CD25 (PE, Clone BC96, Cat# 300708, BioLegend, 1:50) and, where applicable, anti-human CD69 (FITC, Clone FN50, Cat# 310904, BioLegend, 1:50). A matched isotype control and unstained control were included to set gates. Cells were incubated with the antibody cocktail for 30 minutes at 4 ℃ in the dark, washed twice with flow cytometry buffer, resuspended in buffer, and analyzed by flow cytometry (BD LSRFortessa, BD Biosciences, San Jose, CA, USA). Data were analyzed using FlowJo V10.8.1, and the same gating strategy was applied to all samples.

EVG staining

Paraffin sections were dewaxed and stained using Verhoeff’s working solution for 1 hour. After washing, sections were differentiated in 2% ferric chloride for 1~2 minutes, then washed. Elastic fibers appeared black against a gray background. Sections were then immersed in 5% sodium thiosulfate, washed, and counterstained with VG solution. Sections were dehydrated rapidly in graded ethanol, cleared in xylene, and mounted in neutral resin.

Establishment of KD vasculitis in vitro model

A co-culture system was established using Transwell inserts. JURKAT cells stably transduced with lentivirus (OE-FOS, OECON, KO-FOS, KOCON, MOCK) were activated with anti-CD3/CD28 magnetic beads (Cat# 11131D, Thermo Fisher Scientific, Waltham, MA, USA; bead-to-cell ratio =1:1) for 48 hours. Activated JURKAT cells were co-cultured with human coronary artery endothelial cells (HCAECs) using our standard upper/lower chamber configuration (Transwell pore size: 5.0 µm, Corning, Cat# 3421). After determining the optimal co-culture time, HCAECs and culture medium were collected for subsequent experiments. Human T-lymphoblastoid leukemia cells (JURKAT cells) and HCAECs were obtained from the Shanghai Cell Bank, Chinese Academy of Sciences.

Scratch wound healing assay

HCAECs were grown to confluence in 6-well plates. A scratch was made uniformly across the well using a 10 µL pipette tip, guided by a ruler. Cells were washed three times with PBS to remove detached cells. Images were taken at 0, 12, 24, and 36 hours. ImageJ software was used to calculate the scratch area for statistical analysis.

Transwell migration assay

Cells (5×10⁴/well) were seeded into the upper chamber of a 12-well Transwell plate (pore size 8 µm). The upper chamber contained 200 µL of 2% DMEM complete medium, and the lower chamber contained 600 µL of 20% FBSMEM complete medium. After 12 hours of incubation, cells remaining in the upper chamber were gently removed with a cotton swab. Cells that migrated to the lower surface were fixed with 4% paraformaldehyde for 20 minutes, washed with PBS, dried, and stained with 100 µL of 0.1% crystal violet for 30 minutes. After washing, the cells were photographed under a microscope. ImageJ software was used for cell counting and statistical analysis.

Cell adhesion assay

HCAECs at 80%~90% confluence were washed twice with PBS. 5×10³ cells/well were seeded into a 96-well plate and incubated for 2 hours. Cells were washed three times with PBS to remove non-adherent cells. Adherent cells were fixed with 4% paraformaldehyde for 20 minutes and washed with PBS. After drying, 100 µL of 0.1% crystal violet solution was added for 30 minutes. After washing and drying, cells were photographed under a microscope. ImageJ software was used for cell counting and statistical analysis.

RNA sequencing and bioinformatic analysis

For transcriptomic analysis, RNA integrity was assessed before library construction. RNA-seq libraries were prepared and sequenced by Beijing Novogene Bioinformatics Technology Co., Ltd. (Illumina NovaSeq 6000 platform for both clinical T-cell sequencing and JURKAT cell sequencing). Raw reads were filtered to remove adapter sequences and low-quality reads, and clean reads were aligned to the appropriate reference genome using HISAT2 (v2.2.1). Gene-level counts were generated using featureCounts (v2.0.3), and expression levels were normalized as FPKM. Differentially expressed genes (DEGs) were identified using DESeq2 (v1.34.0), with |log2 fold change| >1 and adjusted p value/FDR <0.05 as the screening criteria unless otherwise specified. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed using clusterProfiler (v4.2.2) package in R software. Protein-protein interaction (PPI) networks were generated using STRING database (v11.5) and visualized in Cytoscape (v3.9.1), and hub genes were ranked using the MCC algorithm in cytoHubba.

Statistical analysis

No animals or data points were excluded from the statistical analysis. All experimental units that completed the protocols were included in the final dataset. All experiments were performed in triplicate. Data analysis was performed using GraphPad Prism 9, SPSS 22.0, and ImageJ. Quantitative data were expressed as mean ± standard deviation. Individual raw data points were overlaid on bar graphs to visualize data distribution. Statistical comparisons were performed using Student’s T-test or one-way ANOVA for normally distributed data with equal variances; otherwise, the rank-sum test was used. Pearson correlation analysis was used to explore correlations between groups. P<0.05 was considered statistically significant. The primary outcome measure of this study was the histological score of coronary vasculitis in the KD mouse model. Secondary outcome measures included FOS mRNA and protein expression levels, serum concentrations of pro-inflammatory cytokines (IL-6, TNF-α, and IL-1β), and the migratory/adhesive capacities of HCAECs in the in vitro co-culture model.

Results

FOS expression is significantly upregulated in peripheral blood T cells of KD patients

Transcriptome sequencing of T cells isolated from the peripheral blood of patients with acute KD, subacute KD, and febrile controls (n=3 per group) revealed that FOS was significantly upregulated in the acute KD group compared to the control group (Figure 1). To validate this, mRNA was extracted from T cells of 8 acute KD, 8 subacute KD, and 8 control samples, and RT-qPCR measured FOS mRNA expression. Consistent with the sequencing data, FOS expression was significantly elevated in the acute KD group compared to controls (P<0.001; Figure 2A).

Figure 1 Transcriptomic analysis of peripheral blood T cells in Kawasaki disease patients. (A) Sample correlation plot comparing acute KD PBTs and control PBTs. (B) Sample correlation plot comparing subacute KD PBTs and control PBTs. (C) KEGG pathway enrichment analysis (bubble plot) comparing acute KD PBTs and control PBTs. (D) KEGG pathway enrichment analysis (bubble plot) comparing subacute KD PBTs and control PBTs. (E) Volcano plot of DEGs comparing acute KD PBTs and control PBTs (|log₂foldchange|>1 used as the screening threshold). (F) Volcano plot of DEGs comparing subacute KD PBTs and control PBTs (|log₂foldchange|>1 used as the screening threshold). (G) PPI network of DEGs (Padj <0.05, |log₂foldchange| >1, and a STRING interaction score threshold of 0.4 used as the threshold). (H) Degree algorithm ranking of hub genes (darker color indicates higher rank). DEGs, differentially expressed genes; KD, Kawasaki disease; KEGG, Kyoto Encyclopedia of Genes and Genomes; PBTs, peripheral blood T cells; PPI, protein-protein interaction.

Figure 2 FOS expression in KD patients and the CAWS-induced KD mouse model. (A) FOS mRNA expression in PBTs from acute KD patients. Control: healthy control group; acute: acute KD group; subacute: subacute KD group. (B) H&E staining of aortic root sections from the KD mouse model at different time points, showing coronary arteritis and endothelial damage. (C) Immunohistochemical staining of aortic root sections showing FOS expression in the coronary artery region. (D) Comparison of FOS protein expression in heart tissue of the KD mouse model. (E) Comparison of FOS mRNA expression in PBTs of the KD mouse model. (F) Co-immunofluorescence staining for FOS and the T cell marker CD3 in heart tissue of the KD mouse model. (G-I) Plasma levels of IL-6 (G), IL-1β (H), and TNF-α (I) in the KD mouse model. ns, no statistical significance; *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001. PBS: Control mice; CAWS: KD model mice. CAWS, Candida albicans cell wall extracts; FOS, Fos proto-oncogene, AP-1 transcription factor subunit; H&E, hematoxylin and eosin; KD, Kawasaki disease; PBS, phosphate-buffered saline; PBTs, peripheral blood T cells.

Increased FOS expression in peripheral blood T cells of KD mouse model

To investigate the role of FOS in vivo, a CAWS-induced KD mouse model was established. Histopathological assessment via H&E staining of aortic root sections harvested at 3, 7, 14, and 28 days post-induction revealed no discernible inflammatory infiltration at 3 days. However, perivascular inflammatory infiltration of varying severity degrees was observed around the coronary arteries of the aortic root sections at 7 and 14 days. Coronary artery endothelial layer rupture and stratification were most pronounced at 14 days, with statistical significance (P<0.001) (Figure 2B). Consistent with these findings, IHC staining showed an increased number of FOS-positive cells in the coronary artery endothelium of KD model mice compared to controls, with the 14-day group showing the most significant difference (P<0.001) (Figure 2C). Therefore, 14-day-old mice were selected for subsequent experiments.

Further validation was performed using RT-qPCR on peripheral blood T-cell RNA and Western Blot on cardiac tissue protein, confirming that both FOS mRNA and protein levels were significantly upregulated in the KD mouse model than in controls (Figure 2D,2E). Immunofluorescence staining of aortic root tissue sections showed a clear increase in FOS and CD3 staining in the KD mouse model (Figure 2F). ELISA detection of serum IL-6 (Figure 2G), TNF-α (Figure 2H), and IL-1β (Figure 2I) protein levels showed that all three inflammatory factors were significantly elevated in the model group compared to controls (P<0.001), with IL-6 showing the most pronounced change (P<0.05).

FOS and inflammatory cytokine expression increase after JURKAT cell activation, and validation of stable FOS-modulated JURKAT cells

Human T-lymphoblastoid leukemia cells (JURKAT cells) were stimulated using anti-CD3/28 coated magnetic beads. RT-qPCR measured FOS mRNA expression at 0.5, 4, 6, 12, 24, 36, and 48 hours post-activation. Flow cytometry confirmed robust activation of JURKAT cells at 48 hours (Figure 3A), coinciding with maximal FOS expression (Figure 3B). Therefore, JURKAT cells activated for 48 hours were used in subsequent experiments. RT-qPCR analysis of IL-6, TNF-α, and IL-1β mRNA expression in JURKAT cells 48 hours post-activation showed significant upregulation of IL-6 (Figure 3C) and TNF-α (Figure 3D) (P<0.001), but no significant change was observed in IL-1β levels (Figure 3E). To further investigate the functional role of FOS in activated T cells, stable JURKAT cell lines with FOS overexpression (OE-FOS) and knockdown (KO-FOS) were constructed using lentiviral vectors. Different multiplicity of infection (MOI) gradients were tested. Fluorescence microscopy confirmed that an MOI of 50, in the presence of enhancer P, yielded optimal fluorescence intensity (Figure 3F). JURKAT cells were subsequently stratified into four experimental groups: OE-FOS, overexpression control (OE-CON), KO-FOS, and knockdown control (KO-CON). Fluorescence microscopy confirmed successful lentiviral infection (Figure 3G). Western Blot results confirmed successful construction of stable transfectants, showing increased FOS expression in the OE-FOS group compared to OECON, and decreased FOS expression in the KO-FOS group compared to KOCON (Figure 3H). These findings were corroborated by RT-qPCR, which showed that FOS mRNA was significantly upregulated in the OE-FOS group and significantly downregulated in the KO-FOS group (Figure 3I).

Figure 3 FOS expression and inflammatory cytokine production in activated JURKAT cells, and validation of stable cell lines. (A) Flow cytometry analysis of the T cell activation marker CD25 in JURKAT cells. (B) Time-course of FOS mRNA expression following CD3/28 magnetic bead activation. (C-E) mRNA expression of IL-6 (C), TNF-α (D), and IL-1β (E) 48 hours after JURKAT cell activation. 0: unactivated group; 48: 48 hours post-activation. ns, no statistical significance; ***, P<0.001. (F-I) Construction and validation of stable FOS overexpression and knockdown JURKAT cell lines. (F) Determination of optimal MOI for lentiviral transduction in JURKAT cells (100× fluorescence microscopy). (G) Observation of viral transduction fluorescence 48 hours post-infection (100× fluorescence microscopy). (H) Western blot confirmation of FOS overexpression and knockdown efficiency. (I) RT-qPCR detection of FOS overexpression and knockdown efficiency after 72 hours of puromycin selection. OE-FOS: FOS overexpression group; OECON: overexpression control group; KO-FOS: FOS knockdown group; KOCON: knockdown control group. FOS, Fos proto-oncogene, AP-1 transcription factor subunit; IL, interleukin; MOI, multiplicity of infection; RT-qPCR, real-time quantitative polymerase chain reaction; TNF-α, tumor necrosis factor-α.

Effects of T5224 intervention on FOS and inflammatory factor expression in KD mouse model

To evaluate the therapeutic potential of FOS inhibition, the KD mouse model was established by CAWS injection for 5 days. The FOS inhibitor T5224 was administered intraperitoneally at varying doses for 14 days. RT-qPCR analysis of peripheral blood T cells showed that the T5224 treatment significantly suppressed the mRNA expression of FOS, as well as the activation markers CD69 and CD25 mRNA levels(P<0.05). However, no significant difference in FOS expression was observed between different T5224 concentrations (Figure 4A). Western Blot analysis of cardiac tissue protein showed that T5224 intervention reduced FOS and IL-6 expression in the heart (Figure 4B). ELISA detection of serum IL-6, TNF-α, and IL-1β protein levels showed that T5224 intervention reduced IL-1β (Figure 4C), IL-6 (Figure 4D), and TNF-α (Figure 4E) compared to the control group (P<0.05). Notably, the reductions in these inflammatory cytokines did not exhibit significant dose-dependency.

Figure 4 Inhibition of FOS by T5224 attenuates T cell activation and coronary vasculitis in the KD mouse model. (A) T5224 dose-dependent effect on FOS, CD25, and CD69 mRNA expression in peripheral blood T cells of model mice. (B) Western blot analysis of FOS protein in coronary artery tissue of model mice after T5224 intervention. C-C: CAWS + Corn Oil; C-20: CAWS + T5224 20 mg/kg; C-40: CAWS + T5224 40 mg/kg. (C-E) Plasma cytokine levels in 14-day KD model mice before and after T5224 intervention: IL-1β (C), IL-6 (D), and TNF-α (E). (F-I) Histological analysis of heart tissue sections in 14-day KD model mice before and after T5224 intervention. (F) H&E staining showing cardiac tissue inflammatory infiltration. (G) Elastica van Gieson (EVG) staining showing elastic fiber integrity. (H) FOS immunohistochemical staining. (I) FOS and CD3 immunofluorescence co-staining. ns, no statistical significance; *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001. H&E, hematoxylin and eosin; IL, interleukin; KD, Kawasaki disease; TNF-α, tumor necrosis factor-α.

Histological findings in KD mouse heart tissue after T5224 intervention

Histological assessment via H&E staining revealed that the pronounced inflammatory infiltration observed in the vehicle-treated KD model group was significantly attenuated following T5224 intervention (P<0.001). However, no significant differences in therapeutic efficacy were observed across the varying T5224 doses (Figure 4F). Verhoeff-Van Gieson (EVG) staining showed that while the conventional model group exhibited clear rupture of elastic fibers around the coronary arteries, the T5224 intervention group still showed intact elastic fiber bundles, with no significant difference compared to the control group (Figure 4G). Immunohistochemical analysis confirmed a significant increase in the conventional model group compared with controls, whereas the T5224 intervention group showed a significant decrease (P<0.001). No statistical difference was observed between different T5224 concentrations (Figure 4H). Immunofluorescence co-staining for FOS and the T-cell marker CD3 showed that the T5224 intervention significantly diminished both FOS and CD3 fluorescence intensity compared to the untreated KD model group (Figure 4I).

RNA sequencing (RNA-seq) of activated JURKAT stable transfectants revealed activation of inflammatory pathways

RNA-seq was performed on activated JURKAT cells stably transduced with FOS lentivirus. In the overexpression comparisons, 781 genes were upregulated and 601 genes were downregulated in OE1 versus OECON1, while 786 genes were upregulated and 501 genes were downregulated in OE2 versus OECON2. In the knockdown comparisons, 1,670 genes were upregulated and 1,855 genes were downregulated in KO1 versus KOCON1, while 1,653 genes were upregulated and 3,643 genes were downregulated in KO2 versus KOCON2. Several inflammation-related genes, including CCR2, CCR5, TLR3, and TLR6, were altered. GO enrichment analysis indicated that the inflammatory response pathway was prominently regulated by FOS overexpression and knockdown (Figure 5).

Figure 5 Transcriptome sequencing of activated JURKAT cells with stable FOS lentiviral modulation. (A) Sample correlation distribution map. (B,C) Volcano plots of DEGs, using |log₂foldchange|>1 as the screening threshold. (D,E) GO enrichment analysis highlighting differentially regulated signaling pathways. OE-FOS: FOS overexpression group; OECON: overexpression control group; KO-FOS: FOS knockdown group; KOCON: knockdown control group. DEGs, differentially expressed genes; FOS, Fos proto-oncogene, AP-1 transcription factor subunit; GO, Gene Ontology.

Effects of FOS knockdown in activated JURKAT cells on HCAEC phenotype

Activated JURKAT cells transduced with FOS knockdown (KO-FOS) or control vectors (KOCON) were co-cultured with HCAECs. RT-qPCR of HCAEC mRNA collected at different time points showed that TNF-α and IL-6 mRNA levels were highest at 4~6 hours post-co-culture, with statistical significance. Consequently, a 5-hour co-culture duration was selected for subsequent functional assays (Figure 6A,6B). Before functional assays, the activation status of stable FOS-modulated JURKAT cells was validated (Figure 6C).

Figure 6 FOS knockdown in activated T cells protects HCAECs by reducing inflammation and improving endothelial function. (A,B) mRNA expression of IL-6 (A) and TNF-α (B) in HCAECs after co-culture with activated JURKAT cells. (C-F) Detection of JURKAT activation status and HCAEC phenotype after co-culture with stable FOS-modulated JURKAT cells. (C) Validation of activation status in stable FOS-modulated JURKAT cells. (D) HCAEC horizontal migration capacity (Scratch assay) (1: MOCK, 2: KOCON, 3: KO-FOS). (E) HCAEC transmigration/invasion capacity (Transwell assay). (F) HCAEC adhesion capacity (Adhesion assay). ns, no statistical significance; *, P<0.05; **, P<0.01; ***, P<0.001. KO-FOS: FOS knockdown group; KOCON: knockdown control group. FOS, Fos proto-oncogene, AP-1 transcription factor subunit; HCAECs, human coronary artery endothelial cells; IL, interleukin; TNF-α, tumor necrosis factor-α.

Co-culture of activated KO-FOS JURKAT cells with HCAECs showed that the HCAEC migration rate in the scratch wound healing assay was significantly higher than the control group at both 12 and 24 hours (P<0.01), indicating enhanced horizontal migratory capacity (Figure 6D). The Transwell migration assay showed that the number of HCAECs migrating to the lower membrane layer was significantly reduced in the KO-FOS co-culture group compared to the control group (P<0.01), suggesting impaired vertical migration potential (Figure 6E). The adhesion assay showed that the number of adherent HCAECs was significantly reduced in the KO-FOS co-culture group compared to the control group (P<0.01), indicating compromised endothelial cell adhesiveness (Figure 6F).

Discussion

KD is acute, systemic vasculitis primarily affecting children, characterized by exuberant, systemic inflammation (22,23). The consequent immune dysregulation, particularly the aberrant activation and hyper-responsiveness of T cells, is implicated as a pivotal driver of coronary artery damage and aneurysm formation (24). Indeed, genetic studies have pinpointed variants in genes governing T-cell activation as major risk factors for KD-associated coronary lesions (25). The proto-oncogene FOS, a component of the AP-1 transcription factor complex, is known to regulate T cell proliferation, differentiation, and survival, predominantly via the MAPK/ERK and JNK signaling pathways (26-30). We hypothesized that FOS plays a central role in KD pathogenesis by mediating T cell hyperactivation.

Although CD8+ T cells have been shown to functionally contribute to coronary arteritis in murine KD models (31), our in vitro experiments used JURKAT cells as a simplified human T-cell activation model rather than as a surrogate for CD8+ cytotoxic T cells. JURKAT cells have been widely used to investigate TCR/CD3-CD28-mediated activation, NFAT/AP-1 signaling, FOS activation, and IL-2-related transcriptional responses, and they have also been used in KD-related studies of T-cell activation pathways (32,33). Therefore, this model was appropriate for initial mechanistic interrogation of FOS-dependent T-cell activation, although future validation in primary CD8+ T cells from KD patients or KD mouse models will be necessary.

Our study reveals a significant upregulation of FOS mRNA in peripheral blood T cells isolated from patients with acute KD, which subsequently decreased in the subacute phase, suggesting a strong correlation with the acute inflammatory state. This FOS elevation was recapitulated in T cells from the Candida albicans cell wall extracts (CAWS)-induced KD mouse model and in activated JURKAT cells, mirroring the surge in canonical pro-inflammatory cytokines, such as IL-6. Collectively, these data strongly suggest that FOS functions as a critical mediator of T cell activation and subsequent inflammatory responses in acute KD.

Mechanistic investigation utilizing the FOS inhibitor T5224 revealed that systemic administration significantly suppressed FOS expression, alongside the T cell activation markers CD25 and CD69, within the coronary artery tissue of the KD mouse model. Importantly, T5224 treatment resulted in a marked reduction in circulating pro-inflammatory cytokines, including IL-6, TNF-α, and IL-1β. Given that IL-6 and TNF-α are well-established initiators and drivers of systemic inflammation and vascular injury in KD (34,35), these results underscore the therapeutic potential of FOS inhibition in mitigating KD-associated vasculitis. In vivo immunofluorescence further confirmed that T5224 intervention significantly reduced the co-localization of FOS and the T cell marker CD3 in the perivascular region of the coronary arteries, indicating decreased T cell infiltration and activation. This aligns align with the existing literature demonstrating FOS’s role in promoting inflammation across various diseases (36-39).

To delineate the molecular pathways potentially regulated by FOS, RNA sequencing was performed on activated JURKAT cells subjected to FOS modulation. The results showed that FOS modulation was associated with changes in inflammatory response pathways, including significant changes in key inflammatory and chemokine receptors such as CCR2, CCR5, TLR3, and TLR6. CCR2 and CCR5 are crucial for monocyte and T cell migration and homing to inflammatory sites, while TLR3 and TLR6 are pattern recognition receptors that enhance antigen presentation and T cell activation. Collectively, these findings suggest that CCR2, CCR5, TLR3, and TLR6 may represent candidate downstream inflammatory mediators or modules associated with FOS-related T-cell activation. Rather than indicating a single direct FOS-HCAEC effector pathway, our data support a model in which FOS enhances the inflammatory output and chemotaxis/inflammatory-sensing programs of activated T cells, thereby indirectly promoting endothelial inflammatory phenotypes. Furthermore, our in vitro co-culture model provided direct evidence linking FOS-mediated T cell activation to endothelial injury. Knockdown of FOS in activated JURKAT cells suppressed T cell activation markers (CD25 and CD69) (40). Importantly, this intervention attenuated HCAEC dysfunction, as evidenced by enhanced migratory repair capacity and reduced excessive transwell migration and adhesion. However, we acknowledge certain limitations: First, we observed no significant dose-dependent difference between the 20 mg/kg and 40 mg/kg T5224 groups, suggesting that the effective dose range may require further optimization. Second, the clinical sequencing data were generated from total peripheral blood T cells, the tissue staining mainly used CD3 as a pan-T-cell marker, and the in vitro experiments used JURKAT cells as a mechanistic activation model; therefore, this study cannot determine whether the FOS signal is mainly derived from CD8+ T cells, CD4+ T cells, or other T-cell subsets. Further validation in primary human CD8+ T cells or sorted T-cell subsets from patients with KD is needed. In addition, CCR2, CCR5, TLR3, TLR6, IL-6, and TNF-α should currently be interpreted as candidate downstream inflammatory mediators/modules rather than as definitively validated causal effectors. Future studies are needed to further dissect the precise downstream mechanisms by which FOS-regulated T-cell activation contributes to endothelial inflammatory injury in KD.

Conclusions

In summary, our study establishes FOS as a critical regulator linking T cell activation to coronary endotheliosis in KD. Targeting FOS represents a promising therapeutic strategy for mitigating KD-associated coronary artery damage.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the MDAR and ARRIVE reporting checklists. Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-1-0149/rc

Data Sharing Statement: Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-1-0149/dss

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-1-0149/prf

Funding: This study was funded by the Chinese Natural Science Foundation (Nos. 82371806, 82470523, 82270529 and 82500599), the National Natural Science Foundation for Youth (No. 81900450), the Suzhou Municipal Science and Technology Bureau (No. SYS2024025), and the Suzhou Science and Technology Research program (No. SYW2025117).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2026-1-0149/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. The study was approved by the Ethics Committee of Children’s Hospital of Soochow University (No. 2025CS251) and informed consent was obtained from the children’s legal guardians. All animal experiments were performed under a project license (No. SUDA20220906A01) granted by the Ethics Committee of Soochow University, in compliance with the institutional guidelines for the care and use of laboratory animals.

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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