Urinary microRNAs and Their Significance in Prostate Cancer Diagnosis: A 5-Year Update
Abstract
:Simple Summary
Abstract
1. Introduction
2. microRNAs in Prostate Cancer
3. Urinary miRNAs
4. Urinary miRNAs and Prostate Cancer Diagnostics
4.1. Urinary Cell-Free miRNAs
4.2. miRNAs in Urine Sediment
4.3. Exosomal miRNAs
5. New Frontiers in Urinary miRNA-Based PCa Detection
5.1. Factors Influencing Urinary miRNA Analysis
5.2. Alternative Methods of Detection
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Author, Year | Urine Fraction | Screening (Method/Samples) | Validation (Method/Samples) | Proposed Biomarkers/Comments | Reference |
---|---|---|---|---|---|
Byun, 2021 | urine supernatant | Agilent Human miRNA Microarray/14 PCa, 5 BPH | qPCR/ cohort 1: 9 PCa, 8 BPH; cohort 2: 44 PCa, 39 BPH | ↑ miR-1913 to miR-3659 ratio | [32] |
Fredsøe, 2018 | urine supernatant | RT-qPCR array/188 PCa, 20 BPH | RT-qPCR array/197 PCa, 20 BPH | ↑ miR-222-3p, miR-24-3p, miR-30c-5p/diagnostic model | [33] |
Fredsøe, 2019 | urine supernatant | RT-qPCR array/404 PCa, 42 BPH; merged cohorts from previous study | RT-qPCR array/cohort 1: 214 PCa, 99 BPH; cohort 2: 139 PCa, 148 BPH | ↑ miR-222-3p, miR-24-3p, miR-30c-5p/diagnostic model | [34] |
Lekchnov, 2018 | urine supernatant, urine Evs | RT-qPCR array/10 PCa, 10 HC, 10 BPH | - | supernatant: ↑ miR-107-miR-26b-5p, ↑ miR-375-3p-miR-26b-5p; Evs: miR-20a-5p-miR-16-5p, miR-30b-5p-miR-16-5p, miR-31-5p-miR-16-5p, miR-24-3p-miR-200b-3p/miRNA pairs | [35] |
Konoshenko, 2020 | urine supernatant, urine Evs | based on previous study [35], RT-qPCR array | qPCR/10 PCa, 11 HC, 8 BPH | ↑ miR-125b-miR-30e, ↑ miR-200-miR-30e, ↑ miR-205-miR-30e, ↑ miR-31-miR-30e, ↑ miR-660-miR-30e, ↑ miR-19b-miR-92a/miRNA ratios | [36] |
Hasanoğlu, 2021 | urine sediment | Affymetrix GeneChip miRNA 4.0 Arrays/8 PCa, 30 HC | qPCR/8 PCa, 30 HC | ↑ miR-320a | [37] |
Guelfi, 2018 | urine sediment/ exfoliated cells | small RNA sequencing/11 PCa, 11 HC | qPCR/11 PCa, 11 HC | ↓ let-7 family | [38] |
Ghorbanmehr, 2019 | whole urine | - | qPCR/23 PCa, 22 BPH, 20 HC | ↑ miR-21-5p, ↑ miR-141-3p, ↑ miR-205-5p | [39] |
Nayak, 2020 | urine sediment | - | qPCR/33 PCa, 30 HC | ↑ miR-182, ↓ miR-187/only in tissue | [40] |
Borkowetz, 2020 | urine sediment | - | qPCR/50 suspected PCa (26 PCa, 24 tumor-free) | ↓ miR-16, ↓ miR-195 | [41] |
Foj, 2017 | urinary sediment, urinary Evs | - | qPCR/60 PCa, 10 HC | Sediment: ↑ miR-21, ↑ miR-375, ↑ miR-141, ↓ miR-214; Evs: ↑ miR-21, ↑ miR-375, ↑ let-7c | [42] |
Author, Year | EVs Isolation Method | Screening (Method/Samples) | Validation (Method/Samples) | Proposed Biomarkers | Reference |
---|---|---|---|---|---|
Xu, 2017 | hydrostatic filtration dialysis, ultracentrifugation | qPCR/60 PCa, 37 BPH, 24 HC | - | ↑ miR-145-5p | [49] |
Ku, 2021 | automated acoustic trapping | NGS/46 PCa GG ≥ 4, 127 PCa GG ≤ 3 + Bx-negative samples | In silico, TCGA prostate dataset/497 subjects | ↓ miR-1, ↑ miR-23b, ↑ miR-27a | [50] |
Danarto, 2020 | Exiqon miRCURY | qPCR/60 PCa, 20 BPH | - | ↑ miR-21-5p, ↓ miR-200c-3p | [51] |
Bonnu, 2021 | QIAGEN exosomal Kit | NanoString nCounter Expression Assay/2 PCa, 2 BPH—tissue samples | qPCR/10 PCa, 10 BPH | ↑ has-mir-106b-5p | [52] |
Wani, 2017 | Exiqon miRCURY | qPCR/90 PCa, 10 BPH, 60 BCa, 50 HC | - | ↑ miR-2909, ↑ miR-615-3p | [53] |
Matsuzaki, 2021 | differential centrifugation | Affymetrix miRNA microarray 2.0/10 PCa, 4 HC | qPCR/28 PCa, 25 HC | ↑ miR-30b-3p, ↑ miR-126-3p | [54] |
Li, 2021 | ExoQuick-TC | small RNA sequencing/6 PCa, 3 HC | qPCR/47 PCa, 29 BPH, 25 HC | ↓ miR-375, ↑ miR-451a, ↑ miR-486-3p, ↑ miR-486-5p | [55] |
Wang, 2020 | Exosome RNA Isolation Kit (Norgen Biotek) | Affymetrix GeneChip miRNA 4.0 Arrays/146 PCa, 89 HC | qPCR OpenArray/868 PCa, 568 HC | Sentinel PCa, Sentinel CS and Sentinel HG | [56] |
Factor | Effect/Consequence | Significant miRNAs/Comments | Reference |
---|---|---|---|
anti-cancer treatment (radical prostatectomy) | miRNA level alteration | miR-19b, miR-30e, miR-31, miR-125b, miR-200b, miR-205, miR-375, miR-378, miR-425, miR-660 | [59] |
intraindividual variability | changes in level within one subject across repeated measurements | miR-3195, let-7b-5p, miR-144-3p, miR-451a, miR-148a-3p, miR-512-5p, miR-431-5p/intrastable miRNAs | [60] |
hemolysis | variation in miRNAs enriched in RBC | miR-16, miR-17, miR-92a, miR-106a, miR-210, miR-451 | [65,66] |
inappropriate reference gene | unreliable data normalization | miR-16 | [68] |
EV separation method | enrichment of different EV subpopulations and content | - | [72] |
presence of non-EV components | decrease in EV yield and change in levels of miRNA | miR-21, miR-375 and miR-204 | [74] |
Author, Year | Method/Approach | Advantage | Disadvantage | Reference |
---|---|---|---|---|
Bryzgunova, 2019 | qPCR data evaluation using four-block data analysis algorithm | simplification of miRNA expression, analysis in more urine fractions, compensation of heterogeneity | algorithm based on the analysis of a smaller group of patients, disadvantages connected to qPCR method | [75] |
Markert, 2021 | machine learning classification algorithm for data analysis | low dependence on the (error-free) measurability of a single marker | algorithm based on the analysis of a small sample size | [76] |
Lee, 2018 | bi-labeled molecular beacons | direct detection | unknown effect of urine on technology, suitable exosomes isolation | [57] |
Saha, 2021 | two-step competitive hybridization assay | direct detection, high sensitivity | one marker per analysis, signal normalization | [77] |
Kim, 2021 | hydrogel-based hybridization chain reaction | analysis without target amplification, low urine volume, ratiometric analysis | instrumentation, needs to be validated on extended cohorts | [78] |
Kim, 2021 | graphene-based electrical sensor | label-free detection, durability, dynamic range | instrumentation, limited number of measured biomarkers | [79] |
Yasui, 2017 | electrostatic collection of EVs + standard screening methods | standardized, high efficiency EV collection, small urine volume (1 mL) | only improving EVs extraction, disadvantages connected to subsequent method | [80] |
Li, 2019 | detection of miRNA-driven self-assembly nanospheres | quantification without pre-processing step, high sensitivity and specificity | synthesis of nanospheres, instrumentation | [81] |
Davey, 2020 | multi-marker system | detection in EVs, unified peptide-mediated EV capture, combination of different types of markers | disadvantages connected to qPCR method | [58] |
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Juracek, J.; Madrzyk, M.; Stanik, M.; Slaby, O. Urinary microRNAs and Their Significance in Prostate Cancer Diagnosis: A 5-Year Update. Cancers 2022, 14, 3157. https://doi.org/10.3390/cancers14133157
Juracek J, Madrzyk M, Stanik M, Slaby O. Urinary microRNAs and Their Significance in Prostate Cancer Diagnosis: A 5-Year Update. Cancers. 2022; 14(13):3157. https://doi.org/10.3390/cancers14133157
Chicago/Turabian StyleJuracek, Jaroslav, Marie Madrzyk, Michal Stanik, and Ondrej Slaby. 2022. "Urinary microRNAs and Their Significance in Prostate Cancer Diagnosis: A 5-Year Update" Cancers 14, no. 13: 3157. https://doi.org/10.3390/cancers14133157