College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Department of Respiratory Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin 150081, China.
Brief Bioinform. 2022 Jan 17;23(1). doi: 10.1093/bib/bbab481.
Intertumoral immune heterogeneity is a critical reason for distinct clinical benefits of immunotherapy in lung adenocarcinoma (LUAD). Tumor immunophenotype (immune 'Hot' or 'Cold') suggests immunological individual differences and potential clinical treatment guidelines. However, employing epigenome signatures to determine tumor immunophenotypes and responsive treatment is not well understood. To delineate the tumor immunophenotype and immune heterogeneity, we first distinguished the immune 'Hot' and 'Cold' tumors of LUAD based on five immune expression signatures. In terms of clinical presentation, the immune 'Hot' tumors usually had higher immunoactivity, lower disease stages and better survival outcomes than 'Cold' tumors. At the epigenome levels, we observed that distinct DNA methylation patterns between immunophenotypes were closely associated with LUAD development. Hence, we identified a set of five CpG sites as the immunophenotype-related methylation signature (iPMS) for tumor immunophenotyping and further confirmed its efficiency based on a machine learning framework. Furthermore, we found iPMS and immunophenotype-related immune checkpoints (IPCPs) could contribute to the risk of tumor progression, implying IPCP has the potential to be a novel immunotherapy blockade target. After further parsing of the role of iPMS-predicted immunophenotypes, we found immune 'Hot' was a protective factor leading to better survival outcomes when patients received the anti-PD-1/PD-L1 immunotherapy. And iPMS was also a well-performed signature (AUC = 0.752) for predicting the durable/nondurable clinical benefits. In summary, our study explored the role of epigenome signature in clinical tumor immunophenotyping. Utilizing iPMS to characterize tumor immunophenotypes will facilitate developing personalized epigenetic anticancer approaches.
肿瘤间免疫异质性是免疫疗法在肺腺癌 (LUAD) 中产生不同临床获益的关键原因。肿瘤免疫表型(免疫“热”或“冷”)提示免疫个体差异和潜在的临床治疗指导原则。然而,利用表观基因组特征来确定肿瘤免疫表型和反应性治疗尚不清楚。为了描绘肿瘤免疫表型和免疫异质性,我们首先基于五个免疫表达特征区分 LUAD 的免疫“热”和“冷”肿瘤。在临床表现方面,免疫“热”肿瘤通常具有更高的免疫活性、更低的疾病分期和更好的生存结局。在表观基因组水平上,我们观察到免疫表型之间的不同 DNA 甲基化模式与 LUAD 发展密切相关。因此,我们确定了一组五个 CpG 位点作为肿瘤免疫表型相关的甲基化特征 (iPMS),并进一步基于机器学习框架验证了其效率。此外,我们发现 iPMS 和免疫表型相关免疫检查点 (IPCPs) 可能导致肿瘤进展风险,表明 IPCP 有可能成为新的免疫治疗阻断靶点。进一步解析 iPMS 预测的免疫表型的作用后,我们发现免疫“热”是一个保护因素,当患者接受抗 PD-1/PD-L1 免疫治疗时,可导致更好的生存结局。并且 iPMS 也是一个性能良好的预测持久/不可持久临床获益的特征(AUC=0.752)。总之,我们的研究探索了表观基因组特征在临床肿瘤免疫表型中的作用。利用 iPMS 来描述肿瘤免疫表型将有助于开发个性化的表观遗传抗癌方法。