Literature DB >> 31037764

Identification of prognostic biomarkers for breast cancer based on miRNA and mRNA co-expression network.

Yan Yao1, Ruijuan Liu2, Chundi Gao3, Tingting Zhang4, Lingyu Qi3, Gongxi Liu2, Wenfeng Zhang1, Xue Wang5, Jie Li3, Jia Li1, Changgang Sun6,7.   

Abstract

PURPOSE: Breast cancer (BC) remains a serious health threat for women due to its high incidence and the trend of rejuvenation. Accumulating evidence has highlighted that microRNAs (miRNAs) and messenger RNAs (mRNAs) could play important roles in various biological processes involved in the pathogenesis of BC. The present study aimed to identify potential prognostic biomarkers associated with BC.
METHODS: Here, original gene expression profiles of patients with BC was downloaded from The Cancer Genome Atlas (TCGA) database. TargetScan, miRDB, and miRTarBase databases were used to predict the target genes of prognostic-related differentially expressed miRNAs (DEMs). Subsequently, functional enrichment analysis and topological analysis were performed on the overlaps of target genes and differentially expressed mRNAs (DEGs), and Kaplan-Meier analysis was used to predict prognosis-related target genes to identify prognostic biomarkers.
RESULTS: A total of 218 DEMs and 2222 DEGs were extracted in which eight miRNAs were associated with prognosis, and 278 target DEGs were screened out incorporated into functional enrichment analysis and protein-protein interaction network visualization studies. Additionally, five hub genes (CXCL12, IGF1, LEF1, MMP1, and RACGAP1) were observed as potential biomarkers for BC prognosis through survival analysis.
CONCLUSION: We performed a distinctive correlation analysis of miRNA-mRNA in BC patients, and identified eight miRNAs and five hub genes may be effective biomarkers for the prognosis of BC patients.
© 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  biomarkers; breast cancer; hub genes; miRNA-mRNAco-expression network; protein-protein interaction network

Year:  2019        PMID: 31037764     DOI: 10.1002/jcb.28805

Source DB:  PubMed          Journal:  J Cell Biochem        ISSN: 0730-2312            Impact factor:   4.429


  4 in total

Review 1.  Regulation of breast cancer metastasis signaling by miRNAs.

Authors:  Belinda J Petri; Carolyn M Klinge
Journal:  Cancer Metastasis Rev       Date:  2020-09       Impact factor: 9.264

Review 2.  A review of prognostic and predictive biomarkers in breast cancer.

Authors:  Elaheh Tarighati; Hadi Keivan; Hojjat Mahani
Journal:  Clin Exp Med       Date:  2022-01-15       Impact factor: 3.984

3.  Comprehensive analysis of transcriptome data for identifying biomarkers and therapeutic targets in head and neck squamous cell carcinoma.

Authors:  Yu Jin; Xing Qin
Journal:  Ann Transl Med       Date:  2020-03

4.  A Comprehensive Analysis for Expression, Diagnosis, and Prognosis of m5C Regulator in Breast Cancer and Its ncRNA-mRNA Regulatory Mechanism.

Authors:  Jingxing Liu; Shuyuan Xiao; Jing Chen; Weiyang Lou; Xu Chen
Journal:  Front Genet       Date:  2022-06-22       Impact factor: 4.772

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.