Glioblastoma on a chip
Brain cancer: new test helps to catch the most dangerous cells
Anatoly Glossev, Vesti
Scientists have developed a system that identifies the most dangerous cancer cells. By isolating the most aggressive cells, biologists can study the work of their genes and create drugs aimed at suppressing them. And the test will also help predict the course of the disease.
The researchers tested their development on glioblastoma, the most common and aggressive type of brain cancer in adults.
The achievement is described in a scientific article published in the journal Nature Biomedical Engineering (Wong, et al., A microfluidic cell-migration assay for the prediction of progression-free survival and recurrence time of patients with glioblastoma).
Cancer cells consume the body's resources, but do not perform the functions of healthy cells. If there were few such "selfish" cells, the body, so to speak, would easily feed the parasite. But cancer cells multiply and displace the surrounding healthy cells. Moreover, there is no limit of 52 divisions for them, which limits the reproduction of their healthy "brethren". In the end, an organ affected by an overgrown tumor loses the ability to function normally.
In addition, cancer cells are mobile. Moving through the body, they create new tumors (metastases) in various places, often in vital organs.
Thus, the main danger of cancer cells lies in their two "superpowers": unlimited reproduction and amazing mobility. The new test determines the most dangerous tumor cells, focusing on these two parameters.
The ability of cells to reproduce is determined by the growth rate of "descendants". And to measure mobility, Y-shaped tubes with a diameter of a fraction of a millimeter are used. The most mobile cells move through these tubes the fastest, contracting and pushing themselves forward.
Last year, the group demonstrated that this scheme works successfully with breast cancer cells. Now biologists have tested it on cells of aggressive brain cancer – glioblastoma.
The idea is to separate the most aggressive cells and study them thoroughly. This will make it possible to create drugs aimed specifically at the cells that play the most important role in the growth and metastasis of the tumor.
"Since [now] we have a unique opportunity to identify these deadly cells, we propose to use this platform to test potential therapeutic agents to effectively block the invasion and/or spread of these cells and, ultimately, improve patient survival by applying precision medicine in practice," explains the head of the research group Konstantinos Konstantopoulos (Konstantinos Konstantopoulos) from Johns Hopkins University in a press release New Test Can Target and Capture Most Lethal Cells in Fatal Brain Cancer.
Scientists have already taken the first steps in this direction. Having isolated the most aggressive glioblastoma cells, biologists sequenced their RNA. In this way, the experts determined which genes in these cells work (are expressed), and which are inactive. The authors did the same with ordinary tumor cells and compared the results. It turned out that there are a number of genes whose increased activity makes the cancer cell very aggressive.
Another possible application of the test is prognostics. It is clear that the aggressiveness of the entire tumor depends on how active its "advanced" cells are. Therefore, the new test will help predict the course of the disease and in the future choose the optimal treatment. And if this type of cancer still does not respond well to therapy, then at least the patient will know how much time he has. This is the case with glioblastoma, which kills a person for a period of 6 to 29 months.
To test the prognostic potential of the test, the authors examined the preserved cells of 28 deceased patients. In 85% of cases, the test results allowed us to correctly determine the rate of the disease.
Biologists performed the same analysis with the cells of five patients whose disease was still only in the initial stage. In all these cases, the aggressiveness of the tumor was predicted correctly.
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