Berg ellen 7th braz medchem 12nov2014

Human Cell Systems for Drug Discoveryand Chemical Safety

Ellen L. Berg, Scientific Director

The 7th Brazilian Symposium on Medicinal Chemistry Campos do Jordão-SP, Brazil, November 9-12, 2014

Agenda

• Challenges in pharmaceutical research

• Primary human cell systems – BioMAP

platform

• Case studies

- Understanding ADRs - thrombosis-related side

effects

- Drug combinations

2

• Problem:

- Pharmaceutical productivity is at an all time low

- We are swimming in oceans of data

• A need for new approaches

- Better physiological relevance

- More predictive of clinical effects

Challenges in Drug Discovery

We need to do something different: A Turning Point

3

Complexity of Biology

Scale (meters)

molecules pathways cells tissues humans

10-9 M 10-8 M 10-7 M 10-6 M 10-5 M 10-4 M 10-3 M 10-2 M 10-1 M 1 M

Human exposureMolecular targets

4

• Human biology is complex

- Modular, redundant, highly networked, & full of feedback loops

Complexity of Biology

Scale (meters)

molecules pathways cells tissues humans

10-9 M 10-8 M 10-7 M 10-6 M 10-5 M 10-4 M 10-3 M 10-2 M 10-1 M 1 M

Human exposureMolecular targets

5

• Human biology is complex

- Modular, redundant, highly networked, & full of feedback loops

• Prediction (and understanding!) is difficult

- Emergent properties

Primary human cell systems

Solution: Primary Human Cell Systems

• BioMAP® Profiling:

- In Vitro testing in primary human cell based tissue and disease models

• Data driven chemical biology approach

- Data-driven research methodology

- Leverages the analysis of a large chemical biology dataset

• Applications in drug discovery

- Compound characterization across a broad range of biology

- Drug mechanisms of action – anchored on clinical outcomes

- Guidance for translational studies, indications & biomarkers

Confidential6

Data Driven Research

OLD or

7


NEW

010101010101010101001010101010101

100101001110010100110100101001110

001000100011101001010001000100011

111010010101010101000110100101010

101010101010001110101010000110100

010000110100010001001111010010101

001000100011101001011101010101010

101010101010001110100101010101010

111010010101010101000110100101010

101010101010001110101010000110100

010000110100010001001111010010101

001000100011101001011101010101010

001000100011101001010001000100011

010101010101010101001010101010101

100101001110010100110100101001110

001000100011101001010001000100011

111010010101010101000110100101010

101010101010001110101010000110100

010000110100010001001111010010101

001000100011101001011101010101010

101010101010001110100101010101010

111010010101010101000110100101010

101010101010001110101010000110100

010000110100010001001111010010101

001000100011101001011101010101010

001000100011101001010001000100011

010101010101010101001010101010101

100101001110010100110100101001110

001000100011101001010001000100011

111010010101010101000110100101010

101010101010001110101010000110100

010000110100010001001111010010101

001000100011101001011101010101010

101010101010001110100101010101010

111010010101010101000110100101010

101010101010001110101010000110100

010000110100010001001111010010101

001000100011101001011101010101010

001000100011101001010001000100011

Hypothesis 1

Hypothesis 2

Hypothesis 3

Hypothesis 4 . . .

OLD or


IssuesMany hypotheses are generated

Each hypothesis requires validation

Validation requires both computational

and “domain” expertise

SolutionIncorporate “domain” expertise upfront

BioMAP® Technology Platform

BioMAP®

Assay Systems

Reference

Profile Database

Predictive

Informatics Tools

Human primary cells

Disease-models

30+ systems

Biomarker responses to drugs

are stored in the database

>3000 drugs

Custom informatics tools are

used to predict clinical outcomes

High Throughput Human Biology

10

BioMAP® Systems – Key Features

11

Primary human cell types

Physiologically relevant “context”

Complex activation settings

Co-cultures

Translational biomarker endpoints

Feature Mice ManLifespan 2 Years 70 Years

Size 60 g 60 kg

EnvironmentAnimal facility, cage-mates

Outside world, people, animals, etc.

Why Human?

Key differences:

DNA repair mechanisms

Control of blood flow, hemostasis

Immune system status

12

Closer to the disease process

Downstream of multiple pathways and integrate information

“Decision-making”

Used by clinicians to guide therapy - Provide clinical “line of site”

Predictive

Why Translational Biomarkers?

mRNA,epigenome

Phospho-sites, intracellular proteins,

metabolome

Cell surface,secreted molecules

13

Panel of BioMAP® Systems3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT

Endothelial Cells

Endothelial Cells

PBMC + Endothelial

Cells

PBMC + Endothelial

Cells

Bronchial epithelial cells

Coronary artery SMC

FibroblastsKeratinocytes + Fibroblasts

Th1 Th2 TLR4 TCR Th1 Th1 Th1 + GF Th1 + TGF

Acute Inflammation E-selectin, IL-8

E-selectin, IL-1a, IL-8, TNF-

a, PGE2 IL-8 IL-1a

IL-8, IL-6, SAA

IL-8 IL-1α

Chronic Inflammation

VCAM-1, ICAM-1, MCP-1, MIG

VCAM-1, Eotaxin-3,

MCP-1

VCAM-1, MCP-1

MCP-1, E-selectin, MIG

IP-10, MIG, HLA-DR

MCP-1, VCAM-1,MIG, HLA-

DR

VCAM-1, IP-10, MIG

MCP-1, ICAM-1, IP-10

Immune Response HLA-DR CD40, M-CSFCD38, CD40, CD69, T cell

Prolif., Cytotox.HLA-DR M-CSF M-CSF

Tissue Remodeling uPAR, MMP-1, PAI-1, TGFb1, SRB, tPA, uPA

uPAR,

Collagen III, EGFR, MMP-1, PAI-1, Fibroblast

Prolif., SRB, TIMP-1

MMP-9, SRB, TIMP-2, uPA,

TGFβ1

Vascular Biology

TM, TF, uPAR, EC

Proliferation, SRB, Vis

VEGFRII, uPAR, P-

selectin, SRB

Tissue Factor, SRB

SRB

TM, TF, LDLR, SMC

Proliferation, SRB

Vascular Biology,

Cardiovascular

Disease, Chronic

Inflammation

Asthma, Allergy,

Oncology,

Vascular Biology

Cardiovascular

Disease, Chronic

Inflammation,

Infectious Disease

Autoimmune

Disease, Chronic

Inflammation,

Immune Biology

COPD,

Respiratory,

Epithelial Biology

Vascular Biology,

Cardiovascular

Inflammation,

Restenosis

Tissue Remodeling,

Fibrosis, Wound

Healing

Skin

Biology,Psoriasis,

Dermatitis

En

dp

oin

t Ty

pe

s

Disease / Tissue Relevance

BioMAP System

Primary Human Cell Types

Stimuli

! ! ! ! !

Endothelial Cells

Bronchial Epithelial Cells

Keratinocytes

Smooth Muscle Cells

Dermal Fibroblasts

Peripheral Blood Mononuclear Cells

Profile compounds

across a panel of assays

14

Panel of BioMAP® Systems3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT

Endothelial Cells

Endothelial Cells

PBMC + Endothelial

Cells

PBMC + Endothelial

Cells


Coronary artery SMC





a, PGE2 IL-8 IL-1a

IL-8, IL-6, SAA

IL-8 IL-1α



VCAM-1, Eotaxin-3,

MCP-1

VCAM-1, MCP-1


IP-10, MIG, HLA-DR


DR

VCAM-1, IP-10, MIG





uPAR,




TGFβ1

Vascular Biology

TM, TF, uPAR, EC


VEGFRII, uPAR, P-

selectin, SRB

Tissue Factor, SRB

SRB

TM, TF, LDLR, SMC

Proliferation, SRB

Vascular Biology,

Cardiovascular

Disease, Chronic

Inflammation

Asthma, Allergy,

Oncology,

Vascular Biology

Cardiovascular

Disease, Chronic

Inflammation,

Infectious Disease

Autoimmune

Disease, Chronic

Inflammation,

Immune Biology

COPD,

Respiratory,

Epithelial Biology

Vascular Biology,

Cardiovascular

Inflammation,

Restenosis

Tissue Remodeling,

Fibrosis, Wound

Healing

Skin

Biology,Psoriasis,

Dermatitis

En

dp

oin

t Ty

pes


BioMAP System


Stimuli

! ! ! ! !

15

• Challenges

- Cells and assays are expensive

- Primary cells (all cell-based assays!) are variable

- Very large number of assay components / choices

• Cell types, media, additives, time points, endpoints

Experimental Design

16

• Solutions

- Automation

• Microwell plate-based

- Standardized methods

• Quality management system (SOPs)

• Strict assay acceptance criteria

- Incorporate methods to reduce variability

• Cells from pooled donors, prequalified

• Normalize data within plate (Log10 ratio of compound/vehicle)

• 6+ vehicle replicates, two positive controls per plate

Experimental Design

17

• Compromises:

- Single well per endpoint, but:

• Multiple concentrations (4+) per compound

• Multiple assay systems per compound

• Multiple endpoints per assay system

- Single timepoint

• Suboptimal for some endpoints, but optimal for most endpoints (24 hr – 6 days)

- Pauciparameter (7-22 endpoints per assay system), but:

• Highly informative disease biomarker endpoints

Experimental Design

18

BioMAP Profile of Positive Control

• Colchicine is an inhibitor of microtubules - It is active in every system and used as a positive control on every plate

• Colchicine profile has a distinctive pattern of activities or “shape”

BioMAP Systems

Readout Parameters (Biomarkers)

Cytotoxicity Readouts

Colchicine 1.1 μM

Lo

g e

xp

res

sio

n r

ati

o

(Dru

g/D

MS

O c

on

tro

l)

Vehicle Control

(no drug)

95%

significance

envelope

19

Reproducibility of Profiles

• 16 Experiments over many months

• Pairwise correlation of profiles (Pearson’s) were > 0.8

BioMAP Systems


Houck, K.A., J. Biomolecular Screening, 2009, 14:1054-66.20

Lo

g e

xp

res

sio

n r

ati

o

(Dru

g/D

MS

O c

on

tro

l)

Vehicle Control

(no drug)

95%

significance

envelope

• Assess cytotoxicity in primary human cells

- Cytotoxicity mechanisms are cell type and activation dependent

- Note: cytotoxicity is a confounder• Flag compounds (concentrations) that are overtly cytotoxic

• Analyze overall activity profiles

- Profile characteristics

- Unsupervised and supervised approaches to compare profiles

• Focus on individual endpoints

- Correlate to external data

- Build an understanding of clinical mechanisms

What Can We Do With BioMAP Profile Data?

21

Types of BioMAP Profiles

InactiveActive – Sharp dose-response

Active – Dose resistantActive – Selectively

22

Rapamycin (mTOR) Genistein (multi-target)

Dose ResistanceA Profile “Characteristic”

• “Dose resistant” compounds have similar activity profiles over a wide range of concentrations- No sharp activity jumps; Rapamycin > Genistein

• Characteristic of approved drugs & target-selective compounds- Rapamycin is highly selective for mTOR; Genistein has multiple targets

- The dose resistance index of Rapamycin is > 60,000x

23

BioMAP Profiling: Example ProfileReference p38 MAPK Inhibitor

Lo

g e

xp

ressio

n r

ati

o

(Dru

g/D

MS

O c

on

tro

l)

Control (no drug)

99%

significance

envelope

BioMAP Systems


Dose

Response

Cytotoxicity Readouts

24

This profile shows dose-resistance – similar over a range of concentrations


Lo

g e

xp

ressio

n r

ati

o

(Dru

g/D

MS

O c

on

tro

l)

25

Activities relevant to the role of p38 in monocyte / Th1-type inflammation

p38 kinase is important for Th1-dependent inflammatory responses

Takanami-Ohnishi Y, et al., Essential role of p38 mitogen-activated protein kinase in contact hypersensitivity. J Biol Chem. 2002, 277:37896-903.

IL-8

HLA-DR

Monocyte

activation

IL-6IL-1aCD38HLA-DR

TNF-a


Lo

g e

xp

ressio

n r

ati

o

(Dru

g/D

MS

O c

on

tro

l)

26

Activities relevant to anti-thrombotic effects of p38 inhibitors

Tissue factor is the primary cellular initiator of coagulation

p38α deficiency impairs thrombus formation

Sakurai K, et al. Role of p38 mitogen-activated protein kinase in thrombus formation. J Recept Signal Transduct Res. 2004;24(4):283-96.

Tissue

Factor


Lo

g e

xp

ressio

n r

ati

o

(Dru

g/D

MS

O c

on

tro

l)

27

Activities relevant to side effects – clinical finding: skin rash

Upregulation of VCAM and ITAC are characteristic of skin hyperreactivity

Melikoglu M, et al., Characterization of the divergent wound-healing responses occurring in the pathergy reaction and normal healthy volunteers. J Immunol. 2006, 177:6415-21.

ITAC

VCAM

MMP1

VCAM

28

BioMAP® Data Analysis

Predictive

Informatics Tools

Custom informatics tools are

used to predict clinical outcomes

• Unsupervised Analyses

- Similarity Search of our reference database

- Clustering

• Supervised Analyses

- Computational models (classifiers) for mechanism of action

29

BioMAP® Reference Database

BioMAP®

Reference Database

Biomarker responses to drugs

are stored in the database

>3000 drugs

• More than 3000 agents

- Drugs – Clinical stage, approved, and failed

- Experimental Chemicals - Research tool

compounds, environmental chemicals,

nanomaterials

- Biologics – Antibodies, cytokines, factors,

peptides, soluble receptors

• Availability of reference data

- EPA ToxCast and selected reference data

are published and have been made

available (Houck, 2009; Berg, 2010; Berg,

2013; Kleinstreuer, 2014)

Similarity Analysis of Profiles

Highly correlated Similar

Pearson’s correlation of r > 0.7

Low correlation Not similar

Pearson’s correlation of r < 0.7

30

Microtubule

Stabilizers

Mitochondrial

ET chain

Retinoids

Hsp90

CDK

NFkB

MEK

DNA

synthesis

JNK

Protein

synthesis

Microtubule

Destabilizers

Estrogen R

PI-3K

Ca++

Mobilization

Clustering of Compound Profile DataCompounds Cluster According to Mechanisms of Action

mTOR

PKC Activation

p38 MAPK

HMG-CoA

reductase

Calcineurin

Transcription

31

Each circle represents a compound tested at a single dose

Lines are drawn between compounds whose profiles are similar (r > 0.7)

Figure adopted from Berg, JPTox Meth. 2010

Microtubule

Stabilizers

Mitochondrial

ET chain

Retinoids

Hsp90

CDK

NFkB

MEK

DNA

synthesis

JNK

Protein

synthesis

Microtubule

Destabilizers

Estrogen R

PI-3K

Ca++

Mobilization

BioMAP Data Can Cluster CompoundsAccording to Mechanisms of Action

mTOR

PKC Activation

p38 MAPK

HMG-CoA

reductase

Calcineurin

Transcription

p38 MAPK

Calcineurin

mTOR

Mitochondrial ATPase

32

Each circle represents a compound tested at a single dose

Lines are drawn between compounds whose profiles are similar (r > 0.7)

Figure adopted from Berg, JPTox Meth. 2010

Microtubule

Stabilizers

Mitochondrial

ET chain

Retinoids

Hsp90

CDK

NFkB

MEK

DNA

synthesis

JNK

Protein

synthesis

Microtubule

Destabilizers

Estrogen R

PI-3K

Ca++

Mobilization

BioMAP Data Can Cluster CompoundsAccording to Mechanisms of Action

mTOR

PKC Activation

p38 MAPK

HMG-CoA

reductase

Calcineurin

Transcription

Mechanism of Action

(On-Target)

Pathway

Relationships

33

Consensus Profiles for Mechanism Classes

p38 MAPK inhibitor 1



Consensus profile reflects target-specific biology

Can define mechanism class

34

1 1 1 1 1 1 1 1 1

Mechanism Class Consensus Profiles

AhRAgonist

CalcineurinInhibitor

EGFRInhibitor

EPAgonist

ERAgonist

GRAgonist(Full)

H1Antagonist

HDACInhibitor

HMG-CoAReductaseInhibitor

Hsp90Inhibitor

IKK2Inhibitor

IL-17AAgonist

JAKInhibitor

MEKInhibitor

MicrotubuleDisruptor

MicrotubuleStabilizer

MitochondrialInhibitor

mTORInhibitor

p38MAPKInhibitor

PDEIVInhibitor

PI3KInhibitor

PKC(c+n)Inhibitor

ProteasomeInhibitor

RAR/RXRAgonist

SRCa++ATPaseInhibitor

SrcFamilyInhibitor

TNF-alphaAntagonist

VitaminDReceptorAgonist

Patterns reflect “mechanism class” or target biology

Reproducible patterns permit building of classifiers for automated mechanism assignment

Me

chan

ism

Cla

sse

s

BioMAP Assay / Endpoints

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM

Cyclopamine 13.333 u...

Cyclopamine 4.444 uM


3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

54

/IC

AM−

1

CD

62

E/E−

Se

lec

tin

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

Pro

life

rati

on

SR

B

Vis

ua

l

CC

L2

/MC

P−

1

CC

L2

6/E

ota

xin−

3

CD

10

6/V

CA

M−

1

CD

62

P/P−

se

lecti

n

CD

87

/uP

AR

SR

B

VE

GF

R2

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

2/T

iss

ue

Fa

cto

r

CD

40

CD

62

E/E−

Se

lec

tin

CX

CL

8/I

L−

8

IL−

1a

lph

a

M−

CS

F

sP

GE

2

SR

B

sT

NF−

alp

ha

CC

L2

/MC

P−

1

CD

38

CD

40

CD

62

E/E−

Se

lec

tin

CD

69

CX

CL

8/I

L−

8

CX

CL

9/M

IG

PB

MC

Cy

toto

xic

ity

Pro

life

rati

on

SR

B

CD

87

/uP

AR

CX

CL

10

/IP−

10

CX

CL

9/M

IG

HL

A−

DR

IL−

1a

lph

a

MM

P−

1

PA

I−I

SR

B

TG

F−

be

taI

tPA

uP

A

CC

L2

/MC

P−

1

CD

10

6/V

CA

M−

1

CD

14

1/T

hro

mb

om

od

uli

n

CD

14

2/T

iss

ue

Fa

cto

r

CD

87

/uP

AR

CX

CL

8/I

L−

8

CX

CL

9/M

IG

HL

A−

DR

IL−

6

LD

LR

M−

CS

F

Pro

life

rati

on

Se

rum

Am

ylo

id A

SR

B

CD

10

6/V

CA

M−

1

Co

llag

en

III

CX

CL

10

/IP−

10

CX

CL

8/I

L−

8

CX

CL

9/M

IG

EG

FR

M−

CS

F

MM

P−

1

PA

I−I

Pro

life

rati

on

_7

2h

r

SR

B

TIM

P−

1

CC

L2

/MC

P−

1

CD

54

/IC

AM−

1

CX

CL

10

/IP−

10

IL−

1a

lph

a

MM

P−

9

SR

B

TG

F−

be

taI

TIM

P−

2

uP

A

−1.5

−1.4

−1.3

−1.2

−1.1

−1.0

−0.9

−0.8

−0.7

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Lo

g R

atio

Profiles

Cyclopamine 40 uM





35

TF VCAM

Building Support Vector Machine Classifiers

• 88 Compounds

• 28 Target/Pathway

mechanisms

• 1-8 concentrations

• 327 Profiles

• 84 endpoints (8 BioMAP

Systems)

• Support Vector Machine

• 2-class models

• Mechanism class versus “Null”

set

• Result = Decision Value (DV)

• PPV – positive predictive value

(fraction of profiles that are correctly

classified)• PPV = TP / (TP + FP))

• Sensitivity (fraction of profiles that

are assigned to the class)• Sensitivity = TP / (TP + FN))

MitochondrialInhibitor

Microtubule Stabilizer Hsp90 Inhibitor

Classifier Performance: Examples

PDE IVInhibitor

Generate Data Set

Build Classifiers

Test Performance of Classifiers

Berg, Yang & Polokoff, 2013, J. Biomol Screen. 18:1260.36

• AhR agonist (Aryl Hydrocarbon)

• Calcineurin

• EGFR (Epidermal Growth Factor R)

• SERCA (SR Ca++ ATPase)

• EP agonist

• Estrogen R agonist

• Glucocorticoid R agonist

• H1R Antagonist (Histamine)

• HDAC

• HMG-CoA-Reductase

• Hsp90 Inhibitor

• IKK2

• IL-17 R agonist

• JAK

Confidential37

List of Classifiers (SVM Mechanism Models)

• MEK

• Microtubule Disruptor

• Microtubule Stabilizer

• Mitochondrial Inhibitor

• mTOR

• p38 MAPK

• PDE IV (Phosphodiesterase

• PI3K

• PKC (c+n)

• Proteasome

• RAR-RXR agonist

• Src family

• TNF (Tumor Necrosis Factor)

• VDR agonist (Vitamin D R)

Berg, Yang & Polokoff, 2013, J. Biomol Screen. 18:1260.

• Compound characterization

- Broad biological fingerprint

- Cell types, pathways, possible clinical indications

• Mechanism of action

- Triage hits from phenotypic drug discovery programs

- Unexpected off-targets (toxicity)

• Support therapeutic hypotheses

- Compare to competitor molecules, clinical standards of care

- Identify translational biomarkers

Applications

38

Case Study: Elucidating Mechanisms Underlying Adverse Effects

EPA ToxCastTM Program – BioSeek

Goal is identification of in vitro assays that can help

forecast in vivo toxicity of environmental and other

agents (including pharmaceuticals)

40

Task Order Compound Number Compound Type

TO1 320 Environmental compounds

TO2 500 Environmental compounds

TO3 200 Environmental and Failed Pharma Compounds

TO4 39 Nanomaterials


TO6 100 Failed Pharma Compounds, etc.


Total 1229

40

Houck, K.A., J. Biomolecular Screening, 2009, 14:1054-66; Kleinstreuer, 2014, Nature Biotechnology, 32:583-91.

Chemical Groups & Classes in ToxCast

Most active

Least active

41

Overall: 73% Active

(33 – 83%)

Kleinstreuer, 2014, Nature Biotechnology, 32:583-91.

Results of Supervised AnalysisPerformance of SVM Mechanism Classifiers

Mechanism Class1 Number of Compounds

Correctly Assigned

% Comment

p38 MAPK Inhibitor 2 2 100%

Estrogen R Agonist 10 6 60%Not classified: meso-Hexestrol, 4-nonylphenol and diethystilbestrol

HMG-CoA Reductase Inhibitor 3 3 100%

Histamine R1 Antagonist 1 1 100%

Microtubule Inhibitor 2 1 50% Herbicides

GR Agonist 3 3 100%

Mitochondrial Inhibitor 2 2 100% Fungicides

PDE IV Inhibitor 8 6 75%

RAR/RXR Agonist 2 2 100%

Total 33 26 79%

• 1Mechanisms for which classifiers were available and mechanisms were known

- Dataset: Kleinstreuer, Nature Biotechnology, 2014, 32:583

- Classifiers: Berg, Yang and Polokoff, JBS, 2013, 18:1260

42

Unsupervised Analysis (Self Organizing Maps)AhR Phenotypic Signature

• Phenotypic signature of compounds in SOM cluster #57

- Box and whisker plot for cluster 57 representing a signature for AhR activation

• Confirmation of AhR activity

- 85% of members of clusters 57, 67 (adjacent in the 10X10 SOM) were active in an AhR reporter gene assay (examples shown here).

Tissue Factor

Kleinstreuer, 2014, Nature Biotechnology, 32:583-91.43

Unsupervised Analysis (Self Organizing Maps)Estrogen R Actives: Phenotypic Signatures

• Two clusters of chemicals defined by their BioMAP signatures- Blue = Estradiol, Estrogen Receptor Agonists

- Red = Estrogen Receptor Antagonists, “Selective Estrogen R Modulators”

• Increased levels of Tissue Factor by SERMs and ER antagonists

Kleinstreuer, 2014, Nature Biotechnology, 32:583-91.

Estrogen

Receptor

Antagonists

Estrogen

Receptor

Agonists

Tissue Factor

44

Tissue FactorPrimary Cellular Initiator of Blood Coagulation

RW Colman 2006 J. Exp. Med

Blood

Coagulation

45

• Pathologic setting – aberrant coagulation thrombosis

- The formation of a blood clot (coagulation) within a vein

- Deep vein thrombosis (DVT), stroke

- Pulmonary embolism thrombi break off and get lodged in the lung

Thrombosis

SMC

Endothelial cells

Vessel Lumenplatelets in fibrin clot

46

Thrombosis is Required for Normal Wound Healing

47

• Associated with:

- Exposure to Smoking & Pollution• Polycyclic aromatic hydrocarbons (“Aryl Hydrocarbons”)

- Contraceptives, hormonal replacement therapy

- Various other drugs• mTOR inhibitors (everolimus)

• 2nd generation anti-psychotics

Thrombosis-Related Side Effects

48

• Aryl Hydrocarbon receptor agonists- PAHs, Benz(a)anthracene

- Smoking (Cigarette smoke extract)

• mTOR inhibitors- Everolimus (Baas, 2013, Thromb Res 132:307)

• Anti-Estrogens / SERMS, oral contraceptives- Tamoxifen, Clomiphene, Cyproterone

• Second generation anti-psychotics- Clozapine

• Others- Crizotinib

Mechanisms / Drugs Associated with Thrombosis-Related Side Effects

All show increased Tissue Factor levels in 3C and LPS Systems

49

• Search our reference database for all compounds / test agents that increase TF in the 3C system

- What are the mechanisms represented?

- Do they share any common biology?

• Issues

- Large chemical-biology datasets will have errors• Inactive concentrations, toxic concentrations, variability

- How do we increase our confidence?• Require compound effects at more than one concentration

• Effect size >20% (4 SD)

• Multiple compounds with same target mechanism

Is There A Connection?

50

Reference Compounds that Increase TF

Compound Name Mechanism Compound Name Mechanism

2-Mercaptobenzothiazole AhR agonist 3,5,3-Triiodothyronine Thyroid H R agonist

3-Hydroxyfluorene AhR agonist Concanamycin A Vacuolar ATPase Inhibitor

Benzo(b)fluoranthene AhR agonist MK-2206 AKT Inhibitor

C.I Solvent yellow 14 AhR agonist Crizotinib ALK, c-met Inhibitor

FICZ AhR agonist N-Ethylmaleimide Alkylating agent

Abiraterone CYP17A Inhibitor Terconazole Anti-fungal

Ketoconazole CYP17A Inhibitor GDC-0879 B-Raf Inhibitor

Clomiphene citrate Estrogen R Antagonist KN93 CAMKII Inhibitor

Histamine H1R agonist 8-Hydroxyquinoline Chelating agent

Histamine Phosphate H1R agonist Linoleic Acid Ethyl Ester Fatty Acid

Cobalt(II) Chloride Hexahydrate HIF-1α Inducer Tris(1,3-dichloro-2-propyl) phosphate Flame retardant

Tin(II) Chloride HIF-1α Inducer Fenaminosulf Fungicide

Chloroquine Phosphate Lysosome Inhibitor Mancozeb Fungicide

Primaquine Diphosphate Lysosome Inhibitor Primidone GABA R agonist

Temsirolimus mTOR Inhibitor Mometasone furoate GR agonist

Torin-1 mTOR Inhibitor Desloratadine H1R antagonist

Torin-2 mTOR Inhibitor A 205804 ICAM, E-selectin inhibitor

Bryolog PKC activator Dodecylbenzene Industrial chemical

Bryostatin 1 PKC activator UO126 MEK Inhibitor

Bryostatin 2 PKC activator Imatinib PDGFR, c-Kit, Bcr-Abl Inhibitor

Phorbol 12-myristate 13-acetate PKC activator ZK-108 PI-3K Inhibitor (βγ-selective)

Phorbol 12,13-didecanoate PKC activator GW9662 PPARγ agonist

Picolog PKC activator PP3 SRC Kinase Inhibitor

Z-FA-FMK Cysteine protease Inhibitor TX006146 Unknown

Mifamurtide NOD2 agonist TX006237 Unknown

Ethanol Organic Solvent TX011661 Unknown

Oncostatin M OSM R agonist U-73343 Unknown

PAz-PC Oxidized phospholipid

55/3187 = 1.7%51

Mechanisms that Increase TF

Test Agents Mechanism Confidence in

Mechanism 2-Mercaptobenzothiazole AhR agonist High

3-Hydroxyfluorene AhR agonist High

Benzo(b)fluoranthene AhR agonist High

C.I Solvent yellow 14 AhR agonist High

FICZ AhR agonist High

Abiraterone CYP17A Inhibitor High

Ketoconazole CYP17A Inhibitor High

Clomiphene citrate Estrogen R Antagonist High

Histamine H1R agonist High

Histamine Phosphate H1R agonist High

Cobalt(II) Chloride Hexahydrate HIF-1α Inducer High

Tin(II) Chloride HIF-1α Inducer High

Chloroquine Phosphate Lysosome Inhibitor High

Primaquine Diphosphate Lysosome Inhibitor High

Temsirolimus mTOR Inhibitor High

Torin-1 mTOR Inhibitor High

Torin-2 mTOR Inhibitor High

Bryolog PKC activator High

Bryostatin PKC activator High

Bryostatin 1 PKC activator High

Phorbol 12-myristate 13-acetate PKC activator High

Phorbol 12,13-didecanoate PKC activator High

Picolog PKC activator High

3,5,3-Triiodothyronine Thyroid H R agonist Good

Concanamycin A Vacuolar ATPase Inhibitor Good

Mifamurtide NOD2 agonist Good

Oncostatin M OSM R agonist Good

Ethanol Organic Solvent Good

PAz-PC Oxidized phospholipid Good

Z-FA-FMK Cysteine protease Inhibitor Good

8-Hydroxyquinoline Chelating agent Unknown

A 205804 ICAM, E-selectin inhibitor Unknown

AZD-4547 FGFR Inhibitor Unknown

Crizotinib ALK, c-met Inhibitor Unknown

Desloratadine H1R antagonist Unknown

Dodecylbenzene Industrial chemical Unknown

Fenaminosulf Fungicide Unknown

GDC-0879 B-Raf Inhibitor Unknown

GW9662 PPARγ agonist Unknown

Imatinib PDGFR, c-Kit, Bcr-Abl Inhibitor Unknown

KN93 CaMKII Inhibitor Unknown

Linoleic Acid Ethyl Ester Fatty Acid Unknown

Mancozeb Fungicide Unknown

MK-2206 AKT Inhibitor Unknown

Mometasone furoate GR agonist Unknown

N-Ethylmaleimide Alkylating agent Unknown

PP3 SRC Kinase Inhibitor Unknown

Primidone GABA R agonist Unknown

Sulindac Sulfide NSAID Unknown

Terconazole Anti-fungal Unknown

Tris(1,3-dichloro-2-propyl) phosphate Flame retardant Unknown

TX006146 Unknown Unknown



U-73343 Unknown Unknown

UO126 MEK Inhibitor Unknown

ZK-108 PI-3K Inhibitor (βγ-selective) Unknown


AhR Agonist

CYP17A Inhibitor

Estrogen R Antagonist

H1R Agonist

HIF-1α Inducer

Lysosomal Inhibitor

mTOR Inhibitor

PKC Activator

Thyroid H R Agonist

Vacuolar ATPase Inhibitor

NOD2 Agonist

OSM R Agonist

52



AhR Agonist

CYP17A Inhibitor

Estrogen R Antagonist

H1R Agonist

HIF-1α Inducer

Lysosomal Inhibitor

mTOR Inhibitor

PKC Activator

Thyroid H R Agonist

Vacuolar ATPase Inhibitor

NOD2 Agonist

OSM R Agonist

Implicate Autophagy

53

Autophagy

• Cellular response to nutrient deprivation

• Also contributes to recycling of dysfunctional organelles, handling of protein aggregates, bacteria and viruses54

mTOR

Concanamycin AVATPase

Chloroquine

Caspase

Z-FA-FMK

Increased Tissue Factor

The Autophagy Connection

Autophagy

Lysosomal Function

55

mTOR

Temsirolimus

PI3Kβ

AKT

ZK-108

MK-2206


Chloroquine

Caspase

Z-FA-FMK

PAz-PC

Nutrient Sensing



Autophagy

56

mTOR

Temsirolimus

Oxygen Sensing

CoCl2

TnCl2

HIF-1α

PI3Kβ

AKT

ZK-108

MK-2206


Chloroquine

Caspase

Z-FA-FMK

PAz-PC

REDD1

Ethanol

Nutrient Sensing



Autophagy

57

mTOR

Temsirolimus

Oxygen Sensing

CoCl2

TnCl2

HIF-1α

PI3Kβ

AKT

ZK-108

MK-2206


Chloroquine

Benzo(b)fluoranthene

ER Clomiphene

Caspase

Z-FA-FMK

NPC1

AhR

PAz-PC

Estrogen

AbirateroneCYP17A1

REDD1

Ethanol

Lipid Sensing

Nutrient Sensing



Autophagy

58

mTOR

Temsirolimus

Oxygen Sensing

NOD2Mifamurtide

CoCl2

TnCl2

HIF-1α

PI3Kβ

AKT

ZK-108

MK-2206

PKC

PMA Concanamycin AVATPase

Chloroquine

Benzo(b)fluoranthene

ER Clomiphene

Caspase

Z-FA-FMK

NPC1

AhR

PAz-PC

Estrogen

AbirateroneCYP17A1

REDD1

Ethanol

Lipid Sensing

Nutrient Sensing

Bacterial Sensing



Autophagy

Berg, Polokoff, O’Mahony, Nguyen & Li, submitted, 201459

• Summary

- Compounds that increase TF are associated with thrombosis related side effects

- Compounds that increase TF also increase autophagic vacuoles (increase formation or decrease breakdown)

- Mechanistic Hypothesis: thrombosis-related side effects are associated with alterations in the process of autophagy that increase TF cell surface levels

• Take home message:

- This case study illustrates how chemical biology datasets, combined with external knowledge, can give rise to higher level mechanistic understanding of toxicity mechanisms

Tissue Factor, Autophagy & Thrombosis

60

Adverse Outcome Pathway Framework

MIEKey

EventAdverse

OutcomeKey

EventKey

Event

Molecular

Initiating EventClinical Effect

• Framework for integrating mode of action hypotheses to outcomes for chemical risk assessment (OECD)- http://www.oecd.org/chemicalsafety/testing/adverse-outcome-pathways-

molecular-screening-and-toxicogenomics.htm

• Focused on the clinical outcome- Anchored at both ends

61

AOP for DVT

MIEKey

EventAdverse

Outcome

Inhibition of

mTOR

Upregulation

of Tissue

Factor

Deep Vein

Thrombosis

Initiation of

Coagulation

Key Event

Key Event

Molecular


Increase in

Autophagic

Vacuolization

62

AOP for DVT

MIEKey

EventAdverse

Outcome

Inhibition of

mTOR

Upregulation

of Tissue

Factor

Deep Vein

Thrombosis

Initiation of

Coagulation

Key Event

Key Event

Molecular


MIE

Activation of

AhR

Increase in

Autophagic

Vacuolization

Key Event

Inhibition of

NPC1

Key Event

HDF3CGF

In vitro

disease model

3C


Endothelial Cells

Endothelial Cells

PBMC + Endothelial

Cells

PBMC + Endothelial

Cells


Coronary artery SMC





a, PGE2 IL-8 IL-1a

IL-8, IL-6, SAA

IL-8 IL-1α



VCAM-1, Eotaxin-3,

MCP-1

VCAM-1, MCP-1


IP-10, MIG, HLA-DR


DR

VCAM-1, IP-10, MIG





uPAR,




TGFβ1

Vascular Biology

TM, TF, uPAR, EC


VEGFRII, uPAR, P-

selectin, SRB

Tissue Factor, SRB

SRB

TM, TF, LDLR, SMC

Proliferation, SRB

Vascular Biology,

Cardiovascular

Disease, Chronic

Inflammation

Asthma, Allergy,

Oncology,

Vascular Biology

Cardiovascular

Disease, Chronic

Inflammation,

Infectious Disease

Autoimmune

Disease, Chronic

Inflammation,

Immune Biology

COPD,

Respiratory,

Epithelial Biology

Vascular Biology,

Cardiovascular

Inflammation,

Restenosis

Tissue Remodeling,

Fibrosis, Wound

Healing

Skin

Biology,Psoriasis,

Dermatitis

En

dp

oin

t Ty

pe

s


BioMAP System


Stimuli

! ! ! ! !

63

Case Study: Drug Combinations

• Challenges for studying drug combinations:

- System must include both targets

- Physiologically relevant setting (ideally all human)

- Suitably robust to capture combination effects

• Case Example

- BioMAP Oncology systems that model tumor-host

microenvironments

- Trametinib (MEK kinase inhibitor) + Dabrafenib (Braf inhibitor)

• Combination approved for treatment of melanoma

Drug Combinations

65

Modeling Tumor-Host Microenvironments

66

BioMAP Oncology Systems

System Primary Human Cell TypesDisease / Tissue

RelevanceBiomarker Readouts

StroHT29

HT-29 colon adenocarcinoma cell

line + Primary Human Fibroblasts

+ PBMC

Oncology: Host Tumor-

Stromal Microenvironment

sVEGF, MMP9, TIMP2, tPA, uPA, uPAR, collagen I,

collagen III, PAI-1, SRB, sIL-2, pCyt, sIL-6, sIL-10,

sIFNγ, sTNFα, sIL-17A, sGranzyme B, Keratin 20,

CEACAM5, IP-10, VCAM-1

VascHT29

HT-29 colon adenocarcinoma cell

line + Primary Human Endothelial

cells + PBMC

Oncology: Host Tumor-

Vascular Microenvironment

CD40, CD69, uPAR, collagen IV, MCP-1, VCAM-1,

pCyt, SRB, sIL-2, sIL-6, sIL-10, sIFNγ, sTNFα, sIL-

17A, sGranzyme B, CEACAM5, Keratin 20, IP-10,

MIG

• Biomarker Endpoints:

• Immunomodulation: IL-2, IL-6, IL-10, IL-4, IFNγ, CD40, CD69, IL-17, Granzyme B

• Inflammation: TNFα, MCP-1, VCAM, CXCL9/MIG,

• Metastasis / Remodeling: MMP9, TIMP2, Collagens I, III, IV, uPA, uPAR, PAI-1

• Angiogenesis / Fibrinolysis: uPA, uPAR, PAI-1, VEGF

• Tumor specific markers: CEACAM5, CK2067

Dabrafenib (B-raf) Trametinib (MEK) Dabrafenib +Trametinib

68

Combination Study Example: B-Raf + MEK Inhibitor


• Combination effects of Dabrafenib (B-raf) and Trametinib (MEK)- Tumor cell marker (CEACAM5) is reduced only in the combination (green

arrow)

- Consistent with the combination being more efficacious against tumors in vivo

69



• Combination effects of Dabrafenib (B-raf) and Trametinib (MEK)- Tumor cell marker (CEACAM5) is reduced only in the combination

- Consistent with the combination being more efficacious against tumors in vivo

- Reduced levels of Inflammatory endpoints; collagen III (grey arrows)

- Consistent with reduced Trametinib-related skin side effects (Flaherty, 2012, NEJM 367:1694).

70


• Chemical profiling in human cell systems generates activity profiles that can be used to:

- Group chemicals into bioactivity classes

- Generate MoA hypotheses

- Identify activities that may correlate with in vivo outcomes

• High throughput in vitro data is most informative when combined with external information

- Known targets

- In vivo bioactivities

Summary

Confidential71

• Applications for predicting in vivo effects must also consider:

- Exposure - level and route

- Distribution

- Metabolism

- Human variability

Challenges and Considerations

Confidential72

• BioSeek

- Mark A. Polokoff

- Dat Nguyen

- Xitong Li

- Antal Berenyi

- Alison O’Mahony

- Jian Yang (Oracle)

• UCSF

- Kevan Shokat

Acknowledgements

• EPA

- Keith Houck

- Nicole Kleinstreuer

- Richard Judson

• Support

- NIH/NIAID (SBIR)

- EPA (EP-D-12-047, EP-W-07-039)

73

Contact:

Ellen L. Berg, PhD

Scientific Director

BioSeek, a division of DiscoveRx

[email protected]

Science

Berg ellen 7th braz medchem 12nov2014