Urinary Eubacterium sp. CAG:581 promotes non-muscle-invasive bladder cancer (NMIBC) development through ECM1/MMP9 pathway

doi:10.21203/rs.3.rs-2207998/v1

Download PDF

Research Article

Urinary Eubacterium sp. CAG:581 promotes non-muscle-invasive bladder cancer (NMIBC) development through ECM1/MMP9 pathway

https://doi.org/10.21203/rs.3.rs-2207998/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background: Increasing evidence points to the urinarymicrobiota as a possible key susceptibility factor for early-stage bladder cancer(BCa) progression. However, its underlying mechanism interpretation is often insufficient, given that various environmental conditions have affected the composition of urinary microbiota. Herein, we sought to rule out confounding factors and clarify how urinary Eubacterium sp. CAG:581 promoted non-muscle-invasive bladder cancer (NMIBC) development.

Methods: Differentially abundant urinary microbiota of 51 NMIBC patients and 47 healthy controls as the Cohort 1 were firstly determined by metagenomics analysis. Then we modeled the coculture of NMIBC organoids with candidate urinary Eubacterium sp. CAG:581 in anaerobic condition and explored differentially expressed genes of NMIBC organoids by RNA-Seq. Furthermore, we dissected the mechanisms involved into Eubacterium sp. CAG:581-induced extracellular matrix protein 1 (ECM1) and matrix metalloproteinase 9 (MMP9) upregulation. Finally, we used multivariate Cox modeling to investigate the clinical relevance of urinary Eubacterium sp. CAG:581 16S ribosomal RNA (16SrRNA) levels with the prognosis of 406 NMIBC patients as the Cohort 2.

Results: Eubacterium sp. CAG:581infection accelerated the proliferation of NMIBC organoids (P < 0.01); ECM1 and MMP9 were the most upregulated gene induced by increased colony forming units (CFU) gradient of Eubacterium sp. CAG:581 infection, via phosphorylating ERK1/2 in NMIBC organoids of the Cohort 1. Excluding the favorable impact of potential contributing factors, ROC curve of the Cohort 2 manifested its 3-year AUC value as 0.79 and the cut-off point of Eubacterium sp. CAG:581 16SrRNA as 10.3 (delta CT value).

Conclusion: Our evidence suggests that urinary Eubacterium sp. CAG:581 promoted NMIBC progression through ECM1/MMP9 pathway, which may serve as the promising noninvasive diagnostic biomarker for NMIBC.

Non-muscle-invasive bladder cancer (NMIBC)

Eubacterium sp. CAG:581

Extracellular matrix protein 1 (ECM1)

Matrix metalloproteinase 9 (MMP9)

Noninvasive urinary diagnostics.

Bladder cancer (BCa) is the second most common malignancy of the urinary tract, accounting for 4.6% of all new cancer diagnoses. It causes 400,000 new diagnoses and 160,000 deaths worldwide each year, which is age-associated and individuals aged 75–84 years accounting for the largest percentage at 30% of new cases ^[1]. BCa can be divided into muscle-infiltrating bladder cancer (MIBC) and non-muscle-infiltrating bladder cancer (NMIBC) according to whether it invades into the muscular layer of the bladder wall ^[2]. NMIBC comprises approximately 75–80% of all newly diagnosed BCa ^[3], which is the malignant papillary tumor of the bladder confined to the mucosal layer (TIS/CIS accounting for 10%, Ta for 70%) and lamina propria (T1 for 20%) of the bladder with no muscle infiltration ^[4]. After transurethral resection of bladder tumor (TURBT), the 5-year risk of recurrence for high-risk NMIBC can be as high as 80% ^[5]. However, if NMIBC is screened at an early stage, patients with high-risk NMIBC have much lower rate of tumor recurrence after immediate postoperative perfusion which can be cured with simple surgery ^[6]; improving the sensitivity and specificity of NMIBC screening is thus critical to the prognosis of NMIBC patients. Currently, the preferred method for screening patients with NMIBC is cystoscopy. Still, it is invasive and often screens to confirm for NMIBC only after the solid tumor ^[7]. Exploring more convenient and sensitive early-stage screening modalities is essential for NMIBC treatment.

The development of NMIBC is a complex, multifactorial and multistep pathological process, in which both intrinsic genetic factors and extrinsic environmental factors have contributed to the process ^[8]. Regional, ethnic and gender differences could affect the development of bladder cancer, with a high incidence at 50–70 years old. According to National Central Cancer Registry of China (NCCRC), the ratio of male to female mortality is 2.97:1 ^{[9, 10]}. Smoking is the most definite and major external risk factor for NMIBC. About 50% of NMIBC patients have the history of smoking, which increases the risk of bladder cancer by 2–5 times depending on the intensity and duration of smoking ^{[9, 10]}. Recent studies have shown the composition and content of the urinary flora can also impact the development and prognosis of NMIBC. Previous studies have indicated significant differences in urinary flora characteristics between BCa patients and healthy participants ^{[11, 12]}. Based on their bioinformatics analysis, there may be the link between urinary flora and bladder cancer, and some different genera might be the novel biomarkers for BCa ^[12]. However, these findings were premature and the causal relationship between urinary flora and early-stage BCa is still not clear. It needs further validation through prospective cohort studies and further mechanistic explanation.

ECM1 is a glycoprotein expressed in epithelial organs and secreted into the extracellular matrix, which can promote the proliferation of vascular endothelial cells and angiogenesis ^[13]. It has been found that the expression of ECM1 may associate with BCa progression, which was confirmed with potential anti-tumor effects by siRNA gene silencing experiments ^{[14, 15]}. Overexpression of ECM1 has now been incorporated into scoring models to suggest poor clinical prognosis and metastatic potential in several types of cancer patients ^[16]. Matrix metalloproteinases (MMPs) are critical regulators of the tumor microenvironment. Their protein hydrolytic activity initiates the degradation of extracellular matrix components so that tumors are no longer restricted by the intact basement membrane, invading surrounding tissues and ultimately leading to tumor malignancy ^[17]. MMPs have been shown to regulate not only epithelial-mesenchymal transition through various non-catalytic structural domains but also molecular signaling for cell growth, inflammation and angiogenesis in the non-protein hydrolytic manner ^[18]. Previous studies have demonstrated that ECM1 inhibited MMP9 activity through high-affinity protein/protein interactions ^{[18, 19]}. In certain cancer types, the significant increase of MMP9 transcription can be observed in parallel with the upregulation of ECM1, suggesting that ECM1-MMP9 axis is of great significance for tumorigenesis and progression ^{[18, 20]}.

In this study, we have designed two clinical cohorts for prediction and validation, respectively. Firstly, we compared the urinary microbiota of 51 NMIBC patients and 47 healthy controls as the Cohort 1 by metagenomic analysis. Then we co-cultured NMIBC organoids with candidate urinary bacterium Eubacterium sp. CAG:581 and found its underlying mechanisms that Eubacterium sp. CAG:581 promoted the growth of NMIBC organoids by upregulating the expression of ECM1-MMP9 axis, suggesting that Eubacterium sp. CAG:581 may serve as the potential diagnostic predictor of NMIBC. To further verify whether Eubacterium sp. CAG:581 has the similar predictive value for NMIBC in the different large-scale populations, we designed the Cohort 2 with 406 NMIBC patients and 398 healthy controls to determine the AUC and cut-off value of urinary Eubacterium sp. CAG:581 16SrRNA detection for potentially clinical application.

Clinical Cohorts Design and Specimens

We studied 2 cohorts of NMIBC patients from Peking University First Hospital between 2019–2022. Patients were selected based on the availability of a pre-treatment urine sample and presence of the well-modeling NMIBC organoids. Formalin-fixed paraffin-embedded tissues (FFPE) of 51 NMIBC patients and 47 healthy controls were collected as the Cohort 1. We performed metagenome sequencing studies in Cohort 1 to define which bacterium is predominant (and/or different) in the urine of NMIBC patients compared to those of healthy controls. We used the urine of 406 NMIBC patients and 398 healthy controls of the Cohort 2 as a validation dataset to determine which levels of urinary Eubacterium sp. CAG:581 generated from Cohort 1 could be applied and validated. Thus, Cohorts 1 and 2 serve as the models for our research discovery and validation, respectively. All the patients’ information could be found in Tables S1 and S2. The Ethics Committees in Peking University First Hospital approved the study protocols (Ethical number: 2019 − 138). Written informed consents were obtained from all participants in this study. The whole process of this research was carried out in accordance with the provisions of the Helsinki Declaration of 1975.

Metagenome Sequencing

Briefly, all urine samples were normalized to 0.2 ng/µl DNA material per library using a Quant-iT picogreen assay system (Life Technologies) on an AF2200 plate reader (Eppendorf), then fragmented and tagged via tagmentation. Amplification was performed by Veriti 96 well PCR (Applied Biosystems) followed by AMPure XP bead cleanup (Beckman Coulter). Fragment size was measured using Labchip GX Touch high-sensitivity. For cluster generation and next generation sequencing, samples were normalized to 1 nM, pooled and diluted to 8 pM. The paired-end cluster kit V4 was used and cluster generation was performed on an Illumina cBot, with pooled samples in all 8 lanes. Sequencing was performed on an Illumina HiSeq 2500 using SBS kit V4 chemistry. Median cluster densities were 908.5 for Nextera XT.

NMIBC organoids cocultured with urinary bacterium in the 2-chamber culture system

Coated the bottom of normoxic apical chamber with 5% (vol/vol) β-Mercaptoethanol (BME) in DMEM for 30 min at 37°C, all inserts grant apical and basal access to the cell layer, whereas standard cell culture plates allow for the greatest scalability. After the coating process, remove the supernatant and allow the BME coating to dry in the incubator for another 15–30 min. Harvest organoids from the culture in 1 ml cold DMEM, and transfer to a 15 ml Falcon tube. Top up to 10 mL with cold DMEM. Spin for 5 min at 300g, and discard supernatant. Resuspend in expansion medium with 10 µM Rho Knise Inhibitor at a density of 1000 organoids/ml. Seed 10,000 organoids in 100 µl per well of a tissue-culture-treated normoxic apical chamber of 6.5 mm diameter. Allow cells to settle for 2 days. After 3 days or when the layer is close to confluence, equilibrate the medium in the basal chamber with anaerobic gas and subsequently sealed by inserting a plug made of butyl rubber (AsONE international, Santa Clara, CA). The oxygen concentration of the apical chamber was measured by a fiberoptic oxygen meter (PreSens. Regensburg, Germany). Then add urinary bacterium to the basal side in a medium suitable for exposure. For MOI calculations, a representative well can be harvested and cells counted as described above. Perform read-outs in analogy to 3D coculture.

RNA-seq and Data Processing

Following the manufacturer’s instructions, barcoded sequencing libraries were generated using Chromium Cell Reagent Kits and sequenced across 8 lanes on HiSeq 4000 platform targeting 100,000 reads per cell for the SMC dataset. RNA-seq data were then generated using the NextSeq 500 and NovaSeq 6000 systems. Sequencing data were aligned to the human reference genome (GRCh38) and processed using the Cell Ranger 2.1.0 pipeline (10x Genomics). The raw gene expression matrix from the Cell Ranger pipeline was filtered, normalized using the Seurat R package and selected according to the following criteria: cells with > 1,000 unique molecular identifier (UMI) counts; >200 genes and < 6,000 genes; and < 20% of mitochondrial gene expression in UMI counts. From the filtered cells, the gene expression matrices were normalized to the total UMI counts per cell and transformed into the natural log scale. For batch correction, we used multiple CCA implemented in Seurat v.2.3.4 and variable genes were selected as the top 1,000 highly variable genes expressed by more than 0.1% of cells in each sample. The Metagene Bicor Plot function was used to select the number of standard correlations vectors for choosing the inflection point. Then we aligned the CCA subspaces by selecting the variably per sample origin. The major cell types were annotated by comparing the canonical marker genes and the differentially expressed genes (DEGs).

Western Blotting

All NMIBC organoids were washed twice with cold PBS and harvested for western blot. Then they were lysed in cold radioimmunoprecipitation assay (RIPA) buffer (50 mm Tris-HCl, pH 7.4, 150 mm NaCl, 1% Triton X‐100, 1% sodium deoxycholate, 0.1% SDS) containing protease inhibitors for 30 min. The lysates were then centrifuged and the supernatants were collected. Approximately 40 µg of total protein was denatured and separated by 10% SDS‐PAGE, and then transferred to a polyvinylidene fluoride membrane. The membranes were blocked with 5% non‐fat milk in Tris‐buffered saline containing 0.1% Tween‐20 (TBST) for 2 h at room temperature. The membranes were then incubated with primary antibodies overnight at 4°C. The primary antibodies were listed in the Table S3, Supporting Information. β-actin was used as a loading control. The membranes were washed five times with TBST and then incubated with horseradish peroxidase‐conjugated secondary antibodies for 1 h at room temperature. The signal was visualized using an Enhanced Chemiluminescence Detection Kit (Pierce Biotechnology, USA).

Quantitative Real-Time PCR.

Total RNA was isolated from urinary microbiome with TRIzol (Invitrogen, USA). HiScript II qRT Super Mix (Vazyme, China) was used to synthesize the first strand of cDNA. Quantitative real-time PCR was performed using the Hieff qPCR SYBR Green PCR Master Mix (Yeasen, China) with gene‐specific primers. The primers of Eubacterium sp. CAG:581 16SrRNA, ptpn6, ikzf3, ecm1, mmp9 and gapdh were listed in the Table S4, Supporting Information. All target gene transcripts were normalized to GAPDH, and the relative fold change in expression calculated using the 2^−ΔΔCT method.

Adenoviral shRNA Infection of NMIBC organoids

The shRNA adenoviruses Ad-GFP-U6-m-ECM1-shRNA (shECM1, CCTGATATTTCCTCGGGTCTT) was purchased from Vector Biolabs. A non-specific scrambled shRNA adenovirus Ad-GFP-U6-scrambled-shRNA (Vector Biolabs, 1122N, CCGGCAACAAGATGAAGAGCACCAACTCGAGTTGGTGCT) expressing green fluorescent protein (GFP) alone was used as a control. For adenoviral infection, after centrifugation of dissociated NMIBC organoids in 3.5% BSA gradient, the resulting pellet was resuspended in serum-free DMEM medium containing Ad-GFP-U6-m-ECM1-shRNA or Ad-GFP-U6-scrambled-shRNA at a concentration of 2 × 10⁸ pfu/ml. The mixture was then plated on normoxic basal chamber coated with poly-L-lysine/laminin and incubated at 37°C in 5% CO₂. Two hours after incubation, the medium was replaced with fresh supplemented DMEM medium. Three days after infection, adenovirus-infected NMIBC organoids were used for protein extraction to determine the expression of ECM1.

Statistical Analysis

Statistical analyses were carried out using the program R (www.r-project.org). Data from at least three independent experiments performed in triplicates are presented as the means ± SE. Error bars in the scatterplots and the bar graphs represent SE. Data were examined to determine whether they were normally distributed with the One-Sample Kolmogorov-Smirnov test. If the data were normally distributed, comparisons of measurement data between two groups were performed using independent sample t test and the comparisons among three or more groups were firstly performed by one-way ANOVA test. When the data represented skewed distribution, comparisons were performed by nonparametric test. Measurement data between two groups were performed using nonparametric Mann-Whitney test. To generate the ROC curves, patients were classified as recurrence time either longer or shorter than the median recurrence free survival, excluding patients who were alive for durations less than the median recurrence free survival at last follow-up. Single-sample gene set enrichment analysis (ssGSEA) was used to assess gene set activation scores in gene expression profiling data. ssGSEA calculates a sample level gene set score by comparing the distribution of gene expression ranks inside and outside the gene set. The ssGSEA score was calculated by Gene Set Variation Analysis (GSVA) R package. GraphPad Prism v.8.01 were also used for statistical analysis (GraphPad Software, La Jolla, CA, USA). Univariate and multivariate Cox regression models were used to evaluate survival. The hazard ratio (HR) and 95 percent confidence interval (CI) were adopted to find genes correlated with overall survival. P < 0.05 indicated a difference with statistical significance unless otherwise stated.

Eubacterium sp. CAG:581 is clinically associated with NMIBC occurrence. To examine the potential relationship between the urinary microbiota alteration and NMIBC development, we firstly compared the long-read metagenomics sequencing data of 51 NMIBC patients and 47 healthy controls. LEfSe algorithm was used to define their potential differential bacterium patterns. We found Eubacterium sp. CAG:581, Bacteroides sp. 4_3_47FAA and Flavobacteriales were enriched in NMIBC group as compared to healthy control group (Fig. 1A). Flavobacteriales belong to the taxonomy level of class, hence we further studied Eubacterium sp. CAG:581 and Bacteroides sp. 4_3_47FAA for quantitative validation. The gut microbiota diversity of the above two groups was analyzed by the Chao1 index and Rank Abundance Curves for α diversity and Bray-Curtis distance and Binary-Jaccard distance for β diversity. It showed that α diversity of the urinary bacterial community of NMIBC group was lower than those of healthy control groups (Fig. 1B and 1C). β diversity of the urinary microbiota evaluated by ANOSIM was significantly different between the two groups based on the Bray-Curtis distances (R = 0.144, P = 0.025, Fig. 1D) and Binary-Jaccard distance (R² = 0.190, P = 0.003, Fig. 1E). Then the difference in bacterial community composition was analyzed. At the phylum, class and genus level, the predominantly abundant phyla of the NMIBC group were Eubacterium sp. CAG:581, Bacteroides sp. 4_3_47FAA and Flavobacteriales, while the enriched phyla of the healthy control group were listed as the cyan columns in Fig. 1F.

The functional composition of the urinary microbiome was compared between NMIBC patients and controls by COG and KEGG pathway analyses. Although the functional compositions of the two groups were highly similar, COG analyses indicated the clustering of metabolic modules were increased in NMIBC group including the metabolism of xenobiotics by cytochrome P450 (E-value = 31.357, P < 0.001), purine (E-value = 30.835, P = 0.022), flavone and flavonol biosynthesis (E-value = 29.663, P = 0.029) (Fig. 1G). KEGG pathway analysis showed that these differential metabolisms were majorly concentrated on oxidative phosphorylation, cardiac muscle contraction and carbon metabolism (Fig. 1H). These findings are consistent with the hypermetabolic activity and aggressive characteristics of NMIBC.

Coculture of Eubacterium sp. CAG:581 promoted the growth of NMIBC organoids. Hypoxia is essential for the growth of obligate anaerobes, but prohibitive for the maintenance of viable tumor organoids ^[21]. To surmount this tradeoff in oxygen demands, we developed NMIBC organoids and anaerobes coculture system, consisting of a normoxic apical chamber and a hypoxic basal chamber. The plug inserts tightly, physically blocking the influx of external oxygen, which allows maintenance of hypoxia in the basal chamber, while oxygen freely perfuses the apical chamber (Fig. 2A). NMIBC organoids model derived from NMIBC patients were established on the array chip using 50% Matrigel. Each chip had a reservoir layer on the top, a 3D implanting hole in the middle, and anaerobes culture slide underneath. The nested design allowed convenient medium exchange without disruption of the 3D organoids (Fig. 2A). It showed that organoids size on the chip increased over time and achieved a diameter of 30 µm within 21 days. Eubacterium sp. CAG:581 and Bacteroides sp. 4_3_47FAA coculture groups respectively proliferated faster by 48.5% and 37.8% when compared with control NMIBC organoids on Day 21 (Fig. 2B). On day 21, bright-field images of Eubacterium sp. CAG:581 coculture group has presented heterogeneous morphologies with predominantly thin-walled cystic structure and solid dense structure (Fig. 2C). To gain insights into the underlying mechanisms, we randomly performed RNA-Seq to compare Eubacterium sp. CAG:581-cocultured NMIBC organoids (N14-N26) and control NMIBC organoids (N1-N13). It demonstrated that ECM1 and MMP9 were most significantly upregulated in Eubacterium sp. CAG:581-cocultured NMIBC organoids, while PTPN6 and IKZF3 were mostly downregulated in the heatmap and ssGSEA analysis (Fig. 2D and 2E), which should be further validated by molecular biological experiments.

Eubacterium sp. CAG:581 activated ECM1/ERK1/2 phosphorylation/MMP9 of NMIBC organoids. Based on the above RNA-Seq predictive data, we have determined the transcriptional levels of ptpn6, ikzf3, ecm1 and mmp9 in NMIBC organoids cocultured with Eubacterium sp. CAG:581 and control NMIBC organoids by RT-PCR. It showed that increased colony forming units (CFU) gradient (5×10⁵, 10⁶, 5×10⁶, 10⁷, 5×10⁷) of Eubacterium sp. CAG:581 have significantly increased mRNA levels of ecm1 and mmp9 (Fig. 3A). Then we compared their protein expressions by the assay of western blotting, which also demonstrated increased gradient of Eubacterium sp. CAG:581 could upregulate ECM1 and MMP9 of NMIBC organoids as compared with the control organoids. It was reported that ECM1 induces tumor growth by promoting angiogenesis or enhancing the EGF signaling in the breast cancer ^[22]. We thus detected their expression of ERK1/2 phosphorylation and AKT phosphorylation, which manifested the upregulated ERK1/2 phosphorylation under the exposure of increased CFU gradient of Eubacterium sp. CAG:581 (Fig. 3B). Then we used shRNA of ECM1 to model BCa organoid^shECM1 and control BCa organoid^vector. When exposed to 10⁷ cfu Eubacterium sp. CAG:581, BCa organoid^shECM1 was determined with decreased expression of ERK1/2 phosphorylation and MMP9. Meanwhile, BCa organoid^shECM1 and BCa organoid^vector were treated with 10 µM Ravoxertinib (Rav) or Ulixertinib (Uli), both of which are inhibitors of ERK1/2 ^{[23, 24]}. It showed that both Rav and Uli could impair the expression of MMP9 (Fig. 3C). Lastly, we detected the proliferative size of Rav-treated or Uli-treated BCa organoid^shECM1 and control BCa organoid^vector under the exposure of 10⁷ cfu Eubacterium sp. CAG:581 for 21 days. We found ERK1/2 inhibition or shECM1 could effectively prohibit the growth of BCa organoids (Fig. 3D), which suggested Eubacterium sp. CAG:581 progressed NMIBC organoids by activating ECM1/ERK1/2 phosphorylation/MMP9.

Eubacterium sp. CAG:581 was endowed with the diagnostic predictor for NMIBC. Increasing evidence points to the urinary microbiota as a possible key susceptibility factor for early-stage bladder cancer (BCa) progression ^{[11, 25]}. However, its conclusive interpretation is often insufficient, given that various environmental conditions could significantly alter the regulation of urinary microbiota. Herein we have evaluated the relationship between the amount of Eubacterium sp. CAG:581, ECM1, MMP9 and other baseline features in 51 NMIBC patients and 47 healthy controls (Fig. 4A). The amount of Eubacterium sp. CAG:581 was positively associated with the occurrence of NMIBC (HR: 4.21, 95% CI: 2.54–5.33, log-rank P < 0.001). The expression of ECM1 (HR: 1.87, 95% CI: 1.61–2.83, log-rank P = 0.005) and MMP9 (HR: 1.66, 95% CI: 1.49–1.88, log-rank P = 0.013) were substantially higher in NMIBC group than healthy control group. In contrast, age, sex, smoking status and alcohol consumption of this study were not statistically significant for Pearson correlation analysis (Fig. 4A). In addition, levels of Eubacterium sp. CAG:581, ECM1 and MMP9 with survival probability of NMIBC were also analyzed by Kaplan Meier Curve. The findings revealed that higher amount of Eubacterium sp. CAG:581 was strongly associated with decreased survival probability of NMIBC (Fig. 4B), and the survival time was also favorably linked with the expression of ECM1 and MMP9 (Figs. 4C and 4D). These above data implied the detection of Eubacterium sp. CAG:581 is effective at predicting the occurrence of NMIBC.

Identification of NMIBC occurrence-associated Eubacterium sp. CAG:581 in the larger population. To further validate whether Eubacterium sp. CAG:581 levels had a similar prediction value in a different and larger NMIBC patients’ population, we analyzed an additional cohort with 406 NMIBC patients as the Cohort 2. Using PCA cluster analysis with 398 normal healthy controls, we identified the ability of Eubacterium sp. CAG:581 to distinguish NMIBC urine from healthy control urine (Fig. 5A). LASSO regression analysis of Eubacterium sp. CAG:581-induced prognostic DEGs by RNA-Seq was also modeled to verify its fine cooperativity (Fig. 5B) and stable partial likelihood deviation from the minimum value (Fig. 5C). Based on the abundance of Eubacterium sp. CAG:581 levels, we have also divided them into the group of high risk and low risk, which demonstrated that the prognosis model is feasible in their survival predictions (Figs. 5D and 5E). The prognostic value of increased urine ECM1 and MMP9 were also stable and accurate in larger NMIBC cohort. Decreased PTPN6 and IKZF3 were determined in the Cohort 2 as well (Fig. 5F). The total survival rate was significantly worse (P < 0.001) in NMIBC patients with high amounts of Eubacterium sp. CAG:581, according to the Kaplan-Meier survival curve (Fig. 5G). Receiver operating characteristic (ROC) curve analysis was conducted to predict the potential CRC recurrence using 1-, 2-, and 3-year NMIBC occurrence and 3-year occurrence was demonstrated with the highest AUC value of 0.79. Youden Index was used to determine the optimal cut-off point of 3-year NMIBC occurrence as 10.3 (delta CT value) that provided the best balance between the sensitivity and the specificity of Eubacterium sp. CAG:581 to predict NMIBC occurrence (Fig. 5H). Therefore, the data in Cohort 2 not only confirm our observation in Cohort 1 but also define the potential value of the Eubacterium sp. CAG:581 signature in predicting NMIBC occurrence.

Several studies have demonstrated that 70% NMIBC patients have the disease progression for recurrence within 5 years, and 10%-20% can progress to advanced muscle-invasive disease or distant metastatic disease ^[26]. In case of an advanced stage, high-risk NMIBC patients are thus treated with electrodesiccation of the urinary bladder tumor and postoperative instillation of Bacillus Calmette-Guérin (BCG) ^[27]. Unfortunately, instillation of BCG failed in approximately half of these patients, resulting in approximately 30% persistence or early relapse for high-risk NMIBC. 50% of them will undergo radical cystectomy ^[28]. Despite the advent of minimally invasive surgery and robotic technology, 90-day mortality and morbidity rates for patients undergoing cystectomy still remained as high as 3–6% and 28–64%, respectively ^[29]. For the past 30 years, bladder perfusion for NMIBC patients is dominated by chemotherapeutic agents in China and BCG immunotherapy in the United States. However, bladder chemotherapy instillation is an invasive drug delivery method which has led to 30% of urethral irritation such as dysuria, frequency, urgency, hematuria and cystitis. Moreover, the treatment course usually took up more than one year, resulting in poor patient compliance ^[30]. The standard treatment regimen of BCG, on the other hand, can trigger more adverse reactions. Not only is the prognosis relatively poor, but patients will also endure much suffering in the process. Currently, NMIBC diagnosis mainly relies on cystoscopy ^{[31, 32]}. Conventional imaging methods (CT urography, IVU or ultrasound, etc.) depend decisively on the personal experience of the physician, while ultrasonography, intravenous pyelogram, cystography, magnetic resonance imaging, and lymphography are not very sensitive. Cystoscopy is relatively sensitive, but invasive and expensive, which is difficult for large-scale screening ^[33]. Urine exfoliative cytology is highly specific but lacks sensitivity ^{[34, 35]}. Eurovision fluorescence in situ hybridization has high sensitivity which is widely used for routine clinical detection of NMIBC, but owned with poor sensitivity for low-grade or small tumors ^[36]. Although some studies suggest that methylated CpG sites in urine may be promising markers for the detection or monitoring of NMIBC ^[37], these assays are not fully adopted in routine clinical practice and still need to be validated in multicenter and large-scale cohorts in Asia. Novel insights for early-stage screening of NMIBC are still required with further breakthrough.

In this study, we have compared 51 patients with NMIBC and 47 healthy controls as the Cohort 1 to explore the clinical relevance of altered urinary microbiota with the development of NMIBC. Then the functional composition of the urinary microbiome was compared between NMIBC patients and controls by COG and KEGG pathway analysis. Eubacterium sp. CAG:581 was confirmed to promote the growth of NMIBC organoids by activating ECM1/ERK1/2 phosphorylation/MMP9. Lastly, we used multivariate Cox modeling to investigate the clinical relevance of urinary Eubacterium sp. CAG:581 abundance with the prognosis of 406 NMIBC patients as the Cohort 2, which suggested urinary Eubacterium sp. CAG:581 could be used for early diagnosis and prognosis of NMIBC. Thereinto, phosphorylation of ERK1/2 signalling could regulate numerous transcription factors, known to activate the transcription of a broad number of MMPs. Herein we found that inhibiting ERK1/2 phosphorylation resulted in decreased MMP-9 expression, indicating that the mediation of ERK1/2 in promoting NMIBC progression. A similar study performed by Lee et al. has manifested with tandem decreases in MMP-9 mRNA levels following inhibition of ERK1/2 phosphorylation in rhabdomyosarcoma, fibrosarcoma, bladder, colon and prostate carcinoma cells ^[38], which is in accordance with NMIBC patients of this study. In addition, as the amount of Eubacterium sp. CAG:581 has influenced the expression of ERK1/2 phosphorylation and MMP9, ECM1 is also positioned as potential therapeutic target for the functional transcriptional network with Eubacterium sp. CAG:581-induced NMIBC migration and invasion.

Normal flora of microbial colonies has developed over a long historical evolutionary process and reside on the human body's surface and inside. Microbial flora exists in sites of the oral cavity, urinary tract and intestinal tract. These florae have been found to have a tremendous effect on their hosts. Intestinal flora has been widely used in the early-stage diagnosis of neurodegenerative diseases, mood disorders, lung diseases, as well as the recurrence of digestive tract cancers ^[39–41]. In recent studies, a wealth of research on urinary flora have confirmed that bacteria in urine may play an essential role in many urinary disorders, such as urge incontinence ^[42]. The study of Thomas White et al. found that bacterial diversity of urinary flora was associated with high body mass index, hormonal status, and symptoms of urge incontinence ^[43]. Several studies of bioinformatics analysis have also shown that among NMIBC patients, the relative abundance Sphingomonas, Immunobacterium, Aeromonas and Bacillus spp. in the urinary flora of the tumor group was significantly higher than in the control group ^{[11, 44]}. However, more detailed underlying validation is insufficient for these predictions. In this study, MMP9 served as the downstream executor of NMIBC growth. It belongs to the family of zinc-dependent endopeptidases with proteolytic activity against extracellular matrix components, involving in numerous physiological and pathological processes including tissue remodeling, embryonic development, tumor growth and metastasis ^{[45, 46]}. Previous studies have revealed that MMP-9 got involved into the whole process of pathogenesis in bladder cancer ^{[45, 47, 48]}; however, the present study has only focused on the occurrence of NIMBC. We are constructing the cohort to compare NMIBC patients and MIBC patients for further validating the Eubacterium sp. CAG:581 signature in the conversion from NMIBC into MIBC.

In conclusion, understanding the mechanisms that urine bacterium contributes to NMIBC development has the potential to improve its early-stage diagnostic decisions. This study presents a novel mechanism of Eubacterium sp. CAG:581 in upregulating ECM1-MMP9 axis and identifies Eubacterium sp. CAG:581 to be clinically useful in predicting the occurrence of NMIBC.

Ethics approval and consent to participate：The Ethics Committees in Peking University First Hospital approved the study protocols (Ethical number: 2019-138). Written informed consents were obtained from all participants in this study.

Consent for publication：Written informed consent was obtained from the patients for publication and any accompanying images. The copy of the written consent is available.

Availability of data and material：All generated as well as analyzed data in the present research are contained in this manuscript.

Competing interests：The authors declare that they have no competing interests.

Funding：This project was supported by National Natural Science Foundation of China (82204515), National High Level Hospital Clinical Research Funding (Research Achievement Transformation Project of Peking University First Hospital) (2022RT04), Research Seed Fund of Peking University First Hospital (2022SF04).

Authors' contributions：The manuscript written was completed by Yuhang Zhang and Wenyu Wang. Yimin Cui has conceived the whole program. Experiment performance was done by Yuhang Zhang and Gang Zhao. Data collection was conducted by Wenyu Wang. All authors have discussed the results and reviewed the manuscript.

Acknowledgements：We thank Prof. Zu-Hua Gao at Department of Pathology, McGill University, for helpful discussions and data analysis.

Comperat E, Amin MB, Cathomas R, et al. Current best practice for bladder cancer: a narrative review of diagnostics and treatments. Lancet, 2022.
Lindskrog SV, Prip F, Lamy P, et al. An integrated multi-omics analysis identifies prognostic molecular subtypes of non-muscle-invasive bladder cancer. Nat Commun. 2021;12(1):2301.
Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424.
Sanli O, Dobruch J, Knowles MA, et al. Bladder cancer. Nat Rev Dis Primers. 2017;3:17022.
Jobczyk M, Stawiski K, Fendler W, et al. Validation of EORTC, CUETO, and EAU risk stratification in prediction of recurrence, progression, and death of patients with initially non-muscle-invasive bladder cancer (NMIBC): A cohort analysis. Cancer Med. 2020;9(11):4014–25.
Ba M, Cui S, Wang B, et al. Bladder intracavitary hyperthermic perfusion chemotherapy for the prevention of recurrence of non-muscle invasive bladder cancer after transurethral resection. Oncol Rep. 2017;37(5):2761–70.
Babjuk M, Burger M, Capoun O, et al. European Association of Urology Guidelines on Non-muscle-invasive Bladder Cancer (Ta, T1, and Carcinoma in Situ). Eur Urol. 2022;81(1):75–94.
Lai H, Cheng X, Liu Q, et al. Single-cell RNA sequencing reveals the epithelial cell heterogeneity and invasive subpopulation in human bladder cancer. Int J Cancer. 2021;149(12):2099–115.
Chen W, Zheng R, Zhang S, et al. Report of incidence and mortality in China cancer registries, 2009. Chin J Cancer Res. 2013;25(1):10–21.
Knowles MA, Hurst CD. Molecular biology of bladder cancer: new insights into pathogenesis and clinical diversity. Nat Rev Cancer. 2015;15(1):25–41.
Andolfi C, Bloodworth JC, Papachristos A, et al. The Urinary Microbiome and Bladder Cancer: Susceptibility and Immune Responsiveness. Bladder Cancer. 2020;6(3):225–35.
Liu F, Liu A, Lu X, et al. Dysbiosis signatures of the microbial profile in tissue from bladder cancer. Cancer Med. 2019;8(16):6904–14.
Wang Z, Zhou Q, Li A, et al. Extracellular matrix protein 1 (ECM1) is associated with carcinogenesis potential of human bladder cancer. Onco Targets Ther. 2019;12:1423–32.
Wang J, Guo M, Zhou X, et al. Angiogenesis related gene expression significantly associated with the prognostic role of an urothelial bladder carcinoma. Transl Androl Urol. 2020;9(5):2200–10.
Wang Z, Zhou Q, Li A, et al. Extracellular matrix protein 1 (ECM1) is associated with carcinogenesis potential of human bladder cancer. Onco Targets Ther. 2019;12:1423–32.
Cao R, Yuan L, Ma B, et al. An EMT-related gene signature for the prognosis of human bladder cancer. J Cell Mol Med. 2020;24(1):605–17.
Lu P, Takai K, Weaver VM, et al. Extracellular matrix degradation and remodeling in development and disease. Cold Spring Harb Perspect Biol, 2011, 3(12).
Xiong GP, Zhang JX, Gu SP, et al. Overexpression of ECM1 contributes to migration and invasion in cholangiocarcinoma cell. Neoplasma. 2012;59(4):409–15.
Fujimoto N, Terlizzi J, Aho S, et al. Extracellular matrix protein 1 inhibits the activity of matrix metalloproteinase 9 through high-affinity protein/protein interactions. Exp Dermatol. 2006;15(4):300–7.
Lee KM, Nam K, Oh S, et al. Extracellular matrix protein 1 regulates cell proliferation and trastuzumab resistance through activation of epidermal growth factor signaling. Breast Cancer Res. 2014;16(6):479.
Godet I, Doctorman S, Wu F, et al. Detection of Hypoxia in Cancer Models: Significance, Challenges, and Advances. Cells, 2022, 11(4).
Lee KM, Nam K, Oh S, et al. ECM1 regulates tumor metastasis and CSC-like property through stabilization of beta-catenin. Oncogene. 2015;34(50):6055–65.
Mendzelevski B, Ferber G, Janku F, et al. Effect of ulixertinib, a novel ERK1/2 inhibitor, on the QT/QTc interval in patients with advanced solid tumor malignancies. Cancer Chemother Pharmacol. 2018;81(6):1129–41.
Kidger AM, Sipthorp J, Cook SJ. ERK1/2 inhibitors: New weapons to inhibit the RAS-regulated RAF-MEK1/2-ERK1/2 pathway. Pharmacol Ther. 2018;187:45–60.
Yacouba A, Tidjani AM, Lagier JC, et al. Urinary microbiota and bladder cancer: A systematic review and a focus on uropathogens. Semin Cancer Biol, 2022.
Cui Y, Zhou Z, Chai Y, et al. Identification of a Nomogram from Ferroptosis-Related Long Noncoding RNAs Signature to Analyze Overall Survival in Patients with Bladder Cancer. J Oncol, 2021, 2021: 8533464.
Witjes JA, Palou J, Soloway M, et al. Current clinical practice gaps in the treatment of intermediate- and high-risk non-muscle-invasive bladder cancer (NMIBC) with emphasis on the use of bacillus Calmette-Guerin (BCG): results of an international individual patient data survey (IPDS). BJU Int. 2013;112(6):742–50.
Kamat AM, Shore N, Hahn N, et al. KEYNOTE-676: Phase III study of BCG and pembrolizumab for persistent/recurrent high-risk NMIBC. Future Oncol. 2020;16(10):507–16.
Mari A, Campi R, Tellini R, et al. Patterns and predictors of recurrence after open radical cystectomy for bladder cancer: a comprehensive review of the literature. World J Urol. 2018;36(2):157–70.
Koch GE, Smelser WW, Chang SS. Side Effects of Intravesical BCG and Chemotherapy for Bladder Cancer: What They Are and How to Manage Them. Urology. 2021;149:11–20.
Datovo J, Neto WA, Mendonca GB, et al. Prognostic impact of non-adherence to follow-up cystoscopy in non-muscle-invasive bladder cancer (NMIBC). World J Urol. 2019;37(10):2067–71.
Rezaee ME, Lynch KE, Li Z, et al. The impact of low- versus high-intensity surveillance cystoscopy on surgical care and cancer outcomes in patients with high-risk non-muscle-invasive bladder cancer (NMIBC). PLoS ONE. 2020;15(3):e230417.
Lotan Y, Bivalacqua TJ, Downs T, et al. Blue light flexible cystoscopy with hexaminolevulinate in non-muscle-invasive bladder cancer: review of the clinical evidence and consensus statement on optimal use in the USA - update 2018. Nat Rev Urol. 2019;16(6):377–86.
Reis LO. Non-muscle invasive bladder cancer (NMIBC): boiling arena and promissory future. World J Urol. 2019;37(10):1999–2000.
Roupret M, Neuzillet Y, Pignot G, et al. French ccAFU guidelines - Update 2018–2020: Bladder cancer. Prog Urol. 2019;28(S1):R48–80.
Tipirneni KE, Rosenthal EL, Moore LS, et al. Fluorescence Imaging for Cancer Screening and Surveillance. Mol Imaging Biol. 2017;19(5):645–55.
Wolfs J, Hermans T, Koldewijn EL, et al. Novel urinary biomarkers ADXBLADDER and bladder EpiCheck for diagnostics of bladder cancer: A review. Urol Oncol. 2021;39(3):161–70.
Lee EJ, Lee SJ, Kim S, et al. Interleukin-5 enhances the migration and invasion of bladder cancer cells via ERK1/2-mediated MMP-9/NF-kappaB/AP-1 pathway: involvement of the p21WAF1 expression. Cell Signal. 2013;25(10):2025–38.
Fu X, Liu Z, Zhu C, et al. Nondigestible carbohydrates, butyrate, and butyrate-producing bacteria. Crit Rev Food Sci Nutr. 2019;59(sup1):130–52.
Sun Q, Cheng L, Zeng X, et al. The modulatory effect of plant polysaccharides on gut flora and the implication for neurodegenerative diseases from the perspective of the microbiota-gut-brain axis. Int J Biol Macromol. 2020;164:1484–92.
Si H, Yang Q, Hu H, et al. Colorectal cancer occurrence and treatment based on changes in intestinal flora. Semin Cancer Biol. 2021;70:3–10.
Wu P, Zhang G, Zhao J, et al. Profiling the Urinary Microbiota in Male Patients With Bladder Cancer in China. Front Cell Infect Microbiol. 2018;8:167.
Thomas-White KJ, Kliethermes S, Rickey L, et al. Evaluation of the urinary microbiota of women with uncomplicated stress urinary incontinence. Am J Obstet Gynecol. 2017;216(1):51–5.
Qiu Y, Gao Y, Chen C, 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(2):511–21.
Yan H, Li J, Ying Y, et al. MIR-300 in the imprinted DLK1-DIO3 domain suppresses the migration of bladder cancer by regulating the SP1/MMP9 pathway. Cell Cycle. 2018;17(24):2790–801.
Mondal S, Adhikari N, Banerjee S, et al. Matrix metalloproteinase-9 (MMP-9) and its inhibitors in cancer: A minireview. Eur J Med Chem. 2020;194:112260.
Luo KW, Wei C, Lung WY, et al. EGCG inhibited bladder cancer SW780 cell proliferation and migration both in vitro and in vivo via down-regulation of NF-kappaB and MMP-9. J Nutr Biochem. 2017;41:56–64.
Shin SS, Hwang B, Muhammad K, et al. Nimbolide Represses the Proliferation, Migration, and Invasion of Bladder Carcinoma Cells via Chk2-Mediated G2/M Phase Cell Cycle Arrest, Altered Signaling Pathways, and Reduced Transcription Factors-Associated MMP-9 Expression. Evid Based Complement Alternat Med, 2019, 2019: 3753587.

No competing interests reported.

SupplementaryData.docx

Download PDF

Version 1

posted

You are reading this latest preprint version

Urinary Eubacterium sp. CAG:581 promotes non-muscle-invasive bladder cancer (NMIBC) development through ECM1/MMP9 pathway

Status:

Version 1

Abstract

Figures

Introduction

Materials And Methods

Clinical Cohorts Design and Specimens

Metagenome Sequencing

NMIBC organoids cocultured with urinary bacterium in the 2-chamber culture system

RNA-seq and Data Processing

Western Blotting

Adenoviral shRNA Infection of NMIBC organoids

Statistical Analysis

Results

Discussion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1