You have to be registered and logged in for purchasing articles.

Abstract

ORIGINAL ARTICLELong Non-Coding RNA Expression Signature Hallmarks Promising Efficacy in Identification of Human Non-Small Cell Lung Cancer: a Meta-Analysis Study by Hongyun Yang, Yanyan Han, Lele Wu, Chaojun Wu

Background: The long non-coding RNAs (lncRNAs) are significantly altered in an expanding list of malignant neoplasms, suggesting that they might be popularized as potential biomarkers for cancer detection. This study sought to validate the diagnostic efficacy of lncRNA expression signature(s) as potential biomarker(s) for non-small cell lung cancer (NSCLC) diagnosis.
Methods: We conducted the online databases search for all eligible studies. A quantitative meta-analysis was performed using Stata 12.0 and Meta-Disc 1.4 statistical programs. Sensitivity analysis and a meta-regression test were applied to deeply trace the underlying heterogeneity sources.
Results: Eight cohorts comprised 775 NSCLC patients and 630 matched controls were included. Our data manifested that lncRNA expression profiling harbored a pooled sensitivity of 0.77 (95% CI: 0.71 - 0.82) and specificity of 0.86 (95% CI: 0.80 - 0.90) in discriminating NSCLC cases from cancer-free individuals, along with an AUC (area under the curve) value of 0.88. Further subgroup analysis revealed that paralleled testing of lncRNAs (sensitivity, specificity, and AUC of 0.90, 0.80 and 0.96, respectively) substantially strengthened the diagnostic efficacy as compared with the single testing pattern (sensitivity, specificity, and AUC of 0.71, 0.77 and 0.82, respectively). Other stratified analysis of ethnicity, histology type, and test matrix also presented robust results.
Conclusions: Altogether, our results indicate that lncRNA expression signature(s) might be applicable as complementary biomarker(s) for the identification of NSCLC.

DOI: 10.7754/Clin.Lab.2017.170325