Publication date: Available online 22 January 2017
Source:Artificial Intelligence in Medicine
Author(s): Zhen Li, Qianlan Yao, Songjian Zhao, Zhen Wang, Yixue Li
BackgroundEsophageal adenocarcinoma (EAC) is one of the most aggressive gastroesophageal cancers. PTGS2, EGFR, ERBB2 and TP53 are the traditional EAC prognostic biomarkers, but they are still limited in their ability to effectively predict the overall survival.ObjectivesTo identify an improved biomarker for predicting the prognosis of EAC by using the expression profile.Materials and methodsDifferential co-expression analysis and differential expression analysis were performed to identify the related genes of EAC. The 5-fold cross-validation was used to select a prognostic biomarker from the 532 EAC related genes.ResultsCRNKL1 was identified as a prognostic biomarker to predict the survival of EAC patients. It could significantly stratify EAC patients into high-risk and low-risk groups and was much better than the traditional biomarkers. Furthermore, ROC curve also verified that CRNKL1 with the highest area under the curve (AUC), reaching a sensitivity of 83.33% and a specificity of 78.57%.ConclusionsOur research proposed that CRNKL1 might be a novel prognostic biomarker with better predictive ability by comparing with the traditional biomarkers, which provided a preferable opportunity in the clinical applications of EAC.
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Medicine by Alexandros G. Sfakianakis,Anapafseos 5 Agios Nikolaos 72100 Crete Greece,00302841026182,00306932607174,alsfakia@gmail.com,
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