New Protein Biomarkers Christopher Southan Oxford GLycosciences UK Ltd NATO Workshop, Prague, October 2002

2. Presentation Outline Proteomics technology overview Biofluid analysis Breast cancer biomarkers Cardiotoxicity biomarkers Schizophrenia protein isoform analysis

5. Creating an Expression Proteomics Database

6. PC - Rosetta: Data Flow Reformat graphs with new color and move legendReformat graphs with new color and move legend

8. Detection of Disease-Specific Proteins in Serum, CSF, & Synovial fluid High-abundance proteins limit sensitivity - albumin - haptoglobin - IgG - transferrin Solution : Immunoaffinity enrichment protocol

9. Effect of Enrichment Protocol

10. Serum High Resolution Zoom Gels

11. Synovial Fluid

13. Biofluids Summary A reproducible method to deplete high abundance proteins specifically from biological fluids has been developed Databases relating clinical, biological, image and annotation data are being built Annotation of a composite Serum, CSF proteomes of several hundred individuals is in progress (status= 1,500 protein isoforms in CSF and 800 protein isoforms in serum have been identified at the peptide sequence level) The majority of proteins exists in multiple isoforms Changes observed in many disorders appear to be protein isoform specific and not global Identifying the enzymes responsible for disease associated protein isoforms may help us to better understand the molecular pathophysiology of many diseases

14. Characteristics of an �Ideal� Biomarker Specific High tissue / serum ratio Not present in non-affected tissue Differentiation of pathology stage or toxicity type (acute versus chronic, necrosis, hypertrophy, etc.) Sensitive Zero baseline Marker of �early,� reversible pathology/toxicity Immediate release with disease onset Predictive Long half-life in blood Gives indication of reversibility Release proportionate to disease or toxity progression Robust Rapid, simple, accurate and inexpensive detection in all relevant species Bridge pre-clinical & clinical Non-invasive / accessible

15. OGS Breast Cancer Proteome Studies 3 year collaboration Protein expression database of purified cells- normal breast luminal and myoepithelial cells Expression database of purified, clinically-derived breast cancer samples Patient serum biomarker study- normal, primary and metastatic breast cancer sera Validation studies underway Results include potential targets for monoclonal antibodies and new chemical entities 900 samples; 1700 gels; 1800 annotations

16. Age Matched Serum Samples � Pre & Post Menopause

18. Univariate Selection Criteria (an example)

19. Univariate Analysis

20. Multivariate Analysis Linear Discriminant Analysis (LDA) Cross Validation � Leave one outTake one sample outEstimate the LDA equationPredict the category for the sample (taken out)Estimate the miss-classification rates

21. Linear Discriminant Analysis 

22. Other Isoforms as Discriminants

23. Mining for Assay Specificity We have identified a cohort of approximately 30 Protein Features having the ability to discriminate between sample types. These protein features can be combined to form specific assays. Some possible scenarios for combining are: Minimizing the different proteins involved Combining all the isoforms of a specific protein Combining minimum number of proteins with no isoforms

26. Rat Serum - Gel View

27. Rat Serum � Master Group

31. Disease Associated Protein Isoforms:A Case Study in Schizophrenia CSF Single gene locus 29 observed isoforms in CSF Isoform changes disease-specific

32. PEDF Isoforms in Human CSF: Mapping to the Genome

33. PEDF Proteolysis in Schizophrenia

35. Acknowledgments The OGS Proteome Discovery team Christian Rohlff, Director of Proteome Research Collaborations, Oxford GlycoSciences, (Christian.Rohlff@ogs.co.uk) Breast Cancer studies: Ludwig Institute/ICRF London Cardiotoxicity studies: F Sistare, FDA, USA CSF studies : R Post & H Manji / NIMH, USA Copies of selected publications available