Prognostic biomarkers for Renal Cell Carcinoma
In this project, Maastricht University and MDxHealth have joined forces to identify DNA methylation biomarkers that can be used to discover renal cancer in an early stage, and that can also be used to identify patients with a poor prognosis. These biomarkers can, after validation, be incorporated in a molecular test that can be used in clinical practice.
Renal cell carcinoma (RCC) is the most prevalent kidney cancer, responsible for 90-95% of all cases, and the incidence rates have been rising with 2% per year over the past two decades. The 5-year survival rate of RCC confined to the kidney is 93%, whereas the 5-year survival of distant metastasised RCC is decreased to 13%. Globally, 3.3 million disability-adjusted life-years were estimated for RCC in 2017, and the disease burden has not decreased over the past 30 years despite advancements in RCC management. Early detection of RCC and accurate identification of patients at high risk of a poor outcome are the key to a higher survival rate in RCC. By improving diagnostic procedures and risk-stratification in RCC, diagnostic and prognostic biomarkers could reduce both health- and economic burden not only by directly replacing costly and unpleasant imaging procedures, but also by avoiding unnecessary surgeries and optimising subsequent medical follow-up.
To overcome the current clinical challenges in RCC, we aimed to identify and validate diagnostic and prognostic DNA methylation biomarkers in tissue and urine. These biomarkers could be used in a molecular test for RCC that complements the currently used tools for diagnostics and risk classification.
Within this project, we have shown that molecular testing of urine of RCC patients is feasible and can be used for biomarker testing in renal cancer. In addition, we have been able to develop both a diagnostic biomarker model and a prognostic biomarker model that shows promise for clinical translation. Moreover we have initiated a prospective urine biobank at MUMC+ to ensure rapid validation of biomarkers.
