Department of Ophthalmology, Affiliated Hospital of Weifang Medical University, Clinical Medical Institute, Weifang Medical University, Weifang, China.
Front Immunol. 2022 Jul 5;13:898925. doi: 10.3389/fimmu.2022.898925. eCollection 2022.
Molecular classification based on transcriptional characteristics is often used to study tumor heterogeneity. Human cancer has different cell populations with distinct transcription in tumors, and their heterogeneity is the focus of tumor therapy. Our purpose was to explore the tumor heterogeneity of uveal melanoma (UM) through RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq). Based on the consensus clustering assays of the prognosis-related immune gene set, the immune subtype (IS) of UM and its corresponding immune characteristics were comprehensively analyzed. The heterogeneous cell groups and corresponding marker genes of UM were identified from GSE138433 using scRNA-seq analysis. Pseudotime trajectory analysis and SCENIC analysis were conducted to explore the trajectory of cell differentiation and the regulatory network of single-cell transcription factors (TFs). Based on 37 immune gene sets, UM was divided into two different immune subtypes (IS1 and IS2). The two kinds of ISs have different characteristics in prognosis, immune-related molecules, immune score, and immune cell infiltration. According to 11,988 cells of scRNA-seq data from six UM samples, 11 cell clusters and 10 cell types were identified. The subsets of C1, C4, C5, C8, and C9 were related to the prognosis of UM, and different TF-target gene regulatory networks were involved. These five cell subsets differentiated into 3 different states. Our results provided valuable information about the heterogeneity of UM tumors and the expression patterns of TFs in different cell types.
基于转录特征的分子分类常用于研究肿瘤异质性。人类肿瘤的不同细胞群体在肿瘤中有不同的转录特征,其异质性是肿瘤治疗的重点。我们的目的是通过 RNA 测序(RNA-seq)和单细胞 RNA 测序(scRNA-seq)来探索葡萄膜黑色素瘤(UM)的肿瘤异质性。基于与预后相关免疫基因集的共识聚类分析,全面分析 UM 的免疫亚型(IS)及其相应的免疫特征。通过 scRNA-seq 分析从 GSE138433 中鉴定 UM 的异质细胞群及其相应的标记基因。进行假时间轨迹分析和 SCENIC 分析,以探索细胞分化的轨迹和单细胞转录因子(TF)的调控网络。基于 37 个免疫基因集,UM 被分为两种不同的免疫亚型(IS1 和 IS2)。这两种 IS 在预后、免疫相关分子、免疫评分和免疫细胞浸润方面具有不同的特征。根据 6 个 UM 样本的 scRNA-seq 数据的 11988 个细胞,鉴定出 11 个细胞簇和 10 种细胞类型。C1、C4、C5、C8 和 C9 亚群与 UM 的预后相关,涉及不同的 TF-靶基因调控网络。这五个细胞亚群分化为 3 种不同的状态。我们的结果为 UM 肿瘤的异质性和不同细胞类型中 TF 的表达模式提供了有价值的信息。