Mathematicians and doctors from the University of Bonn in Germany have developed a computational model to select an effective treatment for cancer therapy. In addition, the method allows us to understand why some tumors are hard to fight. A study published in the journal Scientific Reports.
One of the biggest challenges in cancer treatment is that malignant tumors develop resistance to the drugs. Initially effective therapy is followed by relapse, and sometimes the result of non-existent. The reason for this lies in the emergence of cancer cells resistant to therapy.
Some cells of the immune system such as T cells, to fight cancer tumors by identifying cells by specific proteins on the membrane. However, earlier studies have shown that if the immune reaction proceeds in the course of treatment, the cancer cells become invisible to lymphocytes.
In the new study, the researchers developed a mathematical model describing this effect and allowing to consider it in creation of new methods of treatment. It is based on the estimation of random fluctuations in the number of cancer cells and T-lymphocytes. Because cancer is a complex system, a certain way of reacting to the environment, the therapy can only be effective if it takes into account such a reaction. First results have shown that a promising approach may be an immune therapy with several types of lymphocytes.
On the other hand, the wrong treatment may even cause mutations in cancer cells and contribute to the development of aggressive forms of malignant tumor instead of fighting it.
However, it is necessary to check whether the random fluctuations in the growth of the tumor can influence treatment success or is it just “computer” phenomenon. According to the researchers, numerical modeling of cancer allows you to attract more mathematicians to work in the medical field and, conversely, to draw the attention of physicians to the possibility of using probabilistic approaches in developing therapeutic methods.
