Application of genomic approaches in cancer research and diagnostics
The transformation of normal to malignant cells may be caused by many different mechanisms that share a single common feature – the alteration of genetic information and subsequent disruption of cellular regulatory mechanisms, which thus lead to uncontrolled proliferation. Some of these genetic alterations have already been described and are routinely analysed in oncological diagnostics, e.g. TP53, ATM or BRCA gene mutations or specific translocations occurring in leukemias, lymphomas and other tumours. The importance of many other genomic aberrations found in tumours and their influence on the malignant potential of transformed cells should be analysed as well as the impact of individual genetic variants on tumour behaviour. Novel technologies including high-resolution SNP microarrays and high-throughput genome sequencing (massive parallel sequencing) provide fast and complex analysis of the human genome. These methods will be used to characterise genetic information of the patient‘s malignant and non-malignant cells to reveal the mechanisms of cellular transformation.
The expected outputs of this work package are:
1) the identification of recurrent genomic alterations in hematological and other malignancies, which could be used in cancer diagnostics and as a potential therapeutic target,
2) the analysis of the influence of the host genome on disease progression,
3) the characterisation of the regulatory pathways disrupted in tumour cells. The outcome of these studies is expected to be used as an initial point for focused research as well as for direct use in diagnostics of haematological and oncological malignancies.
Technologies used: massive parallel DNA sequencing (next-generation high-throughput sequencing), SNP mapping (high resolution SNP microarrays), gene expression profiling (microarrays, QRT-PCR), FACS, bioinformatic processing.
Brochure about the FP7 project "Next Generation Sequencing platform for targeted Personalized Therapy of Leukemia" to download can be found HERE.
seznam / vizitky
Molecular – biological diagnostic and research laboratory equipped with instrumentation for routine diagnostic tasks such as PCR, qPCR, DNA electrophoresis and DNA sequencing as well as equipment serving mainly for research needs such as microarray scanners (short and long oligonucleotide platforms) or nucleofector for high-efficient transfections.
Supervisor: Mgr. Karla Plevová, Ph.D.
Consultants: Mgr. Kamila Réblová, Ph.D., Mgr. Karol Pál
With the advent of massively parallel sequencing (MPS), many challenges in molecular biology and medicine have emerged including the discovery of novel molecular mechanisms and biological networks. Due to the accelerated development in genomics and computational technologies it is possible to study molecular processes at various levels ranging from primary DNA structure, through genome organization, to its expression in a comprehensive manner. Among other biological contexts this is especially important in human diseases, such as cancer. In the proposed PhD project, a PhD candidate will perform advanced bioinformatics analyses of genomic data obtained using MPS in cases with chronic lymphocytic leukemia (CLL). The student will focus on discovery of genetic and expression patterns related to specific disease conditions, namely CLL early development, and accumulation of adverse genomic defects leading to refractory disease. In particular, tumor signatures will be extracted from DNA and RNA sequencing data in an attempt to provide a detailed picture of molecular processes underlying CLL clonal evolution. It is expected that the student will acquire good knowledge of existing solutions, design his/her own bioinformatics tools and employ computing approaches based on machine learning, if necessary. Obtained data will be validated using available independent datasets and will serve as a basis for consequent wet-lab experiments aiming to define novel clinically relevant biomarkers for better disease stratification and management.
Keywords: chronic lymphocytic leukemia, cancer genome, clonal evolution, biomarkers, mutation signature, expression pattern, tumor interactions, bioinformatics tools, computing technologies
29. ledna 2018 9:46
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