Oncotarget

Research Papers:

Transcriptome analysis reveals a long non-coding RNA signature to improve biochemical recurrence prediction in prostate cancer

Jinyuan Xu, Yujia Lan, Fulong Yu, Shiwei Zhu, Jianrong Ran, Jiali Zhu, Hongyi Zhang, Lili Li, Shujun Cheng _, Yun Xiao and Xia Li

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Oncotarget. 2018; 9:24936-24949. https://doi.org/10.18632/oncotarget.25048

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Abstract

Jinyuan Xu1,*, Yujia Lan1,*, Fulong Yu1,*, Shiwei Zhu1,*, Jianrong Ran1, Jiali Zhu1, Hongyi Zhang1, Lili Li1, Shujun Cheng1,2, Yun Xiao1 and Xia Li1

1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China

2State Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, Cancer Institute and Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100021, China

*These authors contributed equally to this work

Correspondence to:

Shujun Cheng, email: chengshj@263.net.cn

Yun Xiao, email: xiaoyun@ems.hrbmu.edu.cn

Xia Li, email: lixia@hrbmu.edu.cn

Keywords: lncRNA signature; prostate cancer; transcriptome; prognosis; BCR-free survival

Received: December 13, 2017     Accepted: February 27, 2018     Published: May 18, 2018

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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