How can we generate reproducible deep proteomics data from clinical samples across multiple labs?
Sander Piersma and Connie Jimenez of the OncoProteomics Laboratory participated in an international benchmark study. Using harmonized mass spectrometry instrument platforms and standardized data acquisition procedures, they demonstrate robust, sensitive, and reproducible data generation across eleven international sites on seven consecutive days in a 24/7 operation mode.
The novel next generation proteomics workflow based on data-independent acquisition mass spectrometry shows that highly reproducible deep proteomics data acquisition is feasible from complex cancer samples. This work paves the way for precision medicine by proteome analysis of large clinical specimen cohorts across multiple labs.
Read the full article 'Standardization and harmonization of distributed multi-center proteotype analysis supporting precision medicine studies' in Nature Communications 2020.