Carcinogenesis, Teratogenesis & Mutagenesis ›› 2018, Vol. 30 ›› Issue (2): 103-108.doi: 10.3969/j.issn.1004-616x.2018.02.005

Previous Articles     Next Articles

Bioinformation analysis of data regarding breast cancer prognosis in European and American populations

ZUO Ran1,2, REN Xiaohu2, WU Desheng2, LI Ping2,3, WU Wen1,2, XIE Ni3, YUAN Jianhui1,2, RANG Weiqing1   

  1. 1. School of Public Health, University of South China, Hengyang 421001, Hunan;
    2. Institute of Toxicology, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055;
    3. Institute of Translation Medicine, Shenzhen Second People's Hospital, Shenzhen 518000, Guangdong, China
  • Received:2017-12-07 Revised:2018-03-13 Online:2018-03-30 Published:2018-03-30

Abstract: OBJECTIVE: To understand key molecular events in prognosis of breast cancer,we analyzed the data published by TCGA,and to study the associations between microRNAs and potential target genes at the pathway level. METHODS: To collect and organize the gene expression profile and microRNA sequencing data of breast cancer in TCGA database,we use multiple t-tests to analyze the differentially expressed microRNAs and target genes,and R language package microRNA-mRNA to predict the potential target regulated genes in microRNA. General Applicable Gene-set Enrichment (GAGE) was applied to discover the key genes in essential pathways of breast cancer. Integrated association analysis was used to find the potential targets of the microRNAs. The Cox proportional hazard model was used to evaluate the possible prognostic signatures in breast cancer. RESULTS: The results show that there were abnormal expression of 344 genes and 135 microRNAs. 8 microRNAs with 31 potential target genes might have played key roles in breast cancer through 139 essential pathways. Cox regression risk model results show that increased SFRP1 had a protective effect (HR=0.9,P=0.015) while miR-342-5p had neither protective nor hazard effects (HR=0.99,P=0.144). However interactive analysis suggest that has-mir-342-5p inhibited SFRP1 expression in breast cancer with poor prognosis (HR=1.88,P=0.016). CONCLUSION: Through deep excavation of gene expression and microRNA sequencing data from TCGA database,we identified abnormal expression of certain microRNA and genes in breast cancer,and their involvement in key signaling pathways,suggesting that has-mir-342-5p inhibited the expression of SFRP1 in patients with breast cancer who had poor prognosis.

Key words: has-miR-342-5p, SFRP1, breast cancer, prognosis

CLC Number: