Data analysis algorithm for the development of extracellular miRNA-based diagnostic systems for prostate cancer

O E Bryzgunova; I A Zaporozhchenko; E A Lekchnov; E V Amelina; M Yu Konoshenko; S V Yarmoschuk; O A Pashkovskaya; A A Zheravin; S V Pak; E Yu Rykova; P P Laktionov

doi:10.1371/journal.pone.0215003

Data analysis algorithm for the development of extracellular miRNA-based diagnostic systems for prostate cancer

PLoS One. 2019 Apr 10;14(4):e0215003. doi: 10.1371/journal.pone.0215003. eCollection 2019.

Authors

O E Bryzgunova^{1

2}, I A Zaporozhchenko^{1

2}, E A Lekchnov^{1

2}, E V Amelina³, M Yu Konoshenko^{1

2}, S V Yarmoschuk², O A Pashkovskaya², A A Zheravin², S V Pak², E Yu Rykova^{1

2

4}, P P Laktionov^{1

2}

Affiliations

¹ The Laboratory of Molecular Medicine, Institute of Chemical Biology and Fundamental Medicine SB RAS, Novosibirsk, Russia.
² The Laboratory of Biomedical Technologies, Centre of New Medical Technologies,"E. Meshalkin National Medical Research Center" of the Ministry of Health of the Russian Federation, Novosibirsk, Russia.
³ Federal State Autonomous Educational Institution of Higher Education "Novosibirsk National Research University", Novosibirsk, Russia.
⁴ Novosibirsk State Technical University, Novosibirsk, Russia.

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.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Aged
Aged, 80 and over
Algorithms
Biomarkers, Tumor / genetics
Biomarkers, Tumor / urine
Case-Control Studies
Data Interpretation, Statistical
Extracellular Vesicles / genetics
Gene Regulatory Networks
Humans
Male
MicroRNAs / genetics*
MicroRNAs / urine
Middle Aged
Prostatic Hyperplasia / diagnosis
Prostatic Hyperplasia / genetics
Prostatic Hyperplasia / urine
Prostatic Neoplasms / diagnosis*
Prostatic Neoplasms / genetics*
Prostatic Neoplasms / urine

Substances

Biomarkers, Tumor
MicroRNAs

Grants and funding

The work of E.Yu. Rukova, O.E. Bryzgunova, I.A. Zaporozhchenko, E.A. Lekchnov, M.Yu. Konoshenko, S.V. Yarmoschuk, and O.A. Pashkovskaya was supported by the Russian Science Foundation (project No. 16-15-00124). P.P. Laktionov acknowledges financial support within the framework of the Russian state budget project #AAAA-A17-117020210024-8 to the ICBFM SB RAS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.