Abstract
BackgroundPrevious findings have indicated that the tumor, nodes, and metastases (TNM) staging system is not sufficient to accurately predict survival outcomes in patients with non-small lung carcinoma (NSCLC). Thus, this study aims to identify a long non-coding RNA (lncRNA) signature for predicting survival in patients with NSCLC and to provide additional prognostic information to TNM staging system.MethodsPatients with NSCLC were recruited from a hospital and divided into a discovery cohort (n = 194) and validation cohort (n = 172), and detected using a custom lncRNA microarray. Another 73 NSCLC cases obtained from a different hospital (an independent validation cohort) were examined with qRT-PCR. Differentially expressed lncRNAs were determined with the Significance Analysis of Microarrays program, from which lncRNAs associated with survival were identified using Cox regression in the discovery cohort. These prognostic lncRNAs were employed to construct a prognostic signature with a risk-score method. Then, the utility of the prognostic signature was confirmed using the validation cohort and the independent cohort.ResultsIn the discovery cohort, we identified 305 lncRNAs that were differentially expressed between the NSCLC tissues and matched, adjacent normal lung tissues, of which 15 are associated with survival; a 4-lncRNA prognostic signature was identified from the 15 survival lncRNAs, which was significantly correlated with survivals of NSCLC patients. This signature was further validated in the validation cohort and independent validation cohort. Moreover, multivariate Cox analysis demonstrates that the 4-lncRNA signature is an independent survival predictor. Then we established a new risk-score model by combining 4-lncRNA signature and TNM staging stage. The receiver operating characteristics (ROC) curve indicates that the prognostic value of the combined model is significantly higher than that of the TNM stage alone, in all the cohorts.ConclusionsIn this study, we identified a 4-lncRNA signature that may be a powerful prognosis biomarker and can provide additional survival information to the TNM staging system.
Highlights
Previous findings have indicated that the tumor, nodes, and metastases (TNM) staging system is not sufficient to accurately predict survival outcomes in patients with non-small lung carcinoma (NSCLC)
To confirm the reliability and repeatability of the microarray results, 5 out of 15 prognostic long non-coding RNA (lncRNA) were selected for qRT-PCR analysis with 30 pairs of samples that were randomly selected from the discovery cohort
The expression-level ratios of the 5 lncRNAs in cancer tissues versus adjacent tissues detected by qRT-PCR were consistent with the microarray results (Fig. 1a) and significant correlations were found between the qRT-PCR and microarray data for the 5 lncRNAs (Fig. 1b–f )
Summary
Previous findings have indicated that the tumor, nodes, and metastases (TNM) staging system is not sufficient to accurately predict survival outcomes in patients with non-small lung carcinoma (NSCLC). This study aims to identify a long non-coding RNA (lncRNA) signature for predicting survival in patients with NSCLC and to provide additional prognostic information to TNM staging system. In clinical practice, delayed diagnosis and the lack of effective prognostic biomarkers are two main reasons for poor survival of patients with NSCLC [2, 3]. An urgent need exists for new biomarkers that can help improve the accuracy of prognosis prediction, which would enhance the quality of life of patients as well as the survival rate [7, 8]
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