TY - JOUR
T1 - Regulatory network reconstruction of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets
AU - He, Kan
AU - Li, Wen Xing
AU - Guan, Daogang
AU - Gong, Mengting
AU - Ye, Shoudong
AU - Fang, Zekun
AU - Huang, Jing Fei
AU - Lu, Aiping
N1 - Funding Information:
We acknowledge financial support from the Natural Science Foundation Project of Anhui Province (1508085QC63), and Key University Science Research Project of Anhui Province (KJ2017A021), and the Scientific Research Foundation and Academic & Technology Leaders Introduction Project (the 211 Project) of Anhui University (10117700023). Our work was also supported by the Hong Kong Scholars Program 2016 (XJ2016062) and National Basic Research Program of China (Grant No. 2013CB835100). Financial support by the Hong Kong Baptist University Strategic Development Fund (SDF) (SDF15-0324-P02(b) to A.L.) should also be acknowledged.
Publisher copyright:
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature
PY - 2019/7/1
Y1 - 2019/7/1
N2 - Although many of the genetic loci associated with breast cancer risk have been reported, there is a lack of systematic analysis of regulatory networks composed of different miRNAs and mRNAs on survival analysis in breast cancer. To reconstruct the microRNAs-genes regulatory network in breast cancer, we employed the expression data from The Cancer Genome Atlas (TCGA) related to five essential miRNAs including miR-21, miR-22, miR-210, miR-221, and miR-222, and their associated functional genomics data from the GEO database. Then, we performed an integration analysis to identify the essential target factors and interactions for the next survival analysis in breast cancer. Based on the results of our integrated analysis, we have identified significant common regulatory signatures including differentially expressed genes, enriched pathways, and transcriptional regulation such as interferon regulatory factors (IRFs) and signal transducer and activator of transcription 1 (STAT1). Finally, a reconstructed regulatory network of five miRNAs and 34 target factors was established and then applied to survival analysis in breast cancer. When we used expression data for individual miRNAs, only miR-21 and miR-22 were significantly associated with a survival change. However, we identified 45 significant miRNA-gene pairs that predict overall survival in breast cancer out of 170 one-on-one interactions in our reconstructed network covering all of five miRNAs, and several essential factors such as PSMB9, HLA-C, RARRES3, UBE2L6, and NMI. In our study, we reconstructed regulatory network of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets. These results may provide new insights into regulatory network-based precision medicine for breast cancer.
AB - Although many of the genetic loci associated with breast cancer risk have been reported, there is a lack of systematic analysis of regulatory networks composed of different miRNAs and mRNAs on survival analysis in breast cancer. To reconstruct the microRNAs-genes regulatory network in breast cancer, we employed the expression data from The Cancer Genome Atlas (TCGA) related to five essential miRNAs including miR-21, miR-22, miR-210, miR-221, and miR-222, and their associated functional genomics data from the GEO database. Then, we performed an integration analysis to identify the essential target factors and interactions for the next survival analysis in breast cancer. Based on the results of our integrated analysis, we have identified significant common regulatory signatures including differentially expressed genes, enriched pathways, and transcriptional regulation such as interferon regulatory factors (IRFs) and signal transducer and activator of transcription 1 (STAT1). Finally, a reconstructed regulatory network of five miRNAs and 34 target factors was established and then applied to survival analysis in breast cancer. When we used expression data for individual miRNAs, only miR-21 and miR-22 were significantly associated with a survival change. However, we identified 45 significant miRNA-gene pairs that predict overall survival in breast cancer out of 170 one-on-one interactions in our reconstructed network covering all of five miRNAs, and several essential factors such as PSMB9, HLA-C, RARRES3, UBE2L6, and NMI. In our study, we reconstructed regulatory network of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets. These results may provide new insights into regulatory network-based precision medicine for breast cancer.
KW - Breast cancer
KW - MicroRNAs
KW - Network
KW - Pathways
KW - Survival analysis
UR - http://www.scopus.com/inward/record.url?scp=85062840012&partnerID=8YFLogxK
U2 - 10.1007/s10142-019-00670-7
DO - 10.1007/s10142-019-00670-7
M3 - Journal article
C2 - 30859354
AN - SCOPUS:85062840012
SN - 1438-793X
VL - 19
SP - 645
EP - 658
JO - Functional and Integrative Genomics
JF - Functional and Integrative Genomics
IS - 4
ER -