RESUMO
Early detection of cancer is vital for the best chance of successful treatment, but half of all cancers are diagnosed at an advanced stage. A simple and reliable blood screening test applied routinely would therefore address a major unmet medical need. To gain insight into the value of protein biomarkers in early detection and stratification of cancer we determined the time course of changes in the plasma proteome of mice carrying transplanted human lung, breast, colon, or ovarian tumors. For protein measurements we used an aptamer-based assay which simultaneously measures ~ 5000 proteins. Along with tumor lineage-specific biomarkers, we also found 15 markers shared among all cancer types that included the energy metabolism enzymes glyceraldehyde-3-phosphate dehydrogenase, glucose-6-phophate isomerase and dihydrolipoyl dehydrogenase as well as several important biomarkers for maintaining protein, lipid, nucleotide, or carbohydrate balance such as tryptophanyl t-RNA synthetase and nucleoside diphosphate kinase. Using significantly altered proteins in the tumor bearing mice, we developed models to stratify tumor types and to estimate the minimum detectable tumor volume. Finally, we identified significantly enriched common and unique biological pathways among the eight tumor cell lines tested.
Assuntos
Neoplasias Ovarianas , Proteoma , Feminino , Humanos , Camundongos , Animais , Proteoma/metabolismo , Biomarcadores Tumorais/metabolismo , Metabolismo Energético , Linhagem Celular TumoralRESUMO
Background Chronic kidney disease (CKD) confers increased cardiovascular risk, not fully explained by traditional factors. Proteins regulate biological processes and inform the risk of diseases. Thus, in 938 patients with stable coronary heart disease from the Heart and Soul cohort, we quantified 1054 plasma proteins using modified aptamers (SOMAscan) to: (1) discern how reduced glomerular filtration influences the circulating proteome, (2) learn of the importance of kidney function to the prognostic information contained in recently identified protein cardiovascular risk biomarkers, and (3) identify novel and even unique cardiovascular risk biomarkers among individuals with CKD. Methods and Results Plasma protein levels were correlated to estimated glomerular filtration rate (eGFR) using Spearman-rank correlation coefficients. Cox proportional hazard models were used to estimate the association between individual protein levels and the risk of the cardiovascular outcome (first among myocardial infarction, stroke, heart failure hospitalization, or mortality). Seven hundred and nine (67.3%) plasma proteins correlated with eGFR at P<0.05 (ρ 0.06-0.74); 218 (20.7%) proteins correlated with eGFR moderately or strongly (ρ 0.2-0.74). Among the previously identified 196 protein cardiovascular biomarkers, just 87 remained prognostic after correction for eGFR. Among patients with CKD (eGFR <60 mL/min per 1.73 m2), we identified 21 protein cardiovascular risk biomarkers of which 8 are unique to CKD. Conclusions CKD broadly alters the composition of the circulating proteome. We describe protein biomarkers capable of predicting cardiovascular risk independently of glomerular filtration, and those that are prognostic of cardiovascular risk specifically in patients with CKD and even unique to patients with CKD.