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Prognostic Value of Long Non-Coding RNA Signatures in Bladder Cancer
26 Pages Posted: 17 Mar 2019
More...Abstract
Background: Long noncoding RNAs (lncRNAs) contribute to initiation, progression and metastasis of bladder cancer. We aim to evaluate the potential utility of lncRNAs to construct lncRNA-based classifiers of BLCA prognosis and recurrence.
Methods: Based on the RNA-seq data of 406 bladder cancer from The Cancer Genome Atlas project, the lncRNA-based classifier for overall survival(OS) and lncRNA-based classifier for relapse-free survival (RFS) were built by using the least absolute shrinkage and selection operation (LASSO) Cox regression model in 271 randomly selected samples (training cohort) and validated the two classifiers in the remaining 135 samples (internal validation cohort).
Results: In the training cohort, a 14-lncRNA-based classifier for OS and a 12-lncRNA-based classifier for RFS were constructed by LASSO Cox regression mode at 20-fold cross-validation. According to the prediction value, patients were divided into high-risk and low-risk groups based on the cut-off of the median risk score. The Kaplan-Meier log-rank test showed significant differences in OS and RFS between low- and high-risk groups in the training cohorts (p<0.01), validation cohorts (p<0.01) and in the whole cohorts (p<0.01). In the time-dependent ROC curve analysis, the AUCs for OS in the first, third, and fifth year were 0.734, 0.78, and 0.78 respectively, and the prediction capability of the 14-lncRNA classifier was superior to the other published lncRNA classifier. As for RFS, the AUCs in the first, third, and fifth year were 0.755, 0.715, and 0.740 respectively, and the12-lncRNA-based classifier is firstly built to be as powerful prognostic predictor of bladder cancer recurrence.
Conclusions: In conclusion, the 14-lncRNA-based classifier for OS and the 12-lncRNA-based classifier for RFS constructed by LASSO Cox regression could be novel and independent prognostic factors for OS and RFS individually and might complement clinicopathological characteristics and optimize personalized management of BLCA.
Funding: This work was supported by National Natural Science Foundation of China [81672546, 81602253, 81772703, 81872083], Natural Science Foundation of Beijing [7152146, 7172219] and The Capital Health Research and Development of Special [2016–1-4077].
Declaration of Interest: The authors declare no conflict of interest.
Ethical Approval: Not applicable.
Keywords: bladder cancer, lncRNA, prognostic, OS, RFS
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