While cancer immunotherapy can produce dramatic responses, only a minority of patients respond to treatment. Reliable response biomarkers are needed to identify responders, and conventional imaging modalities have not proved adequate. Here, we provide a preclinical proof of concept for the use of granzyme B, a downstream effector of tumoral cytotoxic T cells, as an early biomarker for tumors responding to immunotherapy. We designed novel PET imaging probes for the murine and human granzyme B isoforms that specifically and quantitatively bind granzyme B. Immunotherapy-treated mice were imaged prior to therapy-induced tumor volume reduction. Imaging distinguished treated responders from nonresponders with excellent predictive ability. To assess the clinical value of a granzyme B imaging paradigm, biopsy specimens from melanoma patients on checkpoint inhibitor therapy were analyzed. A marked differential in granzyme B expression was observed between treated responders and nonresponders. Additionally, our human probe was able to specifically detect granzyme B expression in human samples, providing a clear candidate for clinical application. Overall, our results suggest granzyme B PET imaging can serve as a quantitatively useful predictive biomarker for efficacious responses to cancer immunotherapy. Cancer Res; 77(9); 2318–27. ©2017 AACR.

Purpose: The lack of a timely and reliable measure of response to cancer immunotherapy has confounded understanding of mechanisms of resistance and subsequent therapeutic advancement. We hypothesized that PET imaging of granzyme B using a targeted peptide, GZP, could be utilized for early response assessment across many checkpoint inhibitor combinations, and that GZP uptake could be compared between therapeutic regimens and dosing schedules as an early biomarker of relative efficacy. Experimental Design: Two models, MC38 and CT26, were treated with a series of checkpoint inhibitors. GZP PET imaging was performed to assess tumoral GZP uptake, and tumor volume changes were subsequently monitored to determine response. The average GZP PET uptake and response of each treatment group were correlated to evaluate the utility of GZP PET for comparing therapeutic efficacy. Results: In both tumor models, GZP PET imaging was highly accurate for predicting response, with 93% sensitivity and 94% negative predictive value. Mean tumoral GZP signal intensity of treatment groups linearly correlated with percent response across all therapies and schedules. Moreover, GZP PET correctly predicted that sequential dose scheduling of PD-1 and CTLA-4 targeted therapies demonstrates comparative efficacy to concurrent administration. Conclusions: Granzyme B quantification is a highly sensitive and specific early measure of therapeutic efficacy for checkpoint inhibitor regimens. This work provides evidence that GZP PET imaging may be useful for rapid assessment of therapeutic efficacy in the context of clinical trials for both novel drugs as well as dosing regimens.

Immune checkpoint inhibitors have made rapid advances, resulting in multiple Food and Drug Administration (FDA)-approved therapeutics that have markedly improved survival. However these benefits are limited to a minority sub-population that achieves a response. Predicting which patients are most likely to benefit would be valuable for individual therapy optimization. T cell markers such as CD3 represent a more direct approach than pre-treatment biopsy or genetic screening to monitoring tumor immune response, by directly examining active recruitment of T cells responsible for cancer cell-death. This approach could be especially effective as numerous different therapeutic strategies emerge, decreasing the need for drug-specific biomarkers and instead focusing on T cell infiltration, which has been previously correlated with treatment response. A CD3 positron emission tomography (PET) imaging agent targeting T cells was synthesized to test the role of such imaging as a predictive marker. The ⁸⁹Zr- p-isothiocyanatobenzyl-deferoxamine (DFO)-CD3 PET probe was assessed in a murine tumor xenograft model of colon cancer anti-cytotoxic T lymphocyte antigen-4 (CTLA-4) immunotherapy. Imaging on day 14 revealed two distinct groups of mice, stratified by PET signal intensity. Although there was no statistical difference in tumor volume on the day of imaging, in the high PET uptake group subsequent measurements revealed significantly smaller tumors than both the low-CD3 PET uptake group and untreated control. In contrast, low-CD3 PET uptake and untreated control mice demonstrated no statistical difference in size. These findings indicate that high-CD3 PET uptake in the anti-CTLA-4 treated mice is correlated with subsequent reduced tumor volume, and is a predictive biomarker of response.

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.