Abstract
Abstract Background: It is now clear that the tumor microenvironment drives response or resistance to therapy. More specifically, the stroma, vasculature and immune compartment shape tumor response to therapy. In addition, heterogeneity within a tumor and between metastatic sites will invariably affect the outcome of treatment. Due in large part to these biological complexities, predicting how treatment response varies among multiple metastatic sites may impact overall outcome remains poorly established. Methods: Here, we interrogated the genomic and transcriptomic profile of three metastatic lesions from a patient diagnosed with relapsed head and neck squamous cell carcinoma (HNSCC), refractory to second-line Pembrolizumab (PD-1 checkpoint blockade). In addition, we employed CANscript™, a patient-derived ex-vivo model, which uses live tissue to recapitulate the native 3D tumor microenvironment coupled with an algorithm-driven strategy to predict clinical response in the form of an S-Score (Majumder et al., Nat. Comm., 2015). Using this platform, we tested two combination therapies; carboplatin with gemcitabine, and adriamycin with cyclophosphamide. Moreover, we characterized the tumor microenvironment, following combination treatment, using a multiplexed immunohistochemistry (IHC) panel (Ki67, PanCK, CD3, CD4, CD8, DAPI). Results: We determined that the three metastatic sites displayed distinct transcription and whole exome signatures, prior to CANscriptTM. Based on CANscriptTM predicted responses (S-Score) for the two combinations tested, all three sites responded in a non-uniform manner. Interestingly, each site also displayed distinct patterns of proliferative immune subsets (Ki67 staining) and CD4:CD8 ratios, following treatment with each combination therapy. Conclusion: Together, these findings demonstrate that, due to the underlying genetic and tumor microenvironment heterogeneity, metastatic sites might each confer distinct clinical responses to the same drug regimen, even in immunotherapy-resistant disease. Moreover, we highlight the utility of ex-vivo profiling as a tool to predict therapeutic response - not only at the individual patient level, but also at the level of multiple metastatic sites from a single patient. These findings underscore the importance of characterizing the entire tumor-immune contexture under pressure anticancer drugs. Such information can revise our understanding of personalized cancer care, and may impact rational treatment options. Citation Format: Chukwuemeka Ikpeazu, Munisha Smalley, Baraneedharan Ulaganathan, Allen Thayakumar, Laura Majeiko, Jyothsana Ganesh, Basavaraja Shanthappa, Hans Gertje, Mark Lawson, Sara Lapomarda, Aaron Goldman. Case study: Non-uniform response to therapy in multiple metastatic is predicted using CANscriptTM, a live tissue, ex-vivo, platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-346.
