Background Cancer immunotherapy research is expanding to include a more robust understanding of the mechanisms of treatment response and resistance. Identification of drivers of pro-tumor and anti-tumor immunity during treatment offers new strategies for effective alternative or combination immunotherapies. Currently, tissue or blood samples are collected and analyzed, then dichotomized based on clinical end points that may occur months or years after tissue is collected. While overall survival is ultimately the desired clinical outcome, this dichotomization fails to incorporate the nuances that may occur during an anti-tumor response. By failing to directly measure immune activation at the time of sampling, tumors may be misclassified and potentially obscure important biological information. Non-invasive techniques, such as positron emission tomography (PET), allow for global and quantitative measurements of cancer specific processes and are widely used clinically to help manage disease. Methods We have previously developed a novel PET agent that can non-invasively quantify granzyme B release in tumors and have demonstrated its ability to predict response to checkpoint inhibitor therapy in multiple murine models of cancer. Here, we used the quantitative measurement of granzyme B release as a direct and time-matched marker of immune cell activation in order to determine immune cell types and cytokines that correlate with effective checkpoint inhibitor therapy in both tumors and tumor-draining lymph nodes. Results Through PET imaging, we were able to successfully distinguish distinct microenvironments, based on tumor type, which influenced immune cell subpopulations and cytokine release. Although each tumor was marked by functionally distinct pathways of immune cell activation and inflammation, they also shared commonalities that ultimately resulted in granzyme B release and tumor killing. Conclusions These results suggest that discrete tumor immune microenvironments can be identified in both responsive and non-responsive tumors and offers strategic targets for intervention to overcome checkpoint inhibitor resistance.

Purpose: Hypoxia is a common characteristic of many tumor microenvironments, and it has been shown to promote suppression of antitumor immunity. Despite strong biological rationale, longitudinal correlation of hypoxia and response to immunotherapy has not been investigated. Experimental Design: In this study, we probed the tumor and its surrounding microenvironment with 18F-FMISO PET imaging to noninvasively quantify tumor hypoxia in vivo prior to and during PD-1 and CTLA-4 checkpoint blockade in preclinical models of breast and colon cancer. Results: Longitudinal imaging identified hypoxia as an early predictive biomarker of therapeutic response (prior to anatomic changes in tumor volume) with a decreasing standard uptake value (SUV) ratio in tumors that effectively respond to therapy. PET signal correlated with ex vivo markers of tumor immune response including cytokines (IFNγ, GZMB, and TNF), damage-associated molecular pattern receptors (TLR2/4), and immune cell populations (macrophages, dendritic cells, and cytotoxic T cells). Responding tumors were marked by increased inflammation that were spatially distinct from hypoxic regions, providing a mechanistic understanding of the immune signaling pathways activated. To exploit image-guided combination therapy, hypoxia signal from PET imaging was used to guide the addition of a hypoxia targeted treatment to nonresponsive tumors, which ultimately provided therapeutic synergy and rescued response as determined by longitudinal changes in tumor volume. Conclusions: The results generated from this work provide an immediately translatable paradigm for measuring and targeting hypoxia to increase response to immune checkpoint therapy and using hypoxia imaging to guide combinatory therapies.

Advancements in monitoring and predicting of patient-specific response of triple negative breast cancer (TNBC) to immunotherapy (IMT) with and without chemotherapy are needed. Using granzyme B-specific positron emission tomography (GZP-PET) imaging, we aimed to monitor changes in effector cell activation in response to IMT with chemotherapy in TNBC. TNBC mouse models received the paclitaxel (PTX) ± immune checkpoint inhibitors anti-programmed death 1 (anti-PD1) and anti-cytotoxic T-lymphocyte 4 (anti-CTLA4). GZP-PET imaging was performed on treatment days 0, 3, and 6. Mean standard uptake value (SUV_mean), effector cell fractions, and SUV histograms were compared. Mice were sacrificed at early imaging timepoints for cytokine and histological analyses. GZP-PET imaging data revealed differences prior to tumor volume changes. By day six, responders had SUV_mean ≥ 2.2-fold higher (p < 0.0037) and effector cell fractions ≥ 1.9-fold higher (p = 0.03) compared to non-responders. IMT/PTX resulted in a significantly different SUV distribution compared to control, indicating broader distribution of activated intratumoral T-cells. IMT/PTX resulted in significantly more necrotic tumor tissue and increased levels of IL-2, 4, and 12 compared to control. Results implicate immunogenic cell death through upregulation of key Th1/Th2 cytokines by IMT/PTX. Noninvasive PET imaging can provide data on the TNBC tumor microenvironment, specifically intratumoral effector cell activation, predicting response to IMT plus chemotherapy.

The adaptive immune response plays a critical role in detecting, eliminating, and creating a memory towards foreign pathogens and malignant cells. Demonstration of the specific and effective target killing of T cells in cancer has reignited interest in the study and therapeutic manipulation of the interaction between tumor and immune system. To both improve therapeutic efficacy and reduce adverse events, accurate monitoring of the activation of T cells is required. A number of approaches to monitoring not just the presence, but importantly the activation of T cells have been developed. Herein, we review the recent advances in T cell activation imaging and future directions for potential implementation into clinical utility.