期刊
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
卷 8, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fbioe.2020.00460
关键词
ovarian cancer; lncRNAs; transcription factors; prognostic signature; functional analysis
资金
- National Natural Science Foundation of China [81902646, 31601080]
- Postdoctoral Foundation of China [2018T110314, 2016M600258]
- Postdoctoral Foundation of Heilongjiang Province [LBH-Z19077, LBH-TZ18, LBH-Z16141]
The pathological development of ovarian cancer (OC) is a complex progression that depends on multiple alterations of coding and non-coding genes. Therefore, it is important to capture the transcriptional-regulating events during the progression of OC development and to identify reliable markers for predicting clinical outcomes in patients. A dataset of 399 ovarian serous cystadenocarcinoma patients at different stages from The Cancer Genome Atlas (TCGA) was analyzed. Stage-specific transcription factor (TF)-long non-coding RNA (lncRNA) regulatory networks were constructed by integrating high-throughput RNA molecular profiles and TF binding information. Systematic analysis was performed to characterize the TF-lncRNA-regulating behaviors across different stages of OC. Cox regression analysis and Kaplan-Meier survival curves were used to evaluate the prognostic efficiency of TF-lncRNA regulations and cliques. The stage-specific TF-lncRNA regulatory networks at three OC stages (II, III, and IV) exhibited common structures and specific topologies of risk TFs and lncRNAs. A TF-lncRNA activity profile across different stages revealed that TFs were highly stage-selective in regulating lncRNAs. Functional analysis indicated that groups of TF-lncRNA interactions were involved in specific pathological processes in the development of OC. In a STAT3-FOS co-regulating clique, the TFs STAT3 and FOS were selectively regulating target lncRNAs across different OC stages. Further survival analysis indicated that this TF-lncRNA biclique may have the potential for predicting OC prognosis. This study revealed the topological and dynamic principles of TF-lncRNA regulatory networks and provided a resource for further analysis of stage-specific regulating mechanisms of OC.
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