Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
Belic, J.
Analysis of plasma DNA using whole genome sequencing in prostate cancer patients
PhD-Studium (Doctor of Philosophy); Humanmedizin; [ Dissertation ] ; 2015. pp.
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- Autor*innen der Med Uni Graz:
- Belic Jelena
- Betreuer*innen:
- Speicher Michael
- Altmetrics:
- Abstract:
- Prostate cancer is the second leading cause of cancer deaths in men in Western societies. Although there has been tremendous improvement regarding the treatment of patients, prostate cancer still represents a major cause of cancer mortality and morbidity in men. Advanced research and development of massively parallel sequencing methods have enabled the use of ctDNA as a noninvasive approach for the detection of structural rearrangements, copy-number changes, mutations and potential drug targets in cancer patients. A significant number of advanced metastatic prostate cancer cases show only bone metastases, which is very challenging for obtaining of tumor biopsies. This fact limits sequencing approaches since the tumor tissue quality could be very poor and influence the monitoring of tumor patients. Hence, circulating tumor DNA plays an important role in the area of prostate cancer research and treatment. We conducted our research on the analysis of plasma DNA using whole-genome sequencing in metastatic prostate cancer patients. Firstly, we modified the FAST-SeqS approach (mFAST-SeqS) for the pre-screening of plasma DNA samples from cancer patients and to estimate the fraction of ctDNA and its further suitability for genome-wide analysis. Secondly, we focused on the optimization of NGS methods (whole-genome sequencing with shallow sequencing depth; plasma-Seq and targeted enrichment of cancer genes - Gene-Breakpoint Panel) to investigate copy number variation and mutation status. Using the mFAST-SeqS method, we were able to distinguish between samples with high (>10 %) and low ctDNA content (< 10 %). Hence, mFAST-SeqS offers insight into the percentage of tumor DNA amount in plasma samples without any previous knowledge of the tumor genome. Plasma-Seq allowed us to study the genomic landscape and to determine copy number changes and mutation characteristics of prostate cancer through the analysis of cfDNA. By applying this method, we were able to monitor therapy response and to predict resistance to androgen deprivation therapy by detecting high-level AR gene amplifications. We could distinguish among patients either undergoing ADT or chemotherapy as good-responders and non-responders. Therefore, important information could be obtained regarding response to a specific medication and this in turn offered information about a potential need to switch to a more suitable therapy. Plasma-Seq could serve as a potential tool for monitoring of therapy and patients and for detection of new therapeutic targets in a non-invasive manner in clinical practice for the management of prostate cancer patients.