Integrated Multi-Omics Maps of Lower-Grade Gliomas

Multi-omics high-throughput technologies produce data sets which are not restricted to only one but consist of multiple omics modalities, often as patient-matched tumour specimens. The integrative analysis of these omics modalities is essential to obtain a holistic view on the otherwise fragmented information hidden in this data. We present an intuitive method enabling the combined analysis of multi-omics data based on self-organizing maps machine learning. It “portrays” the expression, methylation and copy number variations (CNV) landscapes of each tumour using the same gene-centred coordinate system. It enables the visual evaluation and direct comparison of the different omics layers on a personalized basis. We applied this combined molecular portrayal to lower grade gliomas, a heterogeneous brain tumour entity. It classifies into a series of molecular subtypes defined by genetic key lesions, which associate with large-scale effects on DNA methylation and gene expression, and in final consequence, drive with cell fate decisions towards oligodendroglioma-, astrocytoma- and glioblastoma-like cancer cell lineages with different prognoses. Consensus modes of concerted changes of expression, methylation and CNV are governed by the degree of co-regulation within and between the omics layers. The method is not restricted to the triple-omics data used here. The similarity landscapes reflect partly independent effects of genetic lesions and DNA methylation with consequences for cancer hallmark characteristics such as proliferation, inflammation and blocked differentiation in a subtype specific fashion. It can be extended to integrate other omics features such as genetic mutation, protein expression data as well as extracting prognostic markers

Long-term environmental metal exposure is associated with hypomethylation of CpG sites in NFKB1 and other genes related to oncogenesis

Abstract Background Long-term environmental exposure to metals leads to epigenetic changes and may increase risks to human health. The relationship between the type and level of metal exposure and epigenetic changes in subjects exposed to high concentrations of metals in the environment is not yet clear. The aim of our study is to find the possible association of environmental long-term exposure to metals with DNA methylation changes of genes related to immune response and carcinogenesis. We investigated the association of plasma levels of 21 essential and non-essential metals detected by ICP-MS and the methylation level of 654 CpG sites located on NFKB1, CDKN2A, ESR1, APOA5 , IGF2 and H19 genes assessed by targeted bisulfite sequencing in a cohort of 40 subjects living near metal mining area and 40 unexposed subjects. Linear regression was conducted to find differentially methylated positions with adjustment for gender, age, BMI class, smoking and metal concentration. Results In the metal-exposed group, five CpGs in the NFKB1 promoter region were hypomethylated compared to unexposed group. Four differentially methylated positions (DMPs) were associated with multiple metals, two of them are located on NFKB1 gene, and one each on CDKN2A gene and ESR1 gene. Two DMPs located on NFKB1 (chr4:102500951, associated with Be) and IGF2 (chr11:2134198, associated with U) are associated with specific metal levels. The methylation status of the seven CpGs located on NFKB1 (3), ESR1 (2) and CDKN2A (2) positively correlated with plasma levels of seven metals (As, Sb, Zn, Ni, U, I and Mn). Conclusions Our study revealed methylation changes in NFKB1, CDKN2A, IGF2 and ESR1 genes in individuals with long-term human exposure to metals. Further studies are needed to clarify the effect of environmental metal exposure on epigenetic mechanisms and pathways involved