Background: There is increasing evidence that long non-coding RNA are involved in the occurrence and progression of various tumors as carcinogenic or tumor suppressor regulators. Aims: Our study purposed to identify a novel lncRNA signature panel and evaluate its predictive value on cholangiocarcinoma (CCA) prognosis. Methods: Differentially expressed lncRNA were identified in CCA patients from The Cancer Genome Atlas database. The "edgeR" package and Cox regression analysis was used to establish a lncRNA prognostic model, which allowed patients to be divided into high-risk and low-risk groups. Through Receiver operating curves analysis, 90 CCA patients from the First Affiliated Hospital of Wenzhou Medical University (WMU) was performed to investigate the specificity and sensitivity of the model. By using Gene Ontology function and Kyoto Encyclopedia Gene and Genome pathway enrichment analysis, we explored the potential function of prognosis lncRNA. Results: A total of 1192 differential expression of lncRNA were identified in CCA and normal tissues. Five lncRNAs (HULC; AL359715.5; AC006504.8; AC090114.2; AP00943.4) were screened to establish a predictive model, whose high predictive power was validated in 90 CCA patients from WMU. Further analysis showed the independent prognostic capability of 5-lncRNA in the model, which had high sensitivity and specificity. Moreover, functional enrichment analysis suggested prognostic lncRNAs were primarily associated with CCA-related various biological processes. Conclusions: Our data established a novel lncRNA prognostic model for CCA, provided prognostic more useful information that went beyond traditional clinical pathology to predict survival in CCA patients. In addition, it revealed new molecular mechanisms of CCA. Funding: This work was supported by the grants from the Natural Science Foundation of Zhejiang Province (LY17H160047), the Public Projects of Zhejiang Province (2016C37127, 2018C37114), the National Natural Science Foundation of China (81470868, 81772628, 81703310). Declaration of Interest: The authors declare no conflict of interests. Ethical Approval: This study was approved by WMU’s Ethics Committee.
