Unraveling UCA1 lncRNA prognostic utility in urothelial bladder cancer

2019 
: In the era of precision oncology, bladder cancer (BlCa) is characterized by generic patient management and lack of personalized prognosis and surveillance. Herein, we have studied the clinical significance of urothelial cancer associated 1 (UCA1) lncRNA in improving patients' risk stratification and prognosis. A screening cohort of 176 BlCa patients was used for UCA1 quantification. The Hedegaard et al. (n = 476) and The Cancer Genome Atlas (TCGA) provisional (n = 413) were analyzed as validation cohorts for non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC), respectively. Patients' survival outcome was assessed using recurrence and progression for NMIBC or death for MIBC as clinical endpoint events. Bootstrap analysis was performed for internal validation of Cox regression analysis, whereas the clinical benefit of disease prognosis was assessed by decision curve analysis. UCA1 was significantly overexpressed in bladder tumors compared with normal urothelium, which was confirmed only in the case of NMIBC. Interestingly, reduced expression of UCA1 was correlated with muscle-invasive disease as well as with tumors of higher stage and grade. UCA1 loss was strongly associated with higher risk of short-term relapse [hazard ratio (HR) = 1.974; P = 0.032] and progression to invasive stages (HR = 3.476; P = 0.023) in NMIBC. In this regard, Hedegaard et al. and TCGA validation cohorts confirmed the unfavorable prognostic nature of UCA1 loss in BlCa. Finally, prognosis prediction models integrating UCA1 underexpression and established clinical disease markers contributed to improved stratification specificity and superior clinical benefit for NMIBC prognosis. Underexpression of UCA1 correlates with worse disease outcome in NMIBC and contributes to superior prediction of disease early relapse and progression as well as improved patient stratification specificity.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    60
    References
    8
    Citations
    NaN
    KQI
    []