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

Author:

Xuan Yue,Bateman Nicholas W.ORCID,Gallien Sebastien,Goetze SandraORCID,Zhou Yue,Navarro Pedro,Hu MoORCID,Parikh Niyati,Hood Brian L.,Conrads Kelly A.,Loosse Christina,Kitata Reta BirhanuORCID,Piersma Sander R.,Chiasserini Davide,Zhu Hongwen,Hou GuixueORCID,Tahir MuhammadORCID,Macklin Andrew,Khoo Amanda,Sun Xiuxuan,Crossett BenORCID,Sickmann Albert,Chen Yu-Ju,Jimenez Connie R.,Zhou HuORCID,Liu SiqiORCID,Larsen Martin R.ORCID,Kislinger ThomasORCID,Chen Zhinan,Parker Benjamin L.,Cordwell Stuart J.,Wollscheid BerndORCID,Conrads Thomas P.ORCID

Abstract

AbstractCancer 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.

Publisher

Springer Science and Business Media LLC

Subject

General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry

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