Supplementary Material for: Comprehensive Analysis of Differentially Expressed Profiles of lncRNAs/mRNAs and miRNAs with Associated ceRNA Networks in Triple-Negative Breast Cancer
datasetposted on 11.10.2018 by Yang R., Xing L., Wang M., Chi H., Zhang L., Chen J.
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Background/Aims: Triple-negative breast cancer (TNBC) is a subtype of highly malignant breast cancer with poor prognosis. Growing evidence indicates that Long noncoding RNAs (lncRNAs) play important regulatory roles in the development and progression of a variety of cancers including breast cancer. However, the underlying mechanisms remain largely unknown. Methods: Here, we compared the expression profiles of mRNAs, lncRNAs and miRNAs between 111 TNBC tissues and 104 non-cancerous tissues utilizing RNA-Seq Data from The Cancer Genome Atlas (TCGA). Gene Ontology and KEGG pathway enrichment analyses were executed to investigate the principal functions of the significantly dysregulated mRNAs. Moreover, Kaplan-Meier survival analyses were performed to determine the effects of differentially expressed lncRNAs/mRNAs/miRNAs on overall survival. Subsequently, we constructed a competing endogenous RNA (ceRNA) network, which included 66 dysregulated lncRNAs, 24 miRNAs and 55 mRNAs. The four dysregulated lncRNAs, three aberrantly expressed miRNAs and four mRNAs were confirmed in the ceRNA network by qRT-PCR in 30 pairs of samples, respectively. Results: A total of 1441 lncRNAs, 114 miRNA and 2501 mRNAs were found to be differentially expressed in TNBC tissues compared with controls. 109 lncRNAs and 124 mRNAs might serve as prognostic signature for patients with TNBC according to the survival analysis. Functional analysis revealed that 19 mRNAs in the ceRNA network were enriched in 17 cancer-related pathways. Conclusion: Taken together, we identified novel lncRNAs/miRNAs which may serve as potential biomarkers to predict the survival and therapeutic targets for TNBC patients based on a large-scale sample. More importantly, we constructed the ceRNA network of TNBC, which provides valuable information to further explore the molecular mechanism underlying tumorigenesis and development of TNBC.