Biomarker discovery and clinical proteomics

Abstract

New biomarkers are urgently needed to accelerate efforts in developing new drugs and treatments of known diseases. New clinical and translational proteomics studies emerge almost every day. However, discovery of new diagnostic biomarkers lags behind because of variability at every step in proteomics studies (e.g., assembly of a cohort of patients, sample preparation and the nature of body fluids, selection of a profiling method and uniform protocols for data analysis).Quite often, the validation step that follows the discovery phase does not reach desired levels of sensitivity and specificity or reproducibility between laboratories. Mass spectrometry and gel-based methods do not provide enough throughput for screening thousands of clinical samples. Further development of protein arrays may address this issue.Despite many obstacles, proteomics delivers vast amounts of information useful for understanding the molecular mechanisms underlying diseases.

Figure 1

Typical proteomic workflow used in clinical proteomics leading to biomarker discovery. Sample preparation and the first steps of fractionation (e.g., immunodepletion) can be considered as one process, introducing substantial variability. The chemical-labeling step, whether intact proteins or peptides, is least susceptible to introduction of variability because of wide application of well-established procedures. Most researchers use standard nano-LC-ESI-MS² or MALDI-TOF² methods, which can be easily compared and cross-validated. Bioinformatics tools may translate only part of data into biologically-relevant information and currently no solid standards are available. Building knowledge – data interpretation – is entirely at the discretion of individual investigators.

Figure 2

Biomarker discovery and validation should be free from any bias and performed in a similar fashion to weighing justice – based on facts.