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

肾细胞癌肿瘤免疫异质性分析：用于免疫检查点抑制的下一代放射基因组生物标志物

基本信息

批准号：
426794388
负责人：
Dr. Dominik Deniffel
金额：
--
依托单位：
Lunenfeld Tanenbaum Research Institutess
依托单位国家：
德国
项目类别：
Research Fellowships
财政年份：
2019
资助国家：
德国
起止时间：
2018-12-31 至 2020-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/426794388?language=en
关键词：
Profiling tumour immune heterogeneity renal

项目摘要

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.

近年来，通过免疫检查点信号通路的鉴定和免疫检查点抑制剂（如PD-1抗体nivolumab）的治疗调节，转移性肾细胞癌（RCC）的全身治疗方法发生了革命性的变化。患者亚组的治疗反应失败和治疗过程中的获得性耐药是检查点抑制剂治疗成功的主要障碍。在缺乏可靠的生物标志物的情况下，确定可能受益于检查点阻断的患者和确定治疗反应标准是治疗计划中的主要挑战。现有的放射学标准，主要是基于肿瘤大小的演变，可能不能适当地描述对免疫治疗的复杂反应。拟议项目的目的是利用定量成像参数，在rcc免疫检查点阻断期间，呈现病理形态学特征以及遗传、细胞和分子生物学过程“可见”。为了改进治疗计划，将定义可靠的、非侵入性的生物标志物来预测和监测治疗，以尝试预先选择最有可能从检查点抑制剂治疗中受益的患者。在一项前瞻性、多模式的方法中，通过深入的转录组学、蛋白质组学、基因组学和病理学分析，研究了免疫治疗期间RCC复杂和异质性的肿瘤免疫微环境。这个全面的生物数据集将与定量成像参数（放射基因组学方法）相关。基于多参数MRI，结合CT扫描，生物信息学算法将在高通量过程中以自动化的方式提取和分析可访问的图像信息。在对复杂的生物学和影像学数据进行相关分析后，将开发一种放射基因组图谱，将RCC肿瘤组织及其免疫微环境的分子、遗传和病理特征与定量影像学特征联系起来。提出的基于成像的虚拟活检方法将提供大量无创的候选生物标志物，用于预测和监测对免疫检查点抑制剂治疗的反应。最后，本研究中发现的新的生物标志物可以帮助为RCC量身定制个性化的免疫治疗策略，有可能改善这种疾病的预后。