differential protein expression analysis for biomarker discovery

Differential Protein Expression Analysis for

Biomarker Discovery

Biomarker discovery phase

Develop strategy tailored to samples under study Broad range of conditions

Fractionation

Test multiple chip binding conditions

Each sample generates >36 spectra

Data analysis

Univariate: Biomarker Wizard

Multivariate: Biomarker Pattern Software

Cancer Biomarker Discovery Sample Sources – Dilution of Markers with Distance from Tumor

Sample Type:Neoplastic

TissueCytology Body Fluids

Biomarker Concentration High Medium Low

Examples Analyzed by ProteinChip® Technology

Biopsy LCM

Seminal Plasma Nipple Aspirates

Fine Needle Aspirates

Serum Plasma Urine


Develop strategy tailored to samples under study

Broad range of conditions

Fractionation Test multiple chip binding conditions


Data analysis



Strong anion exchange resin

Fx1 Fx2 Fx3 Fx4

Serum sample+ Urea/CHAPS/TrisHCl pH 9

Protein Profiling of Serum

Flow-through

pH 7 pH 5 pH 3

Fx5 Fx6

pH 4 ACN

Fractionation increases peak count

7500 8000 8500 9000 9500

7500 8000 8500 9000 9500

Total serum

Q Fraction 1

Q Fraction 2

Q Fraction 3

Q Fraction 4

Q Fraction 5

Q Fraction 6



Broad range of conditions Fractionation



Data analysis



Crude Serum Samples

Flow-ThroughpH 9pH 7pH 6pH 4Organic Wash

Anion Exchange Fractionation

H501%TFA1%TFA+10%MeOH1%TFA+25%MeOH1%TFA+1M KCl1%TFA+0.4M KCl1%TFA+0.1M KCl

WCX2pH4pH4+0.1M KClpH4+0.4M KClpH6pH7pH9

IMAC-CuPBSPBS+500mM KClPBS+20mMimmidazole

SAX2pH8pH8+0.1M KClpH8+0.4M KClpH6pH4pH3

NP20WaterPBS+0.5M KCl

ProteinChip® SystemSerum Fraction for High Resolution Profiling

Combined Peak Counts (unique per Surface)

Array Type

H50 (RP) 252

IMAC-Cu 317

SAX2 416

WCX2 365

NP20 N/D

Unique Peak Count

ProteinChip® SystemHigh Resolution Serum Profiling

5000 7500 10000 12500

5000 7500 10000 12500

Rev ersed- Phase ProteinChip

Strong Anionic Exchanger (pH 8.5)

Weak Cationic Exchanger (pH 4.5)

Reversed-Phase (water wash)

Strong Anionic Exchanger (pH 8.5

wash)

Weak Cationic Exchanger (pH 4.5

wash)

Protein Profiling: Crude liver extracts from treated animals profiled on Reversed-Phase, Strong Anionic,

or Weak Cationic Exchange Surfaces

1 0 0 0 0 1 2 0 0 0 1 4 0 0 0

1 0 0 0 0 1 2 0 0 0 1 4 0 0 0

74 1

74 2

74 3

74 4

SA

X2 C

hip

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)S

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hip

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Assay Reproducibility: Crude Rat Liver Lysate Profiled on a Strong Anion Exchange ProteinChip Array

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nsity

(av

erag

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eadi

ngs)

Peak No.

Standard Error 10-25%n=8

19 representative peaks were picked at at random for the analysis

Assay Reproducibility: Crude Rat Liver Lysate Profiled on a Strong Anion Exchange ProteinChip Array

Reproducibility of assays25000 50000 75000

25000 50000 75000

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# of Exp.

The ProteinChip® Bioprocessor

Biomek 2000



Broad range of conditions

Fractionation



Data analysis Univariate: Biomarker Wizard


Multi-marker Analysis using a Large Patient Population – A Prostate Cancer Study

Dr. George Wright, Jr., Virginia Cancer Center, EVMS

Early Detection Research Network (NCI)

Biomarker Center™ (Ciphergen Biosystems)

Prostate Cancer Serum Analysis Study Clinical Question

To classify patient groups based on serum sample analysis

Elucidate important peaks used in the classification schema

Study design

Sample size sufficient to generate good statistics (n = 385 patient samples)

Study included samples that should be easy to classify (late stage cancer versus normal elderly patients)

Study additionally included difficult to classify benign prostatic hyperplasia (BPH) cases

Biomarker ProfilesN

orm

alC

ance

r

Nor

mal

Can

cer

Sampling of spectra from 6 samples at low and high mass. Zoomed in portions showing candidate markers.

Low MW range

High MW range

Serum Profiling for Prostate CancerLike peaks chosen across all samples are analyzed

10000 20000 30000

10000 20000 30000

“Normal”

Cancer

“Normal”

Cancer

GelViews ofsame data

5000 10000 15000 20000 25000 30000

5000 10000 15000 20000 25000 30000

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500010000150002000025000300005000100001500020000250003000050001000015000200002500030000500010000150002000025000300005000100001500020000250003000050001000015000200002500030000

Analysis of Control and Treated Samples on a Strong Anion Exchange Surface Prepared at

pH8.0

All 40 spectra saved in the same ‘xpt’ file

All 40 spectra saved in the same ‘xpt’ file

Normalised on Total Ion Current

Normalised on Total Ion Current

Peak Clusters detected using

Biomarker Wizard

Peak Clusters detected using

Biomarker Wizard

Box and Whisker Plot

Linear Normalised Intensity

Log Normalised Intensity

Clustering: Discovery of Biomarker Candidates by using the Biomarker Wizard

Highlights up- and down- regulated proteins between groups of samples

Biomarker Patterns™ Software

Benefits of Multi-marker pattern analysis a classification software-- determines rules that best group

samples of known phenotype

a tree building software-- reports the important variables (proteins) and the rules in creating the decision tree- the hard work it does for you!

a multivariate analysis-- uncover hidden expression patterns in high dimensional data

Improves the predictive value over univariate analysis

Accommodates biological and systemic variations

uses relatively small sample sets (~30 per group) for both model building and cross-validation

Takes direct data import from ProteinChip® Software 3.0 – seamless transition

20 Controls 15 Correctly Classified20 Disease 18 Correctly Classified

20 Controls 15 Correctly Classified20 Disease 18 Correctly Classified

Does Peak at 10617Da have an intensity less than 34.67 ?

healthydisease

34.67

Does Peak at 5051Da have an intensity less than 24.29 ?

healthydisease24.29

a BPS Example

Yes No

5 Healthy18 Disease

4 Healthy0 Disease

11 healthy2 Disease

TerminalNode 1N = 23

TerminalNode 2N = 4

Node 2M5051_83

N = 27

TerminalNode 3N = 13

Node 1M10617_6

N = 40

Yes No

Biomarker Patterns™ AnalysisSample Results from a Prostate Cancer Serum Study

For 385 starting samples:• 131 of 196 cancer samples classified correctly (sensitivity)• 162 of 189 non-cancer samples classified correctly (specificity)

Sensitivity: 66.8%Specificity: 85.7%

Classification:

• Correctly

• Incorrectly

Peak ACriterion(n=385)

Peak BCriterion(n=203)

Non-Cancer(n=182)

Cancer(n=122)

Peak CCriterion(n=81)

Peak DCriterion(n=54)

Non-Cancer(n=18)

Non-Cancer(n=27)

Cancer(n=36)

“CANCER” = Stage II or III prostate cancer (196 samples)

“NON-CANCER” = patients who were either normal or showing signs of benign prostatic hyperplasia (189 samples)

Data courtesy of Dr. G. Wright, Jr., Virginia Prostate Cancer Center.

Non-cancer: 123

Cancer: 31

Non-cancer: 14

Non-cancer: 25

Cancer: 100

Cancer: 59

Non-cancer: 5

Cancer: 4 Cancer: 2 Non-cancer: 22

vs. PSA Test (Sen./Spe.):75% / 30% lower PSA threshold40% / 65% higher PSA threshold

Results for Highly Stratified Data Set

Peak ACriterion(n=194)

Peak BCriterion(n=102)

Peak CCriterion(n=92)

Peak DCriterion(n=92)

Normal(n=3)

Cancer(n=89)

Normal(n=10)

Normal(n=82)

Cancer(n=10)

Sensitivity: 98.0%Specificity: 96.9%

For the 194 starting samples:• 96 of 98 cancer samples classified correctly• 93 of 96 normal samples classified correctly

Normal: 3 Cancer: 87

Normal: 9 Cancer: 9 Normal: 81

Cancer: 0 Normal: 2 Cancer: 1 Normal: 1 Cancer: 1

“CANCER” = Stage II or III prostate cancer

“NORMAL” = age-matched normal patients

Data courtesy of Dr. G. Wright, Jr., Virginia Prostate Cancer Center.

Prostate Cancer Study Conclusions

Multiple biomarkers were identified from serum using only one type of ProteinChip® array and one wash condition

Biomarker Patterns™ software identified potential biomarkers and classification criteria, and assembled these into a predictive tree

Sensitivity and specificity for both low and high grade prostate cancer were > 90%

Prostate Biomarker Clinical Study – Progress of Clinical Validation and Power of Multimarker Assays

Sensitivity(“True

Positives”)

Specificity (“True Negatives”)

Single Markers from Seminal Plasma Study (152 samples)

57% (Range 42- 85%)

38%(Range 26- 58%)

PSA (total, cutoff = 5 ng/ml) 65% 35%

Accepted Threshold for Clinical Utility 80% 80%

Multivariate Combination of 8 Seminal Plasma Markers

85% 83%

Cancer Study

Sensitivity

Specificity Institution

Ovarian 94-100% 96% NCI, FDA, Northwestern

Prostate 93.3% 93.8% Eastern Virginia Medical School

Breast 92% 82% Johns Hopkins Medical School

Liver 92.5% 90% Chinese University of Hong Kong

Bladder 79% 81% Eastern Virginia Medical School

Rates of cancer detection including sensitivities (true

positives) ranging from 68-100% and specificities

(true negatives)ranging from 81-96%.

Highlights of selected papers presented at AACR 2002:

differential protein expression analysis for biomarker discovery

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