4.1 Article

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

期刊

INVESTIGATIVE AND CLINICAL UROLOGY
卷 61, 期 4, 页码 411-418

出版社

KOREAN UROLOGICAL ASSOC
DOI: 10.4111/icu.2020.61.4.411

关键词

Diagnosis; Microarray analysis; Prostatic neoplasms; Urine

资金

  1. Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [2017R1A6A3A11028303]
  2. National Research Foundation of Korea (NRF) - Korea government (MSIT) [2018R1A2B2005473]
  3. Technological Innovation R&D Program - Small and Medium Business Administration (SMBA, Korea) [S2316843]
  4. Ministry of Health, Welfare and Family Affairs
  5. Korea Technology & Information Promotion Agency for SMEs (TIPA) [S2316843] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
  6. National Research Foundation of Korea [2017R1A6A3A11028303, 2018R1A2B2005473] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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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 (PDLIMS, GDF-1 5, 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 UM PCaRS is useful for discriminating between PCa and BPH in the PSA gray zone.

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