Using cells isolated from pleural effusion and pleural biopsy, we established an efficient 3-D culture system for generating PM and reactive mesothelial (RM) patient-derived organoids. PM-PDOs expressed a specific gene profile, preserved the histological architecture, showing markers of the parental tumor tissues and recapitulated the tumor microenvironment (e.g., macrophages and tumor lymphocytes), which is an important factor influencing responses to therapy. This approach will be useful for drug screening, contributing to a more accurate selection of therapeutic options.

Background/Objectives: The identification of coronary artery disease (CAD) high-risk individuals is a major clinical need for timely diagnosis and intervention. Many different polygenic scores (PGSs) for CAD risk are available today to estimate the genetic risk. It is necessary to carefully choose the score to use, in particular for studies on populations, which are not adequately represented in the large datasets of European biobanks, such as the Italian one. This work aimed to analyze which PGS had the best performance within the Italian population. Methods: We used two Italian independent cohorts: the EPICOR case–control study (576 individuals) and the Atherosclerosis, Thrombosis, and Vascular Biology (ATVB) Italian study (3359 individuals). We evaluated 266 PGS for cardiovascular disease risk from the PGS Catalog, selecting 51 for CAD. Results: Distributions between patients and controls were significantly different for 49 scores (p-value < 0.01). Only five PGS have been trained and tested for the European population specifically. PGS003727 demonstrated to be the most accurate when evaluated independently (EPICOR AUC = 0.68; ATVB AUC = 0.80). Taking into account the conventional CAD risk factors further enhanced the performance of the model, particularly in the ATVB study (p-value = 0.0003). Conclusions: European CAD PGS could have different risk estimates in peculiar populations, such as the Italian one, as well as in various geographical macro areas. Therefore, further evaluation is recommended for clinical applicability.

Pleural mesothelioma (PM) is a lethal cancer primarily caused by asbestos exposure. Not all exposed individuals develop PM, suggesting the involvement of additional factors. This underscores the need for robust predictive models integrating biomarkers from multi‐omic domains to improve risk stratification and early detection. We developed and evaluated polygenic risk scores (PRS) and methylation risk scores (MRS) using a retrospective case–control study (749 participants: 387 PM cases, 362 controls) and a nested case–control European Prospective Investigation into Cancer and Nutrition (EPIC)‐Meso study (268 participants: 134 preclinical PM cases, 134 matched controls) within the EPIC cohort. Genome‐wide association analyses in the retrospective case–control study identified PM‐associated variants. The PRS (1123 SNPs with p < 0.001) in the retrospective training subset stratified disease risk in the test set (ORs 3.46–9.54 across top percentiles) and improved model discrimination (AUC = 0.75 vs. 0.71 in baseline model, p = 0.04). In EPIC‐Meso, PRS performance was limited (AUC = 0.52). External validation in the UK‐Biobank (UKBB) confirmed a modest but consistent association with PM‐risk. A Meta‐PRS derived from the UKBB‐FinnGen meta‐analysis replicated this trend in the full retrospective dataset, showing higher OR across top percentiles (2.5–12.3) and improved discrimination (AUC 0.74 vs. 0.72, p = 0.016). MRS, with 68 differentially methylated CpGs (effect‐size >|0.10|, FDR p < 0.05) in the retrospective training set, increased the AUC from 0.66 to 0.85 ( p < 0.001) in the test set and from 0.51 to 0.62 in EPIC‐Meso. PRS was most predictive in low‐exposure groups, while MRS remained robust across exposure levels. Combined PRS‐MRS models improved discrimination. Integrating multi‐omic biomarkers can enhance PM‐risk stratification and support earlier, targeted interventions in high‐risk asbestos‐exposed groups.

A minority of asbestos-exposed individuals develop Pleural mesothelioma (PM), suggesting a role for inherited genetic factors. We performed germline whole-exome sequencing of blood from 127 EPIC participants who developed PM and controls. Rare pathogenic/likely pathogenic variants were assessed in 193 cancer-associated genes and were evaluated for association with PM risk and overall survival. Exome-wide gene-based rare-variant aggregation analyses were performed using SKAT-O and Firth logistic regression. A PM polygenic risk score (PRS) was integrated with PTV status and asbestos exposure. PTVs were enriched in cases and associated with increased PM risk (OR=3.5, 95% CI 1.3–11.2, p-value = 0.01). PTV carriers had improved survival and lower mortality after adjustment for age at diagnosis and sex (HR=0.54, 95% CI 0.32–0.92, p-value = 0.023). PTV carriers had lower PRS values, and among individuals with low asbestos exposure, they were associated with increased PM risk (OR=5.75, 95% CI 1.09–58.2, p-value = 0.023). Gene-based analyses identified four novel loci. Rare variants and polygenic background may jointly influence PM risk, however validation in larger cohorts is warranted.