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KMID : 1011820200610040411
Investigative and Clinical Urology
2020 Volume.61 No. 4 p.411 ~ p.418
A novel urinary mRNA signature using the droplet digital polymerase chain reaction platform improves discrimination between prostate cancer and benign prostatic hyperplasia within the prostate-specific antigen gray zone
Kang Ho-Won

Lee Hee-Youn
Byun Young-Joon
Jeong Pil-Du
Yoon Jin-Sun
Kim Dong-Ho
Kim Won-Tae
Kim Yong-June
Lee Sang-Cheol
Yun Seok-Joong
Kim Wun-Jae
Abstract
Purpose: The aim of this study was to identify a noninvasive urinary marker for prostate cancer (PCa) diagnosis and to validate the clinical performance of this novel urinary mRNA signature using the droplet digital polymerase chain reaction (ddPCR) approach.

Materials and Methods: A gene expression microarray (HT-12, Illumina Inc., USA) was used to identify genes differentially expressed between 16 PCa and 8 benign prostatic hyperplasia (BPH) tissues; ddPCR (QX200; Bio-Rad Laboratories, USA) was carried out to quantify the expression of selected genes in urine. The urinary molecular PCa risk score (UMPCaRS) was calculated by using the sum of three upregulated genes as the numerator and the sum of three downregulated genes as the denominator. The diagnostic utility of the UMPCaRS was validated by using a screening set (10 PCa and 10 BPH samples) and a validation set (131 PCa and 105 BPH samples).

Results: Three upregulated genes (PDLIM5, GDF-15, THBS4) and three downregulated genes (UPK1A, SSTR3, NPFFR2) were selected from the microarray and subjected to ddPCR. The UMPCaRS for PCa in the screening and validation sets was significantly higher than that for BPH. For the validation set, the diagnostic accuracy of the UMPCaRS was comparable with that of prostate-specific antigen (PSA). Importantly, in the ¡°PSA gray zone¡± (3?10 ng/mL), the AUC for the UMPCaRS was 0.843 and that for PSA was 0.628 (p<0.001).

Conclusions: The data demonstrate that the UMPCaRS is useful for discriminating between PCa and BPH in the ¡°PSA gray zone¡±.
KEYWORD
Diagnosis, Microarray analysis, Prostatic neoplasms, Urine
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