Spatial metabolomics informs the use of clinical imaging for improved detection of cribriform prostate cancer

N Nikita Sushentsev (Department of Radiology, Addenbrooke’s Hospital and University of Cambridge) G Gregory Hamm (Integrated BioAnalysis, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca) R Roido Manavaki (Department of Radiology, Addenbrooke’s Hospital and University of Cambridge) M Mary A. McLean (Department of Radiology, Addenbrooke’s Hospital and University of Cambridge) J Jonathan Birchall (Department of Radiology, Addenbrooke’s Hospital and University of Cambridge) D Dmitry Soloviev (Lewis Group, School of Cancer Sciences, University of Glasgow) D David Y. Lewis L Luigi Aloj (Department of Radiology, Addenbrooke’s Hospital and University of Cambridge) L Lucy Flint (Integrated BioAnalysis, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca) A Aleksandr Zakirov (Department of Clinical Neurosciences, University of Cambridge) I Ian G. Mills (Nuffield Department of Surgical Sciences, University of Oxford) V Vincent J. Gnanapragasam (Department of Urology, Cambridge University Hospitals National Health Service Foundation Trust) A Anne Y. Warren (Department of Pathology, Cambridge University Hospitals National Health Service Foundation Trust) S Simon T. Barry R Richard J. A. Goodwin (Integrated BioAnalysis, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca) F Ferdia A. Gallagher (Department of Radiology, Addenbrooke’s Hospital and University of Cambridge) T Tristan Barrett (Department of Radiology, Addenbrooke’s Hospital and University of Cambridge)

Abstract

Cribriform prostate cancer (crPCa) is associated with poor clinical outcomes, yet its accurate detection remains challenging due to the poor sensitivity of standard-of-care diagnostic tools. Here, we use untargeted spatial metabolomics to identify fatty acid biosynthesis as a key metabolic pathway enriched in crPCa epithelium. We also show that imaging tumor lipid metabolism using [1- 11 C]acetate PET/CT and proton magnetic resonance spectroscopy differentiates cribriform from noncribriform intermediate-risk prostate cancers in two prospective patient cohorts. These findings support the feasibility of using clinical metabolic imaging techniques as adjunctive tools for improving crPCa detection in clinical practice, with prospective studies in larger cohorts warranted to obtain definitive results.

Article Details

Volume / Issue Vol. 122, Issue 26
Published July 01, 2025
ISSN 0027-8424
Publisher National Academy of Sciences

Authors (17)

N

Nikita Sushentsev

Department of Radiology, Addenbrooke’s Hospital and University of Cambridge

G

Gregory Hamm

Integrated BioAnalysis, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca

R

Roido Manavaki

Department of Radiology, Addenbrooke’s Hospital and University of Cambridge

M

Mary A. McLean

Department of Radiology, Addenbrooke’s Hospital and University of Cambridge

J

Jonathan Birchall

Department of Radiology, Addenbrooke’s Hospital and University of Cambridge

D

Dmitry Soloviev

Lewis Group, School of Cancer Sciences, University of Glasgow

D

David Y. Lewis

L

Luigi Aloj

Department of Radiology, Addenbrooke’s Hospital and University of Cambridge

L

Lucy Flint

Integrated BioAnalysis, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca

A

Aleksandr Zakirov

Department of Clinical Neurosciences, University of Cambridge

I

Ian G. Mills

Nuffield Department of Surgical Sciences, University of Oxford

V

Vincent J. Gnanapragasam

Department of Urology, Cambridge University Hospitals National Health Service Foundation Trust

A

Anne Y. Warren

Department of Pathology, Cambridge University Hospitals National Health Service Foundation Trust

S

Simon T. Barry

R

Richard J. A. Goodwin

Integrated BioAnalysis, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca

F

Ferdia A. Gallagher

Department of Radiology, Addenbrooke’s Hospital and University of Cambridge

T

Tristan Barrett

Department of Radiology, Addenbrooke’s Hospital and University of Cambridge