MR molecular imaging for monitoring and predicting tumor responses to immunotherapy.

Background: While immunotherapies show great promise in cancer treatment, variability in patient responses warrant the need for improved methods to assess early responses and guide precision therapy. The tumor microenvironment (TME) plays a critical role in antitumor immunity and tumor response to immunotherapy. Critically, TME components and their crosstalk with immune cells can be leveraged as a prognostic marker for therapeutic response. This study evaluated the use of magnetic resonance molecular imaging (MRMI) targeting the TME protein extradomain B fibronectin (EDB-FN), which is a lymphokine secreted by activated T lymphocytes and a marker of the epithelial-to-mesenchymal transition (EMT) in aggressive tumor cells. MRMI of EDB-FN was evaluated within the tumor extracellular matrix and was correlated with immunotherapy-related outcomes. Methods: C57BL/6 mice bearing orthotopic KPC pancreatic tumors were treated with a novel immune checkpoint inhibitor (VISTA-blocking antibodies), a vaccine (mutant KRAS^G12D peptide with TLR7/8/9 agonists), or a combination of both. MRMI with an EDB-FN-specific contrast agent, MT218, was used to image tumor responses during treatment. T₁-weighted MRI (fast spin echo and FLASH sequences) was acquired before, during, and after tumor treatment. Tumor signal enhancement patterns were analyzed to assess treatment response. EDB-FN expression and the infiltration of CD4⁺ and CD8⁺ T lymphocytes in the tumors were determined by immunohistochemistry (IHC) and immunofluorescence (IF) staining, respectively, and correlated with MRMI observations, tumor response, and therapeutic outcomes. Results: MT218-MRMI revealed distinctive signal enhancement patterns across different treatments. These patterns were detected as early as two weeks after treatment initiation and correlated strongly with EDB-FN expression and CD4⁺ and CD8⁺ T cell infiltration, as confirmed by IHC and IF. Signal profiles corresponded to known TME phenotypes: immune desert, immune excluded, and immune inflamed, which were associated with non-response, partial response, and complete response, respectively. By four weeks post-treatment, MRMI criteria successfully distinguished complete responders from partial responders. Over a 200-day monitoring period, outcome prediction showed complete (100%) long-term disease-free survival in complete responders, 24-27% survival in partial responders, and no (0%) survival in non-responders and those with stable disease. Conclusion: MT218-MRMI non-invasively distinguishes tumor response patterns with significant potential for early prediction of therapeutic outcomes and timely optimization of treatment strategies. While further validation is needed for clinical translation, these findings demonstrate MT218-MRMI's promise as a tool for monitoring immunotherapy response in pancreatic cancer and underscore its potential utility for precision immunotherapy.