Betrokken en zorgvuldig - Kennis maakt ons beter

Pathology

Colorectal and gastric cancer

Secondary prevention of gastrointestinal cancer

Colorectal cancer (CRC) is the second leading cause of cancer death in the western world with over 4200 deaths per year in the Netherlands. Secondary prevention is the most realistic approach for reducing this high number of colorectal cancer deaths. Our research is focusing on
• Development of molecular tests for screening and imaging of CRC
• Detection of new markers of colorectal adenoma to carcinoma progression risk
• Unravelling mechanisms of colorectal adenoma to carcinoma progression.

Tumor profiling of gastrointestinal (i.e. gastric & colorectal) cancer

Gastrointestinal cancer causes >25% of cancer death in the western world, with death rates of 50% (colorectal cancer) to 80-90% (gastric and esophageal cancer). Once cancer has been diagnosed, standard surgical and medical oncological therapy regimens are followed. For both gastric and colorectal cancer we and others have demonstrated the existence of substantial genomic variation, which correlates to clinical outcome. Yet, the standard therapy regimens mentioned above largely neglect the existence and relevance of this genomic variation.
The aim of our program is to improve outcome of gastrointestinal cancer by stratification of GI cancer patients based on tumor profiles for optimized therapy selection

Genomics from technique to therapy

Research within the Micro Array (MA) facility at VUMC focuses on the development of genomic techniques for implementation in research, prognostic and diagnostics of diseases. We aid in the implementation from technique to therapy. Thereby we primarily focus on cancer and but also hereditary, inflammatory and communicable diseases. Chromosomal copy numbers are a hall mark of cancer and bear much specificity. We stratify patients based on these copy numbers, by embryological origin, patient prognosis and therapy.
The aim of our research is personalized therapy through genomic stratification. We develop, implement and provide the technologies, equipment and data-analysis infrastructure for personalized therapy through genomics, whilst disseminating our progress through (scientific) publications, conferences and (online) media.

ICT infrastructure for translational research

The Translational Research Working Group of the NIH defines Translational Research in the following way: "Translational research transforms scientific discoveries arising from laboratory, clinical, or population studies into clinical applications to reduce cancer incidence, morbidity, and mortality."
Large scale translational research projects like CTMM DeCoDe require substantial efforts in data and biobanking, starting with standardized collection and storage protocols for biosamples and clinical data down to data handling and analysis. To this end appropriate physical and ICT infrastructure needs to be put into place using proven technology according to best industrial practices. This will facilitate massive cross talk between the different research projects and will lead to comprehensive utilization of findings generated within the research projects.
The aim of our program is to develop and implement a standardized and harmonized IT infrastructure as integral part of the research projects linking local (in part already existing) ICT infrastructure and data sources of the respective (research) partners outside the VUmc (ranging from e.g. imagers and microarray scanners to MTA data models).

Digital microscopy

Histology is the backbone of oncology and many other areas of biomedical research. Yet, standard histopathological evaluation still implies subjective and time consuming assessment of microscopic slides. At the same time, biomedical research is witnessing a revolution in high throughput functional assays (e.g. siRNA libraries, rescue screens) and molecular biology (expression microarrays, arrayCGH, proteomics). Before the results of these efforts can be translated into clinical applications, confirmation of these findings in human tumour and other tissues, frequently by immunohistochemistry and in situ hybridization, is mandatory. To facilitate this and to keep in pace with the high throughput methods mentioned above, an up scaling of technology in the pathology research lab is required. The aim of our program is the implementation and/or development of image processing algorithms and applications (with an emphasis on tissue micro array (TMA) image analysis) that will assist pathologists and biologists in obtaining quantitative information from microscopic images for making objective diagnostic, prognostic and therapeutic decisions, and to integrate this with the bioinformatics infrastructure of other (high throughput) research facilities on the campus like the microarray and proteomics core facilities.