Abstract 3681: A patient derived ex vivo platform CANScript™ predicts distinct therapeutic outcomes to multiple PD-1 checkpoint inhibitors in single tumor biopsies

Abstract

Background: Emerging clinical evidence using immunotherapy in recent years has demonstrated its power to suppress tumor growth by releasing the brakes on the immune system. For example, blockade of immune checkpoints, such as PD-1, has revolutionized treatment options for patients with aggressive cancers such as head and neck squamous cell carcinoma (HNSCC). However, clinical responses to PD-1 inhibition vary widely among patients while majority of them do not show any anti-tumor response. Multiple FDA-approved drugs against the same immune checkpoints have resulted in globally distinct outcomes in the clinic. There is a huge unmet need to understand these disparities at the individual patient level and to maximize the clinical benefits of these agents. Methods: Here, we employed a patient-derived ex vivo model, CANScript™ (Majumder B et al. Nature Commun 2015 Feb 27;6:6169 and Goldman A et al. Nature Commun 2015 Feb 11;6:6139), which recreates the native 3D tumor microenvironment, autocrine-paracrine dynamic and response to therapy by incorporating fresh tumor tissue and autologous immune cells with immunotherapy agents. Utilizing late stage HNSCC (N=50) we interrogated phenotypic response to two FDA-approved PD-1 inhibitors, Pembrolizumab (KEYTRUDA) and Nivolumab (OPDIVO). To do this, we used a comprehensive panel of immunological assays to evaluate changes in the immune compartments by flowcytometry and immunohistochemistry (primarily CD8, CD45, FOXP3, CXCR4, CD68, PDL1, PD1), multiplex cytokine profiling (IL6, IL8, IFN-g, IL10, IL12, Perforin, GranzymeB), along with functional/phenotypic effects including tumor proliferation, histological changes and cell death. Results: The data demonstrated that CANScript™ preserves the tumor-immune contexture and native heterogeneity across different clinical stages and patients. Importantly, we observed that PD-1 blockade resulted in patient-specific therapeutic response, which was characterized by differential distribution and maintenance of infiltrating CD8+ and CD4+ lymphocytes, distinct patterning of cytokines linked to functional dysregulation, and changes in tumor proliferation and apoptosis. Interestingly, data suggest that both Pembrolizumab and Nivolumab act on the same immune network axis but trigger functionally diverse phenotypes in the tumor immune compartment and distinct antitumor effects within an individual patient tumor. Conclusion: Together, these findings demonstrate the utility of CANScript™ as an ex vivo platform to predict therapeutic response of immune checkpoint inhibitors at the individual patient level. It also highlights mechanistic variations that could impact clinical outcome of these agents having the same molecular target. Such information can re-shape our understanding of patient selection and rational combinations for novel immune checkpoint inhibitors. Citation Format: Padhma Radhakrishnan, Vasanthakumar Sekar, Nilesh Brijwani, Priyanka Chevour, Babu Balakrishnan, Dency D Pinto, Muthusami Oliyarasi, Debapriya G. Mehrotra, Manjusha Biswas, Sabitha K S, Kodaganur S. Gopinath, Arkasubhra Ghosh, M s Ganesh, Ashok M. Shenoy, Saravanan Thiyagarajan, Biswanath Majumder, Aaron Goldman. A patient derived ex vivo platform CANScript™ predicts distinct therapeutic outcomes to multiple PD-1 checkpoint inhibitors in single tumor biopsies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3681. doi:10.1158/1538-7445.AM2017-3681

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Cancer Immunotherapy and Personalized Medicine: Emerging Technologies and Biomarker Based Approaches

“…Excitingly, this platform demonstrates the first use for dynamic cellular heterogeneity, and real-time analysis of the tumor-immune contexture under pressure of immune checkpoint inhibitors. For example, Mitra recently demonstrated the flexibility of the platform to the assay to capture changes to the T-cell immune repertoire, and help predict the clinical efficacy of multiple immuno-oncology agents, such as immune checkpoint inhibitors [ 52 , 53 ]. Indeed, by mapping the role of T-regulatory (T reg ) cells in the presence or absence of multiple PD-1 checkpoint blockade, their research team elucidated that antitumor outcomes can be unique within a single patient sample.…”