Rapid, deep and precise profiling of the plasma proteome with multi-nanoparticle protein corona.

Large-scale, unbiased proteomics studies are constrained by the complexity of the plasma proteome. Here we report a highly parallel protein quantitation platform integrating nanoparticle (NP) protein coronas with liquid chromatography-mass spectrometry for efficient proteomic profiling. A protein corona is a protein layer adsorbed onto NPs upon contact with biofluids.

Evaluation of a Machine Learning-Based Prognostic Model for Unrelated Hematopoietic Cell Transplantation Donor Selection.

The survival of patients undergoing hematopoietic cell transplantation (HCT) from unrelated donors for acute leukemia exhibits considerable variation, even after stringent genetic matching. To improve the donor selection process, we attempted to create an algorithm to quantify the likelihood of survival to 5 years after unrelated donor HCT for acute leukemia, based on the clinical characteristics of the donor selected. All standard clinical variables were included in the model, which also included average leukocyte telomere length of the donor based on its association with recipient survival in severe aplastic anemia, and links to multiple malignancies.

Development of a multi-biomarker disease activity test for rheumatoid arthritis.

Background: Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment.

Objectives: To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis.

Characterization of a multiplex, 12-biomarker test for rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic inflammatory disorder that primarily involves the joints. Accurate and frequent assessment of RA disease activity is critical to optimal treatment planning. A novel algorithm has been developed to determine a multi-biomarker disease activity (MBDA) score based upon measurement of the concentrations of 12 serum biomarkers in multiplex format.

Validation of a novel multibiomarker test to assess rheumatoid arthritis disease activity.

Objective: Quantitative assessment of disease activity in rheumatoid arthritis (RA) is important for patient management, and additional objective information may aid rheumatologists in clinical decision making. We validated a recently developed multibiomarker disease activity (MBDA) test relative to clinical disease activity in diverse RA cohorts.

Methods: Serum samples were obtained from the Index for Rheumatoid Arthritis Measurement, Brigham and Women's Hospital Rheumatoid Arthritis Sequential Study, and Leiden Early Arthritis Clinic cohorts.

Performance of a multi-biomarker score measuring rheumatoid arthritis disease activity in the CAMERA tight control study.

Objectives: To evaluate the performance of individual biomarkers and a multi-biomarker disease activity (MBDA) score in the early rheumatoid arthritis (RA) patient population from the computer assisted management in early rheumatoid arthritis (CAMERA) study.

Methods: Twenty biomarkers were measured in the CAMERA cohort, in which patients were treated with either intensive or conventional methotrexate-based treatment strategies. The MBDA score was calculated using the concentrations of 12 biomarkers (SAA, IL-6, TNF-RI, VEGF-A, MMP-1, YKL-40, MMP-3, EGF, VCAM-1, leptin, resistin and CRP) according to a previously trained algorithm.

Pre-analytical effects of blood sampling and handling in quantitative immunoassays for rheumatoid arthritis.

Variability in pre-analytical blood sampling and handling can significantly impact results obtained in quantitative immunoassays. Understanding the impact of these variables is critical for accurate quantification and validation of biomarker measurements. Particularly, in the design and execution of large clinical trials, even small differences in sample processing and handling can have dramatic effects in analytical reliability, results interpretation, trial management and outcome.

Application of high hydrostatic pressure to dissociate aggregates and refold proteins.

Non-denaturing pressures of around 2000 bar are effective for eliminating and refolding protein aggregates and may be applicable in various phases of protein manufacturing to decrease aggregate levels in products and improve process yields. Lower aggregate levels can result in reduced immunogenicity of proteins and enable the correct refolding of proteins that might not be recovered with traditional techniques. High pressure treatment can also be used to conduct selective PEGylation and protease cleavage reactions while minimizing protein aggregation.

Confronting high-throughput protein refolding using high pressure and solution screens.

Over-expression of heterologous proteins in Escherichia coli is commonly hindered by the formation of inclusion bodies. Nevertheless, refolding of proteins in vitro has become an essential requirement in the development of structural genomics (proteomics) and as a means of recovering functional proteins from inclusion bodies. Many distinct methods for protein refolding are now in use.