NIMG-41. NON-INVASIVE TRACKING OF T-CELL RECRUITMENT TO THE TUMOR MICROENVIRONMENT IN A MURINE GLIOMA MODEL BY HIGH FIELD CELLULAR MRI. (14th November 2022) - Hunger, Jessica; Schregel, Katharina; Fischer, Manuel; Agardy, Dennis; Sturm, Volker; Karimian-Jazi, Kianush; Bunse, Theresa; Heiland, Sabine; Wick, Wolfgang; Bendszus, Martin; Platten, Michael; Breckwoldt, Michael
Abstract: Gliomas are characterized by increased T cell exhaustion and poor T cell infiltration into the tumor as well as an overall highly immunosuppressive tumor microenvironment (TME). Response rates in preclinical glioma models and patients to promising new therapeutic approaches in the field of immunotherapies - such as checkpoint blockade, vaccines and adoptive therapy with chimeric antigen receptor (CAR) or T cell receptor (TCR)-transgenic T cells - remain heterogeneous. This demonstrates the need for non-invasive tracking of T cell recruitment to the TME in order to monitor T cell activating immunotherapies, adapt therapeutic strategies and predict treatment outcome. Iron oxide nanoparticles (NP) can be visualized non-invasively by magnetic resonance imaging (MRI) and dedicated MRI sequences such as T2* mapping. Using isolated murine T cells cultures we show that labeling of T cells with iron oxide NP as contrast agent is feasible and does not impact T cell viability and functionality as assessed by cytokine secretion and antigen-specific killing activity in vitro . We demonstrate that adoptively transferred T cells can be visualized intratumorally in a murine glioma model by high field MRI at 9.4 Tesla with high sensitivity and that T cells can be tracked non-invasively in a time course of over one week. Ongoing work assesses preclinical efficacy of adoptive T cell therapy targeting well characterized model antigens expressed in experimental gliomas using longitudinal MRI to visualize spatial and temporal T-cell dynamics in the TME. Correlative methods include immunohistochemistry, flow cytometry, tissue clearing and ultramicroscopy. We hypothesize that T cell distribution and numbers may predict therapeutic efficacy and correlate with treatment outcome in experimental gliomas.