Invasive cervical cancer (ICC) is caused by high-risk human papillomavirus types (HR-HPVs) and is usually preceded by a long phase of intraepithelial neoplasia (CIN). Before invasion, (epi) genetic changes, potentially applicable as molecular markers within cervical screening, occur in HPV host cells. Epigenetic alterations, such as dysregulation of microRNA (miRNA) expression, are frequently observed in ICC. The mechanisms and role of miRNA dysregulation in cervical carcinogenesis are still largely unknown. We provide an overview of the studies investigating miRNA expression in relation to ICC progression, highlighting their common outcomes and their weaknesses/strengths. To achieve this, we systematically searched through Pubmed database all articles between January 2010 and December 2017. From the 24 studies retrieved, miR-29a and miR-21 are the most frequently down- and up-regulated in ICC progression, respectively. Microarray-based studies show a small overlap, with miR-10a, miR-20b, miR-9, miR-16 and miR-106 found repeatedly dysregulated. miR-34a, miR-125 and miR-375 were also found dysregulated in cervical exfoliated cells in relation to cancer progression. The pivotal role of miRNAs in ICC progression and initial development is becoming more and more relevant. Available studies are essentially based on convenience material, entailing possible selection bias, and frequently of small size: all these points still represent a limitation to a wide comprehension of miRNAs relevant for ICC. The targeted approach instead of a genome-wide investigation still precludes the identification of all the relevant miRNAs in the process. The implementation of deep sequencing on large scale population-based studies will help to discover and validate the relation between altered miRNA expression and CC progression for the identification of biomarkers. Optimally, once explored on a miRNome scale, small specific miRNA signatures maybe used in the context of screening.

A population in a natural crossroad within Europe reveals multiple ancient contributions and substantial population structure.

MicroRNA profiles in urine by next-generation sequencing can stratify bladder cancer subtypes microRNA profiles in urine by next-generation sequencing can stratify bladder cancer subtypes

DNA methylation profiles are responsive to environmental stimuli and metabolic shifts. This makes DNA methylation a potential biomarker of environmental-related and lifestyle-driven diseases of adulthood. Therefore, we investigated if white blood cells’ (WBCs) DNA methylation profiles are associated with myocardial infarction (MI) occurrence. Whole-genome DNA methylation was investigated by microarray analysis in 292 MI cases and 292 matched controls from the large prospective Italian European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (EPICOR study). Significant signals (false discovery rate (FDR) adjusted P < 0.05) were replicated by mass spectrometry in 317 MI cases and 262 controls from the Dutch EPIC cohort (EPIC-NL). Long interspersed nuclear element-1 (LINE-1) methylation profiles were also evaluated in both groups. A differentially methylated region (DMR) within the zinc finger and BTB domain-containing protein 12 (ZBTB12) gene body and LINE-1 hypomethylation were identified in EPICOR MI cases and replicated in the EPIC-NL sample (ZBTB12-DMR meta-analysis: effect size ± se = −0.016 ± 0.003, 95 % CI = −0.021;−0.011, P = 7.54 × 10−10; LINE-1 methylation meta-analysis: effect size ± se = −0.161 ± 0.040, 95 % CI = −0.239;−0.082, P = 6.01 × 10−5). Moreover, cases with shorter time to disease had more pronounced ZBTB12-DMR hypomethylation (meta-analysis, men: effect size ± se = −0.0059 ± 0.0017, P TREND = 5.0 × 10−4; women: effect size ± se = −0.0053 ± 0.0019, P TREND = 6.5 × 10−3) and LINE-1 hypomethylation (meta-analysis, men: effect size ± se = −0.0010 ± 0.0003, P TREND = 1.6 × 10−3; women: effect size ± se = −0.0008 ± 0.0004, P TREND = 0.026) than MI cases with longer time to disease. In the EPIC-NL replication panel, DNA methylation profiles improved case-control discrimination and reclassification when compared with traditional MI risk factors only (net reclassification improvement (95 % CI) between 0.23 (0.02–0.43), P = 0.034, and 0.89 (0.64–1.14), P < 1 × 10−5). Our data suggest that specific methylation profiles can be detected in WBCs, in a preclinical condition, several years before the occurrence of MI, providing an independent signature of cardiovascular risk. We showed that prediction accuracy can be improved when DNA methylation is taken into account together with traditional MI risk factors, although further confirmation on a larger sample is warranted. Our findings support the potential use of DNA methylation patterns in peripheral blood white cells as promising early biomarkers of MI.