CD81 通过阻断 CD274/PD-L1 的选择性自噬降解驱动放射抵抗性胶质母细胞瘤的免疫逃逸
CD81 drives immune evasion in radioresistant glioblastoma by blocking selective autophagic degradation of CD274/PD-L1.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:The T cell receptor landscape of childhood brain tumors.
The T cell receptor landscape of childhood brain tumors.
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多样化的 T 细胞受体(TCR)库使免疫系统能够识别几乎无限种抗原。表征TIL(肿瘤浸润淋巴细胞)的抗原特异性,是理解抗肿瘤免疫以及指导有效免疫疗法开发的关键。本文全面、大规模考察了儿童脑肿瘤各类型中 TIL 的 TCR 图谱;儿童脑肿瘤是儿童癌症相关死亡的首要原因。研究显示,T 细胞克隆性指数可用于预测患者预后,克隆性越高,结局越好。此外,对 TCR 相似性组的分析揭示了具有特定人类白细胞抗原关联的患者聚类。对这些聚类进行计算分析,识别出可能作为抗肿瘤 T 细胞免疫靶点的候选肿瘤抗原和肽,并通过体外 T 细胞刺激试验进行了功能验证。总体而言,本研究提出一个基于原位和计算机模拟 TIL TCR 分析来预测肿瘤抗原的框架。研究者建议,基于 TCR 的研究应为肿瘤分类和精准免疫疗法开发提供依据。
The diverse T cell receptor (TCR) repertoire confers the ability to recognize an almost unlimited array of antigens. Characterization of antigen specificity of tumor-infiltrating lymphocytes (TILs) is key for understanding antitumor immunity and for guiding the development of effective immunotherapies.
Here, we report a large-scale comprehensive examination of the TCR landscape of TILs across the spectrum of pediatric brain tumors, the leading cause of cancer-related mortality in children.
We show that a T cell clonality index can inform patient prognosis, where more clonality is associated with more favorable outcomes.
Moreover, TCR similarity groups' assessment revealed patient clusters with defined human leukocyte antigen associations. Computational analysis of these clusters identified putative tumor antigens and peptides as targets for antitumor T cell immunity, which were functionally validated by T cell stimulation assays in vitro.
Together, this study presents a framework for tumor antigen prediction based on in situ and in silico TIL TCR analyses.
We propose that TCR-based investigations should inform tumor classification and precision immunotherapy development.
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