Biomarkers – Multimedia

To facilitate both prediction and mechanism-based assessment of human cancer risk, a liver gene expression signature was derived from short term experiments in the rat to predict non-genotoxic hepatocarcinogenicity. The signature was shown to classify 47 independent chemicals with 85% accuracy, much greater than other putative early biomarkers.

Characteristic 2D fractions are rapidly identified among thousands using interactive visualization, filtering and data mining with VisualCockpit. Biomarker candidates are found therein after identifying proteins from sequence tags. VisualCockpit correlates their concentrations, reflected by normalized MS peptide peak height sum, enzyme activity and immunoreactivity, to donor conditions.

We have developed a high throughput expression of recombinant proteins containing hexahistidine affinity tag in Escherichia coli followed by one step affinity purification of proteins on Ni²⁺ agarose beads.

The data presented herein demonstrate the unique profiling capabilities of each ProFACT™ surface library subfraction and the collective resolution of 69 non-redundant proteins, calibrated and quantified from image analysis of SDS-PAGE profiles.

This poster provides an overview of the data standards work initiated between several parties, our current work, and the plans towards showcasing an example of a set of proteomics data standards at work in a large scale clinical proteomics setting, in a biomarker discovery context.

MolPAGE (Molecular Phenotyping to Accelerate Genomic Epidemiology) is an EU consortium with almost twenty collaborating universities and companies throughout Europe. One of the aims of MolPAGE is to find early onset biomarkersfor type 2 diabetes (T2DM) and cardio-vascular diseases(CVD).

This work demonstrates the development and validation of a novel clinical proteomics approach in which specific protein targets can be expeditiously and selectively isolated from acomplex biological fluid for MS characterization.