A Scaled Proteomic Discovery Study for Prostate Cancer Diagnostic Markers Using ProteographTM and Trapped Ion Mobility Mass Spectrometry

Sep 21, 2026

Uploaded by Liam

There is a significant unmet need for clinical reflex tests that increase the specificity of prostate-specific antigen (PSA) blood testing, a historically important but imperfect tool for prostate cancer diagnosis. This study presents discovery results identifying new PSA reflex markers from a large-scale patient serum cohort using deep proteomic interrogation. Known markers and novel candidates are detected, and pathway enrichment and network analysis associate differentially abundant proteins with cytoskeletal, metabolic, and ribosomal activities linked to progression.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages26

Reading Time1 h 6 min

AccessFree to download

Introduction

Background on PSA and current diagnostic use

Clinical controversy and limitations of PSA screening

Role and shortcomings of MRI and PSA reflex strategies

Proteomics approach for PSA reflex biomarker discovery

Article A Scaled Proteomic Discovery Study for Prostate Cancer Diagnostic Markers Using ProteographTM and Trapped Ion Mobility Mass Spectrometry Matthew E. K. Chang 1, Jane Lange 1, Jessie May Cartier 1, Travis W. Moore 1, Sophia M. Soriano 1, Brenna Albracht 2, Michael Krawitzky 3, Harendra Guturu 4, Amir Alavi 4, Alexey Stukalov 4, Xiaoyuan Zhou 4, Eltaher M. Elgierari 4, Jessica Chu 4, Ryan Benz 4, Juan C. Cuevas 4, Shadi Ferdosi 4, Daniel Hornburg 4, Omid Farokhzad 4, Asim Siddiqui 4, Serafim Batzoglou 4, Robin J. Leach 2, Michael A. Liss 5, Ryan P. Kopp 1 and Mark R. Flory 1, * Citation: Chang, M.E.K.; Lange, J.; Cartier, J.M.; Moore, T.W.; Soriano, S.M.; Albracht, B.; Krawitzky, M.; Guturu, H.; Alavi, A.; Stukalov, A.; et al. A Scaled Proteomic Discovery Study for Prostate Cancer Diagnostic Markers Using ProteographTM and Trapped Ion Mobility Mass Spectrometry. Int. J. Mol. Sci. 2024, 25, 8010. [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)ijms25158010 Academic Editor: Benedikt Kranzbühler Received: 12 June 2024 Revised: 3 July 2024 Accepted: 9 July 2024 Published: 23 July 2024 Copyright: © 2024 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://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) . 1 Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97201, USA; [changma@ohsu.edu](changma@ohsu.edu) (M.E.K.C.); [ssoriano@sumbeach.com](ssoriano@sumbeach.com) (S.M.S.) 2 Department of Cell Systems and Anatomy, University of Texas Health San Antonio, San Antonio, TX 78229, USA 3 Bruker Daltonics, Billerica, MA 01821, USA 4 Seer Inc., Redwood City, CA 94065, USA 5 Roger L. & Laura D. Zeller Charitable Foundation in Urologic Oncology, University of Texas Health San Antonio, San Antonio, TX 78229, USA * [Correspondence: flory@ohsu.edu](Correspondence: flory@ohsu.edu) Abstract: There is a significant unmet need for clinical reflex tests that increase the specificity of prostate-specific antigen blood testing, the longstanding but imperfect tool for prostate cancer diagnosis. Towards this endpoint, we present the results from a discovery study that identifies new prostate-specific antigen reflex markers in a large-scale patient serum cohort using differentiating technologies for deep proteomic interrogation. We detect known prostate cancer blood markers as well as novel candidates. Through bioinformatic pathway enrichment and network analysis, we reveal associations of differentially abundant proteins with cytoskeletal, metabolic, and ribosomal activities, all of which have been previously associated with prostate cancer progression. Additionally, optimized machine learning classifier analysis reveals proteomic signatures capable of detecting the disease prior to biopsy, performing on par with an accepted clinical risk calculator benchmark. Keywords: prostate cancer; biomarker; serum; proteomics; mass spectrometry; diagnosis 1. Introduction Prostate cancer is the most commonly diagnosed non-cutaneous cancer and the sec[ond leading cause of cancer-related death among U.S. men](ond leading cause of cancer-related death among U.S. men) [1]. For decades, the clinical measurement of the prostate-specific antigen (PSA) protein in blood has been the primary method for detecting prostate cancer. Since the advent of PSA screening in the early 1990s, prostate cancer mortality in the U.S. has decreased by almost 50%[2–4], and today PSA remains the principal marker used for detection, progression, and, in certain contexts, predicting the clinical outcomes of prostate cancer [5,6] . However, PSA screening is controversial due to its association with several harms,

FAQs

What clinical problem does the study address?

The study targets the need for reflex tests that improve the specificity of PSA blood testing while reducing false negatives and unnecessary procedures.

How were potential diagnostic markers discovered?

Markers were identified in a large-scale patient serum cohort using deep proteomic interrogation with ProteographTM and trapped ion mobility mass spectrometry.

What analytical methods supported the findings?

The study used bioinformatic pathway enrichment and network analysis, and applied optimized machine learning classifiers to assess proteomic signatures for pre-biopsy disease detection.

Sep 21, 2026

Uploaded by Liam