The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
The Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Cell Rep Med. 2020 Nov 17;1(8):100139. doi: 10.1016/j.xcrm.2020.100139.
In this study, we incorporate analyses of genome-wide sequence and structural alterations with pre- and on-therapy transcriptomic and T cell repertoire features in immunotherapy-naive melanoma patients treated with immune checkpoint blockade. Although tumor mutation burden is associated with improved treatment response, the mutation frequency in expressed genes is superior in predicting outcome. Increased T cell density in baseline tumors and dynamic changes in regression or expansion of the T cell repertoire during therapy distinguish responders from non-responders. Transcriptome analyses reveal an increased abundance of B cell subsets in tumors from responders and patterns of molecular response related to expressed mutation elimination or retention that reflect clinical outcome. High-dimensional genomic, transcriptomic, and immune repertoire data were integrated into a multi-modal predictor of response. These findings identify genomic and transcriptomic characteristics of tumors and immune cells that predict response to immune checkpoint blockade and highlight the importance of pre-existing T and B cell immunity in therapeutic outcomes.
在这项研究中，我们将对免疫治疗初治黑色素瘤患者进行的全基因组序列和结构改变分析，与治疗前和治疗中的转录组和 T 细胞受体库特征相结合，这些患者接受了免疫检查点阻断治疗。虽然肿瘤突变负担与改善治疗反应相关，但表达基因中的突变频率在预测结果方面更具优势。在基线肿瘤中增加 T 细胞密度，以及在治疗过程中 T 细胞受体库的回归或扩张的动态变化，可以将应答者与无应答者区分开来。转录组分析显示，应答者的肿瘤中 B 细胞亚群的丰度增加，与表达突变消除或保留相关的分子反应模式反映了临床结果。高维基因组、转录组和免疫受体库数据被整合到一个反应的多模态预测因子中。这些发现确定了预测免疫检查点阻断反应的肿瘤和免疫细胞的基因组和转录组特征，并强调了治疗结果中预先存在的 T 和 B 细胞免疫的重要性。
