Network medicine applications for prostate cancer early detection

The rationale for initiating this PhD project originated from the growing awareness, matured through my clinical and research experience, of the unmet need for more precise, accessible, and patient-tailored tools for the early detection of prostate cancer. Despite major advances in imaging, laboratory testing, and clinical management, the diagnostic pathway for prostate cancer remains complex and often dichotomous — swinging between the risks of overdiagnosis and overtreatment on one hand, and underdiagnosis of clinically significant disease on the other. During my training in radiology, I was struck by the potential of magnetic resonance imaging (MRI) to reveal subtle biological information beyond morphology, and by the parallel rise of molecular profiling techniques capable of capturing systemic signatures of disease through minimally invasive methods such as liquid biopsy. At the same time, I became increasingly interested in the emerging field of network medicine, which offers a conceptual and computational framework to integrate heterogeneous data — clinical, imaging, and molecular — to model disease as a complex system rather than a single event. This convergence of disciplines inspired the present project, Network Medicine Applications for Prostate Cancer Early Detection, which aims to design and validate integrated diagnostic pathways capable of improving the identification of clinically significant prostate cancer while reducing unnecessary procedures. The work started from a proof-of-concept study conducted within our group, where we demonstrate the feasibility of identifying MRI biomarkers, circulating microRNAs, and significant clinical data using network analysis techniques. My intention with this PhD has been to translate this integrative vision into a concrete and reproducible methodology, combining the rigor of imaging-based diagnostic protocols with the dynamic complexity of molecular and computational sciences. Ultimately, this work reflects my belief that the future of precision medicine lies in connecting different layers of information — radiological, biological, and clinical — through a systems-based approach that restores the individual patient to the centre of diagnostic decision-making.