Takita, S., Nabok, A., Mussa, M.H. et al. (3 more authors) (2026) Prostate cancer diagnostics in transition: a review of promising biomarkers, multiplex biosensors, and point-of-care diagnostic strategies. Chemosensors, 14 (4). 99. ISSN: 2227-9040
Abstract
Prostate cancer (PCa) remains one of the most prevalent urological malignancies worldwide, with early and accurate diagnosis being critical for improving patient outcomes. Traditional screening approaches, such as digital rectal examination and prostate-specific antigen (PSA) testing, have long served as frontline tools; however, their limited specificity and sensitivity contribute to high rates of false positives, unnecessary biopsies, and overtreatment. Recent UK guidelines and international consensus increasingly question the role of PSA-based population screening, advocating for risk-stratified pathways and multiparametric MRI as first-line investigations. In parallel, advances in molecular biology have identified promising cancer-specific biomarkers, such as prostate cancer antigen 3 (PCA3) and transmembrane protease serine 2 (TMPRSS2:ERG), that outperform PSAs in terms of specificity and prognostic value. These developments have catalysed innovation in biosensor technologies, enabling rapid, cost-effective, and non-invasive detection of single and multiplex biomarkers in urine and serum. Electrochemical and optical affinity-based biosensors offer transformative potential for the development of personalised point-of-care platforms and diagnostics, reducing the reliance on invasive procedures and improving clinical decision-making. The latter can be augmented with artificial intelligence (AI) tools. This review critically examines the limitations of PSAs, synthesises evidence on novel biomarkers and imaging-led strategies, and evaluates the design, performance, and translational challenges of biosensor-based assays. Furthermore, it outlines future directions, including standardisation, large-scale clinical validation, and integration of multiplex biosensors with AI for precision diagnostics. By bridging molecular insights with engineering innovations, these approaches promise to redefine PCa screening and enable accurate, patient-centred care.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. https://creativecommons.org/licenses/by/4.0/ |
| Keywords: | prostate cancer; risk-stratified screening; PSA; PCA3; TMPRSS2:ERG; multiparametric MRI; biosensors; point-of-care diagnostics |
| Dates: |
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| Institution: | The University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > School of Chemical, Materials and Biological Engineering |
| Date Deposited: | 21 Apr 2026 08:37 |
| Last Modified: | 21 Apr 2026 08:37 |
| Status: | Published |
| Publisher: | MDPI AG |
| Refereed: | Yes |
| Identification Number: | 10.3390/chemosensors14040099 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:240256 |
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Filename: chemosensors-14-00099.pdf
Licence: CC-BY 4.0

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