BACKGROUND: Long non-coding RNA (LncRNA) PCA3 has been a well-established urine biomarker for the detection of prostate cancer (PCa). Our previous study showed a novel LncRNA FR0348383 is up-regulated in over 70% of PCa compared with matched benign tissues. The aim of this study was to evaluate the diagnostic value of urinary FR0348383 for men undergoing prostate biopsy due to elevated PSA (PSA > 4.0 ng/ml) and/or abnormal digital rectal examination (DRE). METHODS: Post-DRE first-catch urine specimens prior to prostate biopsies were prospectively collected. After the whole transcriptome amplification, quantitative real time polymerase chain reaction was applied to quantify urine FR0348383 and PSA levels. The FR0348383 score was calculated as the ratio of PSA and FR0348383 mRNA (PSA mRNA/FR0348383 mRNA × 1000). The diagnostic value of FR0348383 score was evaluated by logistic regression and decision curve analysis. RESULTS: 213 cases with urine samples containing sufficient mRNA were included, 94 cases had serum PSA level 4.0-10.0 ng/ml. PCa was identified in 72 cases. An increasing FR0348383 score was correlated with an increasing probability of a positive biopsy (P < 0.001). Multivariable logistic analysis indicated FR0348383 score (P < 0.001), PSA (P = 0.004), age (P = 0.007), prostate volume (P < 0.001) were independent predictors of PCa. ROC analysis demonstrated FR0348383 score outperformed PSA, %free PSA, and PSA Density in the prediction of PCa in the subgroup of patients with grey area PSA (AUC: 0.815 vs. 0.562 vs. 0.599 vs. 0.645). When using a probability threshold of 30% in the grey zone cohort, The FR0348383 score would save 52.0% of avoidable biopsies without missing any high grade cancers. CONCLUSIONS: FR0348383 transcript in post-DRE urine may be a novel biomarker for detection of PCa with great diagnostic value, especially in the grey zone cohort. The application of FR0348383 score in clinical practice might avoid unnecessary prostate biopsies and increase the specificity of PCa diagnosis.
BACKGROUND: Long non-coding RNA (LncRNA) PCA3 has been a well-established urine biomarker for the detection of prostate cancer (PCa). Our previous study showed a novel LncRNA FR0348383 is up-regulated in over 70% of PCa compared with matched benign tissues. The aim of this study was to evaluate the diagnostic value of urinary FR0348383 for men undergoing prostate biopsy due to elevated PSA (PSA > 4.0 ng/ml) and/or abnormal digital rectal examination (DRE). METHODS: Post-DRE first-catch urine specimens prior to prostate biopsies were prospectively collected. After the whole transcriptome amplification, quantitative real time polymerase chain reaction was applied to quantify urine FR0348383 and PSA levels. The FR0348383 score was calculated as the ratio of PSA and FR0348383 mRNA (PSA mRNA/FR0348383 mRNA × 1000). The diagnostic value of FR0348383 score was evaluated by logistic regression and decision curve analysis. RESULTS: 213 cases with urine samples containing sufficient mRNA were included, 94 cases had serum PSA level 4.0-10.0 ng/ml. PCa was identified in 72 cases. An increasing FR0348383 score was correlated with an increasing probability of a positive biopsy (P < 0.001). Multivariable logistic analysis indicated FR0348383 score (P < 0.001), PSA (P = 0.004), age (P = 0.007), prostate volume (P < 0.001) were independent predictors of PCa. ROC analysis demonstrated FR0348383 score outperformed PSA, %free PSA, and PSA Density in the prediction of PCa in the subgroup of patients with grey area PSA (AUC: 0.815 vs. 0.562 vs. 0.599 vs. 0.645). When using a probability threshold of 30% in the grey zone cohort, The FR0348383 score would save 52.0% of avoidable biopsies without missing any high grade cancers. CONCLUSIONS: FR0348383 transcript in post-DRE urine may be a novel biomarker for detection of PCa with great diagnostic value, especially in the grey zone cohort. The application of FR0348383 score in clinical practice might avoid unnecessary prostate biopsies and increase the specificity of PCa diagnosis.
Authors: Juan Pablo Lopez; Alpha Diallo; Cristiana Cruceanu; Laura M Fiori; Sylvie Laboissiere; Isabelle Guillet; Joelle Fontaine; Jiannis Ragoussis; Vladimir Benes; Gustavo Turecki; Carl Ernst Journal: BMC Med Genomics Date: 2015-07-01 Impact factor: 3.063