Identification of EMT-Related lncRNAs as a Potential Prognostic Biomarker and Therapeutic Targets for Pancreatic Adenocarcinoma
Abstract Background: Epithelial-Mesenchymal Transition (EMT) can promote carcinoma progression by multiple mechanisms, many studies demonstrated the invasiveness of pancreatic adenocarcinoma (PAAD) associated with the EMT, but how it acts in a lncRNA dependent manner is unclear. Methods: We investigated 146 PAAD samples from The Cancer Genome Atlas (TCGA) and 92 samples from the International Cancer Genome Consortium (ICGC). Gene set variation analysis (GSVA) and weighted correlation network analysis (WGCNA) were applied to explore the EMT related long non-coding RNAs (EMTlnc). Univariate Cox regression analysis was performed to screen their prognostic roles in PAAD patients. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to establish an EMT-related lncRNA prognostic signature (EMT-LPS). We also established a competing endogenous RNA (ceRNA) network. Results: 33 prognostic EMTlnc were identified as prognostic lncRNAs and an EMT-LPS were established. We divided the patients into low- and high-risk subgroups according to corresponding risk scores. The EMT-LPS showed a powerful prognostic predicting ability in stratification analysis. Principal component analysis (PCA) showed the low- and high-risk subgroups had distinct EMT status. Enrichment analysis indicated malignancy correlated biological processes, pathways and hallmarks were more common in the high-risk subgroup. Moreover, we constructed a nomogram that had a strong ability to forecast the overall survival (OS) of the PAAD patients in both datasets. Conclusion: EMT-LPS are important factors in the carcinoma progression of PAAD and may help in decision making regarding the choice of prognosis assessment and provide us clues to design the new drugs for PAAD.