Coupling a phenotypic assay-based platform, multi-plex IHC and quantitative pathology to predict anti-tumor efficacy to immune checkpoint blockade in melanoma.

Abstract

e21041 Background: Emerging clinical evidence using immunotherapy suggests there is extraordinary antitumor potential by releasing the brakes on the immune system. However, clinical responses vary widely among patients, and a majority do not experience positive response. There is a huge unmet need to understand these disparities at the individual patient level. Methods: Here, we describe a quantitative approach to predict the antitumor effect of immune checkpoint blockade using a live-tissue ex-vivoplatform technology, CANscript™, which captures the native 3D tumor microenvironment. Utilizing fresh melanoma resections we interrogated phenotypic changes to the tumor-immune contexture in response to PD-1 and PD-L1 inhibitors in combination and as single agents. To do this, we used a multi-plexed immunohistochemistry (primarily CD8, CD45, FOXP3, CXCR4, CD68, PDL1, PD1, ERK-phosphorylation), and quantification of immune cell migratory potential, which were correlated to antitumor indications such as tumor cell proliferation, and cell death. Results: The data confirmed that CANScript™ preserves the tumor-immune contexture and native heterogeneity across different patients. Importantly, we observed that PD-1 and PD-L1 blockade resulted in patient-specific therapeutic response, which was characterized by differential, quantitatively distinct distribution and infiltration of immune cells, distinct patterning of cytokines linked to functional dysregulation, and changes in tumor proliferation and apoptosis. Interestingly, the data demonstrated unique immune signatures associated with single agent vs. combination therapy, inducing functionally distinct mechanisms in the tumor immune compartment, and disparate antitumor effects within an individual patient tumor. Conclusions: Together, these findings demonstrate that quantitative pathology can help predict therapeutic response of immune checkpoint inhibitors at the individual patient level. Such information can re-shape our understanding of patient selection and rational combinations for novel immune checkpoint inhibitors.