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Proteomic discovery of non-invasive biomarkers of localized prostate cancer using mass spectrometry

Nature Reviews Urology volume 18, pages 707–724 (2021)Cite this article

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Abstract

Prostate cancer is the second most frequently diagnosed non-skin cancer in men worldwide. Patient outcomes are remarkably heterogeneous and the best existing clinical prognostic tools such as International Society of Urological Pathology Grade Group, pretreatment serum PSA concentration and T-category, do not accurately predict disease outcome for individual patients. Thus, patients newly diagnosed with prostate cancer are often overtreated or undertreated, reducing quality of life and increasing disease-specific mortality. Biomarkers that can improve the risk stratification of these patients are, therefore, urgently needed. The ideal biomarker in this setting will be non-invasive and affordable, enabling longitudinal evaluation of disease status. Prostatic secretions, urine and blood can be sources of biomarker discovery, validation and clinical implementation, and mass spectrometry can be used to detect and quantify proteins in these fluids. Protein biomarkers currently in use for diagnosis, prognosis and relapse-monitoring of localized prostate cancer in fluids remain centred around PSA and its variants, and opportunities exist for clinically validating novel and complimentary candidate protein biomarkers and deploying them into the clinic.

Key points

  • Standard-of-care clinical tools for the management of localized prostate cancer result in substantial overdiagnosis and overtreatment.

  • Fluid-based protein biomarkers have the potential to complement clinical decision-making.

  • Advances in mass spectrometry, such as increased scan speeds and mass resolution, have enabled the systematic discovery and validation of protein biomarkers in prostate-associated fluids.

  • Appropriate sample selection for biomarker discovery and validation can improve detection of prostate-derived proteins in fluids.

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Fig. 1: The role of biomarkers in prostate cancer management.
Fig. 2: Biomarker discovery to translation into the clinic.
Fig. 3: Clinically relevant fluids in prostate cancer.

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Acknowledgements

This work was partially funded by the National Cancer Institute Early Detection Research Network (1U01CA214194-01), a Prostate Cancer Canada Discovery Grant (400398) and a Canadian Cancer Society Impact Grant (705649). A.K. was supported by an Ontario Graduate Scholarship and a Paul STARITA Graduate Student Fellowship. L.Y.L. was supported by a CIHR Vanier Award. This work was supported by the NIH/NCI under award number P30CA016042.

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Author notes

  1. These authors contributed equally: Amanda Khoo, Lydia Y. Liu.

Authors and Affiliations

  1. Department of Medical Biophysics, University of Toronto, Toronto, Canada

    Amanda Khoo, Lydia Y. Liu, Paul C. Boutros, Stanley K. Liu & Thomas Kislinger

  2. Princess Margaret Cancer Centre, University Health Network, Toronto, Canada

    Amanda Khoo, Lydia Y. Liu & Thomas Kislinger

  3. Vector Institute for Artificial Intelligence, Toronto, Canada

    Lydia Y. Liu & Paul C. Boutros

  4. Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA

    Lydia Y. Liu & Paul C. Boutros

  5. Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, USA

    Lydia Y. Liu & Paul C. Boutros

  6. Leroy T. Canoles Jr. Cancer Research Center, Eastern Virginia Medical School, Norfolk, VA, USA

    Julius O. Nyalwidhe & O. John Semmes

  7. Department of Microbiology and Molecular Cell Biology, Eastern Virginia Medical School, Norfolk, VA, USA

    Julius O. Nyalwidhe & O. John Semmes

  8. Department of Radiation Oncology, University of Toronto, Toronto, Canada

    Danny Vesprini & Stanley K. Liu

  9. Odette Cancer Research Program, Sunnybrook Research Institute, Toronto, Canada

    Danny Vesprini & Stanley K. Liu

  10. Division of Anatomic Pathology, Sunnybrook Health Sciences Centre, Toronto, Canada

    Michelle R. Downes

  11. Department of Pharmacology and Toxicology, University of Toronto, Toronto, Canada

    Paul C. Boutros

  12. Department of Urology, University of California, Los Angeles, Los Angeles, CA, USA

    Paul C. Boutros

  13. Institute for Precision Health, University of California, Los Angeles, Los Angeles, CA, USA

    Paul C. Boutros

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  1. Amanda Khoo
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Contributions

All authors made substantial contributions to discussions of content, wrote the article and reviewed and edited the manuscript before submission.

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Correspondence to Paul C. Boutros, Stanley K. Liu or Thomas Kislinger.

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Related links

Clinical Proteomic Tumour Analysis Consortium: https://proteomics.cancer.gov/programs/cptac

The Cancer Genome Atlas: https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga

The Human Protein Atlas: https://www.proteinatlas.org/

Glossary

Protein abundance

A measure of the number of proteins in a sample, estimated from direct measurements of peptide abundance.

Mass spectrometry

(MS). An analytical technique that separates ions by mass:charge ratio in a mass analyser.

Proteomics

The large-scale study of proteomes, which are sets of proteins produced in a biological context such as by a cell, tissue or organism.

Shotgun proteomics

An untargeted workflow for identifying and quantifying proteins by mass spectrometry via proteolytic digestion of proteins into peptides.

Dynamic range

In mass spectrometry, this term is the range of protein abundances in a sample.

Precursor ion

Intact ions that later dissociate into smaller fragment ions.

Fragment ion

An ion that is the product of fragmentation. For peptides, fragment ions are produced from fragmentation at the peptide backbone.

Data-dependent acquisition

(DDA). A mass-spectrometry acquisition method in which the top N most intense peptides are selected for fragmentation.

Data-independent acquisition

(DIA). A mass-spectrometry acquisition method in which all peptides within a given mass window (such as 15–50 m/z) are selected for fragmentation. Peptides in a selected mass range are fragmented using sequential windows.

Selected reaction monitoring/multiple reaction monitoring

(SRM/MRM). A targeted mass spectrometry method that sequentially isolates and records pre-selected fragment ion masses from a peptide.

Triple-quadrupole mass spectrometer

A tandem mass spectrometer consisting of two quadrupole mass analysers arranged sequentially for mass isolation with an additional quadrupole in the middle that is used for collision-induced dissociation.

Parallel reaction monitoring

(PRM). A targeted mass spectrometry method that isolates and records all fragment ion masses from a peptide.

Orbitrap mass analyser

An ion-trap mass analyser that detects m/z signals by oscillating ions around a cylindrical electrode with tapered ends.

Glycoproteomics

The large-scale study of the glycoproteome, the set of glycosylated proteins, by selective enrichment of N-glycosylated or O-glycosylated peptides.

Patient-derived xenografts

(PDX). Tumours grown from the implantation of a patient’s tumour cells into immunodeficient or immunocompromised mice.

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Khoo, A., Liu, L.Y., Nyalwidhe, J.O. et al. Proteomic discovery of non-invasive biomarkers of localized prostate cancer using mass spectrometry. Nat Rev Urol 18, 707–724 (2021). https://doi.org/10.1038/s41585-021-00500-1

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