Skip to main content
Top
Published in: BMC Urology 1/2019

Open Access 01-12-2019 | Prostate Cancer | Research article

Where is the limit of prostate cancer biomarker research? Systematic investigation of potential prognostic and diagnostic biomarkers

Authors: Anika Kremer, Tobias Kremer, Glen Kristiansen, Yuri Tolkach

Published in: BMC Urology | Issue 1/2019

Login to get access

Abstract

Background

The identification of appropriate biomarkers is essential to support important clinical decisions in patients with prostate cancer. The aim of our study was a systematic bioinformatical analysis of the mRNA expression of all genes available for the prostate adenocarcinoma cohort of The Cancer Genome Atlas (TCGA), regarding their potential prognostic and diagnostic role.

Methods

The study cohort comprises 499 patients (TCGA prostate cancer cohort). mRNA expression data were available for approx. 20,000 genes. The bioinformatical statistical pipeline addressed gene expression differences in tumor vs. benign prostate tissue (including gene set enrichment analysis, GSEA) in samples from tumors with different aggressivenesses (Gleason score), as well as prognostic values in multistep survival analyses.

Results

Among all genes analyzed, 1754 were significantly downregulated and 1553 genes were significantly upregulated in tumor tissue. In GSEA, 16 of 30 top enriched biological processes were alterations of epigenetic regulation at different levels. Significant correlation with Gleason Score was evident for 8724 genes (range of Pearson r-values 0.09–0.43; all p < 0.05). In univariate Cox regression analyses, mRNA expression of 3571 genes showed statistically significant association with biochemical recurrence-free survival with a range of hazard ratios 0.3–3.8 (p-value 7.4e− 07 to 0.05). Among these, 571 genes were independently associated with biochemical recurrence in multivariate analysis. Access to the full database including results is provided as supplement.

Conclusions

In our systematic analysis we found a big number of genes of potential diagnostic and prognostic value, many of which have not been studied in prostate cancer to date. Due to the comprehensive nature of this analysis and free access to the results, this study represents a reference database for prostate cancer researchers which can be used as a powerful tool for validation purposes and planning of new studies.
Appendix
Available only for authorised users
Literature
1.
go back to reference Ferlay J, Soerjomataram I, Dikshit R, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2015;136:E359–86.CrossRef Ferlay J, Soerjomataram I, Dikshit R, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2015;136:E359–86.CrossRef
2.
go back to reference Esserman LJ, Thompson IM, Reid B, et al. Addressing overdiagnosis and overtreatment in cancer: a prescription for change. Lancet Oncol. 2014;15:e234–42.CrossRef Esserman LJ, Thompson IM, Reid B, et al. Addressing overdiagnosis and overtreatment in cancer: a prescription for change. Lancet Oncol. 2014;15:e234–42.CrossRef
3.
go back to reference Wilt TJ, Jones KM, Barry MJ, et al. Follow-up of prostatectomy versus observation for early prostate Cancer. N Engl J Med. 2017;377:132–42.CrossRef Wilt TJ, Jones KM, Barry MJ, et al. Follow-up of prostatectomy versus observation for early prostate Cancer. N Engl J Med. 2017;377:132–42.CrossRef
4.
go back to reference Boutros PC, Fraser M, Harding NJ, et al. Spatial genomic heterogeneity within localized, multifocal prostate cancer. Nat Genet. 2015;47:736–45.CrossRef Boutros PC, Fraser M, Harding NJ, et al. Spatial genomic heterogeneity within localized, multifocal prostate cancer. Nat Genet. 2015;47:736–45.CrossRef
5.
go back to reference Tolkach Y, Kristiansen G. The heterogeneity of prostate Cancer: a practical approach. Pathobiology. 2018;85:108–16.CrossRef Tolkach Y, Kristiansen G. The heterogeneity of prostate Cancer: a practical approach. Pathobiology. 2018;85:108–16.CrossRef
6.
go back to reference Kretschmer A, Tolkach Y, Ellinger J, Kristiansen G. Molecular biomarkers and prognostic factors for prostate cancer. Urologe. 2017;56:933–44.CrossRef Kretschmer A, Tolkach Y, Ellinger J, Kristiansen G. Molecular biomarkers and prognostic factors for prostate cancer. Urologe. 2017;56:933–44.CrossRef
7.
go back to reference Kristiansen G. Markers of clinical utility in the differential diagnosis and prognosis of prostate cancer. Mod Pathol. 2018;31:S143–55.CrossRef Kristiansen G. Markers of clinical utility in the differential diagnosis and prognosis of prostate cancer. Mod Pathol. 2018;31:S143–55.CrossRef
8.
go back to reference EAU - ESTRO - ESUR - SIOG Guidelines on Prostate Cancer. Update March 2018. Accessed at uroweb.org. Accessed 25 Jan 2019. EAU - ESTRO - ESUR - SIOG Guidelines on Prostate Cancer. Update March 2018. Accessed at uroweb.​org. Accessed 25 Jan 2019.
9.
go back to reference Nicholson A, Mahon J, Boland A, et al. The clinical effectiveness and cost-effectiveness of the PROGENSA® prostate cancer antigen 3 assay and the prostate health index in the diagnosis of prostate cancer: a systematic review and economic evaluation. Health Technol Assess (Rockv). 2015;19:1–192.CrossRef Nicholson A, Mahon J, Boland A, et al. The clinical effectiveness and cost-effectiveness of the PROGENSA® prostate cancer antigen 3 assay and the prostate health index in the diagnosis of prostate cancer: a systematic review and economic evaluation. Health Technol Assess (Rockv). 2015;19:1–192.CrossRef
10.
go back to reference Van Neste L, Hendriks RJ, Dijkstra S, et al. Detection of high-grade prostate Cancer using a urinary molecular biomarker–based risk score. Eur Urol. 2016;70:740–8.CrossRef Van Neste L, Hendriks RJ, Dijkstra S, et al. Detection of high-grade prostate Cancer using a urinary molecular biomarker–based risk score. Eur Urol. 2016;70:740–8.CrossRef
11.
go back to reference Kristiansen I, Stephan C, Jung K, et al. Sensitivity of HoXB13 as a diagnostic immunohistochemical marker of prostatic origin in prostate cancer metastases: comparison to PSA, prostein, androgen receptor, ERG, NKX3.1, PSAP, and PSMA. Int J Mol Sci. 2017;18. https://doi.org/10.3390/ijms18061151.CrossRef Kristiansen I, Stephan C, Jung K, et al. Sensitivity of HoXB13 as a diagnostic immunohistochemical marker of prostatic origin in prostate cancer metastases: comparison to PSA, prostein, androgen receptor, ERG, NKX3.1, PSAP, and PSMA. Int J Mol Sci. 2017;18. https://​doi.​org/​10.​3390/​ijms18061151.CrossRef
12.
go back to reference Berger I, Annabattula C, Lewis J, et al. 68Ga-PSMA PET/CT vs. mpMRI for locoregional prostate cancer staging: correlation with final histopathology. Prostate Cancer Prostatic Dis. 2018;21:204–11.CrossRef Berger I, Annabattula C, Lewis J, et al. 68Ga-PSMA PET/CT vs. mpMRI for locoregional prostate cancer staging: correlation with final histopathology. Prostate Cancer Prostatic Dis. 2018;21:204–11.CrossRef
13.
go back to reference McShane LM, Altman DG, Sauerbrei W, et al. REporting recommendations for tumour MARKer prognostic studies (REMARK). Br J Cancer. 2005;93:387–91.CrossRef McShane LM, Altman DG, Sauerbrei W, et al. REporting recommendations for tumour MARKer prognostic studies (REMARK). Br J Cancer. 2005;93:387–91.CrossRef
14.
go back to reference Brooks JD, Wei W, Hawley S, et al. Evaluation of ERG and SPINK1 by Immunohistochemical staining and Clinicopathological outcomes in a multi-institutional radical prostatectomy cohort of 1067 patients. PLoS One. 2015;10:e0132343.CrossRef Brooks JD, Wei W, Hawley S, et al. Evaluation of ERG and SPINK1 by Immunohistochemical staining and Clinicopathological outcomes in a multi-institutional radical prostatectomy cohort of 1067 patients. PLoS One. 2015;10:e0132343.CrossRef
15.
go back to reference TCGA. The molecular taxonomy of primary prostate Cancer. Cell. 2015;163:1011–25.CrossRef TCGA. The molecular taxonomy of primary prostate Cancer. Cell. 2015;163:1011–25.CrossRef
16.
go back to reference Leyten GHJM, Hessels D, Smit FP, et al. Identification of a candidate gene panel for the early diagnosis of prostate Cancer. Clin Cancer Res. 2015;21:3061–70.CrossRef Leyten GHJM, Hessels D, Smit FP, et al. Identification of a candidate gene panel for the early diagnosis of prostate Cancer. Clin Cancer Res. 2015;21:3061–70.CrossRef
17.
go back to reference Litovkin K, Joniau S, Lerut E, et al. Methylation of PITX2, HOXD3, RASSF1 and TDRD1 predicts biochemical recurrence in high-risk prostate cancer. J Cancer Res Clin Oncol. 2014;140:1849–61.CrossRef Litovkin K, Joniau S, Lerut E, et al. Methylation of PITX2, HOXD3, RASSF1 and TDRD1 predicts biochemical recurrence in high-risk prostate cancer. J Cancer Res Clin Oncol. 2014;140:1849–61.CrossRef
18.
go back to reference Tischler V, Fritzsche FR, Gerhardt J, et al. Comparison of the diagnostic value of fatty acid synthase (FASN) with alpha-methylacyl-CoA racemase (AMACR) as prostatic cancer tissue marker. Histopathology. 2010;56:811–5.CrossRef Tischler V, Fritzsche FR, Gerhardt J, et al. Comparison of the diagnostic value of fatty acid synthase (FASN) with alpha-methylacyl-CoA racemase (AMACR) as prostatic cancer tissue marker. Histopathology. 2010;56:811–5.CrossRef
19.
go back to reference Chao C, Chi M, Preciado M, Black MH. Methylation markers for prostate cancer prognosis: a systematic review. Cancer Causes Control. 2013;24:1615–41.CrossRef Chao C, Chi M, Preciado M, Black MH. Methylation markers for prostate cancer prognosis: a systematic review. Cancer Causes Control. 2013;24:1615–41.CrossRef
20.
go back to reference Huber F, Montani M, Sulser T, et al. Comprehensive validation of published immunohistochemical prognostic biomarkers of prostate cancer—what has gone wrong? A blueprint for the way forward in biomarker studies. Br J Cancer. 2015;112:140–8.CrossRef Huber F, Montani M, Sulser T, et al. Comprehensive validation of published immunohistochemical prognostic biomarkers of prostate cancer—what has gone wrong? A blueprint for the way forward in biomarker studies. Br J Cancer. 2015;112:140–8.CrossRef
21.
go back to reference Armenia J, Wankowicz SAM, Liu D, et al. The long tail of oncogenic drivers in prostate cancer. Nat Genet. 2018;50:645–51.CrossRef Armenia J, Wankowicz SAM, Liu D, et al. The long tail of oncogenic drivers in prostate cancer. Nat Genet. 2018;50:645–51.CrossRef
22.
go back to reference Linch M, Goh G, Hiley C, et al. Intratumoural evolutionary landscape of high-risk prostate cancer: the PROGENY study of genomic and immune parameters. Ann Oncol. 2017;28:2472–80.CrossRef Linch M, Goh G, Hiley C, et al. Intratumoural evolutionary landscape of high-risk prostate cancer: the PROGENY study of genomic and immune parameters. Ann Oncol. 2017;28:2472–80.CrossRef
23.
go back to reference Li S, Garrett-Bakelman FE, Chung SS, et al. Distinct evolution and dynamics of epigenetic and genetic heterogeneity in acute myeloid leukemia. Nat Med. 2016;22:792–9.CrossRef Li S, Garrett-Bakelman FE, Chung SS, et al. Distinct evolution and dynamics of epigenetic and genetic heterogeneity in acute myeloid leukemia. Nat Med. 2016;22:792–9.CrossRef
Metadata
Title
Where is the limit of prostate cancer biomarker research? Systematic investigation of potential prognostic and diagnostic biomarkers
Authors
Anika Kremer
Tobias Kremer
Glen Kristiansen
Yuri Tolkach
Publication date
01-12-2019
Publisher
BioMed Central
Published in
BMC Urology / Issue 1/2019
Electronic ISSN: 1471-2490
DOI
https://doi.org/10.1186/s12894-019-0479-z

Other articles of this Issue 1/2019

BMC Urology 1/2019 Go to the issue