PeerJ · 2019 · 10 citations · 37 references
MedicineBioinformaticsOncologyMolecular OncologyNeoplasiaSurvival AnalysisCancer BiomarkersCancer Survival AnalysisEsophageal CancerMolecular Classification Of TumorsMolecular Tumor ProfilingNoncoding Rna In CancerAdenocarcinoma Of The EsophagusMicrorna BiomarkersMicrorna In CancerMicrorna Prognostic MarkersMolecular Prognostic MarkersPrognostic Tumor MarkersRna SequencingRna Sequencing (Rna-seq)
BACKGROUND: The microRNAs (miRNAs) have been validated as prognostic markers in many cancers. Here, we aimed at developing a miRNA-based signature for predicting the prognosis of esophagus adenocarcinoma (EAC). METHODS: The RNA-sequencing data set of EAC was downloaded from The Cancer Genome Atlas (TCGA). Eighty-four patients with EAC were classified into a training set and a test set randomly. Using univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO), we identified prognostic factors and constructed a prognostic miRNA signature. The accuracy of the signature was evaluated by the receiver operating characteristic (ROC) curve. RESULT: In general, in the training set, six miRNAs (hsa-mir-425, hsa-let-7b, hsa-mir-23a, hsa-mir-3074, hsa-mir-424 and hsa-mir-505) displayed good prognostic power as markers of overall survival for EAC patients. Relative to patients in the low-risk group, those assigned to the high-risk group according to their risk scores of the designed miRNA model displayed reduced overall survival. This 6-miRNA model was validated in test and entire set. The area under curve (AUC) for ROC at 3 years was 0.959, 0.840, and 0.868 in training, test, and entire set, respectively. Molecular functional analysis and pathway enrichment analysis indicated that the target messenger RNAs associated with 6-miRNA signature were closely related to several pathways involved in carcinogenesis, especially cell cycle. CONCLUSION: In summary, a novel 6-miRNA expression-based prognostic signature derived from the EAC data of TCGA was constructed and validated for predicting the prognosis of EAC.
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Christina Fitzmaurice, Christine A. Allen, Ryan M Barber et al. · JAMA Oncology · 2016 · 6.3K citations · Full text
The Global Burden of Cancer 2013
Christina Fitzmaurice, Daniel Dicker, Amanda Pain et al. · JAMA Oncology · 2015 · 2.8K citations · Full text