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van der Burgt Y, Wuhrer M. The role of clinical glyco(proteo)mics in precision medicine. Mol Cell Proteomics 2023:100565. [PMID: 37169080 DOI: 10.1016/j.mcpro.2023.100565] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/12/2023] [Accepted: 05/02/2023] [Indexed: 05/13/2023] Open
Abstract
Glycoproteomics reveals site-specific O- and N-glycosylation that may influence protein properties including binding, activity and half-life. The increasingly mature toolbox with glycomic- and glycoproteomic strategies is applied for the development of biopharmaceuticals and discovery and clinical evaluation of glycobiomarkers in various disease fields. Notwithstanding the contributions of glycoscience in identifying new drug targets, the current report is focused on the biomarker modality that is of interest for diagnostic and monitoring purposes. To this end it is noted that the identification of biomarkers has received more attention than corresponding quantification. Most analytical methods are very efficient in detecting large numbers of analytes but developments to accurately quantify these have so far been limited. In this perspective a parallel is made with earlier proposed tiers for protein quantification using mass spectrometry. Moreover, the foreseen reporting of multimarker readouts is discussed to describe an individual's health or disease state and their role in clinical decision-making. The potential of longitudinal sampling and monitoring of glycomic features for diagnosis and treatment monitoring is emphasized. Finally, different strategies that address quantification of a multimarker panel will be discussed.
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Affiliation(s)
- Yuri van der Burgt
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands.
| | - Manfred Wuhrer
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
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2
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Katz DH, Robbins JM, Deng S, Tahir UA, Bick AG, Pampana A, Yu Z, Ngo D, Benson MD, Chen ZZ, Cruz DE, Shen D, Gao Y, Bouchard C, Sarzynski MA, Correa A, Natarajan P, Wilson JG, Gerszten RE. Proteomic profiling platforms head to head: Leveraging genetics and clinical traits to compare aptamer- and antibody-based methods. SCIENCE ADVANCES 2022; 8:eabm5164. [PMID: 35984888 PMCID: PMC9390994 DOI: 10.1126/sciadv.abm5164] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Accepted: 07/07/2022] [Indexed: 05/10/2023]
Abstract
High-throughput proteomic profiling using antibody or aptamer-based affinity reagents is used increasingly in human studies. However, direct analyses to address the relative strengths and weaknesses of these platforms are lacking. We assessed findings from the SomaScan1.3K (N = 1301 reagents), the SomaScan5K platform (N = 4979 reagents), and the Olink Explore (N = 1472 reagents) profiling techniques in 568 adults from the Jackson Heart Study and 219 participants in the HERITAGE Family Study across four performance domains: precision, accuracy, analytic breadth, and phenotypic associations leveraging detailed clinical phenotyping and genetic data. Across these studies, we show evidence supporting more reliable protein target specificity and a higher number of phenotypic associations for the Olink platform, while the Soma platforms benefit from greater measurement precision and analytic breadth across the proteome.
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Affiliation(s)
- Daniel H. Katz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Jeremy M. Robbins
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Shuliang Deng
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Usman A. Tahir
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | - Akhil Pampana
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Zhi Yu
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Debby Ngo
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Mark D. Benson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Zsu-Zsu Chen
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Daniel E. Cruz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Dongxiao Shen
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Yan Gao
- University of Mississippi Medical Center, Jackson, MS, USA
| | - Claude Bouchard
- Human Genomic Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Mark A. Sarzynski
- Department of Exercise Science, University of South Carolina, Columbia, SC, USA
| | - Adolfo Correa
- University of Mississippi Medical Center, Jackson, MS, USA
| | - Pradeep Natarajan
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - James G. Wilson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Robert E. Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
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3
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Quantitative proteome comparison of human hearts with those of model organisms. PLoS Biol 2021; 19:e3001144. [PMID: 33872299 PMCID: PMC8084454 DOI: 10.1371/journal.pbio.3001144] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 04/29/2021] [Accepted: 02/12/2021] [Indexed: 01/23/2023] Open
Abstract
Delineating human cardiac pathologies and their basic molecular mechanisms relies on research conducted in model organisms. Yet translating findings from preclinical models to humans present a significant challenge, in part due to differences in cardiac protein expression between humans and model organisms. Proteins immediately determine cellular function, yet their large-scale investigation in hearts has lagged behind those of genes and transcripts. Here, we set out to bridge this knowledge gap: By analyzing protein profiles in humans and commonly used model organisms across cardiac chambers, we determine their commonalities and regional differences. We analyzed cardiac tissue from each chamber of human, pig, horse, rat, mouse, and zebrafish in biological replicates. Using mass spectrometry–based proteomics workflows, we measured and evaluated the abundance of approximately 7,000 proteins in each species. The resulting knowledgebase of cardiac protein signatures is accessible through an online database: atlas.cardiacproteomics.com. Our combined analysis allows for quantitative evaluation of protein abundances across cardiac chambers, as well as comparisons of cardiac protein profiles across model organisms. Up to a quarter of proteins with differential abundances between atria and ventricles showed opposite chamber-specific enrichment between species; these included numerous proteins implicated in cardiac disease. The generated proteomics resource facilitates translational prospects of cardiac studies from model organisms to humans by comparisons of disease-linked protein networks across species. This study provides protein abundance profiles for thousands of proteins across cardiac chambers for humans and five commonly used model organisms. This quantitative proteomics dataset represents the most comprehensive such resource to date, and can be queried via a web browser to identify the most appropriate model organism for future studies.
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Chen Y, Wu T, Zhu Z, Huang H, Zhang L, Goel A, Yang M, Wang X. An integrated workflow for biomarker development using microRNAs in extracellular vesicles for cancer precision medicine. Semin Cancer Biol 2021; 74:134-155. [PMID: 33766650 DOI: 10.1016/j.semcancer.2021.03.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 03/13/2021] [Accepted: 03/16/2021] [Indexed: 02/06/2023]
Abstract
EV-miRNAs are microRNA (miRNA) molecules encapsulated in extracellular vesicles (EVs), which play crucial roles in tumor pathogenesis, progression, and metastasis. Recent studies about EV-miRNAs have gained novel insights into cancer biology and have demonstrated a great potential to develop novel liquid biopsy assays for various applications. Notably, compared to conventional liquid biomarkers, EV-miRNAs are more advantageous in representing host-cell molecular architecture and exhibiting higher stability and specificity. Despite various available techniques for EV-miRNA separation, concentration, profiling, and data analysis, a standardized approach for EV-miRNA biomarker development is yet lacking. In this review, we performed a substantial literature review and distilled an integrated workflow encompassing important steps for EV-miRNA biomarker development, including sample collection and EV isolation, EV-miRNA extraction and quantification, high-throughput data preprocessing, biomarker prioritization and model construction, functional analysis, as well as validation. With the rapid growth of "big data", we highlight the importance of efficient mining of high-throughput data for the discovery of EV-miRNA biomarkers and integrating multiple independent datasets for in silico and experimental validations to increase the robustness and reproducibility. Furthermore, as an efficient strategy in systems biology, network inference provides insights into the regulatory mechanisms and can be used to select functionally important EV-miRNAs to refine the biomarker candidates. Despite the encouraging development in the field, a number of challenges still hinder the clinical translation. We finally summarize several common challenges in various biomarker studies and discuss potential opportunities emerging in the related fields.
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Affiliation(s)
- Yu Chen
- Department of Biomedical Sciences, City University of Hong Kong, 31 To Yuen Street, Kowloon Tong, Hong Kong
| | - Tan Wu
- Department of Biomedical Sciences, City University of Hong Kong, 31 To Yuen Street, Kowloon Tong, Hong Kong
| | - Zhongxu Zhu
- Department of Biomedical Sciences, City University of Hong Kong, 31 To Yuen Street, Kowloon Tong, Hong Kong
| | - Hao Huang
- Department of Biomedical Sciences, City University of Hong Kong, 31 To Yuen Street, Kowloon Tong, Hong Kong
| | - Liang Zhang
- Department of Biomedical Sciences, City University of Hong Kong, 31 To Yuen Street, Kowloon Tong, Hong Kong; Tung Biomedical Sciences Centre, City University of Hong Kong, Hong Kong; Key Laboratory of Biochip Technology, Biotech and Health Centre, Shenzhen Research Institute, City University of Hong Kong, Shenzhen, Guangdong Province, China
| | - Ajay Goel
- Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Mengsu Yang
- Department of Biomedical Sciences, City University of Hong Kong, 31 To Yuen Street, Kowloon Tong, Hong Kong; Tung Biomedical Sciences Centre, City University of Hong Kong, Hong Kong; Key Laboratory of Biochip Technology, Biotech and Health Centre, Shenzhen Research Institute, City University of Hong Kong, Shenzhen, Guangdong Province, China
| | - Xin Wang
- Department of Biomedical Sciences, City University of Hong Kong, 31 To Yuen Street, Kowloon Tong, Hong Kong; Tung Biomedical Sciences Centre, City University of Hong Kong, Hong Kong; Key Laboratory of Biochip Technology, Biotech and Health Centre, Shenzhen Research Institute, City University of Hong Kong, Shenzhen, Guangdong Province, China.
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Barallobre-Barreiro J, Loeys B, Mayr M, Rienks M, Verstraeten A, Kovacic JC. Extracellular Matrix in Vascular Disease, Part 2/4: JACC Focus Seminar. J Am Coll Cardiol 2020; 75:2189-2203. [PMID: 32354385 DOI: 10.1016/j.jacc.2020.03.018] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Revised: 02/26/2020] [Accepted: 03/03/2020] [Indexed: 01/01/2023]
Abstract
Medium-sized and large arteries consist of 3 layers: the tunica intima, tunica media, and tunica adventitia. The tunica media accounts for the bulk of the vessel wall and is the chief determinant of mechanical compliance. It is primarily composed of circumferentially arranged layers of vascular smooth muscle cells that are separated by concentrically arranged elastic lamellae; a form of extracellular matrix (ECM). The tunica media is separated from the tunica intima and tunica adventitia, the innermost and outermost layers, respectively, by the internal and external elastic laminae. This second part of a 4-part JACC Focus Seminar discusses the contributions of the ECM to vascular homeostasis and pathology. Advances in genetics and proteomics approaches have fostered significant progress in our understanding of vascular ECM. This review highlights the important role of the ECM in vascular disease and the prospect of translating these discoveries into clinical disease biomarkers and potential future therapies.
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Affiliation(s)
| | - Bart Loeys
- Center for Medical Genetics, University of Antwerp/Antwerp University Hospital, Antwerp, Belgium; Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands.
| | - Manuel Mayr
- King's British Heart Foundation Centre, King's College London, London, United Kingdom; The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
| | - Marieke Rienks
- King's British Heart Foundation Centre, King's College London, London, United Kingdom
| | - Aline Verstraeten
- Center for Medical Genetics, University of Antwerp/Antwerp University Hospital, Antwerp, Belgium
| | - Jason C Kovacic
- The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Victor Chang Cardiac Research Institute, Darlinghurst, New South Wales, Australia; St. Vincent's Clinical School, University of New South Wales, Darlinghurst, New South Wales, Australia.
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6
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de Haan N, Wuhrer M, Ruhaak L. Mass spectrometry in clinical glycomics: The path from biomarker identification to clinical implementation. CLINICAL MASS SPECTROMETRY (DEL MAR, CALIF.) 2020; 18:1-12. [PMID: 34820521 PMCID: PMC8600986 DOI: 10.1016/j.clinms.2020.08.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Revised: 08/18/2020] [Accepted: 08/21/2020] [Indexed: 02/01/2023]
Abstract
Over the past decades, the genome and proteome have been widely explored for biomarker discovery and personalized medicine. However, there is still a large need for improved diagnostics and stratification strategies for a wide range of diseases. Post-translational modification of proteins by glycosylation affects protein structure and function, and glycosylation has been implicated in many prevalent human diseases. Numerous proteins for which the plasma levels are nowadays evaluated in clinical practice are glycoproteins. While the glycosylation of these proteins often changes with disease, their glycosylation status is largely ignored in the clinical setting. Hence, the implementation of glycomic markers in the clinic is still in its infancy. This is for a large part caused by the high complexity of protein glycosylation itself and of the analytical techniques required for their robust quantification. Mass spectrometry-based workflows are particularly suitable for the quantification of glycans and glycoproteins, but still require advances for their transformation from a biomedical research setting to a clinical laboratory. In this review, we describe why and how glycomics is expected to find its role in clinical tests and the status of current mass spectrometry-based methods for clinical glycomics.
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Affiliation(s)
- N. de Haan
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - M. Wuhrer
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - L.R. Ruhaak
- Department of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Center, Leiden, The Netherlands
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7
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Zhang S, Raedschelders K, Venkatraman V, Huang L, Holewinski R, Fu Q, Van Eyk JE. A Dual Workflow to Improve the Proteomic Coverage in Plasma Using Data-Independent Acquisition-MS. J Proteome Res 2020; 19:2828-2837. [PMID: 32176508 PMCID: PMC10360210 DOI: 10.1021/acs.jproteome.9b00607] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Plasma is one of the most important and common matrices for clinical chemistry and proteomic analyses. Data-independent acquisition (DIA) mass spectrometry has enabled the simultaneous quantitative analysis of hundreds of proteins in plasma samples in support population and disease studies. Depletion of the highest abundant proteins is a common tool to increase plasma proteome coverage, but this strategy can result in the nonspecific depletion of protein subsets with which proteins targeted for depletion interact, adversely affecting their analysis. Our work using an antibody-based depletion column revealed significant complementarity not only in the identification of the proteins derived from depleted and undepleted plasma, but importantly also in the extent to which different proteins can be reproducibly quantified in each fraction. We systematically defined four major quantitative parameters of increasing stringency in both the depleted plasma fraction and in undepleted plasma for 757 observed plasma proteins: Linearity cutoff r2 > 0.8; lower limit of quantification (LLOQ); measurement range; limit of detection (LOD). We applied the results of our study to build a web-based tool, PlasmaPilot, that can serve as a protocol decision tree to determine whether the analysis of a specific protein warrants IgY14 mediated depletion.
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Affiliation(s)
- Shenyan Zhang
- Advanced Clinical Biosystems Research Institute, Barbra Streisand Women’s Heart Center at the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
- BGI Genomics, Shenzhen 518083, China
| | - Koen Raedschelders
- Advanced Clinical Biosystems Research Institute, Barbra Streisand Women’s Heart Center at the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Vidya Venkatraman
- Advanced Clinical Biosystems Research Institute, Barbra Streisand Women’s Heart Center at the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Lilith Huang
- Advanced Clinical Biosystems Research Institute, Barbra Streisand Women’s Heart Center at the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Ronald Holewinski
- Advanced Clinical Biosystems Research Institute, Barbra Streisand Women’s Heart Center at the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Qin Fu
- Advanced Clinical Biosystems Research Institute, Barbra Streisand Women’s Heart Center at the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Jennifer E. Van Eyk
- Advanced Clinical Biosystems Research Institute, Barbra Streisand Women’s Heart Center at the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
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