Atlas-based analyses of patients with cardiovascular diseases have recently been explored to understand the mechanistic link between shape and pathophysiology. The construction of probabilistic atlases is based on statistical shape modeling (SSM) to assess key anatomic features for a given patient population. Such an approach is relevant to study the complex nature of the ascending thoracic aortic aneurysm (ATAA) as characterized by different patterns of aortic shapes and valve phenotypes. This study was carried out to develop an SSM of the dilated aorta with both bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV), and then assess the computational hemodynamic of virtual models obtained by the deformation of the mean template for specific shape boundaries (i.e., ±1.5 standard deviation, σ). Simulations demonstrated remarkable changes in the velocity streamlines, blood pressure, and fluid shear stress with the principal shape modes such as the aortic size (Mode 1), vessel tortuosity (Mode 2), and aortic valve morphologies (Mode 3). The atlas-based disease assessment can represent a powerful tool to reveal important insights on ATAA-derived hemodynamic, especially for aneurysms which are considered to have borderline anatomies, and thus challenging decision-making. The utilization of SSMs for creating probabilistic patient cohorts can facilitate the understanding of the heterogenous nature of the dilated ascending aorta.

Malignant pleural mesothelioma (MPM) is an aggressive tumor with median survival of 12 months and limited effective treatments. The scope of this study was to study the relationship between blood DNA methylation (DNAm) and overall survival (OS) aiming at a noninvasive prognostic test. We investigated a cohort of 159 incident asbestos exposed MPM cases enrolled in an Italian area with high incidence of mesothelioma. Considering 12 months as a cut-off for OS, epigenome-wide association study (EWAS) revealed statistically significant (p value = 7.7 × 10−9) OS-related differential methylation of a single-CpG (cg03546163), located in the 5′UTR region of the FKBP5 gene. This is an independent marker of prognosis in MPM patients with a better performance than traditional inflammation-based scores such as lymphocyte-to-monocyte ratio (LMR). Cases with DNAm < 0.45 at the cg03546163 had significantly poor survival compared with those showing DNAm ≥ 0.45 (mean: 243 versus 534 days; p value< 0.001). Epigenetic changes at the FKBP5 gene were robustly associated with OS in MPM cases. Our results showed that blood DNA methylation levels could be promising and dynamic prognostic biomarkers in MPM.

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Malignant pleural mesothelioma (MPM) is a rare and aggressive neoplasm. Patients are usually diagnosed when current treatments have limited benefits, highlighting the need for noninvasive tests aimed at an MPM risk assessment tool that might improve life expectancy. Three hundred asbestos-exposed subjects (163 MPM cases and 137 cancer-free controls), from the same geographical region in Italy, were recruited. The evaluation of asbestos exposure was conducted considering the frequency, the duration and the intensity of occupational, environmental and domestic exposure. A genome-wide methylation array was performed to identify novel blood DNA methylation (DNAm) markers of MPM. Multiple regression analyses adjusting for potential confounding factors and interaction between asbestos exposure and DNAm on the MPM odds ratio were applied. Epigenome-wide analysis (EWAS) revealed 12 single-CpGs associated with the disease. Two of these showed high statistical power (99%) and effect size (>0.05) after false discovery rate (FDR) multiple comparison corrections: (i) cg03546163 in FKBP5, significantly hypomethylated in cases (Mean Difference in beta values (MD) = −0.09, 95% CI = −0.12|−0.06, p = 1.2 × 10−7), and (ii) cg06633438 in MLLT1, statistically hypermethylated in cases (MD = 0.07, 95% CI = 0.04|0.10, p = 1.0 × 10−6). Based on the interaction analysis, asbestos exposure and epigenetic profile together may improve MPM risk assessment. Above-median asbestos exposure and hypomethylation of cg03546163 in FKBP5 (OR = 20.84, 95% CI = 8.71|53.96, p = 5.5 × 10−11) and hypermethylation of cg06633438 in MLLT1 (OR = 11.71, 95% CI = 4.97|29.64, p = 5.9 × 10−8) genes compared to below-median asbestos exposure and hyper/hypomethylation of single-CpG DNAm, respectively. Receiver Operation Characteristics (ROC) for Case-Control Discrimination showed a significant increase in MPM discrimination when DNAm information was added in the model (baseline model, BM: asbestos exposure, age, gender and white blood cells); area under the curve, AUC = 0.75; BM + cg03546163 at FKBP5. AUC = 0.89, 2.1 × 10−7; BM + cg06633438 at MLLT1. AUC = 0.89, 6.3 × 10−8. Validation and replication procedures, considering independent sample size and a different DNAm analysis technique, confirmed the observed associations. Our results suggest the potential application of DNAm profiles in blood to develop noninvasive tests for MPM risk assessment in asbestos-exposed subjects.

Malignant pleural mesothelioma (MPM) is an aggressive cancer with a dismal prognosis. Early therapeutic interventions could improve patient outcomes. We aimed to identify a pattern of microRNAs (miRNAs) as potential early non-invasive markers of MPM. In a case-control study nested in the European Prospective Investigation into Cancer and Nutrition cohort, we screened the whole miRNome in serum extracellular vesicles (EVs) of preclinical MPM cases. In a subgroup of 20 preclinical samples collected five years prior MPM diagnosis, we observed an upregulation of miR-11400 (fold change (FC) = 2.6, adjusted p-value = 0.01), miR-148a-3p (FC = 1.5, p-value = 0.001), and miR-409-3p (FC = 1.5, p-value = 0.04) relative to matched controls. The 3-miRNA panel showed a good classification capacity with an area under the receiver operating characteristic curve (AUC) of 0.81 (specificity = 0.75, sensitivity = 0.70). The diagnostic ability of the model was also evaluated in an independent retrospective cohort, yielding a higher predictive power (AUC = 0.86). A signature of EV miRNA can be detected up to five years before MPM; moreover, the identified miRNAs could provide functional insights into the molecular changes related to the late carcinogenic process, preceding MPM development.