Translational validation of first-in-class RNF31 inhibitors in human ovarian cancer models

This project aims to develop a new treatment option for women with ovarian cancer through a newly established public–private partnership between the academic researchers from UMCG and Flindr Therapeutics, a Dutch biotechnology company. By combining medical research expertise with drug development know‑how, the partnership will test a promising new medicine in patient‑based cancer models. The project brings laboratory discoveries closer to real patient benefit.

Ovarian cancer is one of the most lethal cancers affecting women. In the Netherlands, more than 4,000 women are diagnosed each year, and fewer than 45% are alive five years after diagnosis. While new targeted drugs have been developed, they mainly help a small group of patients with specific genetic changes. For the large majority of patients, these drugs offer little benefit, and reimbursement for some treatments has recently been withdrawn. As a result, many women with recurrent ovarian cancer have no effective options left, creating a strong societal and economic need for new treatments that work for a broader patient group.

The project focuses on testing a new medicine that blocks a protein that helps ovarian cancer cells survive and resist treatment. Flindr and UMCG will study how this medicine works using cancer cells and tumor material donated by patients. These patient‑based models closely resemble real tumors, allowing researchers to see how cancers respond and why some patients may benefit more than others. The project also explores combining the new medicine with existing treatments to increase their effectiveness, while identifying biological signals that can help select the right patients in the future.

The project will deliver proof that this new treatment approach works in human tumor models, a clearer understanding of how it affects cancer cells and the immune system, and measurable indicators to guide future clinical studies. Together, these results will support the development of more personalized and effective treatments for ovarian cancer.