In search of protein biomarkers in ovarian cancer and Gaucher disease

In this thesis we used proteomic technologies to identify biomarkers for two very different types of disease, i.e., ovarian cancer and Gaucher disease. In order to obtain reliable and reproducible classification of different sample groups in large datasets, we first experimented with optimizing study protocols and data acquisition. In chapter 2 we evaluated different pre-processing and classification methods in search of methods best suited for discovering (multivariable) biomarkers from large proteomic datasets. Using these results we showed that surface-enhanced laser desorption/ionization-time-of-flight-mass spectrometry (SELDI-TOF-MS) can produce reliable classification results in serum and tissue samples of ovarian cancer patients in chapter 3. Chapter 4 gives an overview of the existing literature describing the research on biomarkers in Gaucher disease such as chitotriosidase and the search for novel markers. It also highlights research using novel techniques such as SELDI-TOF-MS for the discovery of CCL18.
Label-free liquid chromatography mass spectrometry (LC-MSe) in combination with laser capture microdissection of macrophages from spleen of Gaucher disease patients resulted in the discovery of glycoprotein nonmetastatic melanoma protein B (gpNMB) as a new marker in Gaucher disease. The results of which are presented in chapter 5.
A label-free LC-MS approach was also used on serum and tissue of patients with an ovarian tumor identifying proteins which were significantly differentially expressed between benign and malignant samples in chapter 6. In chapter 7 we used LC-MSe on ovarian tumor tissue of patients with a difference in disease-free survival in an attempt to find biomarkers predicting patient survival and chemoresistance.