Proteomics

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A new class of protein biomarkers based on subcellular distribution: application to a mouse liver cancer model (validation part)


ABSTRACT: To-date, most proteomic studies aimed at discovering tissue-based cancer biomarkers have compared the quantity of selected proteins between case and control groups. However, proteins generally function in association with other proteins to form modules localized in particular subcellular compartments in specialized cell types and tissues. Sub-cellular mislocalization of proteins has in fact been detected as a key feature in a variety of cancer cells. Here, we describe a strategy for tissue-biomarker detection based on a mitochondrial fold enrichment (mtFE) score, which is sensitive to protein abundance changes as well as changes in subcellular distribution between mitochondria and cytosol. The mtFE score integrates protein abundance data from total cellular lysates and mitochondria-enriched fractions, and provides novel information for the classification of cancer samples that is not necessarily apparent from conventional abundance measurements alone. We apply this new strategy to a panel of wild-type and mutant mice with a liver-specific gene deletion of Liver receptor homolog 1 (Lrh-1hep-/-), with both lines containing control individuals as well as individuals with liver cancer induced by diethylnitrosamine (DEN). Lrh-1 gene deletion attenuates cancer cell metabolism in hepatocytes through mitochondrial glutamine processing. We show that proteome changes based on mtFE scores outperform protein abundance measurements in discriminating DEN-induced liver cancer from healthy liver tissue, and are uniquely robust against genetic perturbation. We validate the capacity of selected proteins with informative mtFE scores to indicate hepatic malignant changes in two independent mouse models of hepatocellular carcinoma (HCC), thus demonstrating the robustness of this new approach to biomarker research.

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: PXD013295 | Pride | 2019-05-09

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
ConvertTSVToTraML.TraML Other
E1803291058_feature_alignment_requantCoh1.tsv Tabular
E1805141609_feature_alignment_requantCoh2.tsv Tabular
SAJICTMITO_EPFL_LIVERE1712141542.prot.xml Xml
Sample_annot._cohort1.txt Txt
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Publications

A new class of protein biomarkers based on subcellular distribution: application to a mouse liver cancer model.

Sajic Tatjana T   Ciuffa Rodolfo R   Lemos Vera V   Xu Pan P   Leone Valentina V   Li Chen C   Williams Evan G EG   Makris Georgios G   Banaei-Esfahani Amir A   Heikenwalder Mathias M   Schoonjans Kristina K   Aebersold Ruedi R  

Scientific reports 20190506 1


To-date, most proteomic studies aimed at discovering tissue-based cancer biomarkers have compared the quantity of selected proteins between case and control groups. However, proteins generally function in association with other proteins to form modules localized in particular subcellular compartments in specialized cell types and tissues. Sub-cellular mislocalization of proteins has in fact been detected as a key feature in a variety of cancer cells. Here, we describe a strategy for tissue-bioma  ...[more]

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