Oncotarget

Reviews:

Insights from animal models of bladder cancer: recent advances, challenges, and opportunities

Bincy Anu John and Neveen Said _

PDF  |  HTML  |  How to cite

Oncotarget. 2017; 8:57766-57781. https://doi.org/10.18632/oncotarget.17714

Metrics: PDF 3267 views  |   HTML 5846 views  |   ?  


Abstract

Bincy Anu John1 and Neveen Said1,2,3

1Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA

2Department of Pathology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA

3Department of Urology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA

Correspondence to:

Neveen Said, email: [email protected]

Keywords: bladder cancer, animal model, xenografts, carcinogen-induced, genetically engineered mice

Received: February 15, 2017     Accepted: April 18, 2017     Published: May 09, 2017

ABSTRACT

Bladder cancer (urothelial cancer of the bladder) is the most common malignancy affecting the urinary system with increasing incidence and mortality. Treatment of bladder cancer has not advanced in the past 30 years. Therefore, there is a crucial unmet need for novel therapies, especially for high grade/stage disease that can only be achieved by preclinical model systems that faithfully recapitulate the human disease. Animal models are essential elements in bladder cancer research to comprehensively study the multistep cascades of carcinogenesis, progression and metastasis. They allow for the investigation of premalignant phases of the disease that are not clinically encountered. They can be useful for identification of diagnostic and prognostic biomarkers for disease progression and for preclinical identification and validation of therapeutic targets/candidates, advancing translation of basic research to clinic. This review summarizes the latest advances in the currently available bladder cancer animal models, their translational potential, merits and demerits, and the prevalent tumor evaluation modalities. Thereby, findings from these model systems would provide valuable information that can help researchers and clinicians utilize the model that best answers their research questions.


Creative Commons License All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 4.0 License.
PII: 17714