Abstract
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.
Highlights
The incidence of breast cancer has increased at a rate of 0.3% per year from 2012 to 2016 in the United States, largely because of the rising rates of local stage and hormone receptor-positive disease [1]
RNAs competitively bind to the same miRNAs as competing endogenous RNAs (ceRNAs)
Chen et al generated a ceRNA network for each subtype of breast cancer, based on the principle of positive co-expression and shared miRNAs [17]
Summary
The incidence of breast cancer has increased at a rate of 0.3% per year from 2012 to 2016 in the United States, largely because of the rising rates of local stage and hormone receptor-positive disease [1]. The transcriptional regulation of estrogen receptor (ER) is an intricate network of signaling and functional processes that is still largely unknown at the single cell level. Investigating the heterogeneity of estrogen regulation at the single cell level could shed more light on estrogen mechanisms and potential breast cancer therapeutics. Zhu et al performed scRNA-seq on estrogen receptor alpha positive breast cancer cells stimulated by E2. Their research revealed a dynamic transcriptional network in which estrogen signaling promotes breast cancer cell survival and growth by mediating a metabolic switch [3]. They provided valuable data resources to explore the heterogeneous response of cells from the same cell line upon estrogen stimulation
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