Supported by the Lundbeck Foundation, researchers at DTU Health Tech together with collaborators from Copenhagen University and Danish Cancer Society have developed a new method for pinpointing which tumour regions are targeted by a drug.
A new method provides precise mapping of drug targeting to help fight glioblastoma, which is, besides being the most common type, the most aggressive type of brain cancer with a mortality rate of 100 percent. In Denmark, the average life expectancy after diagnosis is 14.3 months.
The reason behind these discouraging facts is on one hand that it is difficult to operate in the brain, on the other hand that glioblastoma is scattered with the cells of the brain making it difficult to remove the tumour surgically. At the same time, the so-called blood-brain-barrier blocks the access to the brain, preventing medication from entering the brain. Even internal elements native to the body, such as the immune system’s cells, usually have restricted access to the brain tissue.
The brain protects itself
”One of the major challenges in glioblastoma treatment is to make the tissue in the tumour absorb the therapeutic compounds. The blood-brain-barrier, the underlying basis of the blood-tumour-barrier, limits the entrance of foreign substances to the tissue. Even if a foreign substance did manage to cross the barrier, it could still risk getting kicked out of the tumour and transported back into the bloodstream”, Postdoc at DTU Health Tech Serhii Kostrikov explains.
As a researcher, Serhii Kostrikov is interested in finding an efficient method to make the brain absorb medication. Serhii Kostrikov and his colleagues regard their newly developed method for analysing the tissue to determine which tumour regions are targeted an important step on the way.
"One of the major challenges in glioblastoma treatment is to make the tissue in the tumour absorb the therapeutic compounds"
Huge datasets
”As described in our recently published paper, there are many obstacles in studying drug delivery to glioblastoma tissue. Even sections of tumour tissue from animals injected with a study drug and studied under a microscope can produce false results because of vasculature disruption due to sample preparation”, Serhii Kostrikov states.
However, using a technique making excised tumour tissue transparent and thus avoiding the need for tissue sectioning, allows for much more precise data.
“Such an imaging method provides large heterogeneous datasets that are challenging to process and analyse. We have solved this by developing advanced image analysis workflows, which utilize machine learning. With developed tools in hands, we can now precisely determine which tumor regions are targeted by a given drug. Furthermore, it also allows us to analyse the structure of tumor vessels and gain additional insights into why certain tumor regions are targeted more extensively than the others. It has not solved the issue on how to treat glioblastoma, but it is an essential step towards that goal.”
The next step is to implement the developed methods for large-scale pre-clinical studies as well as translate image analysis development into clinical research
Read the scientific paper in Communications Biology here