Genetic and epigenetic biomarkers in cancer

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Clonal hematopoiesis of indeterminate potential (CHIP) has recently been described as a common phenomenon associated with aging. It is characterized by the accumulation of somatic mutations in cells of the hematopoietic system. Although CHIP is manifested by the expansion of certain cell clones, this condition is not accompanied by any morphological features of hematological neoplasia. However, it has been shown that the incidence of clonal hematopoiesis correlates with increased overall mortality and the risk of developing malignant transformation of hematopoietic cells as well as cardiovascular disease, such as ischemic stroke. To what extent and by what mechanisms clonal hematopoiesis contributes to disease development remains a question of current research. The main aim of the project will be to pinpoint the principal cells carrying CHIP somatic mutations, and to study their role in development and maintenance of atherosclerotic plaques, especially of those involved in development of stroke. The comparison of the phenotype of CHIP positive and negative cells will be of special interest. The use of cellular models not only include different types of leucocytes but circulatory progenitor endothelial cells as well. The study will involve elderly subjects with the positive presence of CHIP (>65 years). Subject will be characterized based on the presence or absence of ischemic stroke and the presence or absence of carotid stenosis by our clinical collaborators. The presence of somatic variants in 38 selected genes associated with CHIP will be tested in subjects of interest within our research group. The project will use various techiques including FACS, MACS, cell cultures, DNA isolation from small amount of cells, a highly sensitive sequencing method for DNA genotyping allowing detection of variant with less than 1% allelic frequency, DNA/RNA sequencing library preparation, deep massively parallel sequencing of panel of genes using unique molecular barcodes/indices, RNAseq, bioinformatics and data analysis with possibilities of calculations using high performance computing cluster, data management and statistical evaluation.