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作 者:赵静静 简星星 王广志 澹小秀 谢鹭 ZHAO Jing-Jing;JIAN Xing-Xing;WANG Guang-Zhi;TAN Xiao-Xiu;XIE Lu(College of Food Science&Technology,Shanghai Ocean University,Shanghai 201306,China;Shanghai Center for Bioinformation Technology,Shanghai Academy of Science and Technology,Shanghai 201203,China;Department of Hematology,Xiangya Hospital,Central South University,Changsha 410008,China)
机构地区:[1]上海海洋大学食品学院,上海201306 [2]上海生物信息技术研究中心,上海201203 [3]中南大学湘雅医院血液科,长沙410008
出 处:《生命科学》2021年第4期466-471,共6页Chinese Bulletin of Life Sciences
基 金:国家自然科学基金项目(31870829)。
摘 要:TCR组库是指机体在特定时间内免疫循环中T细胞克隆的总和,其多样性程度与机体健康密切相关。借助免疫组库测序技术(immune repertoire sequencing, IR-seq),靶向扩增TCR抗原互补决定区(complementarity determining region, CDR) 1-3可有效获取特定时期内疾病患者TCR组库完整的多样性信息。基于此,TCR组库分析可为肿瘤免疫研究提供新型生物标记物,用于监测免疫状态和评估患者预后;同时,TCR组库也可为TCR-T过继免疫疗法的检测与追踪提供有效途径。另外,基于靶向抗原的TCR CDR3序列特征,通过机器学习算法开发"TCR-抗原"识别预测的生物信息学工具,将有利于促进肿瘤免疫研究和治疗应用方面的发展。该文综述了当前TCR组库的检测技术与分析方法,及其在肿瘤免疫中的应用前景与挑战。TCR repertoire refers to the sum of T cell clones in the body’s immune circulation in a specific time, of which the diversity is closely related to human health. With the aid of immune repertoire sequencing(IR-seq) technology, through the targeted amplification of the TCR complementarity determining region(CDR) 1-3, the whole diversity information of disease-related TCR repertoire can be effectively acquired in a specific period. Based on those, TCR repertoire analysis can provide novel biomarkers for tumor immunity research, which can be applied to detect the immunological status and evaluate prognosis. Meanwhile, TCR repertoire analysis would pave an efficient way to monitor and trace TCR-T adoptive immunotherapy. Besides, sequence characteristics of TCR CDR3 can help develop bioinformatics tools regarding "TCR-antigen" recognition and prediction using machine learning algorithms, which could promote the progress of tumor immunology research and application. In this paper, we reviewed the current methods of TCR immune repertoire detection and diversity analysis, as well as the related application prospects and challenges in tumor immunology.
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