Abstract
Accumulating evidence has shown that aberrant lncRNA expression plays an oncogenic or tumor-suppressive role in the tumorigenesis of laryngeal cancer. However, the prognostic roles of lncRNAs in laryngeal cancer recurrence are still poorly understood. In this study, we obtained lncRNA expression profiles of 109 patients with laryngeal cancer by mining previously published gene expression microarray data from the Gene Expression Omnibus (GEO) and identified two lncRNAs associated with laryngeal cancer recurrence in the training dataset by using Cox regression analysis. Then these two lncRNAs were combined to a two-lncRNA signature for identifying patients at high-risk of disease recurrence. By applying this two-lncRNA signature to the testing dataset, a clear separation was observed in the survival curves between patients with low- or high-risk scores, indicating good reproducibility of this two-lncRNA signature in predicting disease-free survival of laryngeal cancer. Further analysis revealed that the prognostic value of the two-lncRNA signature was independent of other clinical features, including age, stage and grade. Subsequent gene set enrichment analysis suggested that the two-lncRNA signature was more likely to involve with GPCRs downstream signaling pathway, potassium channel pathway and aurora-A pathway. Our study demonstrated that the two-lncRNA signature may be a novel potential biomarker for prognosis of laryngeal cancer and may provide novel insights into the molecular mechanism of laryngeal cancer.
Highlights
Head and neck cancer is one of the commonly diagnosed cancers all over the world
By using the sample-splitting method and Cox regression analysis, we identified a twolncRNA signature associated with disease-free survival, and established a risk score formula using the expressions of these two Long non-coding RNAs (lncRNAs) in the training dataset
In order to identify potential prognostic lncRNAs associated with laryngeal cancer recurrence, we performed univariate Cox regression analysis to investigate the association between lncRNA expression and DFS in the training dataset
Summary
Head and neck cancer is one of the commonly diagnosed cancers all over the world. Laryngeal cancer is one of the most common types of head and neck cancer and has 4-fold higher incidence rates in men compared with women, accounting for about 0.79% of estimated numbers of newly diagnosed cases of invasive cancer expected in the United States in 2017 [1]. Assessing the recurrence risk of laryngeal cancer for each patient would greatly accelerate progress toward early detection of recurrent disease and lead to targeted treatment options and better survival rates for patients. Long non-coding RNAs (lncRNAs), a novel class of non-coding RNAs, are defined arbitrarily as noncoding transcripts longer than 200 nucleotides [3]. There is increasing evidence that lncRNAs have crucial roles in transcriptional regulation and epigenetic gene regulation www.impactjournals.com/oncotarget
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