Granzyme B PET imaging of immune-mediated tumor killing as a tool for understanding immunotherapy 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.

The Effectiveness of Checkpoint Inhibitor Combinations and Administration Timing Can Be Measured by Granzyme B PET Imaging.

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.

Soil microbial community responses to multiple experimental climate change drivers.

Researchers agree that climate change factors such as rising atmospheric [CO2] and warming will likely interact to modify ecosystem properties and processes. However, the response of the microbial communities that regulate ecosystem processes is less predictable. We measured the direct and interactive effects of climatic change on soil fungal and bacterial communities (abundance and composition) in a multifactor climate change experiment that exposed a constructed old-field ecosystem to different atmospheric CO2 concentration (ambient, +300 ppm), temperature (ambient, +3 degrees C), and precipitation (wet and dry) might interact to alter soil bacterial and fungal abundance and community structure in an old-field ecosystem. We found that (i) fungal abundance increased in warmed treatments; (ii) bacterial abundance increased in warmed plots with elevated atmospheric [CO2] but decreased in warmed plots under ambient atmospheric [CO2]; (iii) the phylogenetic distribution of bacterial and fungal clones and their relative abundance varied among treatments, as indicated by changes in 16S rRNA and 28S rRNA genes; (iv) changes in precipitation altered the relative abundance of Proteobacteria and Acidobacteria, where Acidobacteria decreased with a concomitant increase in the Proteobacteria in wet relative to dry treatments; and (v) changes in precipitation altered fungal community composition, primarily through lineage specific changes within a recently discovered group known as soil clone group I. Taken together, our results indicate that climate change drivers and their interactions may cause changes in bacterial and fungal overall abundance; however, changes in precipitation tended to have a much greater effect on the community composition. These results illustrate the potential for complex community changes in terrestrial ecosystems under climate change scenarios that alter multiple factors simultaneously.