molecular targeting for lung cancer prevention and therapy ruiwen zhang, md, phd, dabt professor,...

Molecular Targeting for Lung Cancer Prevention and Therapy

Ruiwen Zhang, MD, PhD, DABT

Professor, Pharmacology and ToxicologyDirector, Cancer Pharmacology Laboratory

University of Alabama at BirminghamBirmingham, AL 35294

[email protected]

UCLA, April 14, 2007

Our view on…

Drug Discovery and Development

in Cancer Prevention and Therapy Who we are…

&What we are doing…

(3 Examples)

In the short 30 min...

Drug Discovery & Development

The Players Basic Scientists/Academic Researchers

Chemist Biologist Pharmacologist Geneticist Medical Professionals

Developers Big Pharmaceutical Companies Small Development Companies Biotech/Start-up Companies Contract Research/Management Organizations

Entrepreneurs Regulatory Agencies (US FDA, SFDA, etc.) Government Research Consumers (Patients, Community)

Decision Filter(Go/No Go?)

Overview of Drug Discovery

Decision Filter(Yes/No?)

Overview of Drug Development

Drug Development

ChemicalDevelopment

PharmacologyToxicology

ClinicalDevelopment

NDA Submission

Decision Filter

FDA

10,000-50,000

1

10

1,000

ChemicalDevelopment

PharmacologyToxicology

ClinicalDevelopment

NDA Approval

Decision Filter

1.8 yr

2.2 yr

6.6 yr

4.4 yr

~ $ 250M- $500M

~ $ 250M- $500M

Joanna Owens Nature Reviews Drug Discovery 6, 99–101 (February 2007)

New molecular entities (NMEs) and biologic license applications approved by the US FDA by year. The number of NMEs approved in 2006 stayed the same as in 2005, with a slight increase in the number of approved biologics.

FDA Drug Approvals

Importance of Target Validation

Reality Check: The Apparent decline in success rates for new pharmaceuticals in recent years is consistent with a theory that the development of new technologies that posits in effect that the low-lying fruit will tend to be picked first.

Hope or Hype? Post-genome era Second genomics? “***” Omics? Systems Biology? Individualized Medicine (Drug, Pharmaceuticals)

Key Factors: New Technology, New Targets, Early Decision (go/no go?) New approaches to clinical trial, e.g., Phase 0

Predictive Models are urgently needed: Fail Early, Fast and Often

Target Selection

Drug May Target at Various Subjects:

Foreign Pathogens

Host Internal and External Environments

Host Disease-causing Genes/Proteins

Disease

Target Discovery Process

Target Validation Process Methods

Molecular/Genetic/Genomic Biochemical/Proteomic Physiological/functional Pharmacological/Toxicological Population-based

System Cell-free in vitro Cell Organ (in vitro and in vivo) Small animals Non-human primates Humans

Target Validation Process

Data Interpretation Genotype vs.

Phenotype In vitro vs. In vivo Animals vs. Humans Healthy subjects vs.

Patients Other host factors:

sex, age, race, etc. Other Limitations, e.g.,

dose-range Research tools vs.

Drug class/entity

Criteria Causal relation between

target and disease Correlation with disease

status Specificity (Specific/Non-

specific) Affinity Mode of action (onset,

short-term/long-term) Regulation of effects

Animal Disease ModelsWhat and Why

Cancer

Cardiovascular

Toxicology

HIV

Who We Are…&

What We Are Doing…

Birmingham: Steel City

Birmingham: The beautiful

Birmingham: Magic City

American Idol Taylor Hicks

Miss UAB 2005

Cancer Drug Discovery and Development

Target Validation In Vivo Disease Models PK/PD Toxicology Delivery Combination Therapy

Chemosensitization Radiosensitization Antibody/

Immunotherapy Vaccine Gene Therapy

Clinical Trials & Clinical Pharmacology

Molecular Targets: p53 PKA VEGF ICAM-1 MDM2 XIAP BCL-2 β-catenin E2F1

CpG Oligos (IMOs) Small Molecules Natural Products Imaging agents Antibiotics

Examples: Preclinical and Clinical Drug Development

In vitro Pharmacology In vivo Pharmacology In vitro Toxicology In vitro Toxicology Pharmacogenomics Toxicogenomics Drug Delivery Biomarker

Clinical Trials : Phase 0 Trials/Biomarcker Phases I /Clinical

Pharmacology Phase II Trials Phase III Trials Phase IV/Surveillance Prevention Trials

(TLR)-mediated Immune responses Substrate/ligand specific Cell type dependent Ap-1/NFkappaB pathways

TLR9-mediated Immune stumulation by CpG ODNs Structure dependent Cell type dependent Multiple responses

(Wang et al: Current Pharmaceutical Design 2005;

Molecular Cancer Therapeutics 2006)

Example 1: Toll-Like Receptor Agonists

TLR8TLR10

TLR1TLR6 TLR2

Bacterial lipoproteins (BLP)Lipoarabinomannan (LAM)LPS binding protein (LBP)

Lipoteichoic (LTA)Peptideglycans (PGN)

MALP-2, Zymosan?

?

TLR4

MD2 CD14

LPS, LTA, Taxol, HSP60/HSP70?

F protein, Lipid A

TIRAFMyD88

IRAK

TRAF6

MAPK

AP1

IkB

NF-kB

NF-kB

NucleusActivation of Inflammatory cytokines

TLR3

dsRNA

Caspase-1

Pre-IL-18 IL-18

IRF3

IRF3P

TLR9TLR5 TLR7

Flagellin

Small anti-viral

compounds

Bacterial DNA, Synthetic DNA,

Plasmid DNA

Endosome

CpG DNA

Transcription of immune response genes

•TNF-: Adhesion molecules on endothelial cells; IL-6 upregulation; macrophage activation

•IL-6: B-cell differentiation; antibody section; class switch

•IL-12: IFN- productin by NK and Th1 cells; Th1 cell differentiation; Th2 cell suppression

•IFN-: APC activation; Th1 development; MHC-I upregulation

•IFN-/: MHC-I upregulation; antigen processing and presentation

•IL-1: Adhesion molecule upregulation on endothelial cells; upregulation of IL-6

•IL-10: Inhibitor of IL-12 and IFN- production

•MHC-I: Antigen presentation to CD8+ cells

•CD40: Co-stimulatory signal, IL-12 secretion

•CD86: Co-stimulatory signal

•CD69: Co-stimulatory signal

Toll-like Receptors (TLR), their Ligands and Related Signal Transduction Pathways

CpG DNA

Wang H, Rayburn E, and Zhang R. Current Pharmaceutical Design 11 (22): 2889-2907.

MOA: CpG-TLR9 Signaling

CpGCore

Backbone Modification

5’ Immunomodulatory

Moieties (Including

polyG Nucleobase

Deletion)

5’- NNNNNNNNNNNCpGNNNNNNNNNNN - 3’

• In Vivo Stability

• Immunostimulation (A, B, C – class ODN)

• N – Base modifications

•3’ modifications•3’ – 3’ link

3’ Immunomodulatory Moieties

• Multiple CpG• Synthetic motifs (CpG, YpG, CpR, YpR)

Species Selectivity

5’ modifications

Strategies to Improve CpG ODN PropertiesStrategies to Improve CpG ODN Properties

Novel IMOs: Chimeric IMOs

Saline Gemcitabine

Saline

Control IMO

IMO

In Vivo Anti-tumor Activity

of IMO in Human Lung

Cancer H358 Xenograft

Models Following

Treatment of IMO Alone or

in Combination with

Gemcitabine

Saline

IMO

IMO + Gemcitabine

Gemcitabine

β-actin (~ 600 bp)

TLR9 (~ 259 bp)

β-actin (~ 600 bp)

TLR9 (~ 259 bp)

A549 Cells

PC3 Cells

506 bp

298 bp

506 bp

298 bp

HCT116 (p53+/+)

HCT116 (p53-/-)

DLD-1

PC3

DU145

A549

MCF-7

PANC-1

MIA-PaCa2

U2-0S

U87MG

HCT116 (p53+/+)

HCT116 (p53-/-)

HCT116 (p21-/-)

HCT116 (p53-/-, p21-/-)

MCF7

BT474

A549

ACHN

PC3

MDA-MB-231

B lymphocyte

RT-PCR

Western Blot

Control IMO (100 nM)Control IMO (100 nM)Control IMO (100 nM)Control IMO (100 nM)

RT-PCR

TLR9 mRNA and protein expression in various cancer cell lines

Effects of IMO alone on cell survival, apoptosis and proliferation in various cancer cell lines

E: PC3

A: A549

B: U87MG

C: HCT116(p53 +/+)

D: HCT116(p53 -/-)

Survival Apoptosis Proliferation

0

30

60

90

120

0 20 40 60 80 100

Concentration (nM)

Cell

Su

rv

iva

l (%

)

IMO / Lipofectin (+)IMO / Lipofectin (-)Control IMO / Lipofectin (+)Control IMO / Lipofectin (-)

0

30

60

90

120

0 20 40 60 80 100

Concentration (nM)

Cell

Su

rv

iva

l (%

)


0

30

60

90

120

0 20 40 60 80 100

Concentration (nM)

Cell

Su

rv

iva

l (%

)


0

30

60

90

120

0 20 40 60 80 100

Concentration (nM)

Cell

Su

rv

iva

l (%

)

IMO / Lipofectin (+)

IMO / Lipofectin (-)

Control IMO / Lipofectin (+)Control IMO / Lipofectin (-)

0

30

60

90

120

0 20 40 60 80 100

Concentration (nM)

Cell

Su

rv

iva

l (%

)

IMO / Lipofectin (+)

IMO / Lipofectin (-)

Control IMO / Lipofectin (+)Control IMO / Lipofectin (-)

0

50

100

150

200

250

Control Control IMO(100nM)

IMO (100nM)Ap

op

toti

c In

dex

(%

of

Co

ntr

ol)

Lipofectin (-)

Lipofectin (+)

0

50

100

150

200

250


IMO (100nM)Ap

op

toti

c In

dex

(%

of

Co

ntr

ol)

Lipofectin (-)

Lipofectin (+)

0

50

100

150

200

250

Control Control IMO

(100nM)

IMO (100nM)Ap

op

toti

c In

dex

(%

of

Co

ntr

ol)

Lipofectin (-)

Lipofectin (+)

0

50

100

150

200

250


IMO (100nM)Ap

op

toti

c In

dex

(%

of

Co

ntr

ol)

Lipofectin (-)

Lipofectin (+)

0

20

40

60

80

100

120

140


IMO (100nM)Pro

life

rati

on

In

dex

(%

of

Co

ntr

ol)

Lipofectin (-)

Lipofectin (+)

0

20

40

60

80

100

120

140


IMO (100nM)Pro

life

rati

on

In

dex

(%

of

Co

ntr

ol)

Lipofectin (-)

Lipofectin (+)

0

20

40

60

80

100

120

140


IMO (100nM)

Pro

life

rati

on

In

dex

(%

of

Co

ntr

ol)

Lipofectin (-)

Lipofectin (+)

0

20

40

60

80

100

120

140


IMO (100nM)Pro

life

rati

on

In

dex

(%

of

Co

ntr

ol)

Lipofectin (-)

Lipofectin +)

0

20

40

60

80

100

120

140


IMO (100nM)Pro

life

rati

on

In

dex

(%

of

Co

ntr

ol)

Lipofectin (-)

Lipofectin (+)

0

50

100

150

200

250

Control Control IMO

(100nM)

IMO (100nM)Ap

op

toti

c In

dex

(%

of

Co

ntr

ol)

Lipofectin (-)

Lipofectin (+)

Lung cancer xenograft tumors treated with an anti-VEGF Antisense oligonucleotide +/- chemotherapy

Tumor Mass (mg)

0

500

1000

1500

2000

2500

3000

0 3 6 9 12 15 18 21 24 27 30 33 36

Saline

Control ODN (20 mg/kg)

AS-VEGF (10 mg/kg)

AS-VEGF (20 mg/kg)

0

500

1000

1500

2000

2500

3000

0 3 6 9 12 15 18 21 24 27 30 33 36

Saline

Gemcitabine

Control ODN + Gemcitabine

AS-VEGF + Gemcitabine

Day

Saline

Control ODN (20 mg/kg)

AS-VEGF (10 mg/kg)

AS-VEGF (20 mg/kg)

Saline Gemcitabine

Saline

Cntl ODN (20 mg/kg)

AS-VEGF (20 mg/kg)

BA The anti-VEGF ASO and control ODN were given by ip injection 5d/wk

Gemcitabine (160 mg/kg) was administered by ip injection on days 4 and 11.

IMO inhibits NSCLC tumor growth in animal models (1)

The IMO was administered at doses of 0.5 or 1.0 mg/kg by sc injection 3d/wk

Tumor Mass (mg)

Day

0

500

1000

1500

2000

2500

3000

3500

4000

0 3 6 9 12 15 18 21 24 27

SalineControl Oligo IMO (1 mg/kg)

0

500

1000

1500

2000

2500

3000

0 3 6 9 12 15 18 21 24 27 30 33 36

SalineControl Oligo IMO (1 mg/kg)

A. H520 B. H358

0

500

1000

1500

2000

0 7 14 21 28 35

Saline

IMO (0.5mg/kg)

0

200

400

600

800

1000

0 7 14 21 28 35

Saline

IMO (0.5 mg/kg)

C. A549 D. H1299

Wang H et al. Mol Cancer Ther. 2006 5: 1585-92.

The IMO or Control oligo was administered at 1 mg/kg by sc injection 3 d/wk

Gemcitabine (160 mg/kg) was administered by ip injection on days 4 and 11.

Alimta (100 mg/kg) was administered by ip injection on days 11, 18 and 25.

Wang H et al. Mol Cancer Ther. 2006 5: 1585-92.

Saline

Cntl oligo

IMO

Saline Gemcitabine

D. H358

0

500

1000

1500

2000

2500

3000

0 3 6 9 12 15 18 21 24 27 30 33 36

SalineCont rol Oligo IMOGemcitabineCont rol Oligo + GemcitabineIMO + Gemcitabine

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 3 6 9 12 15 18 21 24 27

SalineCont rol Oligo IMOGemcitabineCont rol Oligo + GemcitabineIMO + Gemcitabine

Tumor Mass (mg)

Day

A. H520

B. H358

Day

0

500

1000

1500

2000

0 3 6 9 12 15 18 21 24 27 30

SalineControl Oligo IMOAlimta Control Oligo + AlimtaIMO + Alimta

C. H520

Tumor Mass (mg)

IMO inhibits NSCLC tumor growth in animal models (2)

Example 2:ECPKA As A Cancer Marker:A Population Study

Wang et al: Cancer Epidemiology Biomarker and Prevention, 2007 April 1 Issue

Purpose: The present study was designed to investigate the population distribution of extra-cellular activity of cAMP-dependent protein kinase (ECPKA) and its potential value in cancer detection. Background: PKA may have a role in tumorigenesis and cancer growth. Elevated PKA expression has been reported in patients with cancer, and PKA inhibitors have been tested in clinical trials as novel cancer therapy. Methods: The population distribution of ECPKA activity was determined in serum samples from normal healthy subjects and cancer patients in a Chinese population, consisting of a total of 603 subjects (374 normal healthy volunteers and 229 cancer patients). The serum ECPKA was determined by a validated sensitive radioassay and its diagnostic values (positive and negative predictive values) were analyzed.

MOA of cAMP-Dependent PKA

ATP

cAMP

C-subunitR-subunit

Inactive

Active

C-subunit

ATPADP

Phosphorylation (Arg, Val, Ser, Val)

Histone H1

[C··· R] + cAMP -> C + R ··· cAMPInactive Active

ECPKA Assay: Affinity Ultrafiltration Separation Assay

Reaction Mixture:•ATP•32P-ATP•Kemptide•CAMP•Reaction Buffer

PKA Reaction

Ultrafiltration & Washing

Adding Avidin

Recover 32P-labeled,biotinylated substrate

Radioactivity Counting

Blood sample

Plasma

32P-ATP

Ultrafiltration system

ECPKA in Normal Population and Cancer Patients

N Mean Standard Deviation

Median Range

Overall 603 5.50 10.90 2.12 0 – 108.45

Cancer Patients

229 10.98 15.84 5.42 0 – 108.45

Controls 374 2.15 2.95 1.02 0 – 25.19

0

5

10

15

20

25U

D

0.0

1-

1-

2-

3-

4-

5-

6-

7-

8-

9-

10

-

11

-

12

-

13

-

>=

14

ECPKA Activity (U/mL)

Fre

qu

ency

(%

)

Control (Total)

Cancer Patient (Total)


0

5

10

15

20

25

30

UD

0.01

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

11-

12-

13-

>=14


Freq

uenc

y (%

)

Control (Female)

Cancer Patient (Female)

0

5

10

15

20

25

30

20-

40-

60-

80-

100-

120-

140-

160-

180-

200-

220-

240-

260-

280-

LDH Activity (U/L)

Freq

uenc

y (%

)

Control (Female)

Cancer Patient (Female)


0

5

10

15

20

25

30

UD

0.01

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

11-

12-

13-

>=14


Freq

uenc

y (%

)

Control (Male)

Cancer Patient (Male)

0

5

10

15

20

25

30

35

20-

40-

60-

80-

100-

120-

140-

160-

180-

200-

220-

240-

260-

280-

LDH Activity (U/L)

Freq

uenc

y (%

)

Control (Male)

Cancer Patient (Male)


0

5

10

15

20

25EC

PKA

Activ

ity (U

/mL)


LDH in Normal Population and Cancer Patients

0

30

60

90

120

LDH

Activ

ity (U

/L)

Ginseng

Example 3: Natural Products

Wang/Zhao et al: Med Chem 2007; Cancer Chemother Pharm 2007

Top 10 Dietary Supplements In the US Market

Rank 天然产物 Name

1 紫锥花 Echinacea

2 人参 Ginseng

3 银杏 Ginkgo

4 大蒜 Garlic

5 葡萄糖胺 Glucosamine

6 金丝桃 St. John’s wort

7 薄荷 Peppermint

8 鱼油 Fish oil

9 生姜 Ginger

10 大豆 Soy

From: Barnes et al: Advance Data Report 343, 2004

Identification of GinsenosidesFruits of P. ginseng

Silica gel columnreverse-phase HPLC

Identification and characterization by EI-MS, IR, 1H- NMR, and 13C-NMR

Compounds 5-11Compounds 1-4

EtOH extract

Resin column

Total saponins

CHCl3 fraction 1-BuOH fraction

1. 20(R)-dammarane- 3β,12β, 20, 25–tetrol2. 20(R)-dammarane-3β, 6α,12β, 20, 25 -

pentol 3. 20(S) -protopanaxadiol 4. Daucosterin

5. 20(S)-ginsenoside-Rh2

6. 20(S)-ginsenoside-Rg3



9. 20(S)-ginsenoside-Rd10. 20(S)-ginsenoside-Re11. 20(S)-ginsenoside-Rb1

Extracted with 75% EtOH

Evaporated in vacuum

Eluted with 70% EtOH

Extracted with CHCl3 and 1-BuOH

CHCl3-MeOH

CH3CN-H2O

CHCl3-MeOH-H2O

MeOH-H2O

Scheme for isolation and identification of compounds 1-11

Compound Name Structure

1

2

4

20(R)-dammarane-3β, 12β, 20, 25-tetrol (25-OH-PPD)

20(R)-dammarane-3β, 6α, 12β, 20, 25-pentol (25-OH-PPT)

β-sitosterol- 3-O-β-D-glucopyranoside (daucosterin)

PPD-type saponin

R1 R2

3 20(S) -PPD H H

5 20(S) -Rh2 Glc H

6 20(S) -Rg3 Glc2-Glc H

9 20(S) –Rd Glc2-Glc Glc

11 20(S) -Rb1 Glc2-Glc Glc6-Glc

R1 R2

7 20(S)-Rg2 Glc2-Rha H

8 20(S)-Rg1 Glc Glc

10 20(S)-Re Glc3-Rha Glc

HO

OH

OH

HO

OH

HO

OH

HO

OH

O

C2H5

glc

R1O

R2OOH

20S

3

12

20R

OR2

R2O

HO

OH

20S

3

12

20R

OR2

OR1

6

PPT-type saponin

SAR of Ginsenosides

20(R)-25- 羟基 - 达玛烷 -3β,12β,20,25- 四醇 [20(R)-25-OH-PPD]

Identification and Purification of Two Novel Ginsenosides

20(S)-25- 甲氧基 - 达玛烷 -3β, 12β, 20- 三醇

[20(S)-25-OCH3-PPD]

HT Screening for Anticancer Activity

Cell-based Assay

No.

MCF-7 （ CV% ） H838 （ CV% ） LNCaP （ CV% ） PC3 （ CV% ）

1μM 10μM 100μM 1μM 10μM 100μM 1μM 10μM 100μM 1μM 10μM 100μM

1 25-OH-PPD

2 25-OH-PPT

3 PPD

4 Daucosterol*

5 Rh2

6 Rg3

7 Rg2

8 Rg1

9 Rd

10 Re

11 Rb1

* Highest concentration was 50 μM. Cell viability (CV) data: inhibition <20%, in black; 20-90%, in green; >90%, in red.

SAR (IC50, μM)

SAR (IC50, μM)

Cancer Type Cell Lines 25-OCH3-PPD Rg3

Glioma A172 38.3 303.0

T98G 5.0 397.0

Pancreatic Ca HPAC 5.8 >500

PANC-1 7.8 180.3

Lung Ca A549 5.7 369.1

H1299 4.9 357.2

H358 8.1 470.0

H838 11.7 293.0

Breast Ca MCF-7 13.5 361.2

MDA-MB-468 18.2 153.1

Prostate Ca LNCaP

PC3

12.0

5.6

302.1

266.5

Lung Cancer ModelA549 H1299

Concentration (µM)

Cell Viability (%)

0

20

40

60

80

100

120

0 10 20 30 40 50

0

20

40

60

80

100

120

0 10 20 30 40 50

0

20

40

60

80

100

120

140

0 10 20 30 40 500

20

40

60

80

100

120

140

160

0 10 20 30 40 50

25-OH-PPD

25-OH-PPT

PPD

Rh2

Rg3

H358H838

Cytotoxicity of ginsenosides to human lung cancer cells in culture

Lung Cancer Model

Induction of apoptosis and anti-proliferative effects of ginsenosides

Apoptotic Index (% of Control)

Concentration (μM)

25-OH-PPD

25-OH-PPT

PPD

Rh2

Rg3

0

50

100

150

200

250

300

350

400

0 1 10 25 50

0

50

100

150

200

250

300

350

400

0 1 10 25 50

H358

H838

Proliferation Index (% of Control)

Concentration (μM)

01 02 03 04 05 0

25-OH-PPD

25-OH-PPT

PPD

Rh2

Rg30 20 40

60 80

100 120

140 160 180

0 10 20 30 40 50

0

20

40

60

80

100

120

0 10 20 30 40 50

H358

H838

Lung Cancer Model

Effect of ginsenosides on the cell cycle progression of lung cancer cells

25-OH-PPD25-OH-PPT

% of Cells

H358(PS18)

0

20

40

60

80

100

G1 S G2/M

H838(PS18)

0

20

40

60

80

100

G1 S G2/M

25-OH-PPDH838(PS26)

0

20

40

60

80

100

G1 S G2/M

25-OH-PPT

H358(PS26)

0

20

40

60

80

100

G1 S G2/M

H838(PS41)

0

20

40

60

80

100

G1 S G2/M

PPD

H358(PS41)

0

20

40

60

80

100

G1 S G2/M

PPD

H838(PS38)

0

20

40

60

80

100

G1 S G2/M

Rh2

H358(PS38)

0

20

40

60

80

100

G1 S G2/M

Rh2

H838(PS36)

0

20

40

60

80

100

G1 S G2/M

Rg3

H358(PS36)

0

20

40

60

80

100

G1 S G2/M

Rg3

H358

H838

0 μM

1 μM

10 μM

25 μM

0 μM

1 μM

10 μM

50 μM

0 μM

1 μM

10 μM

50 μM

0 μM

1 μM

10 μM

50 μM

0 μM

1 μM

10 μM

50 μM

% of Cells

Lung Cancer Model

H358

0

200

400

600

800

1000

0 1 10 25 50 100

concentration(μM)

Apo

ptot

ic In

dex

(% o

f co

ntro

l)

H838

0

200

400

600

800

1000

0 1 10 25 50 100

concentration(μM)

Apo

ptot

ic In

dex

(% o

f co

ntro

l)

A549

0

300

600

900

1200

0 1 10 25 50 100

concentration(μM)

Apo

ptot

ic in

dex

(%

of c

ontr

ol)

H520

0

50

100

150

200

0 1 10 25 50 100

concentration(μM)

Apo

ptot

ic In

dex

(% o

f con

trol

)

BEAS-2B

0

200

400

600

800

1000

0 1 10 25 50 100

concentration(μM)

Apo

ptot

ic In

dex

(%

of c

ontr

ol)

H838

0

30

60

90

120

150

0 1 10 25 50 100

concentration(μM)

Prol

ifera

tion

inde

x (%

of c

ontr

ol)

A549

0

30

60

90

120

0 1 10 25 50 100

concentration(μM)P

rolif

erat

ion

ind

ex (

%

of

con

tro

l)

H358

0

30

60

90

120

150

0 1 10 25 50 100

concentration(μM)

Pro

lifer

atio

n in

dex

(%

of

con

tro

l)

H520-PS25

0

30

60

90

120

0 1 10 25 50 100concentration(μM)

Pro

lifer

atio

n In

dex

(%

of

Co

ntr

ol)

BEAS-2B-PS25

0

30

60

90

120

0 1 10 25 50 100Concentration(μM)

Pro

lifer

atio

n In

dex

(%

of

Co

ntr

ol)

% of Cells

Cell Cycle Phase0

20

40

60

80

100

G1 S G2/M

0 μM

1 μM

10 μM

25 μM

H838(PS25)

0

20

40

60

80

100

G1 S G2/M

H358(PS25)

0

20

40

60

80

100

G1 S G2/M

A549(PS25)

0

20

40

60

80

100

G1 S G2/M

BEAS-2B(PS25)

0

20

40

60

80

100

G1 S G2/M

H520(PS25)

0

20

40

60

80

100

G1 S G2/M

PS25 Induces Apoptosis, Inhibits Cell Proliferation and Arrest Cells in the G1 Phase in Lung Cancer Cells.

PS25

PS25

PS25

Gene Expression Profiling

Lung Cancer Model

0

200

400

600

800

1000

1200

1400

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42

Day

Tum

or M

ass

(mg)

Control

PS25 (1 mg/kg)

PS25 (5 mg/kg)

PS25 (10 mg/kg)

0

200

400

600

800

1000

1200

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42

Day

Tum

or M

ass

(mg)

Control

Paclitaxel (10 mg/kg)

Paclitaxel+PS25

0

200

400

600

800

1000

1200

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42

Day

Tum

or M

ass

(mg)

Control

RT

RT+PS25

0

5

10

15

20

25

30

35

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42

Day

Bod

y W

eigh

t (g

)

Control

PS25 (1 mg/kg)

PS25 (5 mg/kg)

PS25 (10 mg/kg)

0

5

10

15

20

25

30

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42

Day

Bod

yWei

ght

(g)

Control

Paclitaxel (10 mg/kg)

Paclitaxel+PS25

0

5

10

15

20

25

30

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42

Day

Bod

y w

eigh

t (g

)

Control

RT

RT+PS25

PS25(5days/week):10mg/kg/day: 35.2%Paclitaxel: 11.6%+PS25: 40.1%RT: 8.8%+PS25: 42.3%

• Neither of these dosing procedures resulted in any appreciable effect on the body weight of the mice

PS25 inhibits the growth of Lung xenograft tumors and sensitizes tumors to treatment with chemotherapy or radiation

In vivo Antitumor Activity

0

300

600

900

1200

1500

0 3 6 9 12 15 18 21 24 27 30

Saline

25-OCH3-PPD (5mg/kg)


0

300

600

900

1200

1500

0 3 6 9 12 15 18 21 24 27

Saline




0

300

600

900

1200

1500

0 3 6 9 12 15 18 21 24 27 30

Saline

Texotere (15mg/kg)

Texotere + 25-OCH3-PPD

0

300

600

900

1200

1500

0 3 6 9 12 15 18 21 24 27 30

Saline

RT (3Gy)

RT + 25-OCH3-PPD

0

300

600

900

1200

1500

0 3 6 9 12 15 18 21 24 27 30

Saline

Gemcitabine (160mg/kg)

Gemcitabine + 25-OCH3-PPD

0

5

10

15

20

25

30

35

0 3 6 9 12 15 18 21 24 27 30

Saline

RT (3Gy)

RT + 25-OCH3-PPD

0

5

10

15

20

25

30

35

0 3 6 9 12 15 18 21 24 27 30

Saline

Gemcitabine (160mg/kg)

Gemcitabine + 25-OCH3-PPD

0

5

10

15

20

25

30

35

0 3 6 9 12 15 18 21 24 27 30

Saline

Texotere (15mg/kg)

Texotere + 25-OCH3-PPD

0

5

10

15

20

25

30

35

0 3 6 9 12 15 18 21 24 27 30

Saline



0

5

10

15

20

25

30

35

0 3 6 9 12 15 18 21 24 27

Saline




Day

Tu

mo

r M

ass

(mg

)

Day

Bo

dy

Wei

gh

t (g

)

Strength Ginsenosides C3 C6 C20 C25

25-OCH3-PPD -OH -H -OH -OCH3

25-OH-PPD -OH -H -OH -OH

Rg3 -O-G2-G -H -OH

Rh2 -O-G -H -OH

PPD -OH -H -OH

Re -OH -O-G3-Rha -O-G

Rd -O-G2-G -H -O-G

25-OH-PPT -OH -OH -OH -OH

Rg2 -OH -O-G2-Rha -OH

Rg1 -OH -O-G -O-G

Rb1 -O-G2-G -H -O-G6-G

SAR of P450 modulation-CYP2C9

Take-Home Message

Accelerating Drug Discovery and Development by Novel Approaches to Failing Early, Fast, and Often

4R’s: Right Target Right Models Right Approaches Right Timing for Decision-Making (go/no go)

After ALL (You love or hate): Pharmacology & Toxicology Regardless of Targets/Diseases/Products

The partnering of industry, academia, health organizations, and government agencies provides optimal utilization of emerging

science, resulting in enhanced regulatory decision making, expedited drug development, and improved patient care

S Buckman et al. Clinical Pharmacology & Therapeutics 141-144 ( February 2007)

GrantsNIH/NCI R01 CA 80698NIH/NCI R01 CA 112029NIH/NCI N01 CM 47015-45

DoD W81XW04-10845 Hybridon/Idera, Inc.

Zhang LaboratoryH. Wang, MD, PhDD. Hill, PhDM. Li, MDG. Prasad, PhD

Z. Zhang, MD, PhDM. HaslingerV. SchachingerA. AdaimJ. Wu, MDD. Chen, PhDY. Li, MScW. Wang, MDY. Li, PhDE. Rayburn

Collaborators•Dr. S. Agrawal Hybidon, Inc./Idera•Dr. J. Chen Univ. South FL•Late Dr. Y. Cho-Chung NIH/NCI•Dr. C. Deng NIH/NIDDK•Dr. J. Buolamwini Univ. Tennessee•Dr. R. B. Diasio Mayo Clinic •Dr. J. Bonner UAB Radiation Oncology•Dr. X. Chen UC Davis•Dr. C. Elmets UAB Dept of Dermatology•Dr. S. Lee Harvard University•Dr. J.J. Rinehart Univ Kentucky •Dr. J.R. Lindsey UAB Dept of Genomics & Pathobiology•Dr. J He Chinese Academy of Medical Sciences •Dr. H. Wang Chinese Academy of Sciences•Dr. Y. Zhao Shenyang Pharmaceutical Univ

molecular targeting for lung cancer prevention and therapy ruiwen zhang, md, phd, dabt professor,...

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