Division of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Department of Lymphoma and Myeloma, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
PLoS One. 2020 Feb 10;15(2):e0228112. doi: 10.1371/journal.pone.0228112. eCollection 2020.
Neoantigens can be predicted and in some cases identified using the data obtained from the whole exome sequencing and transcriptome sequencing of tumor cells. These sequencing data can be coupled with single-cell RNA sequencing for the direct interrogation of the transcriptome, surfaceome, and pairing of αβ T-cell receptors (TCRαβ) from hundreds of single T cells. Using these 2 large datasets, we established a platform for identifying antigens recognized by TCRαβs obtained from single T cells. Our approach is based on the rapid expression of cloned TCRαβ genes as Sleeping Beauty transposons and the determination of the introduced TCRαβs' antigen specificity and avidity using a reporter cell line. The platform enables the very rapid identification of tumor-reactive TCRs for the bioengineering of T cells with redirected specificity.
新抗原可以通过对肿瘤细胞的全外显子组测序和转录组测序获得的数据进行预测,并在某些情况下进行鉴定。这些测序数据可以与单细胞 RNA 测序相结合,直接检测数百个单个 T 细胞的转录组、表面组和 αβ T 细胞受体 (TCRαβ) 的配对。利用这 2 个大数据集,我们建立了一个从单个 T 细胞中鉴定 TCRαβ 识别的抗原的平台。我们的方法基于快速表达克隆的 TCRαβ 基因作为 Sleeping Beauty 转座子,并使用报告细胞系确定引入的 TCRαβ 的抗原特异性和亲和力。该平台能够快速鉴定肿瘤反应性 TCR,用于工程化具有重定向特异性的 T 细胞。