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Ohata J. Friedel-Crafts reactions for biomolecular chemistry. Org Biomol Chem 2024; 22:3544-3558. [PMID: 38624091 DOI: 10.1039/d4ob00406j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
Abstract
Chemical tools and principles have become central to biological and medical research/applications by leveraging a range of classical organic chemistry reactions. Friedel-Crafts alkylation and acylation are arguably some of the most well-known and used synthetic methods for the preparation of small molecules but their use in biological and medical fields is relatively less frequent than the other reactions, possibly owing to the notion of their plausible incompatibility with biological systems. This review demonstrates advances in Friedel-Crafts alkylation and acylation reactions in a variety of biomolecular chemistry fields. With the discoveries and applications of numerous biomolecule-catalyzed or -assisted processes, these reactions have garnered considerable interest in biochemistry, enzymology, and biocatalysis. Despite the challenges of reactivity and selectivity of biomolecular reactions, the alkylation and acylation reactions demonstrated their utility for the construction and functionalization of all the four major biomolecules (i.e., nucleosides, carbohydrates/saccharides, lipids/fatty acids, and amino acids/peptides/proteins), and their diverse applications in biological, medical, and material fields are discussed. As the alkylation and acylation reactions are often fundamental educational components of organic chemistry courses, this review is intended for both experts and nonexperts by discussing their basic reaction patterns (with the depiction of each reaction mechanism in the ESI) and relevant real-world impacts in order to enrich chemical research and education. The significant growth of biomolecular Friedel-Crafts reactions described here is a testament to their broad importance and utility, and further development and investigations of the reactions will surely be the focus in the organic biomolecular chemistry fields.
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Affiliation(s)
- Jun Ohata
- Department of Chemistry, North Carolina State University, Raleigh, North Carolina 27695, USA.
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2
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Al-Daffaie FM, Al-Mudhafar SF, Alhomsi A, Tarazi H, Almehdi AM, El-Huneidi W, Abu-Gharbieh E, Bustanji Y, Alqudah MAY, Abuhelwa AY, Guella A, Alzoubi KH, Semreen MH. Metabolomics and Proteomics in Prostate Cancer Research: Overview, Analytical Techniques, Data Analysis, and Recent Clinical Applications. Int J Mol Sci 2024; 25:5071. [PMID: 38791108 PMCID: PMC11120916 DOI: 10.3390/ijms25105071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 04/26/2024] [Accepted: 04/26/2024] [Indexed: 05/26/2024] Open
Abstract
Prostate cancer (PCa) is a significant global contributor to mortality, predominantly affecting males aged 65 and above. The field of omics has recently gained traction due to its capacity to provide profound insights into the biochemical mechanisms underlying conditions like prostate cancer. This involves the identification and quantification of low-molecular-weight metabolites and proteins acting as crucial biochemical signals for early detection, therapy assessment, and target identification. A spectrum of analytical methods is employed to discern and measure these molecules, revealing their altered biological pathways within diseased contexts. Metabolomics and proteomics generate refined data subjected to detailed statistical analysis through sophisticated software, yielding substantive insights. This review aims to underscore the major contributions of multi-omics to PCa research, covering its core principles, its role in tumor biology characterization, biomarker discovery, prognostic studies, various analytical technologies such as mass spectrometry and Nuclear Magnetic Resonance, data processing, and recent clinical applications made possible by an integrative "omics" approach. This approach seeks to address the challenges associated with current PCa treatments. Hence, our research endeavors to demonstrate the valuable applications of these potent tools in investigations, offering significant potential for understanding the complex biochemical environment of prostate cancer and advancing tailored therapeutic approaches for further development.
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Affiliation(s)
- Fatima M. Al-Daffaie
- Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates; (F.M.A.-D.); (S.F.A.-M.); (A.A.); (H.T.); (A.M.A.)
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
| | - Sara F. Al-Mudhafar
- Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates; (F.M.A.-D.); (S.F.A.-M.); (A.A.); (H.T.); (A.M.A.)
| | - Aya Alhomsi
- Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates; (F.M.A.-D.); (S.F.A.-M.); (A.A.); (H.T.); (A.M.A.)
| | - Hamadeh Tarazi
- Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates; (F.M.A.-D.); (S.F.A.-M.); (A.A.); (H.T.); (A.M.A.)
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
| | - Ahmed M. Almehdi
- Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates; (F.M.A.-D.); (S.F.A.-M.); (A.A.); (H.T.); (A.M.A.)
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
| | - Waseem El-Huneidi
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
- Department of Basic Medical Sciences, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates;
| | - Eman Abu-Gharbieh
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
- Department of Clinical Sciences, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates
- School of Pharmacy, The University of Jordan, Amman 11942, Jordan
| | - Yasser Bustanji
- Department of Basic Medical Sciences, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates;
- School of Pharmacy, The University of Jordan, Amman 11942, Jordan
| | - Mohammad A. Y. Alqudah
- Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates;
- Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid 22110, Jordan
| | - Ahmad Y. Abuhelwa
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
- Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates;
| | - Adnane Guella
- Nephrology Department, University Hospital Sharjah, Sharjah 27272, United Arab Emirates;
| | - Karem H. Alzoubi
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
- Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates;
| | - Mohammad H. Semreen
- Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates; (F.M.A.-D.); (S.F.A.-M.); (A.A.); (H.T.); (A.M.A.)
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
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Ha A, Khoo A, Ignatchenko V, Khan S, Waas M, Vesprini D, Liu SK, Nyalwidhe JO, Semmes OJ, Boutros PC, Kislinger T. Comprehensive Prostate Fluid-Based Spectral Libraries for Enhanced Protein Detection in Urine. J Proteome Res 2024; 23:1768-1778. [PMID: 38580319 PMCID: PMC11077481 DOI: 10.1021/acs.jproteome.4c00009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 03/02/2024] [Accepted: 03/06/2024] [Indexed: 04/07/2024]
Abstract
Biofluids contain molecules in circulation and from nearby organs that can be indicative of disease states. Characterizing the proteome of biofluids with DIA-MS is an emerging area of interest for biomarker discovery; yet, there is limited consensus on DIA-MS data analysis approaches for analyzing large numbers of biofluids. To evaluate various DIA-MS workflows, we collected urine from a clinically heterogeneous cohort of prostate cancer patients and acquired data in DDA and DIA scan modes. We then searched the DIA data against urine spectral libraries generated using common library generation approaches or a library-free method. We show that DIA-MS doubles the sample throughput compared to standard DDA-MS with minimal losses to peptide detection. We further demonstrate that using a sample-specific spectral library generated from individual urines maximizes peptide detection compared to a library-free approach, a pan-human library, or libraries generated from pooled, fractionated urines. Adding urine subproteomes, such as the urinary extracellular vesicular proteome, to the urine spectral library further improves the detection of prostate proteins in unfractionated urine. Altogether, we present an optimized DIA-MS workflow and provide several high-quality, comprehensive prostate cancer urine spectral libraries that can streamline future biomarker discovery studies of prostate cancer using DIA-MS.
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Affiliation(s)
- Annie Ha
- Department
of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Amanda Khoo
- Department
of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Vladimir Ignatchenko
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Shahbaz Khan
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Matthew Waas
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Danny Vesprini
- Department
of Radiation Oncology, University of Toronto, Toronto, Ontario M5T 1P5, Canada
- Odette
Cancer Research Program, Sunnybrook Research
Institute, Toronto, Ontario M4N 3M5, Canada
| | - Stanley K. Liu
- Department
of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
- Department
of Radiation Oncology, University of Toronto, Toronto, Ontario M5T 1P5, Canada
- Odette
Cancer Research Program, Sunnybrook Research
Institute, Toronto, Ontario M4N 3M5, Canada
| | - Julius O. Nyalwidhe
- Leroy
T. Canoles Jr. Cancer Research Center, Eastern
Virginia Medical School, Norfolk, Virginia 23501, United States
- Department
of Microbiology and Molecular Cell Biology, Eastern Virginia Medical School, Norfolk, Virginia 23501, United States
| | - Oliver John Semmes
- Leroy
T. Canoles Jr. Cancer Research Center, Eastern
Virginia Medical School, Norfolk, Virginia 23501, United States
- Department
of Microbiology and Molecular Cell Biology, Eastern Virginia Medical School, Norfolk, Virginia 23501, United States
| | - Paul C. Boutros
- Department
of Human Genetics, University of California,
Los Angeles, Los Angeles, California 90095, United States
- Department
of Urology, University of California, Los
Angeles, Los Angeles, California 90095, United States
- Institute
for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90095, United States
- Eli
and Edythe Broad Stem Cell Research Center, University of California, Los
Angeles, California 90095, United States
- Broad
Stem Cell Research Center, University of
California, Los Angeles, California 90095, United States
- Jonsson
Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90024, United States
- Department
of Human Genetics, University of California,
Los Angeles, Los Angeles, California 90095, United States
| | - Thomas Kislinger
- Department
of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
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Malinowski N, Morgan MJ, Wylie J, Walsh T, Domingos S, Metcalfe S, Kaksonen AH, Barnhart EP, Mueller R, Peyton BM, Puzon GJ. Prokaryotic microbial ecology as an ecosurveillance tool for eukaryotic pathogen colonisation: Meiothermus and Naegleria fowleri. WATER RESEARCH 2024; 254:121426. [PMID: 38471203 DOI: 10.1016/j.watres.2024.121426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 02/21/2024] [Accepted: 03/04/2024] [Indexed: 03/14/2024]
Abstract
Naegleria fowleri has been detected in drinking water distribution systems (DWDS) in Australia, Pakistan and the United States and is the causative agent of the highly fatal disease primary amoebic meningoencephalitis. Previous small scale field studies have shown that Meiothermus may be a potential biomarker for N. fowleri. However, correlations between predictive biomarkers in small sample sizes often breakdown when applied to larger more representative datasets. This study represents one of the largest and most rigorous temporal investigations of Naegleria fowleri colonisation in an operational DWDS in the world and measured the association of Meiothermus and N. fowleri over a significantly larger space and time in the DWDS. A total of 232 samples were collected from five sites over three-years (2016-2018), which contained 29 positive N. fowleri samples. Two specific operational taxonomic units assigned to M. chliarophilus and M. hypogaeus, were significantly associated with N. fowleri presence. Furthermore, inoculation experiments demonstrated that Meiothermus was required to support N. fowleri growth in field-collected biofilms. This validates Meiothermus as prospective biological tool to aid in the identification and surveillance of N. fowleri colonisable sites.
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Affiliation(s)
- Natalia Malinowski
- CSIRO Environment, Floreat Park, WA, Australia; Water Corporation of Western Australia, Leederville, WA, Australia
| | | | - Jason Wylie
- CSIRO Environment, Floreat Park, WA, Australia
| | - Tom Walsh
- CSIRO Environment, Canberra, ACT, Australia
| | - Sergio Domingos
- Water Corporation of Western Australia, Leederville, WA, Australia
| | | | | | - Elliott P Barnhart
- U.S. Geological Survey, Wyoming-Montana Water Science Center, Helena, Montana (MT), USA
| | - Rebecca Mueller
- Centre for Biofilm Engineering, and Thermal Biology Institute, Montana State University, Bozeman, MT, USA
| | - Brent M Peyton
- Centre for Biofilm Engineering, and Thermal Biology Institute, Montana State University, Bozeman, MT, USA
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Sakarin S, Rungsipipat A, Roytrakul S, Jaresitthikunchai J, Phaonakrop N, Charoenlappanit S, Thaisakun S, Surachetpong S. Phosphoproteomics analysis of serum from dogs affected with pulmonary hypertension secondary to degenerative mitral valve disease. PeerJ 2024; 12:e17186. [PMID: 38708342 PMCID: PMC11067895 DOI: 10.7717/peerj.17186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 03/11/2024] [Indexed: 05/07/2024] Open
Abstract
Pulmonary hypertension (PH), a common complication in dogs affected by degenerative mitral valve disease (DMVD), is a progressive disorder characterized by increased pulmonary arterial pressure (PAP) and pulmonary vascular remodeling. Phosphorylation of proteins, impacting vascular function and cell proliferation, might play a role in the development and progression of PH. Unlike gene or protein studies, phosphoproteomic focuses on active proteins that function as end-target proteins within signaling cascades. Studying phosphorylated proteins can reveal active contributors to PH development. Early diagnosis of PH is crucial for effective management and improved clinical outcomes. This study aimed to identify potential serum biomarkers for diagnosing PH in dogs affected with DMVD using a phosphoproteomic approach. Serum samples were collected from healthy control dogs (n = 28), dogs with DMVD (n = 24), and dogs with DMVD and PH (n = 29). Phosphoproteins were enriched from the serum samples and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Data analysis was performed to identify uniquely expressed phosphoproteins in each group and differentially expressed phosphoproteins among groups. Phosphoproteomic analysis revealed nine uniquely expressed phosphoproteins in the serum of dogs in the DMVD+PH group and 15 differentially upregulated phosphoproteins in the DMVD+PH group compared to the DMVD group. The phosphoproteins previously implicated in PH and associated with pulmonary arterial remodeling, including small nuclear ribonucleoprotein G (SNRPG), alpha-2-macroglobulin (A2M), zinc finger and BTB domain containing 42 (ZBTB42), hemopexin (HPX), serotransferrin (TRF) and complement C3 (C3), were focused on. Their unique expression and differential upregulation in the serum of DMVD dogs with PH suggest their potential as biomarkers for PH diagnosis. In conclusion, this phosphoproteomic study identified uniquely expressed and differentially upregulated phosphoproteins in the serum of DMVD dogs with PH. Further studies are warranted to validate the diagnostic utility of these phosphoproteins.
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Affiliation(s)
- Siriwan Sakarin
- Department of Veterinary Medicine, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, Thailand, Bangkok, Thailand
| | - Anudep Rungsipipat
- Center of Excellence for Companion Animal Cancer, Department of Pathology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, Thailand, Bangkok, Thailand
| | - Sittiruk Roytrakul
- Functional Proteomics Technology Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency, Pathum Thani, Thailand, Bangkok, Thailand
| | - Janthima Jaresitthikunchai
- Functional Proteomics Technology Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency, Pathum Thani, Thailand, Bangkok, Thailand
| | - Narumon Phaonakrop
- Functional Proteomics Technology Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency, Pathum Thani, Thailand, Bangkok, Thailand
| | - Sawanya Charoenlappanit
- Functional Proteomics Technology Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency, Pathum Thani, Thailand, Bangkok, Thailand
| | - Siriwan Thaisakun
- Functional Proteomics Technology Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency, Pathum Thani, Thailand, Bangkok, Thailand
| | - Sirilak Surachetpong
- Department of Veterinary Medicine, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, Thailand, Bangkok, Thailand
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Pérez Compte D, Etourneau L, Hesse AM, Kraut A, Barthelon J, Sturm N, Borges H, Biennier S, Courçon M, de Saint Loup M, Mignot V, Costentin C, Burger T, Couté Y, Bruley C, Decaens T, Jaquinod M, Boursier J, Brun V. Plasma ALS and Gal-3BP differentiate early from advanced liver fibrosis in MASLD patients. Biomark Res 2024; 12:44. [PMID: 38679739 PMCID: PMC11057169 DOI: 10.1186/s40364-024-00583-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 03/19/2024] [Indexed: 05/01/2024] Open
Abstract
BACKGROUND Metabolic dysfunction-associated steatotic liver disease (MASLD) is estimated to affect 30% of the world's population, and its prevalence is increasing in line with obesity. Liver fibrosis is closely related to mortality, making it the most important clinical parameter for MASLD. It is currently assessed by liver biopsy - an invasive procedure that has some limitations. There is thus an urgent need for a reliable non-invasive means to diagnose earlier MASLD stages. METHODS A discovery study was performed on 158 plasma samples from histologically-characterised MASLD patients using mass spectrometry (MS)-based quantitative proteomics. Differentially abundant proteins were selected for verification by ELISA in the same cohort. They were subsequently validated in an independent MASLD cohort (n = 200). RESULTS From the 72 proteins differentially abundant between patients with early (F0-2) and advanced fibrosis (F3-4), we selected Insulin-like growth factor-binding protein complex acid labile subunit (ALS) and Galectin-3-binding protein (Gal-3BP) for further study. In our validation cohort, AUROCs with 95% CIs of 0.744 [0.673 - 0.816] and 0.735 [0.661 - 0.81] were obtained for ALS and Gal-3BP, respectively. Combining ALS and Gal-3BP improved the assessment of advanced liver fibrosis, giving an AUROC of 0.796 [0.731. 0.862]. The {ALS; Gal-3BP} model surpassed classic fibrosis panels in predicting advanced liver fibrosis. CONCLUSIONS Further investigations with complementary cohorts will be needed to confirm the usefulness of ALS and Gal-3BP individually and in combination with other biomarkers for diagnosis of liver fibrosis. With the availability of ELISA assays, these findings could be rapidly clinically translated, providing direct benefits for patients.
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Affiliation(s)
- David Pérez Compte
- Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, FR2048 ProFI, EDyP team, 17 Avenue des Martyrs, 38000, Grenoble, France
| | - Lucas Etourneau
- Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, FR2048 ProFI, EDyP team, 17 Avenue des Martyrs, 38000, Grenoble, France
- Université Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000, Grenoble, France
| | - Anne-Marie Hesse
- Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, FR2048 ProFI, EDyP team, 17 Avenue des Martyrs, 38000, Grenoble, France
| | - Alexandra Kraut
- Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, FR2048 ProFI, EDyP team, 17 Avenue des Martyrs, 38000, Grenoble, France
| | - Justine Barthelon
- Université Grenoble Alpes, Clinique Universitaire d'Hépato-Gastroentérologie, CHU Grenoble Alpes, 38000, Grenoble, France
| | - Nathalie Sturm
- Université Grenoble Alpes, Clinique Universitaire d'Hépato-Gastroentérologie, CHU Grenoble Alpes, 38000, Grenoble, France
| | - Hélène Borges
- Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, FR2048 ProFI, EDyP team, 17 Avenue des Martyrs, 38000, Grenoble, France
| | - Salomé Biennier
- Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, FR2048 ProFI, EDyP team, 17 Avenue des Martyrs, 38000, Grenoble, France
| | - Marie Courçon
- Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, FR2048 ProFI, EDyP team, 17 Avenue des Martyrs, 38000, Grenoble, France
| | - Marc de Saint Loup
- Hepato-Gastroenterology Department, University Hospital, Angers, France
- HIFIH Laboratory, UPRES 3859, SFR 4208, LUNAM University, Angers, France
| | - Victoria Mignot
- Université Grenoble Alpes, Clinique Universitaire d'Hépato-Gastroentérologie, CHU Grenoble Alpes, 38000, Grenoble, France
- Univ. Grenoble Alpes, Institute for Advanced Biosciences-INSERM U1209/ CNRS UMR 5309, Grenoble, France
| | - Charlotte Costentin
- Université Grenoble Alpes, Clinique Universitaire d'Hépato-Gastroentérologie, CHU Grenoble Alpes, 38000, Grenoble, France
- Univ. Grenoble Alpes, Institute for Advanced Biosciences-INSERM U1209/ CNRS UMR 5309, Grenoble, France
| | - Thomas Burger
- Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, FR2048 ProFI, EDyP team, 17 Avenue des Martyrs, 38000, Grenoble, France
| | - Yohann Couté
- Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, FR2048 ProFI, EDyP team, 17 Avenue des Martyrs, 38000, Grenoble, France
| | - Christophe Bruley
- Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, FR2048 ProFI, EDyP team, 17 Avenue des Martyrs, 38000, Grenoble, France
| | - Thomas Decaens
- Université Grenoble Alpes, Clinique Universitaire d'Hépato-Gastroentérologie, CHU Grenoble Alpes, 38000, Grenoble, France
- Univ. Grenoble Alpes, Institute for Advanced Biosciences-INSERM U1209/ CNRS UMR 5309, Grenoble, France
| | - Michel Jaquinod
- Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, FR2048 ProFI, EDyP team, 17 Avenue des Martyrs, 38000, Grenoble, France.
| | - Jérôme Boursier
- Hepato-Gastroenterology Department, University Hospital, Angers, France
- HIFIH Laboratory, UPRES 3859, SFR 4208, LUNAM University, Angers, France
| | - Virginie Brun
- Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, FR2048 ProFI, EDyP team, 17 Avenue des Martyrs, 38000, Grenoble, France.
- Univ. Grenoble Alpes, CEA, Leti, 38000, Grenoble, France.
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Torkamannejad S, Chang G, Aroge FA, Sun B. Single Isotopologue for In-Sample Calibration and Absolute Quantitation by LC-MS/MS. J Proteome Res 2024; 23:1351-1359. [PMID: 38445850 DOI: 10.1021/acs.jproteome.3c00848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2024]
Abstract
Targeted mass spectrometry (MS)-based absolute quantitative analysis has been increasingly used in biomarker discovery. The ability to accurately measure the masses by MS enabled the use of isotope-incorporated surrogates having virtually identical physiochemical properties with the target analytes as calibrators. Such a unique capacity allowed for accurate in-sample calibration. Current in-sample calibration uses multiple isotopologues or structural analogues for both the surrogate and the internal standard. Here, we simplified this common practice by using endogenous light peptides as the internal standards and used a mathematical deduction of "heavy matching light, HML" to directly quantify an endogenous analyte. This method provides all necessary assay performance parameters in the authentic matrix, including the lower limit of quantitation (LLOQ) and intercept of the calibration curve, by using only a single isotopologue of the analyte. This method can be applied to the quantitation of proteins, peptides, and small molecules. Using this method, we quantified the efficiency of heart tissue digestion and recovery using sodium deoxycholate as a detergent and two spiked exogenous proteins as mimics of heart proteins. The results demonstrated the robustness of the assay.
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Affiliation(s)
- Soroush Torkamannejad
- Department of Chemistry, Simon Fraser University, Burnaby, British Columbia V5A1S6, Canada
| | - Ge Chang
- Department of Chemistry, Simon Fraser University, Burnaby, British Columbia V5A1S6, Canada
| | - Fabusuyi A Aroge
- School of Mechatronic Systems Engineering, Simon Fraser University, Surrey, British Columbia V3T0A3, Canada
| | - Bingyun Sun
- Department of Chemistry, Simon Fraser University, Burnaby, British Columbia V5A1S6, Canada
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia V5A1S6, Canada
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8
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Bhardwaj S, Bulluss M, D'Aubeterre A, Derakhshani A, Penner R, Mahajan M, Mahajan VB, Dufour A. Integrating the analysis of human biopsies using post-translational modifications proteomics. Protein Sci 2024; 33:e4979. [PMID: 38533548 DOI: 10.1002/pro.4979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 03/07/2024] [Accepted: 03/16/2024] [Indexed: 03/28/2024]
Abstract
Proteome diversities and their biological functions are significantly amplified by post-translational modifications (PTMs) of proteins. Shotgun proteomics, which does not typically survey PTMs, provides an incomplete picture of the complexity of human biopsies in health and disease. Recent advances in mass spectrometry-based proteomic techniques that enrich and study PTMs are helping to uncover molecular detail from the cellular level to system-wide functions, including how the microbiome impacts human diseases. Protein heterogeneity and disease complexity are challenging factors that make it difficult to characterize and treat disease. The search for clinical biomarkers to characterize disease mechanisms and complexity related to patient diagnoses and treatment has proven challenging. Knowledge of PTMs is fundamentally lacking. Characterization of complex human samples that clarify the role of PTMs and the microbiome in human diseases will result in new discoveries. This review highlights the key role of proteomic techniques used to characterize unknown biological functions of PTMs derived from complex human biopsies. Through the integration of diverse methods used to profile PTMs, this review explores the genetic regulation of proteoforms, cells of origin expressing specific proteins, and several bioactive PTMs and their subsequent analyses by liquid chromatography and tandem mass spectrometry.
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Affiliation(s)
- Sonali Bhardwaj
- Department of Physiology and Pharmacology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- McCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Mitchell Bulluss
- Department of Physiology and Pharmacology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- McCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Ana D'Aubeterre
- Department of Physiology and Pharmacology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- McCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Afshin Derakhshani
- Department of Physiology and Pharmacology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- McCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Regan Penner
- Department of Physiology and Pharmacology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- McCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - MaryAnn Mahajan
- Molecular Surgery Laboratory, Stanford University, Palo Alto, California, USA
| | - Vinit B Mahajan
- Molecular Surgery Laboratory, Stanford University, Palo Alto, California, USA
- Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, California, USA
| | - Antoine Dufour
- Department of Physiology and Pharmacology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- McCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
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9
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Sakarin S, Rungsipipat A, Roytrakul S, Jaresitthikunchai J, Phaonakrop N, Charoenlappanit S, Thaisakun S, Surachetpong SD. Proteomic analysis of the serum in dogs with pulmonary hypertension secondary to myxomatous mitral valve disease: the preliminary study. Front Vet Sci 2024; 11:1327453. [PMID: 38596466 PMCID: PMC11002142 DOI: 10.3389/fvets.2024.1327453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 03/01/2024] [Indexed: 04/11/2024] Open
Abstract
Background Pulmonary hypertension (PH) is a common complication in dogs with myxomatous mitral valve disease (MMVD), characterized by elevated blood pressure in pulmonary artery. Echocardiography is a reliable technique for PH diagnosis in veterinary medicine. However, it is limited to use as an early detection method. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has found extensive application in the discovery of serum protein biomarkers for various diseases. The objective of this study was to identify serum proteins in healthy control dogs and MMVD dogs both with and without PH using LC-MS/MS. Materials and methods In this research, a total of 81 small-breed dogs participated, and they were categorized into three groups: the control (n = 28), MMVD (n = 24) and MMVD+PH (n = 29) groups. Serum samples were collected and analyzed by LC-MS/MS. Results Differentially expressed proteins were identified, and the upregulated and downregulated proteins in MMVD+PH group including Myomesin 1 (MYOM1) and Histone deacetylase 7 (HDAC7), Pleckstrin homology domain containing M3 (PLEKHM3), Diacylglycerol lipase alpha (DAGLA) and Tubulin tyrosine ligase like 6 (TTLL6) were selected as proteins of interest in MMVD dogs with PH. Conclusion Different types of proteins have been identified in healthy dogs and MMVD dogs with and without PH. Additional studies are needed to investigate the potential of these proteins as biomarkers for PH in dogs with MMVD.
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Affiliation(s)
- Siriwan Sakarin
- Faculty of Veterinary Science, Department of Veterinary Medicine, Center of Excellence for Companion Animal Cancer, Chulalongkorn University, Bangkok, Thailand
| | - Anudep Rungsipipat
- Faculty of Veterinary Science, Department of Pathology, Chulalongkorn University, Bangkok, Thailand
| | - Sittiruk Roytrakul
- Functional Proteomics Technology Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Janthima Jaresitthikunchai
- Functional Proteomics Technology Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Narumon Phaonakrop
- Functional Proteomics Technology Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Sawanya Charoenlappanit
- Functional Proteomics Technology Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Siriwan Thaisakun
- Functional Proteomics Technology Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Sirilak Disatian Surachetpong
- Faculty of Veterinary Science, Department of Veterinary Medicine, Center of Excellence for Companion Animal Cancer, Chulalongkorn University, Bangkok, Thailand
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10
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Fu Q, Vegesna M, Sundararaman N, Damoc E, Arrey TN, Pashkova A, Mengesha E, Debbas P, Joung S, Li D, Cheng S, Braun J, McGovern DPB, Murray C, Xuan Y, Eyk JEV. Paradigm shift in biomarker translation: a pipeline to generate clinical grade biomarker candidates from DIA-MS discovery. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.20.586018. [PMID: 38562888 PMCID: PMC10983901 DOI: 10.1101/2024.03.20.586018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package. This innovative tool uses the discovery cohort analysis to select precursors, peptides, and proteins that adhere to established targeted assay criteria. TEAQ was applied to Data-Independent Acquisition MS data from plasma samples acquired on an Orbitrap™ Astral™ MS. Identified precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation from 11-point loading curves under three throughputs, to develop a resource for clinical-grade targeted assays. From a clinical cohort of individuals with inflammatory bowel disease (n=492), TEAQ successfully identified 1116 signature peptides for 327 quantifiable proteins from 1180 identified proteins. Embedding stringent selection criteria adaptable to targeted assay development into the analysis of discovery data will streamline the transition to validation and clinical studies.
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11
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Ye X, Yang J, Hu C, Dong J, Tang H, Zhou B, Wen B, Xiao Z, Zhu M, Cai J, Zhou J. Multi-biomarker combination detection system for diagnosis and classification of dry eye disease by imaging of a multi-channel metasurface. Biosens Bioelectron 2024; 248:115933. [PMID: 38171220 DOI: 10.1016/j.bios.2023.115933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 11/30/2023] [Accepted: 12/13/2023] [Indexed: 01/05/2024]
Abstract
Dry eye disease (DED) is one of the most common ocular surface diseases, characterized by unstable tear film and ocular inflammation, affecting hundreds of millions of people worldwide. Currently, the clinical diagnosis of DED mainly relies on physical methods such as optical microscopy and ocular surface interferometric imaging, but classifying DED is still difficult. Here, we propose a compact and portable immune detection system based on the direct imaging of a nanophotonic metasurface with gradient geometry, for fast and ultra-sensitive detection of multiple biomarkers (i.e. Matrix metalloproteinase-9 (MMP-9), Lipocalin-1 (LCN-1), Lactoferrin (LTF)) in tears for the diagnosis and classification of DED. This centimeter-scale concentric nanophotonic metasurface, which consists of millions of unique metallic nanostructures, was fabricated through a cost-effective nanoimprint lithography (NIL) process. The immune detection system based on the antibody-modified metasurface shows favorable detection selectivity, an ultra-high sensitivity (3350 pixels/Refractive Index Unit (RIU)) and low limit of detection (LOD) (0.3 ng/mL for MMP-9, 1 ng/mL for LTF, and 0.5 ng/mL for LCN-1). Further clinical sampling and detection results demonstrated that this multi-biomarker detection system enabled accurate determination and symptom classification of DED, manifesting high correlation and consistency with clinical diagnosis results. The advantages such as low sample consumption, one-step detection, simple operation, and simultaneous detection of multiple biomarkers make the platform promising for screening and detecting a broader range of biomarker combinations in clinical practice.
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Affiliation(s)
- Xiangyi Ye
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, PR China; Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, PR China
| | - Ji Yang
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, PR China; Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, PR China
| | - Chao Hu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, PR China; Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, PR China
| | - Jianpei Dong
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, PR China; Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, PR China
| | - Hao Tang
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, PR China; Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, PR China
| | - Bin Zhou
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, PR China; Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, PR China
| | - Baohua Wen
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, PR China; Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, PR China
| | - Zihan Xiao
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, PR China; Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, PR China
| | - Minyi Zhu
- Department of Ophthalmology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, 518107, PR China
| | - Jingxuan Cai
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, PR China; Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, PR China.
| | - Jianhua Zhou
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, PR China; Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, PR China.
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12
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Hamza GM, Raghunathan R, Ashenden S, Zhang B, Miele E, Jarnuczak AF. Proteomics of prostate cancer serum and plasma using low and high throughput approaches. Clin Proteomics 2024; 21:21. [PMID: 38475692 DOI: 10.1186/s12014-024-09461-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 02/12/2024] [Indexed: 03/14/2024] Open
Abstract
Despite progress, MS-based proteomics in biofluids, especially blood, faces challenges such as dynamic range and throughput limitations in biomarker and disease studies. In this work, we used cutting-edge proteomics technologies to construct label-based and label-free workflows, capable of quantifying approximately 2,000 proteins in biofluids. With 70µL of blood and a single depletion strategy, we conducted an analysis of a homogenous cohort (n = 32), comparing medium-grade prostate cancer patients (Gleason score: 7(3 + 4); TNM stage: T2cN0M0, stage IIB) to healthy donors. The results revealed dozens of differentially expressed proteins in both plasma and serum. We identified the upregulation of Prostate Specific Antigen (PSA), a well-known biomarker for prostate cancer, in the serum of cancer cohort. Further bioinformatics analysis highlighted noteworthy proteins which appear to be differentially secreted into the bloodstream, making them good candidates for further exploration.
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Affiliation(s)
| | - Rekha Raghunathan
- Bioanalytical and Biomarker, Prevail Therapeutics, Wholly Owned Subsidiary of Eli Lilly and Company, New York, NY, 10016, USA
| | | | - Bairu Zhang
- Discovery Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Eric Miele
- Discovery Sciences, R&D, AstraZeneca, Cambridge, UK.
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13
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Veth TS, Kannegieter NM, de Graaf EL, Ruijtenbeek R, Joore J, Ressa A, Altelaar M. Innovative strategies for measuring kinase activity to accelerate the next wave of novel kinase inhibitors. Drug Discov Today 2024; 29:103907. [PMID: 38301799 DOI: 10.1016/j.drudis.2024.103907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 01/18/2024] [Accepted: 01/25/2024] [Indexed: 02/03/2024]
Abstract
The development of protein kinase inhibitors (PKIs) has gained significance owing to their therapeutic potential for diseases like cancer. In addition, there has been a rise in refining kinase activity assays, each possessing unique biological and analytical characteristics crucial for PKI development. However, the PKI development pipeline experiences high attrition rates and approved PKIs exhibit unexploited potential because of variable patient responses. Enhancing PKI development efficiency involves addressing challenges related to understanding the PKI mechanism of action and employing biomarkers for precision medicine. Selecting appropriate kinase activity assays for these challenges can overcome these attrition rate issues. This review delves into the current obstacles in kinase inhibitor development and elucidates kinase activity assays that can provide solutions.
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Affiliation(s)
- Tim S Veth
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Padualaan 8, Utrecht 3584 CH, The Netherlands; Netherlands Proteomics Center, Padualaan 8, Utrecht 3584 CH, The Netherlands
| | | | - Erik L de Graaf
- Pepscope, Nieuwe Kanaal 7, 6709 PA Wageningen, The Netherlands
| | | | - Jos Joore
- Pepscope, Nieuwe Kanaal 7, 6709 PA Wageningen, The Netherlands
| | - Anna Ressa
- Pepscope, Nieuwe Kanaal 7, 6709 PA Wageningen, The Netherlands
| | - Maarten Altelaar
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Padualaan 8, Utrecht 3584 CH, The Netherlands; Netherlands Proteomics Center, Padualaan 8, Utrecht 3584 CH, The Netherlands.
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14
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Lu C, Yang F, He S, Yu H, Wang Q, Li M, Zeng X, Leng X. Serum proteome analysis identifies a potential biomarker for axial psoriatic arthritis. Eur J Med Res 2024; 29:146. [PMID: 38429803 PMCID: PMC10908212 DOI: 10.1186/s40001-024-01731-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 02/14/2024] [Indexed: 03/03/2024] Open
Abstract
BACKGROUND To identify potential serum biomarkers for differentiating between axial psoriatic arthritis (axPsA) and peripheral psoriatic arthritis (pPsA). METHODS Serum samples were collected from patients with PsA to create a biomarker discovery cohort and a verification cohort. Patients with PsA were classified into axial or peripheral subtypes based on imaging criteria. Untargeted proteomics technology was used in the discovery phase to screen for biomarkers, and candidate biomarkers were evaluated using enzyme-linked immunosorbent assay (ELISA) in the verification phase. RESULTS We identified 45 significantly differentially expressed proteins (DEPs) between axPsA (n = 20) and pPsA (n = 20) with liquid chromatography-mass spectrometry. Among these DEPs, serum pigment epithelium-derived factor (PEDF) was identified as a candidate biomarker using the Boruta algorithm and lasso regression. Results of ELISA further confirmed that the level of serum PEDF expression was significantly higher in axPsA (n = 37) than in pPsA (n = 51) at the verification cohort (37.9 ± 10.1 vs. 30.5 ± 8.9 μg/mL, p < 0.001). Receiver operating characteristics analysis showed that PEDF had an area under the curve (AUC) of 0.72. Serum PEDF was positively correlated with body mass index and C-reactive protein. Additionally, there was a tendency towards a positive correlation between PEDF and the Bath Ankylosing Spondylitis Disease Activity Index. CONCLUSIONS This study provided a comprehensive characterization of the proteome in axPsA and pPsA and identified a candidate biomarker, PEDF, that may contribute to early diagnosis for axPsA.
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Affiliation(s)
- Chaofan Lu
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, No1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China
| | - Fan Yang
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, No1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China
| | - Shihao He
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, No1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China
| | - Hongxia Yu
- Department of Rheumatology, Guizhou Xingyi People's Hospital, Xingyi, China
| | - Qian Wang
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, No1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China
| | - Mengtao Li
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, No1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China
| | - Xiaofeng Zeng
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, No1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China.
| | - Xiaomei Leng
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, No1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China.
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15
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Vitko D, Chou WF, Nouri Golmaei S, Lee JY, Belthangady C, Blume J, Chan JK, Flores-Campuzano G, Hu Y, Liu M, Marispini MA, Mora MG, Ramaswamy S, Ranjan P, Williams PB, Zawada RJX, Ma P, Wilcox BE. timsTOF HT Improves Protein Identification and Quantitative Reproducibility for Deep Unbiased Plasma Protein Biomarker Discovery. J Proteome Res 2024; 23:929-938. [PMID: 38225219 PMCID: PMC10913052 DOI: 10.1021/acs.jproteome.3c00646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 12/15/2023] [Accepted: 12/21/2023] [Indexed: 01/17/2024]
Abstract
Mass spectrometry (MS) is a valuable tool for plasma proteome profiling and disease biomarker discovery. However, wide-ranging plasma protein concentrations, along with technical and biological variabilities, present significant challenges for deep and reproducible protein quantitation. Here, we evaluated the qualitative and quantitative performance of timsTOF HT and timsTOF Pro 2 mass spectrometers for analysis of neat plasma samples (unfractionated) and plasma samples processed using the Proteograph Product Suite (Proteograph) that enables robust deep proteomics sampling prior to mass spectrometry. Samples were evaluated across a wide range of peptide loading masses and liquid chromatography (LC) gradients. We observed up to a 76% increase in total plasma peptide precursors identified and a >2-fold boost in quantifiable plasma peptide precursors (CV < 20%) with timsTOF HT compared to Pro 2. Additionally, approximately 4.5 fold more plasma peptide precursors were detected by both timsTOF HT and timsTOF Pro 2 in the Proteograph analyzed plasma vs neat plasma. In an exploratory analysis of 20 late-stage lung cancer and 20 control plasma samples with the Proteograph, which were expected to exhibit distinct proteomes, an approximate 50% increase in total and statistically significant plasma peptide precursors (q < 0.05) was observed with timsTOF HT compared to Pro 2. Our data demonstrate the superior performance of timsTOF HT for identifying and quantifying differences between biologically diverse samples, allowing for improved disease biomarker discovery in large cohort studies. Moreover, researchers can leverage data sets from this study to optimize their liquid chromatography-mass spectrometry (LC-MS) workflows for plasma protein profiling and biomarker discovery. (ProteomeXchange identifier: PXD047854 and PXD047839).
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Affiliation(s)
- Dijana Vitko
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - Wan-Fang Chou
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - Sara Nouri Golmaei
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - Joon-Yong Lee
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - Chinmay Belthangady
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - John Blume
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - Jessica K. Chan
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | | | - Yuntao Hu
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - Manway Liu
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - Mark A. Marispini
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - Megan G. Mora
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - Saividya Ramaswamy
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - Purva Ranjan
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - Preston B. Williams
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - Robert J. X. Zawada
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - Philip Ma
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
| | - Bruce E. Wilcox
- PrognomiQ Inc., 1900 Alameda de las Pulgas, San Mateo, California 94403, United States
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16
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Webb-Robertson BJM, Nakayasu ES, Dong F, Waugh KC, Flores JE, Bramer LM, Schepmoes AA, Gao Y, Fillmore TL, Onengut-Gumuscu S, Frazer-Abel A, Rich SS, Holers VM, Metz TO, Rewers MJ. Decrease in multiple complement proteins associated with development of islet autoimmunity and type 1 diabetes. iScience 2024; 27:108769. [PMID: 38303689 PMCID: PMC10831269 DOI: 10.1016/j.isci.2023.108769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 10/16/2023] [Accepted: 12/18/2023] [Indexed: 02/03/2024] Open
Abstract
Type 1 diabetes (T1D) is a chronic condition caused by autoimmune destruction of the insulin-producing pancreatic β cells. While it is known that gene-environment interactions play a key role in triggering the autoimmune process leading to T1D, the pathogenic mechanism leading to the appearance of islet autoantibodies-biomarkers of autoimmunity-is poorly understood. Here we show that disruption of the complement system precedes the detection of islet autoantibodies and persists through disease onset. Our results suggest that children who exhibit islet autoimmunity and progress to clinical T1D have lower complement protein levels relative to those who do not progress within a similar time frame. Thus, the complement pathway, an understudied mechanistic and therapeutic target in T1D, merits increased attention for use as protein biomarkers of prediction and potentially prevention of T1D.
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Affiliation(s)
- Bobbie-Jo M. Webb-Robertson
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
- Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL, USA
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Ernesto S. Nakayasu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Fran Dong
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Kathy C. Waugh
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Javier E. Flores
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Lisa M. Bramer
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Athena A. Schepmoes
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Yuqian Gao
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Thomas L. Fillmore
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Ashley Frazer-Abel
- Divison of Rheumatology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - V. Michael Holers
- Divison of Rheumatology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Thomas O. Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Marian J. Rewers
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
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17
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Iacobescu M, Pop C, Uifălean A, Mogoşan C, Cenariu D, Zdrenghea M, Tănase A, Bergthorsson JT, Greiff V, Cenariu M, Iuga CA, Tomuleasa C, Tătaru D. Unlocking protein-based biomarker potential for graft-versus-host disease following allogenic hematopoietic stem cell transplants. Front Immunol 2024; 15:1327035. [PMID: 38433830 PMCID: PMC10904603 DOI: 10.3389/fimmu.2024.1327035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 02/01/2024] [Indexed: 03/05/2024] Open
Abstract
Despite the numerous advantages of allogeneic hematopoietic stem cell transplants (allo-HSCT), there exists a notable association with risks, particularly during the preconditioning period and predominantly post-intervention, exemplified by the occurrence of graft-versus-host disease (GVHD). Risk stratification prior to symptom manifestation, along with precise diagnosis and prognosis, relies heavily on clinical features. A critical imperative is the development of tools capable of early identification and effective management of patients undergoing allo-HSCT. A promising avenue in this pursuit is the utilization of proteomics-based biomarkers obtained from non-invasive biospecimens. This review comprehensively outlines the application of proteomics and proteomics-based biomarkers in GVHD patients. It delves into both single protein markers and protein panels, offering insights into their relevance in acute and chronic GVHD. Furthermore, the review provides a detailed examination of the site-specific involvement of GVHD. In summary, this article explores the potential of proteomics as a tool for timely and accurate intervention in the context of GVHD following allo-HSCT.
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Affiliation(s)
- Maria Iacobescu
- Department of Proteomics and Metabolomics, MEDFUTURE Research Center for Advanced Medicine, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Cristina Pop
- Department of Pharmacology, Physiology and Pathophysiology, Faculty of Pharmacy, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Alina Uifălean
- Department of Pharmaceutical Analysis, Faculty of Pharmacy, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Cristina Mogoşan
- Department of Pharmacology, Physiology and Pathophysiology, Faculty of Pharmacy, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Diana Cenariu
- Department of Translational Medicine, MEDFUTURE Research Center for Advanced Medicine, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Mihnea Zdrenghea
- Department of Hematology, Faculty of Medicine, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Alina Tănase
- Department of Stem Cell Transplantation, Fundeni Clinical Institute, Bucharest, Romania
| | - Jon Thor Bergthorsson
- Department of Laboratory Hematology, Stem Cell Research Unit, Biomedical Center, School of Health Sciences, University Iceland, Reykjavik, Iceland
| | - Victor Greiff
- Department of Immunology, University of Oslo, Oslo, Norway
| | - Mihai Cenariu
- Department of Animal Reproduction, University of Agricultural Sciences and Veterinary Medicine, Cluj-Napoca, Romania
| | - Cristina Adela Iuga
- Department of Proteomics and Metabolomics, MEDFUTURE Research Center for Advanced Medicine, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
- Department of Pharmaceutical Analysis, Faculty of Pharmacy, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Ciprian Tomuleasa
- Department of Translational Medicine, MEDFUTURE Research Center for Advanced Medicine, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
- Department of Hematology, Faculty of Medicine, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Dan Tătaru
- Department of Internal Medicine, Faculty of Medicine, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
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18
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Welsh JA, Goberdhan DCI, O'Driscoll L, Buzas EI, Blenkiron C, Bussolati B, Cai H, Di Vizio D, Driedonks TAP, Erdbrügger U, Falcon‐Perez JM, Fu Q, Hill AF, Lenassi M, Lim SK, Mahoney MG, Mohanty S, Möller A, Nieuwland R, Ochiya T, Sahoo S, Torrecilhas AC, Zheng L, Zijlstra A, Abuelreich S, Bagabas R, Bergese P, Bridges EM, Brucale M, Burger D, Carney RP, Cocucci E, Colombo F, Crescitelli R, Hanser E, Harris AL, Haughey NJ, Hendrix A, Ivanov AR, Jovanovic‐Talisman T, Kruh‐Garcia NA, Ku'ulei‐Lyn Faustino V, Kyburz D, Lässer C, Lennon KM, Lötvall J, Maddox AL, Martens‐Uzunova ES, Mizenko RR, Newman LA, Ridolfi A, Rohde E, Rojalin T, Rowland A, Saftics A, Sandau US, Saugstad JA, Shekari F, Swift S, Ter‐Ovanesyan D, Tosar JP, Useckaite Z, Valle F, Varga Z, van der Pol E, van Herwijnen MJC, Wauben MHM, Wehman AM, Williams S, Zendrini A, Zimmerman AJ, MISEV Consortium, Théry C, Witwer KW. Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches. J Extracell Vesicles 2024; 13:e12404. [PMID: 38326288 PMCID: PMC10850029 DOI: 10.1002/jev2.12404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 12/15/2023] [Accepted: 12/19/2023] [Indexed: 02/09/2024] Open
Abstract
Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly.
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Affiliation(s)
- Joshua A. Welsh
- Translational Nanobiology Section, Laboratory of PathologyNational Cancer Institute, National Institutes of HealthBethesdaMarylandUSA
| | - Deborah C. I. Goberdhan
- Nuffield Department of Women's and Reproductive HealthUniversity of Oxford, Women's Centre, John Radcliffe HospitalOxfordUK
| | - Lorraine O'Driscoll
- School of Pharmacy and Pharmaceutical SciencesTrinity College DublinDublinIreland
- Trinity Biomedical Sciences InstituteTrinity College DublinDublinIreland
- Trinity St. James's Cancer InstituteTrinity College DublinDublinIreland
| | - Edit I. Buzas
- Department of Genetics, Cell‐ and ImmunobiologySemmelweis UniversityBudapestHungary
- HCEMM‐SU Extracellular Vesicle Research GroupSemmelweis UniversityBudapestHungary
- HUN‐REN‐SU Translational Extracellular Vesicle Research GroupSemmelweis UniversityBudapestHungary
| | - Cherie Blenkiron
- Faculty of Medical and Health SciencesThe University of AucklandAucklandNew Zealand
| | - Benedetta Bussolati
- Department of Molecular Biotechnology and Health SciencesUniversity of TurinTurinItaly
| | | | - Dolores Di Vizio
- Department of Surgery, Division of Cancer Biology and TherapeuticsCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Tom A. P. Driedonks
- Department CDL ResearchUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Uta Erdbrügger
- University of Virginia Health SystemCharlottesvilleVirginiaUSA
| | - Juan M. Falcon‐Perez
- Exosomes Laboratory, Center for Cooperative Research in BiosciencesBasque Research and Technology AllianceDerioSpain
- Metabolomics Platform, Center for Cooperative Research in BiosciencesBasque Research and Technology AllianceDerioSpain
- IKERBASQUE, Basque Foundation for ScienceBilbaoSpain
| | - Qing‐Ling Fu
- Otorhinolaryngology Hospital, The First Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
- Extracellular Vesicle Research and Clinical Translational CenterThe First Affiliated Hospital, Sun Yat‐sen UniversityGuangzhouChina
| | - Andrew F. Hill
- Institute for Health and SportVictoria UniversityMelbourneAustralia
| | - Metka Lenassi
- Faculty of MedicineUniversity of LjubljanaLjubljanaSlovenia
| | - Sai Kiang Lim
- Institute of Molecular and Cell Biology (IMCB)Agency for Science, Technology and Research (A*STAR)SingaporeSingapore
- Paracrine Therapeutics Pte. Ltd.SingaporeSingapore
- Department of Surgery, YLL School of MedicineNational University SingaporeSingaporeSingapore
| | - Mỹ G. Mahoney
- Thomas Jefferson UniversityPhiladelphiaPennsylvaniaUSA
| | - Sujata Mohanty
- Stem Cell FacilityAll India Institute of Medical SciencesNew DelhiIndia
| | - Andreas Möller
- Chinese University of Hong KongHong KongHong Kong S.A.R.
- QIMR Berghofer Medical Research InstituteBrisbaneAustralia
| | - Rienk Nieuwland
- Laboratory of Experimental Clinical Chemistry, Amsterdam University Medical Centers, Location AMCUniversity of AmsterdamAmsterdamThe Netherlands
- Amsterdam Vesicle Center, Amsterdam University Medical Centers, Location AMCUniversity of AmsterdamAmsterdamThe Netherlands
| | | | - Susmita Sahoo
- Icahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Ana C. Torrecilhas
- Laboratório de Imunologia Celular e Bioquímica de Fungos e Protozoários, Departamento de Ciências Farmacêuticas, Instituto de Ciências Ambientais, Químicas e FarmacêuticasUniversidade Federal de São Paulo (UNIFESP) Campus DiademaDiademaBrazil
| | - Lei Zheng
- Department of Laboratory Medicine, Nanfang HospitalSouthern Medical UniversityGuangzhouChina
| | - Andries Zijlstra
- Department of PathologyVanderbilt University Medical CenterNashvilleTennesseeUSA
- GenentechSouth San FranciscoCaliforniaUSA
| | - Sarah Abuelreich
- Department of Molecular Medicine, Beckman Research InstituteCity of Hope Comprehensive Cancer CenterDuarteCaliforniaUSA
| | - Reem Bagabas
- Department of Molecular Medicine, Beckman Research InstituteCity of Hope Comprehensive Cancer CenterDuarteCaliforniaUSA
| | - Paolo Bergese
- Department of Molecular and Translational MedicineUniversity of BresciaBresciaItaly
- Center for Colloid and Surface Science (CSGI)FlorenceItaly
- National Center for Gene Therapy and Drugs based on RNA TechnologyPaduaItaly
| | - Esther M. Bridges
- Weatherall Institute of Molecular MedicineUniversity of OxfordOxfordUK
| | - Marco Brucale
- Consiglio Nazionale delle Ricerche ‐ Istituto per lo Studio dei Materiali NanostrutturatiBolognaItaly
- Consorzio Interuniversitario per lo Sviluppo dei Sistemi a Grande InterfaseFlorenceItaly
| | - Dylan Burger
- Kidney Research CentreOttawa Hopsital Research InstituteOttawaCanada
- Department of Cellular and Molecular MedicineUniversity of OttawaOttawaCanada
- School of Pharmaceutical SciencesUniversity of OttawaOttawaCanada
| | - Randy P. Carney
- Department of Biomedical EngineeringUniversity of CaliforniaDavisCaliforniaUSA
| | - Emanuele Cocucci
- Division of Pharmaceutics and Pharmacology, College of PharmacyThe Ohio State UniversityColumbusOhioUSA
- Comprehensive Cancer CenterThe Ohio State UniversityColumbusOhioUSA
| | - Federico Colombo
- Division of Pharmaceutics and Pharmacology, College of PharmacyThe Ohio State UniversityColumbusOhioUSA
| | - Rossella Crescitelli
- Sahlgrenska Center for Cancer Research, Department of Surgery, Institute of Clinical SciencesSahlgrenska Academy, University of GothenburgGothenburgSweden
- Wallenberg Centre for Molecular and Translational Medicine, Institute of Clinical SciencesSahlgrenska Academy, University of GothenburgGothenburgSweden
| | - Edveena Hanser
- Department of BiomedicineUniversity Hospital BaselBaselSwitzerland
- Department of BiomedicineUniversity of BaselBaselSwitzerland
| | | | - Norman J. Haughey
- Departments of Neurology and PsychiatryJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - An Hendrix
- Laboratory of Experimental Cancer Research, Department of Human Structure and RepairGhent UniversityGhentBelgium
- Cancer Research Institute GhentGhentBelgium
| | - Alexander R. Ivanov
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical BiologyNortheastern UniversityBostonMassachusettsUSA
| | - Tijana Jovanovic‐Talisman
- Department of Cancer Biology and Molecular Medicine, Beckman Research InstituteCity of Hope Comprehensive Cancer CenterDuarteCaliforniaUSA
| | - Nicole A. Kruh‐Garcia
- Bio‐pharmaceutical Manufacturing and Academic Resource Center (BioMARC)Infectious Disease Research Center, Colorado State UniversityFort CollinsColoradoUSA
| | - Vroniqa Ku'ulei‐Lyn Faustino
- Department of Molecular Medicine, Beckman Research InstituteCity of Hope Comprehensive Cancer CenterDuarteCaliforniaUSA
| | - Diego Kyburz
- Department of BiomedicineUniversity of BaselBaselSwitzerland
- Department of RheumatologyUniversity Hospital BaselBaselSwitzerland
| | - Cecilia Lässer
- Krefting Research Centre, Department of Internal Medicine and Clinical NutritionInstitute of Medicine at Sahlgrenska Academy, University of GothenburgGothenburgSweden
| | - Kathleen M. Lennon
- Department of Molecular Medicine, Beckman Research InstituteCity of Hope Comprehensive Cancer CenterDuarteCaliforniaUSA
| | - Jan Lötvall
- Krefting Research Centre, Institute of Medicine at Sahlgrenska AcademyUniversity of GothenburgGothenburgSweden
| | - Adam L. Maddox
- Department of Molecular Medicine, Beckman Research InstituteCity of Hope Comprehensive Cancer CenterDuarteCaliforniaUSA
| | - Elena S. Martens‐Uzunova
- Erasmus MC Cancer InstituteUniversity Medical Center Rotterdam, Department of UrologyRotterdamThe Netherlands
| | - Rachel R. Mizenko
- Department of Biomedical EngineeringUniversity of CaliforniaDavisCaliforniaUSA
| | - Lauren A. Newman
- College of Medicine and Public HealthFlinders UniversityAdelaideAustralia
| | - Andrea Ridolfi
- Department of Physics and Astronomy, and LaserLaB AmsterdamVrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Eva Rohde
- Department of Transfusion Medicine, University HospitalSalzburger Landeskliniken GmbH of Paracelsus Medical UniversitySalzburgAustria
- GMP Unit, Paracelsus Medical UniversitySalzburgAustria
- Transfer Centre for Extracellular Vesicle Theralytic Technologies, EV‐TTSalzburgAustria
| | - Tatu Rojalin
- Department of Biomedical EngineeringUniversity of CaliforniaDavisCaliforniaUSA
- Expansion Therapeutics, Structural Biology and BiophysicsJupiterFloridaUSA
| | - Andrew Rowland
- College of Medicine and Public HealthFlinders UniversityAdelaideAustralia
| | - Andras Saftics
- Department of Molecular Medicine, Beckman Research InstituteCity of Hope Comprehensive Cancer CenterDuarteCaliforniaUSA
| | - Ursula S. Sandau
- Department of Anesthesiology & Perioperative MedicineOregon Health & Science UniversityPortlandOregonUSA
| | - Julie A. Saugstad
- Department of Anesthesiology & Perioperative MedicineOregon Health & Science UniversityPortlandOregonUSA
| | - Faezeh Shekari
- Department of Stem Cells and Developmental Biology, Cell Science Research CenterRoyan Institute for Stem Cell Biology and Technology, ACECRTehranIran
- Celer DiagnosticsTorontoCanada
| | - Simon Swift
- Waipapa Taumata Rau University of AucklandAucklandNew Zealand
| | - Dmitry Ter‐Ovanesyan
- Wyss Institute for Biologically Inspired EngineeringHarvard UniversityBostonMassachusettsUSA
| | - Juan P. Tosar
- Universidad de la RepúblicaMontevideoUruguay
- Institut Pasteur de MontevideoMontevideoUruguay
| | - Zivile Useckaite
- College of Medicine and Public HealthFlinders UniversityAdelaideAustralia
| | - Francesco Valle
- Consiglio Nazionale delle Ricerche ‐ Istituto per lo Studio dei Materiali NanostrutturatiBolognaItaly
- Consorzio Interuniversitario per lo Sviluppo dei Sistemi a Grande InterfaseFlorenceItaly
| | - Zoltan Varga
- Biological Nanochemistry Research GroupInstitute of Materials and Environmental Chemistry, Research Centre for Natural SciencesBudapestHungary
- Department of Biophysics and Radiation BiologySemmelweis UniversityBudapestHungary
| | - Edwin van der Pol
- Amsterdam Vesicle Center, Amsterdam University Medical Centers, Location AMCUniversity of AmsterdamAmsterdamThe Netherlands
- Biomedical Engineering and Physics, Amsterdam UMC, location AMCUniversity of AmsterdamAmsterdamThe Netherlands
- Laboratory of Experimental Clinical Chemistry, Amsterdam UMC, location AMCUniversity of AmsterdamAmsterdamThe Netherlands
| | - Martijn J. C. van Herwijnen
- Department of Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityUtrechtThe Netherlands
| | - Marca H. M. Wauben
- Department of Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityUtrechtThe Netherlands
| | | | | | - Andrea Zendrini
- Department of Molecular and Translational MedicineUniversity of BresciaBresciaItaly
- Center for Colloid and Surface Science (CSGI)FlorenceItaly
| | - Alan J. Zimmerman
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical BiologyNortheastern UniversityBostonMassachusettsUSA
| | | | - Clotilde Théry
- Institut Curie, INSERM U932PSL UniversityParisFrance
- CurieCoreTech Extracellular Vesicles, Institut CurieParisFrance
| | - Kenneth W. Witwer
- Department of Molecular and Comparative PathobiologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
- EV Core Facility “EXCEL”, Institute for Basic Biomedical SciencesJohns Hopkins University School of MedicineBaltimoreMarylandUSA
- The Richman Family Precision Medicine Center of Excellence in Alzheimer's DiseaseJohns Hopkins University School of MedicineBaltimoreMarylandUSA
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19
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Cao C, Magalhães P, Krapp LF, Bada Juarez JF, Mayer SF, Rukes V, Chiki A, Lashuel HA, Dal Peraro M. Deep Learning-Assisted Single-Molecule Detection of Protein Post-translational Modifications with a Biological Nanopore. ACS NANO 2024; 18:1504-1515. [PMID: 38112538 PMCID: PMC10795472 DOI: 10.1021/acsnano.3c08623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 11/16/2023] [Accepted: 12/12/2023] [Indexed: 12/21/2023]
Abstract
Protein post-translational modifications (PTMs) play a crucial role in countless biological processes, profoundly modulating protein properties on both spatial and temporal scales. Protein PTMs have also emerged as reliable biomarkers for several diseases. However, only a handful of techniques are available to accurately measure their levels, capture their complexity at a single molecule level, and characterize their multifaceted roles in health and disease. Nanopore sensing provides high sensitivity for the detection of low-abundance proteins, holding the potential to impact single-molecule proteomics and PTM detection, in particular. Here, we demonstrate the ability of a biological nanopore, the pore-forming toxin aerolysin, to detect and distinguish α-synuclein-derived peptides bearing single or multiple PTMs, namely, phosphorylation, nitration, and oxidation occurring at different positions and in various combinations. The characteristic current signatures of the α-synuclein peptide and its PTM variants could be confidently identified by using a deep learning model for signal processing. We further demonstrate that this framework can quantify α-synuclein peptides at picomolar concentrations and detect the C-terminal peptides generated by digestion of full-length α-synuclein. Collectively, our work highlights the advantage of using nanopores as a tool for simultaneous detection of multiple PTMs and facilitates their use in biomarker discovery and diagnostics.
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Affiliation(s)
- Chan Cao
- Institute
of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, EPFL, Lausanne 1015, Switzerland
- Department
of Inorganic and Analytical Chemistry, Chemistry and Biochemistry, University of Geneva, 1211 Geneva, Switzerland
| | - Pedro Magalhães
- Laboratory
of Molecular and Chemical Biology of Neurodegeneration, Brain Mind
Institute, School of Life Sciences, Ecole
Polytechnique Fédérale de Lausanne, EPFL, Lausanne 1015, Switzerland
| | - Lucien F. Krapp
- Institute
of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, EPFL, Lausanne 1015, Switzerland
| | - Juan F. Bada Juarez
- Institute
of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, EPFL, Lausanne 1015, Switzerland
| | - Simon Finn Mayer
- Institute
of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, EPFL, Lausanne 1015, Switzerland
| | - Verena Rukes
- Institute
of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, EPFL, Lausanne 1015, Switzerland
| | - Anass Chiki
- Laboratory
of Molecular and Chemical Biology of Neurodegeneration, Brain Mind
Institute, School of Life Sciences, Ecole
Polytechnique Fédérale de Lausanne, EPFL, Lausanne 1015, Switzerland
| | - Hilal A. Lashuel
- Laboratory
of Molecular and Chemical Biology of Neurodegeneration, Brain Mind
Institute, School of Life Sciences, Ecole
Polytechnique Fédérale de Lausanne, EPFL, Lausanne 1015, Switzerland
| | - Matteo Dal Peraro
- Institute
of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, EPFL, Lausanne 1015, Switzerland
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20
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Saltzman AB, Chan DW, Holt MV, Wang J, Jaehnig EJ, Anurag M, Singh P, Malovannaya A, Kim BJ, Ellis MJ. Kinase inhibitor pulldown assay (KiP) for clinical proteomics. Clin Proteomics 2024; 21:3. [PMID: 38225548 PMCID: PMC10790396 DOI: 10.1186/s12014-023-09448-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 12/07/2023] [Indexed: 01/17/2024] Open
Abstract
Protein kinases are frequently dysregulated and/or mutated in cancer and represent essential targets for therapy. Accurate quantification is essential. For breast cancer treatment, the identification and quantification of the protein kinase ERBB2 is critical for therapeutic decisions. While immunohistochemistry (IHC) is the current clinical diagnostic approach, it is only semiquantitative. Mass spectrometry-based proteomics offers quantitative assays that, unlike IHC, can be used to accurately evaluate hundreds of kinases simultaneously. The enrichment of less abundant kinase targets for quantification, along with depletion of interfering proteins, improves sensitivity and thus promotes more effective downstream analyses. Multiple kinase inhibitors were therefore deployed as a capture matrix for kinase inhibitor pulldown (KiP) assays designed to profile the human protein kinome as broadly as possible. Optimized assays were initially evaluated in 16 patient derived xenograft models (PDX) where KiP identified multiple differentially expressed and biologically relevant kinases. From these analyses, an optimized single-shot parallel reaction monitoring (PRM) method was developed to improve quantitative fidelity. The PRM KiP approach was then reapplied to low quantities of proteins typical of yields from core needle biopsies of human cancers. The initial prototype targeting 100 kinases recapitulated intrinsic subtyping of PDX models obtained from comprehensive proteomic and transcriptomic profiling. Luminal and HER2 enriched OCT-frozen patient biopsies subsequently analyzed through KiP-PRM also clustered by subtype. Finally, stable isotope labeled peptide standards were developed to define a prototype clinical method. Data are available via ProteomeXchange with identifiers PXD044655 and PXD046169.
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Affiliation(s)
- Alexander B Saltzman
- Mass Spectrometry Proteomics Core, Advanced Technology Cores, Baylor College of Medicine, Houston, TX, USA
| | - Doug W Chan
- Lester and Sue Smith Breast Center and Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA
- MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Matthew V Holt
- Lester and Sue Smith Breast Center and Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Junkai Wang
- Lester and Sue Smith Breast Center and Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Eric J Jaehnig
- Lester and Sue Smith Breast Center and Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Meenakshi Anurag
- Lester and Sue Smith Breast Center and Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Purba Singh
- Lester and Sue Smith Breast Center and Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA
- Johnson & Johnson, Springhouse, PA, USA
| | - Anna Malovannaya
- Mass Spectrometry Proteomics Core, Advanced Technology Cores, Baylor College of Medicine, Houston, TX, USA
- Department of Biochemistry and Molecular Pharmacology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Beom-Jun Kim
- Lester and Sue Smith Breast Center and Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA.
- AstraZeneca, Gaithersburg, MD, 20878, USA.
| | - Matthew J Ellis
- Lester and Sue Smith Breast Center and Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA.
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21
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Essouma M. Autoimmune inflammatory myopathy biomarkers. Clin Chim Acta 2024; 553:117742. [PMID: 38176522 DOI: 10.1016/j.cca.2023.117742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 12/21/2023] [Accepted: 12/21/2023] [Indexed: 01/06/2024]
Abstract
The autoimmune inflammatory myopathy disease spectrum, commonly known as myositis, is a group of systemic diseases that mainly affect the muscles, skin and lungs. Biomarker assessment helps in understanding disease mechanisms, allowing for the implementation of precise strategies in the classification, diagnosis, and management of these diseases. This review examines the pathogenic mechanisms and highlights current data on blood and tissue biomarkers of autoimmune inflammatory myopathies.
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Affiliation(s)
- Mickael Essouma
- Network of Immunity in Infections, Malignancy and Autoimmunity, Universal Scientific Education and Research Network, Cameroon
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22
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Wang Y, Duan H, Yalikun Y, Cheng S, Li M. A pendulum-type electrochemical aptamer-based sensor for continuous, real-time and stable detection of proteins. Talanta 2024; 266:125026. [PMID: 37544252 DOI: 10.1016/j.talanta.2023.125026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/27/2023] [Accepted: 08/01/2023] [Indexed: 08/08/2023]
Abstract
Continuous detection of proteins is crucial for health management and biomedical research. Electrochemical aptamer-based (E-AB) sensor that relies on binding affinity between a recognition oligonucleotide and its specific target is a versatile platform to fulfill this purpose. Yet, the vast majority of E-AB sensors are characterized by voltammetric methods, which suffer from signal drifts and low-frequency data acquisition during continuous operations. To overcome these limitations, we developed a novel E-AB sensor empowered by Gold nanoparticle-DNA Pendulum (GDP). Using chronoamperometric interrogation, the developed sensor enabled drift-resistant, high-frequency, and real-time monitoring of vascular endothelial growth factor (VEGF), a vital signaling protein that regulates angiogenesis, endothelial cell proliferation and vasculogenesis. We assembled VEGF aptamer-anchored GDP probes to a reduced graphene modified electrode, where a fast chronoamperometric current transient occurs as the GDP rapidly transport to the electrode surface. In the presence of target molecules, longer and concentration-dependent time decays were observed because of slower motion of the GDP in its bound state. After optimizing several decisive parameters, including composition ratios of GDP, probe density, and incubation time, the GDP empowered E-AB sensor achieves continuous, selective, and reversible monitoring of VEGF in both phosphate buffered saline (PBS) solutions and artificial urine with a wide detection range from 13 fM to 130 nM. Moreover, the developed sensor acquires signals on a millisecond timescale, and remains resistant to signal degradation during operation. This study offers a new approach to designing E-AB architectures for continuous biomolecular monitoring.
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Affiliation(s)
- Yizhou Wang
- School of Engineering, Macquarie University, Sydney, 2109, NSW, Australia
| | - Haowei Duan
- School of Engineering, Macquarie University, Sydney, 2109, NSW, Australia
| | - Yaxiaer Yalikun
- Division of Materials Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, 630-0192, Ikoma, Japan
| | - Shaokoon Cheng
- School of Engineering, Macquarie University, Sydney, 2109, NSW, Australia
| | - Ming Li
- School of Engineering, Macquarie University, Sydney, 2109, NSW, Australia.
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23
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ElAbd H, Franke A. Mass Spectrometry-Based Immunopeptidomics of Peptides Presented on Human Leukocyte Antigen Proteins. Methods Mol Biol 2024; 2758:425-443. [PMID: 38549028 DOI: 10.1007/978-1-0716-3646-6_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
Human leukocyte antigen (HLA) proteins are a group of glycoproteins that are expressed at the cell surface, where they present peptides to T cells through physical interactions with T-cell receptors (TCRs). Hence, characterizing the set of peptides presented by HLA proteins, referred to hereafter as the immunopeptidome, is fundamental for neoantigen identification, immunotherapy, and vaccine development. As a result, different methods have been used over the years to identify peptides presented by HLA proteins, including competition assays, peptide microarrays, and yeast display systems. Nonetheless, over the last decade, mass spectrometry-based immunopeptidomics (MS-immunopeptidomics) has emerged as the gold-standard method for identifying peptides presented by HLA proteins. MS-immunopeptidomics enables the direct identification of the immunopeptidome in different tissues and cell types in different physiological and pathological states, for example, solid tumors or virally infected cells. Despite its advantages, it is still an experimentally and computationally challenging technique with different aspects that need to be considered before planning an MS-immunopeptidomics experiment, while conducting the experiment and with analyzing and interpreting the results. Hence, we aim in this chapter to provide an overview of this method and discuss different practical considerations at different stages starting from sample collection until data analysis. These points should aid different groups aiming at utilizing MS-immunopeptidomics, as well as, identifying future research directions to improve the method.
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Affiliation(s)
- Hesham ElAbd
- Institute of Clinical Molecular Biology, University of Kiel, Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, University of Kiel, Kiel, Germany.
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24
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Cervone DT, Moreno-Justicia R, Quesada JP, Deshmukh AS. Mass spectrometry-based proteomics approaches to interrogate skeletal muscle adaptations to exercise. Scand J Med Sci Sports 2024; 34:e14334. [PMID: 36973869 DOI: 10.1111/sms.14334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 01/30/2023] [Accepted: 02/06/2023] [Indexed: 03/29/2023]
Abstract
Acute exercise and chronic exercise training elicit beneficial whole-body changes in physiology that ultimately depend on profound alterations to the dynamics of tissue-specific proteins. Since the work accomplished during exercise owes predominantly to skeletal muscle, it has received the majority of interest from exercise scientists that attempt to unravel adaptive mechanisms accounting for salutary metabolic effects and performance improvements that arise from training. Contemporary scientists are also beginning to use mass spectrometry-based proteomics, which is emerging as a powerful approach to interrogate the muscle protein signature in a more comprehensive manner. Collectively, these technologies facilitate the analysis of skeletal muscle protein dynamics from several viewpoints, including changes to intracellular proteins (expression proteomics), secreted proteins (secretomics), post-translational modifications as well as fiber-, cell-, and organelle-specific changes. This review aims to highlight recent literature that has leveraged new workflows and advances in mass spectrometry-based proteomics to further our understanding of training-related changes in skeletal muscle. We call attention to untapped areas in skeletal muscle proteomics research relating to exercise training and metabolism, as well as basic points of contention when applying mass spectrometry-based analyses, particularly in the study of human biology. We further encourage researchers to couple the hypothesis-generating and descriptive nature of omics data with functional analyses that propel our understanding of the complex adaptive responses in skeletal muscle that occur with acute and chronic exercise.
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Affiliation(s)
- Daniel T Cervone
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Roger Moreno-Justicia
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Júlia Prats Quesada
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Atul S Deshmukh
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Clinical Proteomics, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
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25
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Forgrave LM, Moon K, Hamden JE, Li Y, Lu P, Foster LJ, Mackenzie IRA, DeMarco ML. Truncated TDP-43 proteoforms diagnostic of frontotemporal dementia with TDP-43 pathology. Alzheimers Dement 2024; 20:103-111. [PMID: 37461300 PMCID: PMC10917011 DOI: 10.1002/alz.13368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 05/26/2023] [Accepted: 06/03/2023] [Indexed: 01/18/2024]
Abstract
INTRODUCTION Biomarkers of TDP-43 pathology are needed to distinguish frontotemporal lobar degeneration with TDP-43 pathology (FTLD-TDP) from phenotypically related disorders. While normal physiological TDP-43 is not a promising biomarker, low-resolution techniques have suggested truncated forms of TDP-43 may be specific to TDP-43 pathology. To advance biomarker efforts for FTLD-TDP, we employed a high-resolution structural technique to characterize TDP-43 post-translational modifications in FTLD-TDP. METHODS High-resolution mass spectrometry was used to characterize TDP-43 proteoforms in brain tissue from FTLD-TDP, non-TDP-43 dementias and neuropathologically unaffected cases. Findings were then verified in a larger cohort of FTLD-TDP and non-TDP-43 dementias via targeted quantitative mass spectrometry. RESULTS In the discovery phase, truncated TDP-43 identified FTLD-TDP with 85% sensitivity and 100% specificity. The verification phase revealed similar findings, with 83% sensitivity and 89% specificity. DISCUSSION The concentration of truncated TDP-43 proteoforms-in particular, in vivo generated C-terminal fragments-have high diagnostic accuracy for FTLD-TDP. HIGHLIGHTS Discovery: Truncated TDP-43 differentiates FTLD-TDP from related dementias. Verification: Truncated TDP-43 concentration has high accuracy for FTLD-TDP. TDP-43 proteoforms <28 kDa have highest discriminatory power for TDP-43 pathology.
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Affiliation(s)
- Lauren M. Forgrave
- Department of Pathology and Laboratory MedicineUniversity of British ColumbiaVancouverCanada
| | - Kyung‐Mee Moon
- Department of Biochemistry and Molecular Biology and Michael Smith LaboratoriesUniversity of British ColumbiaVancouverCanada
| | - Jordan E. Hamden
- Department of Pathology and Laboratory MedicineUniversity of British ColumbiaVancouverCanada
| | - Yun Li
- Department of Pathology and Laboratory MedicineUniversity of British ColumbiaVancouverCanada
| | - Phoebe Lu
- Department of Pathology and Laboratory MedicineUniversity of British ColumbiaVancouverCanada
| | - Leonard J. Foster
- Department of Biochemistry and Molecular Biology and Michael Smith LaboratoriesUniversity of British ColumbiaVancouverCanada
| | - Ian R. A. Mackenzie
- Department of Pathology and Laboratory MedicineUniversity of British ColumbiaVancouverCanada
- Department of Pathology and Laboratory MedicineVancouver General HospitalVancouverCanada
| | - Mari L. DeMarco
- Department of Pathology and Laboratory MedicineUniversity of British ColumbiaVancouverCanada
- Department of Pathology and Laboratory MedicineSt. Paul's Hospital, Providence Health CareVancouverCanada
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26
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Lee S, Kim E, Moon CE, Park C, Lim JW, Baek M, Shin MK, Ki J, Cho H, Ji YW, Haam S. Amplified fluorogenic immunoassay for early diagnosis and monitoring of Alzheimer's disease from tear fluid. Nat Commun 2023; 14:8153. [PMID: 38071202 PMCID: PMC10710446 DOI: 10.1038/s41467-023-43995-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 11/27/2023] [Indexed: 12/18/2023] Open
Abstract
Accurate diagnosis of Alzheimer's disease (AD) in its earliest stage can prevent the disease and delay the symptoms. Therefore, more sensitive, non-invasive, and simple screening tools are required for the early diagnosis and monitoring of AD. Here, we design a self-assembled nanoparticle-mediated amplified fluorogenic immunoassay (SNAFIA) consisting of magnetic and fluorophore-loaded polymeric nanoparticles. Using a discovery cohort of 21 subjects, proteomic analysis identifies adenylyl cyclase-associated protein 1 (CAP1) as a potential tear biomarker. The SNAFIA demonstrates a low detection limit (236 aM), good reliability (R2 = 0.991), and a wide analytical range (0.320-1000 fM) for CAP1 in tear fluid. Crucially, in the verification phase with 39 subjects, SNAFIA discriminates AD patients from healthy controls with 90% sensitivity and 100% specificity in under an hour. Utilizing tear fluid as a liquid biopsy, SNAFIA could potentially aid in long-term care planning, improve clinical trial efficiency, and accelerate therapeutic development for AD.
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Affiliation(s)
- Sojeong Lee
- Department of Chemical and Biomolecular Engineering, Yonsei University, Seoul, 03722, Republic of Korea
| | - Eunjung Kim
- Division of Bioengineering, Incheon National University, Incheon, 22012, Republic of Korea
- Department of Bioengineering & Nano-bioengineering, Research Center for Bio Materials and Process Development, Incheon National University, Incheon, 22012, Republic of Korea
| | - Chae-Eun Moon
- Department of Ophthalmology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, 16995, Republic of Korea
| | - Chaewon Park
- Department of Chemical and Biomolecular Engineering, Yonsei University, Seoul, 03722, Republic of Korea
| | - Jong-Woo Lim
- Department of Chemical and Biomolecular Engineering, Yonsei University, Seoul, 03722, Republic of Korea
| | - Minseok Baek
- Department of Neurology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, 26426, Republic of Korea
| | - Moo-Kwang Shin
- Department of Chemical and Biomolecular Engineering, Yonsei University, Seoul, 03722, Republic of Korea
| | - Jisun Ki
- Department of Chemical and Biomolecular Engineering, Yonsei University, Seoul, 03722, Republic of Korea
| | - Hanna Cho
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, 06273, Republic of Korea.
| | - Yong Woo Ji
- Department of Ophthalmology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, 16995, Republic of Korea.
| | - Seungjoo Haam
- Department of Chemical and Biomolecular Engineering, Yonsei University, Seoul, 03722, Republic of Korea.
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27
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García Á, Aslan JE. Special review series: provocative questions in platelet omics studies. Platelets 2023; 34:2259169. [PMID: 37726881 DOI: 10.1080/09537104.2023.2259169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/21/2023]
Affiliation(s)
- Ángel García
- Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela, and Instituto de Investigación Sanitaria de Santiago (IDIS), Santiago de Compostela, Spain
| | - Joseph E Aslan
- Knight Cardiovascular Institute, Oregon Health & Science University, Portland, OR, USA
- Department of Chemical Physiology and Biochemistry, Oregon Health & Science University, Portland, OR, USA
- Department of Biomedical Engineering, School of Medicine, Oregon Health & Science University, Portland, OR, USA
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28
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Sopic M, Vilne B, Gerdts E, Trindade F, Uchida S, Khatib S, Wettinger SB, Devaux Y, Magni P. Multiomics tools for improved atherosclerotic cardiovascular disease management. Trends Mol Med 2023; 29:983-995. [PMID: 37806854 DOI: 10.1016/j.molmed.2023.09.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 09/20/2023] [Accepted: 09/21/2023] [Indexed: 10/10/2023]
Abstract
Multiomics studies offer accurate preventive and therapeutic strategies for atherosclerotic cardiovascular disease (ASCVD) beyond traditional risk factors. By using artificial intelligence (AI) and machine learning (ML) approaches, it is possible to integrate multiple 'omics and clinical data sets into tools that can be utilized for the development of personalized diagnostic and therapeutic approaches. However, currently multiple challenges in data quality, integration, and privacy still need to be addressed. In this opinion, we emphasize that joined efforts, exemplified by the AtheroNET COST Action, have a pivotal role in overcoming the challenges to advance multiomics approaches in ASCVD research, with the aim to foster more precise and effective patient care.
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Affiliation(s)
- Miron Sopic
- Cardiovascular Research Unit, Department of Precision Health, 1A-B rue Edison, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg; Department of Medical Biochemistry, Faculty of Pharmacy, University of Belgrade, Belgrade, 11000, Serbia
| | - Baiba Vilne
- Bioinformatics Laboratory, Rīga Stradiņš University, Rīga, LV-1007, Latvia
| | - Eva Gerdts
- Center for Research on Cardiac Disease in Women, Department of Clinical Science, University of Bergen, Bergen, 5020, Norway
| | - Fábio Trindade
- Cardiovascular R&D Centre - UnIC@RISE, Department of Surgery and Physiology, Faculty of Medicine of the University of Porto, Porto, 4099-002, Portugal
| | - Shizuka Uchida
- Center for RNA Medicine, Department of Clinical Medicine, Aalborg University, Copenhagen, SV, DK-2450, Denmark
| | - Soliman Khatib
- Natural Compounds and Analytical Chemistry Laboratory, MIGAL-Galilee Research Institute, Kiryat Shemona, 11016, Israel; Department of Biotechnology, Tel-Hai College, Upper Galilee 12210, Israel
| | - Stephanie Bezzina Wettinger
- Department of Applied Biomedical Science, Faculty of Health Sciences, University of Malta, Msida, 2080, Malta
| | - Yvan Devaux
- Cardiovascular Research Unit, Department of Precision Health, 1A-B rue Edison, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg.
| | - Paolo Magni
- Department of Pharmacological and Biomolecular Sciences 'Rodolfo Paoletti', Università degli Studi di Milano, Via G. Balzaretti 9, 20133 Milano, Italy; IRCCS MultiMedica, Via Milanese 300, 20099 Sesto S. Giovanni, Milan, Italy.
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29
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Repetto O, Vettori R, Steffan A, Cannizzaro R, De Re V. Circulating Proteins as Diagnostic Markers in Gastric Cancer. Int J Mol Sci 2023; 24:16931. [PMID: 38069253 PMCID: PMC10706891 DOI: 10.3390/ijms242316931] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 11/22/2023] [Accepted: 11/24/2023] [Indexed: 12/18/2023] Open
Abstract
Gastric cancer (GC) is a highly malignant disease affecting humans worldwide and has a poor prognosis. Most GC cases are detected at advanced stages due to the cancer lacking early detectable symptoms. Therefore, there is great interest in improving early diagnosis by implementing targeted prevention strategies. Markers are necessary for early detection and to guide clinicians to the best personalized treatment. The current semi-invasive endoscopic methods to detect GC are invasive, costly, and time-consuming. Recent advances in proteomics technologies have enabled the screening of many samples and the detection of novel biomarkers and disease-related signature signaling networks. These biomarkers include circulating proteins from different fluids (e.g., plasma, serum, urine, and saliva) and extracellular vesicles. We review relevant published studies on circulating protein biomarkers in GC and detail their application as potential biomarkers for GC diagnosis. Identifying highly sensitive and highly specific diagnostic markers for GC may improve patient survival rates and contribute to advancing precision/personalized medicine.
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Affiliation(s)
- Ombretta Repetto
- Facility of Bio-Proteomics, Immunopathology and Cancer Biomarkers, Centro di Riferimento Oncologico di Aviano (CRO), National Cancer Institute, IRCCS, 33081 Aviano, Italy
| | - Roberto Vettori
- Immunopathology and Cancer Biomarkers, Centro di Riferimento Oncologico di Aviano (CRO), National Cancer Institute, IRCCS, 33081 Aviano, Italy; (R.V.); (A.S.)
| | - Agostino Steffan
- Immunopathology and Cancer Biomarkers, Centro di Riferimento Oncologico di Aviano (CRO), National Cancer Institute, IRCCS, 33081 Aviano, Italy; (R.V.); (A.S.)
| | - Renato Cannizzaro
- Oncological Gastroenterology, Centro di Riferimento Oncologico di Aviano (CRO), National Cancer Institute, IRCCS, 33081 Aviano, Italy;
- Department of Medical, Surgical and Health Sciences, University of Trieste, 34127 Trieste, Italy
| | - Valli De Re
- Facility of Bio-Proteomics, Immunopathology and Cancer Biomarkers, Centro di Riferimento Oncologico di Aviano (CRO), National Cancer Institute, IRCCS, 33081 Aviano, Italy
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30
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Zhang Z, Chen X, Tang R, Zhu Y, Guo H, Qu Y, Xie P, Lian IY, Wang Y, Lo YH. Interpretable unsupervised learning enables accurate clustering with high-throughput imaging flow cytometry. Sci Rep 2023; 13:20533. [PMID: 37996496 PMCID: PMC10667244 DOI: 10.1038/s41598-023-46782-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 11/04/2023] [Indexed: 11/25/2023] Open
Abstract
A primary challenge of high-throughput imaging flow cytometry (IFC) is to analyze the vast amount of imaging data, especially in applications where ground truth labels are unavailable or hard to obtain. We present an unsupervised deep embedding algorithm, the Deep Convolutional Autoencoder-based Clustering (DCAEC) model, to cluster label-free IFC images without any prior knowledge of input labels. The DCAEC model first encodes the input images into the latent representations and then clusters based on the latent representations. Using the DCAEC model, we achieve a balanced accuracy of 91.9% for human white blood cell (WBC) clustering and 97.9% for WBC/leukemia clustering using the 3D IFC images and 3D DCAEC model. Above all, although no human recognizable features can separate the clusters of cells with protein localization, we demonstrate the fused DCAEC model can achieve a cluster balanced accuracy of 85.3% from the label-free 2D transmission and 3D side scattering images. To reveal how the neural network recognizes features beyond human ability, we use the gradient-weighted class activation mapping method to discover the cluster-specific visual patterns automatically. Evaluation results show that the automatically identified salient image regions have strong cluster-specific visual patterns for different clusters, which we believe is a stride for the interpretable neural network for cell analysis with high-throughput IFCs.
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Affiliation(s)
- Zunming Zhang
- Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Xinyu Chen
- Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Rui Tang
- NanoCellect Biomedical, Inc., San Diego, CA, 92121, USA
| | - Yuxuan Zhu
- Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Han Guo
- Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Yunjia Qu
- Department of Bioengineering, Institute of Engineering in Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0435, USA
| | - Pengtao Xie
- Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Ian Y Lian
- Department of Biology, Lamar University, Beaumont, TX, 77710, USA
| | - Yingxiao Wang
- Department of Bioengineering, Institute of Engineering in Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0435, USA
| | - Yu-Hwa Lo
- Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, 92093, USA.
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31
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Xu Z, Huang Y, Hu C, Du L, Du YA, Zhang Y, Qin J, Liu W, Wang R, Yang S, Wu J, Cao J, Zhang J, Chen GP, Lv H, Zhao P, He W, Wang X, Xu M, Wang P, Hong C, Yang LT, Xu J, Chen J, Wei Q, Zhang R, Yuan L, Qian K, Cheng X. Efficient plasma metabolic fingerprinting as a novel tool for diagnosis and prognosis of gastric cancer: a large-scale, multicentre study. Gut 2023; 72:2051-2067. [PMID: 37460165 DOI: 10.1136/gutjnl-2023-330045] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Accepted: 06/26/2023] [Indexed: 10/08/2023]
Abstract
OBJECTIVE Metabolic biomarkers are expected to decode the phenotype of gastric cancer (GC) and lead to high-performance blood tests towards GC diagnosis and prognosis. We attempted to develop diagnostic and prognostic models for GC based on plasma metabolic information. DESIGN We conducted a large-scale, multicentre study comprising 1944 participants from 7 centres in retrospective cohort and 264 participants in prospective cohort. Discovery and verification phases of diagnostic and prognostic models were conducted in retrospective cohort through machine learning and Cox regression of plasma metabolic fingerprints (PMFs) obtained by nanoparticle-enhanced laser desorption/ionisation-mass spectrometry (NPELDI-MS). Furthermore, the developed diagnostic model was validated in prospective cohort by both NPELDI-MS and ultra-performance liquid chromatography-MS (UPLC-MS). RESULTS We demonstrated the high throughput, desirable reproducibility and limited centre-specific effects of PMFs obtained through NPELDI-MS. In retrospective cohort, we achieved diagnostic performance with areas under curves (AUCs) of 0.862-0.988 in the discovery (n=1157 from 5 centres) and independent external verification dataset (n=787 from another 2 centres), through 5 different machine learning of PMFs, including neural network, ridge regression, lasso regression, support vector machine and random forest. Further, a metabolic panel consisting of 21 metabolites was constructed and identified for GC diagnosis with AUCs of 0.921-0.971 and 0.907-0.940 in the discovery and verification dataset, respectively. In the prospective study (n=264 from lead centre), both NPELDI-MS and UPLC-MS were applied to detect and validate the metabolic panel, and the diagnostic AUCs were 0.855-0.918 and 0.856-0.916, respectively. Moreover, we constructed a prognosis scoring system for GC in retrospective cohort, which can effectively predict the survival of GC patients. CONCLUSION We developed and validated diagnostic and prognostic models for GC, which also contribute to advanced metabolic analysis towards diseases, including but not limited to GC.
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Affiliation(s)
- Zhiyuan Xu
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
- Key Laboratory of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer of Zhejiang Province, Hangzhou, China
| | - Yida Huang
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China
- Department of Obstetrics and Gynecology, Shanghai Key Laboratory of Gynecologic Oncology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Can Hu
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
- Key Laboratory of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer of Zhejiang Province, Hangzhou, China
| | - Lingbin Du
- Office of Cancer Center, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
| | - Yi-An Du
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
| | - Yanqiang Zhang
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
| | - Jiangjiang Qin
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
| | - Wanshan Liu
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China
- Department of Obstetrics and Gynecology, Shanghai Key Laboratory of Gynecologic Oncology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Ruimin Wang
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China
- Department of Obstetrics and Gynecology, Shanghai Key Laboratory of Gynecologic Oncology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Shouzhi Yang
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China
- Department of Obstetrics and Gynecology, Shanghai Key Laboratory of Gynecologic Oncology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jiao Wu
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China
- Department of Obstetrics and Gynecology, Shanghai Key Laboratory of Gynecologic Oncology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jing Cao
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China
- Department of Obstetrics and Gynecology, Shanghai Key Laboratory of Gynecologic Oncology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Juxiang Zhang
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China
- Department of Obstetrics and Gynecology, Shanghai Key Laboratory of Gynecologic Oncology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Gui-Ping Chen
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
| | - Hang Lv
- The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
| | - Ping Zhao
- Department of Gastrointestinal Surgery, Sichuan Cancer Hospital, Chengdu, China
| | - Weiyang He
- Department of Gastrointestinal Surgery, Sichuan Cancer Hospital, Chengdu, China
| | - Xiaoliang Wang
- Department of General Surgery, Fenghua People's Hospital, Ningbo, China
| | - Min Xu
- Department of Gastroenterology, Tiantai People's Hospital, Taizhou, China
| | - Pingfang Wang
- Department of Gastroenterology, Xinchang People's Hospital, Shaoxing, China
| | - Chuanshen Hong
- Department of General Surgery, Daishan People's Hospital, Zhoushan, China
| | - Li-Tao Yang
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
| | - Jingli Xu
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
| | - Jiahui Chen
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
| | - Qing Wei
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
| | - Ruolan Zhang
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
| | - Li Yuan
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
| | - Kun Qian
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China
- Department of Obstetrics and Gynecology, Shanghai Key Laboratory of Gynecologic Oncology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Xiangdong Cheng
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
- Key Laboratory of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer of Zhejiang Province, Hangzhou, China
- Office of Cancer Center, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
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Haller N, Reichel T, Zimmer P, Behringer M, Wahl P, Stöggl T, Krüger K, Simon P. Blood-Based Biomarkers for Managing Workload in Athletes: Perspectives for Research on Emerging Biomarkers. Sports Med 2023; 53:2039-2053. [PMID: 37341908 PMCID: PMC10587296 DOI: 10.1007/s40279-023-01866-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/18/2023] [Indexed: 06/22/2023]
Abstract
At present, various blood-based biomarkers have found their applications in the field of sports medicine. This current opinion addresses biomarkers that warrant consideration in future research for monitoring the athlete training load. In this regard, we identified a variety of emerging load-sensitive biomarkers, e.g., cytokines (such as IL-6), chaperones (such as heat shock proteins) or enzymes (such as myeloperoxidase) that could improve future athlete load monitoring as they have shown meaningful increases in acute and chronic exercise settings. In some cases, they have even been linked to training status or performance characteristics. However, many of these markers have not been extensively studied and the cost and effort of measuring these parameters are still high, making them inconvenient for practitioners so far. We therefore outline strategies to improve knowledge of acute and chronic biomarker responses, including ideas for standardized study settings. In addition, we emphasize the need for methodological advances such as the development of minimally invasive point-of-care devices as well as statistical aspects related to the evaluation of these monitoring tools to make biomarkers suitable for regular load monitoring.
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Affiliation(s)
- Nils Haller
- Department of Sports Medicine, Rehabilitation and Disease Prevention, Johannes Gutenberg University of Mainz, Mainz, Germany
- Department of Sport and Exercise Science, University of Salzburg, Salzburg, Austria
| | - Thomas Reichel
- Department of Exercise Physiology and Sports Therapy, Institute of Sports Science, Justus-Liebig-University Gießen, Giessen, Germany
| | - Philipp Zimmer
- Division of Performance and Health (Sports Medicine), Institute for Sport and Sport Science, TU Dortmund University, Dortmund, Germany
| | - Michael Behringer
- Department of Sports Sciences, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Patrick Wahl
- Department of Exercise Physiology, German Sport University Cologne, Cologne, Germany
| | - Thomas Stöggl
- Department of Sport and Exercise Science, University of Salzburg, Salzburg, Austria
- Red Bull Athlete Performance Center, Salzburg, Austria
| | - Karsten Krüger
- Department of Exercise Physiology and Sports Therapy, Institute of Sports Science, Justus-Liebig-University Gießen, Giessen, Germany
| | - Perikles Simon
- Department of Sports Medicine, Rehabilitation and Disease Prevention, Johannes Gutenberg University of Mainz, Mainz, Germany.
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Mengelkoch S, Miryam Schüssler-Fiorenza Rose S, Lautman Z, Alley JC, Roos LG, Ehlert B, Moriarity DP, Lancaster S, Snyder MP, Slavich GM. Multi-omics approaches in psychoneuroimmunology and health research: Conceptual considerations and methodological recommendations. Brain Behav Immun 2023; 114:475-487. [PMID: 37543247 DOI: 10.1016/j.bbi.2023.07.022] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/04/2023] [Accepted: 07/30/2023] [Indexed: 08/07/2023] Open
Abstract
The field of psychoneuroimmunology (PNI) has grown substantially in both relevance and prominence over the past 40 years. Notwithstanding its impressive trajectory, a majority of PNI studies are still based on a relatively small number of analytes. To advance this work, we suggest that PNI, and health research in general, can benefit greatly from adopting a multi-omics approach, which involves integrating data across multiple biological levels (e.g., the genome, proteome, transcriptome, metabolome, lipidome, and microbiome/metagenome) to more comprehensively profile biological functions and relate these profiles to clinical and behavioral outcomes. To assist investigators in this endeavor, we provide an overview of multi-omics research, highlight recent landmark multi-omics studies investigating human health and disease risk, and discuss how multi-omics can be applied to better elucidate links between psychological, nervous system, and immune system activity. In doing so, we describe how to design high-quality multi-omics studies, decide which biological samples (e.g., blood, stool, urine, saliva, solid tissue) are most relevant, incorporate behavioral and wearable sensing data into multi-omics research, and understand key data quality, integration, analysis, and interpretation issues. PNI researchers are addressing some of the most interesting and important questions at the intersection of psychology, neuroscience, and immunology. Applying a multi-omics approach to this work will greatly expand the horizon of what is possible in PNI and has the potential to revolutionize our understanding of mind-body medicine.
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Affiliation(s)
- Summer Mengelkoch
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA.
| | | | - Ziv Lautman
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Jenna C Alley
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | - Lydia G Roos
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | - Benjamin Ehlert
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Daniel P Moriarity
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | | | | | - George M Slavich
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA.
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Gou MJ, Charpentier J, Cobraiville G, Crommen J, Caers J, Fillet M. Improvement of untargeted proteomics workflow for surfaceome profiling and its evaluation through the implementation of quality controls: Application to multiple myeloma. Anal Chim Acta 2023; 1279:341764. [PMID: 37827665 DOI: 10.1016/j.aca.2023.341764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/28/2023] [Accepted: 08/29/2023] [Indexed: 10/14/2023]
Abstract
BACKGROUND Comprehensive surfaceome profiling of cancer cells using mass spectrometry (MS)-based technologies is a valuable approach to identify new antigens that could be targeted by immunotherapies. Multiple myeloma (MM) is an incurable hematological malignancy in which patients suffer from multiple relapses associated with drug resistance. Nevertheless, only three MM-specific antigens are currently targeted by approved immunotherapies which restrain the availability of efficient treatments for severe refractory patients affected by aggressive forms of the disease. Therefore, the discovery of new antigens in this context could open new perspectives for those patients. RESULTS In this study, the first objective was to improve a MS-based untargeted proteomics workflow in order to handle limited patient samples. For this purpose, a highly sensitive and robust miniaturized separation system (LC-Chip) coupled with drift tube ion mobility spectrometry and high-resolution MS was integrated in our workflow to maximize protein identification. As sample preparation can strongly influence the detectability of membrane-associated proteins, the critical steps in sample preparation were carefully optimized. As a result, 4.5 times more membrane-associated proteins were identified and experimental throughput was also drastically improved. In addition to workflow performance, particular attention was paid to assess the quality of the generated data. Indeed, several quality controls (QC) were implemented to assess data quality. Finally, the optimized workflow as well as selected QCs were evaluated in the analysis of samples containing limited number of cells. SIGNIFICANCE This work allowed the improvement of an untargeted proteomics workflow for surfaceome profiling in terms of performance. Besides, the reliability of the obtained data was evaluated through the introduction of QCs in the workflow. The applicability of the improved workflow as well as the implemented QCs for the analysis of MM primary cells obtained from patients was confirmed.
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Affiliation(s)
- Marie-Jia Gou
- Laboratory for the Analysis of Medicines, Center for Interdisciplinary Research on Medicines (CIRM), University of Liege, Quartier Hopital, Avenue Hippocrate 15, 4000, Liege, Belgium
| | - Julien Charpentier
- Laboratory for the Analysis of Medicines, Center for Interdisciplinary Research on Medicines (CIRM), University of Liege, Quartier Hopital, Avenue Hippocrate 15, 4000, Liege, Belgium
| | - Gaël Cobraiville
- Laboratory for the Analysis of Medicines, Center for Interdisciplinary Research on Medicines (CIRM), University of Liege, Quartier Hopital, Avenue Hippocrate 15, 4000, Liege, Belgium
| | - Jacques Crommen
- Laboratory for the Analysis of Medicines, Center for Interdisciplinary Research on Medicines (CIRM), University of Liege, Quartier Hopital, Avenue Hippocrate 15, 4000, Liege, Belgium
| | - Jo Caers
- Laboratory of Hematology, GIGA I3, University of Liège, Liège, Belgium; Department of Hematology, CHU de Liège, Liège, Belgium
| | - Marianne Fillet
- Laboratory for the Analysis of Medicines, Center for Interdisciplinary Research on Medicines (CIRM), University of Liege, Quartier Hopital, Avenue Hippocrate 15, 4000, Liege, Belgium.
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35
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Johansson Å, Andreassen OA, Brunak S, Franks PW, Hedman H, Loos RJ, Meder B, Melén E, Wheelock CE, Jacobsson B. Precision medicine in complex diseases-Molecular subgrouping for improved prediction and treatment stratification. J Intern Med 2023; 294:378-396. [PMID: 37093654 PMCID: PMC10523928 DOI: 10.1111/joim.13640] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Complex diseases are caused by a combination of genetic, lifestyle, and environmental factors and comprise common noncommunicable diseases, including allergies, cardiovascular disease, and psychiatric and metabolic disorders. More than 25% of Europeans suffer from a complex disease, and together these diseases account for 70% of all deaths. The use of genomic, molecular, or imaging data to develop accurate diagnostic tools for treatment recommendations and preventive strategies, and for disease prognosis and prediction, is an important step toward precision medicine. However, for complex diseases, precision medicine is associated with several challenges. There is a significant heterogeneity between patients of a specific disease-both with regards to symptoms and underlying causal mechanisms-and the number of underlying genetic and nongenetic risk factors is often high. Here, we summarize precision medicine approaches for complex diseases and highlight the current breakthroughs as well as the challenges. We conclude that genomic-based precision medicine has been used mainly for patients with highly penetrant monogenic disease forms, such as cardiomyopathies. However, for most complex diseases-including psychiatric disorders and allergies-available polygenic risk scores are more probabilistic than deterministic and have not yet been validated for clinical utility. However, subclassifying patients of a specific disease into discrete homogenous subtypes based on molecular or phenotypic data is a promising strategy for improving diagnosis, prediction, treatment, prevention, and prognosis. The availability of high-throughput molecular technologies, together with large collections of health data and novel data-driven approaches, offers promise toward improved individual health through precision medicine.
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Affiliation(s)
- Åsa Johansson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala university, Sweden
| | - Ole A. Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopment Research, University of Oslo, Oslo, Norway
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2200 Copenhagen, Denmark
- Copenhagen University Hospital, Rigshospitalet, Blegdamsvej 9, DK-2200 Copenhagen, Denmark
| | - Paul W. Franks
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Sweden
- Novo Nordisk Foundation, Denmark
| | - Harald Hedman
- Department of Medical Biosciences, Umeå University, Umeå, Sweden
| | - Ruth J.F. Loos
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Charles Bronfman Institute for Personalized Medicine at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Benjamin Meder
- Precision Digital Health, Cardiogenetics Center Heidelberg, Department of Cardiology, University Of Heidelberg, Germany
| | - Erik Melén
- Department of Clinical Sciences and Education, Södersjukhuset, Karolinska Institutet, Stockholm
- Sachś Children and Youth Hospital, Södersjukhuset, Stockholm, Sweden
| | - Craig E Wheelock
- Unit of Integrative Metabolomics, Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden
- Department of Respiratory Medicine and Allergy, Karolinska University Hospital, 171 76 Stockholm, Sweden
| | - Bo Jacobsson
- Department of Obstetrics and Gynecology, Institute of Clinical Science, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Obstetrics and Gynaecology, Sahlgrenska University Hospital, Göteborg, Sweden
- Department of Genetics and Bioinformatics, Domain of Health Data and Digitalisation, Institute of Public Health, Oslo, Norway
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Wormwood KL, Charette L, Ryan JP, Darie CC, Woods AG. A Proteomics Investigation of Salivary Profiles as Potential Biomarkers for Autism Spectrum Disorder (ASD). Protein J 2023; 42:607-620. [PMID: 37566278 DOI: 10.1007/s10930-023-10146-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/01/2023] [Indexed: 08/12/2023]
Abstract
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that affects approximately 1/68 children, with a more recent study suggesting numbers as high as 1/36. According to Diagnostic and Statistical Manual of Mental Disorders, the etiology of ASD is unknown and diagnosis of this disorder is behavioral. There is currently no biomarker signature for ASD, however, identifying a biomarker signature is crucial as it would aid in diagnosis, identifying treatment targets, monitoring treatments, and identifying the etiology of the disorder. Here we used nanoliquid chromatography-tandem mass spectrometry (nanoLC-MS/MS) to investigate the saliva from individuals with ASD and matched controls in a 14 vs 14 study. We found numerous proteins to have statistically significant dysregulations, including lactotransferrin, transferrin, polymeric immunoglobulin receptor, Ig A L, Ig J chain, mucin 5 AC, and lipocalin 1 isoform X1. These findings are consistent with previous studies by our lab, and others, and point to dysregulations in the immune system, lipid metabolism and/or transport, and gastrointestinal disturbances, which are common and reoccurring topics in ASD research.
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Affiliation(s)
- Kelly L Wormwood
- Biochemistry & Proteomics Laboratories, Department of Chemistry & Biomolecular Science, Clarkson University, 8 Clarkson Ave, Box 5810, Potsdam, NY, 13699, USA
| | - Laci Charette
- Center for Neurobehavioral Health and Department of Psychology, SUNY Plattsburgh, Plattsburgh, NY, USA
| | - Jeanne P Ryan
- Center for Neurobehavioral Health and Department of Psychology, SUNY Plattsburgh, Plattsburgh, NY, USA
| | - Costel C Darie
- Biochemistry & Proteomics Laboratories, Department of Chemistry & Biomolecular Science, Clarkson University, 8 Clarkson Ave, Box 5810, Potsdam, NY, 13699, USA.
| | - Alisa G Woods
- Biochemistry & Proteomics Laboratories, Department of Chemistry & Biomolecular Science, Clarkson University, 8 Clarkson Ave, Box 5810, Potsdam, NY, 13699, USA
- Center for Neurobehavioral Health and Department of Psychology, SUNY Plattsburgh, Plattsburgh, NY, USA
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37
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Aslan JE. Different strokes, different thrombus proteomes. J Thromb Haemost 2023; 21:2715-2717. [PMID: 37739591 DOI: 10.1016/j.jtha.2023.05.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 05/16/2023] [Indexed: 09/24/2023]
Affiliation(s)
- Joseph E Aslan
- Knight Cardiovascular Institute, Oregon Health & Science University, Portland, Oregon, USA; Department of Chemical Physiology and Biochemistry, School of Medicine, Oregon Health & Science University, Portland, Oregon, USA; Department of Biomedical Engineering, School of Medicine, Oregon Health & Science University, Portland, Oregon, USA.
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38
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Kotol D, Woessmann J, Hober A, Álvez MB, Tran Minh KH, Pontén F, Fagerberg L, Uhlén M, Edfors F. Absolute Quantification of Pan-Cancer Plasma Proteomes Reveals Unique Signature in Multiple Myeloma. Cancers (Basel) 2023; 15:4764. [PMID: 37835457 PMCID: PMC10571728 DOI: 10.3390/cancers15194764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 08/31/2023] [Accepted: 09/20/2023] [Indexed: 10/15/2023] Open
Abstract
Mass spectrometry based on data-independent acquisition (DIA) has developed into a powerful quantitative tool with a variety of implications, including precision medicine. Combined with stable isotope recombinant protein standards, this strategy provides confident protein identification and precise quantification on an absolute scale. Here, we describe a comprehensive targeted proteomics approach to profile a pan-cancer cohort consisting of 1800 blood plasma samples representing 15 different cancer types. We successfully performed an absolute quantification of 253 proteins in multiplex. The assay had low intra-assay variability with a coefficient of variation below 20% (CV = 17.2%) for a total of 1013 peptides quantified across almost two thousand injections. This study identified a potential biomarker panel of seven protein targets for the diagnosis of multiple myeloma patients using differential expression analysis and machine learning. The combination of markers, including the complement C1 complex, JCHAIN, and CD5L, resulted in a prediction model with an AUC of 0.96 for the identification of multiple myeloma patients across various cancer patients. All these proteins are known to interact with immunoglobulins.
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Affiliation(s)
- David Kotol
- Science For Life Laboratory, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden; (D.K.); (J.W.); (A.H.); (M.B.Á.); (K.H.T.M.); (L.F.); (M.U.)
- Department of Protein Science, Division of Systems Biology, School of Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden
| | - Jakob Woessmann
- Science For Life Laboratory, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden; (D.K.); (J.W.); (A.H.); (M.B.Á.); (K.H.T.M.); (L.F.); (M.U.)
- Department of Protein Science, Division of Systems Biology, School of Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden
| | - Andreas Hober
- Science For Life Laboratory, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden; (D.K.); (J.W.); (A.H.); (M.B.Á.); (K.H.T.M.); (L.F.); (M.U.)
- Department of Protein Science, Division of Systems Biology, School of Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden
| | - María Bueno Álvez
- Science For Life Laboratory, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden; (D.K.); (J.W.); (A.H.); (M.B.Á.); (K.H.T.M.); (L.F.); (M.U.)
- Department of Protein Science, Division of Systems Biology, School of Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden
| | - Khue Hua Tran Minh
- Science For Life Laboratory, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden; (D.K.); (J.W.); (A.H.); (M.B.Á.); (K.H.T.M.); (L.F.); (M.U.)
- Department of Protein Science, Division of Systems Biology, School of Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden
| | - Fredrik Pontén
- Rudbeck Laboratory, Uppsala University, 752 36 Uppsala, Sweden;
| | - Linn Fagerberg
- Science For Life Laboratory, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden; (D.K.); (J.W.); (A.H.); (M.B.Á.); (K.H.T.M.); (L.F.); (M.U.)
- Department of Protein Science, Division of Systems Biology, School of Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden
| | - Mathias Uhlén
- Science For Life Laboratory, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden; (D.K.); (J.W.); (A.H.); (M.B.Á.); (K.H.T.M.); (L.F.); (M.U.)
- Department of Protein Science, Division of Systems Biology, School of Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden
| | - Fredrik Edfors
- Science For Life Laboratory, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden; (D.K.); (J.W.); (A.H.); (M.B.Á.); (K.H.T.M.); (L.F.); (M.U.)
- Department of Protein Science, Division of Systems Biology, School of Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden
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Sarkar S, Elliott EC, Henry HR, Ludovico ID, Melchior JT, Frazer-Abel A, Webb-Robertson BJ, Davidson WS, Holers VM, Rewers MJ, Metz TO, Nakayasu ES. Systematic review of type 1 diabetes biomarkers reveals regulation in circulating proteins related to complement, lipid metabolism, and immune response. Clin Proteomics 2023; 20:38. [PMID: 37735622 PMCID: PMC10512508 DOI: 10.1186/s12014-023-09429-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 08/25/2023] [Indexed: 09/23/2023] Open
Abstract
BACKGROUND Type 1 diabetes (T1D) results from an autoimmune attack of the pancreatic β cells that progresses to dysglycemia and symptomatic hyperglycemia. Current biomarkers to track this evolution are limited, with development of islet autoantibodies marking the onset of autoimmunity and metabolic tests used to detect dysglycemia. Therefore, additional biomarkers are needed to better track disease initiation and progression. Multiple clinical studies have used proteomics to identify biomarker candidates. However, most of the studies were limited to the initial candidate identification, which needs to be further validated and have assays developed for clinical use. Here we curate these studies to help prioritize biomarker candidates for validation studies and to obtain a broader view of processes regulated during disease development. METHODS This systematic review was registered with Open Science Framework ( https://doi.org/10.17605/OSF.IO/N8TSA ). Using PRISMA guidelines, we conducted a systematic search of proteomics studies of T1D in the PubMed to identify putative protein biomarkers of the disease. Studies that performed mass spectrometry-based untargeted/targeted proteomic analysis of human serum/plasma of control, pre-seroconversion, post-seroconversion, and/or T1D-diagnosed subjects were included. For unbiased screening, 3 reviewers screened all the articles independently using the pre-determined criteria. RESULTS A total of 13 studies met our inclusion criteria, resulting in the identification of 266 unique proteins, with 31 (11.6%) being identified across 3 or more studies. The circulating protein biomarkers were found to be enriched in complement, lipid metabolism, and immune response pathways, all of which are found to be dysregulated in different phases of T1D development. We found 2 subsets: 17 proteins (C3, C1R, C8G, C4B, IBP2, IBP3, ITIH1, ITIH2, BTD, APOE, TETN, C1S, C6A3, SAA4, ALS, SEPP1 and PI16) and 3 proteins (C3, CLUS and C4A) have consistent regulation in at least 2 independent studies at post-seroconversion and post-diagnosis compared to controls, respectively, making them strong candidates for clinical assay development. CONCLUSIONS Biomarkers analyzed in this systematic review highlight alterations in specific biological processes in T1D, including complement, lipid metabolism, and immune response pathways, and may have potential for further use in the clinic as prognostic or diagnostic assays.
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Affiliation(s)
- Soumyadeep Sarkar
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Emily C Elliott
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Hayden R Henry
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Ivo Díaz Ludovico
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - John T Melchior
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
- Department of Pathology and Laboratory Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Ashley Frazer-Abel
- Division of Rheumatology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | - W Sean Davidson
- Department of Pathology and Laboratory Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - V Michael Holers
- Division of Rheumatology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Marian J Rewers
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Thomas O Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Ernesto S Nakayasu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
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40
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Skoczylas Ł, Gawin M, Fochtman D, Widłak P, Whiteside TL, Pietrowska M. Immune capture and protein profiling of small extracellular vesicles from human plasma. Proteomics 2023:e2300180. [PMID: 37713108 PMCID: PMC11046486 DOI: 10.1002/pmic.202300180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 08/11/2023] [Accepted: 08/14/2023] [Indexed: 09/16/2023]
Abstract
Extracellular vesicles (EVs), the key players in inter-cellular communication, are produced by all cell types and are present in all body fluids. Analysis of the proteome content is an important approach in structural and functional studies of these vesicles. EVs circulating in human plasma are heterogeneous in size, cellular origin, and functions. This heterogeneity and the potential presence of contamination with plasma components such as lipoprotein particles and soluble plasma proteins represent a challenge in profiling the proteome of EV subsets by mass spectrometry. An immunocapture strategy prior to mass spectrometry may be used to isolate a homogeneous subpopulation of small EVs (sEV) with a specific endocytic origin from plasma or other biofluids. Immunocapture selectively separates EV subpopulations in biofluids based on the presence of a unique protein carried on the vesicle surface. The advantages and disadvantages of EV immune capture as a preparative step for mass spectrometry are discussed.
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Affiliation(s)
- Łukasz Skoczylas
- Maria Sklodowska-Curie National Research Institute of Oncology, 44-102 Gliwice, Poland
| | - Marta Gawin
- Maria Sklodowska-Curie National Research Institute of Oncology, 44-102 Gliwice, Poland
| | - Daniel Fochtman
- Maria Sklodowska-Curie National Research Institute of Oncology, 44-102 Gliwice, Poland
- Silesian University of Technology, 44-100 Gliwice, Poland
| | - Piotr Widłak
- Medical University of Gdańsk, 80-210 Gdańsk, Poland
| | - Theresa L. Whiteside
- UPMC Hillman Cancer Center, University of Pittsburgh Cancer Institute, Pittsburgh, PA 15232, USA
- Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
- Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Monika Pietrowska
- Maria Sklodowska-Curie National Research Institute of Oncology, 44-102 Gliwice, Poland
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41
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Muselius B, Roux-Dalvai F, Droit A, Geddes-McAlister J. Resolving the Temporal Splenic Proteome during Fungal Infection for Discovery of Putative Dual Perspective Biomarker Signatures. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:1928-1940. [PMID: 37222660 PMCID: PMC10487597 DOI: 10.1021/jasms.3c00114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 05/06/2023] [Accepted: 05/09/2023] [Indexed: 05/25/2023]
Abstract
Fungal pathogens are emerging threats to global health with the rise of incidence associated with climate change and increased geographical distribution; factors also influencing host susceptibility to infection. Accurate detection and diagnosis of fungal infections is paramount to offer rapid and effective therapeutic options. For improved diagnostics, the discovery and development of protein biomarkers presents a promising avenue; however, this approach requires a priori knowledge of infection hallmarks. To uncover putative novel biomarkers of disease, profiling of the host immune response and pathogen virulence factor production is indispensable. In this study, we use mass-spectrometry-based proteomics to resolve the temporal proteome of Cryptococcus neoformans infection of the spleen following a murine model of infection. Dual perspective proteome profiling defines global remodeling of the host over a time course of infection, confirming activation of immune associated proteins in response to fungal invasion. Conversely, pathogen proteomes detect well-characterized C. neoformans virulence determinants, along with novel mapped patterns of pathogenesis during the progression of disease. Together, our innovative systematic approach confirms immune protection against fungal pathogens and explores the discovery of putative biomarker signatures from complementary biological systems to monitor the presence and progression of cryptococcal disease.
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Affiliation(s)
- Benjamin Muselius
- Department
of Molecular and Cellular Biology, University
of Guelph, Guelph, Ontario N1G 2W1, Canada
| | - Florence Roux-Dalvai
- Proteomics
platform, CHU de Québec - Université
Laval Research Center, Québec
City, Québec G1
V 4G2, Canada
- Computational
Biology Laboratory, CHU de Québec
- Université Laval Research Center, Québec City, Québec G1 V 4G2, Canada
- Canadian
Proteomics and Artificial Intelligence Consortium, Guelph, Ontario N1G 2W1, Canada
| | - Arnaud Droit
- Proteomics
platform, CHU de Québec - Université
Laval Research Center, Québec
City, Québec G1
V 4G2, Canada
- Computational
Biology Laboratory, CHU de Québec
- Université Laval Research Center, Québec City, Québec G1 V 4G2, Canada
- Canadian
Proteomics and Artificial Intelligence Consortium, Guelph, Ontario N1G 2W1, Canada
| | - Jennifer Geddes-McAlister
- Department
of Molecular and Cellular Biology, University
of Guelph, Guelph, Ontario N1G 2W1, Canada
- Canadian
Proteomics and Artificial Intelligence Consortium, Guelph, Ontario N1G 2W1, Canada
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42
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Kong NR, Jones LH. Clinical Translation of Targeted Protein Degraders. Clin Pharmacol Ther 2023; 114:558-568. [PMID: 37399310 DOI: 10.1002/cpt.2985] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 06/19/2023] [Indexed: 07/05/2023]
Abstract
Targeted protein degradation (TPD) has emerged as a potentially transformational therapeutic modality with considerable promise. Molecular glue degraders remodel the surface of E3 ligases inducing interactions with neosubstrates resulting in their polyubiquitination and proteasomal degradation. Molecular glues are clinically precedented and have demonstrated the ability to degrade proteins-of-interest (POIs) previously deemed undruggable due to the absence of a traditional small molecule binding pocket. Heterobifunctional proteolysis targeting chimeras (PROTACs) possess ligands for an E3 complex and the POIs, which are chemically linked together, and similarly hijack the ubiquitin machinery to deplete the target. There has been a recent surge in the number of degraders entering clinical trials, particularly directed toward cancer. Nearly all utilize CRL4CRBN as the E3 ligase, and a relatively limited diversity of POIs are currently targeted. In this review, we provide an overview of the degraders in clinical trials and provide a perspective on the lessons learned from their development and emerging human data that will be broadly useful to those working in the TPD field.
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Affiliation(s)
- Nikki R Kong
- Center for Protein Degradation, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts, USA
| | - Lyn H Jones
- Center for Protein Degradation, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts, USA
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43
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Shields PG. Role of untargeted omics biomarkers of exposure and effect for tobacco research. ADDICTION NEUROSCIENCE 2023; 7:100098. [PMID: 37396411 PMCID: PMC10310069 DOI: 10.1016/j.addicn.2023.100098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Tobacco research remains a clear priority to improve individual and population health, and has recently become more complex with emerging combustible and noncombustible tobacco products. The use of omics methods in prevention and cessation studies are intended to identify new biomarkers for risk, compared risks related to other products and never use, and compliance for cessation and reinitation. to assess the relative effects of tobacco products to each other. They are important for the prediction of reinitiation of tobacco use and relapse prevention. In the research setting, both technical and clinical validation is required, which presents a number of complexities in the omics methodologies from biospecimen collection and sample preparation to data collection and analysis. When the results identify differences in omics features, networks or pathways, it is unclear if the results are toxic effects, a healthy response to a toxic exposure or neither. The use of surrogate biospecimens (e.g., urine, blood, sputum or nasal) may or may not reflect target organs such as the lung or bladder. This review describes the approaches for the use of omics in tobacco research and provides examples of prior studies, along with the strengths and limitations of the various methods. To date, there is little consistency in results, likely due to small number of studies, limitations in study size, the variability in the analytic platforms and bioinformatic pipelines, differences in biospecimen collection and/or human subject study design. Given the demonstrated value for the use of omics in clinical medicine, it is anticipated that the use in tobacco research will be similarly productive.
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Affiliation(s)
- Peter G. Shields
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, Columbus, OH
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44
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Maurer J, Grouzmann E, Eugster PJ. Tutorial review for peptide assays: An ounce of pre-analytics is worth a pound of cure. J Chromatogr B Analyt Technol Biomed Life Sci 2023; 1229:123904. [PMID: 37832388 DOI: 10.1016/j.jchromb.2023.123904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 10/04/2023] [Accepted: 10/05/2023] [Indexed: 10/15/2023]
Abstract
The recent increase in peptidomimetic-based medications and the growing interest in peptide hormones has brought new attention to the quantification of peptides for diagnostic purposes. Indeed, the circulating concentrations of peptide hormones in the blood provide a snapshot of the state of the body and could eventually lead to detecting a particular health condition. Although extremely useful, the quantification of such molecules, preferably by liquid chromatography coupled to mass spectrometry, might be quite tricky. First, peptides are subjected to hydrolysis, oxidation, and other post-translational modifications, and, most importantly, they are substrates of specific and nonspecific proteases in biological matrixes. All these events might continue after sampling, changing the peptide hormone concentrations. Second, because they include positively and negatively charged groups and hydrophilic and hydrophobic residues, they interact with their environment; these interactions might lead to a local change in the measured concentrations. A phenomenon such as nonspecific adsorption to lab glassware or materials has often a tremendous effect on the concentration and needs to be controlled with particular care. Finally, the circulating levels of peptides might be low (pico- or femtomolar range), increasing the impact of the aforementioned effects and inducing the need for highly sensitive instruments and well-optimized methods. Thus, despite the extreme diversity of these peptides and their matrixes, there is a common challenge for all the assays: the need to keep concentrations unchanged from sampling to analysis. While significant efforts are often placed on optimizing the analysis, few studies consider in depth the impact of pre-analytical steps on the results. By working through practical examples, this solution-oriented tutorial review addresses typical pre-analytical challenges encountered during the development of a peptide assay from the standpoint of a clinical laboratory. We provide tips and tricks to avoid pitfalls as well as strategies to guide all new developments. Our ultimate goal is to increase pre-analytical awareness to ensure that newly developed peptide assays produce robust and accurate results.
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Affiliation(s)
- Jonathan Maurer
- Service of Clinical Pharmacology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Eric Grouzmann
- Service of Clinical Pharmacology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Philippe J Eugster
- Service of Clinical Pharmacology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
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45
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McKiel LA, Ballantyne LL, Negri GL, Woodhouse KA, Fitzpatrick LE. MyD88-dependent Toll-like receptor 2 signaling modulates macrophage activation on lysate-adsorbed Teflon™ AF surfaces in an in vitro biomaterial host response model. Front Immunol 2023; 14:1232586. [PMID: 37691934 PMCID: PMC10491479 DOI: 10.3389/fimmu.2023.1232586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 08/02/2023] [Indexed: 09/12/2023] Open
Abstract
The adsorbed protein layer on an implanted biomaterial surface is known to mediate downstream cell-material interactions that drive the host response. While the adsorption of plasma-derived proteins has been studied extensively, the adsorption of damage-associated molecular patterns (DAMPs) derived from damaged cells and matrix surrounding the implant remains poorly understood. Previously, our group developed a DAMP-adsorption model in which 3T3 fibroblast lysates were used as a complex source of cell-derived DAMPs and we demonstrated that biomaterials with adsorbed lysate potently activated RAW-Blue macrophages via Toll-like receptor 2 (TLR2). In the present study, we characterized the response of mouse bone marrow derived macrophages (BMDM) from wildtype (WT), TLR2-/- and MyD88-/- mice on Teflon™ AF surfaces pre-adsorbed with 10% plasma or lysate-spiked plasma (10% w/w total protein from 3T3 fibroblast lysate) for 24 hours. WT BMDM cultured on adsorbates derived from 10% lysate in plasma had significantly higher gene and protein expression of IL-1β, IL-6, TNF-α, IL-10, RANTES/CCL5 and CXCL1/KC, compared to 10% plasma-adsorbed surfaces. Furthermore, the upregulation of pro-inflammatory cytokine and chemokine expression in the 10% lysate in plasma condition was attenuated in TLR2-/- and MyD88-/- BMDM. Proteomic analysis of the adsorbed protein layers showed that even this relatively small addition of lysate-derived proteins within plasma (10% w/w) caused a significant change to the adsorbed protein profile. The 10% plasma condition had fibrinogen, albumin, apolipoproteins, complement, and fibronectin among the top 25 most abundant proteins. While proteins layers generated from 10% lysate in plasma retained fibrinogen and fibronectin among the top 25 proteins, there was a disproportionate increase in intracellular proteins, including histones, tubulins, actins, and vimentin. Furthermore, we identified 7 DAMPs or DAMP-related proteins enriched in the 10% plasma condition (fibrinogen, apolipoproteins), compared to 39 DAMPs enriched in the 10% lysate in plasma condition, including high mobility group box 1 and histones. Together, these findings indicate that DAMPs and other intracellular proteins readily adsorb to biomaterial surfaces in competition with plasma proteins, and that adsorbed DAMPs induce an inflammatory response in adherent macrophages that is mediated by the MyD88-dependent TLR2 signaling pathway.
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Affiliation(s)
- Laura A. McKiel
- Department of Chemical Engineering, Faculty of Engineering and Applied Sciences, Queen’s University, Kingston, ON, Canada
| | - Laurel L. Ballantyne
- Department of Chemical Engineering, Faculty of Engineering and Applied Sciences, Queen’s University, Kingston, ON, Canada
- Centre for Health Innovation, Queen’s University and Kingston Health Sciences, Kingston, ON, Canada
| | | | - Kimberly A. Woodhouse
- Department of Chemical Engineering, Faculty of Engineering and Applied Sciences, Queen’s University, Kingston, ON, Canada
| | - Lindsay E. Fitzpatrick
- Department of Chemical Engineering, Faculty of Engineering and Applied Sciences, Queen’s University, Kingston, ON, Canada
- Centre for Health Innovation, Queen’s University and Kingston Health Sciences, Kingston, ON, Canada
- Department of Biomedical and Molecular Sciences, Faculty of Health Sciences, Queen’s University, Kingston, ON, Canada
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46
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Marrella MA, Biase FH. A multi-omics analysis identifies molecular features associated with fertility in heifers (Bos taurus). Sci Rep 2023; 13:12664. [PMID: 37542054 PMCID: PMC10403585 DOI: 10.1038/s41598-023-39858-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 08/01/2023] [Indexed: 08/06/2023] Open
Abstract
Infertility or subfertility is a critical barrier to sustainable cattle production, including in heifers. The development of heifers that do not produce a calf within an optimum window of time is a critical factor for the profitability and sustainability of the cattle industry. In parallel, heifers are an excellent biomedical model for understanding the underlying etiology of infertility because well-nourished heifers can still be infertile, mostly because of inherent physiological and genetic causes. Using a high-density single nucleotide polymorphism (SNP) chip, we collected genotypic data, which were analyzed using an association analysis in PLINK with Fisher's exact test. We also produced quantitative transcriptome data and proteome data. Transcriptome data were analyzed using the quasi-likelihood test followed by the Wald's test, and the likelihood test and proteome data were analyzed using a generalized mixed model and Student's t-test. We identified two SNPs significantly associated with heifer fertility (rs110918927, chr12: 85648422, P = 6.7 × 10-7; and rs109366560, chr11:37666527, P = 2.6 × 10-5). We identified two genes with differential transcript abundance (eFDR ≤ 0.002) between the two groups (Fertile and Sub-Fertile): Adipocyte Plasma Membrane Associated Protein (APMAP, 1.16 greater abundance in the Fertile group) and Dynein Axonemal Intermediate Chain 7 (DNAI7, 1.23 greater abundance in the Sub-Fertile group). Our analysis revealed that the protein Alpha-ketoglutarate-dependent dioxygenase FTO was more abundant in the plasma collected from Fertile heifers relative to their Sub-Fertile counterparts (FDR < 0.05). Lastly, an integrative analysis of the three datasets identified a series of molecular features (SNPs, gene transcripts, and proteins) that discriminated 21 out of 22 heifers correctly based on their fertility category. Our multi-omics analyses confirm the complex nature of female fertility. Very importantly, our results also highlight differences in the molecular profile of heifers associated with fertility that transcend the constraints of breed-specific genetic background.
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Affiliation(s)
- Mackenzie A Marrella
- School of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
| | - Fernando H Biase
- School of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
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47
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Singh PP, Benayoun BA. Considerations for reproducible omics in aging research. NATURE AGING 2023; 3:921-930. [PMID: 37386258 PMCID: PMC10527412 DOI: 10.1038/s43587-023-00448-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 06/01/2023] [Indexed: 07/01/2023]
Abstract
Technical advancements over the past two decades have enabled the measurement of the panoply of molecules of cells and tissues including transcriptomes, epigenomes, metabolomes and proteomes at unprecedented resolution. Unbiased profiling of these molecular landscapes in the context of aging can reveal important details about mechanisms underlying age-related functional decline and age-related diseases. However, the high-throughput nature of these experiments creates unique analytical and design demands for robustness and reproducibility. In addition, 'omic' experiments are generally onerous, making it crucial to effectively design them to eliminate as many spurious sources of variation as possible as well as account for any biological or technical parameter that may influence such measures. In this Perspective, we provide general guidelines on best practices in the design and analysis of omic experiments in aging research from experimental design to data analysis and considerations for long-term reproducibility and validation of such studies.
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Affiliation(s)
- Param Priya Singh
- Department of Anatomy, University of California, San Francisco, San Francisco, CA, USA.
- Bakar Aging Research Institute, University of California, San Francisco, San Francisco, CA, USA.
| | - Bérénice A Benayoun
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.
- Molecular and Computational Biology Department, USC Dornsife College of Letters, Arts and Sciences, Los Angeles, CA, USA.
- Biochemistry and Molecular Medicine Department, USC Keck School of Medicine, Los Angeles, CA, USA.
- Epigenetics and Gene Regulation, USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA.
- USC Stem Cell Initiative, Los Angeles, CA, USA.
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48
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Nakayasu ES, Bramer LM, Ansong C, Schepmoes AA, Fillmore TL, Gritsenko MA, Clauss TR, Gao Y, Piehowski PD, Stanfill BA, Engel DW, Orton DJ, Moore RJ, Qian WJ, Sechi S, Frohnert BI, Toppari J, Ziegler AG, Lernmark Å, Hagopian W, Akolkar B, Smith RD, Rewers MJ, Webb-Robertson BJM, Metz TO. Plasma protein biomarkers predict the development of persistent autoantibodies and type 1 diabetes 6 months prior to the onset of autoimmunity. Cell Rep Med 2023; 4:101093. [PMID: 37390828 PMCID: PMC10394168 DOI: 10.1016/j.xcrm.2023.101093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 04/14/2023] [Accepted: 06/01/2023] [Indexed: 07/02/2023]
Abstract
Type 1 diabetes (T1D) results from autoimmune destruction of β cells. Insufficient availability of biomarkers represents a significant gap in understanding the disease cause and progression. We conduct blinded, two-phase case-control plasma proteomics on the TEDDY study to identify biomarkers predictive of T1D development. Untargeted proteomics of 2,252 samples from 184 individuals identify 376 regulated proteins, showing alteration of complement, inflammatory signaling, and metabolic proteins even prior to autoimmunity onset. Extracellular matrix and antigen presentation proteins are differentially regulated in individuals who progress to T1D vs. those that remain in autoimmunity. Targeted proteomics measurements of 167 proteins in 6,426 samples from 990 individuals validate 83 biomarkers. A machine learning analysis predicts if individuals would remain in autoimmunity or develop T1D 6 months before autoantibody appearance, with areas under receiver operating characteristic curves of 0.871 and 0.918, respectively. Our study identifies and validates biomarkers, highlighting pathways affected during T1D development.
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Affiliation(s)
- Ernesto S Nakayasu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Lisa M Bramer
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Charles Ansong
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Athena A Schepmoes
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Thomas L Fillmore
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Marina A Gritsenko
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Therese R Clauss
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Yuqian Gao
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Paul D Piehowski
- Environmental and Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Bryan A Stanfill
- Computational Analytics Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Dave W Engel
- Computational Analytics Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Daniel J Orton
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Ronald J Moore
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Salvatore Sechi
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | | | - Jorma Toppari
- Department of Pediatrics, Turku University Hospital, Turku, Finland; Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology and Centre for Population Health Research, University of Turku, Turku, Finland
| | - Anette-G Ziegler
- Institute of Diabetes Research, Helmholtz Zentrum München, Munich, Germany; Forschergruppe Diabetes, Technical University of Munich, Klinikum Rechts der Isar, Munich, Germany; Forschergruppe Diabetes e.V. at Helmholtz Zentrum München, Munich, Germany
| | - Åke Lernmark
- Unit for Diabetes and Celiac Disease, Wallenberg/CRC, Department of Clinical Sciences, Lund University/CRC, Skåne University Hospital SUS, 21428 Malmö, Sweden
| | | | - Beena Akolkar
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Richard D Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Marian J Rewers
- Barbara Davis Center for Diabetes, University of Colorado, Aurora, CO, USA
| | | | - Thomas O Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
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49
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Webb-Robertson BJM, Nakayasu ES, Dong F, Waugh KC, Flores J, Bramer LM, Schepmoes A, Gao Y, Fillmore T, Onengut-Gumuscu S, Frazer-Abel A, Rich SS, Holers VM, Metz TO, Rewers MJ. Decrease in multiple complement protein levels is associated with the development of islet autoimmunity and type 1 diabetes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.13.23292628. [PMID: 37502972 PMCID: PMC10370226 DOI: 10.1101/2023.07.13.23292628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Type 1 diabetes (T1D) is a chronic condition caused by autoimmune destruction of the insulin-producing pancreatic β-cells. While it is known that gene-environment interactions play a key role in triggering the autoimmune process leading to T1D, the pathogenic mechanism leading to the appearance of islet autoantibodies - biomarkers of autoimmunity - is poorly understood. Here we show that disruption of the complement system precedes the detection of islet autoantibodies and persists through disease onset. Our results suggest that children who exhibit islet autoimmunity and progress to clinical T1D have lower complement protein levels relative to those who do not progress within a similar timeframe. Thus, the complement pathway, an understudied mechanistic and therapeutic target in T1D, merits increased attention for use as protein biomarkers of prediction and potentially prevention of T1D.
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50
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Haller N, Behringer M, Reichel T, Wahl P, Simon P, Krüger K, Zimmer P, Stöggl T. Blood-Based Biomarkers for Managing Workload in Athletes: Considerations and Recommendations for Evidence-Based Use of Established Biomarkers. Sports Med 2023; 53:1315-1333. [PMID: 37204619 PMCID: PMC10197055 DOI: 10.1007/s40279-023-01836-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/09/2023] [Indexed: 05/20/2023]
Abstract
Blood-based biomarkers can provide an objective individualized measure of training load, recovery, and health status in order to reduce injury risk and maximize performance. Despite enormous potentials, especially owing to currently evolving technology, such as point-of-care testing, and advantages, in terms of objectivity and non-interference with the training process, there are several pitfalls in the use and interpretation of biomarkers. Confounding variables such as preanalytical conditions, inter-individual differences, or an individual chronic workload can lead to variance in resting levels. In addition, statistical considerations such as the detection of meaningful minimal changes are often neglected. The lack of generally applicable and individual reference levels further complicates the interpretation of level changes and thus load management via biomarkers. Here, the potentials and pitfalls of blood-based biomarkers are described, followed by an overview of established biomarkers currently used to support workload management. Creatine kinase is discussed in terms of its evidence for workload management to illustrate the limited applicability of established markers for workload management to date. We conclude with recommendations for best practices in the use and interpretation of biomarkers in a sport-specific context.
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Affiliation(s)
- Nils Haller
- Department of Sports Medicine, Rehabilitation and Disease Prevention, Johannes Gutenberg University of Mainz, Mainz, Germany
- Department of Sport and Exercise Science, University of Salzburg, Schlossallee 49, Salzburg, 5400 Hallein-Rif, Austria
| | - Michael Behringer
- Department of Sports Sciences, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Thomas Reichel
- Department of Exercise Physiology and Sports Therapy, Institute of Sports Science, Justus-Liebig-University Gießen, Gießen, Germany
| | - Patrick Wahl
- Department of Exercise Physiology, German Sport University Cologne, Cologne, Germany
| | - Perikles Simon
- Department of Sports Medicine, Rehabilitation and Disease Prevention, Johannes Gutenberg University of Mainz, Mainz, Germany
| | - Karsten Krüger
- Department of Exercise Physiology and Sports Therapy, Institute of Sports Science, Justus-Liebig-University Gießen, Gießen, Germany
| | - Philipp Zimmer
- Division of Performance and Health (Sports Medicine), Institute for Sport and Sport Science, TU Dortmund University, Dortmund, Germany
| | - Thomas Stöggl
- Department of Sport and Exercise Science, University of Salzburg, Schlossallee 49, Salzburg, 5400 Hallein-Rif, Austria.
- Red Bull Athlete Performance Center, Salzburg, Austria.
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