Abstract
BackgroundIncreasing evidence has underscored the role of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in the development and progression of tumors. Nevertheless, lncRNA biomarkers in lncRNA-related ceRNA network that can predict the prognosis of breast cancer (BC) are still lacking. The aim of our study was to identify potential lncRNA signatures capable of predicting overall survival (OS) of BC patients.MethodsThe RNA sequencing data and clinical characteristics of BC patients were obtained from the Cancer Genome Atlas database, and differentially expressed lncRNA (DElncRNAs), DEmRNAs, and DEmiRNAs were then identified between BC and normal breast tissue samples. Subsequently, the lncRNA–miRNA–mRNA ceRNA network of BC was established, and the gene oncology enrichment analyses for the DEmRNAs interacting with lncRNAs in the ceRNA network was implemented. Using univariate and multivariate Cox regression analyses, a four-lncRNA signature was developed and used for predicting the survival in BC patients. We applied receiver operating characteristic analysis to assess the performance of our model.ResultsA total of 1061 DElncRNAs, 2150 DEmRNAs, and 82 DEmiRNAs were identified between BC and normal breast tissue samples. A lncRNA–miRNA–mRNA ceRNA network of BC was established, which comprised of 8 DEmiRNAs, 48 DElncRNAs, and 10 DEmRNAs. Further gene oncology enrichment analyses revealed that the DEmRNAs interacting with lncRNAs in the ceRNA network participated in cell leading edge, protease binding, alpha-catenin binding, gamma-catenin binding, and adenylate cyclase binding. A univariate regression analysis of the DElncRNAs revealed 7 lncRNAs (ADAMTS9-AS1, AC061992.1, LINC00536, HOTAIR, AL391421.1, TLR8-AS1 and LINC00491) that were associated with OS of BC patients. A multivariate Cox regression analysis demonstrated that 4 of those lncRNAs (ADAMTS9-AS1, LINC00536, AL391421.1 and LINC00491) had significant prognostic value, and their cumulative risk score indicated that this 4-lncRNA signature independently predicted OS in BC patients. Furthermore, the area under the curve of the 4-lncRNA signature associated with 3-year survival was 0.696.ConclusionsThe current study provides novel insights into the lncRNA-related ceRNA network in BC and the 4 lncRNA biomarkers may be independent prognostic signatures in predicting the survival of BC patients.
Highlights
Increasing evidence has underscored the role of long non-coding RNAs acting as compet‐ ing endogenous RNAs in the development and progression of tumors
Identification of differentially expressed mRNAs (DEmRNAs), DElncRNAs, and DEmiRNAs We identified the DEmRNAs, DElncRNAs, and DEmiRNAs in breast cancer (BC) and adjacent-normal breast tissues using the The Cancer Genome Atlas (TCGA) database, with P < 0.01 and |logFC| > 2 as the thresholds
The MiRDB, miRTarBase and Targetscan programs were used to determine the relationship between the 82 DEmiRNAs and 2150 DEmRNAs, and predict the mRNA targets of miRNAs
Summary
Increasing evidence has underscored the role of long non-coding RNAs (lncRNAs) acting as compet‐ ing endogenous RNAs (ceRNAs) in the development and progression of tumors. LncRNA biomarkers in lncRNA-related ceRNA network that can predict the prognosis of breast cancer (BC) are still lacking. The aim of our study was to identify potential lncRNA signatures capable of predicting overall survival (OS) of BC patients. Breast cancer (BC) is a heterogeneous and malignant neoplasm derived from breast tissue, and accounts for about 16% of all cancers and 22.9% of invasive cancers in women [1]. Clinical and pathological symptoms have limited predictive value in detecting early BC, and the clinical outcomes are highly variable on account of its heterogeneity. It is vital to identify potential molecular diagnostic markers and/or therapeutic targets to combat BC, especially the invasive form
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