Profiling and bioinformatics analyses reveal differential circular RNA expression in ovarian cancer

Ovarian cancer (OC) is the deadliest form of gynecologic malignancy, with the majority of patients being diagnosed only once the disease reaches an advanced stage owing to a lack of available biomarkers capable of accurately detecting the disease. Stable circular RNAs (circRNAs) can be found at high levels in exosomes, and there is evidence to suggest that they may be viable diagnostic biomarkers for certain cancers. However, circRNAs in the serum of OC patients have rarely been evaluated to date. We therefore sought to investigate serum circRNA profiles of OC patients, and to explore whether these sorts of circRNAs could be used to detect early OC, serving as biomarkers of disease that may allow for the earlier treatment thereof. Second-generation sequencing was used to screen differentially expressed circRNAs in OC patient serum and also in the serum obtained from healthy controls, and circRNA expression was confirmed by qPCR. A bioinformatics-based approach was then used to assess what biological functions might be affected be the altered regulation of these RNA molecules. We further conducted GO, KEGG, and network analyses to further explore the expression of circRNAs. We detected 178 differentially expressed circRNAs in OC patient serum, of which 175 were up-regulated and 3 were down-regulated. We validated 5 of these identified circRNAs by qPCR to confirm their expression, and further found these RNAs to be closely linked with FC gamma R-mediated phagocytosis, VEGF signaling, Transcriptional misregulation in cancer, Chemokine signaling, ErbB signaling, and TNF signaling based on conducted analyses. This study provides a profile of circRNAs in OC patient serum, revealing a pattern of dysregulation of these RNAs associated with OC. Our bioinformatics analysis suggested that these circRNAs are likely related to OC development, and as such they may be viable novel OC biomarkers.