ArticleFrontiers in genetics2019
Dysregulated lncRNA-miRNA-mRNA Network Reveals Patient Survival-Associated Modules and RNA Binding Proteins in Invasive Breast Carcinoma.
Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 40 citations in OpenAlex.
- hnRNPH1: A Multifaceted Regulator in RNA Processing and Disease Pathogenesis.International journal of molecular sciences · 2025Review
- Tumor tissue-of-origin classification using miRNA-mRNA-lncRNA interaction networks and machine learning methods.Frontiers in bioinformatics · 2025Article
- The Masquelet technique triggers the formation of a network involving LncRNA, circRNA, miRNA, and mRNA during bone repair.Annals of medicine · 2024Article
- Construction of a Wilms tumor risk model based on machine learning and identification of cuproptosis-related clusters.BMC medical informatics and decision making · 2024Article
- Editorial: DNA Methylation Dynamics and Human Diseases.Frontiers in cell and developmental biology · 2022Article
- Pan-Cancer Methylated Dysregulation of Long Non-coding RNAs Reveals Epigenetic Biomarkers.Frontiers in cell and developmental biology · 2022Article
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- Shared Molecular Mechanisms between Alzheimer's Disease and Periodontitis Revealed by Transcriptomic Analysis.BioMed research international · 2021Article
- Immune and Metabolic Dysregulated Coding and Non-coding RNAs Reveal Survival Association in Uterine Corpus Endometrial Carcinoma.Frontiers in genetics · 2021Article
- Integrated analysis identifies a pathway-related competing endogenous RNA network in the progression of pancreatic cancer.BMC cancer · 2020Article
- The Long Non-coding RNA LINC01705 Regulates the Development of Breast Cancer by Sponging miR-186-5p to Mediate TPR Expression as a Competitive Endogenous RNA.Frontiers in genetics · 2020Article
- BaBao Dan Suppresses Tumor Growth of Pancreatic Cancer Through Modulating Transcriptional Reprogramming of Cancer-Related Genes.Frontiers in oncology · 2020Article
- Emerging Roles and Therapeutic Interventions of Aerobic Glycolysis in Glioma.OncoTargets and therapy · 2020Review
- Machine Learning Based Network Analysis Determined Clinically Relevant miRNAs in Breast Cancer.Frontiers in genetics · 2020Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer is the most common cancer in women, but few biomarkers are effective in clinic. Previous studies have shown the important roles of non-coding RNAs in diagnosis, prognosis, and therapy selection for breast cancer and have suggested the significance of integrating molecules at different levels to interpret the mechanism of breast cancer. Here, we collected transcriptome data including long non-coding RNA (lncRNA), microRNA (miRNA), and mRNA for ~1,200 samples, including 1079 invasive breast carcinoma samples and 104 normal samples, from The Cancer Genome Atlas (TCGA) project. We identified differentially expressed lncRNAs, miRNAs, and mRNAs that distinguished invasive carcinoma samples from normal samples. We further constructed an integrated dysregulated network consisting of differentially expressed lncRNAs, miRNAs, and mRNAs and found housekeeping and cancer-related functions. Moreover, 58 RNA binding proteins (RBPs) involved in biological processes that are essential to maintain cell survival were found in the dysregulated network, and 10 were correlated with overall survival. In addition, we identified two modules that stratify patients into high- and low-risk subgroups. The expression patterns of these two modules were significantly different in invasive carcinoma versus normal samples, and some molecules were high-confidence biomarkers of breast cancer. Together, these data demonstrated an important clinical application for improving outcome prediction for invasive breast cancers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.