A Novel Blood Proteomic Signature for Prostate Cancer

Author:

Muazzam Ammara123,Spick Matt4ORCID,Cexus Olivier N. F.5ORCID,Geary Bethany6,Azhar Fowz17,Pandha Hardev5,Michael Agnieszka5ORCID,Reed Rachel2,Lennon Sarah8ORCID,Gethings Lee A.9,Plumb Robert S.10,Whetton Anthony D.11,Geifman Nophar4ORCID,Townsend Paul A.124ORCID

Affiliation:

1. Manchester Cancer Research Centre, Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PL, UK

2. Stoller Biomarker Discovery Centre, Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PL, UK

3. The Hospital for Sick Children (SickKids), 555 University Ave, Toronto, ON M5G 1X8, Canada

4. School of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK

5. School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK

6. School of Life Sciences, University of Dundee, Dundee DD1 4HN, UK

7. Salford Royal NHS Foundation Trust, Salford Royal Hospital, Salford M6 8HD, UK

8. Inserm, EHESP, Irset (Institut de Recherche en Santé, Environnement et Travail)—UMR_S 1085, University of Rennes, 35042 Rennes, France

9. Manchester Institute of Biotechnology, Division of Infection, Immunity and Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PL, UK

10. Murdoch University, Perth, WA 6150, Australia

11. Veterinary Health Innovation Engine, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK

Abstract

Prostate cancer is the most common malignant tumour in men. Improved testing for diagnosis, risk prediction, and response to treatment would improve care. Here, we identified a proteomic signature of prostate cancer in peripheral blood using data-independent acquisition mass spectrometry combined with machine learning. A highly predictive signature was derived, which was associated with relevant pathways, including the coagulation, complement, and clotting cascades, as well as plasma lipoprotein particle remodeling. We further validated the identified biomarkers against a second cohort, identifying a panel of five key markers (GP5, SERPINA5, ECM1, IGHG1, and THBS1) which retained most of the diagnostic power of the overall dataset, achieving an AUC of 0.91. Taken together, this study provides a proteomic signature complementary to PSA for the diagnosis of patients with localised prostate cancer, with the further potential for assessing risk of future development of prostate cancer. Data are available via ProteomeXchange with identifier PXD025484.

Funder

Medical Research Council

Cancer Research UK

Punjab Educational Endowment Fund

Blood Cancer UK

Male Uprising / Hope for Guernsey

Publisher

MDPI AG

Subject

Cancer Research,Oncology

Reference81 articles.

1. (2022, December 20). Prostate Cancer Statistics. Cancer Research UK. Available online: https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/prostate-cancer.

2. USCS (2022, December 18). Data Visualizations, Available online: https://www.cdc.gov/cancer/uscs/dataviz/index.htm.

3. (2023, January 04). Overview. Prostate Cancer: Diagnosis and Management. Guidance. NICE. Available online: https://www.nice.org.uk/guidance/ng131/chapter/recommendations.

4. Total Medicare Costs Associated with Diagnosis and Treatment of Prostate Cancer in Elderly Men;Trogdon;JAMA Oncol.,2019

5. PSA (2021, March 18). North Bristol NHS Trust. Available online: https://www.nbt.nhs.uk/severn-pathology/requesting/test-information/psa.

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