Standardization and harmonization of distributed multi-center proteotype analysis supporting precision medicine studies.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
16 10 2020
16 10 2020
Historique:
received:
12
03
2020
accepted:
16
09
2020
entrez:
17
10
2020
pubmed:
18
10
2020
medline:
18
11
2020
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 33067419
doi: 10.1038/s41467-020-18904-9
pii: 10.1038/s41467-020-18904-9
pmc: PMC7568553
doi:
Substances chimiques
Proteome
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
5248Subventions
Organisme : NCI NIH HHS
ID : U01 CA214194
Pays : United States
Organisme : CIHR
ID : PJT 156357
Pays : Canada
Références
Clin Pharmacol Ther. 2017 May;101(5):619-621
pubmed: 28187513
Cell. 2018 Apr 19;173(3):535-539
pubmed: 29677503
Curr Opin Mol Ther. 2002 Jun;4(3):242-50
pubmed: 12139310
J Proteome Res. 2014 Dec 5;13(12):5415-30
pubmed: 25244318
Int J Anal Chem. 2016;2016:7436849
pubmed: 27298622
Nat Methods. 2004 Oct;1(1):39-45
pubmed: 15782151
Cancers (Basel). 2018 Sep 18;10(9):
pubmed: 30231564
Sci Data. 2014 Sep 16;1:140031
pubmed: 25977788
Nat Biotechnol. 2016 Nov;34(11):1130-1136
pubmed: 27701404
Proteomics. 2011 Feb;11(4):535-53
pubmed: 21243637
Mol Cell Proteomics. 2015 Oct;14(10):2800-13
pubmed: 26199342
Nat Methods. 2017 Sep;14(9):921-927
pubmed: 28825704
Mol Cell Proteomics. 2014 Jan;13(1):329-38
pubmed: 23820513
Clin Cancer Res. 2016 Sep 15;22(18):4556-8
pubmed: 27199492
Nat Commun. 2017 Aug 21;8(1):291
pubmed: 28827567
Nat Rev Clin Oncol. 2015 Dec;12(12):693-704
pubmed: 26196250
Lancet Oncol. 2015 Jan;16(1):25-35
pubmed: 25524798
Sci Rep. 2016 Oct 07;6:34949
pubmed: 27713570
Nat Biotechnol. 2009 Jul;27(7):633-41
pubmed: 19561596
Mol Cell Proteomics. 2015 May;14(5):1400-10
pubmed: 25724911
Proteomics. 2012 Apr;12(8):1111-21
pubmed: 22577012
BMC Cancer. 2019 Jul 16;19(1):698
pubmed: 31311512
J Clin Oncol. 2015 Mar 20;33(9):1000-7
pubmed: 25667274
Nat Methods. 2013 Aug;10(8):744-6
pubmed: 23793237
Mol Cell Proteomics. 2012 Jun;11(6):O111.016717
pubmed: 22261725
Nat Med. 2015 Apr;21(4):407-13
pubmed: 25730263
Nat Methods. 2018 Jun;15(6):440-448
pubmed: 29735998
Clin Pharmacol Ther. 2019 Jul;106(1):52-57
pubmed: 30838639
Nat Methods. 2010 Sep;7(9):681-5
pubmed: 20805795
Nat Methods. 2009 May;6(5):359-62
pubmed: 19377485
Anal Chem. 2000 Jul 15;72(14):3349-54
pubmed: 10939410
Cancer Res. 2012 Jul 15;72(14):3471-9
pubmed: 22628425
J Pathol. 2018 Apr;244(5):550-564
pubmed: 29344971