Knævelsrud's project group


  • How do multicellular organisms turn off autophagy?

Cells in a living organism need to be able to readily respond to changes in nutritional status. Upon starvation, certain tissues respond by autophagy, to provide energy and building blocks to sustain essential cellular functions. Importantly, these cells must also turn off autophagy when nutrient supplies are replenished, because unrestricted autophagy is harmful to cellular fitness. Surprisingly little is known about how autophagy is terminated, especially in the context of a multicellular organism. We work on uncovering and understanding novel mechanisms of autophagy termination, using Drosophila as a model.


  • How can autophagy be exploited for biomarkers or therapy targets in kidney cancer?

Each year around 800 people are diagnosed with kidney cancer in Norway. Whereas localized cancer can be cured by surgery, the challenge is to identify which patients will progress to metastatic cancer and also to identify the best treatment for each of those patients. We are working on the use of markers of autophagy to address these needs in different subtypes of renal cell carcinoma and also in the inherited predisposition for renal cancer associated with Birt-Hogg-Dubé syndrome.


  • Fruit flies as a tool to find new therapies for leukemia.

Chromosomal rearrangements of the MLL gene are associated with development of high-risk acute leukemia. MLL-rearranged (MLL-r) leukemia is treated with aggressive chemotherapy, but patients often relapse and survival rates are dismal. Clearly, there exists a need for novel forms of therapy. However, development of new treatment is hampered by our very limited understanding of the genetic framework that underpins MLL-r leukemia. We are working on unraveling this genetic framework, by taking advantage of the of the powerful genetic tools of Drosophila in a fly model of MLL-r leukemia, where we perform genetic modifier screens and study effects on the hematopoietic system of Drosophila larvae.


Enserink 'group


  • Identification of synergistic drug interactions

Targeted cancer therapy has revolutionized how patients are treated. However, targeted therapies often fail due to various reasons, including development of drug resistance by the cancer cells. The success of therapy for childhood acute lymphocytic leukemia (ALL), which consists of a combination of various drugs, demonstrates that combinations of drugs can provide a much longer-lasting response. However, identifying synergizing drug combinations is a major challenge. We have developed a platform for screening large numbers of drug combinations at high resolution, and created an end-to-end bioinformatics pipeline to design, execute and analyze results from such large-scale drug combination screens. We are now using this pipeline to identify novel, synergistic drug combinations in melanoma, breast cancer and acute myeloid leukemia.


  • Bioinformatics tools for identification of cancer cell vulnerabilities 

Big datasets have been created by ourselves and by numerous other research groups where large amounts of information is collected about cancer cells. However, analysing such datasets for vulnerabilities of cancer cells that can be therapeutically exploited is a major challenge. We have created several tools that can be used to analyze genetic screens in cancer cells (such as CRISPR/Cas9 screens), as well as tools to analyze drug screening datasets for better forecasting of treatment responses, with the main focus on leukemia.


  • Genome-wide profiling of autophagy

Autophagy is a process that helps cells survive periods of starvation. While the basic machinery of autophagy has been characterized in substantial detail, the upstream pathways that feed into this machinery are much less understood. We have recently completed a genome-wide study in which we studied the activation and inactivation of autophagy in the model organism budding yeast ( Saccharomyces cerevisiae ) during changing nutrient conditions. We developed novel bioinformatics tools to study this dataset, which revealed the genome-wide map of cellular pathways that are connected to this process. This has provided us with starting points for numerous follow-up studies, which we are currently pursuing.



Published Apr. 29, 2022 11:35 AM - Last modified May 2, 2022 11:47 AM