CeNETs analysis reveals the prognostic value of a signature integration from five lncRNAs in breast cancer
| Autor: | Haiyan Dong, Rongzhong Jin, Qiong Zhong, Caihua Liao, Ke Wang, Tiancheng Zhang |
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| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Breast Neoplasms Kaplan-Meier Estimate Computational biology Biology Biochemistry Disease-Free Survival 03 medical and health sciences 0302 clinical medicine Breast cancer Cancer genome Databases Genetic microRNA Biomarkers Tumor medicine Humans Gene Regulatory Networks In patient Molecular Biology Competing endogenous RNA Computational Biology RNA Cell Biology Prognosis medicine.disease Long non-coding RNA Gene Expression Regulation Neoplastic MicroRNAs 030104 developmental biology 030220 oncology & carcinogenesis Female RNA Long Noncoding |
| Zdroj: | Journal of Cellular Biochemistry. 120:13509-13519 |
| ISSN: | 1097-4644 0730-2312 |
| DOI: | 10.1002/jcb.28626 |
| Popis: | Background The competitive endogenous RNA (ceRNA) hypothesis is a novel effective theory that can enable us to deeply understand the mechanisms of comprehensive diseases. Methods In this study, we first downloaded RNAseq data and microRNA (miRNA) seq data of breast cancer from The Cancer Genome Atlas and further explored the regulation of ceRNA network in breast cancer using comprehensive bioinformatics tools. Results The results revealed that five miRNAs, including hsa-miR-10b, hsa-miR-21, hsa-miR-183, hsa-miR-1258, and hsa-miR-3200 formed the core of ceRNA network. Moreover, five long noncoding RNAs that could competitively bind with miR-10b, respectively, named ACTA2-AS1, RP11-384P7.7, RP11-327J17.9, RP11-124N14.3, and RP11-645C24.5, were discovered as an integration signature with great potential in the prediction of survival outcomes in patients with different stages of breast cancer. Conclusions This indicates that these five long noncoding RNAs may be potential novel diagnostic and prognostic biomarkers of breast cancer. |
| Databáze: | OpenAIRE |
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