Transcriptome analysis reveals a long non-coding RNA signature to improve biochemical recurrence prediction in
Jinyuan Xu1, Yujia Lan1, Fulong Yu1
1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
Abstract:
Despite highly successful treatments for localized prostate cancer (PCa), prognostic biomarkers are needed to improve patient management and prognosis. Accumulating evidence suggests that long noncoding RNAs (lncRNAs) are key regulators with biological and clinical significance. By transcriptome analysis, we identified a set of consistently dysregulated lncRNAs in PCa across different datasets and revealed an eight-lncRNA signature that significantly associated with the biochemical recurrence (BCR)-free survival. Based on the signature, patients could be classified into high- and low-risk groups with significantly different survival (HR = 2.19; 95% CI = 1.67-2.88; P < 0.0001). Validations in the validation cohorts and another independent cohort confirmed its prognostic value for recurrence prediction. Multivariable analysis showed that the signature was independent of common clinicopathological features and stratified analysis further revealed its role in elevating risk stratification of current prognostic models. Additionally, the eight-lncRNA signature was able to improve on the CAPRA-S score for the prediction of BCR as well as to reflect the metastatic potential of PCa. Functional characterization suggested that these lncRNAs which showed PCa-specific expression patterns may involve in critical processes in tumorigenesis. Overall, our results demonstrated potential application of lncRNAs as novel independent biomarkers. The eight-lncRNA signature may have clinical potential for facilitating further stratification of more aggressive patients who would benefit from adjuvant therapy.
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