Regulatory network reconstruction of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets
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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.
KeywordsMicroRNAs Network Breast cancer Pathways Survival analysis
The Cancer Genome Atlas
interferon regulatory factors
signal transducer and activator of transcription 1
reads per million mapped
Robust Multichip Average
gene set enrichment analysis
normalized enrichment score
differentially expressed genes
transcription factor binding sites
the basic helix-loop-helix
proteasome subunit beta 9
human leukocyte antigen C
retinoic acid receptor responder 3
ubiquitin conjugating enzyme E2 L6
Many thanks to the National Postdoctoral office and the Hongkong Scholars Association.
KH, JFH, and APL designed the study. WXL, DGG, MTG, SDY, and ZF performed the experiments and/or data analysis. KH, WXL, DGG, and APL wrote the paper with input from all authors.
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.
Compliance with ethical standards
Ethics approval and consent to participate
Consent for publication
Availability of data and material
The authors declare that they have no conflicts of interest.
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