A Novel Approach to Engineering Three-dimensional Bladder Tumor Models for Drug Testing.

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Cesar Ulises Monjaras-Avila, Ana Cecilia Luque-Badillo, Jack Bacon, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4345624/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Nov, 2024 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Bladder cancer (BCa) poses a significant health challenge, particularly affecting men with higher incidence and mortality rates. Addressing the need for improved predictive models in BCa treatment, this study introduces an innovative 3D in vitro patient-derived bladder cancer tumor model, utilizing decellularized pig bladders as scaffolds. Traditional 2D cell cultures, insufficient in replicating tumor microenvironments, have driven the development of sophisticated 3D models. In the development of the in vitro bladder cancer model, muscle invasive bladder cancer patients' cells were cultured within decellularized pig bladders, yielding a three-dimensional cancer model. To demonstrate the 3D cancer model's effectiveness as a drug screening platform, the 3D models were treated with Cisplatin (Cis), Gemcitabine (Gem), and a combination of both drugs. Comprehensive cell viability assays and histological analyses illustrated changes in cell survival and proliferation. The model exhibited promising correlations with clinical outcomes, boasting an 83.3% reliability rate in predicting treatment responses. Comparison with traditional 2D cultures and spheroids underscored the 3D model's superiority in reliability, with an 83.3% predictive capacity compared to 50% for spheroids and 33.3% for 2D culture. Acknowledging limitations, such as the absence of immune and stromal components, the study suggests avenues for future improvements. In conclusion, this 3D bladder cancer model, combining decellularization and patient-derived samples, marks a significant advancement in preclinical drug testing. Its potential for predicting treatment outcomes and capturing patient-specific responses opens new avenues for personalized medicine in bladder cancer therapeutics. Future refinements and validations with larger patient cohorts hold promise for revolutionizing BCa research and treatment strategies. Biological sciences/Biotechnology Biological sciences/Cancer Health sciences/Medical research Health sciences/Oncology Health sciences/Urology Bladder cancer cancer model decellularization recellularization tissue engineering Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 INTRODUCTION Bladder cancer (BCa) is four times more prevalent in men than in women, with global incidence and mortality rates of 9.5 and 3.3 per 100,000 among men, and 2.4 and 0.9 for women, respectively [ 1 ]. In Canada, BCa ranks as the fifth most common cancer, with an estimated 13,400 new cases and 2,600 deaths in 2023 [ 2 – 3 ]. Non-muscle-invasive bladder cancer (NMIBC) constitutes 75% of all bladder tumors, characterized by preserved detrusor muscle and invasion limited to outer, mucosal, and submucosal layers. Although NMIBC generally has a favorable prognosis, its high recurrence rates contribute to its status as the most expensive cancer to treat [ 8 ]. Muscle-invasive bladder cancer (MIBC), accounting for the remaining 25% of cases, poses a greater risk of metastasis and requires more aggressive management, often involving neoadjuvant chemotherapy before radical cystectomy [ 4 – 7 ]. The challenge in BCa treatment lies in predicting the efficacy of neoadjuvant chemotherapy, as identifying chemo-sensitive cancer is intricate [ 4 – 7 ]. Without reliable predictive biomarkers, treatment decisions rely on clinical evidence and expert opinion, highlighting the critical need for personalized approaches. Although some predictive tumor models exist, they fall short in meeting all requirements. Traditional 2D cell cultures, while valuable for understanding molecular pathways, lack the complexity to predict responses to therapy effectively [ 8 – 10 ]. In contrast, 3D cultures, such as spheroids and organoids, better mimic the tumor microenvironment (TME), incorporating diverse cell types and extracellular matrices [ 11 – 12 ]. Patient-derived 3D organoids from BCa tissue exhibit promising genetic and histological correlations, proving useful for molecular investigations and preclinical drug testing, albeit with limitations in representing immune and stroma cells for immunotherapy studies [ 13 – 16 ]. Patient-derived tumor xenografts (PDTX) currently stand as the most studied predictive tumor model, offering a closer in vivo environment resembling the original tumor conditions [ 17 – 20 ]. Despite their advantages, PDTX models are labor-intensive, require substantial animal resources, and are time-consuming and expensive, limiting their application primarily to research studies. Recognizing the need for economical, reliable, and high-throughput models, this project proposes the development of a 3D in vitro patient-derived BCa tumor model. This innovative model utilizes decellularization, a biomedical engineering process isolating the extracellular matrix (ECM) of a tissue without its cells. The resulting non-immunogenic ECM scaffold can be reseeded with the host's cells, promoting migration and differentiation. By ensuring complete decellularization, this model holds promise for predicting responses to therapies in a manner that is both clinically relevant and expedient, ultimately offering a personalized and efficient preclinical platform for BCa treatment outcomes. MATERIALS AND METHODS Tissue collection Animal organ retrieval were conducted in accordance with the institutional guidelines, approved by the Institutional Review Board of UBC (Vancouver, British Columbia, Canada; protocol number A22-0119) and all methods were performed in accordance with relevant guidelines and regulations, meeting the ARRIVE guidelines. This protocol ensures compliance with ethical standards and animal welfare principles while facilitating collaboration with existing research endeavors. Prior to bladder retrieval, pigs were anesthetized by injecting Ketamine S (20mg/kg i.m.), infusing 500ml of lactated Ringer’s solution (1–4 ml/kg/h to prevent hypovolemia, followed by propofol (20–30 mg i.v. in increments). Pigs are then intubated with an endotracheal tube (5.5-6 mm internal diameter). Maintenance of anesthesia is performed by morphine (20 mg i.v.) and propagated by an infusion of propofol (6–8 ml/kg/h). For euthanasia, we inject morphine (1mg/kg i.v.) followed 10 min later by propofol (10mg/kg i.v), rocuronium (1mg/kg i.v.) and subsequent injection of potassium chloride (40mmol) unless otherwise specified by approved animal research protocols. Immediately after euthanizing the pig, the abdominal cavity was opened with a midline incision, the bladder was identified and removed. The bladder was cut into multiple small pieces for faster decellularization, that were immediately placed in cold PBS solution. Bladder decellularization by immersion Bladders were collected as described above, pieces were immersed in Dulbecco Modified Eagle Medium (DMEM) (Fisher Scientific, 13345364, PA, USA) with 50 nM Latrunculin B (Cayman Chemical, CAS 76343-94-7, Michigan, USA) and incubated for 120 minutes at 37ºC. After incubation, tissues were washed with dH2O, then immersed in sterile 0.6 M potassium chloride solution (Fisher Scientific, AC424090010, PA, USA) at room temperature (RT) with agitation on a shaker for 2 hours. The tissues were then immersed into sterile 1M potassium iodine solution (Sigma-Aldrich, 03124, Darmstadt, Germany) at room temperature (RT) with agitation on a shaker for 2 hours, followed by immersion in sterile dH2O at room temperature overnight. The above-described steps were considered one full cycle. Each cycle was repeated 10–12 times depending on the dimensions of the tissue to ensure proper decellularization. Finally, tissues were then incubated in DNase I (1 kU/mL; Sigma-Aldrich, D4513, MO, USA) for 120 minutes and washed in dH 2 O for 2 days with daily water changes to remove the remaining reagents. Decellularized tissue was stored at -80ºC for further work. DNA quantification Both native and decellularized tissue were cut into 25 mg pieces prior to DNA extraction procedures. The small pieces were digested individually using Proteinase K (QIAGEN, 19133, Hilden, Germany) at 56ºC with agitation until they were completely lysed. DNA was purified using the DNeasy Blood & Tissue Kit (QIAGEN, 69504, Hilden, Germany) according to the manufacturer’s instructions. Afterward, both native and decellularized tissue’s DNA extracts were quantified spectrophotometrically using NanoDrop technology (Thermo Scientific, ND-2000, MA, USA). Scanning electron microscopy A small piece of the native and decellularized bladder tissue was fixed with 4% paraformaldehyde (Electron Microscopy Sciences, 15710, PA, USA) in 0.1 M PIPES (Sigma-Aldrich, P6757, Darmstadt, Germany), followed by a second fixation in 2.5% glutaraldehyde (Electron Microscopy Sciences, 16020, PA, USA) in 0.1 M PIPES buffer at room temperature. Subsequently, the tissue was fixed in 1% Osmium Tetroxide (OsO4) (Electron Microscopy Sciences, 19150, PA, USA) in 0.1 M PIPES buffer at pH 6.8, at room temperature. After fixation, the tissues were rinsed with double distilled water (ddH2O). After rinsing, the specimen underwent dehydration at room temperature through a graded ethanol-water series, followed by three rounds of 100% ethanol (Electron Microscopy Sciences, 15056, PA, USA). Critical point drying with CO2 (Tousimis Samdri®-795 critical point dryer) was then applied for 1 hour to ensure complete dehydration, and the specimen was mounted on an aluminum stub using sticky carbon tapes. Finally, the specimen on the stub was then coated with a thin layer of Au/Pd coating (2 nm thickness) using the Leica EM MED020 Coating (Centre for High-Throughput Phenogenomics, UBC, Vancouver, Canada). Images were recorded with a Helios NanoLab 650 Focused Ion Beam SEM (Centre for High-Throughput Phenogenomics, UBC, Vancouver, Canada). Cell culture Human urinary bladder transitional cell carcinoma (UM-UC3) were cultured in Minimal Essential Medium (MEM) (Gibco, 11095080) supplemented with 10% Fetal bovine serum (FBS) (Gibco, 12483020). All media used in this study were supplemented with 1% Antibiotic-Antimycotic (Gibco, 15240-062, ON, Canada) to prevent bacterial and fungal contamination. All cells used were cultured at 37° C in a 5% CO 2 incubator and mycoplasma contamination was tested at regular intervals for each cell line or primary cell. When cells were confluent, they were passaged by incubation at 37° C for 3–4 minutes with 0.25% trypsin (Gibco, 25200056, ON, Canada), centrifuged at 1,200 RPM for 5 minutes and resuspension in medium. Cells were stored long term in Bambanker (NIPPON Genetics, BB01, Düren, Germany) at a concentration of one million cells per mL and in liquid nitrogen. 3D cell culture (spheroids) Cells (2 x 10 4 cells/well) were mixed with 20 µl of Matrigel (Corning, 354234, ME, USA) and placed 48-well plates (one spheroids/well). After 30 minutes at 37° C the corresponding media supplemented with 10% R-Spondin1 Conditioned Medium from Cultrex HA-R-Spondin1-Fc 293T Cells (R&D Systems 3710-001-01) and 5 µM Y-27632 (Enzo, ALX-270-333-M001) were added. The cells were maintained in a humidified incubator with 5% CO2 at 37°C for 5 days before starting the treatment with fresh media daily change. Human bladder cancer tissue Human BCa tissue was obtained from the Vancouver General Hospital, Vancouver, BC. All patients provided informed consent and this study was approved by UBC Clinical Research Ethics Board Chair (Protocol #H19-00814) and all studies were performed in accordance with the Declaration of Helsinki. Tissue was washed 3 times with sterile PBS and Antibiotic-Antimycotic10% (Gibco, 15240-062, ON, Canada), then minced with a scalpel and incubated with Collagenase A (Sigma Aldrich, 10103586001) and Dispase II (Gibco, 17105-041) for 2 hours at 37° C with occasional agitation. After this, cells were filtered through a 40um cell strainer. Cells were washed with sterile 1X PBS, and then incubated for 15 minutes at 37° C with TrypLE express enzyme (Thermo fisher, 12605-028). Cells were washed once with 1X PBS and incubated for 5 minutes with 1X Red Blood Cell (RBC) Lysis Buffer (ABCam, ab204733). The cellular pellet was resuspended with a mix of media REBM (Lonza, CC-3190), EMB-2 (Lonza, CC-3202) and DMEM (Gibco, 11965092) and cultured at 37° C and 5% CO 2 . In vitro bladder cancer model To create the cancer model, first decellularized bladders were cut with a punch biopsy into 5 mm diameter pieces and placed in a 6-well plate (Corning, CL-S3516, ME, USA). Tissue was placed on cell culture inserts (Fisher Scientific, 08-771, PA, USA) to create an air-liquid interface. The muscularis propria of the bladder was partially removed in order to expose the stroma for the recellularization. A total of 1.5 x 10 6 UM-UC3 cells were injected into the decellularized pig bladder, at 3 different time points (Day 0, 3 and 5). Tissues were incubated for 9 days more with corresponding growth media (3 mL of each well) at 37° C with 5% CO 2 . The media was changed for fresh media every other day. On day 14, the recellularized tissues would be fixed in 10% formalin and embedded in paraffin, and 5 µm-thick sections were obtained for H&E and immunohistochemistry (IHC) evaluations. Viability assay Cells were seeded in 96-well plates at 4000 cells/well at 37° C and 5% CO2. After 24 hours, different concentrations of drugs (Cisplatin (Cis), Gemcitabine (Gem) and combination) were added and media alone was used as a control. Cells were incubated in treatment media for 72 hours. Cell viability was measured with MTS reagent (Sigma-Aldrich, MO, USA) in 200 µl of fresh media (1:20 ratio) incubated at 37°C, in 5% CO2, and plate readings were taken at 60 minutes at 490nm (BioTek, VT, USA). Each experiment had 3 technical replicates. Luminescence assay Spheroids were evaluated for cell viability using luminescence at day 0 (pre-treatment) and day 6 (post-treatment) following the addition of 50 µL of CellTiter-Glo® 3D Cell Viability Assay (Promega, Madison, WI, G9681) to each well. The plates were then agitated on a shaker for 5 minutes and incubated for an additional 25 minutes on a rocking platform at room temperature before luminescence was measured using a Tecan Infinite M200 Luminometer. All the tests were conducted in triplicate and standard deviations were reported. Histology All tissues were fixed overnight in neutral buffered formalin (10% formalin) (Fisher Scientific, 22-046-361, PA, USA) and then transferred to 70% ethanol prior to paraffin embedding. Formalin-fixed, paraffin-embedded samples were sectioned into 5 µm thickness, placed on glass slides (Fisher Scientific, 12-550-15, USA). After the tissues were deparaffinized and dehydrated, slides were washed with distilled water, hematoxylin solution, Gill No.2 (Sigma Aldrich, GHS232, Darmstadt, Germany) for 3–5 minutes and rinsed with tap water followed by immersion in Shandon bluing reagent (Thermo Fisher, 6769001, MA, USA) for 30 seconds. The sections were again rinsed in tap water and stained with Eosin Y-solution (Millipore Sigma, 1098441000, Darmstadt, Germany) for 30 seconds. We detected apoptotic cells of the tumor model with a TUNEL staining. After dewaxing and dehydrating, paraffin sections were stained with a TUNEL assay kit (Abcam, ab206386, Cambridge, MA, USA) according to the manufacturer's instructions. For Ki-67 labelling, sections were stained with Ki-67 Monoclonal Antibody 1:1000 (eBioscience™13-5698-82). All coverslips were mounted using CitosealTM XYL (Thermo Fisher Scientific, 8312-4). The slides were then scanned with an Aperio Digital Whole Slide Scanner (Leica Biosystems). Drug treatment Drugs were selected based on current application in the clinic for BCa treatment Cis (Cisplatin Injection 100mg/100ml, Teva Standard) and Gem (Gemcitabine injection 2g/52.6m). For this study, both drugs were obtained from BC Cancer Hospital, Vancouver, British Columbia, Canada as a donation. Genetic validation Prior to DNA library preparation, samples were fragmented to a median target insert size of 200bp using the Covaris M220 focused-ultrasonicator. Sequencing libraries were constructed from 50 or 100ng of fragmented input DNA using the KAPA HyperPrep kit and IDT xGen CS adapters. Libraries were pooled and hybridized to a custom KAPA HyperDesign target capture panel spanning 60 bladder cancer-associated genes and 3000 evenly distributed SNPs. Sequencing was performed on the Illumina NovaSeq 6000 using a 2x150bp S4 kit. Analysis was performed using previously published custom in-house bioinformatic tools [ 21 ]. For DNA extracted from unfixed cells, a minimum of 5 supporting reads and a minimum VAF of 1% were required for somatic variant calling. For FFPE-derived samples, 8 supporting reads and 5% VAF were used. Statistical analysis We performed statistical analysis using Prism GraphPad software version 8. We used student – test to compare two variables. One-way ANOVAs were used for multiple comparisons, followed by Bonferroni post hoc testing or 2-way ANOVA when comparing experimental multiple groups. Quantitative data were expressed as means ± SD when relevant. P values of < 0.05 were considered statistically significant. RESULTS Bladder tissue decellularization Bladder tissue decellularization was successfully achieved in pig bladders through five cycles of immersion in salt solutions, resulting in a noticeable macroscopic color change (Fig. 1A1, B1). Histological analysis using H&E staining confirmed the preservation of the microarchitecture typical of a bladder, with intact urothelium, muscle layer, and vascular structures. Notably, all cellular components were effectively removed (Fig. 1A2, B2). Scanning electron microscopy (SEM) further validated complete cell removal, revealing an undisturbed extracellular matrix (Fig. 1C1-D2). Quantitative assessment of DNA concentration showed a significant reduction in the decellularized bladder compared to the native bladder (4.65 ng/µl vs. 213.8 ng/µl, p < 0.0001 by Student’s t-test). This indicates that more than 95% of DNA was successfully eliminated during the decellularization process (Fig. 1 E). Development of an In vitro bladder cancer model The development of an in vitro BCa model involved successful growth of UM-UC3 cells within the decellularized pig bladder, following protocol optimization for the creation of a three-dimensional cancer model. After two weeks in culture, H&E staining images revealed characteristics resembling an in vivo tumor derived from UM-UC3 cells, exhibiting dense cell growth with large nuclei and prominent nucleoli. Optimal results were achieved using an air-liquid interface technique (Fig. 2 A). Cells were injected directly into the scaffold at three different time points (Day 0, 3, and 5), enabling their proliferation and migration throughout the entire tissue. This dynamic process is visually represented in both longitudinal and transversal slides of the tissue (Fig. 2 B-C). In vitro 3D bladder cancer model as a drug screening tool To demonstrate the effectiveness of our 3D cancer model as a drug screening platform, we treated the BCa prototype with Cis, Gem, and a combination of both drugs. Subsequently, we conducted a cell viability assay and histological analyses to showcase changes in cell survival and proliferation. In 2D culture, Cis concentrations ranging from 0.1 to 100 µM, with a 72-hour exposure period, exhibited an IC50 value of 0.8783 µM (Fig. 3 A). For Gem, concentrations ranged from 0.001 to 10 µM, yielding an IC50 value of 10.57 nM (Fig. 3 B). When evaluating drug response in BCa spheroid cells exposed to drugs in 2 cycles of 72 hours each, Cis concentrations ranged from 0.5 to 200 µM, and the IC50 remained comparable to the 2D culture at 0.8389 µM (Fig. 3 C). However, Gem doses, ranging from 0.001 to 1 µM, resulted in an IC50 almost four times higher than in 2D culture, at 40.57 nM (Fig. 3 D-E). Using our developed 3D BCa model for drug testing (Fig. 4 B), we treated cells with Cis doses ranging from 0.5 to 25 µM (Fig. 4 B1) and Gem from 0.005 to 5 µM (Fig. 4 B2), over three cycles of 72 hours each. Even at low concentrations of both drugs, there was up to a 43.8% reduction in luminescence compared to the control (Fig. 4 B3). Histological analysis with H&E staining revealed a decrease in cellularity with increasing Cis dose. Ki67 staining for cell proliferation demonstrated a reduction corresponding to the increase in Cis dose. In contrast, there was a significant increase in TUNEL staining with rising Cis concentrations (Fig. 4 C). Cell viability measurements using luminescence showed a statistically significant reduction as Cis concentrations increased. Similar trends were observed with Gem alone, with statistically significant reduction in viability above 0.05 µM (Fig. 4 D). Combination treatment with both drugs, mimicking clinical usage, resulted in a significant decrease in cell viability as the combined drug dose increased (Fig. 4 E). These findings underscore the potential synergistic effect of the drug combination in our 3D BCa model. Genetic validation To assess the genomic relationship between the original tumour and our model, we performed parallel DNA sequencing of FFPE tissue taken from the original implanted tumour, and cells sampled from the model on day 7, 14 and 21. The median deduplicated depth of coverage was 625x among FFPE samples, and 654x among cell samples. Of the 17 samples profiled, all but one was negative for tumor material, suggesting a selective propagation of benign supportive cells during passaging outside the model. However, samples derived from patient Px_14 did contain detectable somatic alterations that increased in allele frequency in a stepwise manner from time point 7 to 21 (Fig. 5 ). Detected mutations were 100% concordant with the source material from the patients’ original tumour. Human bladder cancer model for drug testing We acquired tumor samples from 17 patients with BCa, encompassing both NMIBC) and MIBC cases (Table 1). Utilizing early passages of patient tumor cells, we successfully developed a 3D cancer model using a decellularized pig bladder as a scaffold, and subsequently subjected it to genetic validation (Fig. 5 ). The recreation of tumors from all 17 samples demonstrated varying results in terms of the number and distribution of cells within the scaffold. Out of the 17 samples, 13 were identified as MIBC, and these were treated with Cis and the combination of Cisplatin and Gemcitabine (Cis/Gem). Notably, a positive response to the drug combination was observed in 3 patients (Fig. 6 A), while the remaining patients did not exhibit a response (Fig. 6 B). A positive correlation in treatment response was identified in 5 out of the 6 patients, providing an 83.3% reliability rate in our BCa model. Histological confirmation of the results was evident in the viability assay. A representative patient responding to therapy displayed a decrease in cells in the H&E stain when treated with Cis and Cis/Gem, accompanied by an increase in TUNEL positive cells (Fig. 6 C). Conversely, a representative patient with no drug response showed similar cellularity in the H&E stain (Fig. 6 D). These findings underscore the potential utility of our 3D BCa model in predicting treatment responses and validating them against clinical outcomes. 2D and 3D human bladder cell cultures Using human BCa cells from the 6 patients with clinical outcomes, we conducted a comparative analysis of the response to Cis and Cis/Gem treatment in 2D culture, spheroids, and our 3D model. Early passages of patient cells were cultured with varying concentrations of Cis, ranging from 0 to 10 µM for 2D culture and 0 to 200 µM for spheroids. The drug dose-response curves exhibited a statistically significant decrease in cell viability in all patients when increasing the Cis dose for both models (Fig. 7 A-B). In the case of Cis/Gem combination treatment at low doses, anticipating a synergistic effect, a significant decrease in cell viability was observed with increasing Cis dose in all patients (Fig. 7 C). A similar response was noted with Cis/Gem, with the exception of one patient who did not exhibit a significant reduction in cell viability (Fig. 7 D). To assess the reliability of our BCa model, treatment responses were compared with clinical outcomes in 6 patients (Table 2). Unfortunately, data from other patients were not available due to therapy refusal, incomplete follow-up, or other reasons. When comparing the results across different models, our 3D model demonstrated higher reliability at 83.3%, as compared to spheroids at 50%, and 2D culture at 33.3%. These findings underscore the enhanced predictive capacity and utility of our 3D BCa model in assessing treatment responses compared to traditional 2D culture and spheroid models. Discussion and conclusion The comprehensive study presented here introduces a 3D in vitro patient derived BCa tumor model as a novel platform for drug screening. BCa poses a significant global health burden, and despite advancements in treatment, predicting the efficacy of neoadjuvant chemotherapy remains a challenge. The study ingeniously addresses this challenge by leveraging the benefits of 3D culture systems, specifically utilizing decellularized pig bladders as scaffolds to create a more clinically relevant microenvironment. Since Eiraku et al. successfully generated cerebral cortex tissue from ESCs utilizing the 3D aggregation culture method in 2009, marking a pioneering endeavor in organoid research, there has been a growing recognition of the significance of developing in vitro cell models that more accurately mimic the complex cellular configurations found in native tissue [ 22 ]. Numerous researchers have successfully developed cancer organoid models derived from tumor patients. These three-dimensional (3D) models effectively recapitulate the histopathology, as well as genetic and transcriptional profiles of tumors. However, a notable limitation is the absence of the immune system and stromal components. This limitation becomes particularly pronounced when studying interactions between tumor cells and stromal or immune cells [ 16 , 23 – 24 ]. Studies conducted with BCa organoids demonstrate a high degree of reliability in detecting mutated genes, such as PIK3CA, FGFR3, EGFR, HRAS, PTEN, MDM2, RB1, and TP53. However, the response to treatment appears heterogeneous, with reduced chemotherapeutic sensitivity compared to 2D culture systems [ 25 – 27 ]. This suggests the influence of both direct and indirect cell-cell interactions within the complex organotypic 3D culture. Conversely, it may also indicate limitations in terms of drug accessibility to the cells. On the other hand, patient-derived xenograft models (PDXs) effectively recapitulate the original cancer's tissue structure and preserve its genetic and histological characteristics [ 28 ]. Despite these advantages, PDXs present several drawbacks. Establishing a PDX model is associated with a relatively low success rate, averaging between 30–40%, and demands a considerable amount of time, ranging from 2 to 10 months. Moreover, the creation and maintenance of PDX models entail significant financial costs and resource investments, which may limit statistical power and hinder the feasibility of high-throughput studies [ 29 – 31 ]. Given the limitations discussed above regarding current cancer models, we decided to integrate a natural extracellular matrix (ECM) into our approach. This ECM is capable of mimicking the microarchitecture of native tissue using innovative tissue engineering methodologies [ 32 – 33 ]. The success in decellularizing pig bladders and recreating the tumor microenvironment (TME) within these scaffolds demonstrates a sophisticated approach to capturing the complexities of BCa. The resulting 3D model better represents in vivo conditions compared to traditional 2D cultures. As we can see how in our model with UM-UC3 cells they preserver the histology [ 34 ] displaying dense cellular proliferation characterized by enlarged nuclei and prominent nucleoli, without necessity of in vivo experiments. After establishing a protocol with a BCa cell line, we treated our models with the first line of treatment for BCa [ 35 ], and the result demonstrate a correlation between cell viability with drug dose. The comparative analysis with traditional 2D cultures and spheroids highlights the superiority of the 3D model. The enhanced reliability (83.3%) of the 3D model compared to spheroids (50%) and 2D culture (33.3%) underscores the importance of incorporating three-dimensional structures for more accurate drug screening. Cancer cell lines are preferred over animal models for cancer research because they are faster, affordable, and easy to access. They are extensively employed in multiples cancer types as a preclinic platform for drug testing. Genetic data and drug sensitivity profiles are available in databases like COSMIC and CCLE proving all the valuable information we can get for 2D culture a cell line [ 35 – 36 ]. However, there are disadvantages associated with cell line use. Prolonged in vitro culture can lead to genetic and epigenetic changes diverging from the original tumors. Synthetic culture conditions and the absence of a supportive 3D environment can influence cell behavior. Moreover, cell lines often fail to accurately predict drug efficacy in clinical settings [ 37 – 38 ]. Organoids have been used as a preclinical platform for predicting response to chemotherapy in different cancer types with an heterogenous accuracy in comparation with clinical response. The TUMOROID study, which represents the most extensive prospective clinical investigation to date regarding the predictive potential of human organoids for treatment response, enrolled 61 patients diagnosed with colorectal cancer. Organoids derived from metastatic colorectal cancer (CRC) were employed in this study to correlate their response with corresponding clinical outcomes. The organoids predicted the response to irinotecan-based therapies in over 80% of patients, without misclassifying individuals who exhibited positive responses to the treatment. However, this predictive capability was not observed for combined 5-fluorouracil (5-FU) and oxaliplatin treatment. The study reported a 63% success rate in establishing in vitro cultures from patient tissue, with only 29 out of 61 patients (~ 47%) yielding evaluable responses and achieving an 80% prediction rate [ 39 ]. Yao et al. treated 80 organoids derived from human colon cancer cells with neoadjuvant chemoradiation (5-FU and irinotecan) demonstrating a sensitivity of 78.01% and specificity of 91.97%. The responses to chemoradiation observed in patients closely corresponded to those in the organoids, with an accuracy of 84.43%. These findings suggest that patient-derived organoids (PDOs) can effectively predict responses of locally advanced rectal cancer (LARC) patients in the clinical setting and may serve as a valuable companion diagnostic tool in rectal cancer treatment [ 40 ]. However, the reliability of organoid treatment response compared to clinical outcomes varies among different cancer types. For instance, in the study by Kim et al., patient-derived cancer cells (PDCs) were generated from 77 individuals with advanced lung adenocarcinoma, achieving a success rate of only 24% [ 41 ]. Predicting response for drugs in BCa have been tested with organoid with not very solid results. Bladder cancer organoids underwent sensitivity testing to various chemotherapeutic agents (epirubicin, mitomycin C, gemcitabine, vincristine, doxorubicin, or cisplatin), yet no significant correlations with patient response were identified [ 15 ]. Another investigation adopted a drug screening strategy employing bladder cancer organoids, revealing robust but variable responses. For instance, in some organoids derived from patients harboring FGFR3 activating mutations, MEK/ERK inhibition proved effective, although not universally. Correlations emerged between more aggressive clinical phenotypes (such as metastasis and recurrence) and resistance to a broad spectrum of drugs in organoids [ 42 ]. Additionally, apart from organoids, various other in vitro 3D cultures have been explored and documented. For instance, Amaral et al. [ 43 ] described a hanging drop method and a floating method utilizing ultra-low attachment (ULA) plates. The drug sensitivity of bladder cancer cells using these techniques is comparable to that observed with patient-derived xenografts. After reviewing the aforementioned studies in BCa aimed at developing preclinical models for drug testing, it is evident that this area of research remains ongoing, and continued efforts are necessary to advance towards personalized medicine. To establish the most reliable model, it is required not only to retain the specific genetic characteristics of the patient but also to recreate a microenvironment that closely mimics the original tumor environment. This includes incorporating components such as the ECM, cancer cells, cancer-associated fibroblasts (CAFs), immune cells, and vasculature to achieve a more physiologically relevant model for drug screening and therapeutic development. The inclusion of patient-derived tumor samples further enhances the model's clinical relevance. The successful recreation of tumors from 17 patient samples, with varying responses to drug treatments, strengthens the potential utility of the 3D model in personalized medicine. The positive correlation observed between treatment responses in the 3D model and clinical outcomes in 83.3% of the cases is a significant finding. This suggests that the developed 3D BCa model has a high predictive reliability, which is crucial for preclinical drug testing. Challenges and Future Directions: While the 3D model successfully captures the cellular and extracellular matrix components, it is acknowledged that immune and stromal components, critical for immunotherapy studies, are not fully represented. Future modifications to incorporate these elements could further enhance the model's applicability. The study's reliability assessment is based on a limited number of patient samples. Extending the validation to a larger cohort of patients will strengthen the model's predictive capabilities and generalizability. The current study focuses on Cis and Gem, commonly used in BCa treatment. Expanding the investigation to include other clinically relevant drugs and combination therapies would provide a more comprehensive understanding of the model's utility. Delving deeper into the molecular and cellular mechanisms underlying the observed treatment responses could provide valuable insights. Understanding the specific pathways influenced by different drug combinations will contribute to refining treatment strategies. In conclusion , this study pioneers the development of a 3D BCa model with promising applications in drug screening and personalized medicine. The model's ability to recreate patient-specific responses and predict treatment outcomes marks a significant step forward in the field of BCa research. Continued advancements in this direction hold the potential to revolutionize preclinical testing, ultimately improving therapeutic outcomes for BCa patients. Declarations Acknowledgments This study received a CIHR Project grant # 401512. We would like to express our gratitude to Drs. Peter Black, Morgan Roberts, Robert Bell and Ali Reza, for their insights during the planning of the experiments. Author Contributions CUMA, AIS and CICM conceived the study and designed the experiments. CUMA and ACLB carried out the organ harvesting, cell culture, histology. CUMA was in charge of developing the 3D model. CUMA, JB and AW did the genetic validation. CUMA, AIS and CCM wrote the manuscript. All the authors read and approved the submitted manuscript. Competing interests All authors declare no financial or non-financial competing interests. Data availability The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. References Sung, H., Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., & Bray, F. (2021). Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. 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Additional Declarations No competing interests reported. Supplementary Files Table1.pdf Table 1. Patient demographics Demographic and clinical characteristics of bladder cancer patients. Table2.pdf Table 2. Treatment response in different models. Comparison between treatment response in clinical outcome, 3D models, spheroids and 2D culture. Cochran q test. p =0.010053. 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6","display":"","copyAsset":false,"role":"figure","size":1454444,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4345624/v1/ac19d2300341be492319c6e8.jpg"},{"id":56477742,"identity":"0ce2d63b-c1bd-4c07-9282-770a769362de","added_by":"auto","created_at":"2024-05-14 17:48:58","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":915469,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4345624/v1/9f00309ca743caf274391fdb.jpg"},{"id":68750009,"identity":"7e68227f-05b1-4749-90c8-c1ecccf4aae3","added_by":"auto","created_at":"2024-11-11 16:08:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":10675699,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4345624/v1/ffd92c7b-cd53-407a-bdf4-3b6efbb369e5.pdf"},{"id":56477743,"identity":"90becc87-5423-46ea-b334-32a7a1e43045","added_by":"auto","created_at":"2024-05-14 17:48:58","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":35913,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 1. Patient demographics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDemographic and clinical characteristics of bladder cancer patients.\u0026nbsp;\u003c/p\u003e","description":"","filename":"Table1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4345624/v1/0a7109dcbfc4e32afd334c44.pdf"},{"id":56477744,"identity":"b80ce4c8-7387-493d-a6ea-f70336163427","added_by":"auto","created_at":"2024-05-14 17:48:58","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":120954,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 2. Treatment response in different models. \u003c/strong\u003eComparison between treatment response in clinical outcome, 3D models, spheroids and 2D culture. Cochran q test. \u003cem\u003ep\u003c/em\u003e=0.010053\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Table2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4345624/v1/b8d64cdfe64be972c715c38c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eA Novel Approach to Engineering Three-dimensional Bladder Tumor Models for Drug Testing.\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eBladder cancer (BCa) is four times more prevalent in men than in women, with global incidence and mortality rates of 9.5 and 3.3 per 100,000 among men, and 2.4 and 0.9 for women, respectively [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In Canada, BCa ranks as the fifth most common cancer, with an estimated 13,400 new cases and 2,600 deaths in 2023 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Non-muscle-invasive bladder cancer (NMIBC) constitutes 75% of all bladder tumors, characterized by preserved detrusor muscle and invasion limited to outer, mucosal, and submucosal layers. Although NMIBC generally has a favorable prognosis, its high recurrence rates contribute to its status as the most expensive cancer to treat [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Muscle-invasive bladder cancer (MIBC), accounting for the remaining 25% of cases, poses a greater risk of metastasis and requires more aggressive management, often involving neoadjuvant chemotherapy before radical cystectomy [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe challenge in BCa treatment lies in predicting the efficacy of neoadjuvant chemotherapy, as identifying chemo-sensitive cancer is intricate [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Without reliable predictive biomarkers, treatment decisions rely on clinical evidence and expert opinion, highlighting the critical need for personalized approaches. Although some predictive tumor models exist, they fall short in meeting all requirements.\u003c/p\u003e \u003cp\u003eTraditional 2D cell cultures, while valuable for understanding molecular pathways, lack the complexity to predict responses to therapy effectively [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In contrast, 3D cultures, such as spheroids and organoids, better mimic the tumor microenvironment (TME), incorporating diverse cell types and extracellular matrices [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Patient-derived 3D organoids from BCa tissue exhibit promising genetic and histological correlations, proving useful for molecular investigations and preclinical drug testing, albeit with limitations in representing immune and stroma cells for immunotherapy studies [\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePatient-derived tumor xenografts (PDTX) currently stand as the most studied predictive tumor model, offering a closer in vivo environment resembling the original tumor conditions [\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Despite their advantages, PDTX models are labor-intensive, require substantial animal resources, and are time-consuming and expensive, limiting their application primarily to research studies.\u003c/p\u003e \u003cp\u003eRecognizing the need for economical, reliable, and high-throughput models, this project proposes the development of a 3D in vitro patient-derived BCa tumor model. This innovative model utilizes decellularization, a biomedical engineering process isolating the extracellular matrix (ECM) of a tissue without its cells. The resulting non-immunogenic ECM scaffold can be reseeded with the host's cells, promoting migration and differentiation. By ensuring complete decellularization, this model holds promise for predicting responses to therapies in a manner that is both clinically relevant and expedient, ultimately offering a personalized and efficient preclinical platform for BCa treatment outcomes.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eTissue collection\u003c/h2\u003e \u003cp\u003e Animal organ retrieval were conducted in accordance with the institutional guidelines, approved by the Institutional Review Board of UBC (Vancouver, British Columbia, Canada; protocol number A22-0119) and all methods were performed in accordance with relevant guidelines and regulations, meeting the ARRIVE guidelines. This protocol ensures compliance with ethical standards and animal welfare principles while facilitating collaboration with existing research endeavors. Prior to bladder retrieval, pigs were anesthetized by injecting Ketamine S (20mg/kg i.m.), infusing 500ml of lactated Ringer\u0026rsquo;s solution (1\u0026ndash;4 ml/kg/h to prevent hypovolemia, followed by propofol (20\u0026ndash;30 mg i.v. in increments). Pigs are then intubated with an endotracheal tube (5.5-6 mm internal diameter). Maintenance of anesthesia is performed by morphine (20 mg i.v.) and propagated by an infusion of propofol (6\u0026ndash;8 ml/kg/h). For euthanasia, we inject morphine (1mg/kg i.v.) followed 10 min later by propofol (10mg/kg i.v), rocuronium (1mg/kg i.v.) and subsequent injection of potassium chloride (40mmol) unless otherwise specified by approved animal research protocols. Immediately after euthanizing the pig, the abdominal cavity was opened with a midline incision, the bladder was identified and removed. The bladder was cut into multiple small pieces for faster decellularization, that were immediately placed in cold PBS solution.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eBladder decellularization by immersion\u003c/h2\u003e \u003cp\u003eBladders were collected as described above, pieces were immersed in Dulbecco Modified Eagle Medium (DMEM) (Fisher Scientific, 13345364, PA, USA) with 50 nM Latrunculin B (Cayman Chemical, CAS 76343-94-7, Michigan, USA) and incubated for 120 minutes at 37\u0026ordm;C. After incubation, tissues were washed with dH2O, then immersed in sterile 0.6 M potassium chloride solution (Fisher Scientific, AC424090010, PA, USA) at room temperature (RT) with agitation on a shaker for 2 hours. The tissues were then immersed into sterile 1M potassium iodine solution (Sigma-Aldrich, 03124, Darmstadt, Germany) at room temperature (RT) with agitation on a shaker for 2 hours, followed by immersion in sterile dH2O at room temperature overnight. The above-described steps were considered one full cycle. Each cycle was repeated 10\u0026ndash;12 times depending on the dimensions of the tissue to ensure proper decellularization. Finally, tissues were then incubated in DNase I (1 kU/mL; Sigma-Aldrich, D4513, MO, USA) for 120 minutes and washed in dH\u003csub\u003e2\u003c/sub\u003eO for 2 days with daily water changes to remove the remaining reagents. Decellularized tissue was stored at -80\u0026ordm;C for further work.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDNA quantification\u003c/h2\u003e \u003cp\u003eBoth native and decellularized tissue were cut into 25 mg pieces prior to DNA extraction procedures. The small pieces were digested individually using Proteinase K (QIAGEN, 19133, Hilden, Germany) at 56\u0026ordm;C with agitation until they were completely lysed. DNA was purified using the DNeasy Blood \u0026amp; Tissue Kit (QIAGEN, 69504, Hilden, Germany) according to the manufacturer\u0026rsquo;s instructions. Afterward, both native and decellularized tissue\u0026rsquo;s DNA extracts were quantified spectrophotometrically using NanoDrop technology (Thermo Scientific, ND-2000, MA, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eScanning electron microscopy\u003c/h2\u003e \u003cp\u003eA small piece of the native and decellularized bladder tissue was fixed with 4% paraformaldehyde (Electron Microscopy Sciences, 15710, PA, USA) in 0.1 M PIPES (Sigma-Aldrich, P6757, Darmstadt, Germany), followed by a second fixation in 2.5% glutaraldehyde (Electron Microscopy Sciences, 16020, PA, USA) in 0.1 M PIPES buffer at room temperature. Subsequently, the tissue was fixed in 1% Osmium Tetroxide (OsO4) (Electron Microscopy Sciences, 19150, PA, USA) in 0.1 M PIPES buffer at pH 6.8, at room temperature. After fixation, the tissues were rinsed with double distilled water (ddH2O). After rinsing, the specimen underwent dehydration at room temperature through a graded ethanol-water series, followed by three rounds of 100% ethanol (Electron Microscopy Sciences, 15056, PA, USA). Critical point drying with CO2 (Tousimis Samdri\u0026reg;-795 critical point dryer) was then applied for 1 hour to ensure complete dehydration, and the specimen was mounted on an aluminum stub using sticky carbon tapes. Finally, the specimen on the stub was then coated with a thin layer of Au/Pd coating (2 nm thickness) using the Leica EM MED020 Coating (Centre for High-Throughput Phenogenomics, UBC, Vancouver, Canada). Images were recorded with a Helios NanoLab 650 Focused Ion Beam SEM (Centre for High-Throughput Phenogenomics, UBC, Vancouver, Canada).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCell culture\u003c/h2\u003e \u003cp\u003eHuman urinary bladder transitional cell carcinoma (UM-UC3) were cultured in Minimal Essential Medium (MEM) (Gibco, 11095080) supplemented with 10% Fetal bovine serum (FBS) (Gibco, 12483020). All media used in this study were supplemented with 1% Antibiotic-Antimycotic (Gibco, 15240-062, ON, Canada) to prevent bacterial and fungal contamination. All cells used were cultured at 37\u0026deg; C in a 5% CO\u003csub\u003e2\u003c/sub\u003e incubator and mycoplasma contamination was tested at regular intervals for each cell line or primary cell. When cells were confluent, they were passaged by incubation at 37\u0026deg; C for 3\u0026ndash;4 minutes with 0.25% trypsin (Gibco, 25200056, ON, Canada), centrifuged at 1,200 RPM for 5 minutes and resuspension in medium. Cells were stored long term in Bambanker (NIPPON Genetics, BB01, D\u0026uuml;ren, Germany) at a concentration of one million cells per mL and in liquid nitrogen.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3D cell culture (spheroids)\u003c/h2\u003e \u003cp\u003eCells (2 x 10\u003csup\u003e4\u003c/sup\u003e cells/well) were mixed with 20 \u0026micro;l of Matrigel (Corning, 354234, ME, USA) and placed 48-well plates (one spheroids/well). After 30 minutes at 37\u0026deg; C the corresponding media supplemented with 10% R-Spondin1 Conditioned Medium from Cultrex HA-R-Spondin1-Fc 293T Cells (R\u0026amp;D Systems 3710-001-01) and 5 \u0026micro;M Y-27632 (Enzo, ALX-270-333-M001) were added. The cells were maintained in a humidified incubator with 5% CO2 at 37\u0026deg;C for 5 days before starting the treatment with fresh media daily change.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eHuman bladder cancer tissue\u003c/h2\u003e \u003cp\u003eHuman BCa tissue was obtained from the Vancouver General Hospital, Vancouver, BC. All patients provided informed consent and this study was approved by UBC Clinical Research Ethics Board Chair (Protocol #H19-00814) and all studies were performed in accordance with the Declaration of Helsinki. Tissue was washed 3 times with sterile PBS and Antibiotic-Antimycotic10% (Gibco, 15240-062, ON, Canada), then minced with a scalpel and incubated with Collagenase A (Sigma Aldrich, 10103586001) and Dispase II (Gibco, 17105-041) for 2 hours at 37\u0026deg; C with occasional agitation. After this, cells were filtered through a 40um cell strainer. Cells were washed with sterile 1X PBS, and then incubated for 15 minutes at 37\u0026deg; C with TrypLE express enzyme (Thermo fisher, 12605-028). Cells were washed once with 1X PBS and incubated for 5 minutes with 1X Red Blood Cell (RBC) Lysis Buffer (ABCam, ab204733). The cellular pellet was resuspended with a mix of media REBM (Lonza, CC-3190), EMB-2 (Lonza, CC-3202) and DMEM (Gibco, 11965092) and cultured at 37\u0026deg; C and 5% CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eIn vitro bladder cancer model\u003c/h2\u003e \u003cp\u003eTo create the cancer model, first decellularized bladders were cut with a punch biopsy into 5 mm diameter pieces and placed in a 6-well plate (Corning, CL-S3516, ME, USA). Tissue was placed on cell culture inserts (Fisher Scientific, 08-771, PA, USA) to create an air-liquid interface. The muscularis propria of the bladder was partially removed in order to expose the stroma for the recellularization. A total of 1.5 x 10\u003csup\u003e6\u003c/sup\u003e UM-UC3 cells were injected into the decellularized pig bladder, at 3 different time points (Day 0, 3 and 5). Tissues were incubated for 9 days more with corresponding growth media (3 mL of each well) at 37\u0026deg; C with 5% CO\u003csub\u003e2\u003c/sub\u003e. The media was changed for fresh media every other day. On day 14, the recellularized tissues would be fixed in 10% formalin and embedded in paraffin, and 5 \u0026micro;m-thick sections were obtained for H\u0026amp;E and immunohistochemistry (IHC) evaluations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eViability assay\u003c/h2\u003e \u003cp\u003eCells were seeded in 96-well plates at 4000 cells/well at 37\u0026deg; C and 5% CO2. After 24 hours, different concentrations of drugs (Cisplatin (Cis), Gemcitabine (Gem) and combination) were added and media alone was used as a control. Cells were incubated in treatment media for 72 hours. Cell viability was measured with MTS reagent (Sigma-Aldrich, MO, USA) in 200 \u0026micro;l of fresh media (1:20 ratio) incubated at 37\u0026deg;C, in 5% CO2, and plate readings were taken at 60 minutes at 490nm (BioTek, VT, USA). Each experiment had 3 technical replicates.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLuminescence assay\u003c/h2\u003e \u003cp\u003eSpheroids were evaluated for cell viability using luminescence at day 0 (pre-treatment) and day 6 (post-treatment) following the addition of 50 \u0026micro;L of CellTiter-Glo\u0026reg; 3D Cell Viability Assay (Promega, Madison, WI, G9681) to each well. The plates were then agitated on a shaker for 5 minutes and incubated for an additional 25 minutes on a rocking platform at room temperature before luminescence was measured using a Tecan Infinite M200 Luminometer. All the tests were conducted in triplicate and standard deviations were reported.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eHistology\u003c/h2\u003e \u003cp\u003eAll tissues were fixed overnight in neutral buffered formalin (10% formalin) (Fisher Scientific, 22-046-361, PA, USA) and then transferred to 70% ethanol prior to paraffin embedding. Formalin-fixed, paraffin-embedded samples were sectioned into 5 \u0026micro;m thickness, placed on glass slides (Fisher Scientific, 12-550-15, USA). After the tissues were deparaffinized and dehydrated, slides were washed with distilled water, hematoxylin solution, Gill No.2 (Sigma Aldrich, GHS232, Darmstadt, Germany) for 3\u0026ndash;5 minutes and rinsed with tap water followed by immersion in Shandon bluing reagent (Thermo Fisher, 6769001, MA, USA) for 30 seconds. The sections were again rinsed in tap water and stained with Eosin Y-solution (Millipore Sigma, 1098441000, Darmstadt, Germany) for 30 seconds. We detected apoptotic cells of the tumor model with a TUNEL staining. After dewaxing and dehydrating, paraffin sections were stained with a TUNEL assay kit (Abcam, ab206386, Cambridge, MA, USA) according to the manufacturer's instructions. For Ki-67 labelling, sections were stained with Ki-67 Monoclonal Antibody 1:1000 (eBioscience\u0026trade;13-5698-82). All coverslips were mounted using CitosealTM XYL (Thermo Fisher Scientific, 8312-4). The slides were then scanned with an Aperio Digital Whole Slide Scanner (Leica Biosystems).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eDrug treatment\u003c/h2\u003e \u003cp\u003eDrugs were selected based on current application in the clinic for BCa treatment Cis (Cisplatin Injection 100mg/100ml, Teva Standard) and Gem (Gemcitabine injection 2g/52.6m). For this study, both drugs were obtained from BC Cancer Hospital, Vancouver, British Columbia, Canada as a donation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eGenetic validation\u003c/h2\u003e \u003cp\u003ePrior to DNA library preparation, samples were fragmented to a median target insert size of 200bp using the Covaris M220 focused-ultrasonicator. Sequencing libraries were constructed from 50 or 100ng of fragmented input DNA using the KAPA HyperPrep kit and IDT xGen CS adapters. Libraries were pooled and hybridized to a custom KAPA HyperDesign target capture panel spanning 60 bladder cancer-associated genes and 3000 evenly distributed SNPs. Sequencing was performed on the Illumina NovaSeq 6000 using a 2x150bp S4 kit. Analysis was performed using previously published custom in-house bioinformatic tools [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. For DNA extracted from unfixed cells, a minimum of 5 supporting reads and a minimum VAF of 1% were required for somatic variant calling. For FFPE-derived samples, 8 supporting reads and 5% VAF were used.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe performed statistical analysis using Prism GraphPad software version 8. We used student \u0026ndash; test to compare two variables. One-way ANOVAs were used for multiple comparisons, followed by Bonferroni post hoc testing or 2-way ANOVA when comparing experimental multiple groups. Quantitative data were expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD when relevant. P values of \u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003eBladder tissue decellularization\u003c/h2\u003e\n \u003cp\u003eBladder tissue decellularization was successfully achieved in pig bladders through five cycles of immersion in salt solutions, resulting in a noticeable macroscopic color change (Fig.\u0026nbsp;1A1, B1). Histological analysis using H\u0026amp;E staining confirmed the preservation of the microarchitecture typical of a bladder, with intact urothelium, muscle layer, and vascular structures. Notably, all cellular components were effectively removed (Fig.\u0026nbsp;1A2, B2). Scanning electron microscopy (SEM) further validated complete cell removal, revealing an undisturbed extracellular matrix (Fig.\u0026nbsp;1C1-D2).\u003c/p\u003e\n \u003cp\u003eQuantitative assessment of DNA concentration showed a significant reduction in the decellularized bladder compared to the native bladder (4.65 ng/\u0026micro;l vs. 213.8 ng/\u0026micro;l, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 by Student\u0026rsquo;s t-test). This indicates that more than 95% of DNA was successfully eliminated during the decellularization process (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eE).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003ch2\u003eDevelopment of an In vitro bladder cancer model\u003c/h2\u003e\n \u003cp\u003eThe development of an in vitro BCa model involved successful growth of UM-UC3 cells within the decellularized pig bladder, following protocol optimization for the creation of a three-dimensional cancer model. After two weeks in culture, H\u0026amp;E staining images revealed characteristics resembling an in vivo tumor derived from UM-UC3 cells, exhibiting dense cell growth with large nuclei and prominent nucleoli.\u003c/p\u003e\n \u003cp\u003eOptimal results were achieved using an air-liquid interface technique (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA). Cells were injected directly into the scaffold at three different time points (Day 0, 3, and 5), enabling their proliferation and migration throughout the entire tissue. This dynamic process is visually represented in both longitudinal and transversal slides of the tissue (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB-C).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n \u003ch2\u003eIn vitro 3D bladder cancer model as a drug screening tool\u003c/h2\u003e\n \u003cp\u003eTo demonstrate the effectiveness of our 3D cancer model as a drug screening platform, we treated the BCa prototype with Cis, Gem, and a combination of both drugs. Subsequently, we conducted a cell viability assay and histological analyses to showcase changes in cell survival and proliferation.\u003c/p\u003e\n \u003cp\u003eIn 2D culture, Cis concentrations ranging from 0.1 to 100 \u0026micro;M, with a 72-hour exposure period, exhibited an IC50 value of 0.8783 \u0026micro;M (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA). For Gem, concentrations ranged from 0.001 to 10 \u0026micro;M, yielding an IC50 value of 10.57 nM (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB). When evaluating drug response in BCa spheroid cells exposed to drugs in 2 cycles of 72 hours each, Cis concentrations ranged from 0.5 to 200 \u0026micro;M, and the IC50 remained comparable to the 2D culture at 0.8389 \u0026micro;M (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC). However, Gem doses, ranging from 0.001 to 1 \u0026micro;M, resulted in an IC50 almost four times higher than in 2D culture, at 40.57 nM (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eD-E).\u003c/p\u003e\n \u003cp\u003eUsing our developed 3D BCa model for drug testing (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB), we treated cells with Cis doses ranging from 0.5 to 25 \u0026micro;M (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB1) and Gem from 0.005 to 5 \u0026micro;M (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB2), over three cycles of 72 hours each. Even at low concentrations of both drugs, there was up to a 43.8% reduction in luminescence compared to the control (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB3). Histological analysis with H\u0026amp;E staining revealed a decrease in cellularity with increasing Cis dose. Ki67 staining for cell proliferation demonstrated a reduction corresponding to the increase in Cis dose. In contrast, there was a significant increase in TUNEL staining with rising Cis concentrations (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eC).\u003c/p\u003e\n \u003cp\u003eCell viability measurements using luminescence showed a statistically significant reduction as Cis concentrations increased. Similar trends were observed with Gem alone, with statistically significant reduction in viability above 0.05 \u0026micro;M (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eD). Combination treatment with both drugs, mimicking clinical usage, resulted in a significant decrease in cell viability as the combined drug dose increased (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eE). These findings underscore the potential synergistic effect of the drug combination in our 3D BCa model.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\n \u003ch2\u003eGenetic validation\u003c/h2\u003e\n \u003cp\u003eTo assess the genomic relationship between the original tumour and our model, we performed parallel DNA sequencing of FFPE tissue taken from the original implanted tumour, and cells sampled from the model on day 7, 14 and 21. The median deduplicated depth of coverage was 625x among FFPE samples, and 654x among cell samples. Of the 17 samples profiled, all but one was negative for tumor material, suggesting a selective propagation of benign supportive cells during passaging outside the model. However, samples derived from patient Px_14 did contain detectable somatic alterations that increased in allele frequency in a stepwise manner from time point 7 to 21 (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Detected mutations were 100% concordant with the source material from the patients\u0026rsquo; original tumour.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\n \u003ch2\u003eHuman bladder cancer model for drug testing\u003c/h2\u003e\n \u003cp\u003eWe acquired tumor samples from 17 patients with BCa, encompassing both NMIBC) and MIBC cases (Table\u0026nbsp;1). Utilizing early passages of patient tumor cells, we successfully developed a 3D cancer model using a decellularized pig bladder as a scaffold, and subsequently subjected it to genetic validation (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). The recreation of tumors from all 17 samples demonstrated varying results in terms of the number and distribution of cells within the scaffold. Out of the 17 samples, 13 were identified as MIBC, and these were treated with Cis and the combination of Cisplatin and Gemcitabine (Cis/Gem). Notably, a positive response to the drug combination was observed in 3 patients (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eA), while the remaining patients did not exhibit a response (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eB).\u003c/p\u003e\n \u003cp\u003eA positive correlation in treatment response was identified in 5 out of the 6 patients, providing an 83.3% reliability rate in our BCa model. Histological confirmation of the results was evident in the viability assay. A representative patient responding to therapy displayed a decrease in cells in the H\u0026amp;E stain when treated with Cis and Cis/Gem, accompanied by an increase in TUNEL positive cells (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eC). Conversely, a representative patient with no drug response showed similar cellularity in the H\u0026amp;E stain (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eD). These findings underscore the potential utility of our 3D BCa model in predicting treatment responses and validating them against clinical outcomes.\u003c/p\u003e\n \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\n \u003ch2\u003e2D and 3D human bladder cell cultures\u003c/h2\u003e\n \u003cp\u003eUsing human BCa cells from the 6 patients with clinical outcomes, we conducted a comparative analysis of the response to Cis and Cis/Gem treatment in 2D culture, spheroids, and our 3D model. Early passages of patient cells were cultured with varying concentrations of Cis, ranging from 0 to 10 \u0026micro;M for 2D culture and 0 to 200 \u0026micro;M for spheroids. The drug dose-response curves exhibited a statistically significant decrease in cell viability in all patients when increasing the Cis dose for both models (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eA-B). In the case of Cis/Gem combination treatment at low doses, anticipating a synergistic effect, a significant decrease in cell viability was observed with increasing Cis dose in all patients (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eC). A similar response was noted with Cis/Gem, with the exception of one patient who did not exhibit a significant reduction in cell viability (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eD). To assess the reliability of our BCa model, treatment responses were compared with clinical outcomes in 6 patients (Table 2). Unfortunately, data from other patients were not available due to therapy refusal, incomplete follow-up, or other reasons. When comparing the results across different models, our 3D model demonstrated higher reliability at 83.3%, as compared to spheroids at 50%, and 2D culture at 33.3%. These findings underscore the enhanced predictive capacity and utility of our 3D BCa model in assessing treatment responses compared to traditional 2D culture and spheroid models.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion and conclusion","content":"\u003cp\u003eThe comprehensive study presented here introduces a 3D in vitro patient derived BCa tumor model as a novel platform for drug screening. BCa poses a significant global health burden, and despite advancements in treatment, predicting the efficacy of neoadjuvant chemotherapy remains a challenge. The study ingeniously addresses this challenge by leveraging the benefits of 3D culture systems, specifically utilizing decellularized pig bladders as scaffolds to create a more clinically relevant microenvironment.\u003c/p\u003e\n\u003cp\u003eSince Eiraku et al. successfully generated cerebral cortex tissue from ESCs utilizing the 3D aggregation culture method in 2009, marking a pioneering endeavor in organoid research, there has been a growing recognition of the significance of developing in vitro cell models that more accurately mimic the complex cellular configurations found in native tissue [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e]. Numerous researchers have successfully developed cancer organoid models derived from tumor patients. These three-dimensional (3D) models effectively recapitulate the histopathology, as well as genetic and transcriptional profiles of tumors. However, a notable limitation is the absence of the immune system and stromal components. This limitation becomes particularly pronounced when studying interactions between tumor cells and stromal or immune cells [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eStudies conducted with BCa organoids demonstrate a high degree of reliability in detecting mutated genes, such as PIK3CA, FGFR3, EGFR, HRAS, PTEN, MDM2, RB1, and TP53. However, the response to treatment appears heterogeneous, with reduced chemotherapeutic sensitivity compared to 2D culture systems [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e]. This suggests the influence of both direct and indirect cell-cell interactions within the complex organotypic 3D culture. Conversely, it may also indicate limitations in terms of drug accessibility to the cells.\u003c/p\u003e\n\u003cp\u003eOn the other hand, patient-derived xenograft models (PDXs) effectively recapitulate the original cancer's tissue structure and preserve its genetic and histological characteristics [\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e]. Despite these advantages, PDXs present several drawbacks. Establishing a PDX model is associated with a relatively low success rate, averaging between 30\u0026ndash;40%, and demands a considerable amount of time, ranging from 2 to 10 months. Moreover, the creation and maintenance of PDX models entail significant financial costs and resource investments, which may limit statistical power and hinder the feasibility of high-throughput studies [\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eGiven the limitations discussed above regarding current cancer models, we decided to integrate a natural extracellular matrix (ECM) into our approach. This ECM is capable of mimicking the microarchitecture of native tissue using innovative tissue engineering methodologies [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]. The success in decellularizing pig bladders and recreating the tumor microenvironment (TME) within these scaffolds demonstrates a sophisticated approach to capturing the complexities of BCa. The resulting 3D model better represents in vivo conditions compared to traditional 2D cultures. As we can see how in our model with UM-UC3 cells they preserver the histology [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e] displaying dense cellular proliferation characterized by enlarged nuclei and prominent nucleoli, without necessity of in vivo experiments. After establishing a protocol with a BCa cell line, we treated our models with the first line of treatment for BCa [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e], and the result demonstrate a correlation between cell viability with drug dose.\u003c/p\u003e\n\u003cp\u003eThe comparative analysis with traditional 2D cultures and spheroids highlights the superiority of the 3D model. The enhanced reliability (83.3%) of the 3D model compared to spheroids (50%) and 2D culture (33.3%) underscores the importance of incorporating three-dimensional structures for more accurate drug screening.\u003c/p\u003e\n\u003cp\u003eCancer cell lines are preferred over animal models for cancer research because they are faster, affordable, and easy to access. They are extensively employed in multiples cancer types as a preclinic platform for drug testing. Genetic data and drug sensitivity profiles are available in databases like COSMIC and CCLE proving all the valuable information we can get for 2D culture a cell line [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e]. However, there are disadvantages associated with cell line use. Prolonged in vitro culture can lead to genetic and epigenetic changes diverging from the original tumors. Synthetic culture conditions and the absence of a supportive 3D environment can influence cell behavior. Moreover, cell lines often fail to accurately predict drug efficacy in clinical settings [\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]. Organoids have been used as a preclinical platform for predicting response to chemotherapy in different cancer types with an heterogenous accuracy in comparation with clinical response.\u003c/p\u003e\n\u003cp\u003eThe TUMOROID study, which represents the most extensive prospective clinical investigation to date regarding the predictive potential of human organoids for treatment response, enrolled 61 patients diagnosed with colorectal cancer. Organoids derived from metastatic colorectal cancer (CRC) were employed in this study to correlate their response with corresponding clinical outcomes. The organoids predicted the response to irinotecan-based therapies in over 80% of patients, without misclassifying individuals who exhibited positive responses to the treatment. However, this predictive capability was not observed for combined 5-fluorouracil (5-FU) and oxaliplatin treatment. The study reported a 63% success rate in establishing in vitro cultures from patient tissue, with only 29 out of 61 patients (~\u0026thinsp;47%) yielding evaluable responses and achieving an 80% prediction rate [\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e]. Yao et al. treated 80 organoids derived from human colon cancer cells with neoadjuvant chemoradiation (5-FU and irinotecan) demonstrating a sensitivity of 78.01% and specificity of 91.97%. The responses to chemoradiation observed in patients closely corresponded to those in the organoids, with an accuracy of 84.43%. These findings suggest that patient-derived organoids (PDOs) can effectively predict responses of locally advanced rectal cancer (LARC) patients in the clinical setting and may serve as a valuable companion diagnostic tool in rectal cancer treatment [\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e]. However, the reliability of organoid treatment response compared to clinical outcomes varies among different cancer types. For instance, in the study by Kim et al., patient-derived cancer cells (PDCs) were generated from 77 individuals with advanced lung adenocarcinoma, achieving a success rate of only 24% [\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003ePredicting response for drugs in BCa have been tested with organoid with not very solid results. Bladder cancer organoids underwent sensitivity testing to various chemotherapeutic agents (epirubicin, mitomycin C, gemcitabine, vincristine, doxorubicin, or cisplatin), yet no significant correlations with patient response were identified [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]. Another investigation adopted a drug screening strategy employing bladder cancer organoids, revealing robust but variable responses. For instance, in some organoids derived from patients harboring FGFR3 activating mutations, MEK/ERK inhibition proved effective, although not universally. Correlations emerged between more aggressive clinical phenotypes (such as metastasis and recurrence) and resistance to a broad spectrum of drugs in organoids [\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e]. Additionally, apart from organoids, various other in vitro 3D cultures have been explored and documented. For instance, Amaral et al. [\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e] described a hanging drop method and a floating method utilizing ultra-low attachment (ULA) plates. The drug sensitivity of bladder cancer cells using these techniques is comparable to that observed with patient-derived xenografts. After reviewing the aforementioned studies in BCa aimed at developing preclinical models for drug testing, it is evident that this area of research remains ongoing, and continued efforts are necessary to advance towards personalized medicine. To establish the most reliable model, it is required not only to retain the specific genetic characteristics of the patient but also to recreate a microenvironment that closely mimics the original tumor environment. This includes incorporating components such as the ECM, cancer cells, cancer-associated fibroblasts (CAFs), immune cells, and vasculature to achieve a more physiologically relevant model for drug screening and therapeutic development.\u003c/p\u003e\n\u003cp\u003eThe inclusion of patient-derived tumor samples further enhances the model's clinical relevance. The successful recreation of tumors from 17 patient samples, with varying responses to drug treatments, strengthens the potential utility of the 3D model in personalized medicine.\u003c/p\u003e\n\u003cp\u003eThe positive correlation observed between treatment responses in the 3D model and clinical outcomes in 83.3% of the cases is a significant finding. This suggests that the developed 3D BCa model has a high predictive reliability, which is crucial for preclinical drug testing.\u003c/p\u003e\n\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\n\u003ch2\u003eChallenges and Future Directions:\u003c/h2\u003e\n\u003cp\u003eWhile the 3D model successfully captures the cellular and extracellular matrix components, it is acknowledged that immune and stromal components, critical for immunotherapy studies, are not fully represented. Future modifications to incorporate these elements could further enhance the model's applicability. The study's reliability assessment is based on a limited number of patient samples. Extending the validation to a larger cohort of patients will strengthen the model's predictive capabilities and generalizability. The current study focuses on Cis and Gem, commonly used in BCa treatment. Expanding the investigation to include other clinically relevant drugs and combination therapies would provide a more comprehensive understanding of the model's utility. Delving deeper into the molecular and cellular mechanisms underlying the observed treatment responses could provide valuable insights. Understanding the specific pathways influenced by different drug combinations will contribute to refining treatment strategies.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn conclusion\u003c/em\u003e, this study pioneers the development of a 3D BCa model with promising applications in drug screening and personalized medicine. The model's ability to recreate patient-specific responses and predict treatment outcomes marks a significant step forward in the field of BCa research. Continued advancements in this direction hold the potential to revolutionize preclinical testing, ultimately improving therapeutic outcomes for BCa patients.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study received a CIHR Project grant # 401512. We would like to express our gratitude to Drs. Peter Black, Morgan Roberts, Robert Bell and Ali Reza, for their insights during the planning of the experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCUMA, AIS and CICM conceived the study and designed the experiments. CUMA and ACLB carried out the organ harvesting, cell culture, histology. CUMA was in charge of developing the 3D model. CUMA, JB and AW did the genetic validation. CUMA, AIS and CCM wrote the manuscript. All the authors read and approved the submitted manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no financial or non-financial competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung, H., Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., \u0026amp; Bray, F. (2021). 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Comparative Analysis of 3D Bladder Tumor Spheroids Obtained by Forced Floating and Hanging Drop Methods for Drug Screening. \u003cem\u003eFrontiers in Physiology\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e, 605. https://doi.org/10.3389/fphys.2017.00605\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 and 2 are available in the Supplementary Files section.\u003c/p\u003e "}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Bladder cancer, cancer model, decellularization, recellularization, tissue engineering","lastPublishedDoi":"10.21203/rs.3.rs-4345624/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4345624/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBladder cancer (BCa) poses a significant health challenge, particularly affecting men with higher incidence and mortality rates. Addressing the need for improved predictive models in BCa treatment, this study introduces an innovative 3D in vitro patient-derived bladder cancer tumor model, utilizing decellularized pig bladders as scaffolds. Traditional 2D cell cultures, insufficient in replicating tumor microenvironments, have driven the development of sophisticated 3D models.\u003c/p\u003e \u003cp\u003eIn the development of the in vitro bladder cancer model, muscle invasive bladder cancer patients' cells were cultured within decellularized pig bladders, yielding a three-dimensional cancer model. To demonstrate the 3D cancer model's effectiveness as a drug screening platform, the 3D models were treated with Cisplatin (Cis), Gemcitabine (Gem), and a combination of both drugs. Comprehensive cell viability assays and histological analyses illustrated changes in cell survival and proliferation. The model exhibited promising correlations with clinical outcomes, boasting an 83.3% reliability rate in predicting treatment responses.\u003c/p\u003e \u003cp\u003eComparison with traditional 2D cultures and spheroids underscored the 3D model's superiority in reliability, with an 83.3% predictive capacity compared to 50% for spheroids and 33.3% for 2D culture. Acknowledging limitations, such as the absence of immune and stromal components, the study suggests avenues for future improvements.\u003c/p\u003e \u003cp\u003eIn conclusion, this 3D bladder cancer model, combining decellularization and patient-derived samples, marks a significant advancement in preclinical drug testing. Its potential for predicting treatment outcomes and capturing patient-specific responses opens new avenues for personalized medicine in bladder cancer therapeutics. Future refinements and validations with larger patient cohorts hold promise for revolutionizing BCa research and treatment strategies.\u003c/p\u003e","manuscriptTitle":"A Novel Approach to Engineering Three-dimensional Bladder Tumor Models for Drug Testing.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-14 17:48:51","doi":"10.21203/rs.3.rs-4345624/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-09T05:25:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-08T08:23:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"147222547563258598765412022272414548673","date":"2024-07-10T02:14:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-08T18:37:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"62194158378061159662063656332032915241","date":"2024-05-16T07:43:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1737441643215281493488910486335694651","date":"2024-05-16T03:10:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-15T20:02:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-14T13:39:02+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-06T11:12:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-06T11:08:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-04-30T02:07:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"41fd41b1-a032-4d13-a368-b09d97070c23","owner":[],"postedDate":"May 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":31835970,"name":"Biological sciences/Biotechnology"},{"id":31835971,"name":"Biological sciences/Cancer"},{"id":31835972,"name":"Health sciences/Medical research"},{"id":31835973,"name":"Health sciences/Oncology"},{"id":31835974,"name":"Health sciences/Urology"}],"tags":[],"updatedAt":"2024-11-11T16:03:14+00:00","versionOfRecord":{"articleIdentity":"rs-4345624","link":"https://doi.org/10.1038/s41598-024-78440-0","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-11-06 15:58:07","publishedOnDateReadable":"November 6th, 2024"},"versionCreatedAt":"2024-05-14 17:48:51","video":"","vorDoi":"10.1038/s41598-024-78440-0","vorDoiUrl":"https://doi.org/10.1038/s41598-024-78440-0","workflowStages":[]},"version":"v1","identity":"rs-4345624","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4345624","identity":"rs-4345624","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}