DR-528 Computational modelling of tumour evolution and treatment resistance in prostate cancer towards personalised therapeutic strategies

This project will use computational modelling to simulate how advanced prostate cancer (PC) evolves, including the impact of different combinations of driver genetic alterations and how tumours adapt under therapy pressure. Whole genome sequencing (WGS) and RNA sequencing (RNA-seq) data from prostate cancer patient biopsies will be used to assess subclonal tumor composition and to build mathematical models of PC, and to simulate individual patient tumour progression and evolution patterns. The project aims to elucidate molecular and evolutionary determinants of aggressive disease and therapeutic resistance. Ultimately, the project aims to generate clinically relevant predictions of tumour behaviour that can inform the application of novel and existing therapeutic strategies.

Joaquin Mateo, Vall d’Hebron Institute of Oncology (VHIO), Spain