Why Study Signaling Networks?

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Why Study Signaling Networks?

Define better therapeutic targets, or combinations

f h i f h h

of therapeutic targets for cancer or other human diseases

The Challenge: How do we get from genetic mutation to therapeutic targets?

genetic mutation to therapeutic targets?

Mutations in human glioblastoma tumor tissue, TCGA, Nature, 2008

Reprinted by permission from Macmillan Publishers Ltd: Nature. Source: The Cancer Genome Atlas Research Network.

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Why Study Signaling Networks?

Disease Stratification and Personalized Medicine:

Analyzing signaling networks can identify activated y g g g y pathways and thereby highlight therapeutic options

Courtesy of Elsevier, Inc., http://www.sciencedirect.com. Used with permission. For complete article, see Irish, Jonathan M., Randi Hovland, Peter O Krutzik, et al. "Single Cell Profiling of Potentiated Phospho-Protein Networks in Cancer Cells" Cell 118, no. 2 (2004).

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Why Study Signaling Networks?

Therapeutic Targeting and Efficacy – is the kinase inhibitor actually y affecting g the tar ggeted kinase?

How are cells in a tumor responding to therapy?

Merrimack – Her3 antibody

AstraZeneca – Gefitinib (Iressa)

AstraZeneca Gefitinib (Iressa)

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Why Study Signaling Networks?

Understanding mechanisms of resistance

Taniguchi et al, Nat. Reviews Mol. Cell Biol, 2006

Reprinted by permission from Macmillan Publishers Ltd: Nature Reviews Molecular Cell Biology. Source: Taniguchi, Cullen M., Brice Emanuelli, and C. Ronald Kahn. "Critical Nodes in Signalling Pathways: Insights into Insulin Action." Nature Reviews Molecular Cell Biology 7 (2006). © 2006.

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How to analyze signaling networks

Classical Approach: Western blots Reverse-Phase Protein Microarray Luminex/ELISA

Mass Spectrometry Phospho-FACS CS

Kinase Activity Assays

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Classical Approach: Western blots – Target Selection?

Reprinted by permission from Macmillan Publishers Ltd: Nature Reviews Molecular Cell Biology. Source: Yarden, Yosef, and Mark X. Sliwkowski. "Untangling the ErbB signalling network." Nature Reviews Molecular Cell Biology 2 (2001). © 2001.

Yarden and Slikowski, Nat. Reviews Mol. Cell Biol, 2001

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Limitations of the Western blots for signaling analysis

Labor-intensive

Limited number of targets

Antibodies – not as specific as advertised No discovery possibility

Q

Quantitation sub-optimal

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Micro-Western Arrays: Tackling the rate-limiting throughput of Western Blots

throughput of Western Blots

Reprinted by permission from Macmillan Publishers Ltd: Nature Methods. Source: Ciaccio, Mark F., et al.

. Ciaccio et al, Nat. Methods 2010

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Micro-Western Arrays: Not the best looking westerns, but still functional

but still functional

Reprinted by permission from Macmillan Publishers Ltd: Nature Methods. Source: Ciaccio, Mark F., et al.

.

Ciaccio et al, Nat. Methods 2010

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Reverse-phase microarrays: an alternate high-throughput strategy for quantifying signaling networks

strategy for quantifying signaling networks

Reprinted by permission from Macmillan Publishers Ltd: Nature Methods. Source: Sevecka, Mark and Gavin MacBeath.

Sevecka et al, Nat. Methods 2006

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How accurate are reverse-phase microarrays?

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Reverse-phase arrays: lots of data on a single chip

Sevecka et al, Nat. Methods 2006

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Using reverse-phase arrays to understand signaling networks

Sevecka et al, Nat. Methods 2006

Reprinted by permission from Macmillan Publishers Ltd: Nature Methods.

Source: Sevecka, Mark and Gavin MacBeath. "State-Based Discovery: A Multidimensional Screen for Small-Molecule Modulators of EGF Signaling."

Nature Methods 3 (2006). © 2006.

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Reverse-phase microarrays work, but accurate quantification is limited by non-specificity of the antibody. specificity of the antibody. How can we

is limited by non How can we

overcome this limitation?

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Luminex – improved specificity due to sandwich format, improved throughput with ~FACS-based quantification

Ph h ifi Ab

pY

Phospho-specific mAb

pY

Phospho-specific mAb

Anti-EGFR mAb

Anti-SHC mAb

pY

Phospho-specific mAb Up to 100 different

beads/targets per analysis

Anti-Erk2 mAb

Sandwich-ELISA format improves specificity

http://www.luminexcorp.com/

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All of these techniques are limited to well-characterized nodes in the signaling network, and limited by existing reagents.

in the signaling network, and limited by existing reagents.

How can we discover novel pathway/network components

while maintaining high coverage of the network?

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-

Sample 1 Lysis

^pS ^pY

Sample 1

Sample 2 Sample 2

Protein Proteolysis

^pY

Sample 2

pS

Sample 3 Desalt

pY

Sample 3 Sample 4

pS

Sample 4

Intensit yy, counts

Biological Samples: EGFR pY1148

GSHQISLDNPDpYQQDFFPK pS pY

Sample 4

cells, tumors, etc…

Stable isotope Stable isotope (iTRAQ) labeling

1000

y

₂

500 Mix

y

₁

114 115 116 117

y

₃ _m/z

b

₃₃

b

₄

b b

₅

y

₄

pS pS

y

₅

b

₈

b

₉

pS pT

0 200 400 600 800 1000 1200 pS

m//z

pY pY pY pY LC-MS/MS

IMAC IMAC LC MS/MS

analysis

phosphopeptide

enrichment pTyr-Peptide

Immunoprecipitation

Photo of QSTAR® XL Hybrid LC/MS/MS System removed due to copyright restrictions.

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Why Study Signaling Networks?

Define better therapeutic targets, or combinations

f h i f h h

of therapeutic targets for cancer or other human diseases

The Challenge: How do we get from genetic mutation to therapeutic targets?

genetic mutation to therapeutic targets?

Mutations in human glioblastoma tumor tissue, TCGA, Nature, 2008

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U87 Glioblastoma cell line

EGFRvIII Signaling Network Analysis

U87 Glioblastoma cell line

Kinase-dead Medium High Super High

EGFR:

EGFRvIII:

100,000 2,000,000

100,000 1,500,000

100,000 2,000,000

100,000 3,000,000 Ki

Kinase dead

Constitutive signaling 24 h

24 hours serum sttarvati tion

w/ Frank Furnari, Web Cavenee

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EGFRvIII signaling preferentially activates PI3K/Akt

V V

Y974 Y845

I I SRC

M H ^Y1086 ^I _I ^I _I ^Y1068 ^Y417

Y1148

Y1148 Y1173 Y1173

SH Fold Change:

IP3

Ca

⁺⁺

STAT3 _Y704 _Y1254 Ca

⁺⁺

x < 1.00

PLC-γ 1.00 < x < 1.50

Ca

⁺⁺

Ca

⁺⁺

1.50 < x < 2.00 2.00 < x < 3.00

Y318 SHC PKCδ 3.00 < x

GRB2 SOS RAS

RAF

RAF Y187

Y605

ERK2 T185 /Y187

Y689 GAB1 p85

Y646 p110 MEK

Y524 Y204

ERK1 ERK1

T202/Y204

PKD AKT

Source: Huang, Paul H., et al. "Quantitative Analysis of EGFRvIII Cellular Signaling Networks Reveals a Combinatorial Therapeutic

Paul Huang

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Self-similar phosphorylation profiles revealed by self organizing map

self-organizing map

2.0

2

0 . 5 1 1 . 5

0.5 1.0

1.5

2.0

2

0.5 n ge

0 . 5 1 1 . 5

0.5 1.0

1.5 Fold Cha n

2

1 5 2.0

0 . 5 1 1 . 5

0.5 1.0

1.5

SOM clustering (x value ) - 0 SOM clustering ( x value ) - 1 SOM clustering (x value ) - 2

Highly g y

DK M H SH DK M H SH DK M H SH

responsive

Paul Huang

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-

The highly responsive cluster contains tyrosine phosphorylation of the c-Met activation site

phosphorylation of the c Met activation site

Paul Huang

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Combinatorial (c-Met and EGFR) inhibition decreases cell viability

cell viability

SU11274

Figure removed due to copyright restrictions. See Figure 1 (top) from Sattler, Martin, et al. "A Novel Small Molecule Met Inhibitor Induces Apoptosis in Cells

Transformed by the Oncogenic TPR-MET Tyrosine Kinase." Cancer Research 63 (2003).

Source: Huang, Paul H., et al. "Quantitative Analysis of EGFRvIII Cellular Signaling Networks Reveals a Combinatorial Therapeutic Strategy for Glioblastoma." Proceedings of the National Academy of Sciences 104, no. 31 (2007). © 2007 National Academy of Sciences, USA.

Paul Huang

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A second, more potent c-Met inhibitor displays similar behavior

behavior

Figure removed due to copyright restrictions. See Figure 1 from Christensen, James G., et al. "A Selective Small Molecule Inhibitor of c-Met Kinase Inhibits c-Met-Dependent Phenotypes in Vitro and Exhibits Cytoreductive Antitumor Activity in Vivo." Cancer Research 63 (2003).

PHA665752

Huang et al., Proc Natl Acad Sci U S A. (2007) 104:12867.

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Independent validation of combinatorial targeting of EGFR and c-Met in GBM

EGFR and c Met in GBM

c-Met c Met EGFR

EGFR

PDGFR PDGFR

Figures from Science removed due to copyright restrictions.

See Figures 2d and 3b from Stommel, Jayne M., et al. "Coactivation

of Receptor Tyrosine Kinases Affects the Response of Tumor Cells

to Targeted Therapies." Science 318 (2007).

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Is there a technique that can determine which of these signals are occurring in the same cell?

are occurring in the same cell?

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Phospho-FACS: Single cell signaling analysis

Courtesy of Elsevier, Inc., http://www.sciencedirect.com. Used with permission.

Krutzik et al., Clinical Immunology , 2004.

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Personalized medicine by Phospho-FACS

Courtesy of Elsevier, Inc., http://www.sciencedirect.com. Used with permission. For complete article, see Irish, Jonathan M., Randi Hovland, Peter O Krutzik, et al. "Single Cell Profiling of Potentiated Phospho-Protein Networks in Cancer Cells" Cell 118, no. 2 (2004).

Irish et al., Cell , 2004.

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All of these techniques measure phosphorylation, but this does not directly measure activity…

does not directly measure activity…

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Courtesy of American Society for Biochemistry and Molecular Biology. Used with permission.

Janes, K. A. (2003) Mol. Cell. Proteomics 2: 463-473

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Why Study Signaling Networks?

Define better therapeutic targets or combinations Define better therapeutic targets, or combinations

of therapeutic targets for cancer or other human diseases

diseases

Disease Stratification and Personalized Medicine:

Analyzing signaling networks can identify activated pathways and thereby highlight therapeutic options Therapeutic Targeting and Efficacy – is the kinase

inhibitor actually affecting the targeted kinase?

How are cells in a tumor responding to therapy?

Understanding mechanisms of resistance

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To clear up my mistake last Thursday:

Modafinil = Monoxidil

Provigil

Provigil = Rogaine Rogaine

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Spring 2010

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