Four Circulating Long Non-Coding RNAs Act as Biomarkers for Predicting Cervical Cancer.

BACKGROUND/AIMS: Circulation long non-coding RNAs (lncRNAs) have emerged recently as major players in tumor biology and might be applied for cancer diagnosis, prognosis, or potential therapeutic targets. In this study, we aimed to explore whether the circulation lncRNA could predict the tumorigenesis of surgical squamous cervical cancer (CC).

METHODS: In this study, we applied the lncRNA microarray to screen the potential biomarker for CC. Real-time quantitate polymerase chain reaction was conducted for further validation in a larger sample size. The multi-stage validation and risk score formula analysis were used to examine the sensitivity and specificity.

RESULTS: We discovered 4 lncRNAs including HOTAIR, PVT1, XLOC_000303, and AL592284.1, which were upregulated in CC comparing with the cancer-free controls. Further, the receiver operating characteristic curve (ROC) analysis by risk score formula revealed the combined 4 factors with a high diagnostic ability with the area under ROC curve value of 0.875 and 0.958 in training set and validation set respectively. We finally confirmed the stable detection of the 4 lncRNAs by 5 cycles of freezing and thawing.

CONCLUSION: HOTAIR, PVT1, XLOC_000303, and AL592284.1 might be the potential biomarkers for predicting the tumorigenesis of CC in the future.