Nicoletta Colombo

Background: Complete gross resection (CGR) a key determinant of survival in advanced ovarian cancer (AOC). Preoperative imaging is used to predict residual disease (RD) and surgical complexity in the primary setting, but its performance after neoadjuvant chemotherapy (NACT) remains unclear. We evaluated the ability of computed tomography (CT)-based models in predicting RD and surgical complexity at interval debulking surgery (IDS).Methods: This multicentre retrospective cohort study included 246 patients with FIGO stage IIIC–IV AOC undergoing NACT-IDS between 2016–2021. The Memorial Sloan Kettering (MSK) CT-based predictive model for RD was applied and recalibrated. Pre- and post-NACT CT scans were independently reviewed by six radiologists for 18 predefined disease sites. Logistic regression identified radiologic and clinical predictors of RD and advanced surgical procedures.Results: CGR was achieved in 61% of patients; 35% had ≤1 cm RD, and 4% had >1 cm. The MSK model demonstrated limited discrimination for RD in the IDS setting (c-statistic 0.670). A revised model incorporating optimized age, CA-125 thresholds together with selected radiologic features improved discrimination (c-statistic 0.711). A model predicting the need for advanced surgical procedures achieved moderate performance (c-statistic 0.736). Subcapsular and perihepatic lesions were associated with diaphragm procedures; however absence on CT imaging did not preclude diaphragmatic stripping. Conclusions: MSK algorithm demonstrated limited discrimination in predicting CGR during IDS. A revised model incorporating optimized age and CA-125 thresholds improved performance. While specific CT findings may help anticipate the need for targeted surgical techniques and multidisciplinary involvement, their absence does not preclude the need for such procedures.

Pleural mesothelioma (PM) is an aggressive tumor that arises from mesothelial cells as a consequence of asbestos exposure. Despite recent therapeutic advances, the prognosis of PM remains poor, with a median overall survival typically below 18 months.Here, we investigated the association between alterations in histone post-translational modifications (PTMs) and patient survival in PM by employing state-of-the-art mass spectrometry-based epiproteomics. We profiled a cohort of 96 primary tumors obtained at diagnosis, including a subset of 25 patients with matched pre- and post-neoadjuvant treatment samples. Patients were stratified by overall survival using a 15-month cutoff, which approximates the reported median survival for PM.Several PTMs in treatment-naïve tumors, as well as a few therapy-induced changes, showed significant differences between short- and long-survivors across the different patient groups. Hyper-acetylation of the histone H4 tail at basal level was significantly and consistently increased in patients with worse prognosis, both in the entire cohort and within individual groups, and was associated with worse overall survival in Kaplan–Meier analyses. This association was independent of clinical variables, including tumor stage, asbestos exposure, and BAP1 status, and remained significant in multivariable Cox regression models. Interestingly, increased histone H4 hyperacetylation was observed across multiple tumor types, supporting its broader relevance in cancer biology. In vitro, inhibition of histone acetyltransferases reduced PM cell viability and enhanced sensitivity to cisplatin in a synergistic manner.These findings identify histone H4 hyperacetylation as an independent prognostic biomarker in PM and highlight epigenetic modulation as a potential therapeutic avenue in PM.