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.

癌症无国界：在全球多个中心进行分子数据的生成和分析对于获得具有统计学意义的有意义的临床见解对于使患者受益至关重要。在这里，我们构思并标准化了能够进行分布式数据生成的原型数据生成和分析工作流程，并评估了国际癌症Moonshot联盟实验室之间生成的定量数据。使用统一的质谱（MS）仪器平台和标准化的数据采集程序，我们以24/7的操作模式连续7天展示了遍布11个国际站点的可靠，敏感和可重现的数据生成。从高分辨率的基于MS1的定量独立数据采集（HRMS1-DIA）工作流程中获得的数据表明，使用这种标准化策略从临床标本中进行协调的原型数据采集是可行的。这项工作为跨多个站点的大型临床标本队列的分布式全组数字化铺平了道路，这是将分子精确医学变为现实的前提。