Research

The research at the Institute for Medical informatics develops and establishes new methods within diagnostics and prognostics of cancer. Our research programs focus on research within informatics but is mainly occupied with translational research focusing on DNA and chromatin based studies of large-scale genome instability.

Overview

Our research focuses on methods in digital image processing and image analysis. The main projects are Nucleotyping and DNA-ploidy where both measure large-scale genome instability, principally after cancer development in the prostate, intestine, breast, and ovaries. The cytometry lab is a central component in the research projects and is considered its own entity in the program.
Our hypothesis is that genome instability is a driving force in cancer development and we are therefore focused on developing and establishing methods for analyzing genome instability under cancer development. Principally, we have developed methods for measurement of what we call large-scale genome instability, in other words, we do not look at each gene per se but each nuclei, and study how the nucleiís DNA content and chromatin structure is described (and understood) in each cancer biopsy related to the patientís diagnosis and disease history.

History

Over the past ten years, we have developed and established new methods for investigating DNA organization and chromatin structure – methods which provide both quantitative and qualitative measurements for functional genetic changes under cancer development. The methods are based on computer-assisted image analysis where we transfer images of cells and tissues from a microscope (light, laser scan, and electron microscopy) to a computer. In the computer, we can digitize the images and analyze the chromatinís structure and organization bit for bit. We call these investigations of interphase nuclei, nucleotyping.

Research Focus

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.

Imaging Research

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.

Cancer Focus

The Institute is conducting basic research in both biomedicine and informatics, have 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.

Better Treatment

The ability to predict treatment response and prognosis are key elements in successful treatment of cancer. Archival material and clinical data from more than 3000 patients are included in our research projects on prostate-, breast-, colorectal- and gynecological malignancies, and the aim is to improve future treatment by the retrospective identification of better prediction and prognosis of the outcome amount these patients.

Key Efforts

Nucleotyping

This is an objective measurement for nuclei atypia – one of the most important parameters for pathology diagnosis and prognosis. The method is arranged sensitively for larger chromosomal aberrations. More importantly is the methodís ability to map and quantify functional changes in DNA organization, which can but doesnít need to be, induced by larger or smaller mutations. Such changes are to a large extent sub-visual and cannot be picked-up by an ordinary microscope. Nucleotyping can be described as interphase cytogenetics, that is, an interphase variant of chromosomal analyses where we map and describe organizational and functional domains of DNA.
Nucleotyping has a large potential as a diagnostic and prognostic/predictive marker for cancer. In contrast to DNA ploidy, this method also has prognostic value for cancer in advanced stages.

DNA ploidy

Analysis where we calculate the total DNA content per nuclei for all the nuclei in a biopsy. This is another objective expression for large-scale genome instability which discriminates between tests which have a normal, stable DNA amount (as most often diploid cells) or abnormal and usually unstable DNA amounts (aneuploid cells). We have established DNA ploidy analysis as a routine method for diagnostic and prognostic assessment in clinical activity within gynecological cancer, cancer of the prostate, and now have ongoing studies for a series of other cancers, among others rectal and colon cancer.

3-D imaging

Both of the above mentioned methods will now possibly be further enhanced to three-dimensional analysis in our 3-D imaging project. This creates many challenges in our methodology, but in the event we succeed, this will open new application areas as a new science of large-scale genome instability under cancer development.

MicroTracker

Another approach we are now investigating is the possibility to directly compare and correlate measurement results (cell for cell) from different analysis methods. Todayís methods limit us usually from comparing different results per patient or per tumor, as one is usually dependent on to use different tests for different investigations. In the project MicroTracker, we develop methods for retrieving the same cell nuclei either from different thin sections or from the same stained section and re-stained for different methods. These sections can also be analyzed in different systems, but with advanced pattern retrieval techniques we can compare different measurement data and present these visually connected to nuclei in a digital image of the whole tissue section.

Path Tool

This project represents a whole different approach. Here, we are trying to establish methods which can objectively and automatically classify the tissue structure (histology) in a biopsy. The method is established primarily to simplify automatization of the above mentioned analysis methods, but we are also looking at the possibility of establishing this as an independent method for histopathological grading of cancerous tumor analyses, and we are working experimentally with Gleason grading of tumors in the prostate.

Tissue Micro Array

We have also established TMA (tissue micro array) as a method in the cytometry laboratory. TMA is available also to users outside our department and hospital.