Dr Chris Southan, Protein Atlas Database Manager, Oxford Glycosciences UK Ltd

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Dr Chris Southan, Protein Atlas Database
Manager, Oxford Glycosciences UK Ltd
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Proteomics - fulfilling the promise of genomics
BioMarkers
Therapeutic Antibodies
Target Protein
Small Molecule Drug Candidate
Human Genome
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Genome gt Transcriptome gt Proteome
Secreted protein Bio-markers - quantity? -
origin ?
transcriptional control
translational control
post-translational control
protein complex formation

• Drug target
• Composition
• of complexes

DNA
RNA

• Protein

• PTMs

Gygi et al. 1999 MCB 19, 1720-1730.
Genomics
Proteomics
Array
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Limitations of the Transcriptome as a Surrogate
for the Proteome

• Lack of correlation, qualitative as well as
  quantitative
• Limited sub-cellular or translocation information
• Limited insights into protein isoforms
• Ambiguous assignment of an EST to a
  protein-coding gene

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How Accurate is the Transcriptome ?
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How Accurate is the Transcriptome?
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Protein Isoforms

• Protein isoforms are numerous, highly conserved,
  and change in a disease-associated way
• These isoforms both yield novel insights into
  pathogenic mechanisms and provide drug targets,
  biomakers
• Discovery of protein expression or isoforms by
  genomics is strictly limited
• Unambiguous annotation of the human genome to
  find protein-coding genes can only be achieved
  through proteomics

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OGS Proteomics Technology Principles
The whole process is fully integrated by state of
the art proprietary bioinformatics tools
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Proteomics Analytical Platform

• Customer Sample
• Preparation

Biological Samples
Peptide Sequence
Protein Extract
Detection
Separation
Selection

• Protein of Interest
• Customer Request

• Post Separation
• Fluorescence

• High Resolution
• SDS-Page
• 1D 2D
• m-HPLC

• Total Extract
• Serum Depletion
• Fractionation

DNA/EST Database

• Program
• Defined

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First generation proteomics platform 2-D gels ?
MS
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Matrix Technology
Proprietary attachment chemistry
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IEF Zoom
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IEF Std.
facing plate
gel plate
bar-coded
2nd dimension polymer

• reproducibility
• long-term archiving

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Comparison of Staining Methods
Limit of Protein MS
Detection Modification Compatible Coomassie 100
ng No Yes Blue Silver Stain 1.0
ng Yes No Fluorescent .1 ng No Yes OGS Dye
Dynamic range 4 log orders
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Creating a Proteomics Database
Rep No1
Rep No2
Rep No3
Composite Gel
Master Cluster Feature
Database Entry
Master Group
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Electronic Mastergroup
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Serum High Resolution Maps
3-10
gt1200
700
Original serum
Enriched serum
gt2000
6-8
pH Range 3.5-5
5-7
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Bio-Markers from fluids only accessible to
proteomic technologies

• Accessible body fluid eg. blood, urine, CSF
• dynamic markers quantitative variations
• Cross-sectional and longitudinal analysis of
  entire biofluid proteome
• Discovery of dynamic bio-markers of disease
  progression and therapeutic response
• Essential for informed clinical trial
  decision-making and monitoring
• Critical to rank and select new therapeutic
  modalities

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Mapping peptides to the human genome
2-D PAGE
ICAT

• Disease/protein/gene Target Class
• Identify disease protein Cell membrane
• Protein sequence Kinases
• Map to gene Proteases
• Complementary approaches Other

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Isotope Coded Affinity Tags (ICAT)
Sample Type 1
Sample Type 2
Fractionate?
Combine
Fragment, e.g., Trypsin
Affinity Purify Labelled Peptides.
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ICAT Affinity Tags
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ICAT Identification of Proteins Following
Quantitative Differential Analysis
Quantitation e.g., LC-MS, MALDI,
ESI-TOF.
Int.
m/z
K
L
Y
G
P
Identification LC-MS/MS
m/z
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How Many Protein-Coding Genes are in the Genome?

• SwissProt / TREMBL (SP/TR) 24211
• Ensembl 3.26.1 34019
• SP / TR / Ensembl 33817
• SP / TR / Ensembl / Ref Seq 54687
• International Protein Index

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Protein Mapping Direct to Genome
peptide sequence
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Mapping peptides to the human genome defining
gene structure

• Map all peptides from protein

• Determine exon structures

• Determine gene structure
• Detect novel exons/splice forms/genes

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Mapping peptides to the human genomeMaking the
Protein Atlas
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Implementation of Proteomics for Cancer

• Critical need for proteomics
• Need to adopt an integrated approach which
• reflects biological processes and clinical
  relevance
• Proteomics Cancer search gives 18 title hits
  in PubMed but none before 1999

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Proteomics for Cancer discovery

• NCE Targets
• Whole cell proteomics
• Highly purified cancer/normal samples
• Sophisticated data analyses
• Direct selection of cancer targets
• 2. Antigens for immunotherapy
• Membrane proteomics for candidate antigens
• Cancer targets defined by proteomics other
  means

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Proteomics - Discovery of Protein Targets for
Breast Cancer
Clinical Network
Ludwig Institute of Cancer Research
Disaggregation
Selection

• immunomagnetic
• cell sorting

Cell types

• gt98 purity
• luminal
• myoepithelial
• endothelial
• fibroblasts

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Human Breast Cancer Staging
Normal
HUT Hyperplasia of U Type (Pre invasive)
ADH ( Atypical Ductal Hyperplasia)
DCIS (Ductal Carsinoma In Situ)
LCIS (Lobular Carcinoma In Situ)
IDC (Invasive Ductal Carcinoma) 60 of Cancers
ILC (Lobular Ductal Carcinoma) 30 of Cancers
Grade I
Grade I
Grade II
Grade II
Grade III
Grade III
PE
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Purified luminal vs non-purified cells
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Human Breast Cancer - Protein Database
Pleural Effusions
Normals
Primary Tumours
Breast Cancer Cell Lines
Breast MasterGroup
202 Samples 9809 Protein Features
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Breast Cancer - Stage Specific Proteins
IDC vs. normal
ILC vs. normal
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123
19
15
2
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p lt 0.05
PE vs. normal
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243 Breast Cancer Targets Markers

• Proteases
• Signal transduction
• Kinases phosphatases
• Metabolism
• Lipid processing
• Chaperones
• Stress proteins
• Structural
• Cell-cell interactions
• Nuclear proteins

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Breast Cancer Antigens - immunotherapy

• Membrane preps from 3 breast cancer cell lines
  and 1 large primary, 1D 2D gels -gt MS
• Huge enrichment for membrane / secreted proteins
  ( cell surface )
• Discovery of known antigens, known membrane
  proteins, novel antigens
• Selection of candidates for immunotherapy
• Ranking via predictions mRNA profiles -
  overexpression in cancer, restricted vital organ
  expression, and trans membrane domains

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Membrane Antigen Discovery
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Membrane Antigen Discovery 1D gel proteomics

• Better than 2D gels for cell membrane
  preparations
• Easily adapted to OGS MS identification
  technology and data processing
• More high MW transmembrane domain containing
  proteins identifed

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Membrane Antigen Discovery
Known Antigens Known proteins - new
antigens Novel proteins ErbB2 BCMP453 668H4
Muc-1 NCAM2 BCMP11 ICAM1 FMLP-R BCMP84
CD98 ADAM10 Muc-like GA733.1/2 KIAA0152
BCF317 EGF receptor Ion Channels PECAM Tra
nsporters CD44
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BCMP11 BCMP84 BCMP453 QT PCR across tissue
samples
BCMP11 BCMP84 BCMP453
80 prevalence
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BCMP84 Immuno Cytochemistry ( rabbit
polyclonals )
aBCMP84 MDA468s breast cancer cell line
-ve cell line T47D breast cell line
Membrane staining
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BCMP84 - ICC MDA468s - confocal demonstration
of membrane localisation
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Breast cancer proteomics summary
targets and markers with direct cancer
relevance purified, characterised
samples stringent selection - novel proteins,
disease specific isoforms novel NCE targets and
biomarkers cancer antigens broad
application to many cancers discovery
validation using easier to obtain
samples novel immunotherapy targets
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Acknowledgements
Dr Christian Rohlff and the OGS Operations
team Dr Jon Terret and the OGS Molecular Biology
team