A model to detect significant prostate cancer integrating urinary peptide and extracellular vesicle RNA data

O’Connell, S. P. et al. (2022) A model to detect significant prostate cancer integrating urinary peptide and extracellular vesicle RNA data. Cancers, 14(8), 1995. (doi: 10.3390/cancers14081995) (PMID:35454901) (PMCID:PMC9027643)

Abstract

There is a clinical need to improve assessment of biopsy-naïve patients for the presence of clinically significant prostate cancer (PCa). In this study, we investigated whether the robust integration of expression data from urinary extracellular vesicle RNA (EV-RNA) with urine proteomic metabolites can accurately predict PCa biopsy outcome. Urine samples collected within the Movember GAP1 Urine Biomarker study (n = 192) were analysed by both mass spectrometry-based urine-proteomics and NanoString gene-expression analysis (167 gene-probes). Cross-validated LASSO penalised regression and Random Forests identified a combination of clinical and urinary biomarkers for predictive modelling of significant disease (Gleason Score (Gs) ≥ 3 + 4). Four predictive models were developed: ‘MassSpec’ (CE-MS proteomics), ‘EV-RNA’, and ‘SoC’ (standard of care) clinical data models, alongside a fully integrated omics-model, deemed ‘ExoSpec’. ExoSpec (incorporating four gene transcripts, six peptides, and two clinical variables) is the best model for predicting Gs ≥ 3 + 4 at initial biopsy (AUC = 0.83, 95% CI: 0.77−0.88) and is superior to a standard of care (SoC) model utilising clinical data alone (AUC = 0.71, p 0.001, 1000 resamples). As the ExoSpec Risk Score increases, the likelihood of higher-grade PCa on biopsy is significantly greater (OR = 2.8, 95% CI: 2.1−3.7). The decision curve analyses reveals that ExoSpec provides a net benefit over SoC and could reduce unnecessary biopsies by 30%.

• Item Type: Articles
• Additional Information: This work was supported in part by the BioGuidePCa (E! 11023, Eurostars) funded by BMBF (Germany). This study was possible thanks to the Movember Foundation GAP1 Urine Biomarker project, The Masonic Charitable Foundation, The Bob Champion Cancer Trust, the King family, The Andy Ripley Memorial Fund, and The Hargrave Foundation.
• Keywords: Extracellular vesicles, mass spectrometry, prostate cancer, urinary biomarkers, RNA.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Mischak, Professor Harald and Salji, Dr Mark and Mullen, Dr Bill
• Authors: O’Connell, S. P., Frantzi, M., Latosinska, A., Webb, M., Mullen, W., Pejchinovski, M., Salji, M., Mischak, H., Cooper, C. S., Clark, J., and Brewer, D. S.
• College/School: College of Medical Veterinary and Life Sciences > School of Cancer Sciences; College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
• Journal Name: Cancers
• Publisher: MDPI
• ISSN: 2072-6694
• ISSN (Online): 2072-6694
• Published Online: 14 April 2022
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in Cancers 14(8): 1995
• Publisher Policy: Reproduced under a Creative Commons License
• Data DOI: 10.5281/zenodo.6448114