Unveiling SNX10: a key player in bladder cancer progression

Abstract

Background

Bladder cancer (BC) ranks as the tenth most common cancer globally, posing a substantial public health burden. Its incidence exhibits marked geographic and demographic variations, emphasizing the need for tailored research and therapeutic approaches. Current strategies prioritize inhibiting BC cell proliferation and invasion to improve survival outcomes. In this study, analysis of 408 BC samples revealed sorting nexin 10 (SNX10) as a key differentially expressed gene. While SNX10 has been implicated in nutrient metabolism, particularly in lipid and bone metabolism, its mechanistic role in BC progression remains poorly defined.

Methods

To investigate SNX10’s function, clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-mediated knockdown was performed in BC cell lines (T24 and UMUC3), followed by phenotypic evaluation. A mouse xenograft model was utilized to assess tumor growth under low SNX10 expression. Functional assays, including proliferation, migration, and invasion tests, were conducted alongside quantitative polymerase chain reaction (qPCR) and Western blot analyses. RNA sequencing (RNA-seq) and Western blot were employed to identify downstream targets and pathways regulated by SNX10, with MYBL2 emerging as a candidate gene.

Results

SNX10 knockdown significantly suppressed BC cell proliferation, migration, and invasion (P<0.05). In vivo, tumors with reduced SNX10 expression exhibited a 40–50% decrease in volume and weight compared to controls (P<0.01). Mechanistic studies linked SNX10 to MYBL2, an oncogene that regulates cell cycle progression and transcriptional activity. RNA-seq data demonstrated that silencing SNX10 downregulated MYBL2 and associated signaling pathways (e.g., PI3K/AKT, MAPK), corroborated by reduced MYBL2 protein levels via Western blot.

Conclusions

This study identifies SNX10 as a pivotal oncogene in BC, driving tumor progression through MYBL2-dependent pathways. Suppression of SNX10 markedly attenuates malignant behaviors and tumor growth, highlighting the therapeutic potential of targeting the SNX10-MYBL2 axis. These findings deepen the current understanding of BC pathogenesis and provide a foundation for metabolism-targeted therapies. Further research is warranted on SNX10’s role in the tumor microenvironment (TME) and its clinical translatability.

Highlight box.

Key findings

• This study identifies sorting nexin 10 (SNX10) as a critical oncogene in bladder cancer (BC), demonstrating that its knockdown suppresses tumor proliferation, migration, and invasion in vitro and reduces tumor growth by 40–50% in a mouse xenograft model. Mechanistically, SNX10 drives BC progression by regulating MYBL2, a downstream oncogene linked to cell cycle progression and transcriptional regulation. RNA-seq and functional analyses reveal that SNX10 silencing downregulates MYBL2 and its associated pathways (e.g., PI3K/AKT, MAPK), establishing a novel SNX10-MYBL2 axis as a central driver of BC malignancy.

What is known and what is new?

• While SNX10 has been implicated in lipid and bone metabolism, its role in cancer progression remains unclear. Besides, MYBL2 has been established as an oncogene in other malignancies, yet its association with SNX10 has not been reported.

• This study identified SNX10 as a master regulator of BC progression via MYBL2-dependent signaling, providing hitherto undocumented evidence of their functional and mechanistic interplay in cancer biology.

What is the implication, and what should change now?

• The SNX10-MYBL2 axis represents a promising therapeutic target for BC, offering potential to impede tumor progression and improve outcomes. Key priorities include the development of SNX10/MYBL2 inhibitors, validation of their efficacy in preclinical models, and the advancement of biomarker-driven clinical trials to translate these findings into precision therapies.

Introduction

Background

Bladder cancer (BC) represents a significant public health concern worldwide, characterized by high incidence and recurrence rates. According to global cancer statistics, BC accounted for over 570,000 new cases and 200,000 deaths worldwide in 2020 (1), ranking as the tenth most common cancer globally, with notable geographic and demographic variations. Epidemiological studies have identified several risk factors contributing to BC, including smoking, occupational exposure to aromatic amines and other carcinogens, and chronic infections, particularly in regions where schistosomiasis is endemic. Age, gender, and genetic predisposition also play critical roles, with higher prevalence observed in older adults, males, and individuals with a family history of the disease (2,3). In recent years, research on the molecular mechanisms underlying BC development and progression has gained significant momentum. This knowledge gap limits the development of new approaches for early diagnosis, personalized treatment, and prognosis evaluation of BC. The present study focused on investigating these mechanisms, aiming to identify critical genetic targets that could unlock new therapeutic avenues. The identification of these key genetic markers could aid in the development of innovative treatment strategies to enhance patient outcomes.

Rationale and knowledge gap

The Cancer Genome Atlas (TCGA) database serves a comprehensive resource for cancer research, providing large-scale genomic, epigenomic, transcriptomic, and proteomic data across numerous cancer types. This repository enables researchers to identify genetic mutations, understand cancer biology, and discover potential biomarkers for diagnosis, prognosis, and treatment. A total of 408 BC samples were obtained from TCGA, including 19 matched cancer-adjacent non-cancerous tissue pairs. Ultimately, sorting nexin 10 (SNX10) was identified as a key differential gene in our study. SNX10, a member of the sorting nexin (SNX) family, reportedly harbors a conserved phosphoinositide-binding phox homology (PX) domain that mediates interactions with phosphorylated phosphatidylinositols (PIs) on cellular membranes (4), playing an essential role in regulating protein sorting, trafficking, and endosomal homeostasis.

Current evidence suggests that SNX10 expression varies across different types of cancers. In some cancers, such as colorectal cancer (CRC) (5) and cervical cancer (CC) (6), lower levels of SNX10 expression have been linked to poorer prognosis, while its functional significance in other malignancies remains to be fully characterized. Zhang et al. systematically analyzed the expression levels and clinical relevance of SNX10 in patients with CRC, exploring the influence of SNX10 on the initiation and advancement of CRC in intestinal epithelium-specific SNX10 conditional knockout (KO) mice (5). They further demonstrated the crucial role of SNX10 in determining the fate of intestinal epithelial cells during CRC development and elucidated the precise mechanisms by which it regulates steroid receptor coactivator (SRC)-mediated signaling pathways. Jiang et al. investigated differential genes between CC and normal tissues using four gene expression profiles from the Gene Expression Omnibus (GEO) database. Patched 1 (PTCH1) and SNX10 were identified as independent prognostic markers, suggesting that these genes offer significant prognostic value (6).

Based on current research findings, SNX10 is not only associated with cancer but also plays a crucial role in the metabolism of key nutrients in the body (7). Hansen and colleagues analyzed genetic data from hundreds of individuals, focusing on the genetic impact on the waist-to-hip ratio and body mass index (BMI). They identified 91 genes associated with waist-to-hip ratio in women and 42 in men, highlighting SNX10 as the most strongly associated gene in women. SNX10 was found to govern adipocyte differentiation and maturation. SNX10 knockdown in precursor cells affected their ability to differentiate into mature fat cells (8). In an animal study, female mice lacking SNX10 did not gain excess fat on a high-fat diet, unlike those with normal SNX10 expression and all male mice on the same diet (8). Lipid metabolism disorders are considered one of the most significant metabolic hallmarks of tumor cells. Lipids not only provide essential nutrients for the malignant proliferation of tumor cells but also help tumor cells adapt to microenvironmental changes (9,10). Bladder carcinogenesis is associated with alterations in lipid metabolism (11,12). Therefore, the identification of SNX10 as a key differential gene is significant for advancing research on the development and progression of BC.

Objective

The current understanding of SNX10’s involvement in BC is limited compared to the well-established knowledge of other genes in this context. Our research focused on how SNX10 affects the proliferation, apoptosis, and migration of BC cells, as well as its interaction with other signaling pathways. Based on our current findings, SNX10 was found to play a crucial role in the progression of BC. Future therapeutic strategies for BC may involve targeting the upstream or downstream pathways of SNX10. We present this article in accordance with the ARRIVE and MDAR reporting checklists (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-169/rc).

Methods

Data acquisition and identification of key gene SNX10

Data was obtained from TCGA to identify differentially expressed genes in bladder urothelial carcinoma (BLCA) compared to normal bladder tissues. Bioinformatics tools and statistical analyses were employed to screen for genes with significant differential expression. Differential gene expression analysis was performed using the “DESeq2” R package. Genes with |log₂ fold change| >1 and false discovery rate (FDR) <0.05 were considered significantly differentially expressed. Among the identified genes, SNX10 was selected for further validation given its potential role in tumor progression.

Cell lines and culture

Human BC cell lines 5637 and T24 were obtained from the American Type Culture Collection (ATCC). The human BC cell lines 5637 and T24 were selected for in vitro experiments due to their well-characterized tumorigenic potential and differential molecular features, which represent distinct subtypes of BC. Both cell lines were cultured in RPMI-1640 medium (Gibco, cat. no. 11875093, New York, USA) supplemented with 10% fetal bovine serum (FBS) (Ausbian, cat. no. A11-102, Shenzhen, China) and 1% penicillin-streptomycin (Gibco, cat. no. 5140122, New York, USA) at 37 ℃ in a humidified atmosphere with 5% CO₂ (SANYO, cat. no. MCO-15A, Osaka, Japan).

Construction of SNX10 knockdown lentiviral vectors

Lentiviral vectors targeting SNX10 and control vectors (scrambled shRNA or empty vector) were obtained from GenePharma (Shanghai, China). 293T cells were seeded at a density of 5×10⁴ cells/well in 24-well plates and cultured for 24 hours before transduction. At the time of infection, virus volumes were determined based on pre-optimized titers. After 8–12 hours of incubation with viral supernatant, the medium was replaced with fresh complete medium. Cells were further cultured for 72 hours. Fluorescence microscopy (Olympus, cat. no. IX71, Tokyo, Japan) was used to assess transduction efficiency. Genomic DNA was extracted using the TIANamp Genomic DNA Kit (Tiangen Biotech, cat. no. DP304-02, Beijing, China) following the manufacturer’s instructions. For antibiotic selection, puromycin (2 µg/mL, Clontech, cat. no. 631303, USA) was added 24–48 hours post-infection. Successfully transduced cells were used for downstream experiments.

Quantitative real-time polymerase chain reaction (qRT-PCR)

Total RNA was extracted from the stable cell lines using the Trizol reagent kit (Pufei Biotechnology Co., Ltd, cat. no. 3101-100, Shanghai, China), according to the manufacturer’s instructions. cDNA was synthesized from 1 µg of total RNA using the Moloney murine leukemia virus (M-MLV) reverse transcriptase kit (Promega, cat. no. M1705, Madison, USA). qRT-PCR was performed using the SYBR Green PCR Master Mix (cat. no. Q311 Vayzme, Nanjing, China) on an ABI 7500 Real-Time PCR System (ABI, cat. No. 4351104, Carlsbad, USA).

Western blot analysis

Protein extraction was performed using radio immunoprecipitation assay (RIPA) buffer (Beyotime, cat. no. P0013B, Shanghai, China) supplemented with protease inhibitor cocktail (Roche, cat. no. P8340, Basel, Swiss). Protein concentrations were determined using the bicinchoninic acid assay (BCA) Protein Assay Kit (Pierce, cat. no. 23227, Waltham, USA). Equal amounts of protein were separated by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred onto polyvinylidene fluoride (PVDF) membranes (cat. no. IPVH00010, Millipore, Boston, USA). The membranes were blocked with 5% fat-free milk in Tris-buffered saline with 0.1% Tween 20 (TBST) for 1 hour at room temperature and then incubated overnight at 4 ℃ with the following primary antibodies: anti-SNX10 (#ab115890, 1:1,000, Abcam, Cambridge, UK) and anti-GAPDH (#2118S, 1:1,000, Cell Signaling Technology, MA, USA). After washing with TBST, the membranes were incubated with horseradish peroxidase-conjugated secondary antibodies (#7704, 1:2,000, Cell Signaling Technology, MA, USA) for 1 hour at room temperature. The protein bands were visualized using the enhanced chemiluminescence (ECL) detection system (cat. no. M3121, Thermo Fisher Scientific, MA, USA) and quantified by ImageJ software.

Colony formation assay

Cells from each experimental group were seeded at a density of 400–1,000 cells per well in a 6-well plate, with three replicates per group. The seeded cells were then cultured in the incubator for up to 14 days or until most individual colonies contained more than 50 cells. During this period, the medium was changed every 3 days, and the cell status was observed. Before the experiment was terminated, cell colonies were photographed under a fluorescence microscope (Olympus, cat. no. IX71), and the cells were washed once with phosphate-buffered saline (PBS). 1 mL of 4% paraformaldehyde (Sinopharm Chemical Reagent Co., Ltd., cat. no. D16013, Shanghai, China) was added to each well to fix the cells for 30–60 minutes, followed by a single wash with PBS; 500 µL of clean, impurity-free Giemsa stain (Shanghai Dingguo Biotechnology Co., Ltd., cat. no. AR-0752, Shanghai, China) was added to each well to stain the cells for 10–20 minutes. The cells were then washed several times with ddH₂O, air-dried, and photographed with a digital camera for colony counting.

Cell proliferation assay [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) & Celigo cell counting assay]

Cells in the logarithmic growth phase were trypsinized and resuspended in complete culture medium. Cell counts were determined using a hemocytometer (Qiujing Bio, cat. no. Xb-K-25, Shanghai, China). Based on the growth rate, 2,000 cells per well were seeded in triplicate to quintuplicate wells. After seeding, plates were allowed to rest until cells settled completely, and cell density was checked under a microscope. In cases of uneven cell distribution, one group was fixed, and the other groups were adjusted and reseeded for uniform density. In this study, we used two methods to detect the proliferation of cells: (I) from day 2 post-seeding, 20 µL of 5 mg/mL MTT solution was added to each well 4 hours before the end of the culture period. After 4 hours, the medium was removed without disrupting the formed formazan crystals, and 100 µL of DMSO was added to dissolve the crystals. Plates were shaken for 2–5 minutes, and OD at 490 nm was measured using a microplate reader (Tecan infinite, cat. no. M2009PR, Männedorf, Switzerland). (II) Starting from the day after seeding, the Celigo (Nexcelom, MA, USA) instrument was used for daily plate readings. By adjusting the input parameters of the analysis settings, the number of cells with green fluorescence in each well of the scanned plate was accurately calculated. The data were then statistically analyzed and plotted to generate a cell proliferation curve over 5 days.

Flow cytometry analysis [fluorescence-activated cell sorting (FACS)]

Cell apoptosis was evaluated by flow cytometry using the Annexin V-FITC/PI apoptosis detection kit (BD Biosciences, cat. no. 556547, New Jersey, USA). Transfected cells were harvested, washed with cold PBS, and resuspended in binding buffer. Cells were dual-stained with Annexin V-FITC and propidium iodide (PI) following the manufacturer’s protocol and analyzed using a FACSCalibur flow cytometer (Millipore, cat. no. Guava easyCyte HT, Boston, USA).

Transwell migration assay

Transwell inserts were placed into new 24-well plates, and 100 µL of serum-free medium was added to the upper chamber. The plates were incubated at 37 ℃ for 1 hour. Cells were harvested, resuspended in a serum-free medium and counted. Cell density was adjusted to 10⁵ cells per well. Serum-free medium was removed from the upper chamber, and 100 µL of cell suspension was added. The lower chamber was filled with 600 µL of 30% FBS medium as a chemoattractant. Plates were incubated at 37 ℃ for 16 hours or as determined by preliminary experiments. After incubation, inserts were inverted on absorbent paper to remove the medium, and non-migratory cells were removed with a cotton swab. Inserts were fixed in 4% paraformaldehyde for 30 minutes, then dried. A staining solution was applied to the lower membrane surface for 1-3 minutes, rinsing, and air drying. Random fields were imaged at 100× and 200× magnification (4 and 9 images, respectively) for each insert.

Wound healing assay

To assess cell migration, a wound-healing assay was performed. Briefly, T24 cells were seeded in a 6-well plate and allowed to reach 90% confluence. A straight scratch was created in the cell monolayer using a sterile 200 µL pipette tip. To ensure consistency, uniform pressure was applied to create a wound of approximately the same width across all wells. The wells were then gently washed with PBS to remove detached cells. Fresh Dulbecco’s Modified Eagle Medium (DMEM) containing 1% FBS was added to minimize cell proliferation and focus on cell migration. Images of the wound area were captured immediately after scratching (0 hours) and at subsequent time points (24 hours, 48 hours) using a phase-contrast microscope.

RNA sequencing (RNA-seq) and bioinformatics analysis

Total RNA was extracted from T24 BC cells transfected with shSNX10 or scrambled shRNA using TRIzol reagent (cat. no. 15596026, Invitrogen, MA, USA), following the manufacturer’s protocol. RNA quality and quantity were assessed using a NanoDrop 2000 spectrophotometer (Thermo Scientific, MA, USA) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, USA). Samples with RNA integrity number (RIN) ≥7.0 were selected for library construction using the NEBNext^® Ultra™ II RNA Library Prep Kit for Illumina (New England Biolabs, Ipswich, USA). Libraries were sequenced using the Illumina NovaSeq 6000 platform (paired-end, 150 bp). Raw sequencing reads were quality-checked using FastQC and trimmed with Trimmomatic (v0.39). Clean reads were aligned to the human reference genome (GRCh38) using HISAT2 (v2.2.1). Gene expression quantification was performed using featureCounts (v2.0.1).

Animal model establishment

BALB/c nude mice (4–6 weeks old) were purchased from the Animal Center of the Chinese Academy of Sciences (Shanghai, China). Mice were kept in specific pathogen-free (SPF) environments with sterilized food and water, maintaining a room temperature of 25–26 ℃. Experiments were performed under a project license (No. GSGC0192193) granted by institutional ethics board of the Peking Union Medical College Hospital, in compliance with institutional guidelines of Institutional Animal Care and Use Committee (IACUC) for the care and use of animals.

Subcutaneous tumor xenograft model

To establish the xenograft model, T24 cells were harvested during the exponential growth phase, washed with PBS, and resuspended in serum-free RPMI-1640 medium. Approximately 5×10⁶ cells in 100 µL were subcutaneously injected into the right flank of each mouse. A completely randomized design was adopted to divide the mice into two groups (n=8 per group). Tumor size was measured every 3 days using digital calipers, and tumor volume was calculated using the following formula:

$$Volume=\frac{Length\times Widt{h}^2}{2}$$ [1]

Mice were monitored for weight loss and general health throughout the experiment. Animals were excluded from the study if any of the following conditions were observed: severe dehydration, lack of spontaneous movement or skin lesions.

Statistical analysis

All experiments were performed in triplicate, and the data were expressed as mean ± standard deviation (SD). Statistical analysis was performed using GraphPad Prism 8.0 software. Differences between groups were analyzed using Student’s t-test or one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test. A P value <0.05 was considered statistically significant.

Results

The association between SNX10 and BC development

A total of 408 RNA-seq samples were collected from TCGA, comprising 19 paired tumor and adjacent normal tissue samples selected and screened for differential expression of SNX10 in BC (Figure 1A). Analysis of these paired samples revealed that SNX10 was closely associated with the development of BC (Figure 1B). Next, cell lines in which SNX10 was knocked down were generated by viral transfection, and expression differences were verified at the protein and RNA levels (Figure 1C,1D). In vivo experiments revealed that SNX10 knockdown significantly suppressed tumor formation (Figure 1E). The results collectively indicated that SNX10 expression was closely associated with BC progression.

Figure 1.

SNX10 expression differences and in vivo experimental validation. (A) The volcano plot visualizes 19 pairs of sample data in BLCA. Each dot represents a gene, with −log10(CPM) on the x-axis and log2 fold change on the y-axis. Red dots indicate significant DEGs (adjusted P value <0.05, |log2FC| >1). Black dots represent DEGs that reject the null hypothesis. (B) Differential expression of SNX10 in 19 pairs of BLCA samples. (C,D) Validation of expression changes in 5637 and T24 stable transplants knocking down SNX10 by Western blot and qPCR. (E) T24 cells with SNX10 knockdown were subcutaneously inoculated into nude mice, and tumor volume and weight were measured after euthanasia. Statistical significance is denoted as follows: **, P<0.01; ***, P<0.001; ****, P<0.0001; Student’s t-test. All data are presented as mean ± SD from at least three independent experiments. BLCA, bladder urothelial carcinoma; CPM, counts per million; DEGs, differentially expressed genes; FC, fold change; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; qPCR, quantitative real-time polymerase chain reaction; SD, standard deviation; SNX10, sorting nexin 10.

SNX10 was significantly associated with BC cell proliferation and apoptosis

After establishing the relationship between SNX10 and BC development, we hypothesized that SNX10 promotes tumor cell proliferation. To verify the above hypothesis, alterations in the proliferative capacity of cells after the knockdown of SNX10 were detected by Celigo cell counting and MTT assays. 5637 and T24 cells showed significantly reduced proliferation compared to controls (Figure 2A,2B). Consistently, colony formation assays revealed a similar trend (Figure 2C). Next, the effect of SNX10 on apoptosis was examined by flow cytometry. Knockdown of SNX10 was found to significantly increase apoptosis in 5637 and T24 cells (Figure 2D). Therefore, these findings suggest that SNX10 promotes the proliferation of BC cells, at least in part, by decreasing their apoptotic capacity.

Figure 2.

Knockdown of SNX10 inhibits the proliferative capacity of BC. (A) Cell proliferation curves of 5637 and T24 cells following SNX10 knockdown were measured by the Celigo cell counting assay over 5 consecutive days (20×). (B) MTT assay showing a decrease in cell viability in 5637 and T24 cells after SNX10 knockdown. (C) Representative images and quantification of colony formation assays in 5637 and T24 cells, indicating reduced clonogenic ability upon SNX10 silencing (100×). (D) Flow cytometry analysis of apoptosis levels in 5637 and T24 cells; increased apoptotic cell populations were observed after SNX10 knockdown using PI and Annexin V-FITC staining. Statistical significance is denoted as follows: ***, P<0.001; ****, P<0.0001. All data are presented as mean ± SD from at least three independent experiments. Student’s t-test was used for statistical analysis. MTT, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide; OD, optical density; PI, propidium iodide; SD, standard deviation; SNX10, sorting nexin 10.

Knockdown of SNX10 expression affected the migration and invasive ability of BC

To clarify the effects of SNX10 on migration and invasion in bladder carcinogenesis, in vitro experiments were conducted to validate its role. In the scratch wound assay, the migratory capacities observed in the experimental group and the control group were compared at 6 and 24 h, respectively. The experimental group exhibited a significant reduction in migration efficiency (Figure 3A,3B). Knockdown of SNX10 significantly reduced the migration and invasion abilities of 5637 and T24 in the transwell assay (Figure 3C,3D). These findings suggest that SNX10 promotes BC metastasis.

Figure 3.

SNX10 modulates the migration and invasion ability of bladder cancer cells. (A) Representative images of wound healing assay at 0, 6, and 24 h in 5637 and T24 cells after SNX10 knockdown (20×). (B) Quantification of the wound healing area shows significantly decreased migration in knockdown groups. (C) Transwell migration assay images showing reduced migratory ability of SNX10-deficient 5637 and T24 cells (crystal violet staining, 100×). (D) Transwell invasion assay demonstrating decreased invasive potential upon SNX10 knockdown. Statistical significance is denoted as follows: ***, P<0.001; ****, P<0.0001. All values represent mean ± SD (standard deviation); experiments were performed in triplicate. Student’s t-test was used for comparisons. SD, standard deviation; SNX10, sorting nexin 10.

SNX10 affected BC progression by regulating MYBL2

To further investigate the specific mechanism by which SNX10 affects BC, cells with knockdown of SNX10 were subjected to RNA-seq, from which the differentially expressed gene MYB proto-oncogene like 2 (MYBL2) associated with SNX10 was screened out (Figure S1). Western blot results showed that protein expression of MYBL2 was significantly reduced in T24 cells with knockdown of SNX10 (Figure 4A). Meanwhile, to clarify the function of MYBL2 as a downstream regulator of SNX10, MYBL2 was overexpressed in T24 with a knockdown of SNX10, which was verified for its expression and phenotype. In transwell assays, overexpression of MYBL2 reversed the inhibitory effect of SNX10 knockdown on cell migratory ability (Figure 4B). Moreover, MTT assays demonstrated that MYBL2 overexpression counteracted the impact of SNX10 knockdown on cell proliferative capacity (Figure 4C). A similar trend was observed in the Celigo cell counting assay (Figure 4D). Overall, our findings suggest that SNX10 drives bladder carcinogenesis via MYBL2-mediated signaling.

Figure 4.

MYBL2 mediates SNX10-regulated proliferation and migration in bladder cancer. (A) Western blot results showing decreased MYBL2 protein expression in SNX10-knockdown T24 cells. (B) Transwell migration and invasion assays reveal that MYBL2 overexpression rescues impaired migratory and invasive capacity caused by SNX10 silencing (crystal violet staining, 100×). (C) MTT assay demonstrates that MYBL2 overexpression restores cell viability in SNX10-knockdown T24 cells. (D) Celigo cell counting assay confirms that MYBL2 overexpression reverses the proliferation defects resulting from SNX10 knockdown (20×). Statistical significance is indicated: ***, P<0.001; ****, P<0.0001. Data are expressed as mean ± SD from at least three independent replicates. Student’s t-test was used for statistical comparison. MYBL2, MYB proto-oncogene like 2; MTT, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide; OD, optical density; SD, standard deviation; SNX10, sorting nexin 10.

Discussion

BC represents a highly prevalent urological malignancy with a significant global impact. A comprehensive understanding of the underlying mechanisms driving BC development is thus essential (13). Our analysis, based on TCGA data, identified SNX10 as being differentially expressed between tumor and normal tissues. Further validation revealed that SNX10 regulates BC proliferation by modulating downstream MYBL2. Based on the TCGA database analysis, high expression of SNX10 is significantly associated with poor prognosis in BC patients, whereas high expression of MYBL2 independently indicates a favorable prognosis, collectively highlighting the antagonistic regulatory effects of molecular heterogeneity on clinical outcomes in BC (Figures S2,S3). Based on our experimental results, further research into the role of SNX10 in BC holds significant promise. Further investigation into SNX10’s mechanisms and interactions within BC could lead to the development of novel treatment strategies and improve patient outcomes.

Members of the SNX family are involved in maintaining endosome/lysosome function, which is crucial for various cellular processes, including the degradation and recycling of cellular components. This positions them as key players in modulating pathways often dysregulated in cancer (14,15). SNX10, similar to other members of the SNX family, contains a PX domain. This domain is structurally conserved across eukaryotes and functions as a phosphoinositide-binding domain. The PX domain plays various crucial roles in cellular processes, including cell signaling, vesicular trafficking, protein sorting, and lipid modification (15). Within the SNX10 gene, the PX domain binds to phosphoinositides and facilitates the interaction between SNX10 and membrane trafficking processes.

In the present study, SNX10 upregulation in BC was associated with enhanced tumor proliferation and migration. Conversely, in colon cancer, SNX10 exhibits contrasting effects. Le et al. explored the role of SNX10 in regulating amino acid metabolism and mTOR signaling pathway activation in mouse CRC (16). Their research was based on the principle that upregulating chaperone-mediated autophagy (CMA) activity aids in regulating the metabolism of cancer cells. Their study demonstrated that SNX10 deficiency promoted the development of colorectal tumors and enhanced the proliferation and survival of CRC cells in male friend virus B (FVB) mice. Besides, SNX10 was found to control mTOR activation by regulating CMA-dependent amino acids, providing a potential target and strategy for CRC treatment. Moreover, another research has shown that p21^Cip1/WAF1, a key effector in various tumor suppressor pathways, is a substrate of CMA. The reduction of p21^Cip1/WAF1 levels due to SNX10-mediated CMA activation contributes to the proliferation and survival of HCT116 cells (17). In gastric cancer, SNX10 also plays a crucial role in tumor proliferation and migration. Deng and Yuan discovered that SNX10 mRNA expression was decreased in gastric cancer tissues and human gastric adenocarcinoma cells (AGS) cell lines (18). Ropivacaine (Rop) has been shown to inhibit the proliferation, migration, and invasion of AGS cells while promoting apoptosis and upregulating SNX10 expression. The mechanism of Rop’s action is likely related to the upregulation of SNX10 expression, which further inhibits the SRC/STAT3 signaling pathway.

Taken together, these studies overlap in their assertion of SNX10’s tumor-suppressive role in colorectal and gastric cancers, typically characterized by downregulation, which inhibits cell proliferation, migration, and survival. This stark contrast with our findings in BC suggests a complex, tissue-specific role for SNX10 that warrants further mechanistic interpretation.

Several factors may explain this duality. Firstly, SNX10 is reportedly involved in endosomal trafficking and vesicle transport, and its downstream targets can vary widely based on the tissue-specific expression of interacting proteins and signaling pathways. Current evidence suggests that, in some epithelial tumors, SNX10 might inhibit Wnt/β-catenin signaling (16), while in others, such as BC, it may facilitate oncogenic signaling through MYBL2 or other mechanisms (17). Secondly, the tumor microenvironment (TME), encompassing immune infiltration, stromal components, and local cytokine profiles, can affect the functional outcomes of SNX10 expression. It is highly conceivable that SNX10 operates in a context-dependent regulatory capacity shaped by extrinsic factors unique to each tissue type. Thirdly, epigenetic regulation (like promoter methylation and histone modification) and post-transcriptional control (such as miRNAs) may play a role in the variable expression and function of SNX10 across different tumor types. Collectively, these insights highlight the necessity of viewing SNX10 not merely as a unidirectional oncogene or tumor suppressor, but rather as a context-specific modulator of cancer behavior. Further mechanistic and in vivo research is essential to clarify how SNX10’s role is delineated across various cancer types, potentially paving the way for tissue-specific therapeutic strategies.

MYBL2, located on chromosome 20q13, is a member of the MYB family of transcription factors (19). The MYBL2 transcript is detectable in various proliferating cell types. In proliferating fibroblasts, MYBL2 activates the expression of CDC2 (116940) and cyclin D1 (168461) genes. The use of MYBL2-specific antisense oligonucleotides inhibits the proliferation of human hematopoietic cell lines. MYBL2 expression is also regulated during the G1/S phase transition, with its transcription being dependent on E2F (189971) activity in a cell cycle-dependent manner. Unlike MYB (189990) and MYBL1 (159405), whose transcriptional activities are primarily restricted to hematopoietic, spermatogenic, and neurogenic progenitor cells, MYBL2 appears to have a broader role in cell proliferation processes (20,21). It is widely expressed in proliferating cells and plays a critical role in cell differentiation, survival, and cycle progression across various tissue types (22). Research has revealed that MYBL2 promotes the progression of malignant tumors, including breast cancer, prostate cancer, lung cancer, and digestive tract malignancies (23-26). Liu et al. conducted a comprehensive study on the role of MYBL2 in BC and uncovered its transcriptional regulatory relationship with CDCA3 (26). Mechanistic investigations identified the specific pathway through which MYBL2 regulates the malignant characteristics of BC cells, identifying MYBL2 as an oncogene in BC. The loss of MYBL2 significantly reduced the aggressiveness of BC cells both in vitro and in vivo, whereas its overexpression increased tumor aggressiveness.

Our research emphasizes the role of SNX10 in regulating MYBL2 expression. While our experiments identified MYBL2 as a key downstream effector of SNX10, the exact regulatory mechanism linking SNX10 to MYBL2 remains unclear. Considering SNX10’s established role in endosomal trafficking and signal transduction, it is likely that SNX10 influences MYBL2 expression indirectly by modulating upstream signaling pathways or transcription factors. One potential mechanism involves the regulation of MYBL2 at the transcriptional level by signaling intermediates, such as E2F or components of the MAPK pathway, which are recognized to regulate MYBL2 transcription. Furthermore, SNX10 may influence the post-transcriptional stability or nuclear localization of regulatory proteins that contribute to MYBL2 expression. These hypotheses warrant further validation using methods like chromatin immunoprecipitation (ChIP), luciferase reporter assays, or co-immunoprecipitation. A more comprehensive understanding of the SNX10-MYBL2 regulatory relationship could uncover new therapeutic vulnerabilities in BC.

To validate the above hypotheses, RNA-seq data was conducted to provide a comprehensive overview of gene expression changes upon SNX10 silencing, pinpointing MYBL2 as a key downstream target. Subsequent validation through western blot confirmed the reduction at the protein level, while quantitative polymerase chain reaction (qPCR) analysis corroborated the decrease at the mRNA level. These results underscore the regulatory relationship between SNX10 and MYBL2, suggesting that SNX10 likely drives cell proliferation and tumorigenesis by modulating MYBL2 expression. Next, rescue experiments were conducted to examine cell proliferation in T24 cells with varying levels of SNX10 knockdown and MYBL2 overexpression. Our results further confirmed MYBL2 as a downstream gene of SNX10.

Our study identified SNX10 as a novel oncogene in BC and highlighted the SNX10-MYBL2 axis as a potential therapeutic target. However, clinical translation remains challenging. Currently, no approved drugs directly target SNX10 or MYBL2. MYBL2, as a nuclear transcription factor, presents inherent challenges for drug development due to the absence of defined ligand-binding domains. Likewise, the role of SNX10 in endosomal trafficking is not fully understood in cancer, and its druggability remains to be established. Future efforts, such as exploring small-molecule inhibitors, RNA-based therapeutics, or targeted delivery strategies, may help overcome these barriers.

Our study has several limitations that should be acknowledged. First, although SNX10 promotes tumor proliferation in BC, it has been reported to function as a tumor suppressor in colorectal and gastric cancers. The tissue-specific duality of SNX10 may arise from context-dependent signaling or epigenetic regulation. Second, our in vivo validation was limited to subcutaneous xenograft models; future investigations employing orthotopic or metastatic models are necessary to better mimic the natural progression of BC. Third, although MYBL2 was confirmed as a downstream effector of SNX10, the detailed molecular mechanisms remain unclear and warrant further investigation. According to RNA-seq, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed significant enrichment of pathways such as EGFR tyrosine kinase inhibitor resistance, AMPK signaling pathway, and ubiquitin-mediated proteolysis. In parallel, the Gene Ontology (GO) analysis highlighted the central roles of ubiquitination, ribosomal function, and mRNA metabolism in the knockdown group (Figure S4A,S4B), providing critical directions for subsequent mechanistic studies. Addressing these limitations will deepen our understanding of SNX10’s oncogenic roles and advance its clinical application as a therapeutic target.

Conclusions

Our findings suggest that SNX10 plays a significant role in BC progression, highlighting its potential as an oncogene. Low expression of SNX10 significantly inhibits BC cell proliferation and migration, promotes apoptosis, and interacts with MYBL2 to enhance the malignant phenotype of BC cells. A comprehensive understanding of SNX10’s regulation of MYBL2 and its impact on BC could pave the way for novel therapeutic strategies targeting SNX10 or its downstream pathways, thereby enhancing clinical outcomes in this patient population. However, further studies are necessary to explore the tissue-specific duality of SNX10’s role in various cancers, and more in-depth mechanistic investigations are required to understand how SNX10 influences tumor progression in BC specifically.

Supplementary

The article’s supplementary files as

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. Experiments were performed under a project license (No. GSGC0192193) granted by institutional ethics board of the Peking Union Medical College Hospital, in compliance with institutional guidelines of Institutional Animal Care and Use Committee (IACUC) for the care and use of animals.

Data Sharing Statement

Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-169/dss

tau-14-07-1912-dss.pdf ^{(98KB, pdf)}

DOI: 10.21037/tau-2025-169