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

被引：59

作者：

Xuan, Yue ^{[1
,2
,3
,4
]}

Bateman, Nicholas W. ^{[2
,3
]}

Gallien, Sebastien ^{[4
,5
]}

Goetze, Sandra ^{[6
,7
]}

Zhou, Yue ^{[8
]}

Navarro, Pedro ^{[1
]}

Hu, Mo ^{[8
]}

Parikh, Niyati ^{[2
,3
]}

Hood, Brian L. ^{[2
,3
]}

Conrads, Kelly A. ^{[2
,3
]}

Loosse, Christina ^{[9
]}

Kitata, Reta Birhanu ^{[10
]}

Piersma, Sander R. ^{[11
]}

Chiasserini, Davide ^{[11
,12
]}

Zhu, Hongwen ^{[13
]}

Hou, Guixue ^{[14
]}

Tahir, Muhammad ^{[15
]}

Macklin, Andrew ^{[16
]}

Khoo, Amanda ^{[16
]}

Sun, Xiuxuan ^{[17
,18
]}

Crossett, Ben ^{[19
]}

Sickmann, Albert ^{[9
,20
,21
]}

Chen, Yu-Ju ^{[10
]}

Jimenez, Connie R. ^{[11
]}

Zhou, Hu ^{[13
]}

Liu, Siqi ^{[14
]}

Larsen, Martin R. ^{[15
]}

Kislinger, Thomas ^{[16
]}

Chen, Zhinan ^{[17
,18
]}

Parker, Benjamin L. ^{[22
]}

Cordwell, Stuart J. ^{[22
]}

Wollscheid, Bernd ^{[6
,7
]}

Conrads, Thomas P. ^{[23
]}

机构：

[1] Thermo Fisher Sci GmbH, Hanna Kunath Str 11, D-28199 Bremen, Germany

[2] Uniformed Serv Univ Hlth Sci, Henry M Jackson Fdn Adv Mil Med Inc, Gynecol Canc Ctr Excellence, 8901 Wisconsin Ave, Bethesda, MD 20889 USA

[3] Walter Reed Natl Mil Med Ctr, 8901 Wisconsin Ave, Bethesda, MD 20889 USA

[4] Thermo Fisher Sci, Paris, France

[5] Thermo Fisher Sci, Precis Med Sci Ctr, Cambridge, MA USA

[6] Swiss Fed Inst Technol, Inst Translat Med, Dept Hlth Sci & Technol, Zurich, Switzerland

[7] Swiss Inst Bioinformat, Lausanne, Switzerland

[8] Thermo Fisher Sci Co Ltd, Shanghai, Peoples R China

[9] Leibniz Inst Analyt Wissensch ISAS, Bunsen Kirchhoff Str 11, D-44139 Dortmund, Germany

[10] Acad Sinica, Inst Chem, 128 Acad Rd,Sect 2, Taipei 11529, Taiwan

[11] Amsterdam UMC, Canc Ctr Amsterdam, Dept Med Oncol, De Boelelaan 1117, NL-1081 HV Amsterdam, Netherlands

[12] Univ Manchester, Fac Med & Human Sci, Stoller Biomarker Discovery Ctr, Manchester M13 9PL, Lancs, England

[13] Chinese Acad Sci, Shanghai Inst Mat Med, 555 Zuchongzhi Rd, Shanghai 201203, Peoples R China

[14] BGI SHENZHEN, Beishan Rd, Shenzhen 518083, Guangdong, Peoples R China

[15] Univ Southern Denmark, Dept Biochem & Mol Biol, Campusvej 55, DK-5230 Odense M, Denmark

[16] Princess Margaret Canc Ctr, 101 Coll St PMCRT 9-807, Toronto, ON M5G 1L7, Canada

[17] Natl Translat Sci Ctr Mol Med, Xian 710032, Peoples R China

[18] Air Force Med Univ, Sch Basic Med, Dept Cell Biol, Xian 710032, Peoples R China

[19] Univ Sydney, Sydney Mass Spectrometry, Sydney, NSW 2006, Australia

[20] Ruhr Univ Bochum, Med Proteom Ctr MPC, Med Fak, D-44801 Bochum, Germany

[21] Univ Aberdeen, Coll Phys Sci, Dept Chem, Aberdeen AB243FX, Scotland

[22] Univ Sydney, Sch Life & Environm Sci, Sydney, NSW 2006, Australia

[23] Inova Hlth Syst, Womens Hlth Integrated Res Ctr, Womens Serv Line, 3289 Woodburn Bldg, Annandale, VA 22003 USA

来源：

NATURE COMMUNICATIONS | 2020年 / 11卷 / 01期

基金：

国家重点研发计划; 澳大利亚国家健康与医学研究理事会;

关键词：

DATA-INDEPENDENT ACQUISITION; RETENTION TIME; PEPTIDE; IDENTIFICATION; THROUGHPUT; PROTEOMICS; TOOLS;

D O I：

10.1038/s41467-020-18904-9

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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. 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.

引用

页数：12

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