Sven Nelander’s research on the systems biology of neural cancers
Invasion routes of glioblastoma and their patient-specific vulnerabilities
Each year over 200,000 people worldwide are affected by the brain tumor glioblastoma. The disease is notorious for its aggressive course and still lacks a treatment. A key difficulty lies in the tumour cells' ability to grow diffusely through the brain. Such diffusely growing cells, which occur in both nerve pathways and along blood vessels, are impossible to remove surgically. Therefore, it is important to understand exactly how the invasion takes place, which genes are behind it, and whether diffusely growing cells can be knocked out with drugs.
Until now, there has been a lack of effective ways to answer these questions. Our team has developed an integrated strategy based on a new biobank of 100 PDX models (patient-derived xenografts), established at our centre (Johansson et al, Cell Reports; unpublished data). The PDX models can be thought of as replicas of the patient tumours. This means that copies of the original tumour can be recreated and studied in a laboratory environment.
Our initial studies show that the tumour cells from different patients differ in terms of tumour growth. We have also shown that computational algorithms can connect such differences to both genes and drugs, which makes the biobank a very powerful and unique research tool.
Data-driven drug discovery for pediatric neural cancers
Nervous system malignancies, such as medulloblastoma, diffuse midline glioma and neuroblastoma, cause a high proportion of childhood cancer deaths. Even though the underlying mutations are often known in these cancers, they still remain out-of-reach from traditional classes of oncology drugs.
To address this problem, our team is exploring how innovative analyses of big data sets can be used to discover new therapeutics. In one of our recent projects, we developed a new algorithm, TargetTranslator, which could identify new treatments for neuroblastoma (Almstedt et al, Nature Communications 2020). In a recent proof of concept study, we mapped the dynamic changes that occur in brain tumour cells (Larsson et al, Molecular Systems Biology 2020).
Presently, our team is exploring how data-driven methods can be used to target a broader range of pediatric cancers, including medulloblastoma and diffuse midline glioma. In a more theoretical line of work, we are also exploring how ideas from statistical physics can help us understand how tumor cells can be targeted. Looking ahead, this research can help meet a need for new therapeutics against these difficult cancers.