ArticleCancer medicine2019
Identification of competitive endogenous RNAs network in breast cancer.
Article in Cancer medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 20 citations in OpenAlex.
- Article
- Non-coding RNAs, a double-edged sword in breast cancer prognosis.Cancer cell international · 2025Review
- Long non-coding RNA MEG3 acts as a suppressor in breast cancer by regulating miR-330/CNN1.Aging · 2024Article
- Pan-Cancer Analysis Reveals Functional Similarity of Three lncRNAs across Multiple Tumors.International journal of molecular sciences · 2023Article
- Roles and Mechanisms of Long Non-Coding RNAs in Breast Cancer.International journal of molecular sciences · 2022Review
- Identification of a prognostic chemoresistance-related gene signature associated with immune microenvironment in breast cancer.Bioengineered · 2021Article
- Path to Clonal Theranostics in Luminal Breast Cancers.Frontiers in oncology · 2021Article
- Comprehensive RNA Sequencing in Adenoma-Cancer Transition Identified Predictive Biomarkers and Therapeutic Targets of Human CRC.Molecular therapy. Nucleic acids · 2020Article
- Coexpression Network Analysis of Genes Related to the Characteristics of Tumor Stemness in Triple-Negative Breast Cancer.BioMed research international · 2020Article
- Dysregulation of CircRNA_0001946 Contributes to the Proliferation and Metastasis of Colorectal Cancer Cells by Targeting MicroRNA-135a-5p.Frontiers in genetics · 2020Article
- Identification of competitive endogenous RNAs network in breast cancer.Cancer medicine · 2019Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMiRNAs can regulate gene expression directly or indirectly, and long noncoding RNAs as competing endogenous RNA (ceRNAs) can bind to miRNAs competitively and affect mRNA expression. The ceRNA network is still unclear in breast cancer. In this study, a ceRNA network was constructed, and new treatment and prognosis targets and biomarkers for breast cancer were explored.
methodsA total of 1 096 cancer tissues and 112 adjacent normal tissues to cancer from the TCGA database were used to screen out significant differentially expressed mRNAs (DEMs), lncRNAs (DELs), and miRNAs (DEMis) to construct a ceRNA network. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to predict potential functions. Survival analysis was performed to predict which functions were significant for prognosis.
resultsFrom the analysis, 2 139 DEMs, 1 059 DELs, and 84 DEMis were obtained. Targeting predictions for DEMis-DELs and DEMis-DEMs can yield 26 DEMs, 90 DELs, and 18 DEMis. We performed GO enrichment analysis, and the results showed that the upregulated DEMs were involved in nucleosomes, extracellular regions, and nucleosome assembly, while the downregulated DEMs were mainly involved in Z disk, muscle contraction, and structural constituents of muscle. KEGG pathway analysis was performed on all DEMs, and the pathways were enriched in retinol metabolism, steroid hormone biosynthesis, and tyrosine metabolism. Through survival analysis of the ceRNA network, we identified four DEMs, two DELs, and two DEMis that were significant for poor prognosis.
conclusionsThis study suggested that constructing a ceRNA network and performing survival analysis on the network could screen out new significant treatment and prognosis targets and biomarkers.
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