Work package 1

Use case: bladder cancer

What is bladder cancer?

Bladder cancer is defined as tumor development of the bladder lining and/or muscle. The risk for this type of cancer increases through contact with some chemical products, such as tobacco in cigarettes, and certain dyes and paints. In about 75% of the patients, the cancer appears to be non-muscle invasive upon first diagnosis. The primary treatment is through transurethral resection, or complete removal, of the tumor tissue.  However, in about 70% of the cases, the cancer will reoccur and in 15% of patients, it will progress into muscle invasive bladder cancer.

 

Why do we study bladder cancer in project ATHENA?

With a yearly incidence of about 2500 new cases in Belgium, bladder cancer is a commonly-diagnosed cancer type. Furthermore, it is accompanied with high mortality rates, with ca. 48% of patients not surviving past five years. In order to reduce the risk of recurrence and progression, patients with non-muscle invasive bladder cancer are monitored frequently, undergoing cystoscopy examination and cytology. The costs accompanying these types of diagnostics are very high.

Due to the high variability in bladder cancer development at the molecular level, it is hard to differentiate between patients who are more or less at risk for disease progression, simply based on clinical and pathological features. No accurate markers exist to differentiate between these patients in an early stage. Recently developed techniques based on next-generation sequencing have shown that there are different molecular subtypes of bladder cancer and that patients with different types also respond differently to treatment.

Project ATHENA aims to set up a multicenter platform to integrate relevant data from patients with non-muscle invasive bladder cancer. Information will include clinical and omics data, both collected preserving the patients’ privacy. Through state-of-the-art machine learning processes, our researchers will be able to link disease outcome and treatment response to certain biomarkers, which can then be used to improve early diagnosis and personalized treatment strategies.

 

Which concrete steps does this work package entail?

In this work package, KU Leuven, UGent and Janssen will set up a generic and standardized data collection system, based on patient records form all participating hospitals. Cancer tissue will be collected from patients at different stages of disease progression and treatment, and will be analyzed using different state-of-the-art techniques, such as comprehensive genomic profiling and immunological assays. This can provide us with possible biomarkers that indicate treatment suitability and disease outcome.

 

What are our goals?

The dataset generated during this work package and the analyses performed, will allow us to:

  • Adapt current guidelines and protocols in the treatment of non-muscle invasive bladder cancer, based on the individual patient’s risk assessment, leading to improved prognosis and patient survival rates;
  • Personalize the risk assessment of the individual patient by assessing novel biomarkers, thereby reducing the cost of frequent patient monitoring;
  • Study the disease in greater detail, allowing researchers to identify novel targets for therapy;
  • Use the strategy found optimal for bladder cancer as a lead in developing similar networks and platforms for other diseases.
     

Active partners

az groeninge | VznkuL

Universiteit Gent | Extreme | A Horizon 2020 Project