A Novel and Robust Long Noncoding RNA Panel to Predict the Prognosis of Pancreatic Cancer.

Abstract

Pancreatic cancer (PC) is one of the most lethal malignancies with an extremely poor prognosis. In this study, we aim to construct a long noncoding RNA (lncRNA)-based panel biomarker to predict the overall survival of PC patients. The lncRNA expression profiles of PC samples were extracted from The Cancer Genome Atlas (TCGA-PAAD, n = 176) and International Cancer Genome Consortium (PACA-CA, n = 180). We then developed a risk score model according to the lncRNAs expressions from the TCGA-PAAD cohort and further validated it in the PACA-CA cohort. The potential biological functions for the prognostic lncRNAs were investigated using gene set enrichment analysis (GSEA). In the TCGA-PAAD cohort, three lncRNAs (AC009014.3, RP11-48O20.4, and UCA1) were found to be strongly associated with the prognosis of PC. These lncRNAs were integrated to build a three-lncRNA prognostic model that could divide individuals into low- and high-risk groups. Patients of TCGA-PAAD cohort in the high-risk group showed a poorer overall survival than those in the low-risk group (median: 17.3 months vs. 30.4 months, log-rank p < 0.001). Similar results were documented in the PACA-CA cohort (median: 15.2 months vs. 21.0 months, log-rank p < 0.001) and in the stratified analyses by patients' age and TNM stage. In addition, the signature exhibited an independent prognostic power and was significantly correlated with tumor relapse and patients' response to chemotherapy. GSEA indicated that the three-lncRNA signature may be involved in many known biological functions in cancer, especially the epithelial mesenchymal transformation. In conclusion, the identified three-lncRNA signature in our study may serve as a robust and useful prognostic biomarker in PC patients.