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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 journalArticlepeer-review

Harvard

Bryzgunova, OE, Zaporozhchenko, IA, Lekchnov, EA, Amelina, EV, Konoshenko, MY, Yarmoschuk, SV, Pashkovskaya, OA, Zheravin, AA, Pak, SV, Rykova, EY & Laktionov, PP 2019, 'Data analysis algorithm for the development of extracellular miRNA-based diagnostic systems for prostate cancer', PLoS ONE, vol. 14, no. 4, 0215003. https://doi.org/10.1371/journal.pone.0215003

APA

Bryzgunova, O. E., Zaporozhchenko, I. A., Lekchnov, E. A., Amelina, E. V., Konoshenko, M. Y., Yarmoschuk, S. V., Pashkovskaya, O. A., Zheravin, A. A., Pak, S. V., Rykova, E. Y., & Laktionov, P. P. (2019). Data analysis algorithm for the development of extracellular miRNA-based diagnostic systems for prostate cancer. PLoS ONE, 14(4), [0215003]. https://doi.org/10.1371/journal.pone.0215003

Vancouver

Bryzgunova OE, Zaporozhchenko IA, Lekchnov EA, Amelina EV, Konoshenko MY, Yarmoschuk SV et al. Data analysis algorithm for the development of extracellular miRNA-based diagnostic systems for prostate cancer. PLoS ONE. 2019 Apr 10;14(4):0215003. doi: 10.1371/journal.pone.0215003

Author

Bryzgunova, O. E. ; Zaporozhchenko, I. A. ; Lekchnov, E. A. et al. / Data analysis algorithm for the development of extracellular miRNA-based diagnostic systems for prostate cancer. In: PLoS ONE. 2019 ; Vol. 14, No. 4.

BibTeX

@article{dd9dead0606f4e9d902c8256780de983,
title = "Data analysis algorithm for the development of extracellular miRNA-based diagnostic systems for prostate cancer",
abstract = "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.",
keywords = "Aged, Aged, 80 and over, Algorithms, Biomarkers, Tumor/genetics, Case-Control Studies, Data Interpretation, Statistical, Extracellular Vesicles/genetics, Gene Regulatory Networks, Humans, Male, MicroRNAs/genetics, Middle Aged, Prostatic Hyperplasia/diagnosis, Prostatic Neoplasms/diagnosis, SIGNATURES, MICROVESICLES, RECEPTOR, MICRORNA EXPRESSION PROFILES, BIOMARKERS, URINE, ANDROGEN, EXOSOMES, HER-2/NEU, PROGRESSION",
author = "Bryzgunova, {O. E.} and Zaporozhchenko, {I. A.} and Lekchnov, {E. A.} and Amelina, {E. V.} and Konoshenko, {M. Yu} and Yarmoschuk, {S. V.} and Pashkovskaya, {O. A.} and Zheravin, {A. A.} and Pak, {S. V.} and Rykova, {E. Yu} and Laktionov, {P. P.}",
note = "Publisher Copyright: {\textcopyright} 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.",
year = "2019",
month = apr,
day = "10",
doi = "10.1371/journal.pone.0215003",
language = "English",
volume = "14",
journal = "PLoS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "4",

}

RIS

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