Proteomic profiling by antibody micro array
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Proteomic Profiling by Antibody Micro-Array. Kent J. Johnson M.D. Roscoe L. Warner Ph.D. Piezorray Non-Contact Printer. Micro-Array System. Y Y. Y Y. Y. Y. Y. DyLight 650 NeutrAvidin. Y. Y Y. Y. Y Y. Y. Y. Y. Biotinyled Secondary Antibody. Y. Y Y. Y. Y. Sandwich ELISA.

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Proteomic profiling by antibody micro array
Proteomic Profiling by Antibody Micro-Array

Kent J. Johnson M.D.

Roscoe L. Warner Ph.D.



Micro-Array System

Y Y

Y Y

Y

Y

Y

DyLight 650NeutrAvidin

Y

Y Y

Y

Y Y

Y

Y

Y

Biotinyled

Secondary Antibody

Y

Y Y

Y

Y

Sandwich ELISA

Target Antigens (Std. or Sample)

Y Y

Y

Y

Y Y

Y

Y

Y

Y

Primary Antibodies

MFI Intensity of Standards

Used for Calculation of Unknowns


Representative well
Representative Well

Chip

Primary Antibodies

….. ….. ….. ….. …..

….. ….. ….. ….. …..

….. ….. ….. ….. …..

….. ….. ….. ….. …..

IL-2

IL-6

IL-8

IL-10

IL-17

IL-2R

TNFa

IFNg

GM-CSF

IP-10

RANTES

EGF

MCP-1

MCP-3

MMP-7

KIM-1

Isotype Controls: Mouse, Rabbit, Human

Each spot receives 325 picoL

of antibody solution applied to

Sialylated Chips as a

Piezorray-static spray

Spot size: 120 mm


Chip-Plate Technology using 5 chips

in an 80 well grouping

Prototype Lab (UM: Medical Innovation Center)


Chip-1

Chip-2

Chip-3

Chip-4

Chip-5

Standard Curve


Cross-Reactivity Testing

Second Series

First Series

DyLight 550 NeutrAvidin

DyLight 650 NeutrAvidin

Y

Y

Y

Biotinylated Secondary Antibody

Y Y

Y

Y

Y

Y

Biotinylated Secondary Antibody

Y

Specific Antigen

YYYYY YYYYY YYYYY

YYYYY YYYYY YYYYY

YYYYY YYYYY YYYYY

YYYYY YYYYY YYYYY

YYYYY YYYYY YYYYY

YYYYY YYYYY YYYYY

MFI Intensity of DyLight 550 and DyLight 650


A.

B.

C.

Determinations

1

2

3

4

5

6

Specific Binding

of Antigen

1

2

3

4

5

6

Non-Specific Binding

of Secondary Antibody


Development of standard curve and linear range
Development of Standard Curve and Linear Range

Standards used as Log4 dilution of master mix plus a zero value.

Standard Curve generated for each antigen and equation of the

line determined.

Antigen concentration of samples calculated from equation of the line.


Performance of Micro-Array Methodology

Human Micro-Array Chip System


Advantages of custom antibody micro array
Advantages of Custom Antibody Micro-Array

  • Easily modified to accommodate unique target antigens.

  • Ability to custom develop chips for desired species, limited

  • only by availability of purified antigen and antibodies.

  • 3. Quantifiable approach to high throughput analysis of multiple

  • antigens using small sample size.

  • 4. Only One U.S. company to date makes Antibody Arrays.

  • 5. Comparable technologies include ELISA, Bead-based assays,




Rat models
Rat Models

Dermal Arthus

Glucan

Streptozotocin Induced Diabetes

Gentamicin

Cyclosporin A

Fenoldopam




Cyclosporin A Injury

*Significantly Different (p < 0.05), Mean +/- SD of Cyclosporin treated rats (n=10) and normal healthy (n=10) control animals.




Analytes of Wegener’s Granulomatosis Patients

.

Proteins Normal (pg/mL) Wegener’s Fold

Granulomatosis change

(pg/mL) .

ACE-1 3,290.1 (+/- 214.3) 5,927.1 (+/- 283.0)* + 1.8

IFN-g 23.4 (+/- 3.4) 151.4 (+/- 19.5)* + 6.5

IL-8 1.7.3 (+/- 9.0) 1,294.0 (+/- 55.3)* + 12.1

s-ICAM 6,195.2 (+/- 533.7) 12,679.4 (+/- 870.7)* + 2

s-VCAM 120.7 (+/- 26.5) 674.3 (+/- 28.8)* + 5.6

.

The quantified values along with standard error of the mean (in parenthesis) are shown and allow for comparison of normal (n=30) and WG serum (n=26) samples. The fold change shows the difference between the normal and affected patients with positive (+) indicating an increase in WG patient serum.


Rave clinical trial
RAVE Clinical Trial

Rituximab in ANCA-Associated Vasculitis (RAVE) trial

Long-term program to identify markers that are clinically useful

in staging vasculitis activity, distinguishing vasculitis from other

inflammatory diseases such as infections, and predicting

response to treatment and risk of relapse.


Of the 186 subjects evaluated at screening,

139 had been diagnosed with GPA and 46 with MPA;

124 were positive for anti-PR3 and 62 for anti-MPO

93 had active glomerulonephritis

90 had a new diagnosis of AAV

96 had established diagnoses and were experiencing relapses.

At screening:

92 patients were receiving glucocorticoids, and

104 were receiving some immune-suppressive drug (glucocorticoids, other drugs, or both).

The 68 healthy controls included 28 males and 40 females, median age 41.


Use of multiple markers to better distinguish severe or mild vasculitis from remission
Use of Multiple Markers to Better Distinguish Severe or Mild Vasculitis from Remission

Four markers (CXCL13/BCA-1, G-CSF, IL-15, and TIMP-1) were significantly higher at month 6, after adjustment for multiple comparisons, in the 25 subjects with active disease than in the 137 subjects in remission,

Five additional markers (IFNg, CXCL8/IL-8, sIL-2R, CCL5/RANTES) might be higher based on unadjusted P values of < 0.05.

Discrimination between mild disease and remission at month 6 was limited, with all AUC < 0.7


Based on logistic regression models with active disease vs. remission as the dichotomous outcome, the set of markers that best distinguished active AAV from remission in the 137 subjects with paired samples was:

ACE (negatively), GM-CSF, MMP-3, TIMP-1, and ESR, with AUC=0.96.

Odds ratios (for active AAV vs. remission in these 137 subjects) associated with 2-fold changes in these markers. When these 5 markers were used to model data limited to month 6, comparing 25 subjects with milder active AAV to 137 in remission, AUC=0.78.



Our findings demonstrate that the protein signature of healthy subjects is distinctly different from renal transplant patients with good allograft function and no previous history of rejection.

We have identified 10 proteins that can reliably differentiate stable renal transplant recipients from healthy subjects in both the training and validation cohorts.

Cystatin-C, EGF, GM-CSF, IL-1 R1, IL-5, KIM-1, MCP-1, MCP-3, MIF, TIMP-4

In addition, 17 proteins were identified that can differentiate rejecting renal transplant recipients from stable renal transplant patients.

TGF-β2, E-Cadherin, GROα, TGF-β1, IL-6, IL-1 R1, EGF, MIP-3α, TNF-RII, KIM-1, Osteopontin, VEGF-R2, Epo-R, MIF, IL-12p70, MCP-1, GM-CSF

The ultimate goal of the protein array is be to monitor non-invasively, renal transplant patients over time in order to detect subclinical changes before they would be detected by conventional methods, ie., change in serum creatinine levels, with the intent to alter long-term graft outcome.


Micro array chip and proplate mask
Micro-Array Chip and ProPlate Mask healthy subjects is distinctly different from renal transplant patients with good allograft function and no previous history of rejection.

TM


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