The purpose of these grants is to support the development of outstanding Canadian research scientists and clinical cancer research investigators who have demonstrated a commitment to improving the understanding and treatment of bladder cancer. Investigators may be working in basic, translational, clinical, epidemiologic, bioengineering or any other field, but must be working in a research environment capable of supporting transformational bladder cancer research.






Metastatic bladder cancer is a lethal and under-studied disease. Chemotherapy has historically been the most effective treatment for advanced bladder cancer, but long-term survival with this metastatic disease has been a rarity. Recently, new drugs including immunotherapies are showing significant promise, but only a certain portion of patients respond to these treatments. Currently, we have no reliable way of predicting who the positive responders will be.
Dr. So and his team have successfully developed 3D bladder cancer tissues through two different methods. Firstly, they established a protocol of 3D bioprinting human bladder tumor structures. They used different human bladder cancer cell lines as proof-of-principle and were able to show that these tumou rs can be kept alive for several weeks. They were also able to treat them with various chemotherapies and saw a regression in tumour size, suggesting usability of their 3D bioprinted bladder cancer model. They are collecting human tissue samples from bladder cancer patients and starting to grow tumours using this approach. Secondly, another method they established uses whole organ decellularization. In this 3D bladder cancer model, they are engineering bladder cancer models in a more complex environment. They successfully established a protocol for whole bladder decellularizaion and established re-seeding the same organ (scaffold) with human bladder cancer cell lines. They are treating them with several chemotherapy drugs to validate their 3D model. They foresee that the 3D bladder cancer models will potentially allow them to identify the most effective therapy for each patient, translating in the improvement of patient care and quality of life.