Detail
Article
Online article
FT
Medvik - BMC
  • Something wrong with this record ?

Combination of Urinary MiR-501 and MiR-335 With Current Clinical Diagnostic Parameters as Potential Predictive Factors of Prostate Biopsy Outcome

J. Juracek, M. Madrzyk, K. Trachtova, M. Ruckova, J. Bohosova, DA. Barth, M. Pichler, M. Stanik, O. Slaby

. 2023 ; 20 (3) : 308-316. [pub] -

Language English Country Greece

Document type Journal Article

BACKGROUND: The detection of prostate cancer (PCa) is currently based on prostate-specific antigen (PSA) quantification as an initial screening followed by ultrasound-guided transrectal biopsy. However, the high rate of false-negative biopsies often leads to inappropriate treatment. Therefore, new molecular biomarkers, such as urine microRNAs (miRNAs), are a possible way to redefine PCa diagnostics. PATIENTS AND METHODS: Urine samples of 356 patients undergoing prostate biopsy (256 cases with confirmed prostate cancer, 100 cases with negative prostate biopsy) at the Masaryk Memorial Cancer Institute (Czech Republic) and additional 36 control subjects (healthy controls, benign prostatic hyperplasia - BPH) were divided into the discovery and validation cohorts and analyzed. In the discovery phase, small RNA sequencing was performed using the QIAseq miRNA Library Kit and the NextSeq 500 platform. Identified miRNA candidates were validated by the RT-qPCR method in the independent validation phase. RESULTS: Using the small RNA sequencing method, we identified 12 urine miRNAs significantly dysregulated between PCa patients and controls. Furthermore, independent validation showed the ability of miR-501-3p and the quantitative miR-335:miR-501 ratio to distinguish between PCa patients and patients with negative prostate biopsy. The subsequent combination of the miR-335:miR-501 ratio with PSA and total prostate volume (TPV) using logistic regression exceeded the analytical accuracy of standalone parameters [area under curve (AUC)=0.75, positive predictive value (PPV)=0.85, negative predictive value (NPV)=0.51)] and discriminated patients according to biopsy outcome. CONCLUSION: Combination of miR-335:miR-501 ratio with PSA and total prostate volume was able to identify patients with negative prostate biopsy and could potentially streamline decision making for biopsy indication.

References provided by Crossref.org

000      
00000naa a2200000 a 4500
001      
bmc23011532
003      
CZ-PrNML
005      
20230801133121.0
007      
ta
008      
230718s2023 gr f 000 0|eng||
009      
AR
024    7_
$a 10.21873/cgp.20383 $2 doi
035    __
$a (PubMed)37093688
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a gr
100    1_
$a Juracek, Jaroslav $u Central European Institute of Technology, Masaryk University, Brno, Czech Republic
245    10
$a Combination of Urinary MiR-501 and MiR-335 With Current Clinical Diagnostic Parameters as Potential Predictive Factors of Prostate Biopsy Outcome / $c J. Juracek, M. Madrzyk, K. Trachtova, M. Ruckova, J. Bohosova, DA. Barth, M. Pichler, M. Stanik, O. Slaby
520    9_
$a BACKGROUND: The detection of prostate cancer (PCa) is currently based on prostate-specific antigen (PSA) quantification as an initial screening followed by ultrasound-guided transrectal biopsy. However, the high rate of false-negative biopsies often leads to inappropriate treatment. Therefore, new molecular biomarkers, such as urine microRNAs (miRNAs), are a possible way to redefine PCa diagnostics. PATIENTS AND METHODS: Urine samples of 356 patients undergoing prostate biopsy (256 cases with confirmed prostate cancer, 100 cases with negative prostate biopsy) at the Masaryk Memorial Cancer Institute (Czech Republic) and additional 36 control subjects (healthy controls, benign prostatic hyperplasia - BPH) were divided into the discovery and validation cohorts and analyzed. In the discovery phase, small RNA sequencing was performed using the QIAseq miRNA Library Kit and the NextSeq 500 platform. Identified miRNA candidates were validated by the RT-qPCR method in the independent validation phase. RESULTS: Using the small RNA sequencing method, we identified 12 urine miRNAs significantly dysregulated between PCa patients and controls. Furthermore, independent validation showed the ability of miR-501-3p and the quantitative miR-335:miR-501 ratio to distinguish between PCa patients and patients with negative prostate biopsy. The subsequent combination of the miR-335:miR-501 ratio with PSA and total prostate volume (TPV) using logistic regression exceeded the analytical accuracy of standalone parameters [area under curve (AUC)=0.75, positive predictive value (PPV)=0.85, negative predictive value (NPV)=0.51)] and discriminated patients according to biopsy outcome. CONCLUSION: Combination of miR-335:miR-501 ratio with PSA and total prostate volume was able to identify patients with negative prostate biopsy and could potentially streamline decision making for biopsy indication.
650    _2
$a mužské pohlaví $7 D008297
650    _2
$a lidé $7 D006801
650    _2
$a prostata $x patologie $7 D011467
650    _2
$a prostatický specifický antigen $7 D017430
650    _2
$a nádorové biomarkery $7 D014408
650    12
$a nádory prostaty $x genetika $7 D011471
650    12
$a mikro RNA $x genetika $7 D035683
650    12
$a hyperplazie prostaty $x genetika $7 D011470
650    _2
$a biopsie $7 D001706
655    _2
$a časopisecké články $7 D016428
700    1_
$a Madrzyk, Marie $u Central European Institute of Technology, Masaryk University, Brno, Czech Republic
700    1_
$a Trachtova, Karolina $u Central European Institute of Technology, Masaryk University, Brno, Czech Republic
700    1_
$a Ruckova, Michaela $u Central European Institute of Technology, Masaryk University, Brno, Czech Republic
700    1_
$a Bohosova, Julia $u Central European Institute of Technology, Masaryk University, Brno, Czech Republic
700    1_
$a Barth, Dominik A $u Research Unit of Non-Coding RNAs and Genome Editing in Cancer, Division of Clinical Oncology, Department of Medicine, Comprehensive Cancer Center Graz, Medical University of Graz, Graz, Austria
700    1_
$a Pichler, Martin $u Research Unit of Non-Coding RNAs and Genome Editing in Cancer, Division of Clinical Oncology, Department of Medicine, Comprehensive Cancer Center Graz, Medical University of Graz, Graz, Austria
700    1_
$a Stanik, Michal $u Department of Urologic Oncology, Clinic of Surgical Oncology, Masaryk Memorial Cancer Institute, Brno, Czech Republic; stanik@mou.cz
700    1_
$a Slaby, Ondrej $u Central European Institute of Technology, Masaryk University, Brno, Czech Republic; ondrej.slaby@ceitec.muni.cz $u Department of Biology, Faculty of Medicine, Masaryk University, Brno, Czech Republic
773    0_
$w MED00180194 $t Cancer genomics & proteomics $x 1790-6245 $g Roč. 20, č. 3 (2023), s. 308-316
856    41
$u https://pubmed.ncbi.nlm.nih.gov/37093688 $y Pubmed
910    __
$a ABA008 $b sig $c sign $y p $z 0
990    __
$a 20230718 $b ABA008
991    __
$a 20230801133117 $b ABA008
999    __
$a ok $b bmc $g 1963759 $s 1197797
BAS    __
$a 3
BAS    __
$a PreBMC-MEDLINE
BMC    __
$a 2023 $b 20 $c 3 $d 308-316 $e - $i 1790-6245 $m Cancer genomics & proteomics $n Cancer Genomics Proteomics $x MED00180194
LZP    __
$a Pubmed-20230718

Find record

Citation metrics

Loading data ...

Archiving options

Loading data ...