Abstract
One of the most promising approaches to cancer treatment is immunotherapy. Suppression of immune checkpoints in tumor tissue (anti-CTLA4, anti-PD1) using monoclonal antibodies has increased the overall survival of patients with some forms of skin melanoma and lung cancer. However, the percentage of patients responding to treatment varies from 20% to 40% depending on the type of cancer and the expression of target molecules by the tumor. The main source of failure of immunotherapy is the tumor microenvironment, which affects both tumor cells and immune cells, causing them to adapt to immunotherapeutic drugs. It is known that the architecture and cellular composition of the microenvironment act on various tumor parameters, promoting the recruitment of immunosuppressive cells into the tumor tissue, as well as the expression of checkpoint inhibitors, such as PD-L1, by tumor cells. Therefore, the complex composition of the tumor microenvironment must be taken into account when searching for new therapies and stratifying patients who may respond to immunotherapy. Therefore, in immunooncological studies, it is necessary to use three-dimensional cellular models that more fully reflect the architecture and cellular composition of the tumor. In this review, we evaluate three-dimensional cell models as tools for research in the field of immuno-oncology, as well as for personalized treatment selection, the search for new targets, and the optimization of existing cancer immunotherapies.