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Systematic analysis of lncRNA-miRNA-mRNA competing endogenous RNA network identifies four-lncRNA signature as a prognostic biomarker for breast cancer.
J Transl Med. 2018 09 27; 16(1):264.JT

Abstract

BACKGROUND

Increasing 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.

METHODS

The 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.

RESULTS

A 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.

CONCLUSIONS

The 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.

Authors+Show Affiliations

Department of Breast Surgery, China-Japan Union Hospital of Jilin University, NO. 126, Xian Tai Street, Changchun, 130033, Jilin, China.Department of Breast Surgery, China-Japan Union Hospital of Jilin University, NO. 126, Xian Tai Street, Changchun, 130033, Jilin, China.Department of Breast Surgery, China-Japan Union Hospital of Jilin University, NO. 126, Xian Tai Street, Changchun, 130033, Jilin, China. liuning120324@163.com.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

30261893

Citation

Fan, Chun-Ni, et al. "Systematic Analysis of lncRNA-miRNA-mRNA Competing Endogenous RNA Network Identifies four-lncRNA Signature as a Prognostic Biomarker for Breast Cancer." Journal of Translational Medicine, vol. 16, no. 1, 2018, p. 264.
Fan CN, Ma L, Liu N. Systematic analysis of lncRNA-miRNA-mRNA competing endogenous RNA network identifies four-lncRNA signature as a prognostic biomarker for breast cancer. J Transl Med. 2018;16(1):264.
Fan, C. N., Ma, L., & Liu, N. (2018). Systematic analysis of lncRNA-miRNA-mRNA competing endogenous RNA network identifies four-lncRNA signature as a prognostic biomarker for breast cancer. Journal of Translational Medicine, 16(1), 264. https://doi.org/10.1186/s12967-018-1640-2
Fan CN, Ma L, Liu N. Systematic Analysis of lncRNA-miRNA-mRNA Competing Endogenous RNA Network Identifies four-lncRNA Signature as a Prognostic Biomarker for Breast Cancer. J Transl Med. 2018 09 27;16(1):264. PubMed PMID: 30261893.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Systematic analysis of lncRNA-miRNA-mRNA competing endogenous RNA network identifies four-lncRNA signature as a prognostic biomarker for breast cancer. AU - Fan,Chun-Ni, AU - Ma,Lei, AU - Liu,Ning, Y1 - 2018/09/27/ PY - 2018/05/28/received PY - 2018/09/20/accepted PY - 2018/9/29/entrez PY - 2018/9/29/pubmed PY - 2019/7/16/medline KW - Breast cancer KW - Competing endogenous RNA network KW - Long non-coding RNA KW - Overall survival KW - Prognosis SP - 264 EP - 264 JF - Journal of translational medicine JO - J Transl Med VL - 16 IS - 1 N2 - BACKGROUND: Increasing 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. METHODS: The 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. RESULTS: A 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. CONCLUSIONS: The 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. SN - 1479-5876 UR - https://www.unboundmedicine.com/medline/citation/30261893/Systematic_analysis_of_lncRNA_miRNA_mRNA_competing_endogenous_RNA_network_identifies_four_lncRNA_signature_as_a_prognostic_biomarker_for_breast_cancer_ L2 - https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-018-1640-2 DB - PRIME DP - Unbound Medicine ER -