TargEting the Nectin fAmily to boost Cancer ImmuniTY
Immune checkpoint Inhibitors (ICI) have demonstrated therapeutic efficacy in many cancer types, but only subgroups of patients have durable responses. One reason is the enormous complexity of interactions within the TME. Identifying the underlying networks to develop complementary treatment strategies beyond existing ICIs is a central challenge for basic and clinical research. With this end in view, the nectin/nectin-like molecules are an emerging class of immune regulators within the TME. They interact with both T cell-inhibitory (TIGIT/CD96/CD112R) and activating receptors (CD226). However, our understanding on the expression, spatial context, function and potential redundancy of nectin family members in the TME is in its infancy. The TENACITY team seeks to (a) systematically map the expression landscape of nectin family members in the TME across different cancer types (b) assess their impact for the efficacy of ICIs and (c) develop single-variable domain nanobodies to target multiple nectin family members. In a concerted effort, we will determine the spatial context of nectin family members in tumor samples from fully annotated cohorts of patients with melanoma, head and neck squamous cell carcinoma, renal and lung cancer using cutting edge ultra-highplex immunofluorescence analyses (CODEX.). In addition, we will integrate transcriptomic and driver mutation landscapes to further elucidate the importance of nectin/nectin-like molecules for the efficacy of ICIs. Finally, we will generate novel diagnostic probes and potential biologicals using our nanobody platform. To enable the clinical development of potential lead-candidates, we will determine the therapeutic efficacy of our nanobodies using patient-derived tumor organoids from aforementioned cancer types. In TENACITY, we will shed light and untangle the complexity of nectin family members in cancer to enable evidenced-based combination immunotherapies and to develop innovative treatment approaches.
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This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No. 964264.