Biophysical analysis of Immunotherapy and Cancer modeling

Sammanfattning: Accounting for 10 million deaths and 20 million new cases every year, cancer is one of the most common causes of death. The interest in trying to understand this lethal disease using mathematical models has increased steadily for many decades. Methods for boosting the immune system to better fight cancer (immunotherapy) have also been long present. However, the full potential of immunotherapy methods is not yet understood due to the immune system's complexity. The immune system naturally fights cancer, but it is not able to keep up when tumors grow too quickly. This is where immunotherapy aims to enhance the immune system to avoid and reverse tumor escape. Existing immunotherapies only work for some cancers and patients, but a better understanding of the cancer-immune dynamics could lead to new and reliable cancer treatments. Experimental images of tumor tissue, with single-cell resolution, are here shown in order to motivate the use of mathematical models for studies of cancer-immune dynamics. The behavior of individual immune cells is (through literature review) concluded to be governed by interactions with other immune cells. For this reason, the development of effective immunotherapies relies on the understanding of these cell-cell interactions, where spatial aspects are also believed to be of importance. This review explores immunotherapy and mathematical cancer modeling by considering various cancer-immune interactions. The review aims to allow researchers from research fields outside of biology and medicine to find interest and potential in the study of immunotherapy.