Unknown

Dataset Information

0

Detection of dysregulated protein-association networks by high-throughput proteomics predicts cancer vulnerabilities.


ABSTRACT: The formation of protein complexes and the co-regulation of the cellular concentrations of proteins are essential mechanisms for cellular signaling and for maintaining homeostasis. Here we use isobaric-labeling multiplexed proteomics to analyze protein co-regulation and show that this allows the identification of protein-protein associations with high accuracy. We apply this 'interactome mapping by high-throughput quantitative proteome analysis' (IMAHP) method to a panel of 41 breast cancer cell lines and show that deviations of the observed protein co-regulations in specific cell lines from the consensus network affects cellular fitness. Furthermore, these aberrant interactions serve as biomarkers that predict the drug sensitivity of cell lines in screens across 195 drugs. We expect that IMAHP can be broadly used to gain insight into how changing landscapes of protein-protein associations affect the phenotype of biological systems.

SUBMITTER: Lapek JD 

PROVIDER: S-EPMC5683351 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

altmetric image

Publications

Detection of dysregulated protein-association networks by high-throughput proteomics predicts cancer vulnerabilities.

Lapek John D JD   Greninger Patricia P   Morris Robert R   Amzallag Arnaud A   Pruteanu-Malinici Iulian I   Benes Cyril H CH   Haas Wilhelm W  

Nature biotechnology 20170911 10


The formation of protein complexes and the co-regulation of the cellular concentrations of proteins are essential mechanisms for cellular signaling and for maintaining homeostasis. Here we use isobaric-labeling multiplexed proteomics to analyze protein co-regulation and show that this allows the identification of protein-protein associations with high accuracy. We apply this 'interactome mapping by high-throughput quantitative proteome analysis' (IMAHP) method to a panel of 41 breast cancer cell  ...[more]

Similar Datasets

| S-EPMC2654914 | biostudies-literature
| S-EPMC2842071 | biostudies-literature
| S-EPMC137474 | biostudies-literature
| S-EPMC5728403 | biostudies-literature
| S-EPMC6007231 | biostudies-literature
| S-EPMC5495102 | biostudies-literature
| S-EPMC9499451 | biostudies-literature
| S-EPMC7818227 | biostudies-literature
| S-EPMC5988721 | biostudies-literature
| S-EPMC6586828 | biostudies-literature