Raphael Itay, Xiong Zujian, Sneiderman Chaim T, Raphael Rebecca A, Mash Moshe, Schwegman Lance, Jackson Sydney A, O'Brien Casey, Anderson Kevin J, Sever ReidAnn E, Hendrikse Liam D, Vincze Sarah R, Diaz Aaron, Felker James, Nazarian Javad, Nechemia-Arbely Yael, Hu Baoli, Kammula Udai S, Agnihotri Sameer, Rich Jeremy N, Broniscer Alberto, Drappatz Jan, Abel Taylor J, Uttam Shikhar, Hwang Eugene I, Pearce Thomas M, Taylor Michael D, Nisnboym Michal, Forsthuber Thomas G, Pollack Ian F, Chikina Maria, Rajasundaram Dhivyaa, Kohanbash Gary
Department of Neurological Surgery, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, PA 15224, USA.
Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA.
Sci Transl Med. 2025 Mar 19;17(790):eadp0675. doi: 10.1126/scitranslmed.adp0675.
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.
多样的T细胞受体（TCR）库赋予了识别几乎无限种类抗原的能力。肿瘤浸润淋巴细胞（TILs）的抗原特异性表征对于理解抗肿瘤免疫和指导有效免疫疗法的开发至关重要。在这里，我们报告了对儿童脑肿瘤谱系中TILs的TCR格局进行的大规模综合检查，儿童脑肿瘤是儿童癌症相关死亡的主要原因。我们表明，T细胞克隆性指数可以为患者预后提供信息，其中克隆性越高与预后越好相关。此外，TCR相似性组的评估揭示了具有明确人类白细胞抗原关联的患者聚类。对这些聚类的计算分析确定了推定的肿瘤抗原和肽作为抗肿瘤T细胞免疫的靶点，并通过体外T细胞刺激试验进行了功能验证。总之，本研究提出了一个基于原位和计算机模拟TIL TCR分析的肿瘤抗原预测框架。我们建议基于TCR的研究应为肿瘤分类和精准免疫疗法的开发提供信息。
