Irma Fredriksson

Breast cancer is a major public health problem affecting over 8,800 women per year in Sweden. Preventing new cases, increasing early detection and improving survival are key goals of the national cancer strategy. In this project we will identify subgroups of women at particularly high risk of breast cancer and subsequent adverse outcomes. This will be achieved by integrating modern statistical methods with high-quality clinical cancer registry data, which will provide better answers to clinical and policy relevant research questions. This project focuses on defining high-risk groups based on both socioeconomic and reproductive factors, to understand their interplay and their association with other factors, such as breast cancer subtype, age, screening, comorbidity, stage, treatments and survival. We will utilise cancer registry data from three countries (Sweden, Norway and the Netherlands) and pool results using federated data analysis. We will apply modern missing data methods and mediation analysis to breast cancer data to optimize the use of the available data. A long-term goal is to improve the utilization of cancer registry data through dissemination of methods and skills across cancer registry groups and build a strategic platform for future international collaborations. The public health goal is to provide essential information to optimise prevention strategies to high-risk groups. The produced evidence will be vital for the patients, clinicians and decision-makers.

Characterizing in time and space the metastatic process of breast cancer<br/><br/>NEIForskningsopphold i utlandetPatients with ER positive breast cancers have a lower risk of relapse within the first five years compared to those with ER negative disease. However, after 5-year, while ER- cancers very rarely relapse, almost 50% of ER+ relapses have yet to occur. The main objective of this project is to understand time-dependent risk for disease progression.The main objective of this project is to understand time-dependent dissemination and tumor evolution with the aim of identifying predictors of late relapse of ER+ breast cancer. A particular focus is to define the potential role of liquid biopsies for tailoring treatment and monitoring disease. Key questions we will seek to answer: Is the metastatic process driven by different mechanisms in patients with different time to relapse? Do the evolutionary processes differ in these patients? Can the evolutionary process be predicted at time of diagnosis or is it revealed by later features discovered in minimal residual disease? To answer this, the study was designed as four work packages where the activity started in 2019. <br/><br/>This project has performed extensive testing of methodology to be able to identfy molecular alterations in minor cell populations, even single tumor cells. A master thesis (Julie S. Monrad) in June 2021 identified suitable techniques, and now we are finalizing this work by analysing single cell sequencing data from the isolated cells. <br/>To understand more about evolution, we have finalized a work where corresponding primary tumors an lymph nodes are investigated at singel cell level (by CyTOF and Hyperion), this is just accepted for publication. <br/>The understand more about the clinical importance of liquid biopsies in ER+ breast cancer we have finished the blood analyses in the ICON trial

here we found that in peripheral blood (CellSearch analyses, inculding PD-L1), patients with Luminal A subtype hade more frequently circulating tumor cells. it was also a trend towards this being a prognostic marker, but the number of patients included in the trial is a little too small to conclude. <br/><br/>We are continuing dataanalyses in this project with regard to late relapse and predictive biomarkers. This project has in addition also been important to identify technology and methodology to identify minimal residual disease in cancer patients suitable as diagnostic tests.<br/>