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Adjudication committee
- First opponent: Associate Professor Clare Verrill, Nuffield Department of Surgical Sciences, University of Oxford
- Second opponent: Professor Arvid Lundervold, The Department of Biomedicine, University of Bergen
- Third member and chair of the adjudication committee: Professor II Åslaug Helland, Institute of Clinical Medicine, University of Oslo
Chair of defence
Professor Emeritus Klaus Beiske, Institute of Clinical Medicine, University of Oslo
Main supervisor
Professor II Håvard E. Danielsen, Department of Informatics, University of Oslo
Summary
Prostate cancer is the most frequently diagnosed cancer in Norwegian men. Identification of accurate markers of good and poor prognosis is a prerequisite for tailored cancer treatment. However, the high degree of genetic variation present within a prostate tumor, termed intratumor heterogeneity, may explain why few markers are used in the clinic.
We aimed to determine the degree of intratumor heterogeneity by analyzing multiple tumor samples from patients with prostate cancer. Furthermore, we evaluated four different biomarkers while considering intratumor heterogeneity by analyzing three samples from each tumor.
We determined the degree of intratumor heterogeneity by DNA ploidy, which measures the DNA ploidy content of the tumor cells. Different DNA ploidy classes were observed in 40% of the patients when we analyzed a median of four sampled from each tumor and in 60% when we analyzed all tumor areas in 40 of the tumors. Importantly, DNA ploidy was a prognostics marker when multiple samples were analyzed, opposed to when one randomly selected sample was used.
Considering intratumor heterogeneity, we demonstrated that DNA ploidy combined with stroma fraction and the expression of three different proteins known to regulate cell division predicted recurrence after surgery. Intratumor heterogeneity was present in 20-30% of the tumors depending on the biomarker under investigation. The patients with such tumors had an intermediate risk of recurrence compared to the patients with all samples indicating either good or poor prognosis.
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