PAIR-Scan：通过库对库筛选一步鉴定高活性TCR-新抗原配对
PAIR-Scan: Single-step identification of highly potent TCR-neoantigen pairs through library-on-library screening
bioRxiv · 2026 年 9 月 15 日 · Marius Messemaker, Connor A Richterich, Jule Wenner 等 25 人
肿瘤中T细胞反应混杂，难以区分针对患者特异性新抗原（肿瘤突变产生的新蛋白片段）的有效T细胞受体（TCR）。研究者开发了PAIR-Scan，一种不依赖HLA（人类白细胞抗原）类型的库对库筛选技术，可在单步中从数万候选配对里识别功能性活跃的TCR-新抗原配对。该技术在多种肿瘤样本中验证，能直接鉴定TCR识别的最短肽段，并按肿瘤杀伤效率对识别同一抗原的TCR排序。这为解析临床样本T细胞反应和构建TCR反应预测模型提供了工具，尚未经同行评审。
为什么推荐给您：新的库对库功能筛选平台，可大规模解析TCR-新抗原配对，转化前景明确。
不需要生物学背景，多打比方
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摘要Abstract
Tumors contain a mixture of T cells with bystander reactivities and reactivities towards different, frequently patient-specific, cancer (neo)antigens. The one-step identification of highly active TCR-antigen pairs in human tumors would be valuable, both as a monitoring tool and to boost T cell reactivities of interest. Here, we develop PAIR-Scan, an HLA-agnostic library-on-library screening technology that identifies functionally active TCR-neoantigen pairs among tens of thousands of candidate pairs in a single step. We demonstrate the value of PAIR-Scan on a range of tumor samples and for the direct identification of TCR-recognized minimal peptides. In addition, we demonstrate that PAIR-Scan correctly ranks TCRs reactive to the same antigen by their relative tumor-killing efficiency. Together, these data demonstrate the value of PAIR-Scan for both the dissection of T cell responses in clinical samples and to generate large-scale datasets for the development of predictive models of TCR reactivity.