Influence of blood sampling on protein profiling and pattern analysis using matrix-assisted laser desorption/ionisation mass spectrometry

New stationary phases for enrichment and separation in the 'omics' era

'Omics' is a general term for a broad discipline of science and engineering concerned with analyzing the interactions of biological molecular components in various 'omes'. These include genome, proteome, metabolome, expressome and interactome. 'Ome' and 'omics' are very convenient handles for describing the holistic approach for looking at complex systems. 'Omics' will not only have an impact on our understanding of biological processes, but also on the prospect of more accurately diagnosing and treating disease. The development of these 'omics' has depended on, and has also driven, advances in chromatography and electrophoresis, as well as highly sensitive and specific analytical techniques to permit the handling of large numbers of samples with high selectivity and sensitivity. The development and design of novel stationary phases for selective enrichment and separation is one of the key points for establishing a successfully running 'omics' platform. Therefore, this review demonstrates the application of different new materials developed in our laboratory, such as chromatographic stationary phases for selective and sensitive high-speed purification, enrichment and separation in genomics, proteomics and metabolomics.

Identification of Serum Biomarkers for Biliary Tract Cancers by a Proteomic Approach Based on Time-of-Flight Mass Spectrometry

Biliary tract cancers (BTCs) are lethal malignancies currently lacking satisfactory methods for early detection and accurate diagnosis. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) is a promising diagnostic tool for this disease. In this pilot study, sera samples from 50 BTCs and 30 cholelithiasis patients as well as 30 healthy subjects from a population-based case-control study were randomly grouped into training set (30 BTCs, 20 cholelithiasis and 20 controls), duplicate of training set, and blind set (20 BTCs, 10 cholelithiasis and 10 controls); all sets were analyzed on Immobilized Metal Affinity Capture ProteinChips via SELDI-TOF-MS. A decision tree classifier was built using the training set and applied to all test sets. The classification tree constructed with the 3,400, 4,502, 5,680, 7,598, and 11,242 mass-to-charge ratio (m/z) protein peaks had a sensitivity of 96.7% and a specificity of 85.0% when comparing BTCs with non-cancers. When applied to the duplicate set, sensitivity was 66.7% and specificity was 70.0%, while in the blind set, sensitivity was 95.0% and specificity was 75.0%. Positive predictive values of the training, duplicate, and blind sets were 82.9%, 62.5% and 79.2%, respectively. The agreement of the training and duplicate sets was 71.4% (Kappa = 0.43, u = 3.98, P < 0.01). The coefficient of variations based on 10 replicates of one sample for the five differential peaks were 15.8–68.8% for intensity and 0–0.05% for m/z. These pilot results suggest that serum protein profiling by SELDI-TOF-MS may be a promising approach for identifying BTCs but low assay reproducibility may limit its application in clinical practice.

Challenges for biomarker discovery in body fluids using SELDI-TOF-MS

Protein profiling using SELDI-TOF-MS has gained over the past few years an increasing interest in the field of biomarker discovery. The technology presents great potential if some parameters, such as sample handling, SELDI settings, and data analysis, are strictly controlled. Practical considerations to set up a robust and sensitive strategy for biomarker discovery are presented. This paper also reviews biological fluids generally available including a description of their peculiar properties and the preanalytical challenges inherent to sample collection and storage. Finally, some new insights for biomarker identification and validation challenges are provided.