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Data analysis algorithm for the development of extracellular miRNA-based diagnostic systems for prostate cancer. / Bryzgunova, O. E.; Zaporozhchenko, I. A.; Lekchnov, E. A. et al.
In: PLoS ONE, Vol. 14, No. 4, 0215003, 10.04.2019.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Data analysis algorithm for the development of extracellular miRNA-based diagnostic systems for prostate cancer
AU - Bryzgunova, O. E.
AU - Zaporozhchenko, I. A.
AU - Lekchnov, E. A.
AU - Amelina, E. V.
AU - Konoshenko, M. Yu
AU - Yarmoschuk, S. V.
AU - Pashkovskaya, O. A.
AU - Zheravin, A. A.
AU - Pak, S. V.
AU - Rykova, E. Yu
AU - Laktionov, P. P.
N1 - Publisher Copyright: © 2019 Bryzgunova et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2019/4/10
Y1 - 2019/4/10
N2 - Urine of prostate cancer (PCa) carries miRNAs originated from prostate cancer cells as a part of both nucleoprotein complexes and cell-secreted extracellular vesicles. The analysis of such miRNA-markers in urine can be a convenient option for PCa screening. The aims of this study were to reveal miRNA–markers of PCa in urine and design a robust and precise diagnostic test, based on miRNA expression analysis. The expression analysis of the 84 miRNAs in paired urine extracellular vesicles (EVs) and cell free urine supernatant samples from healthy donors, patients with benign and malignant prostate tumours was done using miRCURY LNA miRNA qPCR Panels (Exiqon, Denmark). Sets of miRNAs differentially expressed between the donor groups were found in urine EVs and urine supernatant. Diagnostically significant miRNAs were selected and algorithm of data analysis, based on expression data on 24-miRNA in urine and obtained using 17 analytical systems, was designed. The developed algorithm of data analysis describes a series of steps necessary to define cut-off values and sequentially analyze miRNA expression data according to the cut-offs to facilitate classification of subjects in case/control groups and allows to detect PCa patients with 97.5% accuracy.
AB - Urine of prostate cancer (PCa) carries miRNAs originated from prostate cancer cells as a part of both nucleoprotein complexes and cell-secreted extracellular vesicles. The analysis of such miRNA-markers in urine can be a convenient option for PCa screening. The aims of this study were to reveal miRNA–markers of PCa in urine and design a robust and precise diagnostic test, based on miRNA expression analysis. The expression analysis of the 84 miRNAs in paired urine extracellular vesicles (EVs) and cell free urine supernatant samples from healthy donors, patients with benign and malignant prostate tumours was done using miRCURY LNA miRNA qPCR Panels (Exiqon, Denmark). Sets of miRNAs differentially expressed between the donor groups were found in urine EVs and urine supernatant. Diagnostically significant miRNAs were selected and algorithm of data analysis, based on expression data on 24-miRNA in urine and obtained using 17 analytical systems, was designed. The developed algorithm of data analysis describes a series of steps necessary to define cut-off values and sequentially analyze miRNA expression data according to the cut-offs to facilitate classification of subjects in case/control groups and allows to detect PCa patients with 97.5% accuracy.
KW - Aged
KW - Aged, 80 and over
KW - Algorithms
KW - Biomarkers, Tumor/genetics
KW - Case-Control Studies
KW - Data Interpretation, Statistical
KW - Extracellular Vesicles/genetics
KW - Gene Regulatory Networks
KW - Humans
KW - Male
KW - MicroRNAs/genetics
KW - Middle Aged
KW - Prostatic Hyperplasia/diagnosis
KW - Prostatic Neoplasms/diagnosis
KW - SIGNATURES
KW - MICROVESICLES
KW - RECEPTOR
KW - MICRORNA EXPRESSION PROFILES
KW - BIOMARKERS
KW - URINE
KW - ANDROGEN
KW - EXOSOMES
KW - HER-2/NEU
KW - PROGRESSION
UR - http://www.scopus.com/inward/record.url?scp=85064181192&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0215003
DO - 10.1371/journal.pone.0215003
M3 - Article
C2 - 30970027
AN - SCOPUS:85064181192
VL - 14
JO - PLoS ONE
JF - PLoS ONE
SN - 1932-6203
IS - 4
M1 - 0215003
ER -
ID: 23102642