At the core of this research lies the technology of Mass Spectrometry Imaging (MSI). While MSI is a novel, powerful research tool for mapping the molecular composition directly from tissue whilst preserving spatial morphology, it does not hold all the answers to the complex (clinical) biological questions. Thereto, this thesis presents various efforts to integrate MSI data with other valuable, complementary, imaging or non-imaging data sources in order to investigate systematically the complex tissue biology in health and disease. For instance, this work delivers workflows that accelerate histological annotation for rapid correlation with the molecular information provided by high-spatial-resolution MSI and as such lays out the future of high throughput, automated digital pathology-based diagnosis. The highlight of this PhD is a study conducted in collaboration with Johns Hopkins, where the aforementioned multi-disciplinary strategies were employed to investigate molecular signature of metastatic breast cancer in a unique multi-organ sample set from several breast cancer patients. The findings emphasize the clinical importance and benefits of spatial tissue analysis by MSI, which combined with extensive pathology annotation leads to research opportunities with unprecedented translational potential.
|Award date||2 Dec 2020|
|Place of Publication||Maastricht|
|Publication status||Published - 2020|
- Molecular Imaging
- Mass Spectrometry
- systems biology