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A six‐microRNA risk score model predicts prognosis in esophageal squamous cell carcinoma
Author(s) -
Mao Yu,
Fu Zhanzhao,
Zhang Yunjie,
Dong Lixin,
Zhang Yanqiu,
Zhang Qiang,
Li Xin,
Wang Chao
Publication year - 2019
Publication title -
journal of cellular physiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.529
H-Index - 174
eISSN - 1097-4652
pISSN - 0021-9541
DOI - 10.1002/jcp.27429
Subject(s) - microrna , receiver operating characteristic , esophageal cancer , proportional hazards model , survival analysis , cancer , oncology , stage (stratigraphy) , biomarker , medicine , biology , gene , genetics , paleontology
Esophageal cancer ranks the eighth most common cancer and the sixth most common cause of cancer death worldwide. MicroRNAs (miRNAs) are small noncoding RNAs that regulate a wide variety of cancer‐related cellular processes. In the current study, a series of previously published gene expression microarray data from Gene Expression Ominus and The Cancer Genome Atlas were downloaded and further divided into training, internal, and external validation sets. Least absolute shrinkage and selectionator operator Cox regression model along with 10‐fold cross‐validation was performed to select the miRNAs associated with the prognosis of esophageal squamous cell carcinoma (ESCC) and constructed a six‐miRNA signature. Then the prediction accuracy of this signature was assessed in validation and test set using Kaplan–Meier analysis, time‐dependent receiver operating characteristic (ROC) curves and dynamic area under the ROC curve. According to the result, the prediction accuracy of miRNA signature was much better than that of tumor–node–metastasis (TNM) stage in all the three sets. Stratified analysis also demonstrated that the predict ability of this signature was independent of TNM stage. Finally, function experiments including apoptosis and colony formation assay were performed to further reveal the regulatory role of miRNAs in ESCC. Our study demonstrated the promising potential application of this novel six‐miRNA signature as an independent biomarker for survival prediction of ESCC patients.