Andrea Russo

Background: Multiparametric MRI is central to detecting clinically significant prostate cancer (csPCa), but diagnostic accuracy depends on reader experience. Artificial intelligence (AI) tools may support prostate MRI interpretation and reduce inter-reader variability. This study compared the detection rate of a trial, non-commercial version an AI-based software (PAROS) with that of an experienced radiologist. Methods: This retrospective single-center study included 150 patients who underwent prostate MRI followed by combined systematic and MRI-targeted transperineal biopsy. MRI examinations were interpreted by an experienced radiologist according to PI-RADS v2.1 and independently analyzed using a precommercial trial version of PAROS operating on biparametric MRI. Histopathology served as the reference standard. Detection rate was evaluated using sensitivity, specificity, and positive and negative likelihood ratios (PLR and NLR) at PI-RADS thresholds ≥3 and ≥4. Results: CsPCa was present in 63.3% of patients. At both PI-RADS thresholds, PAROS and the radiologist showed comparable sensitivity and specificity, wuth extremely low NLRs, indicating excellent rule-out capability. PLRs were modest and similar at PI-RADS ≥ 3 (1.26 vs. 1.42) and 1.88 for both at PI-RADS ≥ 4. PAROS detected more lesions, particularly in the transition zone. Conclusions: PAROS achieved csPCa detection comparable to an experienced radiologist, supporting its role as a decision-support tool in prostate MRI interpretation.

Metastatic prostate cancer is a lethal disease in patients incapable of responding to therapeutic interventions. Invasive prostate cancer spread is caused by failure of the normal anti-cancer defense systems that are controlled by the tumour suppressor protein, p53. Upon mutation, p53 malfunctions. Therapeutic strategies to directly re-empower the growth-restrictive capacities of p53 in cancers have largely been unsuccessful, frequently because of a failure to discriminate responses in diseased and healthy tissues. Our studies sought alternative prostate cancer drivers, intending to uncover new treatment targets. We discovered the oncogenic potency of MDM4 in prostate cancer cells, both in the presence and absence of p53 and also its mutation. We uncovered that sustained depletion of MDM4 is growth inhibitory in prostate cancer cells, involving either apoptosis or senescence, depending on the cell and genetic context. We identified that the potency of MDM4 targeting could be potentiated in prostate cancers with mutant p53 through the addition of a first-in-class small molecule drug that was selected as a p53 reactivator and has the capacity to elevate oxidative stress in cancer cells to drive their death.