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      Standardization and harmonization of distributed multi-center proteotype analysis supporting precision medicine studies

      research-article
      1 , , 2 , 3 , 4 , 5 , 6 , 7 , 1 , 7 , 2 , 2 , 2 , 8 , 9 , 10 , 10 , 11 , 12 , 13 , 14 , 15 , 15 , 16 , 17 , 18 , 8 , 19 , 20 , 9 , 10 , 12 , 13 , 14 , 15 , 16 , 17 , 21 , 21 , 5 , 6 , , 22 ,
      Nature Communications
      Nature Publishing Group UK
      Proteomics, Cancer, Systems biology, Medical research

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          Abstract

          Cancer has no borders: Generation and analysis of molecular data across multiple centers worldwide is necessary to gain statistically significant clinical insights for the benefit of patients. Here we conceived and standardized a proteotype data generation and analysis workflow enabling distributed data generation and evaluated the quantitative data generated across laboratories of the international Cancer Moonshot consortium. Using harmonized mass spectrometry (MS) instrument platforms and standardized data acquisition procedures, we demonstrate robust, sensitive, and reproducible data generation across eleven international sites on seven consecutive days in a 24/7 operation mode. The data presented from the high-resolution MS1-based quantitative data-independent acquisition (HRMS1-DIA) workflow shows that coordinated proteotype data acquisition is feasible from clinical specimens using such standardized strategies. This work paves the way for the distributed multi-omic digitization of large clinical specimen cohorts across multiple sites as a prerequisite for turning molecular precision medicine into reality.

          Abstract

          Distributed multi-omic digitization of clinical specimen across multiple sites is a prerequisite for turning molecular precision medicine into reality. Here, the authors show that coordinated proteotype data acquisition is feasible using standardized MS data acquisition and analysis strategies.

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          Most cited references33

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          Universal sample preparation method for proteome analysis.

          We describe a method, filter-aided sample preparation (FASP), which combines the advantages of in-gel and in-solution digestion for mass spectrometry-based proteomics. We completely solubilized the proteome in sodium dodecyl sulfate, which we then exchanged by urea on a standard filtration device. Peptides eluted after digestion on the filter were pure, allowing single-run analyses of organelles and an unprecedented depth of proteome coverage.
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            Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis.

            Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400-1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics.
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              The cyclin-dependent kinase 4/6 inhibitor palbociclib in combination with letrozole versus letrozole alone as first-line treatment of oestrogen receptor-positive, HER2-negative, advanced breast cancer (PALOMA-1/TRIO-18): a randomised phase 2 study.

              Palbociclib (PD-0332991) is an oral, small-molecule inhibitor of cyclin-dependent kinases (CDKs) 4 and 6 with preclinical evidence of growth-inhibitory activity in oestrogen receptor-positive breast cancer cells and synergy with anti-oestrogens. We aimed to assess the safety and efficacy of palbociclib in combination with letrozole as first-line treatment of patients with advanced, oestrogen receptor-positive, HER2-negative breast cancer.
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                Author and article information

                Contributors
                yue.xuan@thermofisher.com
                wbernd@ethz.ch
                conrads@whirc.org
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                16 October 2020
                16 October 2020
                2020
                : 11
                : 5248
                Affiliations
                [1 ]GRID grid.424957.9, ISNI 0000 0004 0624 9165, Thermo Fisher Scientific GmbH, ; Hanna-Kunath Str. 11, Bremen, 28199 Germany
                [2 ]GRID grid.414467.4, ISNI 0000 0001 0560 6544, Gynecologic Cancer Center of Excellence, Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., , Uniformed Services University and Walter Reed National Military Medical Center, ; 8901 Wisconsin Avenue, Bethesda, 20889 MD USA
                [3 ]Thermo Fisher Scientific, Paris, France
                [4 ]GRID grid.418190.5, ISNI 0000 0001 2187 0556, Thermo Fisher Scientific, , Precision Medicine Science Center, ; Cambridge, MA USA
                [5 ]GRID grid.5801.c, ISNI 0000 0001 2156 2780, Institute of Translational Medicine, Department of Health Sciences and Technology, ; ETH Zurich, Switzerland
                [6 ]GRID grid.419765.8, ISNI 0000 0001 2223 3006, Swiss Institute of Bioinformatics, ; Lausanne, Switzerland
                [7 ]GRID grid.410750.7, Thermo Fisher Scientific Co. Ltd, ; Shanghai, China
                [8 ]GRID grid.419243.9, ISNI 0000 0004 0492 9407, Leibniz-Institut für Analytische Wissenschaften—ISAS—e.V., ; Bunsen-Kirchhoff-Straße 11, 44139 Dortmund, Germany
                [9 ]GRID grid.482885.b, ISNI 0000 0004 0633 743X, Institute of Chemistry, Academia Sinica, ; 128 Academia Road, Section 2, Nankang Taipei, 11529 Taiwan
                [10 ]Department of Medical Oncology, Cancer Center Amsterdam, Amsterdam UMC De Boelelaan 1117, 1081 HV Amsterdam, the Netherlands
                [11 ]GRID grid.5379.8, ISNI 0000000121662407, Stoller Biomarker Discovery Centre, Institute of Cancer Sciences, Faculty of Medical and Human Sciences, , University of Manchester, ; Manchester, M13 9PL United Kingdom
                [12 ]GRID grid.9227.e, ISNI 0000000119573309, Shanghai Institute of Materia Medica, , Chinese Academy of Sciences, ; 555 Zuchongzhi Road, Shanghai, 201203 China
                [13 ]GRID grid.21155.32, ISNI 0000 0001 2034 1839, BGI-SHENZHEN, Beishan Road, Yantian District, ; Shenzhen, 518083 Guangdong China
                [14 ]GRID grid.10825.3e, ISNI 0000 0001 0728 0170, Department of Biochemistry and Molecular Biology, , University of Southern Denmark, ; Campusvej 55, Odense M, DK-5230 Denmark
                [15 ]GRID grid.415224.4, ISNI 0000 0001 2150 066X, Princess Margaret Cancer Centre, ; 101 College Street PMCRT 9-807, Toronto, ON M5G 1L7 Canada
                [16 ]National Translational Science Center for Molecular Medicine, Xi’an, 710032 China
                [17 ]GRID grid.233520.5, ISNI 0000 0004 1761 4404, Department of Cell Biology, School of Basic Medicine, , Air Force Medical University, ; Xi’an, 710032 China
                [18 ]GRID grid.1013.3, ISNI 0000 0004 1936 834X, Sydney Mass Spectrometry, , The University of Sydney, ; NSW 2006 Sydney, Australia
                [19 ]GRID grid.5570.7, ISNI 0000 0004 0490 981X, Medizinische Fakultät, Medizinisches Proteom-Center (MPC), , Ruhr-Universität Bochum, ; 44801 Bochum, Germany
                [20 ]GRID grid.7107.1, ISNI 0000 0004 1936 7291, Department of Chemistry, College of Physical Sciences, , University of Aberdeen, ; Aberdeen AB243FX Scotland, UK
                [21 ]GRID grid.1013.3, ISNI 0000 0004 1936 834X, School of Life and Environmental Science, , The University of Sydney, ; NSW 2006 Sydney, Australia
                [22 ]GRID grid.414629.c, ISNI 0000 0004 0401 0871, Women’s Health Integrated Research Center, , Women’s Service Line, Inova Health System, ; 3289 Woodburn Bldg, Annandale, VA 22003 USA
                Author information
                http://orcid.org/0000-0002-4425-9511
                http://orcid.org/0000-0001-6880-8020
                http://orcid.org/0000-0001-7364-2790
                http://orcid.org/0000-0002-8973-7679
                http://orcid.org/0000-0003-0342-9593
                http://orcid.org/0000-0002-1833-0206
                http://orcid.org/0000-0001-5366-4554
                http://orcid.org/0000-0001-7006-4737
                http://orcid.org/0000-0001-9744-3681
                http://orcid.org/0000-0001-6203-0123
                http://orcid.org/0000-0003-3525-5540
                http://orcid.org/0000-0002-3923-1610
                http://orcid.org/0000-0003-4742-3281
                Article
                18904
                10.1038/s41467-020-18904-9
                7568553
                33067419
                b2f5699f-dc0d-4479-ad7e-a9a5992827ee
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 12 March 2020
                : 16 September 2020
                Funding
                Funded by: Supported in part by awards from the Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen, the Regierende Bürgermeister von Berlin - inkl. Wissenschaft und Forschung, and the Bundesministerium für Bildung und Forschung to A.S.; the National Cancer Institute Early Detection Research Network (1U01CA214194-01), a CIHR Project Grant (PJT 156357), and a Collaborative Personalized Cancer Medicine Team Grant from the Princess Margaret Cancer Centre, T.K.); the Congressionally Directed Medical Research Program’s Ovarian Cancer Research Program (W81XWH-19-1-0183 and W81XWH-16-2-0038) and the Uniformed Services University of the Health Sciences (USUHS) through cooperative agreements (HU0001-16-2-0006, HU0001-16-2-0014, and HU0001-18-1-0012) with The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc. (T.P.C.); Academia Sinica and Ministry of Science and Technology in Taiwan (R.B.K. and Y.J.C.); Proteomics and mass spectrometry research at SDU is supported by generous grants to the VILLUM Center for Bioanalytical Sciences (VILLUM Foundation grant no. 7292) and PRO-MS: Danish National Mass Spectrometry Platform for Functional Proteomics (grant no. 5072-00007B, M.R.L.); National Key R&D Program of China (2017YFC0908403, S.L.); Cancer Center Amsterdam and Netherlands Organisation for Scientific Research (NWO- Middelgroot 91116017, C.R.J.). An Australian NHMRC Early Career fellowship (B.L.P). This work was also supported by the Personalized Health and Related Technologies (PHRT) strategic focus area of ETH (to B.W.).
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                © The Author(s) 2020

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                proteomics,cancer,systems biology,medical research
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                proteomics, cancer, systems biology, medical research

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