NRAS Mutation Is the Sole Recurrent Somatic Mutation in Large Congenital Melanocytic Nevi

Congenital melanocytic nevus (CMN) is a particular melanocytic in utero proliferation characterized by an increased risk of melanoma transformation during infancy or adulthood. NRAS and BRAF mutations have consistently been reported in CMN samples, but until recently results have been contradictory. We therefore studied a series of large and giant CMNs and compared them with small and medium CMNs using Sanger sequencing, pyrosequencing, high-resolution melting analysis, and mutation enrichment by an enhanced version of ice-COLD-PCR. Large–giant CMNs displayed NRAS mutations in 94.7% of cases (18/19). At that point, the role of additional mutations in CMN pathogenesis had to be investigated. We therefore performed exome sequencing on five specimens of large–giant nevi. The results showed that NRAS mutation was the sole recurrent somatic event found in such melanocytic proliferations. The genetic profile of small–medium CMNs was significantly different, with 70% of cases bearing NRAS mutations and 30% showing BRAF mutations. These findings strongly suggest that NRAS mutations are sufficient to drive melanocytic benign proliferations in utero

Epigenetic modulation of<i> AREL1</i> and increased <i>HLA</i> expression in brains of multiple system atrophy patients

International audienceMultiple system atrophy (MSA) is a rare disease with a fatal outcome. To date, little is known about the molecular processes underlying disease development. Its clinical overlap with related neurodegenerative movement disorders underlines the importance for expanding the knowledge of pathological brain processes in MSA patients to improve distinction from similar diseases. In the current study, we investigated DNA methylation changes in brain samples from 41 MSA patients and 37 healthy controls. We focused on the prefrontal cortex, a moderately affected area in MSA. Using Illumina MethylationEPIC arrays, we investigated 5-methylcytosine (5mC) as well as 5-hydroxymethylcytosine (5hmC) changes throughout the genome. We identified five significantly different 5mC probes (adj. P < 0.05), of which one probe mapping to the AREL1 gene involved in antigen presentation was decreased in MSA patients. This decrease correlated with increased 5hmC levels. Further, we identified functional DNA methylation modules involved in inflammatory processes. As expected, the decreased 5mC levels on AREL1 was concordant with increased gene expression levels of both AREL1 as well as MHC Class I HLA genes in MSA brains. We also investigated whether these changes in antigen-related processes in the brain associated with changes in peripheral mononuclear cells. Using flow cytometry on an independent cohort of MSA patients, we identified a decrease in circulating non-classical CD14+CD16++ blood monocytes, whereas T and NK cell populations were unchanged. Taken together, our results support the view of an active neuroimmune response in brains of MSA patients

Improving Breast Cancer Survival Analysis through Competition-Based Multidimensional Modeling

Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one avenue for improving treatment by matching the proper treatment with molecular subtypes of the disease. In this work, we employed a competition-based approach to modeling breast cancer prognosis using large datasets containing genomic and clinical information and an online real-time leaderboard program used to speed feedback to the modeling team and to encourage each modeler to work towards achieving a higher ranked submission. We find that machine learning methods combined with molecular features selected based on expert prior knowledge can improve survival predictions compared to current best-in-class methodologies and that ensemble models trained across multiple user submissions systematically outperform individual models within the ensemble. We also find that model scores are highly consistent across multiple independent evaluations. This study serves as the pilot phase of a much larger competition open to the whole research community, with the goal of understanding general strategies for model optimization using clinical and molecular profiling data and providing an objective, transparent system for assessing prognostic models

A meta-analysis of pre-pregnancy maternal body mass index and placental DNA methylation identifies 27 CpG sites with implications for mother-child health

Higher maternal pre-pregnancy body mass index (ppBMI) is associated with increased neonatal morbidity, as well as with pregnancy complications and metabolic outcomes in offspring later in life. The placenta is a key organ in fetal development and has been proposed to act as a mediator between the mother and different health outcomes in children. The overall aim of the present work is to investigate the association of ppBMI with epigenome-wide placental DNA methylation (DNAm) in 10 studies from the PACE consortium, amounting to 2631 mother-child pairs. We identify 27 CpG sites at which we observe placental DNAm variations of up to 2.0% per 10 ppBMI-unit. The CpGs that are differentially methylated in placenta do not overlap with CpGs identified in previous studies in cord blood DNAm related to ppBMI. Many of the identified CpGs are located in open sea regions, are often close to obesity-related genes such as GPX1 and LGR4 and altogether, are enriched in cancer and oxidative stress pathways. Our findings suggest that placental DNAm could be one of the mechanisms by which maternal obesity is associated with metabolic health outcomes in newborns and children, although further studies will be needed in order to corroborate these findings.We would like to thank the Pregnancy and Childhood Epigenetics (PACE) consortium, as well as all the families that participated in these studies for their generous contribution. This work was partially funded by GVSAN2018111086 from the Basque Department of Health and PI18/01142 from ISCIII - Spanish Ministry of Science and Innovation - cofounded by the ERDF “A way to make Europe” to JRB and LSM, respectively; and by the Joint Programming Initiative – A Healthy Diet for a Healthy Life (JPI HDHL) (NutriPROGRAM). ACP was supported by grant GVSAN2019111085 from the Basque Department of Health to NFJ. Detailed acknowledgements and funding for each participating cohort are described in Supplementary Note 1

DNA METHYLATION

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Do not be scared of the genome's 5th base-Explaining phenotypic variability and evolutionary dynamics through DNA methylation analysis

International audienceEpigenetic processes have taken center stage for the investigation of many biological processes, and epigenetic modifications have shown to influence phenotype, mor-phology and behavioural traits such as stress resistance by affecting gene regula-tion and expression without altering the underlying genomic sequence. The multiple molecular layers of epigenetics synergistically construct the cell type-specific gene regulatory networks, characterized by a high degree of plasticity and redundancy to create cell-type-specific morphology and function. DNA methylation occurring on the 5′ carbon of cytosines in different genomic sequence contexts is the most studied epigenetic modification. DNA methylation has been shown to provide a molecular record of the exposure to a large variety of environmental factors, which might be persistent through the entire lifetime of an organism and even be passed onto the offspring. Animals might display altered phenotypes mediated by epigenetic modi-fications depending on the developmental stage or the environmental conditions as well as during evolution. Therefore, the analysis of DNA methylation patterns might allow deciphering previous exposures, explaining ecologically relevant phenotypic diversity and predicting evolutionary trajectories enabling accelerated adaption to changing environmental conditions. Despite the explanatory potential of DNA meth-ylation integrating genetic and environmental factors to shape phenotypic variation and contribute significantly to evolutionary dynamics, studies of DNA methylation are still scarce in the field of ecology. This might be at least partly due to the complexity of DNA methylation analysis and the interpretation of the acquired data. In the cur-rent issue of Molecular Ecology Resources, Laine and colleagues (Molecular Ecology Resources, 2022) provide a detailed summary of guidelines and valuable recommen-dations for researchers in the field of ecology to avoid common pitfalls and perform interpretable genome-wide DNA methylation analyses

Current and emerging technologies for the analysis of the genome-wide and locus-specific DNA methylation patterns

International audienceDNA methylation is the most studied epigenetic modification, and altered DNA methylation patterns have been identified in cancer and more recently also in many other complex diseases. Furthermore, DNA methylation is influenced by a variety of environmental factors, and the analysis of DNA methylation patterns might allow deciphering previous exposures. A number of techniques to study DNA methylation either genome-wide or at specific loci have been devised using a limited number of principles for differentiating the methylation state: (1) methylation-sensitive/dependent restriction enzymes, (2) antibody or methyl-binding protein-based enrichment, or (3) chemical or enzymatic conversion, (4) direct sequence readout. Second-generation sequencing has largely replaced microarrays as a readout platform and is also becoming more popular for locus-specific DNA methylation analysis. In this chapter, the currently used methods for both genome-wide and locus-specific analysis of 5-methylcytosine as well as its oxidative derivatives such as 5-hydroxymethylcytosine are reviewed in detail and advantages and limitations of each approach are discussed. Furthermore, emerging technologies avoiding PCR amplification and allowing a direct readout of DNA methylation are summarized, together with novel applications, such as the detection of DNA methylation in single cells or in circulating cell-free DNA

10 years of Epigenomics: a journey with the epigenetic community through exciting times

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Strengthening epithelial barriers through modulation of the histone code in allergic diseases - a novel approach for preventing the atopic march?

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