Asbestos exposure is the main risk factor for malignant pleural mesothelioma (MPM), a rare aggressive tumor. Nevertheless, only 5–17% of those exposed to asbestos develop MPM, suggesting the involvement of other environmental and genetic risk factors.To identify the genetic risk factors that may contribute to the development of MPM, we conducted a genome-wide association study (GWAS; 370,000 genotyped SNPs, 5 million imputed SNPs) in Italy, among 407 MPM cases and 389 controls with a complete history of asbestos exposure. A replication study was also undertaken and included 428 MPM cases and 1269 controls from Australia.Although no single marker reached the genome-wide significance threshold, several associations were supported by haplotype-, chromosomal region-, gene- and gene-ontology process-based analyses. Most of these SNPs were located in regions reported to harbor aberrant alterations in mesothelioma (SLC7A14, THRB, CEBP350, ADAMTS2, ETV1, PVT1 and MMP14 genes), causing at most a 2–3-fold increase in MPM risk. The Australian replication study showed significant associations in five of these chromosomal regions (3q26.2, 4q32.1, 7p22.2, 14q11.2, 15q14).Multivariate analysis suggested an independent contribution of 10 genetic variants, with an Area Under the ROC Curve (AUC) of 0.76 when only exposure and covariates were included in the model, and of 0.86 when the genetic component was also included, with a substantial increase of asbestos exposure risk estimation (odds ratio, OR: 45.28, 95% confidence interval, CI: 21.52–95.28).These results showed that genetic risk factors may play an additional role in the development of MPM, and that these should be taken into account to better estimate individual MPM risk in individuals who have been exposed to asbestos.

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Chronic lymphocytic leukemia (CLL) is a clinically heterogeneous disease characterized by the clonal expansion of malignant B cells. To predict the clinical course of the disease, the identification of diagnostic biomarkers is urgently needed. Aberrant methylation patterns may predict CLL development and its course, being very early changes during carcinogenesis. Our aim was to identify CLL specific methylation patterns and to evaluate whether methylation aberrations in selected genes are associated with changes in gene expression. Here, by performing a genome-wide methylation analysis, we identified several CLL-specific methylation alterations. We focused on the most altered one, at a CpG island located in the body of SHANK1 gene, in our CLL cases compared to healthy controls. This methylation alteration was successfully validated in a larger cohort including 139 CLL and 20 control in silico samples. We also found a positive correlation between SHANK1 methylation level and absolute lymphocyte count, in particular CD19+ B cells, in CLL patients. Moreover, we were able to detect gains of methylation at SHANK1 in blood samples collected years prior to diagnosis. Overall, our results suggest methylation alteration at this SHANK1 CpG island as a biomarker for risk and diagnosis of CLL, and also in the personalized quantification of tumor aggressiveness.