Transgenic Mice07

Applications of Mouse Models To Cancer Research

Jeff Green, M.D.

Chief, Transgenic Oncogenesis and Genomics Section Laboratory of Cancer Biology and Genetics NCI, Bethesda, MD

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Growth Hormone Transgenic Mice

Genetically Engineered Mice: Limited only by our imagination!

Topics: • advantages/disadvantages of mouse models • designing and generating models • validating models as surrogates for human studies • applying models for preclinical

Why Mice? • • • • • • • • • •

They don’t sue! No IRB (but ACUC!) Human trials are expensive Human trials take a long time Genetic background Can identify modifier genes Can control conditions precisely Can validate a target Can generate complex genetic models Can study stage-specific effects of intervention • Can easily perform combination studies

Advantages of GEM Over In

vitro Approaches

• Study gene in context of entire animal • In the context of an intact immune system • Effects on animal development • Study cancer stage progression • Study tissue-tissue interactions • Study genetic interactions • Identify modifier loci • Tools for pre-clinical testing

Disadvantages: • A mouse is only a mouse! • Targeting to correct compartment • Hormone-responsiveness of promoters • Developmental timing • Expression levels of transgene • Pharmacology • Tissue composition • Poor models of metastases

• • • •

Environment

chemical exposures radiation/UV exposure viral infections immune suppression

Aging

Genetic Background • race • genetic modifiers • familial cancer syndromes

Cancer Risk

Life style • • • •

diet/alcohol exercise obesity mentstrual history/parity history

Prior cancer history

Somatic Gene Dysregulation/Muta Oncogene tion

• activation/over-expression • Loss of suppressor gene function • Chromosomal/gene rearrangement

Intelligent Design

Creating mice in our own molecular image

Oncogenic Targets of GEM Mammary CA Models Growth Factors/Receptors

Steroid Hormone Signaling Aromatase

IGF

TGF β

Her2/neu PyMT

Estrogen

Androgen Retinoids Vitamin D

ER AR

IGFR

TGFβR

PIP-2

PI3K

PIP-3

PKC

RXR VDR

PTEN

MEK AKT

JAK

RAS

SMADs STAT

ERK

Prostoglandins

BRCA1 myc

Transcriptional Regulation p53

TAG

CELL CYCLE

Rb

COX-2

Inflammatory Response

Oncogenesis In GEM

Genetic Aberration(s) (~All cells)

- p53 - BRCA1

?

Cancer

ONCOGENES: Her2/neu Myc Ras PyMT SV40 Tag

P53; Rb

?



Mouse

Cancers

Human Cancers

Biology Histopathology

Therapeutic Trials

Genomic Analyses

Therapeutic Trials

Expression Profiling

Bioinformatics

Model Validation

Transgenic Targeting to the Mammary and Prostate Glands • tissue-specificity • cell-compartment specificity • developmental timing • hormone-independent promoter Hormone

Promoter

Oncogene

BAC Recombineering

STRATEGIES FOR HOMOLOGOUS RECOMBINATION

NEO

II

II

TK

III

III

Insertion/Selection NEO II

III

NEO

II

TK

III

II

III

Deletion/Selection NEO

KNOCK-IN STRATEGY

NEO

* II

II

TK

III

III

Replacement NEO

* II

III

CONDITONAL KNOCK-0UT (Cre-lox)

NEO

L

L

II

TK

III

II

III

Replacement/Selection NEO

L

L II

III

L

NEO

L II

III

X Promoter cre recombinase

II

NEO

L III

Examples of Useful Cancer Models Brain Ovary Prostate Breast Lung Colon Pancreas

Ras + Akt Glioma Model (E. Holland)

Ovarian Cancer Model (S. Orsulic)

C3(1)/Tag Transgenic Model

Mammary Lesion Prostate Tumor Progression Progression

N

PIN

CA Human

C3(1)/Tag

Mouse

ATG

I *

SV40

Tag

Tumor Progression in Breast Cance QuickTime™ and a Photo - JPEG decompressor are needed to see this picture.

Human

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Apoptosis

10% 0%

C3(1)/Tag Mouse

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↑ Bax

Shibata, EMBO, 2001

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Normal

DCIS/MIN

Invasive CA

Pancreatic Cancer (D. Tuveson)

Prostate

Courtesy of N. Greenberg

Lung

(T. Jacks)

Colon

Additional GEM Technologies • Viral delivery systems (retrovirus/lentevirus) • RACS system • Embryonic reconstitution • Chimeric mice (VEGF; ets K.O.s)

Embryonic Reconstitution Embryonic U.G. Sinus

Retrovirus + ras/myc

The RCAS-TVA Technology

LTR

gag

pol

SA

SD

SA

RCAS - a viral vector derived from ALV-A TVA - avian receptor for ALV-A

env

LTR X X

TVA

gag, pol env gene X

Y.Li

ene Delivery with RCAS Vector Pr

LTR

gag

tv-a transgeni c mouse

TV-a

pol

env

LTR

 active oncogenes  DN TSGs  inducible genes  Cre recombinase  Tet activator  marker genes

Conditional Expression Models: • Control of tissue specificity and developmental timing of gene expression. • Study oncogene dependence.

Tissue­Specific  Promoter

TK or CD

TISSUE SPECIFIC ABLATION  TISSUE SPECIFIC ABLATION WITH DRUG WITH DRUG

Tissue­Specific  Promoter

Tet­operator   Promoter

Tet­transactivator protein (on/off)

Gene of Interest

TEMPORAL CONTROL OF GENE EXPRESSION TEMPORAL CONTROL OF GENE EXPRESSION  WITH TETRACYCLINE WITH TETRACYCLINE

Oncogene Dependence of Tumors

In vivo Imaging

GFP

LUC

Advanced In Vivo Imaging Techniques

Choosing the right model What is your question?

evelopment of Pathology Nomenclature fo Mouse Models of Mammary Cancer

• need to standardize nomenclature • need to translate between human and mouse pathology • need to assess similarities/differences between human and mouse (Cardiff et al., Oncogene, 2000.)

Comparing Genomic Aberations Between Mouse Models and Human Cancers (Chin L and Depinho R)

How Can the Mouse Help Us Better Understand Breast Cancer?

elp sift through molecular chao

Integrating the Mouse with Human Genomic Studies • identify oncogenic signatures. • improve identification of biologic networks through identification of functionally conserved genes.



Enormous Genetic Diversity

Defined Genetic Background



Global Expression Profiiling of Tumors





Evolutionarily Conserved Genetic Networks

High Throughput Microarray

Sorlie et al., PNAS (2001

ER- stem cell ER-

C3(1)/Tag P53-/BRCA1-/-;p53+/-

Progenitor cell ER-

MMTV-her2/neu MMTV-ras MMTV-myc MMTV-PyMT

ER+

P53-/-

Common Genes/Biomarkers Related to Similar Biologic State

ER+ Mouse

ER+ Human

The Mouse-Human Classifier is the Best Predictor of ER Status

Human classifier

Mouse/Human classifie Mouse classifier

Training

Test

Mouse/Human Classifier ER+ ER-

Using the model for pre-clinical testing

Inhibition of Mammary Tumor Progression By Recombinant Endostatin

Control

Endostatin

Lizt, 2001

Flk-1/DKR X

Angiogenes is

VEGF Receptor Inhibitors

GSK: J. Stafford and Rakesh Kumar

• GW2286 as prototype receptor kinase inhibitor • Specific inhibitor of KDR phosphorylation/Flk-1 (VEGFR-2). H3C

Enzyme IC50 (nM)

N N H

OMe

NH

mVEGFR2 48

src 758

EGFR 7,079

OMe

N N

hVEGFR2 8

N H

OMe

•

Inhibits VEGF-induced endothelial cell proliferation and KDR phosphorylation.

•

Inhibits tumor vascular density, and Matrigel plug and

micropocket assays. • cornea no toxicity

CDK2 1,622

Survival Survival (percentage)

Inhibition of tumor growth with VEGFRII inhibitor Control 10 mg 100 mg

100 75 50 25 0 16

18

20

22

24

26

Age (wk)

Huh, J. et al. 2005, Oncogene

INITIATION

PROGRESSION Dormant

Mammary  Intraepithelial  Neoplasia

Invasive CA

Metastasis

At what stages do preventive agents inhibit cancer?

C3(1)/Tag Mammary Histopatholog P53 Rb

Human C3(1)/Tag Mouse

A

B

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D

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Normal

C

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E

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F

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8-12 weeks 17+ weeks Invasive CA DCIS/MIN

“Chemoprevention” DHEA DFMO 9-cRA Endostatin

The Metastatic Process

dormancy

metastasis

1. Genetic 2. Epigenetic-intracellular -extracellular:ECM

Chambers AF (2002):Nat Rev Cancer 8:563-

MCF-7 cells are dormant in vivo

MDA-MB-231

2 weeks post injection

MCF-7

9 weeks post injection

SCOM

H&E

Experimental Alterations of Risk Factors Generation of GEM Models With Genetic Changes Relevant to Human Cancer

Evaluation of Model Phenotype: • Disease natural history • Histopathology • Hormone responsiveness (breast and prostate) • Cell of origin • Genome integrity • Gene expression • Protein markers

• Energy balance • Nutritional composition • Hormone exposure • Carcinogens • Pregnancy (breast) • Infectious agents • UV exposure (skin) •Radiation •Genetic Background

Selection of Candidate Models

Determining Predictive Value of GEM Models

Assessment of Response in Models

ADMINISTRATION OF PREVENTIVE AGENT(S)

• • • • • • • •

Clinical Trials In Humans

Tumor latency Tumor multiplicity Growth rate Metastases Survival Histologic changes Gene expression Biomarkers

Functional conservation of genes/networks

Green and Hudson, Nature Reviews Cancer, 2005

Lab Members (current/former) Dalit Barkan Christina Bennett Alfonso Calvo Isabel Chu Kartiki Desai Tamaro Hudson Jung-im Huh Mark Hoenerhoff Claudine Kavanaugh Kristin Kee Hark Kim Zi-yao Liu Aleksandra Michalowska Ting Qiu Masa-aki Shibata Christy Tomlinson Min Zhu