Introduction
Bladder cancer, a prevalent urinary system malignancy with rising global morbidity and mortality [ 1 ], is classified into non-muscle invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) [ 2 ]. NMIBC has a better prognosis and is treatable with transurethral resection of bladder tumor (TURBT) surgery and BCG immunotherapy, while MIBC treatment is more complex [ 3 ]. BCG, a live attenuated vaccine from Conjugative Bacillus bovis, introduced in 1921 for tuberculosis prevention, also stimulates the immune system for tumor treatment, especially in NMIBC by activating the bladder’s immune microenvironment to suppress tumor growth [ 4 ]. However, clinical use faces challenges like drug resistance, bladder irritation, and safety risks. Our research aims to enhance BCG’s efficacy, reduce adverse reactions, and improve outcomes and quality of life for bladder cancer patients.
Macrophages are common immune cells in the tumor microenvironment (TME) and can polarize into pro-inflammatory M1 or anti-inflammatory M2 types, influenced by microenvironmental signals [ 5 ]. M1 has anti-tumor effects, while M2 promotes tumor growth [ 6 ]. Previous team research indicates BCG treatment for bladder cancer may promote macrophage polarization to M1.
Mcl-1 , a key Bcl-2 family member that inhibits apoptosis, is involved in various cancers including pancreatic, gastric, and lung cancer [ 7 – 9 ]. Our group has shown Mcl-1 affects tumor formation, macrophage apoptosis and polarization during Mycobacterium tuberculosis invasion. Knocking down Mcl-1 with shRNA changes macrophage polarization under BCG stimulation, suggesting Mcl-1 downregulation may modulate macrophage polarization and impact BCG’s effect on bladder cancer cells.
The c-Jun N-terminal kinase (JNK) signaling pathway, a key MAPK branch, is vital in stress response, apoptosis, and tumorigenesis. Its dysregulation affects the cellular environment, being a therapeutic target [ 10 ]. In bladder cancer, JNK’s role in apoptosis is of interest due to apoptotic dysfunction in tumor cells [ 11 ]. Previous studies show JNK pathway regulates Mcl-1 expression and is crucial for macrophage apoptosis and polarization in a Mycobacterium tuberculosis mouse model [ 12 , 13 ]. CX43, the main cellular gap junction protein, forms channels for cell-to-cell communication and tissue homeostasis [ 14 ]. It participates in physiological processes and pathological conditions, regulating cell death propensity. Its expression correlates with tumor development, especially in elderly colon cancer patients [ 15 ]. Decreased CX43 expression weakens cell binding in multiple myeloma, promoting tumor growth and metastasis, and its inhibition suppresses cell growth [ 16 ]. Previous studies have shown CX43’s significance in macrophage polarization and apoptosis during Mycobacterium tuberculosis infection [ 17 ]. Research indicates an interaction between the JNK signaling pathway, the anti - apoptotic Mcl-1 gene, and the Cx43 gene, which jointly regulate cell proliferation and apoptosis in bladder cancer cells, highlighting their complex relationship [ 14 ]. We hypothesize that down - regulating Mcl-1 affects BCG - treated bladder cancer cells through influencing macrophage polarization. This process seems tightly associated with JNK signaling pathway activation and CX43 expression.
Advances in bioinformatics have enabled the analysis of complex gene and protein data for biomarker and target identification. To better understand Mcl-1 ’s role in bladder cancer treatment, we used bioinformatics to analyze Mcl-1 expression and signaling pathway activation. Through gene expression profiling, network analysis, and signaling pathway enrichment analysis, we aimed to enhance our comprehension of the interplay between Mcl-1 and the JNK pathways in the treatment of bladder cancer with BCG. Using the GSE190529 BCG-infused bladder cancer microarray dataset from NCBI-GEO, we applied bioinformatics tools for analysis. By exploring gene-function links, we identified key Mcl-1 -related and differential gene enrichment pathways in BCG-treated bladder cancer to understand Mcl-1 ’s role in BCG-mediated effects on bladder cancer cells, and investigated its association with the JNK signaling pathway.
Bladder cancer patients often receive BCG immune infusion post - surgery to prevent recurrence by triggering local immune responses. However, some patients show poor response, resulting in treatment failure and recurrence. We hypothesized Mcl-1 impacts tumor-associated macrophage polarization during BCG therapy. Using bioinformatics and co-culturing Raw264.7 macrophages with mouse bladder cancer MB49 cells to model the microenvironment, we explored the roles of Mcl-1 and JNK signaling in regulating macrophage polarization and BCG’s anti-cancer mechanisms. Our findings provide insights into bladder cancer treatment mechanisms, potentially guiding future treatment improvements.
Materials and methods
Download and processing of the GSE190529 dataset
The GEOquery software package was utilized to retrieve the GSE190529 dataset containing gene expression data from bladder cancer patients who received BCG infusion from the NCBI-GEO (National Center for Biotechnology Information - Gene Expression Omnibus) database.
GSE190529 dataset differential gene enrichment analysis
Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP) [ 18 ] were utilized for quality control, followed by differential gene expression analysis using the DESeq2 software package [ 19 ] to identify genes with significantly altered expression levels under varying conditions. To gain deeper insights into the biological implications of these differentially expressed genes, clusterProfiler software package (Version 4.6.2) [ 20 ] was employed for GO (Gene Ontology), KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis, and GSEA (Gene Set Enrichment Analysis).
Enrichment analysis of key genes in differential genes between Mcl-1 and the GSE190529 dataset
WGCNA (Weighted Gene Co-expression Network Analysis) (v1.72) was utilized to investigate gene interactions and networks [ 21 ], leading to the discovery of a gene cluster linked to Mcl-1 . Through the intersection of genes highly correlated with Mcl-1 and differentially expressed genes, a subset was identified that exhibited both strong correlation to Mcl-1 and significant differential expression. Subsequently, clusterProfiler was employed for enrichment analysis on this subset, revealing insights into their potential biological and signaling pathway functions.
Materia
SP600125 (≥ 95%) was purchased from Selleck (Selleck, United States). BCG freeze-dried powder was purchased from Ruichu Biotechnology Co., Ltd. (Shanghai, China). MNU (N837326) was purchased from Macklin Biochemical Technology Co., Ltd. (Shanghai, China). The MB49 cell line was purchased from iCell Bioscience Inc. (Shanghai, China); the Raw264.7 cell line was purchased from the Cell Bank of the Typical Culture Treasure Committee of the Chinese Academy of Sciences. Anti-Arg-1 (1:1000, ab60176), anti-iNOS (1:1000, ab15323), anti-CD86 (1:500, ab239075) and anti-CD206 (1:1000, ab64693)were purchased from Abcam. Anti-JNK (1:5000, 66210-1-Ig), anti-ASK1 (1:3000, 67072-1-Ig), anti-CX43 (1:4000, 26980-1-AP) were purchased from Proteintech Biotechnology Co., LTD. (Wuhan, China).The following antibodies: Bax (1:1000, bs-4605R), Bcl-2 (1:1000, bsm-52304R), P-ASK1(1:3000, bs-3029R), MKK7 (1:1000, bs-1979R), P-MKK7 (1:300, bs-3277R), P-JNK (1:500, bs-1640R), cJUN (1:1000, bs-0670R), P-cJUN (1:1000, bsm-52141R), CyclinD1 (1:1000, bsm-52046R) and PCNA (1:1000, bsm-52347R), were obtained from Bioss Biotechnology Co., LTD. (Beijing, China). Trypsin, Dulbecco’s Modified Eagle’s Medium (DMEM) and fetal bovine serum (FBS) were purchased from GIBCO.
Co-culture experiments and groups
The cells were grouped into (BCG + M0)-MB49 co-culture group, (BCG + Mcl-1 shRNA + M0)-MB49 co-culture group, and (BCG + Mcl-1 shRNA + M0 + SP600125)-MB49 co-culture group. The transwell culture chambers (American Corning Inc.) were positioned in 6-well plates, with BCG + M0 cells, BCG + Mcl-1 shRNA + M0 cells, and BCG + Mcl-1 shRNA + SP600125 + M0 cells placed in the upper chamber according to the experimental groups. MB49 cells were added to the lower chamber for co-culture.
Establishment of an infection model
Raw264.7 cells infected with BCG were exposed to a bacterial ratio of 10:1, following the methodology described in our previous work. After 4 h, the culture medium was refreshed, and the cells were transfected with Mcl-1 shRNA plasmid. Four hours post-transfection, the medium was replaced, and SP600125 (30umol/l) was introduced. The transfection procedure adhered to the guidelines outlined in [ 22 ], involving the combination of 10µL LipofectamineTM 2000 with 250µL OPTI-MEM, and 4 µg plasmid DNA with another 250µL OPTI-MEM. Following a 20-minute incubation at room temperature, 500µL of the mixture was added to the culture plate.
The preparation of animals and models
Healthy female Sprague-Dawley rats (180 ± 20 g) were obtained from Henan Skibes Biotechnology Co., Ltd. All experiments adhered to standard animal research protocols. The rats were housed at a temperature of 25 ± 2 °C, under a 12-hour light-dark cycle, and provided ad libitum access to food and water.
In order to establish a bladder cancer model, thirty-five rats were randomly allocated into two groups. The control group comprised five rodents, while the bladder cancer group consisted of thirty. After a twelve-hour fast from water, the rats in the bladder cancer group received transurethral bladder perfusions of MNU dissolved in citrate buffer solution (pH 6.0) at a concentration of 10 mg/mL, dosing at 2.0 mg per rat, biweekly, for a total of four administrations. The control group of rats was administered an equivalent volume of physiological saline solution. Subsequent to verification through abdominal ultrasonographic evaluation of the bladder, the animals were deemed to have successfully developed bladder cancer and were utilized for further experimental purposes.
Thirty bladder cancer-afflicted rats were arbitrarily distributed into four cohorts: the model group (BLCA), the BCG group (BCG) at a dosage of 0.1mL/100 g, the BCG combined with Mcl-1 shRNA intervention group (BCG + Mcl-1 shRNA), and the group receiving combined treatment of BCG, Mcl-1 shRNA, and SP600125 (BCG + Mcl-1 shRNA + SP600125). In this experiment, 25 rats were treated with a solution of BCG freeze-dried powder dissolved in saline at a concentration of 0.1mL/100 g for bladder instillation, administered bi-weekly for a total of three sessions. Subsequently, 6 of these rodents were subjected to intervention with Mcl-1 shRNA, an optically selected plasmid that our research team had previously identified and screened [ 22 ]. This intervention entailed daily intramuscular injections of 85 µg per rat, sustained over a period of seven days. In an alternative experiment, a cohort of six rats was subjected to a combinatorial intervention involving Mcl-1 shRNA and SP600125, the latter being solubilized in DMSO at a concentration of 10 mg/mL [ 23 ]. The regimen stipulated a daily intraperitoneal injection for a successive period of seven days. Upon the conclusion of all interventions, euthanasia was humanely conducted on the entire rodent population, followed by the procurement of bladder tissues for subsequent experimental analysis(Fig. 7 A).
ELISA assay
The supernatants from the co-cultured cells in each group were collected, and the expression levels of M1 macrophage-related factor TNF-α and M2 macrophage-related factor IL-10 were determined according to the instructions of the assay kit (MultiSciences Biotech Co., Ltd., Hangzhou, China).
Western blotting
Proteins were extracted from Raw264.7 cells using RIPA buffer and their concentrations were determined by BCA assay. Subsequently, the proteins were separated on 10% or 12% SDS-PAGE, transferred to PVDF membrane, and blocked with 5% BSA or milk in TBS for 2 h at room temperature. The primary antibody (1:1000) was incubated overnight at 4 °C, followed by three 10-minute TBST washes. This was succeeded by incubation with the secondary antibody (1:10,000; Zhongshan Jinqiao, China) for 2 h. Following three TBST washes, the membrane was developed using ECL, imaged on an Odyssey system, and analyzed using ImageJ.
Immunofluorescence analysis
MB49 Cells on coverslips were fixed with 4% paraformaldehyde, permeabilized with 0.2% Triton X-100, and blocked with 5% BSA. The cells were then incubated with the primary antibody (1:100) overnight at 4 °C, followed by incubation with FITC/TRITC secondary antibody (1:500) for 2 h at 37 °C. Nuclei were stained with DAPI (1:1000) and images were captured using a fluorescence microscope (Olympus, Tokyo, Japan).
Cell proliferation assay
Harvest cells from the co-culture, discard the supernatant, trypsinize, and collect the cells. Resuspend them in culture medium, inoculate them into a 96-well plate (3 replicates/group, 4 × 10 3 cells/well), and culture for 24 h. After incubation, add 10 µl of CCK8 to each well to evaluate the proliferation ability. Incubate for 2 h and then measure the absorbance at 450 nm to calculate the proliferation ability.
Transwell invasion experiments
MB49 cells were suspended in serum-free medium and placed in the upper chamber of a transwell system, while the lower chamber was filled with medium containing 20% serum. After 24 h, the cells were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet. Non-invasive cells were removed, and the remaining cells were counted under a microscope. For invasion assays, the membranes were coated with basement membrane matrix (American Corning Inc.) prior to the procedure outlined above.
Cell migration assay
After reaching 80–90% confluence, MB49 cells were subjected to linear scratches using a 100 µl pipette tip. Subsequent images were captured under a microscope (SANYO, Japan) at 0 and 24 h post-scratching. The 24-hour mobility was calculated using the formula: [(0-hour scratch area − 24-hour scratch area)/0-hour scratch area] × 100%.
Apoptosis assay
Hoechst 33,258 experiment
Cell samples were fixed with 1–2 ml of 4% paraformaldehyde for 15 min, followed by the addition of Hoechst 33,258. The samples were then incubated in the dark for 25 min. Finally, observation and photography were conducted using a fluorescence inverted microscope for analysis.
Flow cytometry
Instrument parameter adjustment: Adjust the cell concentration to 1 × 10 6 ~ 3 × 10 6 cells/ml and wash twice with pre-cooled PBS. Then, resuspend the cells in 500 µl of apoptosis positive control solution and incubate on ice for 30 min. Following centrifugation and washing with PBS, resuspend the cells in 1×Binding Buffer, mix with untreated viable cells, and adjust the total volume to 1.5mL. Distribute the cell suspension into 3 EP tubes (1 for blank control and 2 for single dye tubes). Add 5 µl of V-FITC and PI to the dye tubes and incubate at room temperature for 5 min in the dark.
Sample processing: Cells were collected and adjusted to a concentration of 1–5 × 10 5 cells/ml. After washing with cold PBS, they were resuspended in 500 µl of 1×AnnexinV binding buffer. Subsequently, 5µl of FITC and 5µl of PI were added, mixed thoroughly, and the mixture was incubated at room temperature in the dark for 10–15 min. Analysis should be done immediately or the samples can be stored on ice to prevent exposure to light. The entire test should be completed within 1 h.
Tunnel staining
Bladder cancer tissue was isolated, fixed in 4% paraformaldehyde, embedded in paraffin, and cut into 5 μm sections using a cryostat. The slices were then used for Tunel staining following the procedures outlined in the Tunel kit (Shanghai Beyotime Biotechnology Co., Ltd., China). After dewaxing and hydrating the slices, DNase-free proteinase K was added dropwise at a concentration of 20 µg/mL and allowed to react at room temperature for 15–30 min. The slices were washed three times with PBS, followed by the preparation and application of the appropriate Tunel detection solution. After washing with PBS, the cell nuclei were stained with DAPI. Finally, a sealing solution was used to secure a glass cover slip on the section for observation under a microscope and photography.
HE staining
The bladder tissue was sectioned, stained with hematoxylin-eosin (HE), and examined under a light microscope to assess pathological changes.
Immunohistochemistry
Paraffin-embedded sections of bladder tissue were initially washed with PBS, followed by blocking with a blocking solution. Subsequently, the sections were treated with primary antibodies at 4 °C for 24 h, washed, and then incubated with secondary antibodies at room temperature for 1 h. Positive cells were visualized using 3,3-diaminobenzidine, followed by image acquisition using a microscope.
Statistical analysis
Statistical analysis was performed using SPSS 23.0, and graphical editing was conducted using GraphPad 9.5.1 The data were described as the mean ± standard deviation. The statistical significance of the differences was assessed using one-way analysis of variance (ANOVA), paired t-test, and chi-square analysis. P values < 0.05 were considered to be statistically significant.
Results
Bioinformatics results
Dimensionality reduction and visualization of differential genes in datasets
The GSE190529 data set was analyzed using PCA and UMAP algorithms to reduce dimensions and visualize sample distribution in a lower-dimensional space. This allowed for the identification of outliers and a better understanding of data distribution characteristics(Fig. 1 A). Subsequent differential gene analysis was conducted, with screening criteria of Fold Change > 1.2 and P value < 0.05. A total of 157 differential genes were identified, with 61 up-regulated genes (red markers) and 96 down-regulated genes (blue markers) displayed in a volcano plot(Fig. 1 B).
Performing GO functional enrichment and KEGG pathway enrichment analysis on the differential genes
GO enrichment analysis was performed on genes with significant differences in the GSE190529 dataset, revealing 12 entries in the GO functional annotation analysis. The genes showing significant differential changes were primarily associated with immunoglobulin binding and heterotypic intercellular adhesion in the molecular functions category. Additionally, the genes were found to be involved in protein binding, cation channel activity, passive transmembrane transport protein activity, proton transport ATP synthase activity, and rotation mechanism, among others(Fig. 1 C).
KEGG enrichment analysis was performed on differential genes, focusing on hematopoietic cell lines. Enriched pathways include aminoacyl-tRNA biosynthesis, B cell receptor signaling pathway, thermogenesis, Staphylococcus aureus infection, oxidative phosphorylation, and NOD-like receptor signaling pathway(Fig. 1 D).
GSEA enrichment analysis
Enrichment analysis was conducted on all 20,818 genes in the GSE190529 data set to gain insight into the biological processes and pathways. GSEA analysis identified 338 entries, with 23 entries showing significant enrichment. Activated pathways included aminoacyl-tRNA biosynthesis, oxidative phosphorylation, pertussis, leishmaniasis, and rheumatoid arthritis. Conversely, the Wnt signaling pathway was predominantly inhibited(Fig. 1 E).
Identification of genes associated with Mcl-1 through WGCNA analysis
Cluster analysis was conducted on the samples to identify genes suitable for analysis and to create a hierarchical clustering tree. The results indicated that all genes were acceptable for further analysis, ensuring that abnormal data would not impact the subsequent analysis(Fig. 2 A).
In the context of Weighted Gene Co-expression Network Analysis (WGCNA), the selection of an optimal soft-thresholding power value is crucial for network construction. This parameter dictates the linearity or nonlinearity of the network structure. A graphical representation depicting the relationship between the power value and the scale-free topology of the network is utilized to guide this selection process. Opting for a higher scale-free topology as the power value can enhance the network’s resemblance to authentic biological networks(Fig. 2 B). Subsequently, following the determination of the appropriate power value, gene modules are defined using a hierarchical clustering approach in WGCNA. These modules represent groups of genes, with highly correlated gene expression patterns being computed within and across the modules(Fig. 2 C).
To investigate the relationship between various modules and external traits, we calculated the correlation between the module characteristic gene Mcl-1 and the traits. A correlation heat map was generated to visually represent the degree of correlation between each module and different traits. The gene module with the strongest correlation with the Mcl-1 trait is Darkslateblue, which consists of a total of 6936 genes(Fig. 2 D).
Screening of Mcl-1 related genes and differential gene targets with enrichment analysis
The study illustrated the intersection of the gene module exhibiting the highest correlation with Mcl-1 and the differential genes identified in WGCNA. Subsequently, a Venn diagram was constructed to identify 38 differential genes that displayed the strongest correlation with sample traits(Fig. 2 E). The GO enrichment analysis of these differential genes, closely associated with Mcl-1 traits, revealed a total of 16 entries. Among these, 10 entries pertained to biological processes, encompassing themes such as thermogenesis, body temperature homeostasis, stress-activated MAPK cascade response, stress-activated protein kinase signaling cascade, and positive regulation of the MAPK cascade. Additionally, 6 entries were linked to molecular functions, highlighting activities like cytokine activity, receptor ligand activity, and signaling receptor activator activity(Fig. 2 F). The KEGG enrichment analysis further emphasized the involvement of the MAPK signaling pathway in the differential genes closely associated with Mcl-1 traits. Overall, the bioinformatics predictions suggest a significant relationship between the Mcl-1 gene and the MAPK signaling pathway in the context of BCG treatment for bladder cancer(Fig. 2 G).
Extracellular experimental results
Mcl-1 shRNA + BCG: enhancement of M1 polarization of tumor-associated macrophages
ELISA was utilized to detect cell polarization-related markers in the supernatants of co-culture chambers across different experimental groups. The findings revealed that following 12 h of co-culture, there was a significant increase in the M1 type (TNF-α) in the M0 + BCG + Mcl-1 shRNA-MB49 group compared to the M0 + BCG-MB49 group, along with a notable decrease in the M2 type (IL-10). Conversely, inhibition of the JNK signaling pathway resulted in a reduction of the M1 type (TNF-α) and an increase in the M2 type (IL-10).(Fig. 3 A).
The Western blot test results indicated a significant increase in the expression of M1 macrophage-related factors (CD86, iNOS) after down-regulating Mcl-1 compared to the M0 + BCG-MB49 group. Subsequent inhibition with SP600126 led to a significant decrease in the protein expression of M1 macrophage-related factors (CD86, iNOS). However, there was no significant decrease or statistical significance in the expression of M2 macrophage polarization-related factors (CD206, Arg-1) (Fig. 3 B-C).
Mcl-1 shRNA + BCG: suppression effects on MB49 cells
The results of the cell scratch experiment demonstrated a significant reduction in cell migration ability in the M0 + BCG + Mcl-1 shRNA-MB49 group compared to the M0 + BCG-MB49 group. Conversely, the cell migration ability was found to be increased in the M0 + BCG + Mcl-1 shRNA + SP600125-MB49 group compared to the former (Fig. 4 A-B).
The results of the cell invasion experiment demonstrated a significant reduction in migration and invasion ability in the M0 + BCG + Mcl-1 shRNA-MB49 group compared to the M0 + BCG-MB49 group. Conversely, the M0 + BCG + Mcl-1 shRNA + SP600125-MB49 group showed an increase in migration and invasion ability (Fig. 4 C-E).
CCK8 was used to assess the proliferation ability of MB49 cells in each experimental group. The results indicated that the cell proliferation ability of the M0 + BCG + Mcl-1 shRNA-MB49 group was significantly reduced compared to the M0 + BCG-MB49 group. Additionally, the cell proliferation ability of the M0 + BCG + Mcl-1 shRNA + SP600125-MB49 group was found to be increased compared to the M0 + BCG + Mcl-1 shRNA-MB49 group (Fig. 4 F).
Mcl-1 shRNA + BCG: enhancement of apoptosis in MB49 cells
Hoechst 33,258 apoptosis staining of MB49 cells in each group revealed that cells in the M0 + BCG-MB49, M0 + BCG + Mcl-1 shRNA-MB49, and M0 + Mcl-1 shRNA + SP600125-MB49 groups exhibited apoptosis. Specifically, cells in the M0 + BCG group also displayed signs of apoptosis. Interestingly, the M0 + BCG + Mcl-1 shRNA-MB49 group demonstrated increased nuclear fragments and pronounced dense staining compared to -MB49. However, upon administration of SP600125, the apoptotic features were mitigated significantly (Fig. 5 A-B).
Cell apoptosis was assessed using AnnexinV-FITC/PI dual-parameter flow cytometry. The findings indicated a significant increase in cell apoptosis rate in the M0 + BCG + Mcl-1 shRNA-MB49 group compared to the M0 + BCG-MB49 group. Interestingly, the increased apoptosis in the M0 + BCG + Mcl-1 shRNA-MB49 group was reversed by the addition of SP600125 in the M0 + BCG + Mcl-1 shRNA + SP600125-MB49 group(Fig. 5 C-D).
Inhibition of bladder cancer cells: role of Mcl-1 shRNA + BCG in ASK1/MKK7/JNK signaling and CX43 expression
Western blot analysis was utilized to assess the protein expression levels of pathway-related proteins including P-ASK1, ASK1, P-MKK7, MKK7, P-JNK, JNK, P-cJUN, cJUN, and the gap junction protein CX43. The results indicated that the combination of Mcl-1 shRNA and BCG intervention in the co-culture cell model led to a significant increase in the protein expressions of P-ASK1, P-MKK7, P-JNK, and P-cJUN. Subsequent treatment with the JNK signaling pathway blocker SP600125 resulted in a significant reduction in the protein expressions of P-ASK1, P-MKK7, P-JNK, P-cJUN, and CX43 (Fig. 5 E-F).
To further validate the Western Blot results, indirect immunofluorescence was employed to assess the expression of macrophage pathway-related proteins P-ASK1, ASK1, P-MKK7, MKK7, P-JNK, JNK, P-cjun, and cJUN in each experimental group. The results, depicted in Figs. 3 –34, revealed a significant increase in the fluorescence intensity of macrophage proteins P-ASK1, P-MKK7, P-JNK, and P-cJUN in the Mcl-1 shRNA combined with BCG intervention group compared to the M0-BCG group. Conversely, the SP600125 group exhibited a notable reduction in the fluorescence intensity of these proteins, aligning with the Western Blot findings(Fig. 6 A-D). The study suggests that Mcl-1 shRNA may facilitate the polarization of macrophages towards the M1 type through the activation of the ASK1/MKK7/JNK signaling pathway and upregulation of the communication protein CX43. This mechanism potentially enhances the therapeutic efficacy of BCG in bladder cancer treatment.
Animal experiment results
Rat in vitro ultrasound identification of bladder cancer model
Upon completion of the modeling process, the rats were subjected to abdominal ultrasound examinations. The ultrasound revealed that, in comparison to the Sham group, the bladder walls of the rats in the other groups exhibited varying degrees of thickening, accompanied by a hyperechoic region that did not adhere to the contours of the surrounding normal tissues. These observations suggest that the modeling was successfully achieved(Fig. 7 B).
Selection of Mcl-1 shRNA dosage
Mcl-1 shRNA plasmid was administered to rats at various concentrations, and the expression of Mcl-1 protein in bladder cancer tissues was monitored using the Western blot method at different time points. The results demonstrated dose-dependent inhibition of Mcl-1 protein expression. Notably, the most significant effect was observed with the administration of 100 µg of Mcl-1 shRNA plasmid, leading to a substantial reduction in Mcl-1 protein levels in bladder cancer tissue. Rats treated with both 85 µg and 100 µg of Mcl-1 shRNA plasmid exhibited pronounced inhibitory effects on the 7th and 10th days. However, there was no significant difference between the two doses, and the inhibitory effect diminished by day 10. Consequently, the lower dose of 85 µg was chosen as the optimal dose of Mcl-1 shRNA plasmid, with a treatment duration of 7 days identified as the most suitable concentration and time for subsequent experiments (Fig. 7 C-D).
Mcl-1 shRNA + BCG: enhancement of CD86/CD206 expression in bladder cancer tissues
Immunofluorescence staining results revealed varying expression ratios of CD86/CD206 in bladder tissue of mice across different groups. The model group showed a decrease, whereas the BCG and BCG + Mcl-1 shRNA groups exhibited an increase. Notably, the BCG + Mcl-1 shRNA group displayed higher CD86/CD206 expression compared to the BCG group. Conversely, the BCG + Mcl-1 shRNA + SP600125 group showed a decrease in CD86/CD206 expression (Fig. 8 A-B).
Mcl-1 shRNA + BCG: reduction of pathological damage and proliferation-related proteins in bladder cancer
HE staining results revealed significant pathological changes in bladder tissue of mice in the BLCA group compared to the Sham group, indicating the presence of bladder cancer. Both the BCG and BCG + Mcl-1 shRNA groups demonstrated a notable therapeutic effect on bladder cancer, with the combination therapy showing superior efficacy over BCG alone. Interestingly, the therapeutic effect of the Mcl-1 shRNA group was found to be attenuated by the signaling pathway blocker SP600125 (Fig. 8 C).
To further investigate bladder cancer cell proliferation, Western blot analysis was conducted to assess the expression of CyclinD1 and PCNA. The results indicated a significant increase in the expression of CyclinD1 and PCNA in the model group compared to the Sham group. Conversely, the expression of CyclinD1 and PCNA was notably reduced in the BCG and BCG + Mcl-1 shRNA treatment groups, with the BCG + Mcl-1 shRNA group showing the most significant decrease. Interestingly, the BCG + Mcl-1 shRNA + SP600125 group was able to counteract the reduction in CyclinD1 and PCNA expression observed in the BCG + Mcl-1 shRNA group (Fig. 8 D-F).
Mcl-1 shRNA + BCG: promoting apoptosis in bladder cancer cells
TUNEL staining results revealed a noticeable increase in apoptosis in the BCG, BCG + Mcl-1 shRNA, and BCG + Mcl-1 shRNA + SP600125 groups compared to the Sham and model groups. Particularly, the BCG + Mcl-1 shRNA group exhibited the most prominent apoptosis (Fig. 9 A).
Western-blot analysis revealed a significant increase in the expression of the pro-apoptotic protein Bax and a decrease in the expression of the anti-apoptotic protein Bcl-2 in the treatment intervention group compared to the Sham group. Specifically, the BCG + Mcl-1 shRNA group exhibited higher Bax expression and lower Bcl-2 expression. Interestingly, the SP600125 group was able to reverse the pro-apoptotic trend observed in the BCG + Mcl-1 shRNA group (Fig. 9 B-D).
Mcl-1 shRNA + BCG: promoting expression of P-JNK, P-cJUN and CX43 in bladder cancer
Immunochemical staining and Western blot test results revealed an upward trend in the expression of P-JNK and CX43 in the model group. In comparison to the BCG treatment group, the BCG + Mcl-1 shRNA group exhibited a significant increase in the expression of P-JNK, P-cJUN, and CX43, whereas the BCG + Mcl-1 shRNA + SP600125 group showed a decrease in the expression of P-JNK, P-cJUN, and CX43 (Fig. 9 E-J).
Discussion
Bladder cancer, a prevalent type of tumor in the urinary system, can be classified into two categories based on clinical stage: muscle-invasive bladder cancer and non-muscle-invasive bladder cancer [ 24 ]. Among patients undergoing initial outpatient screening, three-quarters have non-muscle invasive bladder cancer, which often recurs within two years after surgical treatment. Recurrent tumors tend to be more malignant, with approximately half of cases progressing to muscle-invasive bladder cancer within five years [ 25 – 28 ]. Current treatments for non-muscle invasive bladder cancer primarily consist of transurethral resection of bladder tumors followed by postoperative intravesical instillation therapy based on risk factors. While the majority of NMIBC patients achieve remission with this approach, approximately half of patients experience relapse [ 29 ]. Recent research has highlighted the significant impact of the tumor microenvironment on the response to BCG treatment, recurrence prevention, and progression of bladder cancer in patients receiving BCG infusion. A thorough and scientific evaluation of the microenvironment is essential for gaining a deeper insight into the intricate anti-tumor mechanisms. By strategically influencing the tumor microenvironment, the effectiveness of cancer treatment can be significantly improved.
BCG is a live attenuated vaccine derived from bovine Mycobacterium tuberculosis and is commonly used to prevent tuberculosis [ 30 ]. Since Morales et al. first suggested the use of BCG for treating bladder cancer in 1976, BCG therapy has emerged as a highly effective approach for non-muscle-invasive bladder cancer [ 31 ]. This treatment not only reduces the risk of disease recurrence but also aids in preventing disease progression and lowering patient mortality rates. Recent studies indicate that BCG therapy can achieve its therapeutic benefits by stimulating the human immune system, particularly through interactions with macrophages in the tumor microenvironment [ 32 ]。.
Although BCG therapy is currently the primary immunotherapy approach for preventing recurrence in patients with non-muscle invasive bladder cancer post-surgery, some patients do not respond to BCG therapy or experience disease recurrence [ 33 ]. To address this challenge, the latest bladder cancer treatment guidelines suggest a new strategy that combines BCG treatment with other immunotherapies as a viable option to enhance efficacy in cases of BCG treatment failure or disease recurrence. Vasekar et al. discovered that by downregulating the programmed death receptor PD-1 in conjunction with BCG, tumor-associated macrophages can transition from M2 to M1, thereby slowing the progression of bladder cancer and improving the prognosis of patients with this condition [ 34 , 35 ]. BCG can induce macrophage polarization towards the M1 phenotype via NMAAP1, demonstrating therapeutic effects in CKO and Flox tumor-bearing mice [ 36 ]. Previous research within the group focused on tuberculosis revealed that modulating Mcl-1 expression through Mcl-1 shRNA or inhibiting the Mcl-1 pathway influenced macrophage polarization mediated by BCG. Additionally, high Mcl-1 expression was observed in bladder cancer paraffin sections and fresh tissues, correlating with prognosis and survival in bladder cancer patients [ 37 ]. Previous research has identified Mcl-1 as a gene implicated in the progression of invasive urothelial carcinoma [ 38 ]. Given this, it is hypothesized that Mcl-1 , similar to PD-1, may emerge as a critical target for bladder cancer therapy. This investigation specifically delved into the role of the anti-apoptotic gene Mcl-1 . The study utilized the Transwell co-culture system, employing macrophage supernatant in combination with BCG and Mcl-1 shRNA intervention as a conditioned medium for co-culturing with MB49 cells. The objective was to assess the impact on the proliferation, migration, invasion, and apoptosis of mouse bladder cancer cells. Results indicated that the combined treatment of BCG and Mcl-1 shRNA significantly attenuated the viability, proliferation, migration, and invasion capabilities of mouse bladder cancer cells compared to BCG intervention alone, while also enhancing apoptosis. These findings suggest that Mcl-1 shRNA in conjunction with BCG can effectively suppress bladder cancer progression by modulating macrophage activity and altering the tumor microenvironment.
In the context of bladder cancer, various subtypes of macrophages play a crucial role in disease progression. Research indicates that M1 macrophages have a negative impact on inhibiting bladder tumor development, while M2 macrophages exhibit the opposite effect, potentially promoting tumor occurrence and growth [ 39 ]. Furthermore, studies have shown that following BCG infusion therapy, there is a significant accumulation of macrophages in the area of bladder cancer invasion and surrounding tissue [ 40 ]. Additionally, Muthuswamy and colleagues discovered that the chemokine CXCL10, associated with M1 macrophages, can be produced during the third week of BCG treatment [ 41 ]. BCG may have an anti-tumor effect by enhancing the presence of M1 macrophages. Previous research from our team suggests that BCG-modulated macrophages tend to shift towards the M1 phenotype in the initial stages. In line with these findings, our experimental study revealed that mouse bladder cancer cells treated withboth BCG and Mcl-1 shRNA showed increased expression of M1 markers (CD86, TNF-α, iNOS) compared to cells treated with BCG alone. The decreased expression of M2 markers (IL-10, CD206, Arg-1) indicates that BCG can further impede the growth, movement, and invasion of bladder cancer cells by impacting macrophages and facilitating apoptosis. This indirectly suggests that the combined therapy of BCG and Mcl-1 shRNA could hinder bladder cancer progression by influencing macrophage polarization towards the M1 phenotype. However, the specific mechanism underlying the treatment of bladder cancer with Mcl-1 in combination with BCG infusion, and its interplay with macrophage polarization, warrants further investigation.
Bladder cancer involves tumor cells evading normal cell death mechanisms, inhibiting the apoptosis process, and failing to clear themselves effectively, leading to uncontrolled cell growth. The JNK signaling pathway, a key branch of the MAPK signaling pathway, plays a critical role in regulating cell proliferation, death, and differentiation [ 42 – 44 ]. MKK7, a direct activator of the JNK pathway, transmits signals from ASK1 to JNK, and is essential for JNK activation [ 45 ]. The ASK1/MKK7/JNK pathway is crucial in modulating immune response and tumor development. Several studies have indicated that in cases of bladder cancer, a significant number of M2 macrophages infiltrate, hindering tumor cell apoptosis and facilitating tumor cell proliferation [ 46 ]. Previous research has also shown the crucial role of the JNK signaling pathway in the macrophage polarization process induced by Mycobacterium tuberculosis infection [ 47 ]. In the progression of lung adenocarcinoma, heterogeneous nuclear ribonucleoprotein A2B1 (HNRNPA2B1) can enhance the production of miR-3153, leading to the activation of the c-Junn terminal kinase (JNK) signaling pathway and the promotion of M2 macrophage polarization, ultimately contributing to the advancement of lung adenocarcinoma [ 48 ]. Nevertheless, the correlation between the JNK signaling pathway and macrophage polarization in BCG treatment for bladder cancer remains unclear.This study utilized bioinformatics and the online GEO database to analyze the data set GSE190529 of bladder cancer patients treated with BCG infusion. By identifying differential genes and key enrichment pathways related to Mcl-1 genes, the activation of the MAPK signaling pathway was predominantly observed. To delve deeper into the role of the JNK signaling pathway, the ASK1/MKK7/JNK signaling pathway was investigated to elucidate the signal transduction mechanism of Mcl-1 combined with BCG in regulating macrophage polarization. Results from mouse bladder cancer cells treated with Mcl-1 shRNA combined with BCG showed increased expression of P-ASK1, P-MKK7, P-JNK, and P-cJUN in macrophages, along with an upregulation of M1 markers (CD86, TNF-α, iNOS). Upon administration of the JNK signaling pathway inhibitor SP600125, a decrease in the expression of P-ASK1, P-MKK7, P-JNK, and P-cJUN was observed, alongside a reduction in M1 markers and an increase in M2 markers (IL-10, CD206, Arg-1). These changes were reversed upon intervention with the JNK inhibitor SP600125, further confirming the involvement of the ASK1/MKK7/JNK signaling pathway. This study discovered that the combination of Mcl-1 and BCG can impact the polarization of bladder cancer macrophages through the ASK1/MKK7/JNK signaling pathway. This finding offers novel insights and a molecular foundation for enhancing BCG therapy for bladder cancer, while also shedding light on the pathology of bladder cancer. The study provides experimental evidence and guidance on physiological mechanisms. Furthermore, previous research by the team revealed that the presence of gap junction CX43 facilitates communication between macrophages infected with Mycobacterium tuberculosis, enhancing the macrophages’ ability to phagocytize bacteria. Therefore, this study also investigated the expression of CX43 in bladder cancer treatment with the combination of Mcl-1 and BCG. The results showed a significant increase in CX43 expression in the BCG-intervention cell model compared to both in vivo and in vitro model groups. Moreover, after the combined intervention of Mcl-1 shRNA and BCG, CX43 expression further increased. This suggests that CX43 acts as a mediator in the immune response triggered by the combined treatment of Mcl-1 shRNA and BCG in bladder cancer, potentially serving as a communication channel between macrophages.
Based on the research findings, it has been demonstrated that regulating Mcl-1 can drive macrophages towards the M1 phenotype through activation of the ASK1/MKK7/JNK signaling pathway. This process enhances intercellular communication and improves the efficacy of BCG in treating bladder cancer. These findings offer novel insights and strategies for bladder cancer therapy and serve as a basis for exploring tumor immunotherapy further. Future investigations could delve into the intricate regulatory mechanisms between Mcl-1 and JNK pathways, as well as the specific role of gap junctions in macrophages during BCG treatment of bladder cancer. Furthermore, integrating bioinformatics analysis with in vivo and in vitro experiments could help confirm the suitability of the JNK signaling pathway in treating other types of tumors, thereby bolstering the scientific underpinning for clinical application. The application of these research outcomes is anticipated to lead to more effective treatment approaches for bladder cancer patients and advance the field of tumor immunotherapy.
Conclusion
The research findings demonstrate that regulating Mcl-1 can drive macrophage polarization towards the M1 type through activation of the ASK1/MKK7/JNK signaling pathway. This process enhances intercellular communication and improves the efficacy of BCG in treating bladder cancer. These findings offer new insights and potential strategies for bladder cancer treatment, opening avenues for further exploration in tumor immunotherapy. Future investigations could delve deeper into the intricate regulatory mechanisms between Mcl-1 and JNK signaling pathways, as well as the specific functions of gap junctions in macrophages during BCG treatment for bladder cancer. By integrating bioinformatics analysis with in vivo and in vitro experiments, researchers can validate the applicability of the JNK signaling pathway in treating other types of tumors, thereby establishing a more robust scientific foundation for clinical translation. The application of these research findings holds promise for developing more effective treatment approaches for bladder cancer patients and advancing the field of tumor immunotherapy.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Supplementary Material 1
Acknowledgements
We acknowledge the valuable analytical data contributed by van Puffelen J et al. to the GEO database. Additionally, we extend our appreciation to Figdraw for offering the drawing website: https://www.figdraw.com/#/ .
Abbreviations
Non-muscle invasive bladder cancer
Muscle-invasive bladder cancer
Transurethral resection of bladder tumor
Bacillus Calmette-guerin
Tumor microenvironment
Myeloid cell leukemia-1
c-Jun N-terminal kinase
National Center for Biotechnology Information - Gene Expression Omnibus
Principal Component Analysis
Uniform Manifold Approximation and Projection
Gene Ontology Enrichment Analysis
Kyoto Encyclopedia of Genes and Genomes
Gene set enrichment analysis
Weighted correlation network analysis
Author contributions
C. X. T. an is responsible for paper writing as well as cell and animal experiments; C. L. is responsible for animal breeding and the construction of animal models; R. H. G. and W. Z. are responsible for cell culture and data analysis; Z. Y. W., S. P. W. and H. T. C. are responsible for the construction of animal models, material collection, and animal data analysis; X. M. W. and L. Z. are responsible for supervising the research and revising the manuscript, and obtained funding.
Funding
This work was partially supported by the Xinjiang Production and Construction Corps Guiding Science and Technology Plan Projects (2022ZD073, 2022ZD045).
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethical approval
and content to participate: all animal experiments were complied with the ARRIVE guidelines and performed in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals. The experiments were approved by the Research Ethics Committee of Shihezi University (Xinjiang, China). All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. All subjects have been approved by the First Affiliated Hospital of Shihezi University. Written informed consent was obtained from each subject.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Caixia Tan and Chen Li are co-first authors.
Contributor Information
Xinmin Wang, Email: 1977602697@qq.com.
Le Zhang, Email: 3654463706@qq.com.
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Associated Data
Supplementary Materials
Supplementary Material 1
Data Availability Statement
No datasets were generated or analysed during the current study.