IOSI Journal Club 2007,05,04 Paolo Kunderfranco PhD Student S-I Hwang, Oncogene 2007 26,65-76.

IOSI Journal Club

2007,05,04

Paolo Kunderfranco

PhD Student

S-I Hwang, Oncogene 2007 26,65-76

What is Proteomics?

Proteomics is the systematic identification and characterization of proteins for their structure, function, activity, quantity, and molecular interactions

Proteome:

• A catalog of all proteins• Expressed throughout life• Expressed under all conditions

The goals of proteomics:

• To catalog all proteins• To understand their functions• To understand how they interact with each other


The current status of proteomic technologies, the different data typically collected in proteomic research and the

available technologies are listed

Why might proteomics be more challenging than

genomics?

• Splice variants create an enormous diversity of proteins– ~25,000 genes in humans give rise to 200,000 to 2,000,000 different proteins– Splice variants may have very diverse functions

• Proteins expressed in an organism will vary according to age, health, tissue, and environmental stimuli

• Post-Translational Modifications– Phosphorylation, Acetylation, Methylation, Acylation, Glycosylation, GPI

anchor, Hydroxyproline, Sulfation, Sumoylation, Disulfide-bond formation, Deamidation, Pyroglutamic acid, Ubiquitination and many others……

– Proteolytic cleavege


Why might proteomics be more challenging than

genomics?Proteomics requires a broader range of

technologies than genomicsDIGE Mass spectrometry Protein chips

LCM Yeast two hybrid Interactome


Practical Applications

• Comparison of protein expression in diseased and normal tissues– Likely to reveal new targets

• Today ~500 drug targets• Estimates of possible drug targets: 10,000 to 20,000

• Help to establish proteomic libraries

• Protein expression signatures associated with drug toxicity– To make clinical trials more efficient– To make drug treatments more effective

• Large scale genomics and proteomic characterization of cancer tissues will provide novel insights into the early detection and effective treatment of cancer


Proteomics is instrumental in discovery of biomarkers

What is DTP?

• Direct tissue proteomics: a shotgun proteomics approach, which provides the chemical identity of proteins in cells, tissues and fluids

• Direct Tissue Proteomics identifies proteins in formalin-fixed paraffin embedded tissues using shotgun proteomics methods via tandem mass spectrometry (MS/MS)

• Allows the detection of diagnostic biomarkers and therapeutic targets

• Uses minute tissue biopsy sections


Goals

• Determine if proteins can be conclusively identified from small quantities of biopsy tissue samples from clinically relevant prostate cancers.

– how many proteins can be conclusively identified in small quantities of prostate cancer biopsy tissues using the shotgun proteomic method?

– can a current prostate cancer protein biomarker, such as PSA, be robustly identified using this approach?

– can additional proteins involved in prostate tumorigenesis also be detected using this method?


Flow diagram of the DTP procedure (1)Flow diagram of the DTP procedure (1)

Proteomic Analysis

H & E staining

Gleason Scoring

Bioinformatics

Validation

Immuno- histochemistry

AQUA


A schematic flow diagram depicting the steps for proteomic identification, quantification and validation of prostate tissue arrays


• Commercially available tissue array– 5 normal and 25 cancer biopsy sections in duplicates ( 4μm

thick x 2mm diameter)

• Subdivision of all the tissues according to Gleason s.

• Optimization of protein extraction from PFPE arrays:– Reversing paraformaldehyde crosslinks– Sequencing-grade modified Trypsin digestion of tissues

• Data dependent mass spectrometry analysis– Separating the tryptic peptides using reverse-phase

chromatography– Protein identification using the μ-capillary-LC–MS/MS

proceduresS-I Hwang, Oncogene 2007 26,65-76

low medium

highcontrol

3 6 10Gleason s.



• Data analysis and interpretation

– SEQUEST algorithm”SEQUEST correlates uninterpreted tandem mass spectra of peptides with amino acid sequences from protein and nucleotide databases”

– INTERACT software tool“INTERACT was developed to address the need to curate large datasets from tens to hundreds of LC-MS/MS runs covering multiple tens of thousands of MS/MS spectra”

– PROTEOME-3D software“An Interactive Bioinformatics Tool for Large-Scale Data Exploration and Knowledge Discovery”

– INTERSECT software tool“Allow the generation of a stage specific prostate expression library

N° of identified proteins from each of the 4 Gleason

categories

Functional characterization of identified proteins into 24

GO categories

Results (1)


Identification of 12631 peptides resulted in a list of 428 unique proteins with high confidence

identification

Grouping of enzyme implicated in energy metabolism revealed that:

1. Gluconeogenesis enzymes are preferentially expressed in low and medium stage prostate cancer

2. TCA enzymes were detected in multiple stages of prostate cancers

3. Glycolysis enzymes are found in normal tissue as well as in the cancerous prostate tissues

Results (2)


Detection of know markers of prostate cancer

• Identification of PSA1. MS/MS spectrum of a PSA peptide

Sorting for the KLK3_HUMAN resulted in the identification of 214 tryptic peptides

• Identification of PSA2. Peptide sequence coverage of PSA protein

Coverage: AA 61,7% (161/261 residues)Mass: 63,0% (18102/28741 Da)

3. Estimation of the relative abundance of PSA peptides in normal and cancerous prostate cancer biopsies

Results (2)


Detection of know markers of prostate cancer

How sensitive is the DTP methodology?

Scott A. Gerber, PNAS 2003 12,6940

The DTP technology is not quantitative

• ACQUA: Absolute quantificationDirect quantification of differences in protein and post-translationally modified protein expression levels

This methodology utilizes a standard peptide with known quantity to compare against a biological sample to establish the absolute quantity of protein in the mixture

AQUAMethod development

A PSA peptide was synthesized with deuterium-labeled valine (8Da heavier than normal valine)


AQUAQuantification experiment (1)

100 femptomole (fmol) of standard peptide were spiked in the trypticdigested tissue sections

Two fragment ions from the standard peptide and the endogenous PSA peptide were used for the MRM experiment

ABSOLUTE QUANTIFICATION

peak area of the endogenous peptide

peak area of the AQUA standard peptide

amount of standard spikedX


AQUAQuantification experiment (2)

Extracted ion chromatograms of standard PSA peptides (black) and endogenous peptides (highlighted) from normal control prostate (blue) and three cancer grades (green, orange and red)

Quantification values of PSA from a total of five normal samples and 15 cancerous samples. The values in fmols are converted to pg amounts

The range of PSA quantified directly from the tissues was 0.5–140 pg


• Search for additional proteinsThree broad categories

1. Androgen Rensponsive and Androgen Receptor regulators

2. Known oncoproteins 3. Stromal-associated proteins

Results (3)


Serum PSA levels do not always predict the presence of p.cancer

ClassSwiss Plot Entry Name

Common NameCancer Grades

Control Low Medium High

Androgen Regulated Proteins

NDR1_HUMAN NDRG1 protein (n-myc downstream regulated gene 1 protein) 7 6 24 26

CLUS_HUMAN Clusterin [Precursor] 4 10 34 14

BC007997 Ras-related estrogen-regulated growth inhibiting protein 11 13 54 29

JE0350 Anterior gradient-2 0 3 29 22

PHB_HUMAN Prohibitin 6 9 14 21

Androgen Receptor Repressors

CRTC_HUMAN Calreticulin [Precursor] 2 12 19 14

FKB5_HUMAN fk506-binding protein 5 10 15 40 24

Androgen ReceptorCo-regulators

CTNB_HUMAN Beta-catenin 11 12 43 14

EZRI_HUMAN Ezrin 6 17 34 19

ILK1_HUMAN Integrin-linked protein kinase 1 9 13 24 8

HS9B_HUMAN Heat shock protein HSP 90-beta 11 32 65 66

HS76_HUMAN Heat shock 70 kDa protein 6 9 5 26 15

Androgen Receptor Co-activator

FLNA_HUMAN Filamin A 609 611 1959 782

RAN_HUMAN GTP-binding nuclear protein Ran 2 2 12 9

IMB1_HUMAN Importin beta-1 subunit 7 9 30 20

Oncogene

MUC1_HUMAN mucin 1 precursor 1 6 8 3

PIM1_HUMAN proto-oncogene serine/threonine-protein kinase pim-1 3 2 14 6

JC5394 DJ-1 protein 10 12 34 9PTEN_HUMAN phosphatidylinositol-3,4,5-trisphosphate 3-phosphatase pten 1 3 11 8WNT3_HUMAN Wnt-3 proto-oncogene protein [Precursor] 11 15 33 11

WN3A_HUMAN Wnt-3a protein [Precursor] 34 47 141 77

ZA2G_HUMAN zinc-alpha-2-glycoprotein precursor 7 4 53 11

Angiogenic and cancer stroma associated proteins

KIHUG phosphoglycerate kinase 2 1 8 1

LEG1_HUMAN galectin-1 16 13 34 18

LEG3_HUMAN galectin-3 3 3 11 2

FBL5_HUMAN fibulin-5 precursor 10 2 24 5

MIF_HUMAN macrophage migration inhibitory factor 6 9 33 19

Growth InhibitorsTRFL_HUMAN lactotransferrin precursor 24 40 110 13

THIO_HUMAN thioredoxin 1 4 14 6

Cancer associatedENPL_HUMAN endoplasmin precursor 8 24 78 46

SBP1_HUMAN selenium-binding protein 1 0 15 30 9

Results (3)


Wnt-3, wingless-type MMTV integration site family, member 3

• Identified with multiple peptides control low medium high

WNT3_HUMANWnt-3 proto-oncogene protein

[Precursor] 11 15 33 11

WNT3A_HUMAN Wnt-3a protein [Precursor] 34 47 141 77

Results (3)


• Wnt proteins form a family of highly conserved secreted signaling molecules that regulate cell-to-cell interactions during embryogenesis

• Wnt proteins are secreted protein ligands for cell surface receptors of the frizzled and lipoprotein receptor-related protein family

• The Wnt family of proteins is known to cause oncogenic transformation in a number of cell systems including the prostate cells

• Wnt-3a protein was shown to support the androgen-independent growth of LNCaP prostate cancer cells


Results (3)


Wnt-3, wingless-type MMTV integration site family, member 3Wnt-3 protein immunohistochemistry on the prostate cancer tissue

arraysa) Basal epithelial cells from normal prostate glands

Immuno-reactivity restricted to a few clusters of basal epithelial cells of the prostate glands

b) Luminal epithelial cells of the prostatic intraepithelial

neoplasia

Significant upregulation of Wnt-3 protein was detectable

Results (3)



Wnt-3 protein immunohistochemistry on the prostate cancer tissue arrays

c) Advanced prostate cancer

Strong immunoreactivity was seen in the neoplastic and invasive cells

d) Invasive prostate cancer

Results (3)



•Two fold increase in staining intensities was seen in the cancerous glands of the prostate

•Indeed DTP provides additional protein targets tha may participate in prostate carcinogenesis

Remarks


Primary focus of this study is not about the discovery of novel biomarkers, but to1. Prove that protein identification from archival FFPE is feasible2.To demonstrate that PSA can be detected and quantified by this method3.To demonstrate that this method allows identification of new biologically interesting proteins

But...Discrepancy between published microarray cDNA data sets and identified proteins

Remarks & Comments


•Cancer tissues are heterogeneous in natureMost cancer cells are mixed with normal cells

•Cellular to stroma ratios can be very different in distinct areas

How to normalize the cellular and matrix components???

•Proteomic shotgun approaches suffer from undersampling

the expressed proteinsThe complexity is huge.................

•Duty cicle of the latest MS are relatively slow

•Compatibility between MS analysis and extraction buffer

How to increase the yield for the extracted proteins???

Remarks & Comments


These results sugget that

• More comprehensive characterization of proteomes and mRNAs from normal and cancerous cells

• Ability to analize proteins from pure cell populations, LCM, robots???

• Develop methodology to identify also low abundant and membrane bounds proteins, key enzymes and regulators???

• Are there only some limited genetic mechanisms for each tissue or cell specific cancer???

IOSI Journal Club 2007,05,04 Paolo Kunderfranco PhD Student S-I Hwang, Oncogene 2007 26,65-76.

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