Profiling of tumour-immune heterogeneity in renal cell carcinoma: Next-generation radiogenomic biomarkers for immune checkpoint inhibition

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The systemic treatment approach to metastatic renal cell carcinoma (RCC) has been revolutionized in recent years by the identification of immune checkpoint signalling pathways and their therapeutic modulation by immune-checkpoint inhibitors, such as the PD-1 antibody nivolumab. Failure of treatment response in patient subgroups and acquired drug resistance in the course of therapy represent major barriers to successful checkpoint inhibitor treatment. In the absence of reliable biomarkers, identifying patients who may benefit from checkpoint blockade and defining criteria for treatment response are major challenges in the treatment planning. Established radiological criteria, which are primarily based on the evolution of tumour size, may not appropriately characterize the complex response to immunotherapy.The aims of the proposed project are to render pathomorphological characteristics as well as genetic, cellular and molecular biology processes during immune checkpoint blockage in RCCs "visible" using quantitative imaging parameters. For improved treatment planning, reliable, non-invasive biomarkers will be defined to predict and monitor treatment in an attempt to preselect patients who are most likely to benefit from checkpoint inhibitor therapy.In a prospective, multimodal approach, the complex and heterogeneous tumour immune microenvironment of RCC during immunotherapy is characterized by in-depth transcriptomic, proteomic, genomic, and pathological analysis. This comprehensive biologic dataset will be correlated with quantitative imaging parameters (radiogenomics approach). Based on multiparametric MRI, in combination with CT scans, bioinformatics algorithms will be applied to extract and analyze the totality of accessible image information in an automated manner in a high-throughput process. Following correlative analysis of the complex biological and imaging data, a radiogenomic map will be developed linking molecular, genetic and pathological features of RCC tumour tissue and its immune microenvironment with quantitative imaging features.The proposed imaging-based virtual biopsy approach will provide a large set of noninvasive, candidate biomarkers for predicting and monitoring response to immune checkpoint inhibitor therapy. Finally, the discovery of novel biomarkers in this study can help to tailor personalized immunotherapeutic strategies for RCC, with the potential to improve the prognosis of this disease.