Chen Xin, Xu Jing, Zeng Feng, Yang Chao, Sun Weijun, Yu Tao, Zhang Haokun, Li Yan
School of Automation, Guangdong University of Technology, Guangzhou, China.
Department of Oncology, Changhai Hospital, The Naval Military Medical University, Shanghai, China.
Front Oncol. 2021 Apr 27;11:656675. doi: 10.3389/fonc.2021.656675. eCollection 2021.
Single-cell RNA sequencing is a powerful tool to explore the heterogeneity of breast cancer. The identification of the cell subtype that responds to estrogen has profound significance in breast cancer research and treatment. The transcriptional regulation of estrogen is an intricate network involving crosstalk between protein-coding and non-coding RNAs, which is still largely unknown, particularly at the single cell level. Therefore, we proposed a novel strategy to specify cell subtypes based on a cell-specific ceRNA network (CCN). The CCN was constructed by integrating a cell-specific RNA-RNA co-expression network (RCN) with an existing ceRNA network. The cell-specific RCN was built based on single cell expression profiles with predefined reference cells. Heterogeneous cell subtypes were inferred by enriching RNAs in CCN to the estrogen response hallmark. Edge biomarkers were identified in the early estrogen response subtype. Topological analysis revealed that NEAT1 was a hub lncRNA for the early response subtype, and its ceRNAs could predict patient survival. Another hub lncRNA, DLEU2, could potentially be involved in GPCR signaling, based on CCN. The CCN method that we proposed here facilitates the inference of cell subtypes from a network perspective and explores the function of hub lncRNAs, which are promising targets for RNA-based therapeutics.
单细胞RNA测序是探索乳腺癌异质性的有力工具。识别对雌激素有反应的细胞亚型在乳腺癌研究和治疗中具有深远意义。雌激素的转录调控是一个复杂的网络，涉及蛋白质编码RNA和非编码RNA之间的相互作用，目前仍知之甚少，尤其是在单细胞水平上。因此，我们提出了一种基于细胞特异性ceRNA网络（CCN）来确定细胞亚型的新策略。CCN是通过将细胞特异性RNA-RNA共表达网络（RCN）与现有的ceRNA网络整合构建而成。细胞特异性RCN是基于具有预定义参考细胞的单细胞表达谱构建的。通过在CCN中富集与雌激素反应特征相关的RNA来推断异质细胞亚型。在早期雌激素反应亚型中鉴定出边缘生物标志物。拓扑分析表明，NEAT1是早期反应亚型的枢纽lncRNA，其ceRNAs可以预测患者生存。基于CCN，另一个枢纽lncRNA DLEU2可能参与GPCR信号传导。我们在此提出的CCN方法有助于从网络角度推断细胞亚型，并探索枢纽lncRNA的功能，而枢纽lncRNA是基于RNA的治疗方法的有前景的靶点。
