{"title":"确定与抗癌免疫疗法相关的 TCR 重排模式。","authors":"Romi Vandoren, Sofie Gielis, Kris Laukens, Pieter Meysman","doi":"10.1016/bs.mcb.2023.05.001","DOIUrl":null,"url":null,"abstract":"<p><p>The highly diverse T cell receptor (TCR) repertoire is a crucial component of the adaptive immune system that aids in the protection against a wide variety of pathogens. This TCR repertoire, comprising the collection of all TCRs in an individual, is a valuable source of information on both recent and ongoing T cell activation. Cancer cells, like pathogens, have the ability to trigger an adaptive immune response. However, because cancer cells use a variety of strategies to escape immune responses, this is often insufficient to completely eradicate them. As a result, immunotherapy is a promising treatment option for cancer patients. This treatment is expected to increase T cell activation and subsequently alter the TCR repertoire composition in these patients. Monitoring TCR repertoires before and after immunotherapy can therefore provide additional insight into T cell responses and might identify cancer-associated TCR sequences. Here we present a computational strategy to identify those changes in the TCR repertoire that occur after treatment with immunotherapy. Since this method allows the identification of TCR patterns that might be treatment-associated, it can help future research by revealing those patterns that are related with response. This TCR analysis workflow is illustrated using public data from three different cancer patients who received anti-PD-1 treatment.</p>","PeriodicalId":18437,"journal":{"name":"Methods in cell biology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of TCR repertoire patterns linked with anti-cancer immunotherapy.\",\"authors\":\"Romi Vandoren, Sofie Gielis, Kris Laukens, Pieter Meysman\",\"doi\":\"10.1016/bs.mcb.2023.05.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The highly diverse T cell receptor (TCR) repertoire is a crucial component of the adaptive immune system that aids in the protection against a wide variety of pathogens. This TCR repertoire, comprising the collection of all TCRs in an individual, is a valuable source of information on both recent and ongoing T cell activation. Cancer cells, like pathogens, have the ability to trigger an adaptive immune response. However, because cancer cells use a variety of strategies to escape immune responses, this is often insufficient to completely eradicate them. As a result, immunotherapy is a promising treatment option for cancer patients. This treatment is expected to increase T cell activation and subsequently alter the TCR repertoire composition in these patients. Monitoring TCR repertoires before and after immunotherapy can therefore provide additional insight into T cell responses and might identify cancer-associated TCR sequences. Here we present a computational strategy to identify those changes in the TCR repertoire that occur after treatment with immunotherapy. Since this method allows the identification of TCR patterns that might be treatment-associated, it can help future research by revealing those patterns that are related with response. This TCR analysis workflow is illustrated using public data from three different cancer patients who received anti-PD-1 treatment.</p>\",\"PeriodicalId\":18437,\"journal\":{\"name\":\"Methods in cell biology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Methods in cell biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1016/bs.mcb.2023.05.001\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/9/23 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"Biochemistry, Genetics and Molecular Biology\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Methods in cell biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/bs.mcb.2023.05.001","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/9/23 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 0
摘要
高度多样化的 T 细胞受体(TCR)复合物是适应性免疫系统的重要组成部分,有助于抵御各种病原体。TCR 基因库是个体体内所有 TCR 的集合,是 T 细胞最近和正在激活的宝贵信息来源。与病原体一样,癌细胞也有能力触发适应性免疫反应。然而,由于癌细胞使用各种策略逃避免疫反应,这往往不足以彻底根除它们。因此,免疫疗法对癌症患者来说是一种很有前景的治疗选择。这种治疗方法有望提高 T 细胞的活化程度,从而改变这些患者的 TCR 重排组成。因此,在免疫疗法前后监测 TCR 重排可以进一步了解 T 细胞的反应,并有可能发现与癌症相关的 TCR 序列。在这里,我们提出了一种计算策略,用于识别免疫疗法治疗后TCR基因库中发生的变化。由于这种方法可以识别可能与治疗相关的 TCR 模式,因此它可以揭示与反应相关的模式,从而有助于未来的研究。我们将利用接受过抗 PD-1 治疗的三名不同癌症患者的公开数据来说明这种 TCR 分析工作流程。
Identification of TCR repertoire patterns linked with anti-cancer immunotherapy.
The highly diverse T cell receptor (TCR) repertoire is a crucial component of the adaptive immune system that aids in the protection against a wide variety of pathogens. This TCR repertoire, comprising the collection of all TCRs in an individual, is a valuable source of information on both recent and ongoing T cell activation. Cancer cells, like pathogens, have the ability to trigger an adaptive immune response. However, because cancer cells use a variety of strategies to escape immune responses, this is often insufficient to completely eradicate them. As a result, immunotherapy is a promising treatment option for cancer patients. This treatment is expected to increase T cell activation and subsequently alter the TCR repertoire composition in these patients. Monitoring TCR repertoires before and after immunotherapy can therefore provide additional insight into T cell responses and might identify cancer-associated TCR sequences. Here we present a computational strategy to identify those changes in the TCR repertoire that occur after treatment with immunotherapy. Since this method allows the identification of TCR patterns that might be treatment-associated, it can help future research by revealing those patterns that are related with response. This TCR analysis workflow is illustrated using public data from three different cancer patients who received anti-PD-1 treatment.
期刊介绍:
For over fifty years, Methods in Cell Biology has helped researchers answer the question "What method should I use to study this cell biology problem?" Edited by leaders in the field, each thematic volume provides proven, state-of-art techniques, along with relevant historical background and theory, to aid researchers in efficient design and effective implementation of experimental methodologies. Over its many years of publication, Methods in Cell Biology has built up a deep library of biological methods to study model developmental organisms, organelles and cell systems, as well as comprehensive coverage of microscopy and other analytical approaches.