3 years ago

Using Public Data for Comparative Proteome Analysis in Precision Medicine Programs

Gregg B Morin, Christopher S Hughes
Maximizing the clinical utility of information obtained in longitudinal precision medicine programs would benefit from robust comparative analyses to known information to assess biological features of patient material, in the hopes of identifying the underlying features that drive their disease phenotype. In this study we investigate the potential for utilizing publically deposited mass spectrometry-based proteomics data to perform inter-study comparisons of cell line or tumour tissue materials. Using in-depth quantitative proteomics data acquired from analysis of ovarian cancer cell lines, we demonstrate the robust recapitulation of observable gene expression dynamics between individual studies carried out using significantly different methodologies. The observed signatures enable robust inter-study clustering of cell line samples. In addition, we establish the ability to classify and cluster tumour samples based on observed gene expression trends when using a single patient sample. With this analysis we successfully capture relevant gene expression dynamics from a single patient tumour in the context of a precision medicine analysis by leveraging a large cohort of repository data as a comparator. Together, these data establish the potential for state-of-the-art MS-based proteomics data to serve as resources for robust comparative analyses in precision medicine applications. This article is protected by copyright. All rights reserved

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1002/prca.201600179

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