Bladder Cancer – Prof. Marianna Kruithof-de Julio (UNIBE) and Dr Bernhard Kiss (INSEL)

Development of AI systems to assist in staging and treatment of bladder cancer patients

Project of Prof. Marianna Kruithog-de Julio, University of Bern, and Dr. Bernhard Kiss, University of Bern

Bladder cancers (BLCA) are usually characterized as either superficial or invasive. As with all cancers, the tumor has to be staged in order to make a proper prognosis and decide on an appropriate course of treatment. Currently, bladder tumor staging depends on how deeply nested the tumor is into the bladder wall. However, recent research has shown that this may not reflect the most biologically relevant features of different forms of the disease. The aim of this collaboration is to better understand the biological behavior of bladder cancer on a molecular and cellular level in order to optimize the decision-making process for an effective course of treatment. This decision-making process is time-sensitive, as treatment must start by two weeks after the biopsy is taken.

There is a crucial need to optimize the staging process itself, as accuracy at this point will have a considerable impact on the choice of therapy and the patient’s quality of life. Both the over- and under-treatment of cancers can elicit serious problems.

The overarching goal of this TANDEM project is to explore the biological nature of BLCA through a range of advanced high-throughput molecular techniques (genomics, transcriptomics, epigenetics) combined with the monitoring of functional responses to different therapies. From this, an atlas of tumor cell types and sensitivities will be created, which will allow the researchers to generate an AI framework that should better guide BLCA patient care decisions. The collaborators bring different types of analysis together to shed light on both the tumor and its surrounding tissues (tumor microenvironment) and study the response of the BLCA to chemical inhibitors in vitro. The aim is to offer a more accurate platform for diagnosis and staging of BLCA, enabling clinicians to match patients with the most effective treatment.