Recent studies have demonstrated the presence of clonal diversity in prostate cancer and highlighted the difficulties in designing diagnostic and therapeutic strategies based on morphological evaluation and single-sample biopsies. We propose an in-depth characterization of the tumour clonal architecture through deep-sequencing the state-of-the-art- quantitative proteomics. We will develop mathematical models to gain a mechanistic understanding of clone-specific lesions and predict personalized drug therapies based on individual molecular profiles.