Epigenetic profiling of prostate cancer reveals potential prognostic signatures
Epigenetic profiling of prostate cancer reveals potential prognostic signatures
Purpose: while epigenetic profiling discovered biomarkers in several tumor entities, its application in prostate cancer is still limited. We explored DNA methylation-based deconvolution of benign and malignant prostate tissue for biomarker discovery and the potential of radiomics as a non-invasive surrogate.
Methods: we retrospectively included 30 patients (63 [58–79] years) with prostate cancer (PCa) who had a multiparametric MRI of the prostate before radical prostatectomy between 2014 and 2019. The control group comprised four patients with benign prostate tissue adjacent to the PCa lesions and four patients with benign prostatic hyperplasia. Tissue punches of all lesions were obtained. DNA methylation analysis and reference-free in silico deconvolution were conducted to retrieve Latent Methylation Components (LCMs). LCM-based clustering was analyzed for cellular composition and correlated with clinical disease parameters. Additionally, PCa and adjacent benign lesions were analyzed using radiomics to predict the epigenetic signatures non-invasively.
Results: LCMs identified two clusters with potential prognostic impact. Cluster one was associated with malignant prostate tissue (p < 0.001) and reduced immune-cell-related signatures (p = 0.004) of CD19 and CD4 cells. Cluster one comprised exclusively malignant prostate tissue enriched for significant prostate cancer and advanced tumor stages (p < 0.03 for both). No radiomics model could non-invasively predict the epigenetic clusters.
Conclusion: epigenetic clusters were associated with prognostically and clinically relevant metrics in prostate cancer. Further, immune cell-related signatures differed significantly between prognostically favorable and unfavorable clusters. Further research is necessary to explore potential diagnostic and therapeutic implications.
DNA methylation-based tumor deconvolution, Prostate cancer, Radiomics
Bernatz, Simon
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Reddin, Ian G.
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Fenton, Tim R.
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Vogl, Thomas J.
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Wild, Peter J.
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Köllermann, Jens
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Mandel, Philipp
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Wenzel, Mike
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Hoeh, Benedikt
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Mahmoudi, Scherwin
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Koch, Vitali
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Grünewald, Leon D.
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Hammerstingl, Renate
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Döring, Claudia
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Harter, Patrick N.
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Weber, Katharina J.
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24 August 2024
Bernatz, Simon
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Reddin, Ian G.
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Fenton, Tim R.
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Vogl, Thomas J.
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Wild, Peter J.
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Köllermann, Jens
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Mandel, Philipp
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Wenzel, Mike
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Hoeh, Benedikt
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Mahmoudi, Scherwin
93d2d363-0f7a-4911-9b78-43bd58bd9727
Koch, Vitali
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Grünewald, Leon D.
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Hammerstingl, Renate
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Döring, Claudia
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Harter, Patrick N.
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Weber, Katharina J.
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Bernatz, Simon, Reddin, Ian G., Fenton, Tim R., Vogl, Thomas J., Wild, Peter J., Köllermann, Jens, Mandel, Philipp, Wenzel, Mike, Hoeh, Benedikt, Mahmoudi, Scherwin, Koch, Vitali, Grünewald, Leon D., Hammerstingl, Renate, Döring, Claudia, Harter, Patrick N. and Weber, Katharina J.
(2024)
Epigenetic profiling of prostate cancer reveals potential prognostic signatures.
Journal of Cancer Research and Clinical Oncology, 150 (8).
(doi:10.1007/s00432-024-05921-0).
Abstract
Purpose: while epigenetic profiling discovered biomarkers in several tumor entities, its application in prostate cancer is still limited. We explored DNA methylation-based deconvolution of benign and malignant prostate tissue for biomarker discovery and the potential of radiomics as a non-invasive surrogate.
Methods: we retrospectively included 30 patients (63 [58–79] years) with prostate cancer (PCa) who had a multiparametric MRI of the prostate before radical prostatectomy between 2014 and 2019. The control group comprised four patients with benign prostate tissue adjacent to the PCa lesions and four patients with benign prostatic hyperplasia. Tissue punches of all lesions were obtained. DNA methylation analysis and reference-free in silico deconvolution were conducted to retrieve Latent Methylation Components (LCMs). LCM-based clustering was analyzed for cellular composition and correlated with clinical disease parameters. Additionally, PCa and adjacent benign lesions were analyzed using radiomics to predict the epigenetic signatures non-invasively.
Results: LCMs identified two clusters with potential prognostic impact. Cluster one was associated with malignant prostate tissue (p < 0.001) and reduced immune-cell-related signatures (p = 0.004) of CD19 and CD4 cells. Cluster one comprised exclusively malignant prostate tissue enriched for significant prostate cancer and advanced tumor stages (p < 0.03 for both). No radiomics model could non-invasively predict the epigenetic clusters.
Conclusion: epigenetic clusters were associated with prognostically and clinically relevant metrics in prostate cancer. Further, immune cell-related signatures differed significantly between prognostically favorable and unfavorable clusters. Further research is necessary to explore potential diagnostic and therapeutic implications.
Text
s00432-024-05921-0
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Accepted/In Press date: 11 August 2024
Published date: 24 August 2024
Keywords:
DNA methylation-based tumor deconvolution, Prostate cancer, Radiomics
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Local EPrints ID: 493929
URI: http://eprints.soton.ac.uk/id/eprint/493929
ISSN: 0171-5216
PURE UUID: 488194fc-0051-488c-a9b5-06c16819a3de
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Date deposited: 17 Sep 2024 17:02
Last modified: 18 Sep 2024 02:04
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Contributors
Author:
Simon Bernatz
Author:
Ian G. Reddin
Author:
Thomas J. Vogl
Author:
Peter J. Wild
Author:
Jens Köllermann
Author:
Philipp Mandel
Author:
Mike Wenzel
Author:
Benedikt Hoeh
Author:
Scherwin Mahmoudi
Author:
Vitali Koch
Author:
Leon D. Grünewald
Author:
Renate Hammerstingl
Author:
Claudia Döring
Author:
Patrick N. Harter
Author:
Katharina J. Weber
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