Multivesicular body subunit 12B (MVB12B) overexpression represses proliferation and migration in bladder urothelial carcinoma

Introduction

According to the global cancer statistics 2022, bladder cancer is the ninth most frequently diagnosed cancer globally, with an estimated 614,000 new cases and 220,000 deaths occurring. The incidence and mortality rates are markedly elevated in males, with a male-to-female ratio of approximately 3–4:1 (1). It ranks as the sixth most common cancer and the ninth leading cause of cancer death in men, which characterized by a high recurrence rate and substantial treatment costs, severely impacts patients’ quality of life and survival outcomes (1). Bladder urothelial carcinoma (BLCA), as the most common type of bladder cancer, accounts for more than 90% of case (2). BLCA exhibits remarkable histological and molecular heterogeneity, it is broadly classified into non-muscle-invasive bladder cancer (NMIBC, ~75% of patients) and muscle-invasive bladder cancer (MIBC, ~25% of patients) (3). The World Health Organization (WHO) 2022 classification underscores this diversity, recognizing numerous histological variants beyond conventional urothelial carcinoma, such as micropapillary and plasmacytoid variants, which are highly aggressive and associated with poor survival (4). The diagnostic of NMIBC relies heavily on cystoscopy and urinary cytology. However, cystoscopy is invasive and costly, while urinary cytology suffers from low sensitivity for low-grade tumors (5). To address these limitations, a new generation of non-invasive urinary biomarkers has emerged. Among these, the Bladder EpiCheck test, which analyzes the methylation profile of 15 specific genomic loci, has demonstrated high sensitivity and specificity for high-grade BLCA, offering a promising tool to reduce unnecessary cystoscopies (5,6).

Beyond histology, comprehensive molecular characterization has revealed a complex landscape of genetic alterations and distinct molecular subtypes that drive tumor behavior and therapeutic responses (7,8). These molecular subtypes, broadly categorized into luminal and basal lineages, are driven by alterations in key signaling pathways such as RTK/RAS, PI3K/AKT and cell cycle regulation, which offer potential targets for novel therapeutic strategies (9). Furthermore, dysregulation of chromatin modifiers and other epigenetic mechanisms also contributes to BLCA pathogenesis (9). The clinical presentation of BLCA often correlates with disease stage. Gross hematuria is the predominant presenting symptom in BLCA patients at initial diagnosis, while pain and constitutional symptoms typically arise in advanced or metastatic cases and correlate with poor prognosis (10,11). Current therapeutic strategies primarily include surgery, chemotherapy, and immunotherapy, yet their effectiveness is often hampered by late-stage diagnosis and the development of resistance (12,13). Therefore, understanding the underlying mechanisms of BLCA and identifying potential biomarkers for early detection and prognosis are critical steps in improving patient management and treatment outcomes.

Multivesicular body subunit 12B (MVB12B), also known as C9orf28 or FAM125B, is located on chromosome 9 (9q33.3) and encodes a protein that serves as a component of the endosomal sorting complex required for transport-I (ESCRT-I), which plays a critical role in the biogenesis of multivesicular bodies and the sorting of ubiquitinated cargos into intraluminal vesicles within endosomes (14,15). The function of MVB12B involves promoting the downregulation of the epidermal growth factor receptor (EGFR), and tyrosine phosphorylation of MVB12B may contribute to the upregulation of ubiquitination in response to EGF stimulation (16). Additionally, both MVB12 depletion and overexpression inhibit HIV-1 infectivity and induce aberrant viral assembly defects, and this finding indicates a unique role for MVB12B in regulating ESCRT-mediated virus budding (17). Nandakumar et al. found that intracellular bacteria engage a STING-TBK1-MVB12b pathway to enable paracrine cGAS-STING signaling, indicating it exploits this pathway to evade host immunity (18). Recently, prior research has preliminary explored a correlation between MVB12B and tumors, such as melanoma, glioma and BLCA (19-21). However, the study of MVB12B in tumor is still rare, and its specific role in BLCA remains inadequately explored.

This study aims to elucidate the expression characteristics of MVB12B in BLCA and its relationship with clinicopathological features, and further investigate the biological role of MVB12B in BLCA cells. We employed a multidisciplinary approach integrating bioinformatics analysis, clinical specimen evaluation, and cellular experiments to investigate the role of MVB12B in BLCA. The findings indicated that MVB12B was significantly downregulated in BLCA, correlating with tumor stage and histological grade, vitro experiments also showed that MVB12B overexpression inhibited BLCA cells proliferation and migration. This research not only highlights the potential of MVB12B as a novel biomarker for early diagnosis and prognostic evaluation of BLCA, but also contributes to opening avenues for future therapeutic strategies targeting MVB12B. We present this article in accordance with the TRIPOD and MDAR reporting checklists (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1498/rc).

Methods

Bioinformatics analysis

This study retrieved mRNA sequencing data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) via the University of California, Santa Cruz Xena browser (UCSC Xena) for pan-cancer analysis (https://xenabrowser.net/datapages/). These data encompass RNA-seq raw read counts, which were transformed to FPKM values and further log₂(value +1) converted. In addition, we utilized the limma package and ggplot2 package in R to analyze the expression of MVB12B and detected the expression between paired tumor tissue samples and adjacent tissue samples based on TCGA database (https://portal.gdc.cancer.gov). Next, the expression of MVB12B in BLCA was verified using the GSE3167 dataset (https://www.ncbi.nlm.nih.gov/geo/). The expressions of MVB12B in various BLCA cell lines from the Cancer Cell Line Encyclopedia (CCLE) database (https://sites.broadinstitute.org/ccle) were obtained.

Furthermore, the expression of MVB12B in BLCA patients with different clinicopathologic features was analyzed. To analyze the efficacy of MVB12B expression in BLCA from normal tissues, we performed receiver operating characteristic (ROC) analysis. Then, through the Encyclopedia of RNA Interactomes (ENCORI) database (https://rnasysu.com/encori/panCancer.php), the BLCA samples were classified into high-expression and low-expression groups based on the median expression level of MVB12B, and survival analysis was conducted to compare the overall survival rate between the two groups.

Protein-protein interaction (PPI) network analysis

Additionally, to analyze the protein interactions of MVB12B, we utilized the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database (https://cn.string-db.org/) with a minimum interaction score set at 0.9. As a result, the PPI network was successfully constructed (22).

Gene set enrichment analysis (GSEA)

To further explore the underlying biological mechanisms associated with MVB12B gene in BLCA, the GSEA was performed by GSEA software (version 4.3.3). In this study, the expression level of MVB12B was used as a continuous phenotype, and the c5.go.bp.v2024.1.Hs.symbols.gmt gene set was selected as the reference gene set. Gene sets meeting the criteria of |NES| >1, NOM P-val <0.05, and FDR q-val <0.25 were defined as significantly enriched (23).

Clinical samples

The BLCA tissues were purchased from Guilin Fanpu Biotechnology Co., Ltd., Guangxi, China for immunohistochemistry (IHC) and quantitative real-time polymerase chain reaction (qRT-PCR). A total of 81 tissues were involved in IHC assay, including 63 BLCA and 18 para-cancerous tissues, and 10 BLCA and 10 para-cancerous tissues were detected by qRT-PCR. All patients were newly diagnosed and without other tumors or undergone chemotherapy or radiation. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Guilin Fanpu Biotechnology Co., Ltd. (Fanpu [2018] No. 23). Informed consent was waived in this retrospective study.

IHC assay

The primary antibody used for IHC was the MVB12B polyclonal antibody (Invitrogen, Rockford, USA, PA5-60468). Immunohistochemical SP method was used to routinely dewax, gradual hydration of gradient alcohol, and repair antigen etc. The diluted MVB12B primary antibody (dilution 1:100) was incubated at 4 ℃ overnight, and IHC staining kit SP-9002 (zsbio, Beijing, China) were used. After DAB color reagent was added, hematoxylin was counterstained to the slice. The scoring of MVB12B was calculated by employing a semi-quantitative method with a staining index (SI), and SI = (percentage score of positive cells) × (staining intensity score). Staining intensity (contrast of staining with background) as follows: 0 (background color), 1 (light yellow), 2 (brown), 3 (tan). Percentage of positive cells as follows: 1 (<10%), 2 (10−50%), 3 (51−75%), 4 (>75%). The staining results were classified based on SI values as follows: 0 to 2 (negative), 3 to 4 (weak), 5 to 8 (moderate), and 9 to 12 (strong) (24).

Cell culture

Cell lines [SV-HUC-1 (TCHu169), T24 (SCSP-536), and UM-UC-3 (TCHu217)] were purchased from the Cell Bank of Shanghai Institute of Cell Biology (Shanghai, China). The T24 and UM-UC-3 were cultured in complete cell culture medium, which was mixed with 89% Dulbecco’s Modified Eagle Medium (DMEM) (Gibco, Grand Island, NY, USA), 10% fetal bovine serum (FBS; Gibco, USA), and 1% penicillin-streptomycin mixture (Solarbio, Beijing, China) at 37 ℃ with 5% CO₂. The SV-HUC-1 was cultured in SV-HUC-1 cell specific medium (Procell, Wuhan, China) at 37 ℃ with 5% CO₂.

qRT-PCR assay

Total RNA was extracted from tissues and cells by using Trizol reagent (Takara, Dalian, China). cDNA was synthesized using PrimeScriptTM RT reagent Kit with gDNA Eraser (Takara). The expression of cDNA of MVB12B was detected by using TB Green Premix Ex TaqTM II (Takara) and the primers were synthesized by Sangon Biotech (Shanghai, China).

Construction of stable overexpression cell lines of MVB12B

The design, packaging and identification of lentivirus vector were completed by Jikai Gene Technology Co., Ltd., Shanghai, China. Transfecting the lentivirus into the cells according to the instructions and verifying the successful construction of overexpression cell lines of MVB12B by qRT-PCR.

Cell Counting Kit-8 (CCK-8) assay

The cells were digested by trypsin, and the cell resuspension solution was plated in 96-well plates. The absorbance of CCK-8 [optical density (OD) 450 nm] was then measured at 0, 24, 48, and 72 hours after cell adhesion. Absorbance at OD 450 nm reflects the proliferation rate of cells.

Transwell migration and invasion assay

In the transwell migration and invasion assay, cells were inoculated into transwell chambers and cultured for 48 hours (transwell migration had no Matrigel). The number of cells that crossed the membrane indicates the ability of migration and invasion of tumor cells.

Cell scratch healing assay

The scratched area was recorded in the six-well plate of cell overgrowth and labeled D0. The cells were then incubated in 37 ℃, 5% CO₂, and DMEM medium free of FBS for 24 hours and labeled D24. Cell scratch healing rate reflects cell migration ability.

Statistical analysis

All data were analyzed by R software (version 4.2.1) and GraphPad Prism5 software. A P value <0.05 was considered statistically significant difference.

Results

MVB12B expression in various cancers

First, we used the UCSC Xena database to analyze MVB12B expression in TCGA and GTEx mRNA sequencing data, uncovering notable variations in the expression of MVB12B across a range of cancers. MVB12B mRNA expression was down-regulated in 14 cancer types, including adrenocortical carcinoma (ACC), BLCA, breast invasive carcinoma (BRCA), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), glioblastoma multiforme (GBM), kidney renal papillary cell carcinoma (KIRP), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), ovarian serous cystadenocarcinoma (OV), prostate adenocarcinoma (PRAD), rectum adenocarcinoma (READ) and uterine corpus endometrial carcinoma (UCEC), prominently in BLCA (Figure 1A). Then, paired difference analysis of pan cancer patients in the TCGA database was analyzed. Compared with those in adjacent normal tissues group, MVB12B mRNA expression was down-regulated in BLCA, BRCA, COAD, LUAD, LUSC, PRAD and UCEC, especially in BLCA (Figure 1B). Given this significant downregulation, we further focused on BLCA, as shown in Figure 1C,1D. Next, The GSE3167 dataset in the Gene Expression Omnibus (GEO) database confirmed that MVB12B was down-regulated in BLCA when compared with those in normal urothelial tissues (Figure 1E).

Figure 1 The expression levels of MVB12B across various cancers and normal tissues. (A) Differential expression of MVB12B was analyzed in pan-cancer tissues derived from TCGA and GTEx datasets. (B) MVB12B expression in paired cancer tissues and adjacent normal tissues sourced from TCGA. (C) Differences in MVB12B expression between BLCA and normal tissues. (D) Paired difference analysis of BLCA patients in the TCGA database. (E) MVB12B expression in GSE3167 dataset. *, P<0.05; **, P<0.01; ***, P<0.001; ns, not significant. BLCA, bladder urothelial carcinoma; FPKM, fragments per kilobase of transcript per million; GTEx, Genotype-Tissue Expression; MVB12B, multivesicular body subunit 12B; TCGA, The Cancer Genome Atlas.

Relationship between MVB12B expression and clinicopathologic characteristics of BLCA

Baseline data of 412 patients with BLCA from the TCGA database were statistically analyzed (Table 1). The data were divided into two groups: 206 samples of patients with BLCA with relatively low MVB12B expression and 206 samples of those with relatively high MVB12B expression. There was no significant difference in gender (P>0.99) or age (P=0.32) between the two groups. Regarding different tumor-node-metastasis (TNM) stages, there was no significant difference in the number of BLCA patients with M stage (P=0.14) between the two groups; however, there were significant differences in BLCA patients with T stage (P=0.01), and N stage (P=0.003). Notably, there were significant differences in the number of BLCA patients between the two groups regarding the pathological stage (P<0.001) and histologic grade (P=0.003).

In addition, we conducted a logistic regression analysis to examine the relationship between MVB12B expression and the clinicopathologic features of BLCA (Table 2). Consistent with the baseline statistics, the logistic regression analysis showed no significant differences in gender (P>0.99), age (P=0.32), or M stage (P=0.15) between the two groups. However, the analysis indicated a significant difference between T3 & T4 stage samples and T1 & T2 stage samples [odds ratio (OR) =0.633, 95% confidence interval (CI): 0.411–0.977, P=0.04]. The analysis also indicated a significant difference between N1 & N2 & N3 stage samples and N0 stage samples (OR =0.463, 95% CI: 0.298–0.718, P<0.001). Additionally, the analysis revealed that samples in III & IV and I & II stage was significantly different (OR =0.490, 95% CI: 0.321–0.747, P<0.001). Moreover, a significant difference was found between samples with high grade and low grade (OR =0.217, 95% CI: 0.072–0.656, P=0.007).

Finally, to elucidate the correlation between MVB12B expression and the various pathological stages and histologic grades of BLCA, we conducted an analysis of MVB12B levels in BLCA samples across different pathological stages and histologic grade. The findings indicated that the expression of MVB12B levels were significantly lower in samples classified under the two T stages compared to normal tissues, significant differences were also found between the samples within the two T stages (Figure 2A). Furthermore, MVB12B expression showed a notable decrease in BLCA samples across both N stages, relative to normal tissues. Significant differences were also detected between the samples designated as N0 and N1 & N2 & N3 stages (Figure 2B). In addition, MVB12B was markedly reduced in BLCA classified under two M stages, when compared to normal tissues. However, no significant variations were observed between the samples with M0 and M1 stage (Figure 2C). Additionally, MVB12B expression was significantly down-regulated in samples with two TNM stages of BLCA in comparison to normal tissues. Noteworthy differences were identified between stage I & II and stage III & IV (Figure 2D). The results with the histologic grades of BLCA patients also revealed that MVB12B expression was lower in high-grade BLCA patients when compared with those in low-grade, whereas no significant variations were observed between normal samples and patients in low-grade (Figure 2E).

Figure 2 The variations in MVB12B expression correlated with the clinicopathological features of BLCA. (A) Differences of MVB12B expression between T stages. (B) Differences of MVB12B expression between N stages. (C) Differences of MVB12B expression between M stages. (D) Differences of MVB12B expression between TNM stages. (E) Differences of MVB12B expression between histologic grades. *, P<0.05; **, P<0.01; ***, P<0.001. BLCA, bladder urothelial carcinoma; FPKM, fragments per kilobase of transcript per million; M, metastasis; MVB12B, multivesicular body subunit 12B; N, node; T, tumor; TNM, tumor-node-metastasis.

Diagnostic and prognostic evaluation of MVB12B in BLCA

In TCGA and GTEx datasets, the area under the curve for MVB12B was 0.815 (95% CI: 0.738–0.891) (Figure 3A); In the GSE3167 dataset, the area under the curve for MVB12B was 0.845 (95% CI: 0.737–0.953) (Figure 3B), both results indicating a better diagnostic value for BLCA. Furthermore, to investigate the prognostic significance of MVB12B in BLCA, Kaplan-Meier survival curve was conducted based on TCGA. Result showed the overall survival rate of BLCA patients in the MVB12B high-expression group was significantly higher than that in the MVB12B low-expression group (Figure 3C).

Figure 3 Diagnostic and prognostic evaluation of MVB12B in BLCA. (A) ROC curve base on TCGA and GTEx datasets. (B) ROC curve base on GSE3167 dataset. (C) Overall survival curve. AUC, area under the curve; BLCA, bladder urothelial carcinoma; CI, confidence interval; FPR, false positive rate; GTEx, Genotype-Tissue Expression; MVB12B, multivesicular body subunit 12B; ROC, receiver operating characteristic; TCGA, The Cancer Genome Atlas; TPR, true positive rate.

MVB12B expression is significantly decreased in BLCA cell lines and tissues

We delved into the expression patterns of MVB12B in diverse BLCA cell lines by leveraging the CCLE database (Figure 4A). Subsequently, to substantiate the findings from bioinformatics analysis, we evaluated the expression of MVB12B in BLCA cell lines and tissues. Notably, our results indicated a significant downregulation of MVB12B mRNA in T24 and UM-UC-3 cell lines when compared to SV-HUC-1 cell line (Figure 4B). Consistent with the TCGA dataset, qRT-PCR analysis revealed that MVB12B mRNA levels were significantly lower in BLCA tissues than in para-cancerous tissues (Figure 4C). The IHC results indicated that MVB12B protein was stained strong in the non-tumor group, moderate in the low-grade BLCA group, and weak in the high-grade BLCA group (Figure 4D-4F).

Figure 4 Expression of MVB12B is down-regulated in BLCA tissues and cell lines through experiments validation. (A) Analysis of MVB12B expression in different BLCA cell lines using the CCLE database. (B) mRNA levels of MVB12B in human urinary bladder epithelial cells (SV-HUC-1) and BLCA cell lines (T24, UM-UC-3). (C) MVB12B mRNA levels were significantly lower in BLCA tissues than in paired non-tumorous tissues. (D) IHC analysis of the expression of MVB12B in adjacent non-tumor tissues (100×). (E) IHC analysis of the expression of MVB12B in low-grade BLCA tissues (100×). (F) IHC analysis of the expression of MVB12B in high-grade BLCA tissues (100×). ***, P<0.001. BLCA, bladder urothelial carcinoma; CCLE, Cancer Cell Line Encyclopedia; IHC, immunohistochemistry; MVB12B, multivesicular body subunit 12B.

In addition, the relationships between the expression level of MVB12B protein and gender, age, pathological stage, and histologic grade were verified (Table 3). There was no significant difference in gender (P=0.57) or age (P=0.69) between the two groups. IHC evaluation revealed that the expression of MVB12B was substantially lower in BLCA group than that in the non-tumor group (P=0.04). In addition, the expression of MVB12B protein was higher in the low-grade group than that in the high-grade group (P=0.03). However, there were no obvious differences in the expression level of MVB12B protein when comparing the TNM stage I & II with stage III & IV in the BLCA group (P=0.28). These results showed that MVB12B is significantly reduced in BLCA, and it may be associated with BLCA histologic grade.

Overexpression of MVB12B inhibits the proliferation and migration of BLCA cells

MVB12B was overexpressed using lentiviral transduction in T24 and UM-UC-3 cells. The T24 and UM-UC-3 cells transfected with the MVB12B overexpression segment were considered the experimental group, labeled as OE, while cells transfected only with the empty vector were considered the control group, labeled as NC. The qRT-PCR experimental results indicated that MVB12B overexpression stable cell line was successfully constructed, which can be used for subsequent cellular functional experiments (Figure 5A). To explore the effect of MVB12B overexpression on BLCA cell proliferation, we carried out cell proliferation assays. The results showed that the overexpression of MVB12B significantly inhibited T24 and UM-UC-3 cells proliferation at 24, 48, and 72 h (Figure 5B). To further study the influence of MVB12B on the metastatic capabilities of BLCA cells, we carried out wound healing, transwell migration and transwell invasion assays. Both wound healing and transwell migration assays reveled that MVB12B overexpression attenuated the migration ability of T24 and UM-UC-3 cells (Figure 5C,5D). However, as shown in Figure 5E, there were no significant differences in the number of invaded cells among the various groups of T24 and UM-UC-3 cells, suggesting that overexpression of MVB12B had no significant influence on the invasive ability of T24 and UM-UC-3 cells.

Figure 5 Overexpression of MVB12B could inhibit the proliferation and migration of BLCA cells. (A) qPCR assay was applied to analyze the expression level of MVB12B after transfection by lentiviral. (B) CCK-8 assays. (C) Scratch assays (×40). (D) Transwell migration assays (0.1% crystal violet staining; ×100). (E) Transwell invasion assays (0.1% crystal violet staining; ×100). *, P<0.05; **, P<0.01; ***, P<0.001; ns, not significant. BLCA, bladder urothelial carcinoma; CCK-8, Cell Counting Kit-8; MVB12B, multivesicular body subunit 12B; NC, negative control; OE, overexpression; OD, optical density; qPCR, quantitative polymerase chain reaction.

PPI network and GSEA of MVB12B

Based on the PPI network constructed using the STRING database, we identified 10 proteins interacting with MVB12B: TSG101, VPS25, VPS37B, VPS37C, VPS37A, VPS37D, SNF8, VPS36, UBAP1, VPS28. These proteins are core components of the ESCRT machinery. PPI network is illustrated in Figure 6A, and the functional annotations and interaction scores of these proteins are summarized in Table 4.

Figure 6 PPI network and GSEA results of MVB12B. (A) The PPI network diagram of MVB12B. (B,C) GSEA enrichment plots for biological processes of MVB12B. GSEA, gene set enrichment analysis; MVB12B, multivesicular body subunit 12B; PPI, protein-protein interaction.

GSEA showed that there was a significant negative correlation between the expression level of MVB12B and the two biological processes of keratinization and intermediate filament organization (Figure 6B,6C). This indicated that low MVB12B expression leads to abnormal activation of keratinization and intermediate filament organization, driving the malignant progression of BLCA. This finding is consistent with the association of MVB12B with TNM stage and histological grade based on clinical characteristics, and further aligned with the observation that low MVB12B expression predicted poor prognosis in BLCA patients.

Discussion

As a component of the ESCRT-I complex, a regulator of vesicular trafficking process, MVB12B plays a key role in EGFR downregulation, regulating ESCRT-mediated virus budding, autophagy, systemic lupus erythematosus and other pathological processes (16,17,25-27). A functional connection has been suggested between MVB12B and tumors. Specifically, novel genetic variants of MVB12B in the endosome-related pathway genes may be associated with melanoma prognostic, and MVB12B may be a susceptibility gene in glioma (19,20). Although a study has reported that MVB12B is a potential target gene of miR-212-3p, miR-30c-5p, and miR-206 linked to BLCA pathogenesis, the specific role of MVB12B in BLCA remains unclear (21). To uncover the molecular basis of BLCA progression, this study examined MVB12B expression in BLCA and assessed its functional role in regulating cancer cell phenotypes.

Our study integrates bioinformatics analyses, clinical sample assessments, and cellular experiments to elucidate the expression patterns of MVB12B and its correlation with clinicopathological features. Our findings demonstrate that MVB12B is down-regulated in 14 cancer types, particularly in BLCA. Validation via the GSE3167 dataset confirmed MVB12B’s decreased expression in BLCA, suggesting its potential role in tumorigenesis, which is consistent with prior GEPIA-based analyses (21). Furthermore, the association between MVB12B expression and clinicopathological features of BLCA underscores its clinical relevance. Specifically, reduced MVB12B levels were significantly associated with advanced TNM stages and higher histological grades. Logistic regression analyses confirmed these observations, demonstrating that diminished MVB12B expression correlates with enhanced tumor invasiveness and metastatic potential. Collectively, these findings suggest that MVB12B downregulation may contribute to BLCA progression, positioning it as a promising diagnostic and prognostic biomarker.

Furthermore, experimental validation via qRT-PCR and IHC confirmed significantly reduced MVB12B expression in BLCA cell lines and tumor tissues when compared to normal controls. These findings not only align with our bioinformatics predictions, but also provides a solid foundation for further functional studies. Notably, the marked downregulation of MVB12B in high-grade versus low-grade tumors implies its functional relevance to tumor biology, prompting further exploration of its role in BLCA progression. Beyond its expression profile, we investigated the functional consequences of MVB12B overexpression in BLCA cells. Functional assays revealed that MVB12B overexpression significantly suppresses BLCA cell proliferation and migration, indicating its tumor-suppressive role likely mediated by regulating signaling pathways controlling growth and motility. The above results suggested the low expression of MVB12B is associated with malignant progression and poor prognosis in BLCA patients. Collectively, these results advocate for further exploring and elucidating the precise molecular mechanisms through which MVB12B serves as a therapeutic target in BLCA.

The PPI network analysis indicates that MVB12B significantly interacts with 10 core proteins, all these proteins are critical components of the ESCRT machinery. The ESCRT machinery is responsible for ubiquitinated protein sorting, MVB formation, and lysosomal degradation of membrane receptors (28,29). This study demonstrates that MVB12B interacts with core proteins of the ESCRT-I, -II, and -III complexes, mechanistically linking its function to endocytosis, vesicle trafficking, and ubiquitinated membrane protein sorting (16). Through this axis, MVB12B may promote the downregulation of EGFR, thereby inhibiting the proliferation and metastasis of BLCA. Low MVB12B expression potentially disrupts these interactions, contributing to BLCA progression. While our PPI network predicts these interactions, functional validation through co-immunoprecipitation (co-IP) and lysosomal trafficking assays is required to confirm their mechanistic role in tumor progression.

Notably, GSEA showed significant negative correlation of MVB12B expression with two biological processes closely to epithelial differentiation: keratinization and intermediate filament organization. As we known, keratins, the primary constituents of epithelial intermediate filaments, are essential for maintaining cytoskeletal integrity and cell polarity (30). Keratinization is a critical process in epithelial differentiation, and its dysregulation can promote tumorigenesis by enhancing cellular proliferation and migration. Previous studies reported that keratin facilitates tumor growth and invasion through stimulation of multiple signaling pathways in oral cancer; and Trp53 mutation in keratin 5 expressing basal cells of the bladder disrupts normal keratinization-associated differentiation programs and significantly promotes the development of basal squamous-like invasive bladder cancer (31,32). Furthermore, intermediate filaments play a vital role in maintaining cellular integrity and facilitating cell signaling pathways, such as participating in cell adhesion, tissue integrity, mitosis, apoptosis, and migration (33). Intermediate filament aberrant organization can disrupt normal cellular functions, and promote cancer cell proliferation and migration (34,35). Collectively, these data suggest that low MVB12B expression may dysregulate keratinization and intermediate filament organization—two processes in which aberrant activation is mechanistically linked to BLCA progression. The tumor-suppressive function of MVB12B likely stems from its ability to constrain oncogenic signaling via these pathways, necessitating functional studies to dissect its precise role in maintaining epithelial differentiation.

There appears to be a notable discrepancy between our clinical observations and experimental findings regarding MVB12B. While low MVB12B expression shows an association with advanced disease stage and lymph node metastasis in patients, vitro experiments demonstrated that overexpressing MVB12B inhibits cell migration without affecting matrigel-based invasion. This discrepancy can be attributed to the limitations of the transwell assay, which measures a cell’s isolated capacity to degrade and migrate through an artificial matrix. In contrast, clinical metastasis encompasses a multi-step cascade, including local invasion, intravasation, survival in circulation, and distant colonization, which is heavily influenced by the tumor microenvironment (36). This suggests MVB12B may function primarily by limiting early tumor expansion and local spread (consistent with its migration-blocking effects), thereby indirectly decreasing the likelihood of lymph node metastasis seen clinically, even though it doesn’t directly alter the specific invasive capacity measured in vitro. Three-dimensional (3D) co-culture or in vivo metastasis models are needed to fully resolve this question in future.

Conclusions

Our findings suggest that MVB12B plays an important role in the pathogenesis of BLCA through its involvement in key biological processes and protein interactions. The downregulation of MVB12B correlates with adverse clinical features, including higher tumor grades and stages, and indicates its potential as a prognostic biomarker. Future studies should focus on elucidating the molecular mechanisms by which MVB12B influences tumor progression, and exploring its therapeutic potential in BLCA.

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-2025-1498/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1498/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1498/prf

Funding: This work was supported by the Guangxi Zhuang Autonomous Region Health Committee Self-Funded Scientific Research (Nos. Z20210487 and Z20210951).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1498/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 Guilin Fanpu Biotechnology Co., Ltd. (Fanpu [2018] No. 23). Informed consent was waived in this retrospective 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/.

References

1. Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024;74:229-63. [Crossref] [PubMed]
2. Alfred Witjes J, Max Bruins H, Carrión A, et al. European Association of Urology Guidelines on Muscle-invasive and Metastatic Bladder Cancer: Summary of the 2023 Guidelines. Eur Urol 2024;85:17-31. [Crossref] [PubMed]
3. Minoli M, Kiener M, Thalmann GN, et al. Evolution of Urothelial Bladder Cancer in the Context of Molecular Classifications. Int J Mol Sci 2020;21:5670. [Crossref] [PubMed]
4. Lobo A, Collins K, Kaushal S, et al. Advances, recognition, and interpretation of molecular heterogeneity among conventional and subtype histology of urothelial carcinoma (UC): a survey among urologic pathologists and comprehensive review of the literature. Histopathology 2024;85:748-59. [Crossref] [PubMed]
5. Fiorentino V, Pizzimenti C, Franchina M, et al. Bladder Epicheck Test: A Novel Tool to Support Urothelial Carcinoma Diagnosis in Urine Samples. Int J Mol Sci 2023;24:12489. [Crossref] [PubMed]
6. Pierconti F, Martini M, Cenci T, et al. Methylation study of the Paris system for reporting urinary (TPS) categories. J Clin Pathol 2021;74:102-5. [Crossref] [PubMed]
7. Ramal M, Corral S, Kalisz M, et al. The urothelial gene regulatory network: understanding biology to improve bladder cancer management. Oncogene 2024;43:1-21. [Crossref] [PubMed]
8. Komura K, Hirosuna K, Tokushige S, et al. The Impact of FGFR3 Alterations on the Tumor Microenvironment and the Efficacy of Immune Checkpoint Inhibitors in Bladder Cancer. Mol Cancer 2023;22:185. [Crossref] [PubMed]
9. Audenet F, Attalla K, Sfakianos JP. The evolution of bladder cancer genomics: What have we learned and how can we use it? Urol Oncol 2018;36:313-20. [Crossref] [PubMed]
10. Ahmadi H, Duddalwar V, Daneshmand S. Diagnosis and Staging of Bladder Cancer. Hematol Oncol Clin North Am 2021;35:531-41. [Crossref] [PubMed]
11. Babjuk M, Burger M, Capoun O, et al. European Association of Urology Guidelines on Non-muscle-invasive Bladder Cancer (Ta, T1, and Carcinoma in Situ). Eur Urol 2022;81:75-94. [Crossref] [PubMed]
12. Lenis AT, Lec PM, Chamie K, et al. Bladder Cancer: A Review. JAMA 2020;324:1980-91. [Crossref] [PubMed]
13. Holzbeierlein J, Bixler BR, Buckley DI, et al. Treatment of Non-Metastatic Muscle-Invasive Bladder Cancer: AUA/ASCO/SUO Guideline (2017; Amended 2020, 2024). J Urol 2024;212:3-10. [Crossref] [PubMed]
14. Philips JA, Porto MC, Wang H, et al. ESCRT factors restrict mycobacterial growth. Proc Natl Acad Sci U S A 2008;105:3070-5. [Crossref] [PubMed]
15. Babst M. MVB vesicle formation: ESCRT-dependent, ESCRT-independent and everything in between. Curr Opin Cell Biol 2011;23:452-7. [Crossref] [PubMed]
16. Tsunematsu T, Yamauchi E, Shibata H, et al. Distinct functions of human MVB12A and MVB12B in the ESCRT-I dependent on their posttranslational modifications. Biochem Biophys Res Commun 2010;399:232-7. [Crossref] [PubMed]
17. Morita E, Sandrin V, Alam SL, et al. Identification of human MVB12 proteins as ESCRT-I subunits that function in HIV budding. Cell Host Microbe 2007;2:41-53. [Crossref] [PubMed]
18. Nandakumar R, Tschismarov R, Meissner F, et al. Intracellular bacteria engage a STING-TBK1-MVB12b pathway to enable paracrine cGAS-STING signalling. Nat Microbiol 2019;4:701-13. [Crossref] [PubMed]
19. Lu G, Zhou B, He Y, et al. Novel genetic variants of PIP5K1C and MVB12B of the endosome-related pathway predict cutaneous melanoma-specific survival. Am J Cancer Res 2020;10:3382-94.
20. Robinson JW, Martin RM, Tsavachidis S, et al. Transcriptome-wide Mendelian randomization study prioritising novel tissue-dependent genes for glioma susceptibility. Sci Rep 2021;11:2329. [Crossref] [PubMed]
21. Ge Z, Lin S, Lu C, et al. Panel containing three serum microRNAs: a promising biomarker for early detection of bladder cancer. Front Oncol 2024;14:1470457. [Crossref] [PubMed]
22. Szklarczyk D, Gable AL, Nastou KC, et al. The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res 2021;49:D605-12. [Crossref] [PubMed]
23. Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 2005;102:15545-50. [Crossref] [PubMed]
24. Deng H, Deng L, Chao H, et al. RAB14 promotes epithelial-mesenchymal transition in bladder cancer through autophagy dependent AKT signaling pathway. Cell Death Discov 2023;9:292. [Crossref] [PubMed]
25. Noh SH, Gee HY, Kim Y, et al. Specific autophagy and ESCRT components participate in the unconventional secretion of CFTR. Autophagy 2018;14:1761-78. [Crossref] [PubMed]
26. Gerovska D, Fernández Moreno P, Zabala A, et al. Cell-Free Genic Extrachromosomal Circular DNA Profiles of DNase Knockouts Associated with Systemic Lupus Erythematosus and Relation with Common Fragile Sites. Biomedicines 2023;12:80. [Crossref] [PubMed]
27. Uddin M, Pellecchia G, Thiruvahindrapuram B, et al. Indexing Effects of Copy Number Variation on Genes Involved in Developmental Delay. Sci Rep 2016;6:28663. [Crossref] [PubMed]
28. Vietri M, Radulovic M, Stenmark H. The many functions of ESCRTs. Nat Rev Mol Cell Biol 2020;21:25-42. [Crossref] [PubMed]
29. Henne WM, Buchkovich NJ, Emr SD. The ESCRT pathway. Dev Cell 2011;21:77-91. [Crossref] [PubMed]
30. Li Y, Sun Y, Yu K, et al. Keratin: A potential driver of tumor metastasis. Int J Biol Macromol 2025;307:141752. [Crossref] [PubMed]
31. Khanom R, Nguyen CT, Kayamori K, et al. Keratin 17 Is Induced in Oral Cancer and Facilitates Tumor Growth. PLoS One 2016;11:e0161163. [Crossref] [PubMed]
32. Masuda N, Murakami K, Kita Y, et al. Trp53 Mutation in Keratin 5 (Krt5)-Expressing Basal Cells Facilitates the Development of Basal Squamous-Like Invasive Bladder Cancer in the Chemical Carcinogenesis of Mouse Bladder. Am J Pathol 2020;190:1752-62. [Crossref] [PubMed]
33. Etienne-Manneville S. Cytoplasmic Intermediate Filaments in Cell Biology. Annu Rev Cell Dev Biol 2018;34:1-28. [Crossref] [PubMed]
34. Sharma P, Alsharif S, Fallatah A, et al. Intermediate Filaments as Effectors of Cancer Development and Metastasis: A Focus on Keratins, Vimentin, and Nestin. Cells 2019;8:497. [Crossref] [PubMed]
35. Holle AW, Kalafat M, Ramos AS, et al. Intermediate filament reorganization dynamically influences cancer cell alignment and migration. Sci Rep 2017;7:45152. [Crossref] [PubMed]
36. Gao Y, Rosen JM, Zhang XH. The tumor-immune ecosystem in shaping metastasis. Am J Physiol Cell Physiol 2023;324:C707-17. [Crossref] [PubMed]