决定异体 CAR T 细胞排斥与扩增的细胞和分子机制
Cellular and molecular mechanisms determining allogeneic CAR T cell rejection and expansion.
我们评估了11例接受单一批次cemacabtagene ansegedleucel(cema-cel)治疗的大B细胞淋巴瘤患者,cemacabtagene ansegedleucel是一种异体抗CD19 CAR T产品。
英文原题:Cytokine release symptoms rather than syndromes: a call for granular reporting of cytokine-related adverse events in clinical trials.
转向标准化、以症状为驱动的报告模式,对于应对“免疫肿瘤学2.0”的复杂性至关重要。这样的框架将统一全球试验中的安全性评估,并最终优化下一代免疫疗法的治疗指数。
T细胞重定向疗法,尤其是CAR-T 细胞和双特异性抗体,已经彻底改变了血液系统恶性肿瘤的治疗。它们迅速向实体瘤领域扩展,同时免疫细胞因子和CD28共刺激双特异性抗体等下一代药物的出现,使细胞因子释放综合征(CRS)成为临床肿瘤学的焦点。然而,针对这些新型构建体缺乏统一的分级系统,仍然是药物开发和患者安全的关键障碍。当前的毒性管理依赖于不同的分级量表,导致报告不一致并阻碍了跨试验比较。一个根本性挑战在于CRS、输注相关反应及其他诊断之间在临床和时间上的显著重叠所造成的诊断模糊性。尽管发热、低血压和低氧是共同特征,但它们不同的病理生理驱动因素需要不同的治疗干预。
我们主张从总体综合征分级转向细粒度、纵向报告框架的范式转变。该方法优先精确记录症状动力学、具体干预措施(例如确切的血管加压药需求和氧流量)以及实时生物标志物整合。通过捕获高保真数据,研究人员可以回顾性应用不断发展的标准,并制定更具针对性、基于证据的管理算法。
BACKGROUND: T-cell redirecting therapies, notably chimeric antigen receptor T cells and bispecific antibodies, have revolutionized the treatment of hematologic malignancies. Their rapid expansion into solid tumors, alongside the emergence of next-generation agents, such as immunocytokines and CD28-costimulatory bispecifics, has brought cytokine release syndrome (CRS) to the forefront of clinical oncology. However, the absence of a unified grading system for these novel constructs remains a critical barrier to drug development and patient safety. Current toxicity management relies on disparate grading scales, leading to inconsistent reporting and hindering cross-trial comparisons. A fundamental challenge lies in the diagnostic ambiguity created by the significant clinical and temporal overlap among CRS, infusion-related reactions, and other diagnoses. Although fever, hypotension, and hypoxia are common denominators, their distinct pathophysiological drivers necessitate divergent therapeutic interventions. DESIGN: We advocate for a paradigm shift from aggregate syndromic grading toward a granular, longitudinal reporting framework. This approach prioritizes the precise documentation of symptom kinetics, specific interventions (e.g. exact vasopressor requirements and oxygen flow rates), and real-time biomarker integration. By capturing high-fidelity data, researchers can retrospectively apply evolving criteria and develop more tailored, evidence-based management algorithms. CONCLUSION: Transitioning to a standardized, symptom-driven reporting model is essential to navigate the complexities of 'Immuno-oncology 2.0.' Such a framework will harmonize safety assessments across global trials and ultimately optimize the therapeutic index of next-generation immunotherapies.
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