Identification of a seven-miRNA signature as prognostic biomarker for lung squamous cell carcinoma
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Xujie Gao1,3,4,*, Yupeng Wu1,3,4,*, Wenwen Yu1,3,4, Hui Li1,2,3,4
1Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
2Department of Gastrointestinal Cancer Biology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
3National Clinical Research Center of Cancer, Tianjin, China
4Key Laboratory of Cancer Immunology and Biotherapy, Tianjin, China
*These authors have contributed equally to this work
Hui Li, email: [email protected]
Keywords: lung squamous cell carcinoma, microRNA, prognostic marker
Received: August 20, 2016 Accepted: October 19, 2016 Published: November 07, 2016
Background: Specific biomarkers for outcome prediction of lung squamous cell carcinoma (LUSC) are still lacking. This study assessed the prognostic value of differentially expressed miRNAs of LUSC patients.
Results: Twelve of the 133 most significantly altered miRNAs were associated with overall survival (OS) across different clinical subclasses of the Cancer Genome Atlas (TCGA) LUSC cohort. A linear prognostic model of seven miRNAs was developed to divide patients into high- and low-risk groups. Patients assigned to the high-risk group exhibited poor OS compared with patients in the low-risk group, which was further validated in the validation cohort and entire LUSC cohort.
Methods: MiRNA expression profiles with clinical information of 447 LUSC patients were obtained from TCGA. Most significantly altered miRNAs were identified between tumor and normal samples. Using survival analysis and supervised principal components method, a seven-miRNA signature for prediction of OS of LUSC patients was established. Survival receiver operating characteristic (ROC) analysis was used to assess the performance of survival prediction. The biological relevance of predicted miRNA targets was also analyzed using bioinformatics method.
Conclusions: The current study suggests that seven-miRNA signature may have clinical implications in the outcome prediction of LUSC.
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