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.