Next-generation sequencing will allow us to gain an overview of the genomic landscape that correlates with aggressiveness in different tumour types such as prostate, bladder and endometrial cancer. Comparing high stage/grade tumours to low stage/grade or precursor lesions and to the surrounding healthy tissue in the same patient samples will help us identify the “driver” mutations of cancer progression and distinguish them from the “passenger” mutations that randomly accumulated during tumour development. Furthermore, employing functional genomic screening approaches (e.g. siRNA screens in cancer cell lines) we will narrow down the list of candidate genes and validate the identified targets. Our final aim is to use the gained biological knowledge for improving personalised molecular pathological diagnosis and guide the treatment of patients based on rationally chosen molecular targets specific for the patient’s individual tumour.
We also design and develop mathematical models and perform computational simulations to conduct data-driven biomedical research as well as clinical studies. Our focus is computational genomics and image-based tissue phenomics.
This project has received funding from the European Union’s Horizon 2020
research and innovation programme under grant agreement No. 668858.
Zurich / Switzerland