Brain metastasis


PI: Vigdis Nygaard              

Brain metastasis (BM) remains the leading cause of cancer-related deaths for tumor types such as malignant melanoma despite new therapy options for these patients. We currently have a limited understanding of the effectiveness of these new therapies in BM treatment and how to benefit from precision medicine. Filling our knowledge gap on the molecular profiles and mechanisms underlying BMs may provide advances in the field.

In this research project we utilize a biobank consisting of surgically removed BM samples for genomic analyses. To date the biobank holds >180 clinically annotated samples. These samples are processed for next generation sequencing (NGS) analyses in order to obtain mutational and transcriptional profiles. Our goal is to molecularly characterize BMs and to identify new treatment opportunities and biomarkers which may indicate benefit from precision medicine approaches for BM patients. Candidate targets identified by data exploration can be tested for efficacy in our experimental BM metastasis models, and thereby provide a basis for novel brain-specific therapy approaches.

The rapid advancement of immunotherapy has created an immediate need for increased knowledge of BM immune profiles and how these tumors respond to these therapies. In this project we direct specific focus on characterizing the immune phenotypes of BMs using known immune signatures associated with response to check point blockade.



Breast Cancer Biomarkers


PI: Mads H. Haugen
Numerous cancer drugs are not in use because we do not know which subgroup of patients obtains an adequate response. The mission of this project, which is supported by Kreftforeningen, is to develop diagnostic tools using expression of proteins and mRNA to reveal which patients could benefit from specific treatments. An important aspect is further to translate results from the laboratory into clinical use, so they can be of real benefit for the patients. Biomarkers at the proteomic level have been successfully used in clinical BC prognostics and diagnostics for decades (e.g. ER and Her2), primarily by means of immunehistochemistry (IHC). However, there is a practical limit in the number of markers that can be evaluated simultaneously, and future cancer diagnostics will likely also rely on information from signatures of multiple proteins simultaneously assessed.

In the NeoAva clinical trial we have developed a protein signature score by coupling protein expression in the tumor prior to treatment with tumor shrinkage during neoadjuvant treatment capable of predicting which BC patients that have a good response to treatment with bevacizumab in combination with chemotherapy. We are currently in the process of adapting use of this protein signature to the clinically usable platform NanoString.