Plasma circRNA microarray profiling identifies novel circRNA biomarkers for the diagnosis of ovarian cancer

Circular RNA (circRNA), a class of RNA with a covalent closed circular structure that widely existed in serum and plasma, has been considered an ideal liquid biopsy marker in many diseases. In this study, we employed microarray and qRT-PCR to evaluate the potential circulating circRNAs with diagnostic efficacy in ovarian cancer.

We used microarray to explore the circRNA expression profile in ovarian cancer patients' plasma and quantitative real-time (qRT)-PCR approach to assessing the candidate circRNA's expression. Then the receiver operating characteristic (ROC) curve was employed to analyze the diagnostic values of candidate circRNAs. The diagnostic model circCOMBO was a combination of hsa_circ_0003972 and hsa_circ_0007288 built by binary logistic regression. Then bioinformatic tools were used to predict their potential mechanisms.

Hsa_circ_0003972 and hsa_circ_0007288 were downregulated in ovarian cancer patients' plasma, tissues, and cell lines, comparing with the controls. Hsa_circ_0003972 and hsa_circ_0007288 exhibited diagnostic values with the Area Under Curve (AUC) of 0.724 and 0.790, respectively. circCOMBO showed a better diagnostic utility (AUC: 0.781), while the combination of circCOMBO and carbohydrate antigen 125 (CA125) showed the highest diagnostic value (AUC: 0.923). Furthermore, the higher expression level of hsa_circ_0007288 in both plasma and ovarian cancer tissues was associated with lower lymph node metastasis potential in ovarian cancer.

Our results revealed that hsa_circ_0003972 and hsa_circ_0007288 may serve as novel circulating biomarkers for ovarian cancer diagnosis.