Prognostic microarray in ovarian cancer : toward patient-tailored therapy

Research output: ThesisThesis fully internal (DIV)

715 Downloads (Pure)

Abstract

In advanced stage ovarian cancer the ceiling seems to be reached for conventional chemotherapeutic drugs and almost every imaginable combination of chemotherapy has been evaluated in clinical trials. The 5-year overall survival rate (10-30%) has hardly improved the last decades'. Therefore, a paradigm shift is needed; instead of treating all patients according to standard guidelines, individualized molecular targeted treatment should be aimed for. Ovarian cancer is a heterogeneous disease, both at the clinicopathologic and at the molecular level. This suggests that identification of prognostic markers or profiles may yield potentially new targets for drug development and thus may lead to more individualized treatment. In this thesis several studies in ovarian cancer are described which focus on the identification of molecular markers (profiles), pathways and/or transcription factors associated with survival and/or chemoresistance using high-throughput techniques such as DNA, tissue and cytokine bead microarrays. There were various strategies for the identification of prognostic and/or predictive markers followed, summarized below
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • University of Groningen
Supervisors/Advisors
  • de Vries, Liesbeth, Supervisor
  • van der Zee, Ate, Supervisor
  • de Jong, Steven, Co-supervisor
  • Gerbens, Frans, Co-supervisor
  • te Meerman, Gerard, Co-supervisor
Award date28-May-2008
Publisher
Print ISBNs9789036733939
Publication statusPublished - 2008

Keywords

  • Proefschriften (vorm)
  • Metastasen
  • Ovaria , Tumoren, DNA Microarrays, Epidermale groeifactor, R
  • gynaecologie en obstetrie
  • neoplasmata, gezwellen

Fingerprint

Dive into the research topics of 'Prognostic microarray in ovarian cancer : toward patient-tailored therapy'. Together they form a unique fingerprint.

Cite this