MassIVE MSV000080770

Imported Reanalysis Dataset Public PXD005210

Large-Scale Analysis of Breast Cancer-Related Conformational Changes in Proteins using Limited Proteolysis

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Description

Conformational changes in proteins can lead to disease. Thus, methods for identifying conformational changes in proteins can further improve our understanding and facilitate detection of disease states. Here we combine limited proteolysis (LiP) with Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC) to characterize breast cancer-related conformational changes in proteins on the proteomic scale. Studied here are the conformational properties of proteins in two cell culture models of breast cancer, including the MCF-10A and MCF-7 cell lines. The SILAC-LiP approach described here identified ~200 proteins with cell-line dependent conformational changes, as determined by their differential susceptibility to proteolytic digestion using the non-specific protease, proteinase K. The protease susceptibility profiles of the proteins in these cell lines were compared to thermodynamic stability and expression level profiles previously generated for proteins in these same breast cancer cell lines. The comparisons revealed that there was little overlap between the proteins with protease susceptibility changes and the proteins with thermodynamic stability and/or expression level changes. Thus, the large-scale conformational analysis described here provides unique insight into the molecular basis of the breast cancer phenotypes in this study. [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Mass Spectrometry ; SILAC ; proteomics ; MCF-7 ; MCF-10A ; protein folding ; limited proteolysis

Contact

Principal Investigators:
(in alphabetical order) 		Michael C. Fitzgerald, Department of Chemistry, Duke University, Durham, North Carolina 27708, United States, N/A
Submitting User: ccms

Publications

Liu F, Fitzgerald MC.
Large-Scale Analysis of Breast Cancer-Related Conformational Changes in Proteins Using Limited Proteolysis.
J. Proteome Res. 2016 Dec 2;15(12):4666-4674. Epub 2016 Nov 17.

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When complete, the converted files will be available in the "ccms_peak" subdirectory of the dataset's FTP space (accessible via the "FTP Download" link to the right).
Number of distinct conditions across all analyses (original submission and reanalyses) associated with this dataset.

Distinct condition labels are counted across all files submitted in the "Metadata" category having a "Condition" column in this dataset.

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Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

Distinct replicate labels are counted across all files submitted in the "Metadata" category having a "BioReplicate" or "Replicate" column in this dataset.

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Number of distinct technical replicates across all analyses (original submission and reanalyses) associated with this dataset.

The technical replicate count is defined as the maximum number of times any one distinct combination of condition and biological replicate was analyzed across all files submitted in the "Metadata" category. In the case of fractionated experiments, only the first fraction is considered.

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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct unmodified peptide sequences reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
This dataset may not contain all raw spectra data as originally deposited in PRIDE. It has been imported to MassIVE for reanalysis purposes, so its spectra data here may consist solely of processed peak lists suitable for reanalysis with most software.