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预测TCRpcDist癌症患者的孤儿T细胞受体的抗原特异性

Marta A S Perez^1,2, Johanna Chiffelle^1,3, Sara Bobisse^1,3

¹Department of Oncology, Ludwig Institute for Cancer Research, Lausanne Branch, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Agora Cancer Research Center, Lausanne, CH-1005, Switzerland.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)

|August 19, 2024

概括

TCRpcDist是一种新的3D方法,通过分析物理化学性质,准确地聚集T细胞受体谱. 这种方法有助于识别针对个性化癌症免疫疗法的抗原特异性.

科学领域:

免疫学免疫学免疫学
生物信息学是一种生物信息学.
计算生物学计算生物学

背景情况:

对T细胞受体 (TCR) 谱系分析对于诊断免疫疾病和开发个性化疗法至关重要.
目前用于TCR分析的基于序列和基于结构的方法存在局限性,特别是在稀缺数据或大规模预测的情况下.

研究的目的:

介绍TCRpcDist,一种基于3D的计算方法,用于基于物理化学性质分析TCR相似性.
评估TCRpcDist的性能与现有方法对比,以集群具有类似抗原特异性的TCR.

主要方法:

TCRpcDist使用基于预测与表位体相互作用的循环残留物的物理化学性质的度量计算TCR相似性.
该方法使用私人和公共数据集进行了验证,并将其性能与竞争方法进行了比较.

主要成果:

TCRpcDist准确地识别了可能与相同表位组结合的TCR组.
该方法经过实验验证,用于确定癌症患者孤儿瘤透淋巴细胞 (TIL) 的抗原特异性.

结论:

TCRpcDist是一个有前途的工具,用于分析TCR的曲目和TCR的deorphanization.
这种方法支持开发个性化的治疗方法,包括癌症免疫疗法.

关键词:

甲化除甲化标本特异性的特异性特异性预测的预测.t细胞受体 (TCRs) 的使用.在tcr集群化中,tcr集群化瘤抗原是一种瘤抗原.

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