- 1Department of Nuclear Medicine, Shengjing Hospital of China Medical University, Shenyang, China
- 2Department of Pediatrics, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China
- 3Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China
- 4Department of Microbiology and Immunology, Keio University School of Medicine, Tokyo, Japan
Bladder cancer (BC) represents a paradigm of infection-associated malignancy in which microbial dysbiosis, immune aging, and tumor microenvironmental remodeling converge to shape disease progression. Increasing evidence highlights the dual role of the urinary and gut microbiota in modulating bladder carcinogenesis through infection-driven inflammation and immune dysfunction. Chronic exposure to uropathogens and microbial imbalance disrupts epithelial integrity, promotes extracellular matrix degradation, and reprograms local immune signaling, collectively fostering a tumor-permissive niche. Concurrently, immunosenescence exacerbates microbial persistence and impairs antitumor immunity, reinforcing a pathogenic feedback loop between infection and immune decline. This review integrates current insights from microbiome research, tumor immunology, and microbial pathogenesis to delineate the mechanistic continuum linking infection, dysbiosis, and immune remodeling in BC. Finally, we discuss emerging microbiome-targeted and immunomodulatory strategies aimed at restoring microbial–immune equilibrium and improving therapeutic efficacy. Together, these perspectives provide a refined conceptual framework for understanding infection-driven oncogenesis and guiding precision interventions in BC.
1 Introduction
Bladder cancer (BC) is the second most common genitourinary malignancy globally, with around 550,000 new cases and 200,000 deaths each year (1). Despite significant advances in surgical and systemic therapies, BC continues to exhibit high recurrence rates and poor survival, particularly in advanced or muscle-invasive disease. For advanced BC, the prognosis remains poor, with a 5-year survival rate below 40% (2). This persistent clinical burden underscores the need to better understand non-genetic and microenvironmental factors that shape tumor initiation and progression. In addition to microbial and immune factors, key environmental risk factors for BC include tobacco smoking, which accounts for approximately 50% of cases in developed countries, and occupational exposure to aromatic amines and other toxic chemicals (e.g., in dye, rubber, and leather industries), which contribute to 5-10% of cases. These exposures can induce DNA damage and chronic inflammation, potentially interacting with the urinary microbiome by promoting dysbiosis—such as reduced microbial diversity and enrichment of pro-inflammatory taxa like Proteobacteria—which may exacerbate infection-driven carcinogenesis (3, 4). Exploring these links could reveal how smoking-induced alterations in gut and urinary microbiota amplify oxidative stress and immune dysregulation in the bladder. In recent years, the human microbiome has emerged as a critical determinant of oncogenesis, influencing cancer risk, immune modulation, and therapeutic outcomes across multiple organ systems. The discovery of a resident microbiota within the urinary tract has challenged the long-held assumption of its sterility, paving the way for new research exploring the role of host-microbe interactions in bladder carcinogenesis.
Historically, the role of infection in BC was recognized in regions endemic for Schistosoma haematobium, where chronic parasitic inflammation predisposes to squamous cell carcinoma of the bladder (5–7). Beyond schistosomiasis, growing evidence indicates that bacterial infections—particularly recurrent urinary tract infections (UTIs)—contribute to urothelial carcinogenesis through persistent inflammation, oxidative stress, and epithelial injury. Uropathogenic Escherichia coli (UPEC), responsible for over 70% of UTIs, can invade bladder epithelial cells, form intracellular bacterial communities, and establish chronic reservoirs that are resistant to host clearance. These persistent infections elicit prolonged inflammatory signaling and reactive oxygen species (ROS) production, both of which promote DNA damage and mutagenesis (8–10). Moreover, interactions between schistosomes and cohabiting bacteria—such as Fusobacterium, Sphingobacterium, and Enterococcus—can enhance carcinogenicity through the generation of N-nitrosamines and estrogen-like DNA-reactive metabolites (11–13) (Figure 1). Epidemiologic studies further suggest that recurrent UTIs, pyuria, and chronic cystitis correlate with increased risk of BC recurrence and progression, reinforcing the clinical relevance of infection-mediated pathways.
Figure 1. Schistosoma infection is often accompanied by microbial infections, which can trigger chronic inflammation and the accumulation of harmful substances, collectively contributing to the development of bladder cancer.
An additional layer of complexity arises from aging-related immune decline, or immunosenescence. Bladder cancer predominantly affects older adults, with a median age at diagnosis of approximately 73 years (14). Aging is accompanied by diminished immune surveillance, reduced antigen presentation, and impaired cytotoxic T-cell responses, which collectively reduce the host’s ability to eliminate pathogens and emerging tumor cells (2, 15, 16). Immunosenescence also facilitates microbial persistence, establishing a vicious cycle in which chronic infection perpetuates inflammation, and inflammation accelerates immune deterioration (17–21). This interplay between microbial dysbiosis and immune aging represents a critical yet underexplored determinant of BC pathogenesis. Understanding this dynamic crosstalk may reveal why elderly individuals are more susceptible to both infection and cancer, and why immune-based therapies exhibit variable efficacy in this population.
The duality of microbes as both carcinogenic agents and therapeutic tools further highlights the complexity of host–microbe interactions in BC. The attenuated strain Mycobacterium bovis Bacillus Calmette–Guérin (BCG) remains the cornerstone of intravesical therapy for non–muscle-invasive bladder cancer (NMIBC), harnessing microbial activation of innate and adaptive immunity to suppress tumor recurrence (22). This paradox—where microbes can either promote or suppress tumorigenesis—underscores the necessity of disentangling the mechanistic nuances governing microbial behavior within the bladder milieu. Clarifying the context-dependent effects of microbial exposure is essential to advancing precision interventions that exploit beneficial microbial functions while mitigating pathogenic consequences (23).
In this context, the present review aims to synthesize current knowledge on the microbiome–infection axis in bladder cancer and to propose a unifying conceptual framework linking microbial dysbiosis, chronic inflammation, and immunosenescence to tumor initiation and progression. We first examine evidence from clinical and experimental studies delineating how infection-driven inflammatory signaling contributes to urothelial carcinogenesis. We then explore the composition and ecological dynamics of urinary and gut microbiota in BC, identifying microbial signatures associated with disease progression and therapeutic response. Subsequently, we integrate mechanistic insights into how microbes and immune aging remodel the tumor microenvironment (TME) through epithelial barrier disruption, immune reprogramming, and extracellular matrix modification. Finally, we discuss therapeutic implications, emphasizing microbiome-targeted and immunomodulatory strategies that hold promise for restoring microbial–immune homeostasis and improving clinical outcomes.
By bridging microbiology, immunology, and cancer biology, this review positions the microbiome not as a peripheral feature but as a central determinant of bladder cancer pathogenesis. Understanding the intricate relationship between infection, microbial ecology, and host immunity will be essential for developing next-generation diagnostic tools and personalized therapeutic strategies that move beyond the tumor-centric paradigm toward a holistic model of host–microbe–tumor interaction.
2 Infection-driven microbiome dysregulation in BC
Chronic and recurrent infections are among the most significant environmental pressures shaping the bladder’s microbial ecosystem and influencing tumor initiation. The urothelial surface, once thought to be sterile, is now recognized as a dynamic microbial niche whose composition is constantly modulated by host immunity, urinary flow, and exposure to pathogens. When these regulatory mechanisms fail—particularly under conditions of persistent infection or age-related immune decline—the resulting microbial imbalance, or dysbiosis, can initiate a cascade of inflammatory and mutagenic processes that contribute to bladder carcinogenesis.
2.1 Pathogenic infections and carcinogenic inflammation
Chronic infection by E. coli, the primary pathogen responsible for 70% of UTIs, has been implicated as a potential carcinogenic factor. Histopathological studies show that persistent E. coli infection alone induces epithelial dysplasia in the mucosal lining and promotes inflammatory cell infiltration into the lamina propria. When combined with nitrosamine precursors, chronic infection significantly increases the incidence of bladder lesions, surpassing the effects of nitrosamine precursors alone. This synergy highlights the critical role of infection-driven inflammation in bladder carcinogenesis (17). Kawai et al. further demonstrated that E. coli-derived lipopolysaccharide (LPS) significantly enhances N-methyl-N-nitrosourea (MNU)-induced bladder carcinogenesis, with inflammation and oxidative stress, driven by reactive oxygen species (ROS), playing key roles in this process (24). However, these findings, largely based on animal models, may not fully capture the complexities of human BC. Additionally, genetic and environmental variations limit the direct applicability of these results to clinical settings. Therefore, future research should focus on validating these mechanisms in human populations while accounting for these influencing factors.
2.2 UTIs and prognosis of BC
The connection between inflammation and bladder cancer (BC) progression is well-established. Sazuka et al. found that preoperative pyuria is closely associated with intravesical recurrence after transurethral resection of bladder tumor (TURBT), suggesting its role in predicting recurrence risk (19). Similarly, Jing et al. highlighted the importance of tumor-neutrophil interactions within the TME as a key driver of BC progression, emphasizing the critical role of inflammation in this process (25). Abd-El-Raouf et al. demonstrated that E. coli infection accelerates BC progression by inducing epithelial-mesenchymal transition (EMT), stem cell-like behaviors, and metabolic reprogramming (26). Nesi et al., in their systematic review, identified chronic inflammation as a central mechanism in BC pathophysiology (27), while Russell et al. further supported the inflammatory hypothesis by showing that epigenetic reprogramming induced by uropathogenic E. coli influences BC outcomes (28). Although the role of inflammation in BC progression is widely recognized, there remains some disagreement on its exact contribution. While some studies focus on the direct effects of inflammation on tumorigenesis, others suggest a more complex interplay involving microbial dysbiosis and immune suppression. Furthermore, most studies rely on mechanistic or single-center data, which may oversimplify the multifactorial nature of BC progression. To address these discrepancies, future research should adopt longitudinal studies with integrated approaches that assess inflammation, microbial composition, and tumor dynamics across diverse populations.
2.3 Prognostic biomarkers in infection-associated BC
Clinical studies have identified pyuria and recurrent UTIs as negative prognostic factors in BC patients. Vermeulen et al. reported that recurrent UTIs significantly increase the risk of developing BC (29). Azuma et al. identified pyuria as a poor prognostic indicator in patients with NMIBC and found it correlated with lower survival rates (21). Similarly, Singh et al. showed that preoperative pyuria and an elevated neutrophil-to-lymphocyte ratio (NLR) independently predict poor outcomes (18). Satake et al. also highlighted the prognostic value of preoperative pyuria in NMIBC patients (20). Although these studies emphasize the relevance of pyuria and recurrent UTIs as prognostic markers, inconsistencies remain in sample sizes and study designs. Many rely on single-center populations or small cohorts, which may introduce sampling bias and limit the generalizability of the results. To improve the accuracy of prognostic assessments, future studies should adopt multicenter designs with larger and more diverse populations to better define the value of these biomarkers across different clinical and demographic contexts.
3 Microbiome composition and its clinical correlates
The recognition that the bladder harbors a distinct microbial ecosystem has fundamentally transformed our understanding of urinary tract biology and its contribution to disease. Advances in metagenomic sequencing and culture-independent techniques have revealed that both the urinary and gut microbiota undergo profound compositional shifts during BC development. These alterations—manifesting as reduced microbial diversity, loss of beneficial commensals, and enrichment of opportunistic pathogens—reflect a disrupted ecological equilibrium, or dysbiosis, that can influence immune homeostasis, inflammatory signaling, and tumor behavior. Importantly, the specific microbial signatures observed in urine, tissue, and stool samples from BC patients provide valuable insights into the pathophysiology of the disease and its potential diagnostic and prognostic biomarkers (12, 30–35) (Table 1).
3.1 Urinary microbiota and BC
Studies on the urinary microbiome in BC patients have revealed significant alterations in microbial diversity and composition. However, findings across studies remain inconsistent. Popovic et al. and Wu et al. analyzed urine samples using 16S rRNA sequencing but reported differing results. Popovic et al. observed no significant differences in microbial diversity or abundance between BC patients and healthy controls, while Wu et al. reported higher alpha diversity in BC patients, noting differences at the genus level (36, 37). Wu et al. specifically identified higher Shannon and Simpson diversity indices in BC patients compared to controls, with Streptococcus and Escherichia-Shigella as dominant taxa (36, 37). Bi et al. found reduced abundances of Bifidobacterium and Lactobacillus in BC patients and identified Actinomyces europaeus as a potential biomarker for the disease (38). In contrast, Chipollini et al. reported reduced alpha diversity in BC patients, whereas Zeng et al. found alpha diversity significantly higher in BC patients, with a 145% increase in the Chao1 index and a 123% increase in the Ace index compared to controls (35, 39). Hussein et al. further supported the reduction of Lactobacillus abundance in urine of BC patients (40). These discrepancies may arise from variations in sequencing platforms, data analysis strategies, sample types (urine vs. tissue), and patient characteristics such as tumor stage and treatment history. Additionally, the urinary microbiome is highly influenced by external factors, including diet and antibiotic use, which may not be uniformly controlled across studies. To better elucidate the role of the urinary microbiome in BC, future research should incorporate larger cohorts and standardized methodologies for sample collection and data analysis.
3.2 Tissue-resident microbiota and BC
Changes in the microbiota within BC tissues are closely linked to the TME. Liu et al. performed 16S rRNA sequencing on 22 cancerous and 12 adjacent normal tissues, reporting significantly lower alpha diversity in cancer tissues, indicating reduced microbial diversity in BC (41). Mansour et al. compared microbiota in 10 catheter urine samples and 14 TURBT-resected tumor tissues, finding significantly higher abundances of Akkermansia, Bacteroides, Clostridium, Enterobacter, and Klebsiella in cancer tissues, while Staphylococcus and Lactobacillus were consistently present in both sample types (42). Further studies corroborated these findings. Parra-Grande et al. observed lower microbial richness in tumor tissues compared to paired non-tumor tissues, alongside higher Actinobacteria levels in non-tumor samples, supporting its potential protective role against BC (43). Similarly, Pederzoli et al. identified Klebsiella as more prevalent in the urine of female BC patients, while Burkholderia was enriched in cancer tissues (44). Yao et al., using RNA sequencing, highlighted the enrichment of Pseudomonas, Porphyrobacter, and Acinetobacter in cancer tissues, suggesting their potential involvement in BC progression (45). While multiple studies consistently report a reduction in microbial diversity within BC tissues compared to normal tissues. These variations may stem from differences in sample types (tumor tissue vs. urine), patient demographics (gender, age, lifestyle), and analytical approaches (16S rRNA sequencing vs. metagenomic sequencing). Additionally, the microbial composition may undergo dynamic changes at different stages of BC. Therefore, future longitudinal studies with standardized methodologies are essential to elucidate the evolving role of microbiota in BC development and progression.
3.3 Microbes associated with BC progression and recurrence
Alterations in the bladder microbiome are closely associated with BC progression and recurrence, with distinct microbial patterns influencing disease outcomes and therapeutic responses. Oresta et al. reported significant increases in Veillonella and Corynebacterium and a reduction in Ruminococcus in urine samples from BC patients, with these shifts correlating with disease advancement (46). Sun et al., using 2bRAD-M sequencing, found that NMIBC tissues exhibited higher microbial diversity than muscle-invasive bladder cancer (MIBC) tissues, with Ralstonia sp. dominating in MIBC, contrasting with Acinetobacter guillouiae and Anoxybacillus rupiensis in NMIBC (47). High-grade tumors were linked to reduced microbial diversity and richness. Bilski et al. reported lower Chao1 and Shannon indices in high-grade tumors compared to low-grade tumors, with notable sex-related differences in microbial composition at the phylum level (e.g., Firmicutes dominance in males, Proteobacteria in females) (48).
In recurrence, specific microbial patterns also emerged. Yao et al. identified higher levels of Mycolicibacterium and Streptomyces in patients with sustained responses to BCG therapy, while Knorr et al. found increased Lactobacillus levels in BCG responders, suggesting protective effects of these genera (45, 49). Conversely, Micrococcus and Brachybacterium were enriched in recurrent patients (39). Hussein et al. observed post-TURBT increases in Veillonella and Bifidobacterium in recurrent cases, while Escherichia-Shigella and Helococcus were more abundant in non-recurrent cases (50). Qiu et al. linked higher alpha diversity in recurrent patients with elevated abundances of Pseudomonas, Corynebacterium, and Acinetobacter, potentially facilitating immune evasion and tumor growth (51). Particular attention should be given to BCG-refractory tumors, where up to 30-50% of NMIBC patients fail to respond to BCG intravesical therapy, leading to higher recurrence and progression rates (52–54). Microbial signatures in these cases often show enrichment of certain taxa associated with poor response (e.g., reduced Lactobacillus or altered diversity), which may impair BCG-induced immune activation by promoting an immunosuppressive TME (40, 55, 56). Recent studies suggest that gut or urinary microbiota modulation (e.g., via probiotics or potential fecal microbiota transplantation in preclinical models) could influence BCG responsiveness by enhancing Th1 responses and modulating immune cell infiltration (57, 58). Mechanisms involve altered TLR signaling and cytokine profiles, highlighting the need for microbiome-based predictors of BCG failure to guide alternative therapies like radical cystectomy or ICIs (59).
3.4 Gut microbiota and BC
Emerging evidence indicates that the gut microbiota exerts distal effects on bladder carcinogenesis through systemic immune modulation and metabolic signaling—a concept known as the “gut–bladder axis.” A case-control study in Harbin indicated that BC patients exhibited a significant reduction in gut microbiota diversity, with a notable decrease in the abundance of Clostridium cluster XI and Prevotella. This reduction was closely associated with low fruit intake among BC patients, and a significant decrease in butyrate concentration in their feces was also observed (60). Butyrate, a crucial short-chain fatty acid, plays a vital role in anti-inflammatory processes and in protecting the intestinal barrier. Its reduction may increase intestinal permeability, leading to chronic inflammation induced by elevated levels of LPS and D-lactic acid, thereby accelerating the development of BC. Furthermore, evidence from Mendelian randomization studies indicates a significant causal relationship between specific gut microbiota, such as Bilophila, and BC. This may occur through the modulation of amino acid and NAD metabolism pathways, promoting the onset of BC (61). Other microbiota, such as Bifidobacterium and Actinobacteria, are also associated with an increased risk of BC, while Allisonella has been found to be linked with a reduced risk of both bladder and prostate cancers (62). These microbiota alterations may influence tumorigenesis by modulating host metabolic pathways, immune signaling, and inflammatory responses. In the field of cancer immunotherapy, further research has uncovered the role of gut microbiota in regulating the therapeutic efficacy of BC treatments. The abundance of Parabacteroides distasonis was significantly higher in healthy controls than in BC patients. This bacterium enhances the infiltration of CD4+ and CD8+ T cells within tumors and activates anti-tumor immune pathways, thereby significantly improving the efficacy of anti-PD-1 treatment (63). This finding suggests that specific gut microbiota could serve as a potential adjunct to immunotherapy.
4 Mechanistic interplay: microbes, immunosenescence, and TME
4.1 Microbial modulation of epithelial integrity and EMT activation
4.1.1 Microbial dysbiosis and EMT activation
Recent bioinformatics studies analyzing the microbial communities in BC have identified strong associations between specific microorganisms and the expression of EMT-related genes. Specifically, an analysis of tumor samples from over 400 patients with MIBC revealed significant correlations between various microorganisms, including E. coli, butyrate-producing bacterium SM4/1, and an Oscillatoria species, and the expression of classic EMT-related genes such as E-cadherin, vimentin, snail family transcriptional repressor 2 (SNAI2), snail family transcriptional repressor 3 (SNAI3), and twist family BHLH transcription factor 1 (TWIST1). Additionally, the study uncovered significant links between these microorganisms and the expression of extracellular matrix (ECM)-related genes, particularly those encoding collagen and elastin. These findings suggest that intratumoral microbiota may influence EMT and, consequently, clinical outcomes in BC (64). However, it is crucial to emphasize that these results are derived primarily from correlation-based bioinformatics analyses, and a direct causal relationship between microbial presence and EMT gene regulation remains to be established. While these associations provide compelling evidence for a potential microbial role in tumor progression, mechanistic insights into how these bacteria modulate EMT in BC are still lacking and require experimental validation.
Moreover, intratumoral bacteria are not randomly distributed but are highly organized within distinct ecological niches that are often characterized by immunosuppressive conditions and poor vascularization. By remodeling the TME and promoting cellular heterogeneity, bacteria may exert profound effects on tumor progression (65). Bacterial invasion can induce the upregulation of genes associated with inflammation, EMT, hypoxia response, and DNA repair, leading to the emergence of distinct cancer cell subpopulations with enhanced invasive potential. For example, in colorectal cancer (CRC), Fusobacterium nucleatum infection has been shown to drive the transition from collective migration to single-cell invasion, with significant activation of tumor progression signaling pathways (65). While these observations have been experimentally validated in CRC, direct evidence supporting a similar bacterial-driven EMT mechanism in BC is currently lacking. Thus, although bioinformatics analyses provide valuable insights into potential microbial contributions to EMT and tumor progression pathways, further in-depth mechanistic studies are necessary to confirm the direct role of specific bacteria in BC pathogenesis.
4.1.2 Bacterial ECM degradation and remodeling
In BC, bacteria residing within the tumor stroma may influence extracellular matrix (ECM) integrity through the secretion of proteolytic enzymes. Bacterial proteases such as collagenase, elastase, and alkaline protease are capable of degrading key ECM components including collagen and elastin, thereby weakening structural barriers and potentially facilitating bacterial persistence (66, 67). Among these enzymes, collagenases are particularly relevant due to their broad substrate specificity and their ability to disrupt intercellular junctions and tissue organization (68–70).
Additionally, several Gram-positive bacteria produce hyaluronidase, an enzyme that hydrolyzes hyaluronic acid (HA), a major ECM component involved in tissue cohesion and cell adhesion. The degradation of HA provides nutrients for bacterial metabolism and may enhance tissue permeability, conditions that could theoretically support local invasion (71).
Beyond structural effects, bacterial proteases have been implicated in modulating host immune signaling in other pathological contexts by degrading cytokines and growth factors (72, 73). However, direct evidence of such mechanisms in BC remains scarce. While these findings collectively suggest that bacterial proteolytic activity might contribute to ECM remodeling within the bladder microenvironment (Figure 2), further mechanistic studies are needed to confirm its direct role in tumor progression and immune modulation in BC.
Figure 2. In progressive bladder cancer, cancer cells and CAFs grow intertwined. CAFs create an immunosuppressive environment that facilitates the rapid proliferation of cancer cells. Along with inflammation induced by bacterial infections, they manipulate and exploit the immune response, synergistically driving rapid cancer progression.
4.1.3 Post-translational modulation by microbes
In addition to enzymatic ECM degradation, bacteria can also induce post-translational modifications (PTM) of host proteins, altering the biochemical and physical properties of the TME. For instance, Porphyromonas gingivalis, a known periodontal pathogen, produces peptidylarginine deiminase, an enzyme responsible for citrullination of collagen type I, which can disrupt the interactions between fibroblasts and collagen fibers (74, 75). These modifications may alter ECM stiffness and architecture, further promoting cancer cell invasion and metastasis. However, the functional significance of such bacterial-driven ECM modifications in BC and other solid tumors remains unclear. Although PTM-induced ECM alterations have been observed in multiple cancer types, their specific contribution to BC progression is yet to be fully elucidated and requires further experimental investigation.
4.2 Immunosenescence: the aging immune system and infection susceptibility
Immunosenescence—the progressive decline of immune function associated with aging—represents a critical but underappreciated determinant of host susceptibility to infection-driven carcinogenesis. In the context of bladder cancer (BC), recurrent microbial exposure and chronic urinary tract infections act as persistent antigenic stimuli that accelerate immune exhaustion and cellular senescence. This infection-induced immune aging not only impairs pathogen clearance but also fosters a permissive microenvironment that supports tumor initiation and progression (76, 77). Therefore, immunosenescence should not be viewed solely as an age-related phenomenon but as an integral component of the infection–microbiota–tumor axis.
4.2.1 Immune aging in the TME
Such senescent immune phenotypes are further aggravated by recurrent infections, particularly in the bladder where chronic bacterial exposure induces continuous antigenic stimulation. This suggests that infection not only coexists with immune aging but actively accelerates it, shaping a tumor-permissive environment. Senescence affects both innate and adaptive immune cells, compromising their surveillance, cytotoxicity, and signaling capacity. CD8+ T cells exhibit classic immunosenescent phenotypes: loss of CD28, upregulation of KLRG1 and CD57, and metabolic dysregulation involving oxidative phosphorylation, ROS accumulation, and mitochondrial remodeling (78–86). Unlike exhausted T cells, senescent T cells are metabolically active but irreversibly dysfunctional, limiting the efficacy of checkpoint blockade therapies (87, 88). Thymic involution further restricts naïve T cell output, exacerbating immune decline. Clinical and preclinical studies have shown that the TME directly induces immunosenescence in tumor-infiltrating lymphocytes. For instance, CD8+ T cells in breast cancer brain metastases lose migratory and cytotoxic function despite originating from healthy lymphoid niches (78, 89).
NK cells and myeloid compartments are similarly affected. NK cells in the elderly show altered subset distributions (e.g., CD56dim accumulation), reduced activating receptor expression, and metabolic rewiring induced by tumor-secreted cAMP (90–92). Aging macrophages often display reduced antigen presentation and altered Toll-like receptor (TLR) signaling; however, their polarization state appears context-dependent. Many studies report a shift toward M2-like, pro-tumor phenotypes that reinforce immunosuppression and angiogenesis (93–101). However, others have documented sustained or even heightened pro-inflammatory M1-like activity associated with systemic “inflammaging” (102, 103). This bidirectional plasticity underscores the complexity of macrophage aging within the TME. Regarding BCG therapy in BC, which promotes macrophage repolarization from M2 (immunosuppressive) to M1 (pro-inflammatory) phenotypes to enhance anti-tumor immunity (104, 105), comparative analyses with other cancers reveal limitations. In colorectal and lung cancers, M1 macrophages can paradoxically promote tumor progression by secreting pro-angiogenic factors or fostering chronic inflammation, leading to mixed M1/M2 states that support metastasis (106). Unlike BC, where BCG-induced M1 shifts are often beneficial in NMIBC, these approaches have been less successful in solid tumors like melanoma, where M1 activation may exacerbate TME heterogeneity and resistance (107, 108). This highlights the tumor-specific context of macrophage reprogramming and the need for targeted strategies to avoid unintended pro-tumor effects. Senescent neutrophils contribute to tumor progression through the senescence-associated secretory phenotype (SASP), promoting myeloid-derived suppressor cells (MDSCs) recruitment and ECM remodeling. Markers such as TREM2 and CXCR4+CD62L^low phenotypes are associated with metastasis and therapeutic resistance (109–115). In addition, senescent dendritic cells, often modulated by tumor-derived γδ regulatory T cells (Tregs), suppress effector T cell differentiation via PD-L1 and STAT3 signaling (116).
4.2.2 Impact on tumor surveillance and chronic inflammation
Infection acts as both a trigger and an amplifier of immunosenescence. Recurrent bacterial colonization, especially by uropathogens, perpetuates inflammatory signaling that exhausts immune competence. Immunosenescence also impacts systemic immune equilibrium, particularly mucosal immunity and microbial recognition. B cell senescence manifests as reduced bone marrow output, metabolic inflammation, and impaired antibody production (117–121). This state not only affects pathogen clearance but also contributes to T cell dysfunction via pro-inflammatory cytokines and clonal restriction of the T cell receptor repertoire (119). These immune alterations collectively diminish host capacity to eliminate pathogens, creating a permissive environment for microbial colonization and chronic infection. In the bladder, age-related immune decline may promote the persistence of uropathogens and delay resolution of UTIs, especially in elderly patients. This in turn can lead to prolonged inflammation, epithelial damage, and microbial-driven carcinogenesis. From a translational perspective, immunosenescence represents a potential therapeutic target. Rejuvenation strategies, such as senolytic therapies, metabolic reprogramming, and targeted epigenetic modulation, may help restore immune competence in elderly patients and improve response to both immunotherapy and microbiome-modulating interventions. Thus, age-related immune decline and infection-induced inflammation converge to form a pathogenic feedback loop that sustains microbial persistence and tumor-promoting chronic inflammation in the bladder.
4.3 Immune reprogramming in response to microbial infections
4.3.1 Uropathogenic E. coli and host immune modulation
The innate immune system promptly detects uropathogenic Escherichia coli (UPEC) through pattern recognition receptors (PRRs), particularly Toll-like receptor 4 (TLR4), which recognizes bacterial LPS. Activation of TLR4 initiates the NF-κB signaling pathway and stimulates the release of pro-inflammatory cytokines such as IL-6, IL-8, and TNF-α, which recruit neutrophils and macrophages (122–125). These immune cells utilize phagocytosis, ROS, and neutrophil extracellular traps (NETs) to eliminate bacterial invaders (126–129). Macrophages further contribute to immune activation through secretion of chemokines such as CXCL1 and CCL2, while dendritic cells (DCs) function as antigen-presenting cells that activate adaptive immune responses by priming T cells (130–134). Interestingly, bacterial products may also exert anti-tumor effects. For instance, E. coli supernatants downregulate c-MYC and pro-inflammatory cytokines like IL-1β and CCL2, while upregulating NQO1 expression. These changes promote apoptosis via BAX activation and suppression of anti-apoptotic BCL2 in bladder cancer cells (135–138). However, while bacterial-induced apoptosis may initially appear beneficial, it can also modulate the TME in ways that support immune evasion or chronic inflammation. UPEC adheres to bladder epithelial cells via type 1 pili and FimH adhesin, initiating actin reorganization and PI3-kinase signaling to promote bacterial internalization (139–143) (Figure 3). The formation of intracellular bacterial communities (IBCs) enables UPEC to evade host immunity, persist intracellularly, and drive chronic inflammation—factors that may contribute to bladder cancer progression.
Figure 3. Bladder infections caused by E. coli activate the innate immune response. Immune cells are recruited to the infection site to capture and clear E. coli. Neutrophils and macrophages eliminate E. coli through phagocytosis, while mast cells facilitate the shedding and death of epithelial cells infected by E. coli. E. coli can evade the acute inflammatory response by invading and colonizing host cells.
4.3.2 Infection-induced epithelial exfoliation and barrier disruption
Bladder epithelial cell exfoliation is a key host defense strategy against UTI. Upon E. coli infection, bladder epithelial cells secrete IL-1β, which recruits mast cells (MCs) to the infection site. These MCs release granules rich in chymase and tryptase, triggering apoptosis and exfoliation of infected cells (144–147). This response reduces bacterial burden and promotes epithelial renewal. Notably, mast cells undergo functional switching from a pro-inflammatory to an anti-inflammatory state approximately six hours post-infection, facilitating immune resolution and tissue repair (146, 148). UPEC-derived virulence factors, such as hemolysin, may further contribute to epithelial disruption (140, 149). While exfoliation is essential for bacterial clearance, it may also expose basal epithelial cells to inflammation-induced stress, potentially initiating or exacerbating malignant transformation.
4.4 Tumor susceptibility to bacterial invasion
4.4.1 Morphological and barrier defects
BC cells exhibit significant morphological alterations compared to normal urothelial cells, which enhance their susceptibility to bacterial infection. Normal urothelial cells form a well-organized epithelial barrier with tight and adherens junctions, preventing bacterial adherence and protecting against infection (150–152). These cells are typically flat, multilayered, and exhibit apical-basal polarity, with smooth membranes and limited adhesion sites. Tight junction proteins, such as Occludin, Claudins, and E-cadherin, play a crucial role in maintaining this barrier function (153–155).
In contrast, bladder cancer cells display surface microvilli proliferation, pseudopod formation, and altered glycosylation patterns, including the abnormal expression of Tn and sialyl-Tn antigens, which provide additional bacterial adhesion sites (156, 157). Loss of cellular polarity and weakened intercellular junctions result in larger gaps between cells, exposing extracellular matrix components like fibronectin and laminin, which serve as binding sites for bacterial adhesion (158). Moreover, bladder cancer cells often resist infection-induced apoptosis, partly due to increased BCL2 expression, which allows them to persist in inflammatory environments triggered by infection, further promoting tumor proliferation and invasion (Figure 4).
Figure 4. In superficial bladder cancer, acute inflammatory responses triggered by bacterial infections can significantly promote cancer progression. While acute inflammation can inhibit and kill cancer cells, cancer cells differ from normal urothelial cells by upregulating anti-apoptotic genes such as BCL2, thereby suppressing apoptosis. Infected cancer cells are less prone to detachment or death, exhibit morphological changes, and have disrupted intercellular connections, leading to widespread invasion and intracellular bacterial colonization. The deep invasion of acute inflammation can cause substantial damage to the stroma. Cancer cells are more prone to invasion and growth, and can drive the malignant transformation of fibroblasts through inflammation.
Clinically, these morphological changes contribute to the increased risk of UTIs in BC patients, with bacterial adhesion exacerbating disease progression. Targeting bacterial adhesion, for instance by inhibiting lectin-glycan interactions, may reduce colonization. These altered morphological features could also serve as biomarkers for assessing infection risk in BC.
4.4.2 Immunosuppressive tumor states
The immunosuppressive microenvironment in bladder cancer facilitates bacterial colonization by dampening the host’s immune response. In healthy urothelial tissue, antimicrobial peptides like β-defensins, along with cytokines such as IL-6 and IL-8, are secreted to recruit immune cells and combat pathogens (159–162). However, BC cells often secrete immunosuppressive cytokines, including TGF-β and IL-10, which impair immune cell activity and local immune responses (163–166). Treg infiltration further diminishes effector T cell function, hindering the clearance of pathogens and tumor cells (167).
BC cells also frequently downregulate MHC class I expression, reducing antigen presentation and immune recognition of both bacterial pathogens and tumor cells (168, 169). This creates an immunosuppressive TME that favors bacterial persistence. Studies have shown that bacterial presence in BC tissues correlates with increased infiltration of CD66b+ neutrophils and higher levels of immunosuppressive molecules like ARG1 and CTLA4. Additionally, activation of mitogen-activated protein kinase (MAPK) signaling in this context supports chronic bacterial colonization and inflammation, potentially accelerating tumor progression (65).
Clinically, targeting immunosuppressive pathways—such as blocking ARG1 or CTLA4—could enhance the immune system’s ability to clear both bacterial infections and cancer cells. Moreover, microbiome-based interventions, such as probiotics or engineered bacteria, may help modulate the TME and reduce bacterial infections, offering a potential complement to conventional cancer therapies.
4.5 Gut microbiota and immunosenescence
Immunosenescence, the gradual decline in immune system function during aging, is closely associated with chronic inflammation (inflammaging) and the onset of age-related diseases, such as cancer and infections. The gut microbiota plays a central role in this process. With aging, the composition and functionality of the gut microbiota undergo significant changes, manifested as a reduction in diversity, a decrease in beneficial bacteria (e.g., Faecalibacterium prausnitzii and Akkermansia muciniphila), and an increase in pro-inflammatory bacteria (e.g., Enterobacteriaceae and Proteobacteria) (170). These changes are closely related to T-cell aging, especially in middle-aged and older individuals. Individuals with lower gut microbiota richness show significantly higher mRNA biomarkers of T-cell senescence, and Shannon diversity is negatively correlated with the epigenetic age of T-cell DNA methylation (171). Additionally, metagenomic analysis of centenarians (≥90 years) revealed that age-related changes in the gut microbiota, chronic inflammation, and microbial metabolic reprogramming are key drivers of immunosenescence (172). These alterations in the gut microbiota accelerate the process of immune aging through various mechanisms. This process is accompanied by functional decline in specific immune cells, such as long-term stimulation by symbiotic bacteria that leads to the proliferation arrest and aging of germinal center (GC) B cells in Peyer’s patches (PPs), resulting in the loss of PP function. This damage, through bacterial-dependent compensatory mechanisms, promotes further aging of B cells in lymphoid follicles (ILFs), ultimately leading to a significant reduction in IgA production and diversity. This weakens the regulation of the gut microbiota, creating a vicious cycle between gut microbiota and immunosenescence (173).
Interventions targeting the gut microbiota are considered an important strategy to delay immunosenescence. For example, probiotics, such as Lactobacillus plantarum, can restore aging-related dendritic cell function and improve gut immune regulation in elderly individuals (174). Lifestyle interventions, such as caloric restriction, can reshape the gut microbiota and promote the functional recovery of T cells and B cells, thereby mitigating immunosenescence (175). Furthermore, fecal microbiota transplantation and combined interventions with prebiotics and probiotics have been shown to improve the composition of the gut microbiota in elderly patients, enhancing their response to immune checkpoint blockade (ICB) therapy, which provides anti-tumor benefits (176). Studies have also demonstrated that ICB therapy is associated with the enrichment of specific microbiota, particularly in elderly patients. The modulation of age-related gut microbiota is considered a key factor in improving ICB efficacy (177).
5 Therapeutic implications and future perspectives
The future of BC treatment lies in innovative, integrated strategies that combine microbiome modulation and immune therapies. These approaches focus on overcoming challenges such as microbial dysbiosis and immunosenescence, leveraging cutting-edge technologies like artificial intelligence (AI) and CRISPR for precision medicine. The integration of gut–bladder axis interventions with microbiome–immune therapies provide new avenues to improve clinical outcomes for BC patients. This chapter explores three major therapeutic strategies that hold great promise in advancing BC treatment.
5.1 Personalized microbiota modulation
Microbiome alterations in BC present a unique opportunity for personalized treatment strategies. Dynamic changes in microbial communities, such as shifts in urinary or stool microbiota, offer potential biomarkers for tumor progression and therapeutic response. Non-invasive microbiome analyses can enable real-time monitoring, guiding therapeutic interventions. For instance, machine learning algorithms can identify specific taxa like Lactobacillus or Veillonella, which are associated with either tumor progression or favorable responses to immunotherapy. Additionally, CRISPR-based microbial engineering could be harnessed to generate beneficial metabolites like short-chain fatty acids (SCFAs) or indole derivatives, potentially enhancing immune responses and improving the TME. Personalized microbiome modulation could significantly optimize treatment efficacy and patient outcomes (178).
5.2 Microbiome–immunotherapy combinations
The combination of microbiome modulation with immunotherapies represents a highly promising therapeutic strategy. Recent studies have shown that prebiotics, synbiotics, and microbiota-derived metabolites, such as butyrate, can work synergistically with immune checkpoint inhibitors (ICIs). These compounds enhance tumor-infiltrating lymphocyte (TIL) activity and modulate immunosuppressive cells like MDSCs and Tregs. Additionally, engineered microbial therapeutics that secrete immune-activating molecules (e.g., IL-15, GM-CSF) or anti-inflammatory agents (e.g., IL-10) could help reverse immunosenescence, particularly in aging populations. Preclinical studies have shown that Lactobacillus reuteri can translocate into tumors and release the tryptophan metabolite indole-3-aldehyde (I3A), which activates the aryl hydrocarbon receptor in CD8+ T cells and enhances anti-PD-L1 immune checkpoint blockade efficacy in melanoma models (179). Additionally, engineered bacterial platforms releasing PD-L1 nanobodies have demonstrated tumor-localized immune activation and reduced systemic toxicity in breast cancer models, highlighting the potential of microbiome-based strategies to modulate the TME and improve immunotherapy outcomes (180). While these findings suggest a promising direction for microbiome engineering in cancer therapy, comparable work specific to bladder cancer models has not yet been reported. This combination approach has the potential to enhance immune responses during various stages of treatment, from reducing preoperative infection risks to boosting immune memory during ICI therapy. Future research will focus on optimizing microbiome–immunotherapy interactions and tailoring these approaches to individual patient needs.
5.3 Gut–bladder axis therapeutic targeting
The interaction between the gut and bladder microbiota plays a crucial yet underexplored role in BC progression. Gut-derived metabolites, such as SCFAs and indoles, influence bladder immunity through systemic circulation and can modulate the bladder’s immune microenvironment. Targeting this “gut-bladder axis” with therapeutic interventions could offer a novel approach to improving the TME. For example, dietary modifications, such as high-fiber diets, or probiotic formulations that promote butyrate production, could boost systemic T-cell regeneration and enhance TIL activity within the bladder. These strategies could potentially reduce chronic inflammation, improve antigen presentation, and modulate the immune responses in the bladder, ultimately contributing to better treatment outcomes (178).
5.4 Multi-modal microbiome therapies
Future BC treatments will likely involve multi-modal strategies that combine microbiome-based therapies with conventional cancer treatments. Personalized microbiome modulation can complement traditional therapies like chemotherapy and radiotherapy, as well as advanced treatments such as ICIs. Customized microbial formulations may also enhance post-surgical recovery, improve patients’ immune response, and reduce recurrence rates in high-risk individuals. Furthermore, microbiome interventions could be incorporated into tumor vaccines to boost long-term anti-tumor immunity. As microbiome data accumulation accelerates, AI will play a critical role in optimizing these multi-modal strategies by identifying microbial targets, predicting patient-specific responses, and enabling truly personalized therapies. Examples of enhanced BCG-based approaches in bladder cancer include the use of PD-1/PD-L1 inhibitors such as pembrolizumab, which as monotherapy has demonstrated complete response rates of ~40% in BCG-unresponsive NMIBC cohorts (181). Recombinant BCG strains engineered to express IL-15 fused with antigen 85B have shown enhanced immunogenicity and prolonged survival in preclinical mouse bladder cancer models, associated with increased neutrophil and chemokine responses (182). Additionally, BCG combined with chemotherapy agents such as gemcitabine is being evaluated in clinical settings, with some early studies reporting promising response rates, though results remain preliminary and variable (183).
6 Conclusion
The relationship between the microbiome and BC is increasingly recognized as a critical factor in tumor initiation, progression, and recurrence. Both urinary and gut microbiota have significant roles in shaping the TME, with microbial infections serving as key drivers of cancer development. Disruptions in microbial communities—microbial dysbiosis—are strongly associated with chronic inflammation, immune modulation, and alterations in urothelial integrity, all of which contribute to tumor progression and metastasis. Bacterial infections, particularly those involving uropathogenic species, exacerbate these processes, facilitating the initiation and invasiveness of BC.
Infection-induced mechanisms, including microbial dysbiosis, drive important changes in the immune landscape of the TME. These changes are often exacerbated by immunosenescence, which weakens immune surveillance and increases susceptibility to persistent infections. Immunosenescence, while not the primary driver of BC, enhances the persistence of microbial dysbiosis by impairing the body’s ability to mount effective immune responses against both pathogens and tumor cells. This immune decline creates a favorable environment for tumorigenesis, as chronic inflammation and microbial imbalance promote immune evasion and tumor progression.
Future research should focus on elucidating how the gut and urinary microbiota interact to influence BC, particularly through their impact on immune responses and TME remodeling. Understanding the mechanisms by which microbial dysbiosis influences the development of BC will be essential for the development of novel diagnostic and therapeutic approaches. Microbiome-based therapies, particularly those targeting microbial imbalances and combined with immune modulation, offer promising avenues for personalized BC treatment. A more comprehensive understanding of these interactions will not only advance our knowledge of BC pathogenesis but also provide new strategies for improving early detection, prognosis, and treatment outcomes.
Author contributions
SP: Funding acquisition, Investigation, Project administration, Supervision, Visualization, Writing – original draft, Writing – review & editing. WC: Project administration, Supervision, Validation, Visualization, Writing – review & editing. ZW: Conceptualization, Formal Analysis, Project administration, Supervision, Validation, Writing – original draft. BL: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. JL: Data curation, Validation, Writing – original draft. ZL: Supervision, Validation, Writing – review & editing.
Funding
The author(s) declared that financial support was received for work and/or its publication This work was supported by grants from Japan China Sasakawa Medical Fellowship, Shengjing Hospital 345 Talent Project (Grant No. M1357 and M1358) and Liaoning Provincial Science and Technology Joint Applied Basic Research Project (Grant No. 2022JH2/101300073, 2023JH2/101700141 and 2025110367-JH2/1018).
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Glossary
APCs: antigen-presenting cells
ARG1: arginase 1
BAX: Bcl-2-associated X protein
BCL2: B-cell lymphoma 2
BCG: Bacillus Calmette-Guérin
BECs: bladder epithelial cells
CAFs: cancer-associated fibroblasts
CCL2: C-C motif chemokine ligand 2
CTLA4: cytotoxic T-lymphocyte–associated protein 4
CTLs: cytotoxic T lymphocytes
CX3CL1: C-X3-C motif chemokine ligand 1
CXCL12: C-X-C motif chemokine ligand 12
DCs: dendritic cells
DCA: deoxycholic acid
ECM: extracellular matrix
E. coli: Escherichia coli
EMT: epithelial–mesenchymal transition
FM: first-morning
FXR: farnesoid X receptor
IBCs: intracellular bacterial communities
IFN-γ: interferon-gamma
IL: interleukin
ILCs: innate lymphoid cells
LCA: lithocholic acid
LPS: lipopolysaccharide
MAPK: mitogen-activated protein kinase
MCP-1: monocyte chemoattractant protein-1
MCs: mast cells
MDSCs: myeloid-derived suppressor cells
MHC: major histocompatibility complex
MIBC: muscle-invasive bladder cancer
MMPs: matrix metalloproteinases
MNU: N-methyl-N-nitrosourea
NETs: neutrophil extracellular traps
NF-κB: nuclear factor kappa B
NLR: neutrophil-to-lymphocyte ratio
NMIBC: non-muscle-invasive bladder cancer
NK: natural killer
NO: nitric oxide
NQO1: NAD(P)H quinone dehydrogenase 1
PAMPs: pathogen-associated molecular patterns
PCR: polymerase chain reaction
PD-1: programmed cell death protein 1
PD-L1: programmed death-ligand 1
PI3-kinase: phosphoinositide 3-kinase
PRRs: pattern recognition receptors
ROS: reactive oxygen species
SCFAs: short-chain fatty acids
SNAI2: snail family transcriptional repressor 2
SNAI3: snail family transcriptional repressor 3
TANs: tumor-associated neutrophils
TAAs: tumor-associated antigens
TCA: tricarboxylic acid
TGF-β: transforming growth factor-beta
Th1: T helper type 1
Th2: T helper type 2
TLRs: toll-like receptors
Tregs: regulatory T cells
TURBT: transurethral resection of bladder tumor
Teff: effector CD8+ T cells
Tex: exhausted CD8+ T cells
TGR5: G-protein-coupled bile acid receptor 5
TNF-α: tumor necrosis factor-alpha
TWIST1: twist family BHLH transcription factor 1
UPEC: uropathogenic Escherichia coli
UTIs: urinary tract infections
UTP: uridine triphosphate
VEGF: vascular endothelial growth factor
References
1. Compérat E, Amin MB, Cathomas R, Choudhury A, De Santis M, Kamat A, et al. Current best practice for bladder cancer: a narrative review of diagnostics and treatments. Lancet. (2022) 400:1712–21. doi: 10.1016/s0140-6736(22)01188-6
2. Antoni S, Ferlay J, Soerjomataram I, Znaor A, Jemal A, and Bray F. Bladder cancer incidence and mortality: A global overview and recent trends. Eur Urol. (2017) 71:96–108. doi: 10.1016/j.eururo.2016.06.010
3. Siegel RL, Miller KD, Wagle NS, and Jemal A. Cancer statistics, 2023. CA Cancer J Clin. (2023) 73:17–48. doi: 10.3322/caac.21763
4. Burger M, Catto JW, Dalbagni G, Grossman HB, Herr H, Karakiewicz P, et al. Epidemiology and risk factors of urothelial bladder cancer. Eur Urol. (2013) 63:234–41. doi: 10.1016/j.eururo.2012.07.033
5. Mantica G, Terrone C, and Der Merwe AV. Bladder cancer and associated risk factors: the african panorama. Eur Urol. (2021) 79:568–70. doi: 10.1016/j.eururo.2020.11.041
6. Honeycutt J, Hammam O, Fu CL, and Hsieh MH. Controversies and challenges in research on urogenital schistosomiasis-associated bladder cancer. Trends Parasitol. (2014) 30:324–32. doi: 10.1016/j.pt.2014.05.004
7. Barsoum RS. Urinary schistosomiasis: review. J Adv Res. (2013) 4:453–9. doi: 10.1016/j.jare.2012.08.004
8. El-Rifai W, Kamel D, Larramendy ML, Shoman S, Gad Y, Baithun S, et al. DNA copy number changes in Schistosoma-associated and non-Schistosoma-associated bladder cancer. Am J Pathol. (2000) 156:871–8. doi: 10.1016/s0002-9440(10)64956-5
9. Pezone A, Olivieri F, Napoli MV, Procopio A, Avvedimento EV, and Gabrielli A. Inflammation and DNA damage: cause, effect or both. Nat Rev Rheumatol. (2023) 19:200–11. doi: 10.1038/s41584-022-00905-1
10. O’Byrne KJ, Dalgleish AG, Browning MJ, Steward WP, and Harris AL. The relationship between angiogenesis and the immune response in carcinogenesis and the progression of Malignant disease. Eur J Cancer. (2000) 36:151–69. doi: 10.1016/s0959-8049(99)00241-5
11. Adebayo AS, Suryavanshi MV, Bhute S, Agunloye AM, Isokpehi RD, Anumudu CI, et al. The microbiome in urogenital schistosomiasis and induced bladder pathologies. PloS Negl Trop Dis. (2017) 11:e0005826. doi: 10.1371/journal.pntd.0005826
12. Markowski MC, Boorjian SA, Burton JP, Hahn NM, Ingersoll MA, Maleki Vareki S, et al. The microbiome and genitourinary cancer: A collaborative review. Eur Urol. (2019) 75:637–46. doi: 10.1016/j.eururo.2018.12.043
13. Gouveia MJ, Santos J, Brindley PJ, Rinaldi G, Lopes C, Santos LL, et al. Estrogen-like metabolites and DNA-adducts in urogenital schistosomiasis-associated bladder cancer. Cancer Lett. (2015) 359:226–32. doi: 10.1016/j.canlet.2015.01.018
14. Siegel RL, Miller KD, and Jemal A. Cancer statistics, 2020. CA Cancer J Clin. (2020) 70:7–30. doi: 10.3322/caac.21590
15. Zeng G, Zhu W, Lam W, and Bayramgil A. Treatment of urinary tract infections in the old and fragile. World J Urol. (2020) 38:2709–20. doi: 10.1007/s00345-020-03159-2
16. Schaeffer AJ. Urinary tract infections in the elderly. Eur Urol. (1991) 19 Suppl:12–6. doi: 10.1159/000473669
17. El-Mosalamy H, Salman TM, Ashmawey AM, and Osama N. Role of chronic E. coli infection in the process of bladder cancer- an experimental study. Infect Agent Cancer. (2012) 7:19. doi: 10.1186/1750-9378-7-19
18. Singh R, Sharma G, Priyadarshi S, and Fauzdar G. Prognostic significance of preoperative pyuria & neutrophil to lymphocyte ratio in patients with non-muscle-invasive bladder cancer: A prospective cohort study. Urologia. (2024) 91:69–75. doi: 10.1177/03915603231203780
19. Sazuka T, Sakamoto S, Imamura Y, Nakamura K, Yamamoto S, Arai T, et al. Relationship between post-void residual urine volume, preoperative pyuria and intravesical recurrence after transurethral resection of bladder carcinoma. Int J Urol. (2020) 27:1024–30. doi: 10.1111/iju.14352
20. Satake N, Ohno Y, Nakashima J, Ohori M, and Tachibana M. Prognostic value of preoperative pyuria in patients with non-muscle-invasive bladder cancer. Int J Urol. (2015) 22:645–9. doi: 10.1111/iju.12788
21. Azuma T, Nagase Y, and Oshi M. Pyuria predicts poor prognosis in patients with non-muscle-invasive bladder cancer. Clin Genitourin Cancer. (2013) 11:331–6. doi: 10.1016/j.clgc.2013.04.002
22. Redelman-Sidi G, Glickman MS, and Bochner BH. The mechanism of action of BCG therapy for bladder cancer--a current perspective. Nat Rev Urol. (2014) 11:153–62. doi: 10.1038/nrurol.2014.15
23. Isali I, Helstrom EK, Uzzo N, Lakshmanan A, Nandwana D, Valentine H, et al. Current trends and challenges of microbiome research in bladder cancer. Curr Oncol Rep. (2024) 26:292–8. doi: 10.1007/s11912-024-01508-7
24. Kawai K, Yamamoto M, Kameyama S, Kawamata H, Rademaker A, and Oyasu R. Enhancement of rat urinary bladder tumorigenesis by lipopolysaccharide-induced inflammation. Cancer Res. (1993) 53:5172–5.
25. Jing W, Wang G, Cui Z, Li X, Zeng S, Jiang X, et al. Tumor-neutrophil cross talk orchestrates the tumor microenvironment to determine the bladder cancer progression. Proc Natl Acad Sci U.S.A. (2024) 121:e2312855121. doi: 10.1073/pnas.2312855121
26. Abd-El-Raouf R, Ouf SA, Gabr MM, Zakaria MM, El-Yasergy KF, and Ali-El-Dein B. Escherichia coli foster bladder cancer cell line progression via epithelial mesenchymal transition, stemness and metabolic reprogramming. Sci Rep. (2020) 10:18024. doi: 10.1038/s41598-020-74390-5
27. Nesi G, Nobili S, Cai T, Caini S, and Santi R. Chronic inflammation in urothelial bladder cancer. Virchows Arch. (2015) 467:623–33. doi: 10.1007/s00428-015-1820-x
28. Russell SK, Harrison JK, Olson BS, Lee HJ, O’Brien VP, Xing X, et al. Uropathogenic Escherichia coli infection-induced epithelial trained immunity impacts urinary tract disease outcome. Nat Microbiol. (2023) 8:875–88. doi: 10.1038/s41564-023-01346-6
29. Vermeulen SH, Hanum N, Grotenhuis AJ, Castaño-Vinyals G, van der Heijden AG, Aben KK, et al. Recurrent urinary tract infection and risk of bladder cancer in the Nijmegen bladder cancer study. Br J Cancer. (2015) 112:594–600. doi: 10.1038/bjc.2014.601
30. Heidar NA, Bhat TA, Shabir U, and Hussein AA. The urinary microbiome and bladder cancer. Life (Basel). (2023) 13:812. doi: 10.3390/life13030812
31. Russo AE, Memon A, and Ahmed S. Bladder cancer and the urinary microbiome-new insights and future directions: A review. Clin Genitourin Cancer. (2024) 22:434–44. doi: 10.1016/j.clgc.2023.12.015
32. Friedrich V and Choi HW. The urinary microbiome: role in bladder cancer and treatment. Diagnost (Basel). (2022) 12:2068. doi: 10.3390/diagnostics12092068
33. Whiteside SA, Razvi H, Dave S, Reid G, and Burton JP. The microbiome of the urinary tract--a role beyond infection. Nat Rev Urol. (2015) 12:81–90. doi: 10.1038/nrurol.2014.361
34. Hourigan SK, Zhu W, SWW W, Clemency NC, Provenzano M, Vilboux T, et al. Studying the urine microbiome in superficial bladder cancer: samples obtained by midstream voiding versus cystoscopy. BMC Urol. (2020) 20:5. doi: 10.1186/s12894-020-0576-z
35. Chipollini J, Wright JR, Nwanosike H, Kepler CY, Batai K, Lee BR, et al. Characterization of urinary microbiome in patients with bladder cancer: Results from a single-institution, feasibility study. Urol Oncol. (2020) 38:615–21. doi: 10.1016/j.urolonc.2020.04.014
36. Bučević Popović V, Šitum M, Chow CT, Chan LS, Roje B, and Terzić J. The urinary microbiome associated with bladder cancer. Sci Rep. (2018) 8:12157. doi: 10.1038/s41598-018-29054-w
37. Wu P, Zhang G, Zhao J, Chen J, Chen Y, Huang W, et al. Profiling the urinary microbiota in male patients with bladder cancer in China. Front Cell Infect Microbiol. (2018) 8167:167. doi: 10.3389/fcimb.2018.00167
38. Bi H, Tian Y, Song C, Li J, Liu T, Chen Z, et al. Urinary microbiota - a potential biomarker and therapeutic target for bladder cancer. J Med Microbiol. (2019) 68:1471–8. doi: 10.1099/jmm.0.001058
39. Zeng J, Zhang G, Chen C, Li K, Wen Y, Zhao J, et al. Alterations in urobiome in patients with bladder cancer and implications for clinical outcome: A single-institution study. Front Cell Infect Microbiol. (2020) 10555508:555508. doi: 10.3389/fcimb.2020.555508
40. Hussein AA, Elsayed AS, Durrani M, Jing Z, Iqbal U, Gomez EC, et al. Investigating the association between the urinary microbiome and bladder cancer: An exploratory study. Urol Oncol. (2021) 39:370. doi: 10.1016/j.urolonc.2020.12.011
41. Liu F, Liu A, Lu X, Zhang Z, Xue Y, Xu J, et al. Dysbiosis signatures of the microbial profile in tissue from bladder cancer. Cancer Med. (2019) 8:6904–14. doi: 10.1002/cam4.2419
42. Mansour B, Monyók Á, Makra N, Gajdács M, Vadnay I, Ligeti B, et al. Bladder cancer-related microbiota: examining differences in urine and tissue samples. Sci Rep. (2020) 10:11042. doi: 10.1038/s41598-020-67443-2
43. Parra-Grande M, Oré-Arce M, Martínez-Priego L, D’Auria G, Rosselló-Mora R, Lillo M, et al. Profiling the bladder microbiota in patients with bladder cancer. Front Microbiol. (2021) 12718776:718776. doi: 10.3389/fmicb.2021.718776
44. Pederzoli F, Ferrarese R, Amato V, Locatelli I, Alchera E, Lucianò R, et al. Sex-specific alterations in the urinary and tissue microbiome in therapy-naïve urothelial bladder cancer patients. Eur Urol Oncol. (2020) 3:784–8. doi: 10.1016/j.euo.2020.04.002
45. Yao R, Ai B, Wang Z, Shen B, Xue G, and Yu D. Uncovering microbial composition of the tissue microenvironment in bladder cancer using RNA sequencing data. J Cancer. (2024) 15:2431–41. doi: 10.7150/jca.93055
46. Oresta B, Braga D, Lazzeri M, Frego N, Saita A, Faccani C, et al. The microbiome of catheter collected urine in males with bladder cancer according to disease stage. J Urol. (2021) 205:86–93. doi: 10.1097/ju.0000000000001336
47. Sun JX, Xia QD, Zhong XY, Liu Z, and Wang SG. The bladder microbiome of NMIBC and MIBC patients revealed by 2bRAD-M. Front Cell Infect Microbiol. (2023) 131182322:1182322. doi: 10.3389/fcimb.2023.1182322
48. Bilski K, Żeber-Lubecka N, Kulecka M, Dąbrowska M, Bałabas A, Ostrowski J, et al. Microbiome sex-related diversity in non-muscle-invasive urothelial bladder cancer. Curr Issues Mol Biol. (2024) 46:3595–609. doi: 10.3390/cimb46040225
49. Knorr J, Lone Z, Werneburg G, Adler A, Agudelo J, Suryavanshi M, et al. An exploratory study investigating the impact of the bladder tumor microbiome on Bacillus Calmette Guerin (BCG) response in non-muscle invasive bladder cancer. Urol Oncol. (2024) 42:291.e291–291.e211. doi: 10.1016/j.urolonc.2024.04.011
50. Hussein AA, Bhat TA, Jing Z, Gomez EC, Wasay MA, Singh PK, et al. Does the urinary microbiome profile change after treatment of bladder cancer? World J Urol. (2023) 41:3593–8. doi: 10.1007/s00345-023-04627-1
51. Qiu Y, Gao Y, Chen C, Xie M, Huang P, Sun Q, et al. Deciphering the influence of urinary microbiota on FoxP3+ regulatory T cell infiltration and prognosis in Chinese patients with non-muscle-invasive bladder cancer. Hum Cell. (2022) 35:511–21. doi: 10.1007/s13577-021-00659-0
52. Kamat AM, Sylvester RJ, Böhle A, Palou J, Lamm DL, Brausi M, et al. Definitions, end points, and clinical trial designs for non-muscle-invasive bladder cancer: recommendations from the international bladder cancer group. J Clin Oncol. (2016) 34:1935–44. doi: 10.1200/jco.2015.64.4070
53. Chang SS, Bochner BH, Chou R, Dreicer R, Kamat AM, Lerner SP, et al. Treatment of non-metastatic muscle-invasive bladder cancer: AUA/ASCO/ASTRO/SUO guideline. J Urol. (2017) 198:552–9. doi: 10.1016/j.juro.2017.04.086
54. Ghodoussipour S, Bivalacqua T, Bryan RT, Li R, Mir MC, Palou J, et al. A systematic review of novel intravesical approaches for the treatment of patients with non-muscle-invasive bladder cancer. Eur Urol. (2025) 88:33–55. doi: 10.1016/j.eururo.2025.02.010
55. Heidrich V, Mariotti ACH, Inoue LT, Coser EM, Dos Santos EX, Dos Santos HDB, et al. The bladder microbiota is not significantly altered by intravesical BCG therapy. Urol Oncol. (2024) 42:22.e13–21. doi: 10.1016/j.urolonc.2023.11.003
56. Min K, Zheng CM, Kim S, Kim H, Lee M, Piao XM, et al. Differential urinary microbiome and its metabolic footprint in bladder cancer patients following BCG treatment. Int J Mol Sci. (2024) 25:11157. doi: 10.3390/ijms252011157
57. Isali I, Almassi N, Nizam A, Campbell R, Weight C, Gupta S, et al. State of the art: the microbiome in bladder cancer. Urol Oncol. (2025) 43:199–208. doi: 10.1016/j.urolonc.2024.11.008
58. Zhang Y, Wang W, Zhou H, and Cui Y. Urinary Eubacterium sp. CAG:581 Promotes Non-Muscle Invasive Bladder Cancer (NMIBC) Development through the ECM1/MMP9 Pathway. Cancers (Basel). (2023) 15:809. doi: 10.3390/cancers15030809
59. Camargo JA, Passos GR, Ferrari KL, Billis A, Saad MJA, and Reis LO. Intravesical immunomodulatory imiquimod enhances bacillus calmette-guérin downregulation of nonmuscle-invasive bladder cancer. Clin Genitourin Cancer. (2018) 16:e587–93. doi: 10.1016/j.clgc.2017.10.019
60. He C, Li B, Huang L, Teng C, Bao Y, Ren M, et al. Gut microbial composition changes in bladder cancer patients: A case-control study in Harbin, China. Asia Pac J Clin Nutr. (2020) 29:395–403. doi: 10.6133/apjcn.202007_29(2).0022
61. Yang H, Jin C, Li J, Zhang Z, Zhao K, Yin X, et al. Causal relationship between bladder cancer and gut microbiota contributes to the gut-bladder axis: A two-sample Mendelian randomization study. Urol Oncol. (2024) 43:267. doi: 10.1016/j.urolonc.2024.10.014
62. Mingdong W, Xiang G, Yongjun Q, Mingshuai W, and Hao P. Causal associations between gut microbiota and urological tumors: a two-sample mendelian randomization study. BMC Cancer. (2023) 23:854. doi: 10.1186/s12885-023-11383-3
63. Wang B, Qiu Y, Xie M, Huang P, Yu Y, Sun Q, et al. Gut microbiota Parabacteroides distasonis enchances the efficacy of immunotherapy for bladder cancer by activating anti-tumor immune responses. BMC Microbiol. (2024) 24:237. doi: 10.1186/s12866-024-03372-8
64. Li WT, Iyangar AS, Reddy R, Chakladar J, Bhargava V, Sakamoto K, et al. The bladder microbiome is associated with epithelial-mesenchymal transition in muscle invasive urothelial bladder carcinoma. Cancers (Basel). (2021) 13:3649. doi: 10.3390/cancers13153649
65. Galeano Niño JL, Wu H, LaCourse KD, Kempchinsky AG, Baryiames A, Barber B, et al. Effect of the intratumoral microbiota on spatial and cellular heterogeneity in cancer. Nature. (2022) 611:810–7. doi: 10.1038/s41586-022-05435-0
66. Woolley DE and Grafton CA. Collagenase immunolocalization studies of cutaneous secondary melanomas. Br J Cancer. (1980) 42:260–5. doi: 10.1038/bjc.1980.225
67. de Almeida LGN, Thode H, Eslambolchi Y, Chopra S, Young D, Gill S, et al. Matrix metalloproteinases: from molecular mechanisms to physiology, pathophysiology, and pharmacology. Pharmacol Rev. (2022) 74:712–68. doi: 10.1124/pharmrev.121.000349
68. Wysocki AB, Bhalla-Regev SK, Tierno PM Jr., Stevens-Riley M, and Wiygul RC. Proteolytic activity by multiple bacterial species isolated from chronic venous leg ulcers degrades matrix substrates. Biol Res Nurs. (2013) 15:407–15. doi: 10.1177/1099800412464683
69. Langston JP and Carson CC 3rd. Peyronie’s disease: review and recent advances. Maturitas. (2014) 78:341–3. doi: 10.1016/j.maturitas.2014.05.024
70. Watanabe K. Collagenolytic proteases from bacteria. Appl Microbiol Biotechnol. (2004) 63:520–6. doi: 10.1007/s00253-003-1442-0
71. Goekeri C, Linke KAK, Hoffmann K, Lopez-Rodriguez E, Gluhovic V, Voß A, et al. Enzymatic modulation of the pulmonary glycocalyx enhances susceptibility to streptococcus pneumoniae. Am J Respir Cell Mol Biol. (2024) 71:646–58. doi: 10.1165/rcmb.2024-0003OC
72. Theander TG, Kharazmi A, Pedersen BK, Christensen LD, Tvede N, Poulsen LK, et al. Inhibition of human lymphocyte proliferation and cleavage of interleukin-2 by Pseudomonas aeruginosa proteases. Infect Immun. (1988) 56:1673–7. doi: 10.1128/iai.56.7.1673-1677.1988
73. Wilson M, Seymour R, and Henderson B. Bacterial perturbation of cytokine networks. Infect Immun. (1998) 66:2401–9. doi: 10.1128/iai.66.6.2401-2409.1998
74. Maresz KJ, Hellvard A, Sroka A, Adamowicz K, Bielecka E, Koziel J, et al. Porphyromonas gingivalis facilitates the development and progression of destructive arthritis through its unique bacterial peptidylarginine deiminase (PAD). PloS Pathog. (2013) 9:e1003627. doi: 10.1371/journal.ppat.1003627
75. Zeltz C and Gullberg D. Post-translational modifications of integrin ligands as pathogenic mechanisms in disease. Matrix Biol. (2014) 40:5–9. doi: 10.1016/j.matbio.2014.08.001
76. Xu X, Wei F, Xiao L, Wu R, Wei B, Huang S, et al. High proportion of circulating CD8 + CD28- senescent T cells is an independent predictor of distant metastasis in nasopharyngeal canrcinoma after radiotherapy. J Transl Med. (2023) 21:64. doi: 10.1186/s12967-023-03912-2
77. Mace EM and Orange JS. Emerging insights into human health and NK cell biology from the study of NK cell deficiencies. Immunol Rev. (2019) 287:202–25. doi: 10.1111/imr.12725
78. Kakuda T, Suzuki J, Matsuoka Y, Kikugawa T, Saika T, and Yamashita M. Senescent CD8(+) T cells acquire NK cell-like innate functions to promote antitumor immunity. Cancer Sci. (2023) 114:2810–20. doi: 10.1111/cas.15824
79. Shin E, Bak SH, Park T, Kim JW, Yoon SR, Jung H, et al. Understanding NK cell biology for harnessing NK cell therapies: targeting cancer and beyond. Front Immunol. (2023) 141192907:1192907. doi: 10.3389/fimmu.2023.1192907
80. Nuñez C, Nishimoto N, Gartland GL, Billips LG, Burrows PD, Kubagawa H, et al. B cells are generated throughout life in humans. J Immunol. (1996) 156:866–72. doi: 10.4049/jimmunol.156.2.866
81. de Mol J, Kuiper J, Tsiantoulas D, and Foks AC. The dynamics of B cell aging in health and disease. Front Immunol. (2021) 12733566:733566. doi: 10.3389/fimmu.2021.733566
82. Cakala-Jakimowicz M, Kolodziej-Wojnar P, and Puzianowska-Kuznicka M. Aging-related cellular, structural and functional changes in the lymph nodes: A significant component of immunosenescence? An overview. Cells. (2021) 10:3148. doi: 10.3390/cells10113148
83. Turner VM and Mabbott NA. Structural and functional changes to lymph nodes in ageing mice. Immunology. (2017) 151:239–47. doi: 10.1111/imm.12727
84. Lanfermeijer J, Borghans JAM, and van Baarle D. How age and infection history shape the antigen-specific CD8(+) T-cell repertoire: Implications for vaccination strategies in older adults. Aging Cell. (2020) 19:e13262. doi: 10.1111/acel.13262
85. Miller J. The function of the thymus and its impact on modern medicine. Science. (2020) 369:eaba2429. doi: 10.1126/science.aba2429
86. Wilkinson AC, Igarashi KJ, and Nakauchi H. Haematopoietic stem cell self-renewal in vivo and ex vivo. Nat Rev Genet. (2020) 21:541–54. doi: 10.1038/s41576-020-0241-0
87. Frasca D, Diaz A, Romero M, Mendez NV, Landin AM, and Blomberg BB. Effects of age on H1N1-specific serum IgG1 and IgG3 levels evaluated during the 2011–2012 influenza vaccine season. Immun Ageing. (2013) 10:14. doi: 10.1186/1742-4933-10-14
88. Dowery R, Benhamou D, Benchetrit E, Harel O, Nevelsky A, Zisman-Rozen S, et al. Peripheral B cells repress B-cell regeneration in aging through a TNF-α/IGFBP-1/IGF-1 immune-endocrine axis. Blood. (2021) 138:1817–29. doi: 10.1182/blood.2021012428
89. Li J, Huang D, Lei B, Huang J, Yang L, Nie M, et al. VLA-4 suppression by senescence signals regulates meningeal immunity and leptomeningeal metastasis. Elife. (2022) 11:e83272. doi: 10.7554/eLife.83272
90. Liu X, Li L, Si F, Huang L, Zhao Y, Zhang C, et al. NK and NKT cells have distinct properties and functions in cancer. Oncogene. (2021) 40:4521–37. doi: 10.1038/s41388-021-01880-9
91. Manser AR and Uhrberg M. Age-related changes in natural killer cell repertoires: impact on NK cell function and immune surveillance. Cancer Immunol Immunother. (2016) 65:417–26. doi: 10.1007/s00262-015-1750-0
92. Shehata HM, Hoebe K, and Chougnet CA. The aged nonhematopoietic environment impairs natural killer cell maturation and function. Aging Cell. (2015) 14:191–9. doi: 10.1111/acel.12303
93. Agrawal A and Gupta S. Impact of aging on dendritic cell functions in humans. Ageing Res Rev. (2011) 10:336–45. doi: 10.1016/j.arr.2010.06.004
94. Gardner JK, Mamotte CDS, Jackaman C, and Nelson DJ. Modulation of dendritic cell and T cell cross-talk during aging: The potential role of checkpoint inhibitory molecules. Ageing Res Rev. (2017) 38:40–51. doi: 10.1016/j.arr.2017.07.002
95. Gon Y, Hashimoto S, Hayashi S, Koura T, Matsumoto K, and Horie T. Lower serum concentrations of cytokines in elderly patients with pneumonia and the impaired production of cytokines by peripheral blood monocytes in the elderly. Clin Exp Immunol. (1996) 106:120–6.
96. van Duin D, Allore HG, Mohanty S, Ginter S, Newman FK, Belshe RB, et al. Prevaccine determination of the expression of costimulatory B7 molecules in activated monocytes predicts influenza vaccine responses in young and older adults. J Infect Dis. (2007) 195:1590–7. doi: 10.1086/516788
97. Liang S, Domon H, Hosur KB, Wang M, and Hajishengallis G. Age-related alterations in innate immune receptor expression and ability of macrophages to respond to pathogen challenge. vitro. Mech Ageing Dev. (2009) 130:538–46. doi: 10.1016/j.mad.2009.06.006
98. Jackaman C, Radley-Crabb HG, Soffe Z, Shavlakadze T, Grounds MD, and Nelson DJ. Targeting macrophages rescues age-related immune deficiencies in C57BL/6J geriatric mice. Aging Cell. (2013) 12:345–57. doi: 10.1111/acel.12062
99. Sharma S, Dominguez AL, and Lustgarten J. High accumulation of T regulatory cells prevents the activation of immune responses in aged animals. J Immunol. (2006) 177:8348–55. doi: 10.4049/jimmunol.177.12.8348
100. Fontana L, Zhao E, Amir M, Dong H, Tanaka K, and Czaja MJ. Aging promotes the development of diet-induced murine steatohepatitis but not steatosis. Hepatology. (2013) 57:995–1004. doi: 10.1002/hep.26099
101. Kelly J, Ali Khan A, Yin J, Ferguson TA, and Apte RS. Senescence regulates macrophage activation and angiogenic fate at sites of tissue injury in mice. J Clin Invest. (2007) 117:3421–6. doi: 10.1172/jci32430
102. Franceschi C, Garagnani P, Parini P, Giuliani C, and Santoro A. Inflammaging: a new immune-metabolic viewpoint for age-related diseases. Nat Rev Endocrinol. (2018) 14:576–90. doi: 10.1038/s41574-018-0059-4
103. Thevaranjan N, Puchta A, Schulz C, Naidoo A, Szamosi JC, Verschoor CP, et al. Age-associated microbial dysbiosis promotes intestinal permeability, systemic inflammation, and macrophage dysfunction. Cell Host Microbe. (2017) 21:455–466.e454. doi: 10.1016/j.chom.2017.03.002
104. Martínez-López MF, de Almeida CR, Fontes M, Mendes RV, Kaufmann SHE, and Fior R. Macrophages directly kill bladder cancer cells through TNF signaling as an early response to BCG therapy. Dis Model Mech. (2024) 17:dmm050693. doi: 10.1242/dmm.050693
105. Tan C, Li C, Ge R, Zhang W, Wu Z, Wang S, et al. Mcl-1 downregulation enhances BCG treatment efficacy in bladder cancer by promoting macrophage polarization. Cancer Cell Int. (2025) 25:48. doi: 10.1186/s12935-025-03676-3
106. Xu J, Ding L, Mei J, Hu Y, Kong X, Dai S, et al. Dual roles and therapeutic targeting of tumor-associated macrophages in tumor microenvironments. Signal Transduct Target Ther. (2025) 10:268. doi: 10.1038/s41392-025-02325-5
107. Duan Z and Luo Y. Targeting macrophages in cancer immunotherapy. Signal Transduct Target Ther. (2021) 6:127. doi: 10.1038/s41392-021-00506-6
108. Jian N, Yu L, Ma L, Zheng B, and Huang W. BCG therapy in bladder cancer and its tumor microenvironment interactions. Clin Microbiol Rev. (2025) 38:e0021224. doi: 10.1128/cmr.00212-24
109. Salminen A, Kauppinen A, and Kaarniranta K. Myeloid-derived suppressor cells (MDSC): an important partner in cellular/tissue senescence. Biogerontology. (2018) 19:325–39. doi: 10.1007/s10522-018-9762-8
110. Salminen A, Kauppinen A, and Kaarniranta K. AMPK activation inhibits the functions of myeloid-derived suppressor cells (MDSC): impact on cancer and aging. J Mol Med (Berl). (2019) 97:1049–64. doi: 10.1007/s00109-019-01795-9
111. Ecker BL, Kaur A, Douglass SM, Webster MR, Almeida FV, Marino GE, et al. Age-related changes in HAPLN1 increase lymphatic permeability and affect routes of melanoma metastasis. Cancer Discov. (2019) 9:82–95. doi: 10.1158/2159-8290.Cd-18-0168
112. Kaur A, Webster MR, Marchbank K, Behera R, Ndoye A, Kugel CH 3rd, et al. sFRP2 in the aged microenvironment drives melanoma metastasis and therapy resistance. Nature. (2016) 532:250–4. doi: 10.1038/nature17392
113. Bancaro N, Calì B, Troiani M, Elia AR, Arzola RA, Attanasio G, et al. Apolipoprotein E induces pathogenic senescent-like myeloid cells in prostate cancer. Cancer Cell. (2023) 41:602–619.e611. doi: 10.1016/j.ccell.2023.02.004
114. Choi UY, Choi YJ, Lee SA, and Yoo JS. Cisd2 deficiency impairs neutrophil function by regulating calcium homeostasis via Calnexin and SERCA. BMB Rep. (2024) 57:256–61. doi: 10.5483/BMBRep.2024-0011
115. Yang C, Wang Z, Li L, Zhang Z, Jin X, Wu P, et al. Aged neutrophils form mitochondria-dependent vital NETs to promote breast cancer lung metastasis. J Immunother Cancer. (2021) 9:e002875. doi: 10.1136/jitc-2021-002875
116. Si F, Liu X, Tao Y, Zhang Y, Ma F, Hsueh EC, et al. Blocking senescence and tolerogenic function of dendritic cells induced by γδ Treg cells enhances tumor-specific immunity for cancer immunotherapy. J Immunother Cancer. (2024) 12:e008219. doi: 10.1136/jitc-2023-008219
117. Piskor EM, Ross J, Möröy T, and Kosan C. Myc-interacting zinc finger protein 1 (Miz-1) is essential to maintain homeostasis and immunocompetence of the B cell lineage. Biol (Basel). (2022) 11:504. doi: 10.3390/biology11040504
118. Frasca D, Romero M, Garcia D, Thaller S, and Bueno V. Adipocyte-derived inflammatory molecules induce senescent B cells through metabolic pathways. Obes (Silver Spring). (2024) 32:1441–7. doi: 10.1002/oby.24013
119. Khan S, Chakraborty M, Wu F, Chen N, Wang T, Chan YT, et al. B cells promote T cell immunosenescence and mammalian aging parameters. bioRxiv. (2023) 556363. doi: 10.1101/2023.09.12.556363
120. Wang SS, Liu W, Ly D, Xu H, Qu L, and Zhang L. Tumor-infiltrating B cells: their role and application in anti-tumor immunity in lung cancer. Cell Mol Immunol. (2019) 16:6–18. doi: 10.1038/s41423-018-0027-x
121. Kogut I, Scholz JL, Cancro MP, and Cambier JC. B cell maintenance and function in aging. Semin Immunol. (2012) 24:342–9. doi: 10.1016/j.smim.2012.04.004
122. Medzhitov R. Toll-like receptors and innate immunity. Nat Rev Immunol. (2001) 1:135–45. doi: 10.1038/35100529
123. Karin M and Ben-Neriah Y. Phosphorylation meets ubiquitination: the control of NF-[kappa]B activity. Annu Rev Immunol. (2000) 18:621–63. doi: 10.1146/annurev.immunol.18.1.621
124. Zarember KA and Godowski PJ. Tissue expression of human Toll-like receptors and differential regulation of Toll-like receptor mRNAs in leukocytes in response to microbes, their products, and cytokines. J Immunol. (2002) 168:554–61. doi: 10.4049/jimmunol.168.2.554
125. Baggiolini M, Dewald B, and Moser B. Human chemokines: an update. Annu Rev Immunol. (1997) 15:675–705. doi: 10.1146/annurev.immunol.15.1.675
126. Amulic B, Cazalet C, Hayes GL, Metzler KD, and Zychlinsky A. Neutrophil function: from mechanisms to disease. Annu Rev Immunol. (2012) 30:459–89. doi: 10.1146/annurev-immunol-020711-074942
127. Brinkmann V, Reichard U, Goosmann C, Fauler B, Uhlemann Y, Weiss DS, et al. Neutrophil extracellular traps kill bacteria. Science. (2004) 303:1532–5. doi: 10.1126/science.1092385
128. Nathan C. Neutrophils and immunity: challenges and opportunities. Nat Rev Immunol. (2006) 6:173–82. doi: 10.1038/nri1785
129. Nathan C. Points of control in inflammation. Nature. (2002) 420:846–52. doi: 10.1038/nature01320
130. Sharma P, Vijaykumar A, Raghavan JV, Rananaware SR, Alakesh A, Bodele J, et al. Particle uptake driven phagocytosis in macrophages and neutrophils enhances bacterial clearance. J Contr Rel. (2022) 343:131–41. doi: 10.1016/j.jconrel.2022.01.030
131. Aderem A and Underhill DM. Mechanisms of phagocytosis in macrophages. Annu Rev Immunol. (1999) 17:593–623. doi: 10.1146/annurev.immunol.17.1.593
132. Banchereau J and Steinman RM. Dendritic cells and the control of immunity. Nature. (1998) 392:245–52. doi: 10.1038/32588
133. Zhu J and Paul WE. CD4 T cells: fates, functions, and faults. Blood. (2008) 112:1557–69. doi: 10.1182/blood-2008-05-078154
134. Kaech SM and Cui W. Transcriptional control of effector and memory CD8+ T cell differentiation. Nat Rev Immunol. (2012) 12:749–61. doi: 10.1038/nri3307
135. Butler DSC, Cafaro C, Putze J, Wan MLY, Tran TH, Ambite I, et al. A bacterial protease depletes c-MYC and increases survival in mouse models of bladder and colon cancer. Nat Biotechnol. (2021) 39:754–64. doi: 10.1038/s41587-020-00805-3
136. Mehmandar-Oskuie A, Tohidfar M, Hajikhani B, and Karimi F. Anticancer effects of cell-free culture supernatant of Escherichia coli in bladder cancer cell line: New insight into the regulation of inflammation. Gene. (2023) 889:147795. doi: 10.1016/j.gene.2023.147795
137. Andersson M, Poljakovic M, and Persson K. Caspase-3-dependent apoptosis in Escherichia coli-infected urothelium: involvement of inducible nitric oxide synthase. BJU Int. (2006) 98:160–5. doi: 10.1111/j.1464-410X.2006.06151.x
138. Abraham SN and Miao Y. The nature of immune responses to urinary tract infections. Nat Rev Immunol. (2015) 15:655–63. doi: 10.1038/nri3887
139. Murray BO, Flores C, Williams C, Flusberg DA, Marr EE, Kwiatkowska KM, et al. Recurrent urinary tract infection: A mystery in search of better model systems. Front Cell Infect Microbiol. (2021) 11691210:691210. doi: 10.3389/fcimb.2021.691210
140. Mulvey MA, Lopez-Boado YS, Wilson CL, Roth R, Parks WC, Heuser J, et al. Induction and evasion of host defenses by type 1-piliated uropathogenic Escherichia coli. Science. (1998) 282:1494–7. doi: 10.1126/science.282.5393.1494
141. Justice SS, Hung C, Theriot JA, Fletcher DA, Anderson GG, Footer MJ, et al. Differentiation and developmental pathways of uropathogenic Escherichia coli in urinary tract pathogenesis. Proc Natl Acad Sci U.S.A. (2004) 101:1333–8. doi: 10.1073/pnas.0308125100
142. Wright KJ, Seed PC, and Hultgren SJ. Uropathogenic Escherichia coli flagella aid in efficient urinary tract colonization. Infect Immun. (2005) 73:7657–68. doi: 10.1128/iai.73.11.7657-7668.2005
143. Martinez JJ, Mulvey MA, Schilling JD, Pinkner JS, and Hultgren SJ. Type 1 pilus-mediated bacterial invasion of bladder epithelial cells. EMBO J. (2000) 19:2803–12. doi: 10.1093/emboj/19.12.2803
144. Choi HW, Bowen SE, Miao Y, Chan CY, Miao EA, Abrink M, et al. Loss of bladder epithelium induced by cytolytic mast cell granules. Immunity. (2016) 45:1258–69. doi: 10.1016/j.immuni.2016.11.003
145. Chen MC, Blunt LW, Pins MR, and Klumpp DJ. Tumor necrosis factor promotes differential trafficking of bladder mast cells in neurogenic cystitis. J Urol. (2006) 175:754–9. doi: 10.1016/s0022-5347(05)00171-0
146. Chen MC, Keshavan P, Gregory GD, and Klumpp DJ. RANTES mediates TNF-dependent lamina propria mast cell accumulation and barrier dysfunction in neurogenic cystitis. Am J Physiol Renal Physiol. (2007) 292:F1372–1379. doi: 10.1152/ajprenal.00472.2006
147. Wernersson S and Pejler G. Mast cell secretory granules: armed for battle. Nat Rev Immunol. (2014) 14:478–94. doi: 10.1038/nri3690
148. Nagamatsu K, Hannan TJ, Guest RL, Kostakioti M, Hadjifrangiskou M, Binkley J, et al. Dysregulation of Escherichia coli α-hemolysin expression alters the course of acute and persistent urinary tract infection. Proc Natl Acad Sci U.S.A. (2015) 112:E871–880. doi: 10.1073/pnas.1500374112
149. Broz P, von Moltke J, Jones JW, Vance RE, and Monack DM. Differential requirement for Caspase-1 autoproteolysis in pathogen-induced cell death and cytokine processing. Cell Host Microbe. (2010) 8:471–83. doi: 10.1016/j.chom.2010.11.007
150. Haynes MD, Martin TA, Jenkins SA, Kynaston HG, Matthews PN, and Jiang WG. Tight junctions and bladder cancer (review). Int J Mol Med. (2005) 16:3–9. doi: 10.3892/ijmm.16.1.3
151. Otani T and Furuse M. Tight junction structure and function revisited. Trends Cell Biol. (2020) 30:805–17. doi: 10.1016/j.tcb.2020.08.004
152. Tsukita S and Furuse M. Occludin and claudins in tight-junction strands: leading or supporting players? Trends Cell Biol. (1999) 9:268–73. doi: 10.1016/s0962-8924(99)01578-0
153. Tsukita S, Tanaka H, and Tamura A. The claudins: from tight junctions to biological systems. Trends Biochem Sci. (2019) 44:141–52. doi: 10.1016/j.tibs.2018.09.008
154. Montalbetti N, Rued AC, Taiclet SN, Birder LA, Kullmann FA, and Carattino MD. Urothelial tight junction barrier dysfunction sensitizes bladder afferents. eNeuro. (2017) 4:ENEURO.0381-16.2017. doi: 10.1523/eneuro.0381-16.2017
155. Zhang CO, Wang JY, Koch KR, and Keay S. Regulation of tight junction proteins and bladder epithelial paracellular permeability by an antiproliferative factor from patients with interstitial cystitis. J Urol. (2005) 174:2382–7. doi: 10.1097/01.ju.0000180417.11976.99
156. Gao J, Young G, Xue KX, Li BG, and Sun YL. Characteristics of invasiveness of human nasopharyngeal carcinoma cells in organ culture, as observed by scanning electron microscopy. Pathol Res Pract. (1982) 174:325–41. doi: 10.1016/S0344-0338(82)80015-0
157. Pinho SS and Reis CA. Glycosylation in cancer: mechanisms and clinical implications. Nat Rev Cancer. (2015) 15:540–55. doi: 10.1038/nrc3982
158. Alfano M, Canducci F, Nebuloni M, Clementi M, Montorsi F, and Salonia A. The interplay of extracellular matrix and microbiome in urothelial bladder cancer. Nat Rev Urol. (2016) 13:77–90. doi: 10.1038/nrurol.2015.292
159. Ganz T. Defensins: antimicrobial peptides of innate immunity. Nat Rev Immunol. (2003) 3:710–20. doi: 10.1038/nri1180
160. Zasloff M. Antimicrobial peptides, innate immunity, and the normally sterile urinary tract. J Am Soc Nephrol. (2007) 18:2810–6. doi: 10.1681/asn.2007050611
161. Sobel JD. Pathogenesis of urinary tract infection. Role Host defenses. Infect Dis Clin North Am. (1997) 11:531–49. doi: 10.1016/s0891-5520(05)70372-x
162. Billips BK, Forrestal SG, Rycyk MT, Johnson JR, Klumpp DJ, and Schaeffer AJ. Modulation of host innate immune response in the bladder by uropathogenic Escherichia coli. Infect Immun. (2007) 75:5353–60. doi: 10.1128/iai.00922-07
163. Blobe GC, Schiemann WP, and Lodish HF. Role of transforming growth factor beta in human disease. N Engl J Med. (2000) 342:1350–8. doi: 10.1056/nejm200005043421807
164. Moore KW, de Waal Malefyt R, Coffman RL, and O’Garra A. Interleukin-10 and the interleukin-10 receptor. Annu Rev Immunol. (2001) 19:683–765. doi: 10.1146/annurev.immunol.19.1.683
165. Xu Y, Zeng H, Jin K, Liu Z, Zhu Y, Xu L, et al. Immunosuppressive tumor-associated macrophages expressing interlukin-10 conferred poor prognosis and therapeutic vulnerability in patients with muscle-invasive bladder cancer. J Immunother Cancer. (2022) 10:e003416. doi: 10.1136/jitc-2021-003416
166. Chen Z, Zhou L, Liu L, Hou Y, Xiong M, Yang Y, et al. Single-cell RNA sequencing highlights the role of inflammatory cancer-associated fibroblasts in bladder urothelial carcinoma. Nat Commun. (2020) 11:5077. doi: 10.1038/s41467-020-18916-5
167. Whiteside TL. Regulatory T cell subsets in human cancer: are they regulating for or against tumor progression? Cancer Immunol Immunother. (2014) 63:67–72. doi: 10.1007/s00262-013-1490-y
168. Ritz U and Seliger B. The transporter associated with antigen processing (TAP): structural integrity, expression, function, and its clinical relevance. Mol Med. (2001) 7:149–58. doi: 10.1007/BF03401948
169. Zheng X, Chen J, Deng M, Ning K, Peng Y, Liu Z, et al. G3BP1 and SLU7 jointly promote immune evasion by downregulating MHC-I via PI3K/akt activation in bladder cancer. Adv Sci (Weinh). (2024) 11:e2305922. doi: 10.1002/advs.202305922
170. DeJong EN, Surette MG, and Bowdish DME. The gut microbiota and unhealthy aging: disentangling cause from consequence. Cell Host Microbe. (2020) 28:180–9. doi: 10.1016/j.chom.2020.07.013
171. Madison AA, Burd CE, Andridge R, Wilson SJ, Bailey MT, Belury MA, et al. Gut microbiota richness and diversity track with T cell aging in healthy adults. J Gerontol A Biol Sci Med Sci. (2024) 79:glad276. doi: 10.1093/gerona/glad276
172. Chulenbayeva L, Ganzhula Y, Kozhakhmetov S, Jarmukhanov Z, Nurgaziyev M, Nurgozhina A, et al. The trajectory of successful aging: insights from metagenome and cytokine profiling. Gerontology. (2024) 70:390–407. doi: 10.1159/000536082
173. Kawamoto S, Maruya M, Kato LM, Suda W, Atarashi K, Doi Y, et al. Foxp3(+) T cells regulate immunoglobulin a selection and facilitate diversification of bacterial species responsible for immune homeostasis. Immunity. (2014) 41:152–65. doi: 10.1016/j.immuni.2014.05.016
174. Bashir H, Singh S, Singh RP, Agrewala JN, and Kumar R. Age-mediated gut microbiota dysbiosis promotes the loss of dendritic cells tolerance. Aging Cell. (2023) 22:e13838. doi: 10.1111/acel.13838
175. Sbierski-Kind J, Grenkowitz S, Schlickeiser S, Sandforth A, Friedrich M, Kunkel D, et al. Effects of caloric restriction on the gut microbiome are linked with immune senescence. Microbiome. (2022) 10:57. doi: 10.1186/s40168-022-01249-4
176. Zhu X, Huang X, Hu M, Sun R, Li J, Wang H, et al. A specific enterotype derived from gut microbiome of older individuals enables favorable responses to immune checkpoint blockade therapy. Cell Host Microbe. (2024) 32:489–505.e485. doi: 10.1016/j.chom.2024.03.002
177. Gopalakrishnan V, Helmink BA, Spencer CN, Reuben A, and Wargo JA. The influence of the gut microbiome on cancer, immunity, and cancer immunotherapy. Cancer Cell. (2018) 33:570–80. doi: 10.1016/j.ccell.2018.03.015
178. Trầ;n TA, Lee HY, and Choi HW. Metabolite-mediated mechanisms linking the urinary microbiome to bladder cancer. J Microbiol. (2025) 63:e2509001. doi: 10.71150/jm.2509001
179. Bender MJ, McPherson AC, Phelps CM, Pandey SP, Laughlin CR, Shapira JH, et al. Dietary tryptophan metabolite released by intratumoral Lactobacillus reuteri facilitates immune checkpoint inhibitor treatment. Cell. (2023) 186:1846–1862.e1826. doi: 10.1016/j.cell.2023.03.011
180. Yue L, Geng F, Jin J, Li W, Liu B, Du M, et al. Lactobacillus reuteri assists engineered bacteria that target tumors to release PD-L1nb to mitigate the adverse effects of breast cancer immunotherapy. Biotechnol J. (2024) 19:e202400428. doi: 10.1002/biot.202400428
181. Soliman A, Murad MR, Jabrieh G, AlEdani EM, Saeed A, Belabaci Z, et al. A systematic review and meta-analysis of the effectiveness and safety of immune checkpoint inhibitors in patients with BCG-unresponsive non-muscle-invasive bladder cancer. Clin Genitourin Cancer. (2025) 23:102445. doi: 10.1016/j.clgc.2025.102445
182. Takeuchi A, Eto M, Tatsugami K, Shiota M, Yamada H, Kamiryo Y, et al. Antitumor activity of recombinant Bacille Calmette-Guérin secreting interleukin-15-Ag85B fusion protein against bladder cancer. Int Immunopharmacol. (2016) 35:327–31. doi: 10.1016/j.intimp.2016.03.007
Keywords: bladder cancer, immunosenescence, inflammation, microbiome, urinary tract infections
Citation: Pan S, Cui W, Lin J, Wang Z, Li Z and Liu B (2026) The infection–microbiome–immunity axis in bladder cancer: mechanistic insights and therapeutic perspectives. Front. Immunol. 16:1716230. doi: 10.3389/fimmu.2025.1716230
Received: 30 September 2025; Accepted: 16 December 2025; Revised: 15 December 2025;
Published: 12 January 2026.
Edited by:
Lorenzo Mortara, University of Insubria, ItalyReviewed by:
Ben Woolbright, University of Kansas Medical Center, United StatesAlexei Gratchev, Russian Cancer Research Center NN Blokhin, Russia
Whye Kit Leonard Lim, University of Malaysia Sarawak, Malaysia
Copyright © 2026 Pan, Cui, Lin, Wang, Li and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Zhujun Wang, emh1anVuLndAa2Vpby5qcA==; Zhenhua Li, MTM4MDQwMTYzNTNAMTM5LmNvbQ==; Bitian Liu, YnRsaXVAY211LmVkdS5jbg==; bGl1X2JpdGlhbkAxNjMuY29t
†These authors have contributed equally to this work and share first authorship
Wanlin Cui2†