Dataset Information

Global Analysis of Protein Folding Thermodynamics for Disease State Characterization, MCF7 vs MCF10A

ABSTRACT: Protein biomarkers can be used to characterize and diagnose disease states such as cancer. They can also serve as therapeutic targets. Current methods for protein biomarker discovery, which generally rely on the large-scale analysis of gene and/or protein expression levels, fail to detect protein biomarkers with disease-related functions and unaltered expression levels. Here we describe the large-scale use of thermodynamic measurements of protein folding and stability for disease state characterization and the discovery of protein biomarkers. Using the Stable Isotope Labeling with Amino Acids in Cell Culture and Stability of Proteins from Rates of Oxidation (SILAC-SPROX) technique, we assayed ~800 proteins for protein folding and stability changes in three different cell culture models of breast cancer including the MCF-10A, MCF-7, and MDA-MB-231 cell lines. The thermodynamic stability profiles generated here created distinct molecular markers for the three cell lines, and a significant fraction (~45%) of the differentially stabilized proteins did not have altered expression levels. Thus, the protein biomarkers reported here created novel molecular signatures of breast cancer and provided additional insight into the molecular basis of the disease. Our results establish the utility of protein folding and stability measurements for the study of disease processes.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Permanent Cell Line Cell

DISEASE(S): Breast Cancer

SUBMITTER: Jagat Adhikari

LAB HEAD: Michael C. Fitzgerald

PROVIDER: PXD001847 | Pride | 2015-04-10

REPOSITORIES: Pride

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Publications

Global analysis of protein folding thermodynamics for disease state characterization.

Adhikari Jagat J West Graham M GM Fitzgerald Michael C MC

Journal of proteome research 20150409 5

Current methods for the large-scale characterization of disease states generally rely on the analysis of gene and/or protein expression levels. These existing methods fail to detect proteins with disease-related functions and unaltered expression levels. Here we describe the large-scale use of thermodynamic measurements of protein folding and stability for the characterization of disease states. Using the Stable Isotope Labeling with Amino Acids in Cell Culture and Stability of Proteins from Rat ...[more]

PMID: 25825992

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Project description:Large-scale studies of protein phosphorylation have generally focused on determining the sites and stoichiometry of phosphorylated proteins derived from different biological specimens such as cell lines and tissue samples. While such information is important for understanding the role of phosphorylation in biological systems, it fails to expose the relationship between protein phosphorylation and protein function. Because of the close link between protein function and protein folding stability, knowledge about phosphorylation-induced protein folding stability changes can lead to a better understanding of the functional effects of protein phosphorylation. As part of this work, the Stability of Proteins from Rate of OXidation (SPROX) and Limited Proteolysis (LiP) techniques were utilized to identify phosphorylation-induced conformational and stability changes in proteins derived from a human breast cancer cell line MCF-7. This was accomplished by comparing the conformation properties of proteins in two MCF-7 cell lysates including one that was and one that was not dephosphorylated with alkaline phosphatase. The SPROX technique, which probes the global unfolding/refolding properties of proteins, identified 168 proteins with dephosphorylation-induced stability changes, and the LiPs technique, which probes the more local unfolding/refolding properties of proteins, identified 251 proteins with dephosphorylation-induced stability changes. A total of 49 proteins identified here with dephosphorylation-induced conformational changes, were previously identified in phosphoproteomic studies to be differentially phosphorlyated in different human breast cancer subtypes. A total of 98 proteins identified here overlapped with protein hits previously found to be differentially stabilized in four human breast cancer phenotypes, suggesting that the phosphorylated changes observed here may be disease related. The experimental approach and results reported here create a novel approach for identifying functionally significant PTMs in proteins.

Dataset Information

Global Analysis of Protein Folding Thermodynamics for Disease State Characterization, MCF7 vs MCF10A

Publications

Global analysis of protein folding thermodynamics for disease state characterization.

Similar Datasets

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