Search PubMed⌕ Search
Home/Archive/PubMed

PubMed · 42491241

Induction and characterization of neoplastic bladder tumors in a transgenic porcine model.

Andreas Aulitzky·Viranda H Jayalath·Abraham Meyerson·Sanaz Firouzi·Daniel V Rodriguez·Rebecca Dubrovsky·Laura Alvim·Caoimhe Ryan·Rand Wilcox Vanden Berg·Christopher Cheleuitte-Nieves·Alexandre Doudt·Lennert Eismann·Natasha Kudinova·Kwanghee Kim·Hikmat Al-Ahmadie·Sebastien Monette·Shahrokh F Shariat·Jonathan A Coleman
View original source ↗Export metadata ↓

Abstract

BACKGROUND: Large animal models of bladder cancer are lacking. OBJECTIVE: This study aimed to develop and characterize a transgenic porcine model of bladder cancer (BC) using Oncopigs expressing Cre-inducible KRASG12D and TP53R167H mutations. METHODS: Eleven female Oncopigs underwent tumor induction via three cystoscopic inoculation procedures: Procedure I (N = 3, 1 inoculation/pig), chemical dissolution of the glycosaminoglycan layer with N-Dodecyl-β-d-Maltoside DDM followed by adenoviral Cre-recombinase (AdCre) instillation; Procedure II (N = 4, 3 inoculation/pig), mechanical mucosal denudation followed by AdCre instillation; and Procedure III (N = 4, 3 inoculation/pig), cystoscopy-guided submucosal injection of AdCre. Animals were clinically monitored throughout follow-up (14-28 days). Tumor development was assessed on cystoscopy and ultrasonography, and pathologically, immunohistochemically (IHC), and genomically characterized. RESULTS: All pigs remained clinically healthy. Tumors developed at 59% (16/27) of inoculation sites: nine (33%) were neoplastic and seven (26%) were inflammatory. Procedure I achieved 100% neoplastic tumors and produced both non-muscle invasive (71%) and muscle-invasive (29%) tumors. Procedure II achieved 50% neoplastic tumors, all of which were muscle invasive (100%). Procedure III generated only inflammatory tumors. Histologically, neoplastic tumors were pathologically interpreted as urothelial cell carcinomas with sarcomatoid differentiation, with IHC confirming the presence of both epithelioid and sarcomatoid features with abundant mixed leukocytic infiltrates. Genomic analyses verified Cre-induced alterations alongside other mutations seen in human BC. CONCLUSIONS: We herein demonstrate an efficient and reproducible method for developing autochthonous neoplastic bladder tumors in Oncopigs that resemble human bladder cancer of varying stages. This large animal model facilitates the evaluation of novel surgical and intravesical therapies in BC.

Explore related subjects

bladder cancerneoplastic cell transformationoncopigswinetransgenic animalsviral cell transformationJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Andreas Aulitzky, Viranda H Jayalath, Abraham Meyerson, Sanaz Firouzi, Daniel V Rodriguez, Rebecca Dubrovsky, Laura Alvim, Caoimhe Ryan, Rand Wilcox Vanden Berg, Christopher Cheleuitte-Nieves, Alexandre Doudt, Lennert Eismann, Natasha Kudinova, Kwanghee Kim, Hikmat Al-Ahmadie, Sebastien Monette, Shahrokh F Shariat, Jonathan A Coleman. 2026-07-16. Induction and characterization of neoplastic bladder tumors in a transgenic porcine model.. https://doi.org/10.1177/23523735261439691

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2026

Nonmuscle-Invasive Recurrence and Management During Surveillance in Patients with Muscle-Invasive Bladder Cancer Who Achieve Clinical Complete Response to Neoadjuvant Chemotherapy.

PURPOSE: Many patients are medically unfit for or refuse radical cystectomy. Few postchemotherapy bladder-sparing active surveillance programs have reported on nonmuscle-invasive recurrences and treatment outcomes. In this study, we present data on nonmuscle-invasive recurrences and their management in this population. MATERIALS AND METHODS: This is a retrospective review of a prospectively maintained database. All patients received cisplatin-based neoadjuvant chemotherapy and were determined to have a clinical complete response (cCR) based on negative endoscopic resection, urine cytology, and cross-sectional imaging. Patient data were entered into a strict active surveillance protocol. Primary outcomes of interest were number of nonmuscle-invasive recurrences, grade and stage, and treatment. Secondary outcomes of interest were nonmuscle-invasive treatment response rate and muscle-invasive and metastatic recurrence rate. RESULTS: A total of 61 cCR patients were identified. In total, 28 patients experienced a median of 1 nonmuscle-invasive recurrence over a median follow-up of 28.3 months. There were a total of 46 nonmuscle-invasive recurrences, including 9 (20%) low-grade recurrences and 37 (80%) high-grade recurrences. Of the 37 high-grade recurrences, the majority (60%) were treated with Bacillus Calmette-Guérin induction. Nonmuscle-invasive recurrence was not associated with later muscle-invasive recurrence or metastasis. Genomic analysis of paired tumor samples demonstrated clonal relatedness in one patient sample while another sample demonstrated a likely precancerous urothelial field effect. CONCLUSIONS: There is a high rate of nonmuscle-invasive recurrences in patients who achieve cCR to neoadjuvant chemotherapy. However, most of these patients may be safely managed with bladder-preserving treatments. These findings emphasize the importance of vigilant surveillance protocols and appropriate patient selection.

bladder cancer↗
PubMed2026

SurvGRN: a multi-feature fusion framework for bladder cancer survival prediction.

Bladder cancer survival outcomes exhibit significant heterogeneity, influenced by multifaceted factors. While digital pathology-based survival models leveraging artificial intelligence show promise, they often overlook complementary data sources. Conversely, imaging lacks cellular detail, and genomics/proteomics entail complexity and cost. To integrate multidimensional data for enhanced survival prediction, we propose SurvGRN, a multi-feature fusion framework. SurvGRN synergistically combines clinical variables, transcriptomics, and digital pathology slides using a gated residual network architecture. Pathological features are extracted via multiple instance learning, while clinical and transcriptomic data are processed as static inputs. These features are dynamically fused using a long short-term memory (LSTM) network for comprehensive survival risk assessment. Evaluated on 400 bladder cancer patients, SurvGRN significantly outperformed existing methods: improving the C-index by 12.6% over DeepMISL; 20.6% and 7.1% over graph-based models (DeepGraphConv and Patch-GCN); and 5.4% and 4.0% over attention-based approaches (Surformer and HVTSurv). Ablation studies confirmed the contributions of pathology features (extracted via ResNet-50 pre-trained on bladder tissue), clinical/transcriptomic data, and the LSTM fusion. SurvGRN also enabled significant stratification of patients into distinct risk cohorts. This work demonstrates that holistic integration of multi-source data through tailored fusion architectures substantially improves bladder cancer survival prediction.

bladder cancer↗
PubMed2025

Biomarker-Based Nomogram to Predict Neoadjuvant Chemotherapy Response in Muscle-Invasive Bladder Cancer.

Background/Objectives: The aim of this study was to identify response prediction and prognostic biomarkers in muscle-invasive bladder cancer (MIBC) patients undergoing neoadjuvant chemotherapy (NAC). Methods: A retrospective multicentre study including 191 patients with MIBC who received NAC previous to radical cystectomy (RC) between 1996 and 2013. Gene expression patterns were analysed in 34 samples from transurethral resection of the bladder (TURB) using Illumina microarrays. The expression levels of 45 selected differentially expressed genes between responders and non-responders to NAC were validated by quantitative PCR in an independent cohort of 157 patients. Regression analysis was used to identify predictors of downstaging and relapse. A nomogram for predicting downstaging and relapse-including clinicopathological and gene expression variables-was developed. Results: The expression levels of 1352 transcripts differed between responders and non-responders to NAC. A nomogram based on the most predictive clinical variables (age, Tis (in situ), gender, history of NMIBC, and lymphadenopathy) and genes selected following the Akaike information criterion (AIC) (CBTB16, CHMP6, DDX54, CASP8, LOR, and PLEC) was then created. In addition, a three-gene expression prognostic model to predict tumour relapse was generated. This model was able to discriminate between two groups of patients with a significantly different probability of tumour relapse (HR: 2.11; CI: 1.16-3.83, p = 0.01). Conclusions: Our nomogram based on gene expression and clinical data is a useful tool to predict downstaging and tumour relapse after NAC in MIBC patients. Further validation is warranted.

bladder cancer↗