Innovative Biomarkers and Imaging Techniques for the Early Detection and Risk Stratification of Urological Tumours

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Epidemiology and Prevention".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 2153

Special Issue Editor


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Guest Editor
1. Senior Physician, Urology Clinic, Heidelberg University Hospital, Heidelberg, Germany
2. Head of Department, Junior Clinical Cooperation Unit ‘Multiparametric Methods for the Early Detection of Prostate Cancer’, German Cancer Research Center (DKFZ), Heidelberg, Germany
Interests: artificial intelligence; early detection; multi-omics; precision medicine; surgery; uro-oncology

Special Issue Information

Dear Colleagues,

The early detection and risk stratification of uro-oncology tumours are being driven by novel biomarkers and advanced imaging techniques. These innovations are transforming the diagnosis and management of urological tumours, providing deeper insights into disease mechanisms and enabling more precise and personalized treatment strategies.

We are pleased to invite you to contribute to this Special Issue, entitled "Innovative Biomarkers and Imaging Techniques for the Early Detection and Risk Stratification of Urological Tumours". This Special Issue aims to provide a detailed exploration of the current landscape and future directions in the early detection and risk stratification of urological tumours, focusing on the integration of novel diagnostic technologies and their impact on clinical outcomes.

In this Special Issue, original research articles and reviews are welcome to be submitted. Research areas may include novel biomarkers in blood, urine, and tissue with significant potential for clinical application, providing a benefit for the early detection, prognosis, and risk stratification of urological tumours. In addition, we invite manuscripts that address the potential, challenges, and future prospects of incorporating advanced imaging techniques in uro-oncology. This includes the exploration of multimodal imaging approaches and their synergy with novel biomarkers to improve diagnostic accuracy and patient management.

Manuscripts that explore the integration of these novel biomarkers and imaging modalities into clinical workflows and their potential to improve patient stratification and therapeutic decision making are particularly encouraged.

I look forward to receiving your contributions.

Dr. Magdalena Görtz
Guest Editor

Manuscript Submission Information

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Keywords

  • urological tumours
  • novel biomarkers
  • advanced imaging techniques
  • early detection
  • risk stratification
  • molecular diagnostics
  • multimodal data integration
  • personalized treatment

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Published Papers (1 paper)

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Research

15 pages, 1569 KiB  
Article
Prediagnostic Plasma Nutrimetabolomics and Prostate Cancer Risk: A Nested Case–Control Analysis Within the EPIC Study
by Enrique Almanza-Aguilera, Miriam Martínez-Huélamo, Yamilé López-Hernández, Daniel Guiñón-Fort, Anna Guadall, Meryl Cruz, Aurora Perez-Cornago, Agnetha L. Rostgaard-Hansen, Anne Tjønneland, Christina C. Dahm, Verena Katzke, Matthias B. Schulze, Giovanna Masala, Claudia Agnoli, Rosario Tumino, Fulvio Ricceri, Cristina Lasheras, Marta Crous-Bou, Maria-Jose Sánchez, Amaia Aizpurua-Atxega, Marcela Guevara, Kostas K. Tsilidis, Anastasia Chrysovalantou Chatziioannou, Elisabete Weiderpass, Ruth C. Travis, David S. Wishart, Cristina Andrés-Lacueva and Raul Zamora-Rosadd Show full author list remove Hide full author list
Cancers 2024, 16(23), 4116; https://doi.org/10.3390/cancers16234116 - 8 Dec 2024
Viewed by 1779
Abstract
Background and Objective: Nutrimetabolomics may reveal novel insights into early metabolic alterations and the role of dietary exposures on prostate cancer (PCa) risk. We aimed to prospectively investigate the associations between plasma metabolite concentrations and PCa risk, including clinically relevant tumor subtypes. [...] Read more.
Background and Objective: Nutrimetabolomics may reveal novel insights into early metabolic alterations and the role of dietary exposures on prostate cancer (PCa) risk. We aimed to prospectively investigate the associations between plasma metabolite concentrations and PCa risk, including clinically relevant tumor subtypes. Methods: We used a targeted and large-scale metabolomics approach to analyze plasma samples of 851 matched PCa case–control pairs from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Associations between metabolite concentrations and PCa risk were estimated by multivariate conditional logistic regression analysis. False discovery rate (FDR) was used to control for multiple testing correction. Results: Thirty-one metabolites (predominately derivatives of food intake and microbial metabolism) were associated with overall PCa risk and its clinical subtypes (p < 0.05), but none of the associations exceeded the FDR threshold. The strongest positive and negative associations were for dimethylglycine (OR = 2.13; 95% CI 1.16–3.91) with advanced PCa risk (n = 157) and indole-3-lactic acid (OR = 0.28; 95% CI 0.09–0.87) with fatal PCa risk (n = 57), respectively; however, these associations did not survive correction for multiple testing. Conclusions: The results from the current nutrimetabolomics study suggest that apart from early metabolic deregulations, some biomarkers of food intake might be related to PCa risk, especially advanced and fatal PCa. Further independent and larger studies are needed to validate our results. Full article
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