Our research is focused on large scale genomic instability in cancer. Our aim is to understand the process of changes in DNA- and chromatin structure during cancer development, and to use this knowledge to predict treatment response and prognosis for cancer patients.
Microscopic images of cell nuclei from different sources (Light microscopy, Laser Scan microscopy, Electron microscopy & digital scanners) are digitally processed and analyzed. Methods and applications are developed to process very large amounts of image data for quantitative and qualitative analysis of DNA- and chromatin structure.
The Institute is conducting basic research in both biomedicine and informatics, has a number of projects in translational/clinical research, and several development projects on supportive clinical tools. Our biomedical and clinical research is focused on cancer, whereas the development projects are more general.
Our main research hypothesis is that genomic instability is a driving force in cancer, and the ability to identify and measure genomic instability might therefore be useful markers in predictive diagnosis and prognosis. Our key projects here are Nucleotyping, DNA ploidy, Histotracker, 3D-imaging, TMA and Path Tool.
Most of these projects are expected to result in new biomarkers and replace or be an objective supplement to pathology. We have already demonstrated that Nucleotyping is a pan-cancer biomarker of prognosis (Lancet Oncology 2018) and that Histotyping outperforms all available prognostic markers in colorectal cancer (Lancet 2020). These AI projects are now being expanded to include other types of cancer, including cancers of the lung, prostate and endometrium. Mitotic Index is an old generic marker of tumour aggressiveness, and continues to be very time consuming for pathologists and hampered with an inter-and intraobserver variation. This method will be fully automated, and current results demonstrate a strong prognostic potential in several cancer types.