Center for Artificial Intelligence Biology, Hubei Bioinformatics and Molecular Imaging Key Laboratory, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, Nantong, Jiangsu, China.
Cancer Immunol Res. 2022 Nov 2;10(11):1398-1406. doi: 10.1158/2326-6066.CIR-22-0249.
Immune checkpoint blockade (ICB) therapy provides remarkable clinical benefits for multiple cancer types. Much work is currently being conducted to investigate the mechanisms of ICB therapy at the transcriptional level. Integrating the data produced by these studies will help us give more insight into the transcriptomic features of ICB therapy. We collected the transcriptome and clinical data of ICB-treated patient samples from the Gene Expression Omnibus, ArrayExpress, The Cancer Genome Atlas, and dbGaP databases. On the basis of the clinical information, all samples are initially classified into response/nonresponse or pretreatment/on-treatment groups. Differential expression, pathway enrichment, and immune cell infiltration analyses are performed between the samples from different groups. We also introduce the Response Score (RS) calculated by integrating the variability degree and the frequency of the dysregulated genes in the responders to evaluate the impact of gene expression on the response. Finally, all the abovementioned contents are integrated into the ICBatlas database. ICBatlas provides the transcriptome features of ICB therapy through the analysis of 1,515 ICB-treated samples from 25 studies across nine cancer types. The data in ICBatlas include clinical outcomes, treatment-related genes, biological pathways, and immune cell infiltration. Users can investigate the abovementioned transcriptome features in the response (R vs. NR) or treatment (Pre vs. On) modules at the data set, cancer type, or immune checkpoint level and compare the degree of gene impact on the response in the RS module. ICBatlas is the first database to show the transcriptome features on ICB therapy in human cancers and freely available at http://bioinfo.life.hust.edu.cn/ICBatlas/.
免疫检查点阻断 (ICB) 治疗为多种癌症类型提供了显著的临床获益。目前正在进行大量工作，以研究 ICB 治疗在转录水平上的机制。整合这些研究产生的数据将有助于我们更深入地了解 ICB 治疗的转录组特征。我们从基因表达综合数据库、ArrayExpress、癌症基因组图谱和 dbGaP 数据库中收集了接受 ICB 治疗的患者样本的转录组和临床数据。根据临床信息，所有样本最初分为应答/无应答或预处理/治疗组。在不同组的样本之间进行差异表达、通路富集和免疫细胞浸润分析。我们还引入了通过整合应答者中失调基因的可变性程度和频率计算得到的响应评分 (RS)，以评估基因表达对响应的影响。最后，将所有上述内容整合到 ICBatlas 数据库中。ICBatlas 通过分析来自 25 项研究的 9 种癌症类型的 1515 个接受 ICB 治疗的样本，提供了 ICB 治疗的转录组特征。ICBatlas 中的数据包括临床结果、治疗相关基因、生物途径和免疫细胞浸润。用户可以在数据集、癌症类型或免疫检查点水平的响应 (R 与 NR) 或治疗 (Pre 与 On) 模块中研究上述转录组特征，并在 RS 模块中比较基因对响应的影响程度。ICBatlas 是第一个展示人类癌症中 ICB 治疗转录组特征的数据库，可在 http://bioinfo.life.hust.edu.cn/ICBatlas/ 免费获取。
