Identification of a seven-miRNA signature as prognostic biomarker for lung squamous cell carcinoma.
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.
Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.|National Clinical Research Center of Cancer, Tianjin, China.|Key Laboratory of Cancer Immunology and Biotherapy, Tianjin, China.
Xujie
X
Gao
Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.|National Clinical Research Center of Cancer, Tianjin, China.|Key Laboratory of Cancer Immunology and Biotherapy, Tianjin, China.
Yupeng
Y
Wu
Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.|National Clinical Research Center of Cancer, Tianjin, China.|Key Laboratory of Cancer Immunology and Biotherapy, Tianjin, China.
Wenwen
W
Yu
Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.|Department of Gastrointestinal Cancer Biology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.|National Clinical Research Center of Cancer, Tianjin, China.|Key Laboratory of Cancer Immunology and Biotherapy, Tianjin, China.
Hui
H
Li
D000368:Aged; D019540:Area Under Curve; D014408:Biomarkers, Tumor / Q000235:genetics*; D002294:Carcinoma, Squamous Cell / Q000235:genetics* / Q000401:mortality / Q000473:pathology; D030541:Databases, Genetic; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D020022:Genetic Predisposition to Disease; D006801:Humans; D053208:Kaplan-Meier Estimate; D016014:Linear Models; D008175:Lung Neoplasms / Q000235:genetics* / Q000401:mortality / Q000473:pathology; D008297:Male; D035683:MicroRNAs / Q000235:genetics*; D008875:Middle Aged; D015999:Multivariate Analysis; D010641:Phenotype; D011237:Predictive Value of Tests; D025341:Principal Component Analysis; D011379:Prognosis; D016016:Proportional Hazards Models; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors; D059467:Transcriptome
D014408:Biomarkers, Tumor; D035683:MicroRNAs
lung squamous cell carcinoma; microRNA; prognostic marker