Azienda Ospedaliero-Universitaria Meyer

Liver metastases (LM) are common in various types of malignant diseases, either at the diagnosis of the primary tumour or at a later time point. While the resection of colorectal LM (CRLM) is a well-established procedure, with survival rates superior to chemotherapy alone, controversial data still exist on liver resection for non-colorectal LM (NCRLM) (2, 3). These patients comprise a diverse and heterogeneous group usually excluded from surgery due to advanced tumour stage or the presence of concomitant extrahepatic disease. To date, no randomized clinical trial on the surgical treatment of NCRLM has been conducted, and only few retrospective reports are available.The scope of this research project is to develop a large registry of patients undergoing liver surgery for non-colorectal liver metastases.

The goal of this observational study is to use an artificial intelligence-based platform, integrating clinical, pathologic, imaging, genomic and transcriptomic profiles of prostate cancer in order to outperform currently available risk-stratification tools. Thus could lead to a better risk assessment of prostate cancer progression and recurrence.
A key challenge in managing non-metastatic Prostate Cancer is identifying and distinguishing between men that are likely to progress to clinically significant disease and those whose disease is likely to remain indolent for the remainder of their lifetime, aiming to offer invasive treatment only to patients harboring a disease which would affect cancer specific survival.
In the context of a multidisciplinary team of urologists and digital health experts, a two-phases study has been designed. A retrospective cohort of 200 radical prostatectomy patients will be identified within three participating clinical centres. Clinical, pathology, MRI data will be collected and stored in an appropriate anonymised online platform. Whole exome sequences (DNAseq) will be analyzed for each patients (total samples=200) and transcriptome analyses (RNAseq) for both cancer and non-cancer tissues (total samples=400). In parallel, the recruitment of a prospective cohort of 200 biopsy-proven newly PCa patients will start. For these patients, blood and urine samples will be also collected. Data will be collected and genetic analyses (total samples=1,000) will be performed as in the retrospective phase. Patients will be treated and followed according to best clinical practice.
Expected Results The retrospective phase would allow to identify genes, pathological features and MRI imaging features that can correlate with PCa biology, in order to create and train the AI-based algorithm. The prospective phase will allow the validation of the prognostic tool, the definition of a novel risk grouping and the evaluation of the prognostic role of biofluid analysis.

The study aims to explore whether a high level of AGEs (Advanced Glycation end products) derived from the diet may mediate diet-related muscle loss in Western-type diet, influencing the onset and progression of sarcopenia, predisposing to earlier and more severe metabolic consequences, including type 2 diabetes (T2D).
The primary objective of the study is to investigate how the accumulation of AGEs is correlated with muscle loss in adult patients with obesity and type 2 diabetes or lipodystrophy in order to identify possible targets to mitigate the metabolic alterations caused by the Western diet (WD). Specifically, circulating AGEs levels on the skin will be evaluated and correlated with the stage of sarcopenia in a group of patients with obesity and a T2D diagnosis. Furthermore, the relationship between disease duration and AGE levels will be assessed.
A secondary objective will be to analyze the clinical data obtained to identify metabolites and metabolic pathways responsible for the phenotype induced by the WD.
The ultimate aim of the study is therefore to verify whether high levels of AGEs are correlated with an early and/or more pronounced onset of sarcopenia, concurrently with an increase in inflammation and oxidative stress.