Abstract
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.
Highlights
Ovarian cancer (OC) is the most common disease worldwide with the highest death rate of all gynecological tumors (Siegel et al, 2018)
58,119 potential transcription factor (TF)-long non-coding RNA (lncRNA) relationships were identified based on initial sequence binding analysis, only a fraction (4.91–6.72%) of these regulating edges were actively constructed in each stage
We explored the functions of lncRNAs by using Enrichr web based tool (Chen et al, 2013; Kuleshov et al, 2016), FIGURE 4 | Functional analysis of stage-specific TF-lncRNA regulatory groups. (A) Group a was found to be associated with Repression of WNT target genes and other ovarian cancer (OC)-related pathways. (B) Group c was found to be associated with chondroitin sulfate biosynthesis pathway and process (GO:0030206). (C) A series of immune cell activation and differentiation processes were found in group d. (D) Group e was associated with FGFR ligand binding and activation pathways
Summary
Ovarian cancer (OC) is the most common disease worldwide with the highest death rate of all gynecological tumors (Siegel et al, 2018). Due to its asymptomatic stages and rapid metastasis to the peritoneum, most patients have already developed metastases by the time they are first diagnosed (Bowtell, 2010). Prognostic TF-lncRNA Regulation in Ovarian Cancer diagnosis (Rustin et al, 2011). The pathological development of OC is a complex progression that depends on multiple alterations of oncogenes and tumor suppressors. Our knowledge of OC is increasingly expanding, the precise molecular mechanisms underlying this complex disease are still not fully understood. It is important to understand mechanisms promoting the progression of OC and to identify reliable markers for predicting clinical outcomes in patients
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call