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Richard V, Mitsa G, Eshghi A, Chaplygina D, Mohammed Y, Goodlett DR, Zahedi RP, Thevis M, Borchers CH. Establishing Personalized Blood Protein Reference Ranges Using Noninvasive Microsampling and Targeted Proteomics: Implications for Antidoping Strategies. J Proteome Res 2024; 23:1779-1787. [PMID: 38655860 PMCID: PMC11077581 DOI: 10.1021/acs.jproteome.4c00020] [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: 01/11/2024] [Revised: 03/28/2024] [Accepted: 04/05/2024] [Indexed: 04/26/2024]
Abstract
To prevent doping practices in sports, the World Anti-Doping Agency implemented the Athlete Biological Passport (ABP) program, monitoring biological variables over time to indirectly reveal the effects of doping rather than detect the doping substance or the method itself. In the context of this program, a highly multiplexed mass spectrometry-based proteomics assay for 319 peptides corresponding to 250 proteins was developed, including proteins associated with blood-doping practices. "Baseline" expression profiles of these potential biomarkers in capillary blood (dried blood spots (DBS)) were established using multiple reaction monitoring (MRM). Combining DBS microsampling with highly multiplexed MRM assays is the best-suited technology to enhance the effectiveness of the ABP program, as it represents a cost-effective and robust alternative analytical method with high specificity and selectivity of targets in the attomole range. DBS data were collected from 10 healthy athlete volunteers over a period of 140 days (28 time points per participant). These comprehensive findings provide a personalized targeted blood proteome "fingerprint" showcasing that the targeted proteome is unique to an individual and likely comparable to a DNA fingerprint. The results can serve as a baseline for future studies investigating doping-related perturbations.
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Affiliation(s)
- Vincent
R. Richard
- Segal
Cancer Proteomics Centre, Lady Davis Institute
for Medical Research, Jewish General Hospital, Montréal, Quebec H3T 1E2, Canada
| | - Georgia Mitsa
- Segal
Cancer Proteomics Centre, Lady Davis Institute
for Medical Research, Jewish General Hospital, Montréal, Quebec H3T 1E2, Canada
- Division
of Experimental Medicine, McGill University, Montréal, Quebec H4A 3J1, Canada
| | - Azad Eshghi
- University
of Victoria-Genome BC Proteomics Centre, Victoria, British Columbia V8Z 7X8, Canada
| | - Daria Chaplygina
- Segal
Cancer Proteomics Centre, Lady Davis Institute
for Medical Research, Jewish General Hospital, Montréal, Quebec H3T 1E2, Canada
| | - Yassene Mohammed
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, Leiden 2333 ZC, The Netherlands
| | - David R. Goodlett
- University
of Victoria-Genome BC Proteomics Centre, Victoria, British Columbia V8Z 7X8, Canada
| | - Rene P. Zahedi
- Manitoba
Centre for Proteomics and Systems Biology, Winnipeg, Manitoba R3E 3P4, Canada
- Department
of Internal Medicine, University of Manitoba, Winnipeg, Manitoba R3E 3P4, Canada
- Department
of Biochemistry and Medical Genetics, University
of Manitoba, Winnipeg, Manitoba R3E 0J9, Canada
- CancerCare
Manitoba Research Institute, Winnipeg, Manitoba R3E 0V9, Canada
| | - Mario Thevis
- Institute
of Biochemistry, Center for Preventive Doping Research, German Sport University Cologne, Cologne 50933, Germany
- European
Monitoring Center for Emerging Doping Agents (EuMoCEDA), Cologne/Bonn 50933, Germany
| | - Christoph H. Borchers
- Segal
Cancer Proteomics Centre, Lady Davis Institute
for Medical Research, Jewish General Hospital, Montréal, Quebec H3T 1E2, Canada
- Division
of Experimental Medicine, McGill University, Montréal, Quebec H4A 3J1, Canada
- Gerald
Bronfman Department of Oncology, McGill
University, Montréal, Quebec H4A 3T2, Canada
- Department
of Pathology, McGill University, Montréal, Quebec H4A 3J1, Canada
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2
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Weaver C, Nam A, Settle C, Overton M, Giddens M, Richardson KP, Piver R, Mysona DP, Rungruang B, Ghamande S, McIndoe R, Purohit S. Serum Proteomic Signatures in Cervical Cancer: Current Status and Future Directions. Cancers (Basel) 2024; 16:1629. [PMID: 38730581 PMCID: PMC11083044 DOI: 10.3390/cancers16091629] [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: 02/29/2024] [Revised: 04/18/2024] [Accepted: 04/19/2024] [Indexed: 05/13/2024] Open
Abstract
In 2020, the World Health Organization (WHO) reported 604,000 new diagnoses of cervical cancer (CC) worldwide, and over 300,000 CC-related fatalities. The vast majority of CC cases are caused by persistent human papillomavirus (HPV) infections. HPV-related CC incidence and mortality rates have declined worldwide because of increased HPV vaccination and CC screening with the Papanicolaou test (PAP test). Despite these significant improvements, developing countries face difficulty implementing these programs, while developed nations are challenged with identifying HPV-independent cases. Molecular and proteomic information obtained from blood or tumor samples have a strong potential to provide information on malignancy progression and response to therapy in CC. There is a large amount of published biomarker data related to CC available but the extensive validation required by the FDA approval for clinical use is lacking. The ability of researchers to use the big data obtained from clinical studies and to draw meaningful relationships from these data are two obstacles that must be overcome for implementation into clinical practice. We report on identified multimarker panels of serum proteomic studies in CC for the past 5 years, the potential for modern computational biology efforts, and the utilization of nationwide biobanks to bridge the gap between multivariate protein signature development and the prediction of clinically relevant CC patient outcomes.
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Affiliation(s)
- Chaston Weaver
- Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA; (C.W.); (K.P.R.); (R.P.); (D.P.M.); (R.M.)
| | - Alisha Nam
- Department of Undergraduate Health Professions, College of Allied Health Sciences, Augusta University, Augusta, GA 30912, USA; (A.N.); (C.S.); (M.O.); (M.G.)
| | - Caitlin Settle
- Department of Undergraduate Health Professions, College of Allied Health Sciences, Augusta University, Augusta, GA 30912, USA; (A.N.); (C.S.); (M.O.); (M.G.)
| | - Madelyn Overton
- Department of Undergraduate Health Professions, College of Allied Health Sciences, Augusta University, Augusta, GA 30912, USA; (A.N.); (C.S.); (M.O.); (M.G.)
| | - Maya Giddens
- Department of Undergraduate Health Professions, College of Allied Health Sciences, Augusta University, Augusta, GA 30912, USA; (A.N.); (C.S.); (M.O.); (M.G.)
| | - Katherine P. Richardson
- Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA; (C.W.); (K.P.R.); (R.P.); (D.P.M.); (R.M.)
| | - Rachael Piver
- Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA; (C.W.); (K.P.R.); (R.P.); (D.P.M.); (R.M.)
- Department of Obstetrics and Gynecology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA; (B.R.); (S.G.)
| | - David P. Mysona
- Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA; (C.W.); (K.P.R.); (R.P.); (D.P.M.); (R.M.)
- Department of Obstetrics and Gynecology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA; (B.R.); (S.G.)
| | - Bunja Rungruang
- Department of Obstetrics and Gynecology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA; (B.R.); (S.G.)
| | - Sharad Ghamande
- Department of Obstetrics and Gynecology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA; (B.R.); (S.G.)
| | - Richard McIndoe
- Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA; (C.W.); (K.P.R.); (R.P.); (D.P.M.); (R.M.)
- Department of Obstetrics and Gynecology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA; (B.R.); (S.G.)
| | - Sharad Purohit
- Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA; (C.W.); (K.P.R.); (R.P.); (D.P.M.); (R.M.)
- Department of Undergraduate Health Professions, College of Allied Health Sciences, Augusta University, Augusta, GA 30912, USA; (A.N.); (C.S.); (M.O.); (M.G.)
- Department of Obstetrics and Gynecology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA; (B.R.); (S.G.)
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3
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Wang Y, Bednarcik M, Ament C, Cheever ML, Cummings S, Geng T, Gunasekara DB, Houston N, Kouba K, Liu Z, Shippar J. Immunoassays and Mass Spectrometry for Determination of Protein Concentrations in Genetically Modified Crops. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72. [PMID: 38607999 PMCID: PMC11046482 DOI: 10.1021/acs.jafc.3c09188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 03/14/2024] [Accepted: 03/21/2024] [Indexed: 04/14/2024]
Abstract
Quantifying protein levels in genetically modified (GM) crops is crucial in every phase of development, deregulation, and seed production. Immunoassays, particularly enzyme-linked immunosorbent assay, have been the primary protein quantitation techniques for decades within the industry due to their efficiency, adaptability, and credibility. Newer immunoassay technologies like Meso Scale Discovery and Luminex offer enhanced sensitivity and multiplexing capabilities. While mass spectrometry (MS) has been widely used for small molecules and protein detection in the pharmaceutical and agricultural industries (e.g., biomarkers, endogenous allergens), its use in quantifying protein levels in GM crops has been limited. However, as trait portfolios for GM crop have expanded, MS has been increasingly adopted due to its comparable sensitivity, increased specificity, and multiplexing capabilities. This review contrasts the benefits and limitations of immunoassays and MS technologies for protein measurement in GM crops, considering factors such as cost, convenience, and specific analytical needs. Ultimately, both techniques are suitable for assessing protein concentrations in GM crops, with MS offering complementary capabilities to immunoassays. This comparison aims to provide insights into selecting between these techniques based on the user's end point needs.
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Affiliation(s)
- Yanfei Wang
- Bayer
CropScience, 700 Chesterfield
Pkwy West, Chesterfield, Missouri 63017, United
States
| | - Mark Bednarcik
- Syngenta
Crop Protection, Limited Liability Company, 9 Davis Drive, Post Office Box 12257, Research Triangle Park, North Carolina 27709-2257, United
States
| | - Christopher Ament
- Eurofins
Food Chemistry Testing Madison, Incorporated, 6304 Ronald Reagan Avenue, Madison, Wisconsin 53704, United States
| | - Matthew L. Cheever
- BASF
Corporation, 26 Davis Drive, Research Triangle Park, North Carolina 27709, United States
| | - Simone Cummings
- Syngenta
Crop Protection, Limited Liability Company, 9 Davis Drive, Post Office Box 12257, Research Triangle Park, North Carolina 27709-2257, United
States
| | - Tao Geng
- Bayer
CropScience, 700 Chesterfield
Pkwy West, Chesterfield, Missouri 63017, United
States
| | - Dulan B. Gunasekara
- BASF
Corporation, 26 Davis Drive, Research Triangle Park, North Carolina 27709, United States
| | - Norma Houston
- Corteva
Agriscience, Johnston, Iowa 50131, United States
| | - Kristen Kouba
- Corteva
Agriscience, Johnston, Iowa 50131, United States
| | - Zi Liu
- Bayer
CropScience, 700 Chesterfield
Pkwy West, Chesterfield, Missouri 63017, United
States
| | - Jeffrey Shippar
- Eurofins
Food Chemistry Testing Madison, Incorporated, 6304 Ronald Reagan Avenue, Madison, Wisconsin 53704, United States
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Wenk D, Zuo C, Kislinger T, Sepiashvili L. Recent developments in mass-spectrometry-based targeted proteomics of clinical cancer biomarkers. Clin Proteomics 2024; 21:6. [PMID: 38287260 PMCID: PMC10826105 DOI: 10.1186/s12014-024-09452-1] [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: 11/10/2023] [Accepted: 01/14/2024] [Indexed: 01/31/2024] Open
Abstract
Routine measurement of cancer biomarkers is performed for early detection, risk classification, and treatment monitoring, among other applications, and has substantially contributed to better clinical outcomes for patients. However, there remains an unmet need for clinically validated assays of cancer protein biomarkers. Protein tumor markers are of particular interest since proteins carry out the majority of biological processes and thus dynamically reflect changes in cancer pathophysiology. Mass spectrometry-based targeted proteomics is a powerful tool for absolute peptide and protein quantification in biological matrices with numerous advantages that make it attractive for clinical applications in oncology. The use of liquid chromatography-tandem mass spectrometry (LC-MS/MS) based methodologies has allowed laboratories to overcome challenges associated with immunoassays that are more widely used for tumor marker measurements. Yet, clinical implementation of targeted proteomics methodologies has so far been limited to a few cancer markers. This is due to numerous challenges associated with paucity of robust validation studies of new biomarkers and the labor-intensive and operationally complex nature of LC-MS/MS workflows. The purpose of this review is to provide an overview of targeted proteomics applications in cancer, workflows used in targeted proteomics, and requirements for clinical validation and implementation of targeted proteomics assays. We will also discuss advantages and challenges of targeted MS-based proteomics assays for clinical cancer biomarker analysis and highlight some recent developments that will positively contribute to the implementation of this technique into clinical laboratories.
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Affiliation(s)
- Deborah Wenk
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Charlotte Zuo
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Thomas Kislinger
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
- Princess Margaret Cancer Research Tower, Room 9-807, 101 College Street, Toronto, ON, M5G 1L7, Canada.
| | - Lusia Sepiashvili
- Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, 555 University Ave, Rm 3606, Toronto, ON, M5G 1X8, Canada.
- Department of Laboratory Medicine & Pathobiology, University of Toronto, Toronto, ON, Canada.
- Sickkids Research Institute, Toronto, ON, Canada.
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5
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Ryu J, Boylan KLM, Twigg CAI, Evans R, Skubitz APN, Thomas SN. Quantification of putative ovarian cancer serum protein biomarkers using a multiplexed targeted mass spectrometry assay. Clin Proteomics 2024; 21:1. [PMID: 38172678 PMCID: PMC10762856 DOI: 10.1186/s12014-023-09447-4] [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: 08/04/2023] [Accepted: 12/07/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Ovarian cancer is the most lethal gynecologic malignancy in women, and high-grade serous ovarian cancer (HGSOC) is the most common subtype. Currently, no clinical test has been approved by the FDA to screen the general population for ovarian cancer. This underscores the critical need for the development of a robust methodology combined with novel technology to detect diagnostic biomarkers for HGSOC in the sera of women. Targeted mass spectrometry (MS) can be used to identify and quantify specific peptides/proteins in complex biological samples with high accuracy, sensitivity, and reproducibility. In this study, we sought to develop and conduct analytical validation of a multiplexed Tier 2 targeted MS parallel reaction monitoring (PRM) assay for the relative quantification of 23 putative ovarian cancer protein biomarkers in sera. METHODS To develop a PRM method for our target peptides in sera, we followed nationally recognized consensus guidelines for validating fit-for-purpose Tier 2 targeted MS assays. The endogenous target peptide concentrations were calculated using the calibration curves in serum for each target peptide. Receiver operating characteristic (ROC) curves were analyzed to evaluate the diagnostic performance of the biomarker candidates. RESULTS We describe an effort to develop and analytically validate a multiplexed Tier 2 targeted PRM MS assay to quantify candidate ovarian cancer protein biomarkers in sera. Among the 64 peptides corresponding to 23 proteins in our PRM assay, 24 peptides corresponding to 16 proteins passed the assay validation acceptability criteria. A total of 6 of these peptides from insulin-like growth factor-binding protein 2 (IBP2), sex hormone-binding globulin (SHBG), and TIMP metalloproteinase inhibitor 1 (TIMP1) were quantified in sera from a cohort of 69 patients with early-stage HGSOC, late-stage HGSOC, benign ovarian conditions, and healthy (non-cancer) controls. Confirming the results from previously published studies using orthogonal analytical approaches, IBP2 was identified as a diagnostic biomarker candidate based on its significantly increased abundance in the late-stage HGSOC patient sera compared to the healthy controls and patients with benign ovarian conditions. CONCLUSIONS A multiplexed targeted PRM MS assay was applied to detect candidate diagnostic biomarkers in HGSOC sera. To evaluate the clinical utility of the IBP2 PRM assay for HGSOC detection, further studies need to be performed using a larger patient cohort.
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Affiliation(s)
- Joohyun Ryu
- Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, MN, USA
| | - Kristin L M Boylan
- Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, MN, USA
| | - Carly A I Twigg
- Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, MN, USA
| | - Richard Evans
- Clinical and Translational Research Institute, University of Minnesota, Minneapolis, MN, USA
| | - Amy P N Skubitz
- Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, MN, USA
| | - Stefani N Thomas
- Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, MN, USA.
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6
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Michaud SA, Pětrošová H, Sinclair NJ, Kinnear AL, Jackson AM, McGuire JC, Hardie DB, Bhowmick P, Ganguly M, Flenniken AM, Nutter LMJ, McKerlie C, Smith D, Mohammed Y, Schibli D, Sickmann A, Borchers CH. Multiple reaction monitoring assays for large-scale quantitation of proteins from 20 mouse organs and tissues. Commun Biol 2024; 7:6. [PMID: 38168632 PMCID: PMC10762018 DOI: 10.1038/s42003-023-05687-0] [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: 09/16/2020] [Accepted: 12/07/2023] [Indexed: 01/05/2024] Open
Abstract
Mouse is the mammalian model of choice to study human health and disease due to its size, ease of breeding and the natural occurrence of conditions mimicking human pathology. Here we design and validate multiple reaction monitoring mass spectrometry (MRM-MS) assays for quantitation of 2118 unique proteins in 20 murine tissues and organs. We provide open access to technical aspects of these assays to enable their implementation in other laboratories, and demonstrate their suitability for proteomic profiling in mice by measuring normal protein abundances in tissues from three mouse strains: C57BL/6NCrl, NOD/SCID, and BALB/cAnNCrl. Sex- and strain-specific differences in protein abundances are identified and described, and the measured values are freely accessible via our MouseQuaPro database: http://mousequapro.proteincentre.com . Together, this large library of quantitative MRM-MS assays established in mice and the measured baseline protein abundances represent an important resource for research involving mouse models.
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Affiliation(s)
- Sarah A Michaud
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria, BC, Canada.
| | - Helena Pětrošová
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria, BC, Canada
| | - Nicholas J Sinclair
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria, BC, Canada
| | - Andrea L Kinnear
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria, BC, Canada
| | - Angela M Jackson
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria, BC, Canada
| | - Jamie C McGuire
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria, BC, Canada
| | - Darryl B Hardie
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria, BC, Canada
| | - Pallab Bhowmick
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria, BC, Canada
| | - Milan Ganguly
- The Center for Phenogenomics, Toronto, ON, Canada
- The Hospital for Sick Children, Toronto, ON, Canada
| | - Ann M Flenniken
- The Center for Phenogenomics, Toronto, ON, Canada
- Sinai Health Lunenfeld-Tanenbaum Research Institute, Toronto, ON, Canada
| | - Lauryl M J Nutter
- The Center for Phenogenomics, Toronto, ON, Canada
- The Hospital for Sick Children, Toronto, ON, Canada
| | | | - Derek Smith
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria, BC, Canada
| | - Yassene Mohammed
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V, Dortmund, 44139, Germany
- Segal Cancer Proteomics Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, QC, Canada
| | - David Schibli
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria, BC, Canada
| | - Albert Sickmann
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V, Dortmund, 44139, Germany
| | - Christoph H Borchers
- Segal Cancer Proteomics Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, QC, Canada.
- Gerald Bronfman Department of Oncology, Jewish General Hospital, Montreal, QC, Canada.
- Department of Experimental Medicine, McGill University, Montreal, QC, Canada.
- Department of Pathology, McGill University, Montreal, QC, Canada.
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7
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Starodubtseva NL, Tokareva AO, Volochaeva MV, Kononikhin AS, Brzhozovskiy AG, Bugrova AE, Timofeeva AV, Kukaev EN, Tyutyunnik VL, Kan NE, Frankevich VE, Nikolaev EN, Sukhikh GT. Quantitative Proteomics of Maternal Blood Plasma in Isolated Intrauterine Growth Restriction. Int J Mol Sci 2023; 24:16832. [PMID: 38069155 PMCID: PMC10706154 DOI: 10.3390/ijms242316832] [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: 10/24/2023] [Revised: 11/17/2023] [Accepted: 11/24/2023] [Indexed: 12/18/2023] Open
Abstract
Intrauterine growth restriction (IUGR) remains a significant concern in modern obstetrics, linked to high neonatal health problems and even death, as well as childhood disability, affecting adult quality of life. The role of maternal and fetus adaptation during adverse pregnancy is still not completely understood. This study aimed to investigate the disturbance in biological processes associated with isolated IUGR via blood plasma proteomics. The levels of 125 maternal plasma proteins were quantified by liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) with corresponding stable isotope-labeled peptide standards (SIS). Thirteen potential markers of IUGR (Gelsolin, Alpha-2-macroglobulin, Apolipoprotein A-IV, Apolipoprotein B-100, Apolipoprotein(a), Adiponectin, Complement C5, Apolipoprotein D, Alpha-1B-glycoprotein, Serum albumin, Fibronectin, Glutathione peroxidase 3, Lipopolysaccharide-binding protein) were found to be inter-connected in a protein-protein network. These proteins are involved in plasma lipoprotein assembly, remodeling, and clearance; lipid metabolism, especially cholesterol and phospholipids; hemostasis, including platelet degranulation; and immune system regulation. Additionally, 18 proteins were specific to a particular type of IUGR (early or late). Distinct patterns in the coagulation and fibrinolysis systems were observed between isolated early- and late-onset IUGR. Our findings highlight the complex interplay of immune and coagulation factors in IUGR and the differences between early- and late-onset IUGR and other placenta-related conditions like PE. Understanding these mechanisms is crucial for developing targeted interventions and improving outcomes for pregnancies affected by IUGR.
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Affiliation(s)
- Natalia L. Starodubtseva
- National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia; (A.O.T.); (M.V.V.); (A.S.K.); (A.G.B.); (A.E.B.); (A.V.T.); (E.N.K.); (V.L.T.); (N.E.K.); (V.E.F.); (G.T.S.)
- Moscow Institute of Physics and Technology, 141700 Moscow, Russia
| | - Alisa O. Tokareva
- National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia; (A.O.T.); (M.V.V.); (A.S.K.); (A.G.B.); (A.E.B.); (A.V.T.); (E.N.K.); (V.L.T.); (N.E.K.); (V.E.F.); (G.T.S.)
| | - Maria V. Volochaeva
- National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia; (A.O.T.); (M.V.V.); (A.S.K.); (A.G.B.); (A.E.B.); (A.V.T.); (E.N.K.); (V.L.T.); (N.E.K.); (V.E.F.); (G.T.S.)
| | - Alexey S. Kononikhin
- National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia; (A.O.T.); (M.V.V.); (A.S.K.); (A.G.B.); (A.E.B.); (A.V.T.); (E.N.K.); (V.L.T.); (N.E.K.); (V.E.F.); (G.T.S.)
| | - Alexander G. Brzhozovskiy
- National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia; (A.O.T.); (M.V.V.); (A.S.K.); (A.G.B.); (A.E.B.); (A.V.T.); (E.N.K.); (V.L.T.); (N.E.K.); (V.E.F.); (G.T.S.)
| | - Anna E. Bugrova
- National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia; (A.O.T.); (M.V.V.); (A.S.K.); (A.G.B.); (A.E.B.); (A.V.T.); (E.N.K.); (V.L.T.); (N.E.K.); (V.E.F.); (G.T.S.)
- Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Angelika V. Timofeeva
- National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia; (A.O.T.); (M.V.V.); (A.S.K.); (A.G.B.); (A.E.B.); (A.V.T.); (E.N.K.); (V.L.T.); (N.E.K.); (V.E.F.); (G.T.S.)
| | - Evgenii N. Kukaev
- National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia; (A.O.T.); (M.V.V.); (A.S.K.); (A.G.B.); (A.E.B.); (A.V.T.); (E.N.K.); (V.L.T.); (N.E.K.); (V.E.F.); (G.T.S.)
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Victor L. Tyutyunnik
- National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia; (A.O.T.); (M.V.V.); (A.S.K.); (A.G.B.); (A.E.B.); (A.V.T.); (E.N.K.); (V.L.T.); (N.E.K.); (V.E.F.); (G.T.S.)
| | - Natalia E. Kan
- National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia; (A.O.T.); (M.V.V.); (A.S.K.); (A.G.B.); (A.E.B.); (A.V.T.); (E.N.K.); (V.L.T.); (N.E.K.); (V.E.F.); (G.T.S.)
| | - Vladimir E. Frankevich
- National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia; (A.O.T.); (M.V.V.); (A.S.K.); (A.G.B.); (A.E.B.); (A.V.T.); (E.N.K.); (V.L.T.); (N.E.K.); (V.E.F.); (G.T.S.)
- Laboratory of Translational Medicine, Siberian State Medical University, 634050 Tomsk, Russia
| | - Evgeny N. Nikolaev
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Gennady T. Sukhikh
- National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia; (A.O.T.); (M.V.V.); (A.S.K.); (A.G.B.); (A.E.B.); (A.V.T.); (E.N.K.); (V.L.T.); (N.E.K.); (V.E.F.); (G.T.S.)
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8
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Guan XL, Chang DPS, Mok ZX, Lee B. Assessing variations in manual pipetting: An under-investigated requirement of good laboratory practice. J Mass Spectrom Adv Clin Lab 2023; 30:25-29. [PMID: 37841753 PMCID: PMC10569977 DOI: 10.1016/j.jmsacl.2023.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 08/05/2023] [Accepted: 09/27/2023] [Indexed: 10/17/2023] Open
Abstract
Pipettes are essential tools for biomedical and analytical laboratories, analogous to workstations for computer scientists. Variation in pipetting is a known unknown, as it is generally accepted that variations exist, but thus far, there have been limited studies on the extent of these variations in practice. In this mini-review, we highlight how manual pipetting is a key technique in the laboratory, and, although simple, inaccuracy and imprecision exist. If variations are not adequately addressed, errors can be compounded and consequently compromise data quality. Determination of the accuracy and precision of manual pipetting is straightforward, and here we review two common approaches that use gravimetry and spectrophotometry as readouts. We also provide detailed protocols for determination of accuracy and precision using manual single and multi-channel pipettes. These simple-to-use methods can be used by any laboratory for competency training and regular checks. Having a common protocol for evaluation of variation will also enable cross-laboratory comparison and potentially facilitate establishment of a reference value of acceptable ranges for operator error. Such a value could be of relevance to the scientific community for benchmarking and assuring good laboratory practice.
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Affiliation(s)
- Xue Li Guan
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | | | - Zhen Xuan Mok
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Bernett Lee
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
- Centre for Biomedical Informatics, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore 138648, Singapore
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9
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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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10
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Bowser BL, Patterson KL, Robinson RA. Evaluating cPILOT Data toward Quality Control Implementation. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:1741-1752. [PMID: 37459602 DOI: 10.1021/jasms.3c00179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/03/2023]
Abstract
Multiplexing enables the monitoring of hundreds to thousands of proteins in quantitative proteomics analyses and increases sample throughput. In most mass-spectrometry-based proteomics workflows, multiplexing is achieved by labeling biological samples with heavy isotopes via precursor isotopic labeling or isobaric tagging. Enhanced multiplexing strategies, such as combined precursor isotopic labeling and isobaric tagging (cPILOT), combine multiple technologies to afford an even higher sample throughput. Critical to enhanced multiplexing analyses is ensuring that analytical performance is optimal and that missingness of sample channels is minimized. Automation of sample preparation steps and use of quality control (QC) metrics can be incorporated into multiplexing analyses and reduce the likelihood of missing information, thus maximizing the amount of usable quantitative data. Here, we implemented QC metrics previously developed in our laboratory to evaluate a 36-plex cPILOT experiment that encompassed 144 mouse samples of various tissue types, time points, genotypes, and biological replicates. The evaluation focuses on the use of a sample pool generated from all samples in the experiment to monitor the daily instrument performance and to provide a means for data normalization across sample batches. Our results show that tracking QC metrics enabled the quantification of ∼7000 proteins in each sample batch, of which ∼70% had minimal missing values across up to 36 sample channels. Implementation of QC metrics for future cPILOT studies as well as other enhanced multiplexing strategies will help yield high-quality data sets.
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Affiliation(s)
- Bailey L Bowser
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States
| | - Khiry L Patterson
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States
| | - Renã As Robinson
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee 37232, United States
- Vanderbilt Memory & Alzheimer's Center, Nashville, Tennessee 37212, United States
- Vanderbilt Institute of Chemical Biology, Nashville, Tennessee 37232, United States
- Vanderbilt Brain Institute, Nashville, Tennessee 37232, United States
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11
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Crotty EE, Wilson AL, Davidson T, Tahiri S, Gust J, Griesinger AM, Venkataraman S, Park JR, Mueller S, Rood BR, Hwang EI, Wang LD, Vitanza NA. Cellular Therapy for Children with Central Nervous System Tumors: Mining and Mapping the Correlative Data. Curr Oncol Rep 2023; 25:847-855. [PMID: 37160547 PMCID: PMC10326126 DOI: 10.1007/s11912-023-01423-3] [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] [Accepted: 04/04/2023] [Indexed: 05/11/2023]
Abstract
PURPOSE OF REVIEW Correlative studies should leverage clinical trial frameworks to conduct biospecimen analyses that provide insight into the bioactivity of the intervention and facilitate iteration toward future trials that further improve patient outcomes. In pediatric cellular immunotherapy trials, correlative studies enable deeper understanding of T cell mobilization, durability of immune activation, patterns of toxicity, and early detection of treatment response. Here, we review the correlative science in adoptive cell therapy (ACT) for childhood central nervous system (CNS) tumors, with a focus on existing chimeric antigen receptor (CAR) and T cell receptor (TCR)-expressing T cell therapies. RECENT FINDINGS We highlight long-standing and more recently understood challenges for effective alignment of correlative data and offer practical considerations for current and future approaches to multi-omic analysis of serial tumor, serum, and cerebrospinal fluid (CSF) biospecimens. We highlight the preliminary success in collecting serial cytokine and proteomics from patients with CNS tumors on ACT clinical trials.
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Affiliation(s)
- Erin E Crotty
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, M/S JMB-8, 1900 9thAvenue, Seattle, WA, 98101, USA
- Department of Pediatrics, Seattle Children's Hospital, University of Washington, Seattle, WA, USA
| | | | - Tom Davidson
- Cancer and Blood Disease Institute, Keck School of Medicine, Children's Hospital Los Angeles, University of Southern California, Los Angeles, CA, USA
| | - Sophia Tahiri
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, M/S JMB-8, 1900 9thAvenue, Seattle, WA, 98101, USA
| | - Juliane Gust
- Division of Pediatric Neurology, Department of Neurology, University of Washington, Seattle, WA, USA
- Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, WA, USA
| | - Andrea M Griesinger
- Morgan Adams Foundation Pediatric Brain Tumor Research Program, Children's Hospital Colorado, Aurora, CO, USA
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Sujatha Venkataraman
- Morgan Adams Foundation Pediatric Brain Tumor Research Program, Children's Hospital Colorado, Aurora, CO, USA
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Julie R Park
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, M/S JMB-8, 1900 9thAvenue, Seattle, WA, 98101, USA
- Department of Pediatrics, Seattle Children's Hospital, University of Washington, Seattle, WA, USA
- Seattle Children's Therapeutics, Seattle, WA, USA
| | - Sabine Mueller
- Department of Neurology, Neurosurgery, and Pediatrics, University of California San Francisco, San Francisco, CA, USA
| | - Brian R Rood
- Center for Cancer and Blood Disorders, Children's National Hospital, Washington, DC, USA
| | - Eugene I Hwang
- Center for Cancer and Blood Disorders, Children's National Hospital, Washington, DC, USA
| | - Leo D Wang
- Departments of Pediatrics and ImmunoOncology, City of Hope, Duarte, CA, USA
| | - Nicholas A Vitanza
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, M/S JMB-8, 1900 9thAvenue, Seattle, WA, 98101, USA.
- Department of Pediatrics, Seattle Children's Hospital, University of Washington, Seattle, WA, USA.
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.
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12
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Mohammed Y, Goodlett D, Borchers CH. Absolute Quantitative Targeted Proteomics Assays for Plasma Proteins. Methods Mol Biol 2023; 2628:439-473. [PMID: 36781801 DOI: 10.1007/978-1-0716-2978-9_27] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2023]
Abstract
Preclinical and clinical trials require rapid, precise, and multiplexed analytical methods to characterize the complex samples and to allow high-throughput biomarker monitoring with low consumption of sample material. Targeted proteomics has been used to address these challenges when quantifying protein abundances in complex biological matrices. In many of these studies, blood plasma is collected either as the main research or diagnostic sample or in combination with other specimens. Mass spectrometry (MS)-based targeted proteomics using multiple reaction monitoring (MRM) or parallel reaction monitoring (PRM) with stable isotope-labeled internal standard (SIS) peptides allows robust characterization of blood plasma protein via absolute quantification. Compared to other commonly used technologies like enzyme-linked immunosorbent assay (ELISA), targeted proteomics is faster, more sensitive, and more cost-effective. Here we describe a protocol for the quantification of proteins in blood plasma using targeted MRM proteomics with heavy-labeled internal standards. The 270-protein panel allows rapid and robust absolute quantitative proteomic characterization of blood plasma in a 1 h gradient. The method we describe here works for non-depleted plasma, which makes it simple and easy to implement. Moreover, the protocol works with the two most commonly used blood plasma collection methods used in practice, namely, either K2EDTA or sodium citrate as anticoagulants.
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Affiliation(s)
- Yassene Mohammed
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands. .,University of Victoria - Genome BC Proteomics Centre, Victoria, BC, Canada.
| | - David Goodlett
- University of Victoria - Genome BC Proteomics Centre, Victoria, BC, Canada.,Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC, Canada.,University of Gdansk, International Centre for Cancer Vaccine Science, Gdansk, Poland
| | - Christoph H Borchers
- Proteomics Centre, Segal Cancer Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, QC, Canada.,Gerald Bronfman Department of Oncology, Jewish General Hospital, Montreal, QC, Canada.,Division of Experimental Medicine, McGill University, Montreal, QC, Canada.,Department of Pathology, McGill University, Montreal, QC, Canada
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13
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Vitanza NA, Wilson AL, Huang W, Seidel K, Brown C, Gustafson JA, Yokoyama JK, Johnson AJ, Baxter BA, Koning RW, Reid AN, Meechan M, Biery MC, Myers C, Rawlings-Rhea SD, Albert CM, Browd SR, Hauptman JS, Lee A, Ojemann JG, Berens ME, Dun MD, Foster JB, Crotty EE, Leary SE, Cole BL, Perez FA, Wright JN, Orentas RJ, Chour T, Newell EW, Whiteaker JR, Zhao L, Paulovich AG, Pinto N, Gust J, Gardner RA, Jensen MC, Park JR. Intraventricular B7-H3 CAR T Cells for Diffuse Intrinsic Pontine Glioma: Preliminary First-in-Human Bioactivity and Safety. Cancer Discov 2023; 13:114-131. [PMID: 36259971 PMCID: PMC9827115 DOI: 10.1158/2159-8290.cd-22-0750] [Citation(s) in RCA: 72] [Impact Index Per Article: 72.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 09/13/2022] [Accepted: 10/13/2022] [Indexed: 01/16/2023]
Abstract
Diffuse intrinsic pontine glioma (DIPG) remains a fatal brainstem tumor demanding innovative therapies. As B7-H3 (CD276) is expressed on central nervous system (CNS) tumors, we designed B7-H3-specific chimeric antigen receptor (CAR) T cells, confirmed their preclinical efficacy, and opened BrainChild-03 (NCT04185038), a first-in-human phase I trial administering repeated locoregional B7-H3 CAR T cells to children with recurrent/refractory CNS tumors and DIPG. Here, we report the results of the first three evaluable patients with DIPG (including two who enrolled after progression), who received 40 infusions with no dose-limiting toxicities. One patient had sustained clinical and radiographic improvement through 12 months on study. Patients exhibited correlative evidence of local immune activation and persistent cerebrospinal fluid (CSF) B7-H3 CAR T cells. Targeted mass spectrometry of CSF biospecimens revealed modulation of B7-H3 and critical immune analytes (CD14, CD163, CSF-1, CXCL13, and VCAM-1). Our data suggest the feasibility of repeated intracranial B7-H3 CAR T-cell dosing and that intracranial delivery may induce local immune activation. SIGNIFICANCE This is the first report of repeatedly dosed intracranial B7-H3 CAR T cells for patients with DIPG and includes preliminary tolerability, the detection of CAR T cells in the CSF, CSF cytokine elevations supporting locoregional immune activation, and the feasibility of serial mass spectrometry from both serum and CSF. This article is highlighted in the In This Issue feature, p. 1.
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Affiliation(s)
- Nicholas A. Vitanza
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, Seattle, Washington.,Department of Pediatrics, Seattle Children's Hospital, University of Washington, Seattle, Washington.,Corresponding Author: Nicholas A. Vitanza, Seattle Children's Research Institute, M/S JMB-8, 1900 9th Avenue, Seattle, WA 98101. Phone: 206-884-4084; E-mail:
| | | | - Wenjun Huang
- Seattle Children's Therapeutics, Seattle, Washington
| | - Kristy Seidel
- Seattle Children's Therapeutics, Seattle, Washington
| | - Christopher Brown
- Seattle Children's Therapeutics, Seattle, Washington.,Therapeutic Cell Production Core, Seattle Children's Research Institute, Seattle, Washington
| | | | | | | | | | | | | | - Michael Meechan
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, Seattle, Washington
| | - Matthew C. Biery
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, Seattle, Washington
| | - Carrie Myers
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, Seattle, Washington
| | | | - Catherine M. Albert
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, Seattle, Washington.,Department of Pediatrics, Seattle Children's Hospital, University of Washington, Seattle, Washington
| | - Samuel R. Browd
- Division of Neurosurgery, Seattle Children's Hospital and Department of Neurological Surgery, University of Washington, Seattle, Washington
| | - Jason S. Hauptman
- Division of Neurosurgery, Seattle Children's Hospital and Department of Neurological Surgery, University of Washington, Seattle, Washington
| | - Amy Lee
- Division of Neurosurgery, Seattle Children's Hospital and Department of Neurological Surgery, University of Washington, Seattle, Washington
| | - Jeffrey G. Ojemann
- Division of Neurosurgery, Seattle Children's Hospital and Department of Neurological Surgery, University of Washington, Seattle, Washington
| | - Michael E. Berens
- Cancer and Cell Biology Division, The Translational Genomics Research Institute (TGen), Phoenix, Arizona
| | - Matthew D. Dun
- School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, Callaghan, Australia.,Precision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, Australia
| | - Jessica B. Foster
- Division of Oncology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.,Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Erin E. Crotty
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, Seattle, Washington.,Department of Pediatrics, Seattle Children's Hospital, University of Washington, Seattle, Washington
| | - Sarah E.S. Leary
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, Seattle, Washington.,Department of Pediatrics, Seattle Children's Hospital, University of Washington, Seattle, Washington
| | - Bonnie L. Cole
- Department of Laboratories, Seattle Children's Hospital, Seattle, Washington.,Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, Washington
| | - Francisco A. Perez
- Department of Radiology, Seattle Children's Hospital, Seattle, Washington
| | - Jason N. Wright
- Department of Radiology, Seattle Children's Hospital, Seattle, Washington
| | - Rimas J. Orentas
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, Seattle, Washington.,Department of Pediatrics, Seattle Children's Hospital, University of Washington, Seattle, Washington
| | - Tony Chour
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, Washington.,Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Evan W. Newell
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, Washington.,Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | | | - Lei Zhao
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Amanda G. Paulovich
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Navin Pinto
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, Seattle, Washington.,Department of Pediatrics, Seattle Children's Hospital, University of Washington, Seattle, Washington
| | - Juliane Gust
- Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, Washington.,Division of Pediatric Neurology, Department of Neurology, University of Washington, Seattle, Washington
| | - Rebecca A. Gardner
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, Seattle, Washington.,Department of Pediatrics, Seattle Children's Hospital, University of Washington, Seattle, Washington.,Seattle Children's Therapeutics, Seattle, Washington
| | | | - Julie R. Park
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, Seattle, Washington.,Department of Pediatrics, Seattle Children's Hospital, University of Washington, Seattle, Washington.,Seattle Children's Therapeutics, Seattle, Washington
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14
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Mehta D, Ahkami AH, Walley J, Xu SL, Uhrig RG. The incongruity of validating quantitative proteomics using western blots. NATURE PLANTS 2022; 8:1320-1321. [PMID: 36456804 DOI: 10.1038/s41477-022-01314-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Affiliation(s)
- Devang Mehta
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
- Department of Biosystems, KU Leuven, Leuven, Belgium.
- Plant Cell Atlas Proteomics Committee, Stanford, CA, USA.
| | - Amir H Ahkami
- Plant Cell Atlas Proteomics Committee, Stanford, CA, USA
- Environmental Molecular Sciences Laboratory (EMSL), Pacific Northwest National Laboratories, Richland, WA, USA
- School of Biological Science (SBS), Washington State University (WSU), Pullman, WA, USA
| | - Justin Walley
- Plant Cell Atlas Proteomics Committee, Stanford, CA, USA
- Iowa State University, Ames, IA, USA
| | - Shou-Ling Xu
- Plant Cell Atlas Proteomics Committee, Stanford, CA, USA
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA, USA
| | - R Glen Uhrig
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
- Plant Cell Atlas Proteomics Committee, Stanford, CA, USA.
- Department of Biochemistry, University of Alberta, Edmonton, Alberta, Canada.
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15
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Translational proteomics and phosphoproteomics: Tissue to extracellular vesicles. Adv Clin Chem 2022; 112:119-153. [PMID: 36642482 DOI: 10.1016/bs.acc.2022.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
We are currently experiencing a rapidly developing era in terms of translational and clinical medical sciences. The relatively mature state of nucleic acid examination has significantly improved our understanding of disease mechanism and therapeutic potential of personalized treatment, but misses a large portion of phenotypic disease information. Proteins, in particular phosphorylation events that regulates many cellular functions, could provide real-time information for disease onset, progression and treatment efficacy. The technical advances in liquid chromatography and mass spectrometry have realized large-scale and unbiased proteome and phosphoproteome analyses with disease relevant samples such as tissues. However, tissue biopsy still has multiple shortcomings, such as invasiveness of sample collection, potential health risk for patients, difficulty in protein preservation and extreme heterogeneity. Recently, extracellular vesicles (EVs) have offered a great promise as a unique source of protein biomarkers for non-invasive liquid biopsy. Membranous EVs provide stable preservation of internal proteins and especially labile phosphoproteins, which is essential for effective routine biomarker detection. To aid efficient EV proteomic and phosphoproteomic analyses, recent developments showcase clinically-friendly EV techniques, facilitating diagnostic and therapeutic applications. Ultimately, we envision that with streamlined sample preparation from tissues and EVs proteomics and phosphoproteomics analysis will become routine in clinical settings.
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16
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Vanderboom PM, Renuse S, Maus AD, Madugundu AK, Kemp JV, Gurtner KM, Singh RJ, Grebe SK, Pandey A, Dasari S. Machine Learning-Based Fragment Selection Improves the Performance of Qualitative PRM Assays. J Proteome Res 2022; 21:2045-2054. [PMID: 35849720 DOI: 10.1021/acs.jproteome.2c00156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Targeted mass spectrometry-based platforms have become a valuable tool for the sensitive and specific detection of protein biomarkers in clinical and research settings. Traditionally, developing a targeted assay for peptide quantification has involved manually preselecting several fragment ions and establishing a limit of detection (LOD) and a lower limit of quantitation (LLOQ) for confident detection of the target. Established thresholds such as LOD and LLOQ, however, inherently sacrifice sensitivity to afford specificity. Here, we demonstrate that machine learning can be applied to qualitative PRM assays to discriminate positive from negative samples more effectively than a traditional approach utilizing conventional methods. To demonstrate the utility of this method, we trained an ensemble machine learning model using 282 SARS-CoV-2 positive and 994 SARS-CoV-2 negative nasopharyngeal swabs (NP swab) analyzed using a targeted PRM method. This model was then validated using an independent set of 200 positive and 150 negative samples and achieved a sensitivity of 92% relative to results obtained by RT-PCR, which was superior to a traditional approach that resulted in 86.5% sensitivity when analyzing the same data. These results demonstrate that machine learning can be applied to qualitative PRM assays and results in superior performance relative to traditional methods.
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Affiliation(s)
- Patrick M Vanderboom
- Department of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Santosh Renuse
- Department of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Mayo Clinic, Rochester, Minnesota 55905, United States.,Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Anthony D Maus
- Department of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Anil K Madugundu
- Department of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Mayo Clinic, Rochester, Minnesota 55905, United States.,Institute of Bioinformatics, International Technology Park, Bangalore 560066, Karnataka, India.,Manipal Academy of Higher Education, Manipal 576104, Karnataka, India.,Center for Molecular Medicine, National Institute of Mental Health and Neurosciences, Hosur Road, Bangalore 560029, Karnataka, India
| | - Jennifer V Kemp
- Department of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Kari M Gurtner
- Department of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Ravinder J Singh
- Department of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Stefan K Grebe
- Department of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Mayo Clinic, Rochester, Minnesota 55905, United States.,Department of Medicine, Division of Endocrinology, Mayo Clinic, Rochester, Minnesota 55902, United States
| | - Akhilesh Pandey
- Department of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Mayo Clinic, Rochester, Minnesota 55905, United States.,Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota 55905, United States.,Center for Molecular Medicine, National Institute of Mental Health and Neurosciences, Hosur Road, Bangalore 560029, Karnataka, India
| | - Surendra Dasari
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota 55905, United States
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17
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Kennedy MA, Tyl MD, Betsinger CN, Federspiel JD, Sheng X, Arbuckle JH, Kristie TM, Cristea IM. A TRUSTED targeted mass spectrometry assay for pan-herpesvirus protein detection. Cell Rep 2022; 39:110810. [PMID: 35545036 PMCID: PMC9245836 DOI: 10.1016/j.celrep.2022.110810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 02/11/2022] [Accepted: 04/21/2022] [Indexed: 11/23/2022] Open
Abstract
The presence and abundance of viral proteins within host cells are part of the essential signatures of the cellular stages of viral infections. However, methods that can comprehensively detect and quantify these proteins are still limited, particularly for viruses with large protein coding capacity. Here, we design and experimentally validate a mass spectrometry-based Targeted herpesviRUS proTEin Detection (TRUSTED) assay for monitoring human viruses representing the three Herpesviridae subfamilies—herpes simplex virus type 1, human cytomegalovirus (HCMV), and Kaposi sarcoma-associated herpesvirus. We demonstrate assay applicability for (1) capturing the temporal cascades of viral replication, (2) detecting proteins throughout a range of virus concentrations and in in vivo models of infection, (3) assessing the effects of clinical therapeutic agents and sirtuin-modulating compounds, (4) studies using different laboratory and clinical viral strains, and (5) discovering a role for carbamoyl phosphate synthetase 1 in supporting HCMV replication. Herpesviruses encode many proteins, making it difficult to comprehensively monitor viral protein levels by traditional approaches. Kennedy et al. develop a set of targeted mass spectrometry-based assays for measuring herpesvirus protein levels spanning all virus subfamilies (α, β, and γ) and demonstrate their usefulness for a wide range of applications.
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Affiliation(s)
- Michelle A Kennedy
- Department of Molecular Biology, Princeton University, Lewis Thomas Laboratory, Washington Road, Princeton, NJ 08544, USA
| | - Matthew D Tyl
- Department of Molecular Biology, Princeton University, Lewis Thomas Laboratory, Washington Road, Princeton, NJ 08544, USA
| | - Cora N Betsinger
- Department of Molecular Biology, Princeton University, Lewis Thomas Laboratory, Washington Road, Princeton, NJ 08544, USA
| | - Joel D Federspiel
- Department of Molecular Biology, Princeton University, Lewis Thomas Laboratory, Washington Road, Princeton, NJ 08544, USA
| | - Xinlei Sheng
- Department of Molecular Biology, Princeton University, Lewis Thomas Laboratory, Washington Road, Princeton, NJ 08544, USA
| | - Jesse H Arbuckle
- Laboratory of Viral Diseases, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Thomas M Kristie
- Laboratory of Viral Diseases, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Ileana M Cristea
- Department of Molecular Biology, Princeton University, Lewis Thomas Laboratory, Washington Road, Princeton, NJ 08544, USA.
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18
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UPLC-MS/MS-Based Analysis of Trastuzumab in Plasma Samples: Application in Breast Cancer Patients Sample Monitoring. Processes (Basel) 2022. [DOI: 10.3390/pr10030509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
Trastuzumab is a target-based recombinant humanized IgG1 monoclonal antibody (mAbs), extensively employed for treatment of metastatic breast cancer with human epidermal growth receptor 2 (HER2) overexpression. Studies around the world have reported that mAbs have substantial inter-patient unpredictable absorption, distribution, metabolism, and excretion (ADME-pharmacokinetics) because of multiple elements manipulating the concentration of mAbs in plasma. Herein, we have established a bioanalytical technique using UPLC-MS/MS with an easy sample workup method and in-solution digestion protocol to assay the trastuzumab plasma samples from breast cancer patients in clinical studies. Surrogated proteolytic peptides were used for accurate quantification of trastuzumab (CanMab) with a trastuzumab signature peptide with [13C6, 15N4]-arginine and [13C6, 15N2]-lysine stable isotope-labeled (SIL) peptide. Experiments to validate the method were accurately carried out according to the guidelines mentioned in the bioanalytical method validation protocol. The evaluation established excellent linearity over a wide range of 5–500 µg/mL. The experimental procedure was efficaciously performed in a pilot study of five breast cancer patients and residual concentrations of drugs from responding and non-responding subjects were compared. The receiver operating characteristic (ROC) examination displayed that 52.25 µg/mL was the Cmin threshold predictive response with a satisfactory sensitivity of 88.58% and specificity of 79.25%.
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19
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Reinspection of a Clinical Proteomics Tumor Analysis Consortium (CPTAC) Dataset with Cloud Computing Reveals Abundant Post-Translational Modifications and Protein Sequence Variants. Cancers (Basel) 2021; 13:cancers13205034. [PMID: 34680183 PMCID: PMC8534219 DOI: 10.3390/cancers13205034] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 09/14/2021] [Accepted: 10/01/2021] [Indexed: 12/14/2022] Open
Abstract
The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has provided some of the most in-depth analyses of the phenotypes of human tumors ever constructed. Today, the majority of proteomic data analysis is still performed using software housed on desktop computers which limits the number of sequence variants and post-translational modifications that can be considered. The original CPTAC studies limited the search for PTMs to only samples that were chemically enriched for those modified peptides. Similarly, the only sequence variants considered were those with strong evidence at the exon or transcript level. In this multi-institutional collaborative reanalysis, we utilized unbiased protein databases containing millions of human sequence variants in conjunction with hundreds of common post-translational modifications. Using these tools, we identified tens of thousands of high-confidence PTMs and sequence variants. We identified 4132 phosphorylated peptides in nonenriched samples, 93% of which were confirmed in the samples which were chemically enriched for phosphopeptides. In addition, our results also cover 90% of the high-confidence variants reported by the original proteogenomics study, without the need for sample specific next-generation sequencing. Finally, we report fivefold more somatic and germline variants that have an independent evidence at the peptide level, including mutations in ERRB2 and BCAS1. In this reanalysis of CPTAC proteomic data with cloud computing, we present an openly available and searchable web resource of the highest-coverage proteomic profiling of human tumors described to date.
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20
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Keshishian H, McDonald ER, Mundt F, Melanson R, Krug K, Porter DA, Wallace L, Forestier D, Rabasha B, Marlow SE, Jane‐Valbuena J, Todres E, Specht H, Robinson ML, Jean Beltran PM, Babur O, Olive ME, Golji J, Kuhn E, Burgess M, MacMullan MA, Rejtar T, Wang K, Mani DR, Satpathy S, Gillette MA, Sellers WR, Carr SA. A highly multiplexed quantitative phosphosite assay for biology and preclinical studies. Mol Syst Biol 2021; 17:e10156. [PMID: 34569154 PMCID: PMC8474009 DOI: 10.15252/msb.202010156] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 08/19/2021] [Accepted: 08/20/2021] [Indexed: 12/14/2022] Open
Abstract
Reliable methods to quantify dynamic signaling changes across diverse pathways are needed to better understand the effects of disease and drug treatment in cells and tissues but are presently lacking. Here, we present SigPath, a targeted mass spectrometry (MS) assay that measures 284 phosphosites in 200 phosphoproteins of biological interest. SigPath probes a broad swath of signaling biology with high throughput and quantitative precision. We applied the assay to investigate changes in phospho-signaling in drug-treated cancer cell lines, breast cancer preclinical models, and human medulloblastoma tumors. In addition to validating previous findings, SigPath detected and quantified a large number of differentially regulated phosphosites newly associated with disease models and human tumors at baseline or with drug perturbation. Our results highlight the potential of SigPath to monitor phosphoproteomic signaling events and to nominate mechanistic hypotheses regarding oncogenesis, response, and resistance to therapy.
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Affiliation(s)
- Hasmik Keshishian
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | | | - Filip Mundt
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
- Present address:
Novo Nordisk Foundation Center for Protein ResearchFaculty of Health SciencesUniversity of CopenhagenCopenhagenDenmark
- Present address:
Department of Oncology and PathologyScience for Life LaboratoryKarolinska InstitutetStockholmSweden
| | - Randy Melanson
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | - Karsten Krug
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | - Dale A Porter
- Novartis Institute of Biomedical ResearchCambridgeMAUSA
- Present address:
Cedilla TherapeuticsCambridgeMAUSA
| | - Luke Wallace
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | - Dominique Forestier
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | - Bokang Rabasha
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | - Sara E Marlow
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | - Judit Jane‐Valbuena
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | - Ellen Todres
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | - Harrison Specht
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | | | | | - Ozgun Babur
- Computer Science DepartmentUniversity of Massachusetts BostonBostonMAUSA
| | - Meagan E Olive
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | - Javad Golji
- Novartis Institute of Biomedical ResearchCambridgeMAUSA
| | - Eric Kuhn
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | - Michael Burgess
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | - Melanie A MacMullan
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | - Tomas Rejtar
- Novartis Institute of Biomedical ResearchCambridgeMAUSA
| | - Karen Wang
- Novartis Institute of Biomedical ResearchCambridgeMAUSA
| | - DR Mani
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | - Shankha Satpathy
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
| | - Michael A Gillette
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
- Division of Pulmonary and Critical Care MedicineMassachusetts General HospitalBostonMAUSA
| | - William R Sellers
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
- Department of Medical OncologyDana‐Farber Cancer Institute and Harvard Medical SchoolBostonMAUSA
| | - Steven A Carr
- Broad Institute of Massachusetts Institute of Technology and HarvardCambridgeMAUSA
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21
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Coppieters G, Deventer K, Van Eenoo P, Judák P. Combining direct urinary injection with automated filtration and nanoflow LC-MS for the confirmatory analysis of doping-relevant small peptide hormones. J Chromatogr B Analyt Technol Biomed Life Sci 2021; 1179:122842. [PMID: 34216910 DOI: 10.1016/j.jchromb.2021.122842] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 06/16/2021] [Accepted: 06/18/2021] [Indexed: 01/17/2023]
Abstract
Nano-liquid chromatography (nanoLC) has proven itself as a powerful tool and its scope entails various applications in (bio)analytical fields. Operation at low (nL/min) flow rates in combination with reduced inner dimensions (ID < 100 µm), leads to significantly enhanced sensitivity when coupled with electrospray ionization-mass spectrometry (ESI-MS). Challenges that remain for the routine implementation of such miniaturized setups are related to clogging of the system and robustness in general, and thus the application of tedious sample preparation steps. To improve ruggedness, a filter placed upstream in the LC prevents particles from entering and clogging the system. This so-called online automatic filtration and filter back-flush (AFFL) system was combined with nanoLC and the direct injection principle for the sensitive confirmatory analysis of fifty different doping-relevant peptides in urine. The presented assay was fully validated for routine purposes according to selectivity and matrix interference, limit of identification (LOI), carryover, matrix effect, sample extract stability, analysis of educational external quality assessment (EQAS) samples, robustness of the online AFFL-setup and retention time stability. It was also fully compliant with the most recent minimum required performance levels (MRPL) and chromatographic/mass spectrometric identification criteria (IDCR), as imposed by the World Anti-Doping Agency (WADA). In the absence of labor-intensive sample preparation, the application of AFFL allowed for the injection of diluted urine samples without any noticeable pressure buildup in the nanoLC system. Contrary to earlier observations by our group and others, the addition of dimethylsulfoxide (DMSO) to the mobile phase did not enhance sensitivity in the presented nanoflow setup, yet was beneficial to reduce carry over. Although the robustness of the presented setup was evaluated only for the analysis of diluted urine samples, it is entirely conceivable that routine applications employing other matrices and currently running on analytical scale LC instruments could be transferred to micro/nanoLC scale systems to reach lower detection limits.
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Affiliation(s)
- Gilles Coppieters
- Doping Control Laboratory (DoCoLab), Ghent University, Department Diagnostic Sciences, Ottergemsesteenweg 460, B-9000 Ghent, Belgium.
| | - Koen Deventer
- Doping Control Laboratory (DoCoLab), Ghent University, Department Diagnostic Sciences, Ottergemsesteenweg 460, B-9000 Ghent, Belgium
| | - Peter Van Eenoo
- Doping Control Laboratory (DoCoLab), Ghent University, Department Diagnostic Sciences, Ottergemsesteenweg 460, B-9000 Ghent, Belgium
| | - Péter Judák
- Doping Control Laboratory (DoCoLab), Ghent University, Department Diagnostic Sciences, Ottergemsesteenweg 460, B-9000 Ghent, Belgium
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22
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Orsburn BC. Evaluation of the Sensitivity of Proteomics Methods Using the Absolute Copy Number of Proteins in a Single Cell as a Metric. Proteomes 2021; 9:34. [PMID: 34287363 PMCID: PMC8293326 DOI: 10.3390/proteomes9030034] [Citation(s) in RCA: 145] [Impact Index Per Article: 48.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 07/13/2021] [Accepted: 07/15/2021] [Indexed: 01/24/2023] Open
Abstract
Proteomic technology has improved at a staggering pace in recent years, with even practitioners challenged to keep up with new methods and hardware. The most common metric used for method performance is the number of peptides and proteins identified. While this metric may be helpful for proteomics researchers shopping for new hardware, this is often not the most biologically relevant metric. Biologists often utilize proteomics in the search for protein regulators that are of a lower relative copy number in the cell. In this review, I re-evaluate untargeted proteomics data using a simple graphical representation of the absolute copy number of proteins present in a single cancer cell as a metric. By comparing single-shot proteomics data to the coverage of the most in-depth proteomic analysis of that cell line acquired to date, we can obtain a rapid metric of method performance. Using a simple copy number metric allows visualization of how proteomics has developed in both sensitivity and overall dynamic range when using both relatively long and short acquisition times. To enable reanalysis beyond what is presented here, two available web applications have been developed for single- and multi-experiment comparisons with reference protein copy number data for multiple cell lines and organisms.
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Affiliation(s)
- Benjamin C Orsburn
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University, Baltimore, MD 21205, USA
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23
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Kennedy JJ, Whiteaker JR, Kennedy LC, Bosch DE, Lerch ML, Schoenherr RM, Zhao L, Lin C, Chowdhury S, Kilgore MR, Allison KH, Wang P, Hoofnagle AN, Baird GS, Paulovich AG. Quantification of Human Epidermal Growth Factor Receptor 2 by Immunopeptide Enrichment and Targeted Mass Spectrometry in Formalin-Fixed Paraffin-Embedded and Frozen Breast Cancer Tissues. Clin Chem 2021; 67:1008-1018. [PMID: 34136904 DOI: 10.1093/clinchem/hvab047] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 03/03/2021] [Indexed: 11/12/2022]
Abstract
BACKGROUND Conventional HER2-targeting therapies improve outcomes for patients with HER2-positive breast cancer (BC), defined as tumors showing HER2 protein overexpression by immunohistochemistry and/or ERBB2 gene amplification determined by in situ hybridization (ISH). Emerging HER2-targeting compounds show benefit in some patients with neither HER2 protein overexpression nor ERBB2 gene amplification, creating a need for new assays to select HER2-low tumors for treatment with these compounds. We evaluated the analytical performance of a targeted mass spectrometry-based assay for quantifying HER2 protein in formalin-fixed paraffin-embedded (FFPE) and frozen BC biopsies. METHODS We used immunoaffinity-enrichment coupled to multiple reaction monitoring-mass spectrometry (immuno-MRM-MS) to quantify HER2 protein (as peptide GLQSLPTHDPSPLQR) in 96 frozen and 119 FFPE BC biopsies. We characterized linearity, lower limit of quantification (LLOQ), and intra- and inter-day variation of the assay in frozen and FFPE tissue matrices. We determined concordance between HER2 immuno-MRM-MS and predicate immunohistochemistry and ISH assays and examined the benefit of multiplexing the assay to include proteins expressed in tumor subcompartments (e.g., stroma, adipose, lymphocytes, epithelium) to account for tissue heterogeneity. RESULTS HER2 immuno-MRM-MS assay linearity was ≥103, assay coefficient of variation was 7.8% (FFPE) and 5.9% (frozen) for spiked-in analyte, and 7.7% (FFPE) and 7.9% (frozen) for endogenous measurements. Immuno-MRM-MS-based HER2 measurements strongly correlated with predicate assay HER2 determinations, and concordance was improved by normalizing to glyceraldehyde-3-phosphate dehydrogenase. HER2 was quantified above the LLOQ in all tumors. CONCLUSIONS Immuno-MRM-MS can be used to quantify HER2 in FFPE and frozen BC biopsies, even at low HER2 expression levels.
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Affiliation(s)
- Jacob J Kennedy
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Jeffrey R Whiteaker
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Laura C Kennedy
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dustin E Bosch
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Melissa L Lerch
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Regine M Schoenherr
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Lei Zhao
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - ChenWei Lin
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Shrabanti Chowdhury
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mark R Kilgore
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Kimberly H Allison
- Department of Pathology, Stanford University Medical Center, Palo Alto, CA, USA
| | - Pei Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrew N Hoofnagle
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA
| | - Geoffrey Stuart Baird
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA
| | - Amanda G Paulovich
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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24
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Melby JA, Roberts DS, Larson EJ, Brown KA, Bayne EF, Jin S, Ge Y. Novel Strategies to Address the Challenges in Top-Down Proteomics. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:1278-1294. [PMID: 33983025 PMCID: PMC8310706 DOI: 10.1021/jasms.1c00099] [Citation(s) in RCA: 93] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Top-down mass spectrometry (MS)-based proteomics is a powerful technology for comprehensively characterizing proteoforms to decipher post-translational modifications (PTMs) together with genetic variations and alternative splicing isoforms toward a proteome-wide understanding of protein functions. In the past decade, top-down proteomics has experienced rapid growth benefiting from groundbreaking technological advances, which have begun to reveal the potential of top-down proteomics for understanding basic biological functions, unraveling disease mechanisms, and discovering new biomarkers. However, many challenges remain to be comprehensively addressed. In this Account & Perspective, we discuss the major challenges currently facing the top-down proteomics field, particularly in protein solubility, proteome dynamic range, proteome complexity, data analysis, proteoform-function relationship, and analytical throughput for precision medicine. We specifically review the major technology developments addressing these challenges with an emphasis on our research group's efforts, including the development of top-down MS-compatible surfactants for protein solubilization, functionalized nanoparticles for the enrichment of low-abundance proteoforms, strategies for multidimensional chromatography separation of proteins, and a new comprehensive user-friendly software package for top-down proteomics. We have also made efforts to connect proteoforms with biological functions and provide our visions on what the future holds for top-down proteomics.
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Affiliation(s)
- Jake A Melby
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - David S Roberts
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Eli J Larson
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Kyle A Brown
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
- Department of Surgery, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Elizabeth F Bayne
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Song Jin
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Ying Ge
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
- Human Proteomics Program, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
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25
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Serum N-glycan profiles differ for various breast cancer subtypes. Glycoconj J 2021; 38:387-395. [PMID: 33877489 PMCID: PMC8116229 DOI: 10.1007/s10719-021-10001-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 03/15/2021] [Accepted: 04/12/2021] [Indexed: 12/09/2022]
Abstract
Breast cancer is the most prevalent cancer in women. Early detection of this disease improves survival and therefore population screenings, based on mammography, are performed. However, the sensitivity of this screening modality is not optimal and new screening methods, such as blood tests, are being explored. Most of the analyses that aim for early detection focus on proteins in the bloodstream. In this study, the biomarker potential of total serum N-glycosylation analysis was explored with regard to detection of breast cancer. In an age-matched case-control setup serum protein N-glycan profiles from 145 breast cancer patients were compared to those from 171 healthy individuals. N-glycans were enzymatically released, chemically derivatized to preserve linkage-specificity of sialic acids and characterized by high resolution mass spectrometry. Logistic regression analysis was used to evaluate associations of specific N-glycan structures as well as N-glycosylation traits with breast cancer. In a case-control comparison three associations were found, namely a lower level of a two triantennary glycans and a higher level of one tetraantennary glycan in cancer patients. Of note, various other N-glycomic signatures that had previously been reported were not replicated in the current cohort. It was further evaluated whether the lack of replication of breast cancer N-glycomic signatures could be partly explained by the heterogenous character of the disease since the studies performed so far were based on cohorts that included diverging subtypes in different numbers. It was found that serum N-glycan profiles differed for the various cancer subtypes that were analyzed in this study.
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26
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Addona T, Abbatiello S, Carr SA. From Skepticism to Embrace: The Role of Targeted Mass Spectrometry in Validating Proteomics. Clin Chem 2021; 66:973-974. [PMID: 32628755 DOI: 10.1093/clinchem/hvaa111] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 05/01/2020] [Indexed: 12/12/2022]
Affiliation(s)
| | - Susan Abbatiello
- Department of Chemistry and Chemical Biology, Barnett Institute of Chemical and Biological Analysis, Northeastern University Boston, MA
| | - Steven A Carr
- Proteomics Group, Broad Institute of MIT and Harvard, Cambridge, MA
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27
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Michaud SA, Pětrošová H, Jackson AM, McGuire JC, Sinclair NJ, Ganguly M, Flenniken AM, Nutter LMJ, McKerlie C, Schibli D, Smith D, Borchers CH. Process and Workflow for Preparation of Disparate Mouse Tissues for Proteomic Analysis. J Proteome Res 2020; 20:305-316. [PMID: 33151080 DOI: 10.1021/acs.jproteome.0c00399] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We investigated the effect of homogenization strategy and protein precipitation on downstream protein quantitation using multiple reaction monitoring mass spectrometry (MRM-MS). Our objective was to develop a workflow capable of processing disparate tissue types with high throughput, minimal variability, and maximum purity. Similar abundances of endogenous proteins were measured in nine different mouse tissues regardless of the homogenization method used; however, protein precipitation had strong positive effects on several targets. The best throughput was achieved by lyophilizing tissues to dryness, followed by homogenization via bead-beating without sample buffer. Finally, the effect of tissue perfusion prior to dissection and collection was explored in 20 mouse tissues. MRM-MS showed decreased abundances of blood-related proteins in perfused tissues; however, complete removal was not achieved. Concentrations of nonblood proteins were largely unchanged, although significantly higher variances were observed for proteins from the perfused lung, indicating that perfusion may not be suitable for this organ. We present a simple yet effective tissue processing workflow consisting of harvest of fresh nonperfused tissue, novel lyophilization and homogenization by bead-beating, and protein precipitation. This workflow can be applied to a range of mouse tissues with the advantages of simplicity, minimal manual manipulation of samples, use of commonly available equipment, and high sample quality.
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Affiliation(s)
- Sarah A Michaud
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria V8Z 7X8, British Columbia, Canada
| | - Helena Pětrošová
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria V8Z 7X8, British Columbia, Canada
| | - Angela M Jackson
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria V8Z 7X8, British Columbia, Canada
| | - Jamie C McGuire
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria V8Z 7X8, British Columbia, Canada
| | - Nicholas J Sinclair
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria V8Z 7X8, British Columbia, Canada
| | - Milan Ganguly
- The Center for Phenogenomics, Toronto M5T 3H7, Ontario, Canada.,The Hospital for Sick Children, Toronto M5G 1X8, Ontario, Canada
| | - Ann M Flenniken
- The Center for Phenogenomics, Toronto M5T 3H7, Ontario, Canada.,Sinai Health Lunenfeld-Tanenbaum Research Institute, Toronto M5G 1X5, Ontario, Canada
| | - Lauryl M J Nutter
- The Center for Phenogenomics, Toronto M5T 3H7, Ontario, Canada.,The Hospital for Sick Children, Toronto M5G 1X8, Ontario, Canada
| | - Colin McKerlie
- The Center for Phenogenomics, Toronto M5T 3H7, Ontario, Canada.,The Hospital for Sick Children, Toronto M5G 1X8, Ontario, Canada
| | - David Schibli
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria V8Z 7X8, British Columbia, Canada
| | - Derek Smith
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria V8Z 7X8, British Columbia, Canada
| | - Christoph H Borchers
- University of Victoria-Genome British Columbia Proteomics Centre, Victoria V8Z 7X8, British Columbia, Canada.,Department of Data Intensive Science and Engineering, Skolkovo Innovation Center, Skolkovo Institute of Science and Technology, Nobel Street, Moscow 143026, Russia.,Segal Cancer Proteomics Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal H3T 1E2, Quebec, Canada.,Gerald Bronfman Department of Oncology, Jewish General Hospital, McGill University, Montreal H3T 1E2, Quebec, Canada
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Cerciello F, Choi M, Sinicropi-Yao SL, Lomeo K, Amann JM, Felley-Bosco E, Stahel RA, Robinson BWS, Creaney J, Pass HI, Vitek O, Carbone DP. Verification of a Blood-Based Targeted Proteomics Signature for Malignant Pleural Mesothelioma. Cancer Epidemiol Biomarkers Prev 2020; 29:1973-1982. [PMID: 32732250 PMCID: PMC7541795 DOI: 10.1158/1055-9965.epi-20-0543] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 06/18/2020] [Accepted: 07/27/2020] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND We have verified a mass spectrometry (MS)-based targeted proteomics signature for the detection of malignant pleural mesothelioma (MPM) from the blood. METHODS A seven-peptide biomarker MPM signature by targeted proteomics in serum was identified in a previous independent study. Here, we have verified the predictive accuracy of a reduced version of that signature, now composed of six-peptide biomarkers. We have applied liquid chromatography-selected reaction monitoring (LC-SRM), also known as multiple-reaction monitoring (MRM), for the investigation of 402 serum samples from 213 patients with MPM and 189 cancer-free asbestos-exposed donors from the United States, Australia, and Europe. RESULTS Each of the biomarkers composing the signature was independently informative, with no apparent functional or physical relation to each other. The multiplexing possibility offered by MS proteomics allowed their integration into a single signature with a higher discriminating capacity than that of the single biomarkers alone. The strategy allowed in this way to increase their potential utility for clinical decisions. The signature discriminated patients with MPM and asbestos-exposed donors with AUC of 0.738. For early-stage MPM, AUC was 0.765. This signature was also prognostic, and Kaplan-Meier analysis showed a significant difference between high- and low-risk groups with an HR of 1.659 (95% CI, 1.075-2.562; P = 0.021). CONCLUSIONS Targeted proteomics allowed the development of a multianalyte signature with diagnostic and prognostic potential for MPM from the blood. IMPACT The proteomic signature represents an additional diagnostic approach for informing clinical decisions for patients at risk for MPM.
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Affiliation(s)
- Ferdinando Cerciello
- James Thoracic Center, James Cancer Center, The Ohio State University Medical Center, Columbus, Ohio.
| | - Meena Choi
- College of Computer and Information Science, Northeastern University, Boston, Massachusetts
| | - Sara L Sinicropi-Yao
- James Thoracic Center, James Cancer Center, The Ohio State University Medical Center, Columbus, Ohio
| | - Katie Lomeo
- James Thoracic Center, James Cancer Center, The Ohio State University Medical Center, Columbus, Ohio
| | - Joseph M Amann
- James Thoracic Center, James Cancer Center, The Ohio State University Medical Center, Columbus, Ohio
| | - Emanuela Felley-Bosco
- Laboratory of Molecular Oncology, Division of Thoracic Surgery, University Hospital Zürich, Zürich, Switzerland
| | - Rolf A Stahel
- Department of Oncology, Center of Hematology and Oncology, Comprehensive Cancer Center Zürich, University Hospital Zürich, Zürich, Switzerland
| | - Bruce W S Robinson
- National Centre for Asbestos Related Disease, University of Western Australia, School of Medicine and Pharmacology, Nedlands, Western Australia
| | - Jenette Creaney
- National Centre for Asbestos Related Disease, University of Western Australia, School of Medicine and Pharmacology, Nedlands, Western Australia
| | - Harvey I Pass
- New York University, Langone Medical Center, New York, New York
| | - Olga Vitek
- College of Computer and Information Science, Northeastern University, Boston, Massachusetts
| | - David P Carbone
- James Thoracic Center, James Cancer Center, The Ohio State University Medical Center, Columbus, Ohio.
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29
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Genetics meets proteomics: perspectives for large population-based studies. Nat Rev Genet 2020; 22:19-37. [PMID: 32860016 DOI: 10.1038/s41576-020-0268-2] [Citation(s) in RCA: 163] [Impact Index Per Article: 40.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/14/2020] [Indexed: 12/22/2022]
Abstract
Proteomic analysis of cells, tissues and body fluids has generated valuable insights into the complex processes influencing human biology. Proteins represent intermediate phenotypes for disease and provide insight into how genetic and non-genetic risk factors are mechanistically linked to clinical outcomes. Associations between protein levels and DNA sequence variants that colocalize with risk alleles for common diseases can expose disease-associated pathways, revealing novel drug targets and translational biomarkers. However, genome-wide, population-scale analyses of proteomic data are only now emerging. Here, we review current findings from studies of the plasma proteome and discuss their potential for advancing biomedical translation through the interpretation of genome-wide association analyses. We highlight the challenges faced by currently available technologies and provide perspectives relevant to their future application in large-scale biobank studies.
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Ibrahim S, Froehlich BC, Aguilar-Mahecha A, Aloyz R, Poetz O, Basik M, Batist G, Zahedi RP, Borchers CH. Using Two Peptide Isotopologues as Internal Standards for the Streamlined Quantification of Low-Abundance Proteins by Immuno-MRM and Immuno-MALDI. Anal Chem 2020; 92:12407-12414. [DOI: 10.1021/acs.analchem.0c02157] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Affiliation(s)
- Sahar Ibrahim
- Segal Cancer Proteomics Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Québec H3T 1E2, Canada
| | - Bjoern C. Froehlich
- University of Victoria-Genome British Columbia Proteomics Centre, University of Victoria, Victoria V8Z 7X8, Canada
| | - Adriana Aguilar-Mahecha
- Segal Cancer Center, Lady Davis Institute for Medical Research, Sir Mortimer B. Davis Jewish General Hospital, McGill University, Montréal, Québec H3T 1E2, Canada
| | - Raquel Aloyz
- Segal Cancer Center, Lady Davis Institute for Medical Research, Sir Mortimer B. Davis Jewish General Hospital, McGill University, Montréal, Québec H3T 1E2, Canada
- Division of Experimental Medicine, McGill University, Montréal, Québec H3T 1E2, Canada
- Gerald Bronfman Department of Oncology, Jewish General Hospital, McGill University, Montréal, Québec H3T 1E2, Canada
| | - Oliver Poetz
- NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen 72770, Germany
- SIGNATOPE GmbH, Reutlingen 72770, Germany
| | - Mark Basik
- Segal Cancer Center, Lady Davis Institute for Medical Research, Sir Mortimer B. Davis Jewish General Hospital, McGill University, Montréal, Québec H3T 1E2, Canada
- Division of Experimental Medicine, McGill University, Montréal, Québec H3T 1E2, Canada
- Gerald Bronfman Department of Oncology, Jewish General Hospital, McGill University, Montréal, Québec H3T 1E2, Canada
| | - Gerald Batist
- Segal Cancer Center, Lady Davis Institute for Medical Research, Sir Mortimer B. Davis Jewish General Hospital, McGill University, Montréal, Québec H3T 1E2, Canada
- Gerald Bronfman Department of Oncology, Jewish General Hospital, McGill University, Montréal, Québec H3T 1E2, Canada
| | - René P. Zahedi
- Segal Cancer Proteomics Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Québec H3T 1E2, Canada
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Christoph H. Borchers
- Segal Cancer Proteomics Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Québec H3T 1E2, Canada
- University of Victoria-Genome British Columbia Proteomics Centre, University of Victoria, Victoria V8Z 7X8, Canada
- Gerald Bronfman Department of Oncology, Jewish General Hospital, McGill University, Montréal, Québec H3T 1E2, Canada
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
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31
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Preparation of Tissue Samples for Large-scale Quantitative Mass Spectrometric Analysis. BIOTECHNOL BIOPROC E 2020. [DOI: 10.1007/s12257-019-0495-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
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32
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Achour B, Al-Majdoub ZM, Rostami-Hodjegan A, Barber J. Mass Spectrometry of Human Transporters. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2020; 13:223-247. [PMID: 32084322 DOI: 10.1146/annurev-anchem-091719-024553] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Transporters are key to understanding how an individual will respond to a particular dose of a drug. Two patients with similar systemic concentrations may have quite different local concentrations of a drug at the required site. The transporter profile of any individual depends upon a variety of genetic and environmental factors, including genotype, age, and diet status. Robust models (virtual patients) are therefore required and these models are data hungry. Necessary data include quantitative transporter profiles at the relevant organ. Liquid chromatography with tandem mass spectrometry (LC-MS/MS) is currently the most powerful method available for obtaining this information. Challenges include sourcing the tissue, isolating the hydrophobic membrane-embedded transporter proteins, preparing the samples for MS (including proteolytic digestion), choosing appropriate quantification methodology, and optimizing the LC-MS/MS conditions. Great progress has been made with all of these, especially within the last few years, and is discussed here.
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Affiliation(s)
- Brahim Achour
- Centre for Applied Pharmacokinetic Research, School of Health Sciences, University of Manchester, Manchester M13 9PT, United Kingdom;
| | - Zubida M Al-Majdoub
- Centre for Applied Pharmacokinetic Research, School of Health Sciences, University of Manchester, Manchester M13 9PT, United Kingdom;
| | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, School of Health Sciences, University of Manchester, Manchester M13 9PT, United Kingdom;
- Certara, Princeton, New Jersey 08540, USA
| | - Jill Barber
- Centre for Applied Pharmacokinetic Research, School of Health Sciences, University of Manchester, Manchester M13 9PT, United Kingdom;
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33
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Van Gool A, Corrales F, Čolović M, Krstić D, Oliver-Martos B, Martínez-Cáceres E, Jakasa I, Gajski G, Brun V, Kyriacou K, Burzynska-Pedziwiatr I, Wozniak LA, Nierkens S, Pascual García C, Katrlik J, Bojic-Trbojevic Z, Vacek J, Llorente A, Antohe F, Suica V, Suarez G, t'Kindt R, Martin P, Penque D, Martins IL, Bodoki E, Iacob BC, Aydindogan E, Timur S, Allinson J, Sutton C, Luider T, Wittfooth S, Sammar M. Analytical techniques for multiplex analysis of protein biomarkers. Expert Rev Proteomics 2020; 17:257-273. [PMID: 32427033 DOI: 10.1080/14789450.2020.1763174] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
INTRODUCTION The importance of biomarkers for pharmaceutical drug development and clinical diagnostics is more significant than ever in the current shift toward personalized medicine. Biomarkers have taken a central position either as companion markers to support drug development and patient selection, or as indicators aiming to detect the earliest perturbations indicative of disease, minimizing therapeutic intervention or even enabling disease reversal. Protein biomarkers are of particular interest given their central role in biochemical pathways. Hence, capabilities to analyze multiple protein biomarkers in one assay are highly interesting for biomedical research. AREAS COVERED We here review multiple methods that are suitable for robust, high throughput, standardized, and affordable analysis of protein biomarkers in a multiplex format. We describe innovative developments in immunoassays, the vanguard of methods in clinical laboratories, and mass spectrometry, increasingly implemented for protein biomarker analysis. Moreover, emerging techniques are discussed with potentially improved protein capture, separation, and detection that will further boost multiplex analyses. EXPERT COMMENTARY The development of clinically applied multiplex protein biomarker assays is essential as multi-protein signatures provide more comprehensive information about biological systems than single biomarkers, leading to improved insights in mechanisms of disease, diagnostics, and the effect of personalized medicine.
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Affiliation(s)
- Alain Van Gool
- Translational Metabolic Laboratory, Department of Laboratory Medicine, Radboud Institute of Molecular Life Sciences, Radboud University Medical Center , Nijmegen, The Netherlands
| | - Fernado Corrales
- Functional Proteomics Laboratory, Centro Nacional De Biotecnología , Madrid, Spain
| | - Mirjana Čolović
- Department of Physical Chemistry, "Vinča" Institute of Nuclear Sciences, University of Belgrade , Belgrade, Serbia
| | - Danijela Krstić
- Institute of Medical Chemistry, Faculty of Medicine, University of Belgrade , Belgrade, Serbia
| | - Begona Oliver-Martos
- Neuroimmunology and Neuroinflammation Group. Instituto De Investigación Biomédica De Málaga-IBIMA. UGC Neurociencias, Hospital Regional Universitario De Málaga , Malaga, Spain
| | - Eva Martínez-Cáceres
- Immunology Division, LCMN, Germans Trias I Pujol University Hospital and Research Institute, Campus Can Ruti, Badalona, and Department of Cellular Biology, Physiology and Immunology, Universitat Autònoma De Barcelona , Cerdanyola Del Vallès, Spain
| | - Ivone Jakasa
- Laboratory for Analytical Chemistry, Department of Chemistry and Biochemistry, Faculty of Food Technology and Biotechnology, University of Zagreb , Zagreb, Croatia
| | - Goran Gajski
- Mutagenesis Unit, Institute for Medical Research and Occupational Health , Zagreb, Croatia
| | - Virginie Brun
- Université Grenoble Alpes, CEA, Inserm, IRIG, BGE , Grenoble, France
| | - Kyriacos Kyriacou
- Department of Electron Microscopy/Molecular Biology, The Cyprus School of Molecular Medicine/The Cyprus Institute of Neurology and Genetics , Nicosia, Cyprus
| | - Izabela Burzynska-Pedziwiatr
- Medical Faculty, Department of Biomedical Sciences, Chair of Medical Biology & Department of Structural Biology, Medical University of Lodz , Łódź, Poland
| | - Lucyna Alicja Wozniak
- Medical Faculty, Department of Biomedical Sciences, Chair of Medical Biology & Department of Structural Biology, Medical University of Lodz , Łódź, Poland
| | - Stephan Nierkens
- Center for Translational Immunology, University Medical Center Utrecht & Princess Máxima Center for Pediatric Oncology , Utrecht, The Netherlands
| | - César Pascual García
- Materials Research and Technology Department, Luxembourg Institute of Science and Technology (LIST) , Belvaux, Luxembourg
| | - Jaroslav Katrlik
- Department of Glycobiotechnology, Institute of Chemistry, Slovak Academy of Sciences , Bratislava, Slovakia
| | - Zanka Bojic-Trbojevic
- Laboratory for Biology of Reproduction, Institute for the Application of Nuclear Energy - INEP, University of Belgrade , Belgrade, Serbia
| | - Jan Vacek
- Department of Medical Chemistry and Biochemistry, Faculty of Medicine and Dentistry, Palacky University , Olomouc, Czech Republic
| | - Alicia Llorente
- Department of Molecular Cell Biology, Institute for Cancer Research, Oslo University Hospital , Oslo, Norway
| | - Felicia Antohe
- Proteomics Department, Institute of Cellular Biology and Pathology "N. Simionescu" of the Romanian Academy , Bucharest, Romania
| | - Viorel Suica
- Proteomics Department, Institute of Cellular Biology and Pathology "N. Simionescu" of the Romanian Academy , Bucharest, Romania
| | - Guillaume Suarez
- Center for Primary Care and Public Health (Unisanté), University of Lausanne , Lausanne, Switzerland
| | - Ruben t'Kindt
- Research Institute for Chromatography (RIC) , Kortrijk, Belgium
| | - Petra Martin
- Department of Medical Oncology, Midland Regional Hospital Tullamore/St. James's Hospital , Dublin, Ireland
| | - Deborah Penque
- Human Genetics Department, Instituto Nacional De Saúde Dr Ricardo Jorge, Lisboa, Portugal and Centre for Toxicogenomics and Human Health, Universidade Nova De Lisboa , Lisbon,Portugal
| | - Ines Lanca Martins
- Human Genetics Department, Instituto Nacional De Saúde Dr Ricardo Jorge, Lisboa, Portugal and Centre for Toxicogenomics and Human Health, Universidade Nova De Lisboa , Lisbon,Portugal
| | - Ede Bodoki
- Analytical Chemistry Department, Faculty of Pharmacy, "Iuliu Hatieganu" University of Medicine and Pharmacy , Cluj-Napoca, Romania
| | - Bogdan-Cezar Iacob
- Analytical Chemistry Department, Faculty of Pharmacy, "Iuliu Hatieganu" University of Medicine and Pharmacy , Cluj-Napoca, Romania
| | - Eda Aydindogan
- Department of Chemistry, Graduate School of Sciences and Engineering, Koç University , Istanbul, Turkey
| | - Suna Timur
- Institute of Natural Sciences, Department of Biochemistry, Ege University , Izmir, Turkey
| | | | | | - Theo Luider
- Department of Neurology, Erasmus MC , Rotterdam, The Netherlands
| | | | - Marei Sammar
- Ephraim Katzir Department of Biotechnology Engineering, ORT Braude College , Karmiel, Israel
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34
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Pino LK, Searle BC, Bollinger JG, Nunn B, MacLean B, MacCoss MJ. The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics. MASS SPECTROMETRY REVIEWS 2020; 39:229-244. [PMID: 28691345 PMCID: PMC5799042 DOI: 10.1002/mas.21540] [Citation(s) in RCA: 393] [Impact Index Per Article: 98.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2016] [Accepted: 06/01/2017] [Indexed: 05/03/2023]
Abstract
Skyline is a freely available, open-source Windows client application for accelerating targeted proteomics experimentation, with an emphasis on the proteomics and mass spectrometry community as users and as contributors. This review covers the informatics encompassed by the Skyline ecosystem, from computationally assisted targeted mass spectrometry method development, to raw acquisition file data processing, and quantitative analysis and results sharing.
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Affiliation(s)
- Lindsay K Pino
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington
| | - Brian C Searle
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington
| | - James G Bollinger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington
| | - Brook Nunn
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington
| | - Brendan MacLean
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington
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35
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Martins CO, Huet S, Yi SS, Ritorto MS, Landgren O, Dogan A, Chapman JR. Mass Spectrometry-Based Method Targeting Ig Variable Regions for Assessment of Minimal Residual Disease in Multiple Myeloma. J Mol Diagn 2020; 22:901-911. [PMID: 32302778 DOI: 10.1016/j.jmoldx.2020.04.002] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 03/25/2020] [Accepted: 04/01/2020] [Indexed: 12/11/2022] Open
Abstract
Multiple myeloma is a systemic malignancy of monoclonal plasma cells that accounts for 10% of hematologic cancers. With development of highly effective therapies for multiple myeloma, minimal residual disease (MRD) assessment has emerged as an important end point for management decisions. Currently, serologic assays lack the sensitivity for MRD assessment, and invasive bone marrow sampling with flow cytometry or molecular methods has emerged as the gold standard. We report a sensitive and robust targeted mass spectrometry proteomics method to detect MRD in serum, without the need of invasive, sequential bone marrow aspirates. The method detects Ig-derived clonotypic tryptic peptides predicted by sequencing the clonal plasma cell Ig genes. A heavy isotope-labeled Ig internal standard is added to patient serum at a known concentration, the Ig is enriched in a light chain type specific manner, and proteins are digested and analyzed by targeted mass spectrometry. Peptides from the constant regions of the λ or κ light chains, Ig heavy chains, and clonotypic peptides unique to the patient monoclonal Igs are targeted. This technique is highly sensitive and specific for the patient-specific monoclonal Igs, even in samples negative by multiparametric flow cytometry. Our method can accurately and precisely detect monoclonal protein in serum of patients treated for myeloma and has broad implications for management of hematologic patients.
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Affiliation(s)
- Carlo O Martins
- Hematopathology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Sarah Huet
- Hematopathology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - San S Yi
- Hematopathology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Maria S Ritorto
- Hematopathology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Ola Landgren
- Myeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Ahmet Dogan
- Hematopathology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Jessica R Chapman
- Hematopathology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
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36
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Adams KJ, Pratt B, Bose N, Dubois LG, St John-Williams L, Perrott KM, Ky K, Kapahi P, Sharma V, MacCoss MJ, Moseley MA, Colton CA, MacLean BX, Schilling B, Thompson JW. Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics. J Proteome Res 2020; 19:1447-1458. [PMID: 31984744 DOI: 10.1021/acs.jproteome.9b00640] [Citation(s) in RCA: 216] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Vendor-independent software tools for quantification of small molecules and metabolites are lacking, especially for targeted analysis workflows. Skyline is a freely available, open-source software tool for targeted quantitative mass spectrometry method development and data processing with a 10 year history supporting six major instrument vendors. Designed initially for proteomics analysis, we describe the expansion of Skyline to data for small molecule analysis, including selected reaction monitoring, high-resolution mass spectrometry, and calibrated quantification. This fundamental expansion of Skyline from a peptide-sequence-centric tool to a molecule-centric tool makes it agnostic to the source of the molecule while retaining Skyline features critical for workflows in both peptide and more general biomolecular research. The data visualization and interrogation features already available in Skyline, such as peak picking, chromatographic alignment, and transition selection, have been adapted to support small molecule data, including metabolomics. Herein, we explain the conceptual workflow for small molecule analysis using Skyline, demonstrate Skyline performance benchmarked against a comparable instrument vendor software tool, and present additional real-world applications. Further, we include step-by-step instructions on using Skyline for small molecule quantitative method development and data analysis on data acquired with a variety of mass spectrometers from multiple instrument vendors.
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Affiliation(s)
- Kendra J Adams
- Proteomics and Metabolomics Shared Resource, Duke University, Durham, North Carolina 27701, United States.,Department of Neurology, Duke University, Durham, North Carolina 27710, United States
| | - Brian Pratt
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Neelanjan Bose
- Buck Institute for Research on Aging, Novato, California 94945, United States
| | - Laura G Dubois
- Proteomics and Metabolomics Shared Resource, Duke University, Durham, North Carolina 27701, United States
| | - Lisa St John-Williams
- Proteomics and Metabolomics Shared Resource, Duke University, Durham, North Carolina 27701, United States
| | - Kevin M Perrott
- Buck Institute for Research on Aging, Novato, California 94945, United States
| | - Karina Ky
- University of California San Francisco, San Francisco, California 94143, United States
| | - Pankaj Kapahi
- Buck Institute for Research on Aging, Novato, California 94945, United States
| | - Vagisha Sharma
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - M Arthur Moseley
- Proteomics and Metabolomics Shared Resource, Duke University, Durham, North Carolina 27701, United States
| | - Carol A Colton
- Department of Neurology, Duke University, Durham, North Carolina 27710, United States
| | - Brendan X MacLean
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Birgit Schilling
- Buck Institute for Research on Aging, Novato, California 94945, United States
| | - J Will Thompson
- Proteomics and Metabolomics Shared Resource, Duke University, Durham, North Carolina 27701, United States.,Department of Pharmacology and Cancer Biology, Duke University, Durham, North Carolina 27710, United States
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37
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Marzano V, Tilocca B, Fiocchi AG, Vernocchi P, Levi Mortera S, Urbani A, Roncada P, Putignani L. Perusal of food allergens analysis by mass spectrometry-based proteomics. J Proteomics 2020; 215:103636. [DOI: 10.1016/j.jprot.2020.103636] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Revised: 12/19/2019] [Accepted: 01/05/2020] [Indexed: 12/30/2022]
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38
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Pino LK, Searle BC, Yang HY, Hoofnagle AN, Noble WS, MacCoss MJ. Matrix-Matched Calibration Curves for Assessing Analytical Figures of Merit in Quantitative Proteomics. J Proteome Res 2020; 19:1147-1153. [PMID: 32037841 DOI: 10.1021/acs.jproteome.9b00666] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Mass spectrometry is a powerful tool for quantifying protein abundance in complex samples. Advances in sample preparation and the development of data-independent acquisition (DIA) mass spectrometry approaches have increased the number of peptides and proteins measured per sample. Here, we present a series of experiments demonstrating how to assess whether a peptide measurement is quantitative by mass spectrometry. Our results demonstrate that increasing the number of detected peptides in a proteomics experiment does not necessarily result in increased numbers of peptides that can be measured quantitatively.
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Affiliation(s)
- Lindsay K Pino
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Brian C Searle
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Han-Yin Yang
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Andrew N Hoofnagle
- Department of Laboratory Medicine, University of Washington, Seattle, Washington 98195, United States
| | - William S Noble
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States.,Department of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
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39
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Kohl M, Stepath M, Bracht T, Megger DA, Sitek B, Marcus K, Eisenacher M. CalibraCurve: A Tool for Calibration of Targeted MS-Based Measurements. Proteomics 2020; 20:e1900143. [PMID: 32086983 DOI: 10.1002/pmic.201900143] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Revised: 02/07/2020] [Indexed: 01/29/2023]
Abstract
Targeted proteomics techniques allow accurate quantitative measurements of analytes in complex matrices with dynamic linear ranges that span up to 4-5 orders of magnitude. Hence, targeted methods are promising for the development of robust protein assays in several sensitive areas, for example, in health care. However, exploiting the full method potential requires reliable determination of the dynamic range along with related quantification limits for each analyte. Here, a software named CalibraCurve that enables an automated batch-mode determination of dynamic linear ranges and quantification limits for both targeted proteomics and similar assays is presented. The software uses a variety of measures to assess the accuracy of the calibration, namely precision and trueness. Two different kinds of customizable graphs are created (calibration curves and response factor plots). The accuracy measures and the graphs offer an intuitive, detailed, and reliable opportunity to assess the quality of the model fit. Thus, CalibraCurve is deemed a highly useful and flexible tool to facilitate the development and control of reliable SRM/MRM-MS-based proteomics assays.
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Affiliation(s)
- Michael Kohl
- Medizinisches Proteom-Center, Medical Faculty, Ruhr University Bochum, Gesundheitscampus 4, Bochum, D-44 801, Germany
| | - Markus Stepath
- Medizinisches Proteom-Center, Medical Faculty, Ruhr University Bochum, Gesundheitscampus 4, Bochum, D-44 801, Germany
| | - Thilo Bracht
- Medizinisches Proteom-Center, Medical Faculty, Ruhr University Bochum, Gesundheitscampus 4, Bochum, D-44 801, Germany
| | - Dominik A Megger
- Medizinisches Proteom-Center, Medical Faculty, Ruhr University Bochum, Gesundheitscampus 4, Bochum, D-44 801, Germany.,Institute for Virology, University Hospital Essen, University of Duisburg-Essen, Essen, D-45 147, Germany
| | - Barbara Sitek
- Medizinisches Proteom-Center, Medical Faculty, Ruhr University Bochum, Gesundheitscampus 4, Bochum, D-44 801, Germany
| | - Katrin Marcus
- Medizinisches Proteom-Center, Medical Faculty, Ruhr University Bochum, Gesundheitscampus 4, Bochum, D-44 801, Germany
| | - Martin Eisenacher
- Medizinisches Proteom-Center, Medical Faculty, Ruhr University Bochum, Gesundheitscampus 4, Bochum, D-44 801, Germany
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40
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Wu HY, Pan YY, Kopylov AT, Zgoda V, Ma MC, Wang CH, Su WC, Lai WW, Cheng PN, Liao PC. Assessment of Serological Early Biomarker Candidates for Lung Adenocarcinoma by using Multiple Reaction Monitoring-Mass Spectrometry. Proteomics Clin Appl 2020; 14:e1900095. [PMID: 32012456 DOI: 10.1002/prca.201900095] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 12/24/2019] [Indexed: 12/11/2022]
Abstract
PURPOSE Plasma markers that enable diagnosis in the early stage of lung cancer is not discovered. A liquid chromatography multiple reaction monitoring-mass spectrometry (LC-MRM-MS) assay for identifying potential early marker proteins for lung adenocarcinoma is developed. EXPERIMENTAL DESIGN LC-MRM-MS assay is used for measuring the level of 35 candidate peptides in plasma from 102 lung adenocarcinoma patients (including n = 50, 16, 24, and 12 in stage I, II, III, and IV, respectively.) and 84 healthy controls. Stable isotope labeled standard peptides are synthesized to accurately measure the amount of these proteins. RESULTS Seven proteins are able to distinguish stage I patients from controls. These proteins are combined in to a protein marker panel which improve the sensitivity to discriminate stage I patients from controls with cross-validated area under the curve = 0.76. Besides, it is found that low expression of eukaryotic initiation factor 4A-I and high expression of lumican show significantly poor prognosis in overall survival (p = 0.012 and 0.0074, respectively), which may be used as prognostic biomarkers for lung cancer. CONCLUSIONS AND CLINICAL RELEVANCE Proteins highlighted here may be used for early detection of lung adenocarcinoma or therapeutics development after validation in a larger cohort.
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Affiliation(s)
- Hsin-Yi Wu
- Instrumentation Center, National Taiwan University, Taipei, 106, Taiwan
| | - Yu-Yi Pan
- Department of Statistics, National Cheng Kung University, Tainan, 701, Taiwan
| | - Arthur T Kopylov
- Orekhovich Institute of Biomedical Chemistry, Moscow, 119121, Russia
| | - Victor Zgoda
- Orekhovich Institute of Biomedical Chemistry, Moscow, 119121, Russia
| | - Mi-Chia Ma
- Department of Statistics, National Cheng Kung University, Tainan, 701, Taiwan
| | - Ching-Hsun Wang
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, 701, Taiwan
| | - Wu-Chou Su
- Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, 701, Taiwan
| | - Wu-Wei Lai
- Department of Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, 701, Taiwan
| | - Pin-Nan Cheng
- Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, 701, Taiwan
| | - Pao-Chi Liao
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, 701, Taiwan
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41
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Dubois C, Payen D, Simon S, Junot C, Fenaille F, Morel N, Becher F. Top-Down and Bottom-Up Proteomics of Circulating S100A8/S100A9 in Plasma of Septic Shock Patients. J Proteome Res 2020; 19:914-925. [PMID: 31913637 DOI: 10.1021/acs.jproteome.9b00690] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Well-characterized prognostic biomarkers and reliable quantitative methods are key in sepsis management. Among damage-associated molecular patterns, S100A8/S100A9 complexes are reported to be markers for injured cells and to improve the prediction of death in septic shock patients. In view of the structural diversity observed for the intracellular forms, insight into circulating complexes and proteoforms is required to establish prognostic biomarkers. Here, we developed top-down and bottom-up proteomics to characterize the association of S100A8 and S100A9 in complexes and major circulating proteoforms. An antibody-free method was developed for absolute quantification of S100A8/S100A9 in a cohort of 49 patients to evaluate the prognostic value on the first day after admission for septic shock. The predominant circulating forms identified by top-down proteomics were S100A8, mono-oxidized S100A8, truncated acetylated S100A9, and S-nitrosylated S100A9. S100A8, truncated acetylated S100A9, and mono-oxidized S100A8 discriminated between survivors and nonsurvivors, along with total S100A8/S100A9 measured by the antibody-free bottom-up method. Overall, new insights into circulating S100A8/S100A9 and confirmation of its prognostic value in septic shock are crucial in qualification of this biomarker. Also, the simple antibody-free assay would support the harmonization of S100A8/S100A9 measurements.
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Affiliation(s)
- Christelle Dubois
- Service de Pharmacologie et Immunoanalyse (SPI), CEA, INRA, Université Paris-Saclay , Gif-sur Yvette F-91191 , France
| | - Didier Payen
- Université Paris 7 Cité Sorbonne, UMR INSERM 1160 , 110 Avenue de Verdun , Paris 75010 , France.,Department of Anesthesiology & Critical Care , Hôpital Lariboisière, Assistance Publique-Hôpitaux de Paris (AP-HP) , Paris 75010 , France
| | - Stéphanie Simon
- Service de Pharmacologie et Immunoanalyse (SPI), CEA, INRA, Université Paris-Saclay , Gif-sur Yvette F-91191 , France
| | - Christophe Junot
- Service de Pharmacologie et Immunoanalyse (SPI), CEA, INRA, Université Paris-Saclay , Gif-sur Yvette F-91191 , France
| | - François Fenaille
- Service de Pharmacologie et Immunoanalyse (SPI), CEA, INRA, Université Paris-Saclay , Gif-sur Yvette F-91191 , France
| | - Nathalie Morel
- Service de Pharmacologie et Immunoanalyse (SPI), CEA, INRA, Université Paris-Saclay , Gif-sur Yvette F-91191 , France
| | - François Becher
- Service de Pharmacologie et Immunoanalyse (SPI), CEA, INRA, Université Paris-Saclay , Gif-sur Yvette F-91191 , France
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42
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Gaither C, Popp R, Mohammed Y, Borchers CH. Determination of the concentration range for 267 proteins from 21 lots of commercial human plasma using highly multiplexed multiple reaction monitoring mass spectrometry. Analyst 2020; 145:3634-3644. [DOI: 10.1039/c9an01893j] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Multiple reaction monitoring (MRM) is a key tool for biomarker validation and the translation of potential biomarkers into the clinic.
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Affiliation(s)
| | | | - Yassene Mohammed
- University of Victoria – Genome British Columbia Proteomics Centre
- University of Victoria
- Victoria
- Canada
- Center for Proteomics and Metabolomics
| | - Christoph H. Borchers
- University of Victoria – Genome British Columbia Proteomics Centre
- University of Victoria
- Victoria
- Canada
- Department of Biochemistry and Microbiology
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43
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Minikel EV, Kuhn E, Cocco AR, Vallabh SM, Hartigan CR, Reidenbach AG, Safar JG, Raymond GJ, McCarthy MD, O'Keefe R, Llorens F, Zerr I, Capellari S, Parchi P, Schreiber SL, Carr SA. Domain-specific Quantification of Prion Protein in Cerebrospinal Fluid by Targeted Mass Spectrometry. Mol Cell Proteomics 2019; 18:2388-2400. [PMID: 31558565 PMCID: PMC6885701 DOI: 10.1074/mcp.ra119.001702] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 09/16/2019] [Indexed: 01/11/2023] Open
Abstract
Therapies currently in preclinical development for prion disease seek to lower prion protein (PrP) expression in the brain. Trials of such therapies are likely to rely on quantification of PrP in cerebrospinal fluid (CSF) as a pharmacodynamic biomarker and possibly as a trial endpoint. Studies using PrP ELISA kits have shown that CSF PrP is lowered in the symptomatic phase of disease, a potential confounder for reading out the effect of PrP-lowering drugs in symptomatic patients. Because misfolding or proteolytic cleavage could potentially render PrP invisible to ELISA even if its concentration were constant or increasing in disease, we sought to establish an orthogonal method for CSF PrP quantification. We developed a multi-species targeted mass spectrometry method based on multiple reaction monitoring (MRM) of nine PrP tryptic peptides quantified relative to an isotopically labeled recombinant protein standard for human samples, or isotopically labeled synthetic peptides for nonhuman species. Analytical validation experiments showed process replicate coefficients of variation below 15%, good dilution linearity and recovery, and suitable performance for both CSF and brain homogenate and across humans as well as preclinical species of interest. In n = 55 CSF samples from individuals referred to prion surveillance centers with rapidly progressive dementia, all six human PrP peptides, spanning the N- and C-terminal domains of PrP, were uniformly reduced in prion disease cases compared with individuals with nonprion diagnoses. Thus, lowered CSF PrP concentration in prion disease is a genuine result of the disease process and not an artifact of ELISA-based measurement. As a result, dose-finding studies for PrP lowering drugs may need to be conducted in presymptomatic at-risk individuals rather than in symptomatic patients. We provide a targeted mass spectrometry-based method suitable for preclinical quantification of CSF PrP as a tool for drug development.
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Affiliation(s)
- Eric Vallabh Minikel
- Chemical Biology and Therapeutics Science Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142; Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA 02115; Prion Alliance, Cambridge, MA 02139; Proteomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142.
| | - Eric Kuhn
- Proteomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142; Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA 02115
| | - Alexandra R Cocco
- Proteomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - Sonia M Vallabh
- Chemical Biology and Therapeutics Science Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142; Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA 02115; Prion Alliance, Cambridge, MA 02139
| | | | - Andrew G Reidenbach
- Chemical Biology and Therapeutics Science Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - Jiri G Safar
- Departments of Pathology and Neurology Case Western Reserve University, Cleveland, OH 44106
| | - Gregory J Raymond
- Laboratory of Persistent Viral Diseases, NIAID Rocky Mountain Labs, Hamilton, MT 59840
| | - Michael D McCarthy
- Environmental Health and Safety, Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - Rhonda O'Keefe
- Environmental Health and Safety, Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - Franc Llorens
- National Reference Center for TSE, Georg-August University, Göttingen, 37073, Germany; Biomedical Research Networking Center on Neurodegenerative Diseases (CIBERNED), L'Hospitalet de Llobregat, 08908, Barcelona, Spain
| | - Inga Zerr
- National Reference Center for TSE, Georg-August University, Göttingen, 37073, Germany
| | - Sabina Capellari
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, 40139, Italy; Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, 40123, Italy
| | - Piero Parchi
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, 40139, Italy; Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, 40138, Italy
| | - Stuart L Schreiber
- Chemical Biology and Therapeutics Science Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142; Department of Chemistry & Chemical Biology, Harvard University, Cambridge, MA 02138
| | - Steven A Carr
- Proteomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142.
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44
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Quantitative mass spectrometry-based proteomics in the era of model-informed drug development: Applications in translational pharmacology and recommendations for best practice. Pharmacol Ther 2019; 203:107397. [DOI: 10.1016/j.pharmthera.2019.107397] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 07/29/2019] [Indexed: 02/08/2023]
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45
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Zhang Z, Burke MC, Wallace WE, Liang Y, Sheetlin SL, Mirokhin YA, Tchekhovskoi DV, Stein SE. Sensitive Method for the Confident Identification of Genetically Variant Peptides in Human Hair Keratin. J Forensic Sci 2019; 65:406-420. [PMID: 31670846 PMCID: PMC7064992 DOI: 10.1111/1556-4029.14229] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 09/20/2019] [Accepted: 10/14/2019] [Indexed: 12/20/2022]
Abstract
Recent reports have demonstrated that genetically variant peptides derived from human hair shaft proteins can be used to differentiate individuals of different biogeographic origins. We report a method involving direct extraction of hair shaft proteins more sensitive than previously published methods regarding GVP detection. It involves one step for protein extraction and was found to provide reproducible results. A detailed proteomic analysis of this data is presented that led to the following four results: (i) A peptide spectral library was created and made available for download. It contains all identified peptides from this work, including GVPs that, when appropriately expanded with diverse hair-derived peptides, can provide a routine, reliable, and sensitive means of analyzing hair digests; (ii) an analysis of artifact peptides arising from side reactions is also made using a new method for finding unexpected modifications; (iii) detailed analysis of the gel-based method employed clearly shows the high degree of cross-linking or protein association involved in hair digestion, with major GVPs eluting over a wide range of high molecular weights while others apparently arise from distinct non-cross-linked proteins; and (v) finally, we show that some of the specific GVP identifications depend on the sample preparation method.
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Affiliation(s)
- Zheng Zhang
- Biomolecular Measurement Division, Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899
| | - Meghan C Burke
- Biomolecular Measurement Division, Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899
| | - William E Wallace
- Biomolecular Measurement Division, Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899
| | - Yuxue Liang
- Biomolecular Measurement Division, Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899
| | - Sergey L Sheetlin
- Biomolecular Measurement Division, Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899
| | - Yuri A Mirokhin
- Biomolecular Measurement Division, Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899
| | - Dmitrii V Tchekhovskoi
- Biomolecular Measurement Division, Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899
| | - Stephen E Stein
- Biomolecular Measurement Division, Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899
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46
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Ignjatovic V, Geyer PE, Palaniappan KK, Chaaban JE, Omenn GS, Baker MS, Deutsch EW, Schwenk JM. Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data. J Proteome Res 2019; 18:4085-4097. [PMID: 31573204 DOI: 10.1021/acs.jproteome.9b00503] [Citation(s) in RCA: 104] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The proteomic analysis of human blood and blood-derived products (e.g., plasma) offers an attractive avenue to translate research progress from the laboratory into the clinic. However, due to its unique protein composition, performing proteomics assays with plasma is challenging. Plasma proteomics has regained interest due to recent technological advances, but challenges imposed by both complications inherent to studying human biology (e.g., interindividual variability) and analysis of biospecimens (e.g., sample variability), as well as technological limitations remain. As part of the Human Proteome Project (HPP), the Human Plasma Proteome Project (HPPP) brings together key aspects of the plasma proteomics pipeline. Here, we provide considerations and recommendations concerning study design, plasma collection, quality metrics, plasma processing workflows, mass spectrometry (MS) data acquisition, data processing, and bioinformatic analysis. With exciting opportunities in studying human health and disease though this plasma proteomics pipeline, a more informed analysis of human plasma will accelerate interest while enhancing possibilities for the incorporation of proteomics-scaled assays into clinical practice.
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Affiliation(s)
- Vera Ignjatovic
- Haematology Research , Murdoch Children's Research Institute , Parkville , VIC 3052 , Australia.,Department of Paediatrics , The University of Melbourne , Parkville , VIC 3052 , Australia
| | - Philipp E Geyer
- NNF Center for Protein Research, Faculty of Health Sciences , University of Copenhagen , 2200 Copenhagen , Denmark.,Department of Proteomics and Signal Transduction , Max Planck Institute of Biochemistry , 82152 Martinsried , Germany
| | - Krishnan K Palaniappan
- Freenome , 259 East Grand Avenue , South San Francisco , California 94080 , United States
| | - Jessica E Chaaban
- Haematology Research , Murdoch Children's Research Institute , Parkville , VIC 3052 , Australia
| | - Gilbert S Omenn
- Departments of Computational Medicine & Bioinformatics, Human Genetics, and Internal Medicine and School of Public Health , University of Michigan , 100 Washtenaw Avenue , Ann Arbor , Michigan 48109-2218 , United States
| | - Mark S Baker
- Department of Biomedical Sciences, Faculty of Medicine & Health Sciences , Macquarie University , 75 Talavera Road , North Ryde , NSW 2109 , Australia
| | - Eric W Deutsch
- Institute for Systems Biology , 401 Terry Avenue North , Seattle , Washington 98109 , United States
| | - Jochen M Schwenk
- Affinity Proteomics, SciLifeLab , KTH Royal Institute of Technology , 171 65 Stockholm , Sweden
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47
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Croote D, Braslavsky I, Quake SR. Addressing Complex Matrix Interference Improves Multiplex Food Allergen Detection by Targeted LC-MS/MS. Anal Chem 2019; 91:9760-9769. [PMID: 31339301 DOI: 10.1021/acs.analchem.9b01388] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
The frequent use of precautionary food allergen labeling (PAL) such as "may contain" frustrates allergic individuals who rely on such labeling to determine whether a food is safe to consume. One technique to study whether foods contain allergens is targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) employing scheduled multiple reaction monitoring (MRM). However, the applicability of a single MRM method to many commercial foods is unknown as complex and heterogeneous interferences derived from the unique composition of each food matrix can hinder quantification of trace amounts of allergen contamination. We developed a freely available, open source software package MAtrix-Dependent Interference Correction (MADIC) to identify interference and applied it with a method targeting 14 allergens. Among 84 unique food products, we found patterns of allergen contamination such as wheat in grains, milk in chocolate-containing products, and soy in breads and corn flours. We also found additional instances of contamination in products with and without PAL as well as highly variable soy content in foods containing only soybean oil and/or soy lecithin. These results demonstrate the feasibility of applying LC-MS/MS to a variety of food products with sensitive detection of multiple allergens in spite of variable matrix interference.
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Affiliation(s)
- Derek Croote
- Department of Bioengineering , Stanford University , Stanford , California 94305 , United States
| | - Ido Braslavsky
- Department of Bioengineering , Stanford University , Stanford , California 94305 , United States.,Robert H. Smith Faculty of Agriculture, Food, and Environment , The Hebrew University of Jerusalem , Rehovot 7610001 , Israel
| | - Stephen R Quake
- Department of Bioengineering , Stanford University , Stanford , California 94305 , United States.,Department of Applied Physics , Stanford University , Stanford , California 94305 , United States.,Chan Zuckerberg Biohub , San Francisco , California 94158 , United States
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48
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Grozdanić M, Vidmar R, Vizovišek M, Fonović M. Degradomics in Biomarker Discovery. Proteomics Clin Appl 2019; 13:e1800138. [PMID: 31291060 DOI: 10.1002/prca.201800138] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2019] [Revised: 05/01/2019] [Indexed: 12/13/2022]
Abstract
The upregulation of protease expression and proteolytic activity is implicated in numerous pathological conditions such as neurodegeneration, cancer, cardiovascular and autoimmune diseases, and bone degeneration. During disease progression, various proteases form characteristic patterns of cleaved proteins and peptides, which can affect disease severity and course of progression. It has been shown that qualitative and quantitative monitoring of cleaved protease substrates can provide relevant prognostic, diagnostic, and therapeutic information. As proteolytic fragments and peptides generated in the affected tissue are commonly translocated to blood, urine, and other proximal fluids, their possible application as biomarkers is the subject of ongoing research. The field of degradomics has been established to enable the global identification of proteolytic events on the organism level, utilizing proteomic approaches and sample preparation techniques that facilitate the detection of proteolytic processing of protease substrates in complex biological samples. In this review, some of the latest developments in degradomic methodologies used for the identification and validation of biologically relevant proteolytic events and their application in the search for clinically relevant biomarker candidates are presented. The current state of degradomics in clinics is discussed and the future perspectives of the field are outlined.
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Affiliation(s)
- Marija Grozdanić
- Department of Biochemistry, Molecular and Structural Biology, Jozef Stefan Institute, SI-1000, Ljubljana, Slovenia.,International Postgraduate School Jožef Stefan, SI-1000, Ljubljana, Slovenia
| | - Robert Vidmar
- Department of Biochemistry, Molecular and Structural Biology, Jozef Stefan Institute, SI-1000, Ljubljana, Slovenia
| | - Matej Vizovišek
- Department of Biochemistry, Molecular and Structural Biology, Jozef Stefan Institute, SI-1000, Ljubljana, Slovenia
| | - Marko Fonović
- Department of Biochemistry, Molecular and Structural Biology, Jozef Stefan Institute, SI-1000, Ljubljana, Slovenia
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49
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Duangkumpha K, Stoll T, Phetcharaburanin J, Yongvanit P, Thanan R, Techasen A, Namwat N, Khuntikeo N, Chamadol N, Roytrakul S, Mulvenna J, Mohamed A, Shah AK, Hill MM, Loilome W. Discovery and Qualification of Serum Protein Biomarker Candidates for Cholangiocarcinoma Diagnosis. J Proteome Res 2019; 18:3305-3316. [DOI: 10.1021/acs.jproteome.9b00242] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Kassaporn Duangkumpha
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
- Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Thomas Stoll
- QIMR Berghofer Medical Research Institute, Herston, Queensland 4006, Australia
| | - Jutarop Phetcharaburanin
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
- Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Puangrat Yongvanit
- Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Raynoo Thanan
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Anchalee Techasen
- Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen 40002, Thailand
- Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Nisana Namwat
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
- Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Narong Khuntikeo
- Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen 40002, Thailand
- Department of Surgery, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Nittaya Chamadol
- Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen 40002, Thailand
- Department of Radiology, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Sittiruk Roytrakul
- Proteomics Research Laboratory, Genome Institute, National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani 12120, Thailand
| | - Jason Mulvenna
- QIMR Berghofer Medical Research Institute, Herston, Queensland 4006, Australia
| | - Ahmed Mohamed
- QIMR Berghofer Medical Research Institute, Herston, Queensland 4006, Australia
| | - Alok K. Shah
- QIMR Berghofer Medical Research Institute, Herston, Queensland 4006, Australia
| | - Michelle M. Hill
- QIMR Berghofer Medical Research Institute, Herston, Queensland 4006, Australia
| | - Watcharin Loilome
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
- Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen 40002, Thailand
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50
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Kim KH, Kim JY, Yoo JS. Mass spectrometry analysis of glycoprotein biomarkers in human blood of hepatocellular carcinoma. Expert Rev Proteomics 2019; 16:553-568. [DOI: 10.1080/14789450.2019.1626235] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Kwang Hoe Kim
- Biomedical Omics Group, Korea Basic Science Institute, Cheongju, Republic of Korea
| | - Jin Young Kim
- Biomedical Omics Group, Korea Basic Science Institute, Cheongju, Republic of Korea
| | - Jong Shin Yoo
- Biomedical Omics Group, Korea Basic Science Institute, Cheongju, Republic of Korea
- Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, Republic of Korea
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