Characterization of checkpoint receptor-mediated B-T-cell communication as novel targets for immunotherapies

检查点受体介导的 B-T 细胞通讯作为免疫疗法新靶点的表征

• 批准号: 525945623
• 负责人: Professor Dr. Thomas Dörner
• 金额: --
• 依托单位: Medizinische Klinik mit Schwerpunkt Rheumatologie und Klinische Immunologie (einschließlich Arbeitsbereich Physikalische Medizin)
• 依托单位国家: 德国
• 项目类别: Clinical Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/525945623?language=en
• 关键词: Characterization; checkpoint; receptor; mediated; cell

This project will perform deep clinical and immunological phenotyping of two antibody-mediated neurological diseases, such as autoimmune encephalitis (AIE) and myasthenia gravis (MG) to reveal underlying common or distinct dysregulated immune pathways. Our research will focus on pathological interactions between T and B/plasma cells, their altered composition and disturbed communication including altered expression of co-stimulatory and co-inhibitory checkpoint molecules (CM) in a disease-specific context. Immunological analysis will be flanked by continuous detection and analysis of physiological (neuro)monitoring parameters stored in a data warehouse connect (DWC WC; Philips) system during the entire stay at the neurointensive care unit (NICU), evaluation of neurological and outcome scores at NIC U and later follow-up. Obtained insights will be used to identify novel and individualized targets for more specific and innovative e.g. cell-based immunotherapies, but also to develop early predictive classifiers of treatment response to standard immunotherapies and long-term outcome by artificial intelligence-based algorithms. This would allow decision making for escalating treatment strategies at an early disease stage and thus improve patient outcome.

该项目将对两种抗体介导的神经系统疾病（如自身免疫性脑炎（AIE）和重症肌无力（MG））进行深入的临床和免疫学表型分析，以揭示潜在的常见或独特的免疫失调途径。我们的研究将集中在T和B/浆细胞之间的病理相互作用，它们的组成改变和通信紊乱，包括在特定疾病背景下共刺激和共抑制检查点分子（CM）的表达改变。在神经重症监护病房（NICU）的整个住院期间，免疫学分析将被连续检测和分析存储在数据仓库连接（DWC WC; Philips）系统中的生理（神经）监测参数，评估NICU的神经学和预后评分以及随后的随访。获得的见解将用于识别更具体和创新的新颖和个性化靶点，例如基于细胞的免疫疗法，但也用于开发对标准免疫疗法的治疗反应和基于人工智能的算法的长期结果的早期预测分类器。这将有助于在疾病早期制定逐步升级的治疗策略，从而改善患者的预后。