BACKGROUND & AIMS: Current studies have indicated that long non-coding RNAs (lncRNAs) could act as tumor biomarkers for disease diagnosis and prognosis prediction. In this study, we mainly focused on determining the expression of circulating lncRNAs in patients suffering for hilar cholangiocarcinoma (HC), aiming to reveal the potential lncRNA as a fingerprint. METHODS: A total 12 lncRNAs were previously proven to be aberrantly expressed in HC tumor tissues. All of the 12 lncRNAs were selected as candidate targets for subsequent circulating lncRNA assay. The candidate lncRNAs were validated by qRT-PCR arranged in training and validation sets. The risk score analysis was employed. Data was presented with receiver operating characteristic curve (ROC). RESULTS: Circulating PCAT1, MALAT1, and CPS1-IT1 were significantly increased in plasma samples of HC patients in both the training set and validation set. Through ROC analysis, we found that the three plasmatic lncRNAs presented the area under ROC curve value (AUC) as 0.784, 0.860, and 0.677. Further combination with the three factors indicated a higher power (AUC, 0.893; sensitivity, 85.5%; specificity, 93.2%). CONCLUSION: This was the first time to reveal the potential circulating fingerprints for predicting HC. PCAT1, MALAT1, and CPS1-IT1 may act as novel early diagnosis biomarkers for predicting HC.
BACKGROUND & AIMS: Current studies have indicated that long non-coding RNAs (lncRNAs) could act as tumor biomarkers for disease diagnosis and prognosis prediction. In this study, we mainly focused on determining the expression of circulating lncRNAs in patients suffering for hilar cholangiocarcinoma (HC), aiming to reveal the potential lncRNA as a fingerprint. METHODS: A total 12 lncRNAs were previously proven to be aberrantly expressed in HC tumor tissues. All of the 12 lncRNAs were selected as candidate targets for subsequent circulating lncRNA assay. The candidate lncRNAs were validated by qRT-PCR arranged in training and validation sets. The risk score analysis was employed. Data was presented with receiver operating characteristic curve (ROC). RESULTS: Circulating PCAT1, MALAT1, and CPS1-IT1 were significantly increased in plasma samples of HC patients in both the training set and validation set. Through ROC analysis, we found that the three plasmatic lncRNAs presented the area under ROC curve value (AUC) as 0.784, 0.860, and 0.677. Further combination with the three factors indicated a higher power (AUC, 0.893; sensitivity, 85.5%; specificity, 93.2%). CONCLUSION: This was the first time to reveal the potential circulating fingerprints for predicting HC. PCAT1, MALAT1, and CPS1-IT1 may act as novel early diagnosis biomarkers for predicting HC.