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Inferring Cell Subtypes and LncRNA Function by a Cell-Specific CeRNA Network in Breast Cancer
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 involvin...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8111082/ https://www.ncbi.nlm.nih.gov/pubmed/33987091 http://dx.doi.org/10.3389/fonc.2021.656675 |
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author | Chen, Xin Xu, Jing Zeng, Feng Yang, Chao Sun, Weijun Yu, Tao Zhang, Haokun Li, Yan |
author_facet | Chen, Xin Xu, Jing Zeng, Feng Yang, Chao Sun, Weijun Yu, Tao Zhang, Haokun Li, Yan |
author_sort | Chen, Xin |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8111082 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81110822021-05-12 Inferring Cell Subtypes and LncRNA Function by a Cell-Specific CeRNA Network in Breast Cancer Chen, Xin Xu, Jing Zeng, Feng Yang, Chao Sun, Weijun Yu, Tao Zhang, Haokun Li, Yan Front Oncol Oncology 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. Frontiers Media S.A. 2021-04-27 /pmc/articles/PMC8111082/ /pubmed/33987091 http://dx.doi.org/10.3389/fonc.2021.656675 Text en Copyright © 2021 Chen, Xu, Zeng, Yang, Sun, Yu, Zhang and Li https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Chen, Xin Xu, Jing Zeng, Feng Yang, Chao Sun, Weijun Yu, Tao Zhang, Haokun Li, Yan Inferring Cell Subtypes and LncRNA Function by a Cell-Specific CeRNA Network in Breast Cancer |
title | Inferring Cell Subtypes and LncRNA Function by a Cell-Specific CeRNA Network in Breast Cancer |
title_full | Inferring Cell Subtypes and LncRNA Function by a Cell-Specific CeRNA Network in Breast Cancer |
title_fullStr | Inferring Cell Subtypes and LncRNA Function by a Cell-Specific CeRNA Network in Breast Cancer |
title_full_unstemmed | Inferring Cell Subtypes and LncRNA Function by a Cell-Specific CeRNA Network in Breast Cancer |
title_short | Inferring Cell Subtypes and LncRNA Function by a Cell-Specific CeRNA Network in Breast Cancer |
title_sort | inferring cell subtypes and lncrna function by a cell-specific cerna network in breast cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8111082/ https://www.ncbi.nlm.nih.gov/pubmed/33987091 http://dx.doi.org/10.3389/fonc.2021.656675 |
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