ArticleJournal of proteome research2015
Global analysis of protein folding thermodynamics for disease state characterization.
Article in Journal of proteome research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 32 citations in OpenAlex.
- Analysis of Brain Protein Stability Changes in a Mouse Model of Alzheimer's Disease.Journal of proteome research · 2024Article
- Protein Folding Stability Profiling of Colorectal Cancer Chemoresistance Identifies Functionally Relevant Biomarkers.Journal of proteome research · 2023Article
- Comparative Analysis of Protein Folding Stability-Based Profiling Methods for Characterization of Biological Phenotypes.Journal of the American Society for Mass Spectrometry · 2023Article
- Hsp40 Affinity to Identify Proteins Destabilized by Cellular Toxicant Exposure.Analytical chemistry · 2021Article
- Analysis of Brain Protein Stability Changes in Mouse Models of Normal Aging and α-Synucleinopathy Reveals Age- and Disease-Related Differences.Journal of proteome research · 2021Article
- Direct visualization and profiling of protein misfolding and aggregation in live cells.Current opinion in chemical biology · 2021Review
- Comparative Analysis of Mass-Spectrometry-Based Proteomic Methods for Protein Target Discovery Using a One-Pot Approach.Journal of the American Society for Mass Spectrometry · 2020Article
- Proteome-Wide Structural Biology: An Emerging Field for the Structural Analysis of Proteins on the Proteomic Scale.Journal of proteome research · 2018Review
- Proteome-Wide Characterization of Phosphorylation-Induced Conformational Changes in Breast Cancer.Journal of proteome research · 2018Article
- Discovery of Tamoxifen and N-Desmethyl Tamoxifen Protein Targets in MCF-7 Cells Using Large-Scale Protein Folding and Stability Measurements.Journal of proteome research · 2017Article
- Large-Scale Analysis of Breast Cancer-Related Conformational Changes in Proteins Using SILAC-SPROX.Journal of proteome research · 2017Article
- Large-Scale Analysis of Breast Cancer-Related Conformational Changes in Proteins Using Limited Proteolysis.Journal of proteome research · 2016Article
- Discovery of Age-Related Protein Folding Stability Differences in the Mouse Brain Proteome.Journal of proteome research · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
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 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 to differentiate the three cell lines, and a significant fraction (∼45%) of the differentially stabilized proteins did not have altered expression levels. Thus, the differential thermodynamic profiling strategy 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, and they suggest that such measurements may be useful for biomarker discovery in disease.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.