F-box protein 28 serves as a prognostic and predictive biomarker for gastric cancer

Introduction

With over 1 million new cases each year, gastric cancer (GC) is a common cancer of which incidence and mortality rates rank in the forefront of all types of tumors. The incidence rate is higher in men than in women (1). GC is a complex disease resulting from multiple interactions of genetic, environmental, and host factors (2). Endoscopy and biopsy are the gold standards for diagnosing GC. However, in the early stage of the disease, the symptoms often do not cause obvious discomfort to patients, so the GC has usually progressed by the time of diagnosis. That often renders the patients prone to local recurrence and distant metastasis, even after undergoing surgical treatments, which greatly affects the prognosis (3). For patients with early GC, the optimal course of treatment is surgical resection, while for individuals who are unsuitable for surgery or have advanced metastasis, the most optimal method of treatment is chemotherapy (4). Therefore, clarifying the possible mechanisms of GC progression and studying GC at the molecular level may provide patients with targeted therapy, which imposes a favorable impact on GC prognosis.

F-box protein 28 (FBXO28) belongs to the FBXO subclass of the F-box protein (FBP) family, encoding a regulatory protein that functions in tumor cell proliferation. The absence of FBXO28 can affect mitotic progression and impair Myc-dependent transcription, proliferation, and tumor development (5,6). The current research indicates that FBXO28 has a strong regulatory effect on β-cell survival and can promote the survival of pancreatic β-cells (7). FBXO28 exerts its oncogenic function through the regulation of SMARCC2 ubiquitination and can serve as a potential therapeutic target for pancreatic cancer (8). In human liver cancer, FBXO28 is a key inhibitor of migration, invasion, and metastasis, which can promote the degradation of SNAI2 in a PKA-dependent manner (9). Currently, the expression of FBXO28 in GC and its possible association with GC patient prognosis are not clear.

In the present study, bioinformatics analysis was combined with the experiments to explore the expression, molecular function, prognostic value, and the associated mechanisms of FBXO28 in GC, which could possibly offer novel targets for diagnosis and therapy. We present this article in accordance with the TRIPOD and MDAR reporting checklists (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-2039/rc).

Methods

Bioinformatics analysis

The TIMER2.0 database (http://timer.cistrome.org/) was used to analyze the expression of FBXO28 messenger RNA (mRNA) in various types of cancer, and the FBXO28 mRNA in GC was verified on the Gene Expression Profiling Interactive Analysis (GEPIA) database (http://gepia.cancer-pku.cn/). The GSE62254 dataset containing 300 GC samples was retrieved from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/), and the related clinical information was statistically analyzed and processed using R language. The association between FBXO28 expression and the prognosis of patients with GC was investigated using Kaplan-Meier Plotter (https://kmplot.com/analysis/).

Cell lines

Five types of GC cell lines were selected at the early stage of the experiment. Among them, AGS and HGC27 cells had the best growth status and the most stable expression. Therefore, AGS and HGC27 cells, and a human gastric mucosal epithelial cell line (GES-1) were selected for the experiments (The Chinese Academy of Sciences). And the data from the other three cell lines were not shown. AGS cells were grown in F12 medium (MeilunBio, Dalian, China), HGC27 cells were maintained in RPMI1640 medium (Corning, Inc., Corning, United States), and GES-1 cells were cultured in high glucose medium (HyClone, Logan, United States). 10% fetal bovine serum (FBS) and penicillin/streptomycin (SevenBio, Beijing, China) were supplemented into all media. The cells were cultured at 37 ℃ in a humidified incubator with 5% CO₂ (Thermo Fisher Scientific, Inc., Waltham, United States).

Clinical specimens

The research subjects were 213 who experienced radical operation at The First Hospital of China Medical University between March 2007 and December 2008, among whom 152 were male and 61 were female, with an average age of 59 years (26–83 years). None of the patients received chemotherapy or radiation therapy prior to surgery, while they underwent clinical observation every 2–3 months. All specimens were diagnosed by two professional pathologists. Furthermore, the present study was authorized by the Ethics Committee of The First Hospital of China Medical University (No. AF-SOP-07-1.2-01/IRB approval No. [2023]592), and all patients signed informed consent. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Reverse transcription-quantitative polymerase chain reaction (RT-qPCR)

According to the operation procedure, TRIzol was used to extract total RNA, and complementary DNA (cDNA) was obtained using a reverse transcription kit (TransGen Biotech Co., Beijing, China). Next, primers and reaction buffer were added to start the reaction. This experiment was performed in the following order: 94 ℃ for 30 sec, followed by 45 cycles of denaturation at 94 ℃ for 5 sec and annealing at 60 ℃ for 60 sec. Data processing was performed using the 2^−ΔΔCq method and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was selected for normalization.

Western blotting

The Radio Immunoprecipitation Assay (RIPA) lysis buffer (SevenBio, Beijing, China) could isolate proteins from cells, and the bicinchoninic acid assay kit was selected to quantify the protein content. The proteins were separated using 10% sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) gel (Epizyme, Inc., Cambridge, United States) and transferred to the polyvinylidene fluoride (PVDF) membrane. The membranes were blocked by rapid sealing solution (Wuhan Servicebio Technology Co., Ltd., Wuhan, China) for 15 min at room temperature to prevent non-specific binding, and then placed in the solvent containing primary antibodies overnight at 4 ℃. Following washing, the membranes were incubated with the secondary antibodies for 1 h. The enhanced chemiluminescence reagents (Biosharp Life Sciences, Shanghai, China) were then applied to detect the protein expression. The primary antibodies used included FBXO28 (dilution, 1:2,000; cat No. FNab03042; FineTest, Wuhan, China), Vimentin (dilution, 1:2,000; cat No. PTM-5376; PTM Biolabs, Hangzhou, China), N-Cadherin (dilution, 1:2,000; cat No. PTM-5221; PTM Biolabs), E-Cadherin (dilution, 1:2,000; cat No. PTM-6222; PTM Biolabs), extracellular signal-regulated kinase (ERK) (dilution, 1:2,000; T40071; Abmart, Shanghai, China); phosphorylated ERK (p-ERK) (dilution, 1:2,000; T40072; Abmart); cellular myelocytomatosis oncogene (c-Myc) (dilution, 1:2,000; T55150; Abmart); GAPDH (dilution, 1:20,000; M20006; Abmart). The secondary antibody was HRP-conjugated Affinipure goat Anti-Rabbit IgG (dilution, 1:20,000). ImageJ, a software specifically designed for the scientific processing of Western blotting results, was used for densitometry analysis.

Cell transfection

The GC cells were transfected with small interfering RNA (siRNA) and plasmids (Hanbio Biotechnology Co., Ltd., Shanghai, China) using Lipo8000 (Beyotime Institute of Biotechnology, Shanghai, China) upon reaching 70–80% confluence in 6-well plates. The sequences of the siRNAs were as follows—si-FBXO28-1: forward, CAUUCUUGCUGCUGUUGAATT; reverse, UUCAACAGCAGCAAGAAUGTT; si-FBXO28-2: forward, GGCAGAGCUAGAACGCAAATT; reverse, UUUGCGUUCUAGCUCUGCCTT; si-NC: forward, UUCUCCGAACGUGUCACGUTT; reverse, ACGUGACACGUUCGGAGAATT. To each well, 5 µL of siRNA or 2.5 µg of plasmid, 125 µL of Opti-MEM medium, and 4 µL of Lipo8000 transfection reagent were added. A total of 48 h after the transfection, the cells were harvested for further experiments. Simultaneously, RT-qPCR and western blotting were used to assess the efficiency of knockdown and overexpression at the RNA and protein levels.

Cell viability assay

The Cell Counting Kit-8 (CCK-8) assay is a method commonly used to explore cell viability. GC cells in good growth state were selected, and 1×10³ cells were placed in each well of a 96-well plate. At 0, 24, 48, 72, and 96 h of culture, 100 µL fresh medium and 10 µL CCK-8 reagent were added to every well, and the optical density (OD) values were measured at 450 nm following incubation for a further 1 h in the incubator.

Wound healing test

In a 6-well plate, the same number of GC cells were placed in each well. When no gap could be seen between cells, a 200 µL pipette tip was utilized to scratch the bottom of every well. Following three washes of the cells with 1× phosphate-buffered saline (PBS), the FBS-free medium was added, and the healing status of the scratches was photographed under a microscope (Olympus Corporation, Tokyo, Japan) at intervals of 0 and 48 h in the same position.

Transwell assay

A solution containing 5×10⁴ cells was placed in the Transwell’s upper layer with the volume supplemented to 200 µL with serum-free medium, while 600 µL serum-containing medium was placed into the lower layer of the chamber. Following a 48-h incubation period, cells passing through the membrane were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet dye. Five locations were randomly chosen to evaluate the migration ability of the cells. Subsequently, the cell invasion assay was conducted using a Matrigel-coated Transwell chamber, and the other procedures were the same as before.

Flow cytometry

GC cells transfected for 48 h were collected and resuspended with 195 µL Annexin V-FITC conjugate, 5 µL Annexin V-FITC, and 10 µL propidium iodide (PI) staining solution. The cell apoptosis was checked by flow cytometry following culture for 15 min at room temperature. The transfected cells were then fixed with 70% ethanol at 4 ℃ for 2 h in order to analyze the cell cycle. Following centrifugation and after discarding the supernatant, 500 µL PI staining solution was injected and incubated for 30 min at 37 ℃. The flow cytometry detected red fluorescence at 488 nm.

Immunohistochemical (IHC) staining

The obtained clinical samples of GC were made into tissue microarrays and stained with hematoxylin-eosin. The microarrays were boiled in citrate buffer for 10 min for antigen retrieval, and then incubated with primary antibody overnight at 4 ℃, followed by secondary antibody incubation for 30 min, and staining with 3,3'-diaminobenzidine for 1 min. Scoring was based on the intensity of staining, which was categorized as follows: 0 (−, negative), 1 (+, weak expression), 2 (++, moderate expression) or 3 (+++, strong expression). If IHC showed heterogeneity, the score was based on the proportion of positive cells: 0 (negative), 1 (≤10%), 2 (>10% and <50%), 3 (>50 and ≤80%), and 4 (>80%). The two scores were multiplied: 0–4 for the negative group and 5–12 for the positive group.

Statistical analysis

The experimental data acquired in the present study were evaluated and processed by R 4.4.2, SPSS 26.0, and GraphPad Prism 9. The mean ± standard deviation could illustrate the data, and the unpaired t-test was adopted to assess the differences between the measurements of the two groups. If the unequal variances occurred when the unpaired t-test was performed, the Welch test was selected for comparison. One-way analysis of variance (ANOVA) followed by Tukey’s multiple comparisons test was used to compare multiple groups. The Chi-squared test and Fisher’s exact test were utilized to analyze the categorical variables. Survival analysis was performed using the Kaplan-Meier method and compared via the log-rank test. All experiments were repeated independently three times, and P<0.05 was regarded as statistically significant.

Results

FBXO28 expression in GC

The online database TIMER2.0 could analyze the differential mRNA expression of FBXO28 in various cancers, and the results showed high transcription levels in 7 types of cancer: BRCA, CHOL, ESCA, HNSC, LUAD, LUSC, and STAD, as well as low levels of transcripts were observed in KICH, KIRP, and UCEC (Figure 1A). The mRNA expression of FBXO28 was analyzed in 408 GC cases and 211 paracancerous tissues included in The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases through the GEPIA database, and it was discovered that the expression of FBXO28 mRNA in GC tissues was higher than that in adjacent tissues (P<0.05) (Figure 1B). Subsequently, the FBXO28 expression was examined in GES-1 and GC cell lines (AGS, HGC27) using RT-qPCR and western blotting experiments. The differences in expression levels between GES-1 and AGS/HGC27 were compared. RT-qPCR results manifested that FBXO28 mRNA expression in AGS was higher than that in GES-1 (P<0.005), and the expression in HGC27 cell line showed a decreasing trend without statistical significance (Figure 1C). The phenomenon of opposite expression may be related to the differences in the transcription process of different GC cells. At the protein expression level, it was observed that the FBXO28 expression in both AGS (P<0.001) and HGC27 (P<0.001) was lower than that in GES-1 (Figure 1D). The fact that FBXO28 exhibited different expression levels in AGS may be related to its translational process regulated by other factors. The protein expression of FBXO28 was examined in human normal mucosal tissues and GC tissues by immunohistochemistry. The findings indicated that GC tissues had lower levels of FBXO28 protein expression than normal mucosal tissues (P=0.04) (Figure 1E; Table 1). The inconsistency between mRNA and protein expression is a common phenomenon in the regulation of eukaryotic gene expression, which is mostly related to post-transcriptional regulation, post-translational regulation, and post-translational modification. The differential expression of FBXO28 at the mRNA and protein levels is not a conflict of experimental results, but a reflection of the multi-level regulation of gene expression in GC. The expression of a gene is mostly evaluated from the protein level, so the expression at the mRNA level is more suitable as a reference.

Figure 1 Bioinformatics analysis and expression of FBXO28 in GC cells and tissues. (A) Pan-cancer analysis of FBXO28 mRNA expression by the TIMER2.0 database (*, P<0.05; **, P<0.01; ***, P<0.001). (B) The GEPIA database was used to analyze the mRNA expression of FBXO28 in GC. T represented tumor, which was GC tissues; N represented normal, which refers to adjacent tissues. Red represents GC tissues and black represents adjacent tissues (*, P<0.05). (C) RT-qPCR (**, P<0.005). (D) Western blotting (***, P<0.0005; ****, P<0.0001). (E) IHC staining. FBXO28, F-box protein 28; GC, gastric cancer; GEPIA, Gene Expression Profiling Interactive Analysis; IHC, immunohistochemical; mRNA, messenger RNA; RT-qPCR, reverse transcription-quantitative polymerase chain reaction; TPM, transcripts per million.

Roles of FBXO28 knockdown and overexpression in GC

Among the two GC cell lines selected, siRNA transfection was performed to decrease the expression of FBXO28, and plasmid transfection was performed to overexpress FBXO28. The differences in expression levels between si-NC and si-FBXO28-1/2, empty vector and oe-FBXO28 were compared. The efficiencies are shown in Figure 2A,2B. Based on this result, si-FBXO28-2 and oe-FBXO28 were selected for follow-up GC cell function experiments. The effect of the changes in FBXO28 on the proliferation ability of GC was analyzed using CCK-8 assay. The results demonstrated that the cell viability of the si-FBXO28-2 group was higher than that of the negative control group, while the oe-FBXO28 group’s cell viability was lower than that of the empty vector group (Figure 2C). Cell scratch healing and Transwell assays revealed the effect of FBXO28 on the migration and invasion ability of AGS and HGC27 cells. FBXO28 knockdown enhanced the process of migration and invasion, and FBXO28 overexpression inhibited these processes (Figure 3). Figure 3A was analyzed by calculating the difference in the area occupied by cells that grew within 48 h; Figure 3B was analyzed by calculating the difference in the number of cells that migrated and invaded after 48 h. Flow cytometry with annexin V-FITC and PI dual staining was also employed to investigate the role of FBXO28 on apoptosis. The si-NC/empty vector group was used as the control group in each experiment, and their apoptosis rate was set to 1. The apoptosis rate in the si-FBXO28-2 group was found to be lower than that in the si-NC group in both types of GC cells, and the oe-FBXO28 group exhibited a higher ratio (Figure 4A). In addition, the data between the G0/G1 phase, S phase, and G2/M phase of the si-NC/empty vector group and si-FBXO28-2/oe-FBXO28 group were compared to investigate whether the expression level of FBXO28 affected the distribution of the cell cycle. The results of the RNase A/PI staining flow cell cycle assay indicated that the majority of cells were in the G0/G1 phase and the cycle distribution was unaffected by FBXO28 (Figure 4B). In conclusion, FBXO28 inhibited the proliferation, migration, and invasion of GC cells and induced cell apoptosis.

Figure 2 Construction of GC cells with FBXO28 knockdown and overexpression. The knockdown (A) and overexpression (B) efficiency of FBXO28 were detected by RT-qPCR and western blotting. (C) The proliferation of GC cells was discovered by the CCK-8 assay. The proliferative ability was weakened with the increase in FBXO28 expression (*, P<0.05; **, P<0.005; ***, P<0.0005; ****, P<0.0001). CCK-8, Cell Counting Kit-8; FBXO28, F-box protein 28; GC, gastric cancer; OD, optical density; RT-qPCR, reverse transcription-quantitative polymerase chain reaction.

Figure 3 The effects of knocking down and overexpressing FBXO28 on the migration and invasion ability of GC cells. (A) The scratch healing assay evaluated the migration (magnification ×40). (B) The Transwell assay evaluated the migration and invasion (magnification ×200). ***, P<0.0005; ****, P<0.0001. FBXO28, F-box protein 28; GC, gastric cancer.

Figure 4 Flow cytometry. (A) Effect of changes in the FBXO28 expression level on the apoptotic ability of GC cells. Q1: necrotic cells; Q2: early apoptotic cells; Q3: late apoptotic cells; Q4: normal cells. (B) Cell cycle distribution of GC cells. *, P<0.05. FBXO28, F-box protein 28; GC, gastric cancer.

FBXO28 might affect epithelial-mesenchymal transition (EMT) via the MAPK/ERK signaling pathway

Cell function assays suggested that FBXO28 might participate in the migration and invasion process of GC cells, which could be induced by the aberrant activation of EMT. N-cadherin/cadherin 2 (CDH2) is an essential EMT-related biomarker, and its expression level is closely correlated with the invasiveness of tumor cells. The analysis of the GEPIA database manifested that N-cadherin mRNA exhibited lower expression levels in STAD tissues (Figure 5A). The N-cadherin expression in 27 normal mucosal specimens and 213 GC tissues was analyzed, and no significant difference was found (Table 2; Figure 5B). Therefore, western blotting experiments were carried out to examine the changes in the protein expression levels of EMT-related genes in GC cells following the knockdown and overexpression of FBXO28. The experimental results showed that the expression of Vimentin and N-cadherin in the AGS and HGC27 cells of the si-FBXO28-2 group was higher than that in the si-NC group, whereas the expression of E-cadherin was lower than that in the si-NC group; the opposite expression could be seen when FBXO28 was overexpressed (Figure 5C,5D). Considering that the MAPK/ERK pathway could regulate the EMT process, the connection between the expression levels of MAPK/ERK pathway-associated biomarkers and FBXO28 was explored. According to the western blotting results, the expression of ERK1/2, p-ERK1/2, and c-Myc was elevated in the HGC27 cell line of the si-FBXO28-2 group, and their expression was decreased in the oe-FBXO28 group compared with the empty vector group. To further verify whether FBXO28 indeed regulated its function through the MAPK/ERK pathway, an inhibitor (PD98059) was added to the HGC27 cells that knocked down and overexpressed FBXO28. PD98059 was a potent and selective MEK inhibitor, and it was also an ERK1/2 signaling inhibitor. PD98059 was dissolved in dimethyl sulfoxide (DMSO) and incubated at a concentration of 40 µmol/L for 12 h before termination. The differences between si-FBXO28-2 group and si-FBXO28-2 + PD98059 group, oe-FBXO28 group and oe-FBXO28 + PD98059 group were compared. It could be seen that, compared with the si-FBXO28-2 group, the expression of ERK1/2, p-ERK1/2, and c-Myc was all reduced after the addition of the inhibitor, while the expression of these biomarkers was increased in the oe-FBXO28 group after the addition of the inhibitor (Figure 5E). This meant that PD98059 could reverse the downregulation of EMT-related gene expression caused by FBXO28 overexpression. The same experiments were also performed in AGS cells, but the results obtained were not all meaningful, so they were not presented. The above results suggested that FBXO28 may participate in the EMT of GC cells through the MAPK/ERK pathway.

Figure 5 Pathway analysis. (A,B) Expression of N-cadherin in GC. (A) The GEPIA database analyzed the expression of N-cadherin mRNA in GC. T represented tumor, which was GC tissues; N represented normal, which refers to adjacent tissues. Red represents GC tissues and black represents adjacent tissues. (B) IHC staining. Effects of FBXO28 knockdown (C) and overexpression (D) on the expression levels of EMT-associated molecules in GC cells. (E) Effects of FBXO28 knockdown and overexpression on the expression of the proteins associated with the MAPK/ERK pathway. *, P<0.05; **, P<0.005; ***, P<0.0005. EMT, epithelial-mesenchymal transition; FBXO28, F-box protein 28; GC, gastric cancer; GEPIA, Gene Expression Profiling Interactive Analysis; IHC, immunohistochemical; MAPK/ERK, mitogen-activated protein kinase/extracellular signal-regulated kinase; mRNA, messenger RNA; TPM, transcripts per million.

Correlation between FBXO28 expression and clinicopathological features

The GSE62254 dataset in the GEO database, which included 300 GC samples, was selected to investigate whether FBXO28 was associated with the clinicopathological features of patients. The FBXO28 expression in the GSE62254 was found to differ between these clinical subgroups (Figure 6A). The difference in expression levels between every two groups was compared, and the horizontal line under each P value represented the two selected datasets. It was shown that patients with GC aged >65 years had a higher FBXO28 expression than those aged <65 years (P=0.01), and male patients had a higher FBXO28 expression than female patients (P=0.03). In addition, as the malignancy of GC increases, the expression of FBXO28 gradually decreased (T2 vs. T3, P=0.02; N0 vs. N2, P=0.003; N0 vs. N3, P=0.002; N1 vs. N3, P=0.04; M0 vs. M1, P=0.02). The clinical data collected from 213 patients with GC were then analyzed. It was found that the proportion of FBXO28-positive patients was higher in the ≤60-year group than in the >60-year group (P=0.03), and high expression of FBXO28 was significantly correlated with lower lymph node metastasis rate (P=0.04) and lower malignancy degree (P=0.04), but it was not relevant to gender, tumor site, tumor size, depth of infiltration, degree of differentiation or lymphatic vessel invasion (Table 3). The high expression of N-cadherin may be associated with the low differentiation of GC (P=0.04) (Table 4). The Spearman’s correlation coefficient results verified that FBXO28 was negatively correlated with N-cadherin in GC tissues (R=−0.621). The same conclusion was reached in the Spearman correlation coefficient on the GEPIA database (R=−0.38) (Figure 6B).

Figure 6 The relationship between FBXO28 and clinical factors. (A) The distribution of FBXO28 in clinicopathological features of GC samples included in the GSE62254 dataset. (B) Spearman correlation test of the association between FBXO28 and N-cadherin/CDH2 in GC by using the GEPIA database. (C,D) The correlation between clinicopathological characteristics and survival time in GC patients: (C) univariate Cox regression analysis; (D) multivariate Cox regression analysis. (E,F) The relationship between FBXO28/N-cadherin expression and prognosis of GC: (E) high expression of FBXO28 predicted better OS; (F) low expression of N-cadherin predicted better OS. CI, confidence interval; FBXO28, F-box protein 28; GC, gastric cancer; GEPIA, Gene Expression Profiling Interactive Analysis; HR, hazard ratio; M, metastasis; N, node; OS, overall survival; T, tumor; TPM, transcripts per million.

FBXO28 is linked to GC prognosis

To understand the value of the clinicopathological characteristics on patients with GC prognosis, univariate and multivariate Cox regression analysis were performed on GC samples in GSE62254. It was found that all clinical factors except age and gender were associated with prognosis, and FBXO28 could serve as an independent predictor to determine the prognosis of GC (Figure 6C,6D). Analysis on the Kaplan-Meier Plotter database showed the high expression of FBXO28 and low expression of N-cadherin/CDH2 predicted a better overall survival (OS) (Figure 6E,6F). Univariate and multivariate Cox regression analysis was also performed for 213 patients with GC using SPSS software, and indicated that the FBXO28 expression, N-cadherin expression, age, lymph node metastasis and lymphatic invasion could be separate risk variables for GC and played a predictive role for OS (Table 5). The Kaplan-Meier survival curves of 213 patients with primary GC showed that patients with a positive FBXO28 expression in GC tissues had a better OS than those with negative expression. However, higher N-cadherin expression was associated with worse OS. The expression of FBXO28 was combined with that of N-cadherin in GC and categorized the patients into a double-positive group (FBXO28⁺/N-cadherin⁺), two single-expression groups (FBXO28⁺/N-cadherin⁻, FBXO28⁻/N-cadherin⁺) and a double-negative group (FBXO28⁻/N-cadherin⁻). The survival time of the FBXO28⁺/N-cadherin⁻ group was prominently higher than that of the FBXO28⁻/N-cadherin⁺ group (Figure 7A). This outcome was consistent with the results covered in the public database. To further investigate the relationship between FBXO28 and prognosis in different subtypes of GC, statistical analysis was performed according to age, Borrmann classification and lymph node metastasis. The stronger the FBXO28 staining, the better the prognosis for each subtype of GC (Figure 7B). The association between N-cadherin and the prognosis of subgroups with different degrees of differentiation was investigated. It was found that the stronger the expression of N-cadherin, the worse the OS (Figure 7C). Based on the risk factors identified by the multivariate COX regression analysis, a nomogram was created in which higher total points meant a worse prognosis (Figure 8A). The nomogram’s prediction efficacy was assessed by calibration curves (Figure 8B), and the 3- and 5-year area under the curve (AUC) values were 0.757 and 0.817 (Figure 8C), which indicated that our model had a good predictive ability.

Figure 7 The relationship between FBXO28 and GC patient prognosis. (A) High expression of FBXO28 in GC tissues predicted better OS; high expression of N-cadherin in GC tissues predicted poorer OS; the OS of the FBXO28⁺/N-cadherin⁻ group was higher than that of the FBXO28⁻/N-cadherin⁺ group. (B,C) The relationship between FBXO28/N-cadherin and GC patient prognosis in different clinical subgroups. (B) Kaplan-Meier survival analysis of the correlation between FBXO28 and the prognosis of GC patients based on age, Borrmann typing and lymph node metastasis. (C) The N-cadherin expression was strongly related to OS in subgroups with different degrees of differentiation. FBXO28, F-box protein 28; GC, gastric cancer; OS, overall survival.

Figure 8 Construction and verification of nomogram. (A) Nomogram of 3- and 5-year OS. (B) The calibration curves for predicting 3- and 5-year patient survival. (C) 3- and 5-year ROC curves. AUC, area under the curve; FBXO28, F-box protein 28; LVI, lymphatic invasion; N, lymph node metastasis; OS, overall survival; ROC, receiver operating characteristic.

Discussion

GC is one of the most common tumors, and its incidence increases with age. Recent studies have indicated that the incidence and mortality of GC are gradually decreasing in certain high-prevalence regions and developed countries (10). Nevertheless, GC still has a high mortality rate of 75% in many parts of the world, with higher rates in males (11). In addition, recurrence and metastasis are common factors leading to poor prognosis in patients with advanced GC (12-14). Although there has been a great breakthrough in GC treatment, its prognosis is still not optimistic. The existing prognostic biomarkers for GC are hampered by poor specificity, low clinical applicability, and a lack of predictive power for treatment response, making it difficult to accurately assess patient prognosis and formulate individualized treatment strategies. Consequently, it is particularly necessary to research the molecular mechanisms of GC and actively seek specific biomarkers for diagnosis and treatment.

FBPs are essential components of SKP1-cullin 1-F-box (SCF) E3 ligase complex, which is involved in the ubiquitination cascade reaction. FBPs are able to specifically recognize the substrate and determine the reaction type (15,16). According to different carboxyl-terminal regions, FBPs are divided into three subclasses: FBXW, FBXL, and FBXO (17). The abnormal activation of FBPs has been widely reported in several cancer types, particularly in digestive system tumors (18,19). FBPs influence carcinogenesis and tumor progression by ubiquitination and degradation of downstream substrates (20). The cancer stem cells (CSCs) in tissues coordinate tumor growth, advancement, and metastasis (21). FBPs have been shown to be integral players in the development of cancer stemness traits. For instance, FBXW7 participates in protecting CSCs from cell death caused by anti-cancer drugs (22,23). In addition, FBPs may serve as targets for reversing the onset and impacts of chemotherapy resistance, which may contribute to studying chemical resistance in individualized cancer therapies (24). FBXO28, mentioned in this study, belongs to the FBXO subclass. The core function of FBXO28 is to serve as the substrate-recognition subunit of the SCF ubiquitin ligase complex in the ubiquitin-proteasome system (UPS), participating in fundamental biological processes such as cell cycle regulation and signal transduction by mediating the ubiquitination and degradation of target proteins (25). Currently, research on FBXO28 in tumors is insufficient, and FBXO28 is highly expressed in pancreatic ductal adenocarcinoma (26). To date, no study has reported a link between FBXO28 and GC.

The results of the online databases indicated that the mRNA expression of FBXO28 was high in some tumors, including GC. RT-qPCR and western blotting experiments were selected to detect the FBXO28 expression in GC cells. It was found that at the mRNA expression level, the FBXO28 expression in AGS was higher than that in GES-1. However, the FBXO28 expression in both GC cells was lower at the protein expression level, which might be related to the regulatory process after mRNA synthesis. A decrease in FBXO28 expression was also observed in GC tissue specimens. Next, siRNA and overexpression plasmid were utilized to knock down and overexpress FBXO28 in two types of GC cells. A series of cell function experiments were conducted on these transfected GC cells, including CCK-8 assay, cell scratch assay, Transwell migration and invasion assay, and flow cytometry for apoptosis and cell cycle distribution. Knocking down FBXO28 could improve the proliferation, migration, and invasion ability of GC cells, but decrease their apoptotic ability. The opposite result was observed when FBXO28 was overexpressed. In addition, flow cytometry revealed that FBXO28 did not play a role in the cycle distribution of GC cells.

EMT is a biological process associated with carcinogenesis (27,28). Cancer cells become a highly migratory and invasive phenotype through this process and are regulated by multiple epigenetic mechanisms, with changes in their relevant biological indicators. EMT is a key biological process for GC cells to acquire invasive and metastatic capabilities. Its core features include the downregulation of epithelial markers (such as E-cadherin) and the upregulation of mesenchymal markers (such as N-cadherin and Vimentin), accompanied by a morphological transformation from an epithelial to a mesenchymal phenotype. This transition enhances the migration, invasion, and anti-apoptotic abilities of the cells. Furthermore, EMT promotes tumor progression and drug resistance by modulating the tumor microenvironment (29-31). A number of studies have explored the ways in which FBPs act on the EMT process. FBXW7 induces ubiquitination and proteasomal degradation of Ras homolog gene family member A proteins, leading to the blockade of EMT (32). It plays an important anti-cancer role and can regulate Snail, which is a key factor in EMT (33,34). FBXO11 stimulates EMT through the PI3K/Akt signaling pathway and facilitates the metastasis of GC cells (35). Furthermore, FBXO22 and FBXO31 restrain cancer’s EMT by mediating ubiquitin-proteasome degradation of Snail1 (36). Given the above analysis of the relationship between FBP family members and EMT, it can be speculated that FBXO28 may also regulate the EMT process. The present results showed that FBXO28 knockdown increased the expression of Vimentin and N-cadherin and decreased that of E-cadherin, indicating that it encouraged the occurrence of EMT in GC cells. The opposite result was observed following FBXO28 overexpression, indicating that the EMT process was inhibited. This suggested that FBXO28 plays a significant role in the EMT process of GC.

The mitogen-activated protein kinase (MAPK) cascade represents one of the oldest evolutionary signaling pathways, transmitting signals by sequentially activating three to five layers of protein kinase (37-39). Four MAPK cascades have been discovered in eukaryotic cells, each containing at least three layers: MAP3K, MAPKK, and MAPK (40). Among them, the MAPK/ERK pathway is the most well-studied one. ERK 1/2 is a member of the MAPK family that can transmit extracellular signals to intracellular targets (41). The ERK cascade is responsible for fundamental processes such as cell proliferation and differentiation, and is a highly regulated cascade (42). The ERK cascade’s activation happens in most tumors (43). The MAPK/ERK signaling pathway is a key regulatory component in cell biology, and the stimulation of this pathway promotes the malignant phenotype of cancer. In GC, multiple biomarkers can regulate the MAPK/ERK pathway to drive the proliferation and malignant transformation of tumor cells, thereby promoting tumor growth and metastasis and influencing the prognosis of GC patients. The MAPK/ERK pathway can also promote EMT progression in cancer (44,45). For example, GINS2 can advance EMT of pancreatic cancer by specifically activating the MAPK/ERK signaling pathway (46). The progression and recurrence of hepatocellular carcinoma may be associated with the occurrence of EMT induced by exosomes via the MAPK/ERK pathway (47).

Since the MAPK/ERK signaling pathway can regulate EMT, the effect of FBXO28 on this pathway was investigated. Western blotting experiments showed that knocking down FBXO28 expression increased the expression levels of pathway-related markers ERK, p-ERK, and c-Myc, while FBXO28 overexpression decreased the expression of ERK, p-ERK, and c-Myc. In addition, the PD98059 pathway inhibitor was added to transfected GC cells and it was found that FBXO28 could partially reverse the activation of the MAPK/ERK signaling pathway. Thus, it was confirmed that FBXO28 affected cell function through the MAPK/ERK pathway in GC cells. Moreover, the GSE62254 dataset containing 300 GC samples from the GEO database was selected to investigate whether there were differences in the expression level of FBXO28 among different clinical factor groups. The same analysis was performed on 213 GC samples. Univariate and multivariate Cox regression analyses were utilized to explore the correlation between these clinical factors and GC patient prognosis, and it was found that FBXO28 could be an independent predictor of GC prognosis. Survival analysis showed GC patients with a high expression of FBXO28 had a better OS.

The present study examined the expression, biological function, and clinical significance of FBXO28 in GC, which helped elucidate the correlation between FBXO28 and GC. The downstream mechanism of FBXO28 in GC was also investigated, and it was found that FBXO28 was able to induce EMT through the MAPK/ERK pathway, which might be related to the changes in the biological functions of GC cells. However, there are some limitations in this study. In vivo experiments are needed to complement and validate the anticancer function of FBXO28 in the GC mouse model. There is an inconsistency in the expression of FBXO28 at the mRNA and protein levels in GC cells, which also needs to be further studied. Based on the above discussions and experimental results, we boldly hypothesize that FBXO28 may exert its tumor-suppressive effect by ubiquitinating and degrading oncogenic proteins, as well as inhibiting the MAPK/ERK signaling pathway. However, the specific molecular mechanisms require further in-depth investigation. GC treatment regimens involve the use of various drugs, and the relationship between FBXO28 and drug sensitivity necessitates more detailed clinical studies. And exploring the clinical significance of constructing a prognostic model jointly based on FBXO28 and the clinical characteristics of GC is crucial for promoting the clinical translation of FBXO28. All of the above are our future research directions.

Conclusions

In summary, the findings revealed that FBXO28 plays an anti-cancer role in GC. The molecular mechanism research results indicated that FBXO28 is involved in the occurrence of EMT, which may be mediated by the MAPK/ERK pathway. The high expression of FBXO28 predicted a better prognosis for GC patients. All the work above suggests that FBXO28 may become a potential target for the diagnosis and treatment of GC.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the TRIPOD and MDAR reporting checklists. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-2039/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037tcr-2025-2039/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-2039/prf

Funding: This work was supported by the National Natural Science Foundation of China (No. 81870539 to C.L.); the Xingliao Talent Plan Project of Young Talents (No.XLYC1907086 to C.L.); and Natural Science Foundation Program of Liaoning Province (No. 2024-MS-055 to X.S.).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-2039/coif). C.L. reports that this work was supported by the National Natural Science Foundation of China (No. 81870539 to C.L.); the Xingliao Talent Plan Project of Young Talents (No. XLYC1907086 to C.L.). X.S. reports that this work was supported by Natural Science Foundation Program of Liaoning Province (No. 2024-MS-055 to X.S.). The other 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 present study was performed in line with the principles of the Declaration of Helsinki and its subsequent amendments and approved by the Ethics Committee of The First Hospital of China Medical University (No. AF-SOP-07-1.2-01/ IRB approval No. [2023]592). Written informed consent was obtained from all participants prior to the commencement of the study.

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

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