Evidence map›Paper›PMID 39180680›Full record

ArticleJournal of cancer research and clinical oncology2024

Epigenetic profiling of prostate cancer reveals potential prognostic signatures.

Simon Bernatz, Ian G Reddin, Tim R Fenton, Thomas J Vogl, Peter J Wild, Jens Köllermann, Philipp Mandel, Mike Wenzel, Benedikt Hoeh, Scherwin Mahmoudi and 6 more

Abstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Simon BernatzGoethe University Frankfurt, University Hospital, Clinic for Radiology and Nuclear Medicine, Frankfurt am Main, Germany.
Ian G ReddinSchool of Cancer Sciences, University of Southampton, Southampton, UK.
Tim R FentonSchool of Cancer Sciences, University of Southampton, Southampton, UK.
Thomas J VoglGoethe University Frankfurt, University Hospital, Clinic for Radiology and Nuclear Medicine, Frankfurt am Main, Germany.
Peter J WildGoethe University Frankfurt, University Hospital, Dr. Senckenberg Institute for Pathology, Frankfurt am Main, Germany.
Jens KöllermannGoethe University Frankfurt, University Hospital, Dr. Senckenberg Institute for Pathology, Frankfurt am Main, Germany.
Philipp MandelGoethe University Frankfurt, University Hospital, Department of Urology, Frankfurt am Main, Germany.
Mike WenzelGoethe University Frankfurt, University Hospital, Department of Urology, Frankfurt am Main, Germany.
Benedikt HoehGoethe University Frankfurt, University Hospital, Department of Urology, Frankfurt am Main, Germany.
Scherwin MahmoudiGoethe University Frankfurt, University Hospital, Clinic for Radiology and Nuclear Medicine, Frankfurt am Main, Germany.
Vitali KochGoethe University Frankfurt, University Hospital, Clinic for Radiology and Nuclear Medicine, Frankfurt am Main, Germany.
Leon D GrünewaldGoethe University Frankfurt, University Hospital, Clinic for Radiology and Nuclear Medicine, Frankfurt am Main, Germany.
Renate HammerstinglGoethe University Frankfurt, University Hospital, Clinic for Radiology and Nuclear Medicine, Frankfurt am Main, Germany.
Claudia DöringGoethe University Frankfurt, University Hospital, Dr. Senckenberg Institute for Pathology, Frankfurt am Main, Germany.
Patrick N HarterFrankfurt Cancer Institute (FCI), Frankfurt am Main, Germany.
Katharina J WeberFrankfurt Cancer Institute (FCI), Frankfurt am Main, Germany. K.Weber@med.uni-frankfurt.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWhile 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.

methodsWe 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.

resultsLCMs 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.

conclusionEpigenetic 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.

Indexed as

Biomarkers, TumorDNA MethylationEpigenesis, GeneticProstatic NeoplasmsAgedHumansMaleMiddle AgedPrognosisProstatectomyRetrospective StudiesBiomarkers, TumorDNA methylation-based tumor deconvolutionProstate cancerRadiomics

Identifiers

PMID39180680
PMCPMC11344710

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.