MicroRNAs from urinary exosomes as alternative biomarkers in the differentiation of benign and malignant prostate diseases

Authors

  • Jonas Holdmann Chair for Biochemistry and Molecular Medicine, Division of Functional Genomics, Witten/Herdecke University, Witten - Germany
  • Lukas Markert Chair for Biochemistry and Molecular Medicine, Division of Functional Genomics, Witten/Herdecke University, Witten - Germany https://orcid.org/0000-0002-1739-3619
  • Claudia Klinger Chair for Biochemistry and Molecular Medicine, Division of Functional Genomics, Witten/Herdecke University, Witten and Center for Biomedical Education and Research (ZBAF), Witten/Herdecke University, Witten - Germany https://orcid.org/0000-0002-6085-9584
  • Michael Kaufmann Chair for Biochemistry and Molecular Medicine, Division of Functional Genomics, Witten/Herdecke University, Witten and Center for Biomedical Education and Research (ZBAF), Witten/Herdecke University, Witten - Germany https://orcid.org/0000-0001-7595-1386
  • Karin Schork Medizinisches Proteom-Center, Ruhr-University Bochum, Bochum and Center for Protein Diagnostics (PRODI), Medical Proteome Analysis, Ruhr-University, Bochum - Germany https://orcid.org/0000-0003-3756-4347
  • Michael Turewicz Medizinisches Proteom-Center, Ruhr-University Bochum, Bochum and Center for Protein Diagnostics (PRODI), Medical Proteome Analysis, Ruhr-University, Bochum - Germany https://orcid.org/0000-0003-0737-1114
  • Martin Eisenacher Medizinisches Proteom-Center, Ruhr-University Bochum, Bochum and Center for Protein Diagnostics (PRODI), Medical Proteome Analysis, Ruhr-University, Bochum - Germany https://orcid.org/0000-0003-2687-7444
  • Stephan Degener Department of Urology, Helios University Hospital Wuppertal, Center for Clinical and Translational Research, Witten/Herdecke University, Wuppertal - Germany https://orcid.org/0000-0003-4428-7202
  • Nici M. Dreger Department of Urology, Helios University Hospital Wuppertal, Center for Clinical and Translational Research, Witten/Herdecke University, Wuppertal - Germany https://orcid.org/0000-0002-2153-7371
  • Stephan Roth Department of Urology, Helios University Hospital Wuppertal, Center for Clinical and Translational Research, Witten/Herdecke University, Wuppertal - Germany
  • Andreas Savelsbergh Chair for Biochemistry and Molecular Medicine, Division of Functional Genomics, Witten/Herdecke University, Witten and Center for Biomedical Education and Research (ZBAF), Witten/Herdecke University, Witten - Germany https://orcid.org/0000-0002-6136-3230

DOI:

https://doi.org/10.33393/jcb.2022.2317

Keywords:

Biomarker, Extracellular vesicles, Liquid biopsy, microRNA, Prostate cancer, Urine

Abstract

Introduction: Prostate cancer (PCa) is the second most frequently diagnosed cancer and the fifth most cancer-related cause of death worldwide. Various tools are used in the diagnosis of PCa, such as the Prostate-Specific Antigen (PSA) value or digital rectal examination. A final differentiation from benign prostate diseases such as benign prostatic hyperplasia (BPH) can often only be made by a transrectal prostate biopsy. This procedure carries post-procedural complications for the patients and may lead to hospitalization.

Urinary exosomes contain unique components, such as microRNAs (miRNAs) with information about their original tissue. As miRNAs appear to play a role in the development of PCa, they might be useful to develop procedures that could potentially make transrectal biopsies avoidable in certain situations.

Methods: The current study aimed to investigate whether miRNAs from urinary exosomes can be used to differentiate PCa from BPH. For this purpose, urine samples from 28 patients with PCa and 25 patients with BPH were collected and analysed using next-generation sequencing to obtain expression profiles.

Results and conclusion: The two miRNAs hsa-miR-532-3p and hsa-miR-6749-5p showed a significant differential expression within the group of patients with PCa in a training subset of the data containing 32 patients. They were further validated on the independent test data subset containing 20 patients. Additionally, a machine learning algorithm was used to generate a miRNA pattern to distinguish the two disease entities. Both approaches seem to be suitable for the search of alternative diagnostic tools for the differentiation of benign and malignant prostate diseases.

Author Biographies

Jonas Holdmann, Chair for Biochemistry and Molecular Medicine, Division of Functional Genomics, Witten/Herdecke University, Witten - Germany

* Contributed equally

Lukas Markert, Chair for Biochemistry and Molecular Medicine, Division of Functional Genomics, Witten/Herdecke University, Witten - Germany

* Contributed equally

References

McNeal JE. Normal histology of the prostate. Am J Surg Pathol. 1988;12(8):619-633. https://doi.org/10.1097/00000478-198808000-00003 PMID:2456702 DOI: https://doi.org/10.1097/00000478-198808000-00003

Garraway WM, Collins GN, Lee RJ. High prevalence of benign prostatic hypertrophy in the community. Lancet. 1991;338(8765):469-471. https://doi.org/10.1016/0140-6736(91)90543-XPMID:1714529 DOI: https://doi.org/10.1016/0140-6736(91)90543-X

Egan KB. The epidemiology of benign prostatic hyperplasia associated with lower urinary tract symptoms: prevalence and incident rates. Urol Clin North Am. 2016;43(3):289-297. https://doi.org/10.1016/j.ucl.2016.04.001 PMID:27476122 DOI: https://doi.org/10.1016/j.ucl.2016.04.001

Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209-249. https://doi.org/10.3322/caac.21660 PMID:33538338 DOI: https://doi.org/10.3322/caac.21660

Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011;61(2):69-90. https://doi.org/10.3322/caac.20107 PMID:21296855 DOI: https://doi.org/10.3322/caac.20107

European Association of Urology Guidelines. 2020 Edition. Arnhem, The Netherlands: European Association of Urology Guidelines Office; 2020. https://uroweb.org/guideline/prostate-cancer/

Loeb S, Vellekoop A, Ahmed HU, et al. Systematic review of complications of prostate biopsy. Eur Urol. 2013;64(6):876-892. https://doi.org/10.1016/j.eururo.2013.05.049 PMID:23787356 DOI: https://doi.org/10.1016/j.eururo.2013.05.049

Sharma S, Zapatero-Rodríguez J, O’Kennedy R. Prostate cancer diagnostics: clinical challenges and the ongoing need for disruptive and effective diagnostic tools. Biotechnol Adv. 2017;35(2):135-149. https://doi.org/10.1016/j.biotechadv.2016.11.009 PMID:27939303 DOI: https://doi.org/10.1016/j.biotechadv.2016.11.009

Buschow SI, Liefhebber JM, Wubbolts R, Stoorvogel W. Exosomes contain ubiquitinated proteins. Blood Cells Mol Dis. 2005;35(3):398-403. https://doi.org/10.1016/j.bcmd.2005.08.005PMID:16203162 DOI: https://doi.org/10.1016/j.bcmd.2005.08.005

Valadi H, Ekström K, Bossios A, Sjöstrand M, Lee JJ, Lötvall JO. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol. 2007;9(6):654-659. https://doi.org/10.1038/ncb1596 PMID:17486113 DOI: https://doi.org/10.1038/ncb1596

Nilsson J, Skog J, Nordstrand A, et al. Prostate cancer-derived urine exosomes: a novel approach to biomarkers for prostate cancer. Br J Cancer. 2009;100(10):1603-1607. https://doi.org/10.1038/sj.bjc.6605058 PMID:19401683 DOI: https://doi.org/10.1038/sj.bjc.6605058

Friedman RC, Farh KK-H, Burge CB, Bartel DP. Most mammalian mRNAs are conserved targets of microRNAs. Genome Res. 2009;19(1):92-105. https://doi.org/10.1101/gr.082701.108PMID:18955434 DOI: https://doi.org/10.1101/gr.082701.108

Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004;116(2):281-297. https://doi.org/10.1016/S0092-8674(04)00045-5 PMID:14744438 DOI: https://doi.org/10.1016/S0092-8674(04)00045-5

Marton S, Garcia MR, Robello C, et al. Small RNAs analysis in CLL reveals a deregulation of miRNA expression and novel miRNA candidates of putative relevance in CLL pathogenesis. Leukemia. 2008;22(2):330-338. https://doi.org/10.1038/sj.leu.2405022 PMID:17989717 DOI: https://doi.org/10.1038/sj.leu.2405022

Mitchell PS, Parkin RK, Kroh EM, et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA. 2008;105(30):10513-10518. https://doi.org/10.1073/pnas.0804549105 PMID:18663219 DOI: https://doi.org/10.1073/pnas.0804549105

Mall C, Rocke DM, Durbin-Johnson B, Weiss RH. Stability of miRNA in human urine supports its biomarker potential. Biomarkers Med. 2013;7(4):623-631. https://doi.org/10.2217/bmm.13.44 PMID:23905899 DOI: https://doi.org/10.2217/bmm.13.44

Markert L, Holdmann J, Klinger C, et al. Small RNAs as biomarkers to differentiate benign and malign prostate diseases: an alternative for transrectal punch biopsy of the prostate? PLoS One. 2021;16(3):e0247930. https://doi.org/10.1371/journal.pone.0247930 PMID:33760831 DOI: https://doi.org/10.1371/journal.pone.0247930

R Core Team. R: A Language and Environment for Statistical Computing. 2019. https://www.r-project.org/

Turewicz M, Kohl M, Ahrens M, et al. BioInfra.Prot: a comprehensive proteomics workflow including data standardization, protein inference, expression analysis and data publication. J Biotechnol. 2017;261:116-125. https://doi.org/10.1016/j.jbiotec.2017.06.005 PMID:28606611 DOI: https://doi.org/10.1016/j.jbiotec.2017.06.005

Walker A. openxlsx: Read, Write and Edit XLSX Files. 2019 https://CRAN.R-project.org/package=openxlsx

Kuhn M. caret: Classification and Regression Training. 2019. https://CRAN.R-project.org/package=caret

Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550. https://doi.org/10.1186/s13059-014-0550-8 PMID:25516281 DOI: https://doi.org/10.1186/s13059-014-0550-8

Wickham H. ggplot2: Elegant Graphics for Data Analysis. 2016. https://ggplot2.tidyverse.org DOI: https://doi.org/10.1007/978-3-319-24277-4

Wilke CO. cowplot: Streamlined Plot Theme and Plot Annotations for 'ggplot2'. 2019. https://CRAN.R-project.org/package=cowplot

Slowikowski K. ggrepel: Automatically Position Non-Overlapping Text Labels with 'ggplot2'. 2019. https://CRAN.R-project.org/package=ggrepel

Robin X, Turck N, Hainard A, et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 2011;12(1):77. https://doi.org/10.1186/1471-2105-12-77 PMID:21414208 DOI: https://doi.org/10.1186/1471-2105-12-77

Breiman L. Random Forests. Mach Learn. 2001;45(1):5-32. https://doi.org/10.1023/A:1010933404324 DOI: https://doi.org/10.1023/A:1010933404324

Liaw A, Wiener M. Classification and regression by randomForest. R News. 2002;2(3):18-22.

Griffiths-Jones S. The microRNA Registry. Nucleic Acids Res. 2004;32(Database issue)(suppl 1):D109-D111. https://doi.org/10.1093/nar/gkh023 PMID:14681370 DOI: https://doi.org/10.1093/nar/gkh023

Yamada Y, Arai T, Kato M, et al. Role of pre-miR-532 (miR-532-5p and miR-532-3p) in regulation of gene expression and molecular pathogenesis in renal cell carcinoma. Am J Clin Exp Urol. 2019;7(1):11-30. PMID:30906802

Han J, Wang F, Lan Y, et al. KIFC1 regulated by miR-532-3p promotes epithelial-to-mesenchymal transition and metastasis of hepatocellular carcinoma via gankyrin/AKT signaling. Oncogene. 2019;38(3):406-420. https://doi.org/10.1038/s41388-018-0440-8 PMID:30115976 DOI: https://doi.org/10.1038/s41388-018-0440-8

Gu C, Cai J, Xu Z, et al. MiR-532-3p suppresses colorectal cancer progression by disrupting the ETS1/TGM2 axis-mediated Wnt/β-catenin signaling. Cell Death Dis. 2019;10(10):739. https://doi.org/10.1038/s41419-019-1962-x PMID:31570702 DOI: https://doi.org/10.1038/s41419-019-1962-x

Jiang W, Zheng L, Yan Q, Chen L, Wang X. MiR-532-3p inhibits metastasis and proliferation of non-small cell lung cancer by targeting FOXP3. J BUON. 2019;24(6):2287-2293. PMID:31983096

Andl T, Ganapathy K, Bossan A, Chakrabarti R. MicroRNAs as guardians of the prostate: those who stand before cancer. What do we really know about the role of microRNAs in prostate biology? Int J Mol Sci. 2020;21(13):4796. https://doi.org/10.3390/ijms21134796 PMID:32645914 DOI: https://doi.org/10.3390/ijms21134796

Guo J, Liu C, Wang W, et al. Identification of serum miR-1915-3p and miR-455-3p as biomarkers for breast cancer. PLoS One. 2018;13(7):e0200716-e. DOI: 10.1371/journal.pone.0200716 PMID 30048472 DOI: https://doi.org/10.1371/journal.pone.0200716

Li K, Zhu X, Li L, et al. Identification of non-invasive biomarkers for predicting the radiosensitivity of nasopharyngeal carcinoma from serum microRNAs. Sci Rep. 2020;10(1):5161. https://doi.org/10.1038/s41598-020-61958-4 PMID:32198434 DOI: https://doi.org/10.1038/s41598-020-61958-4

Zou X, Li M, Huang Z, et al. Circulating miR-532-502 cluster derived from chromosome X as biomarkers for diagnosis of breast cancer. Gene. 2020;722:144104. https://doi.org/10.1016/j.gene.2019.144104 PMID:31493506 DOI: https://doi.org/10.1016/j.gene.2019.144104

Pospisilova S, Pazourkova E, Horinek A, et al. MicroRNAs in urine supernatant as potential non-invasive markers for bladder cancer detection. Neoplasma. 2016;63(5):799-808. https://doi.org/10.4149/neo_2016_518 PMID:27468885 DOI: https://doi.org/10.4149/neo_2016_518

Liang Y, Ridzon D, Wong L, Chen C. Characterization of microRNA expression profiles in normal human tissues. BMC Genomics. 2007;8(1):166. https://doi.org/10.1186/1471-2164-8-166PMID:17565689 DOI: https://doi.org/10.1186/1471-2164-8-166

Thomas CE, Sexton W, Benson K, Sutphen R, Koomen J. Urine collection and processing for protein biomarker discovery and quantification. Cancer Epidemiol Biomarkers Prev. 2010;19(4):953-959. https://doi.org/10.1158/1055-9965.EPI-10-0069 PMID:20332277 DOI: https://doi.org/10.1158/1055-9965.EPI-10-0069

Published

2022-02-10

How to Cite

1.
Holdmann J, Markert L, Klinger C, Kaufmann M, Schork K, Turewicz M, Eisenacher M, Degener S, Dreger NM, Roth S, Savelsbergh A. MicroRNAs from urinary exosomes as alternative biomarkers in the differentiation of benign and malignant prostate diseases. J Circ Biomark [Internet]. 2022 Feb. 10 [cited 2022 May 20];11(1):5-13. Available from: https://journals.aboutscience.eu/index.php/jcb/article/view/2317

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Section

Original research article