Pathology Research Group

Due to the enormous development of new drugs coming on the market, and new methods of diagnostics, there are opportunities for a more personalised treatment. Nevertheless, over- and under-treatment is a major problem.

Many patients develop resistance during treatment or relapse, while other patients suffer from side effects of treatment.

The morphological (structure), immunohistochemical (proteins) and molecular analyses (genetic material) of pathology are central to the work on cancer diagnoses. We want to improve pathology diagnostics by finding, validating and using new biomarkers. We will achieve this goal by using large-scale analyses for proteins and genetic material, artificial intelligence and digital pathology.

Research projects

Breast cancer

• International Consortium for Advancing Research on TNBC = Triple negative breast cancer (ICART); The goal is to find new biomarkers that can identify patients who need more or less treatment compared to current treatment. Collaborative project with Georgia State University, Atlanta, USA and University of Nottingham, UK.
• Clarify; an EU training network that aims to educate multidisciplined researchers who can collaborate on and develop artificial intelligence that can improve diagnostics for TNBC patients. Collaborative projects with universities in Stavanger, Amsterdam, Rotterdam, Valencia and Granada.
• PErsonalized TREatment of high-risk MAmmary Cancer - the PETREMAC trial; Our department was the National Center for Pathology in this study. We study the interaction between the defense system around the tumor and the tumor cells; Can we identify groups of patients who respond better to new types of treatment? Collaborative project with Helse Bergen.
• Digital pathology in Western Norway Regional Health Authority; We will develop, validate and implement new digital tools to measure proliferation in tissue from breast cancer patients. Collaborative project with Helse Bergen.
• Integrated molecular monitoring of breast cancer patients; Here we are looking for new biomarkers for long-term follow-up of operable breast cancer patients by examining blood samples and tissue collected in the unique biobank PBCB (Prospective Breast Cancer Biobank). Findings from different big data techniques will be integrated and analysed together. Collaborative project with Bergen Regional Health Authority and Oslo University Hospital.
• The Effects of Insulin and Insulin-related Characteristics, and Short-Term Low-glycemic and High-glycemic Carbohydrate lntervention on Breast Cancer Proliferation; Tumors from patients who have been given a high dose of carbohydrates before surgery are biologically altered and show higher proliferation. We investigate which proteins are altered (glycosylation) in blood and tissues to understand more about the interaction between diet and tumor development. Collaborative project with Griffith University, Gold Coast, Australia.
• Proliferation as a biomarker for therapy response and survival; collaborative project with the University of Aarhus.
• MicroRNA (miR18a/b); We are exploring whether microRNA molecules found in tissues or blood can provide better information about treatment efficacy or survival in patients with breast cancer.
• Other projects together with research group for breast cancer and research group for Cancer and Physics.

Bladder cancer

• Improving diagnostics for TaT1 urothelial carcinoma in bladder; The project focuses on early bladder cancer and we want to improve diagnostics by investigating new biomarkers such as proliferation, the defense system and genetic changes in tumor tissue. Collaborative project with Erasmus University Hospital in Rotterdam.
• Artificial intelligence for improving bladder diagnostics; Use of artificial intelligence to automatically identify tumor tissue and risk of recurrence/progression for the patient with bladder cancer. Collaborative project with the University of Stavanger and part of Clarify.
• Immune system and bladder cancer; investigating interaction between the defense system and bladder cancer. Collaborative project with Icahn School of Medicine, Mount Sinai, New York, USA.

Prostate cancer

• Improved diagnostics of prostate cancer by means of artificial intelligence; Use of artificial intelligence to automatically identify tumor tissue and risk of recurrence/progression for the patient with prostate cancer. Collaborative project with University of Stavanger and Karolinska Institutet, Stockholm, Sweden.
• Biomarkers in blood; Biobank project that collects blood for future research projects, aims to develop new biomarkers in blood to predict recurrence in patients with prostate cancer.

Colon cancer

• Use of quantitative pathology to improve grading and predict prognosis in tumours of the gastrointestinal tract. Use of digital image analysis to evaluate immune response in colorectal cancer. The project looks at T cells in colorectal cancer and compares immune responses against other prognostic markers such as microsatellite instability. The project is part of the ACROBATICC biobank and there is a collaboration with the University of Stavanger.

Neuroendocrine tumors of the gastrointestinal tract

• Quantification of proliferative markers in neuroendocrine tumours in the gastrointestinal tract implementing digital pathology. The project is looking at digital image analysis of the proliferation markers Ki67 and phosphohistone-H3 (PHH3) in neuroendocrine tumors of the gastrointestinal tract.

Uterine cancer

• Diagnostic and prognostic biomarkers in endometrioid endometrial carcinogenesis; The goal is to develop, validate and implement new biomarkers for precancerous lesions of uterine cancer. Overtreatment is a major problem and therefore there is a need for better and more reproducible biomarkers. The collaborative project with Helse Bergen, part of the Western Norway Regional Health Authority's project "Digital pathology in the Western Norway Regional Health Authority".

Cervical cancer

• "Who are at risk of developing cervical cancer?" Development of new biomarkers that can predict which women are at risk of developing cervical cancer. Foci of immune function and genetic changes in tissues. Collaborative project with the Cancer Registry of Norway and Sørlandet Hospital.

Skin cancer

• Artificial intelligence as screening tool for digitized histological slides from skin biopsies; Use of artificial intelligence to automatically identify tumor tissue and risk of recurrence/progression for the patient with skin cancer. Subproject by Clarify.

Cause of Death Registry

• Data quality in the Norwegian Cause of Death Registry. The Cause of Death Registry is an important source of data for health surveillance, statistics, research and quality assurance work. The quality of the data in the register will affect the quality of the analyses that use the data from the register. In particular, the project aims to investigate the use of non-informative diagnostic codes ("junk codes") and what real conditions may be hiding behind these codes. The project is linked to the Norwegian Burden of Disease project at the Norwegian Institute of Public Health.

Biobank

• SOLIDTH (SOLID Tumors and Hematological malignancies); A general research biobank established to collect biological material from most types of cancer. The material will be used for ongoing and future cancer research at SUS and other collaborating institutions. The research will be able to create a better biological understanding of cancer, including better biomarkers for diagnosis, prognosis and prediction of treatment response. The research will also lay the foundation for developing new drugs or treatment methods.
• General Biobank for Cervical Cancer and High-grade Cervical Intraepithelial Neoplasia; a general research biobank that could form the basis for developing prognostic biomarkers that can identify women who are at greatest risk of developing cervical cancer after a persistent HPV infection.
• Prognostic and predictive factors in urothelial carcinoma of the urinary bladder; A general research biobank created to investigate existing and new biomarkers to predict the prognosis of urothelial carcinomas in the urinary bladder.