A technique to identify context-based protein biomarkers: Application to a mouse liver cancer model

ABSTRACT: To date, most proteomic analyses towards cancer biomarker discovery have been based on protein quantification. However, proteins function in association with other proteins to form modules that are localized in specific subcellular compartments. Cellular mislocalization of proteins has in fact been detected as a key feature in a variety of cancer cells1,2. Here, we describe a strategy for biomarker detection based on a mitochrondrial enrichment score (mtES), which is sensitive to protein abundance as well as protein translocation between mitochondria and cytosol. The mtES score integrates protein expression data from total cellular lysates and enriched mitochondrial fractions and provides important information for the classification of cancer samples, which is not apparent from conventional quantitative protein measurements. We apply the new strategy to a panel of wild-type and mutant mice that are either healthy or present liver cancer. We show that proteome changes based on mtES scores outperform protein abundance measurements in discriminating liver cancer from healthy liver tissue and that they are uniquely robust against strong genetic perturbation. Overall, our method provides a more sensitive approach to cancer biomarker discovery that takes into account contextual information of tested proteins.

INSTRUMENT(S): TripleTOF 5600

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Hepatocyte, Liver

DISEASE(S): Liver Cancer

SUBMITTER: Tatjana Sajic  

LAB HEAD: Prof. Dr. Ruedi Aebersold

PROVIDER: PXD008758 | Pride | 2019-05-09

REPOSITORIES: Pride